An appraisal of the learning curve in robotic general surgery.

Science.gov (United States)

Pernar, Luise I M; Robertson, Faith C; Tavakkoli, Ali; Sheu, Eric G; Brooks, David C; Smink, Douglas S

2017-11-01

Robotic-assisted surgery is used with increasing frequency in general surgery for a variety of applications. In spite of this increase in usage, the learning curve is not yet defined. This study reviews the literature on the learning curve in robotic general surgery to inform adopters of the technology. PubMed and EMBASE searches yielded 3690 abstracts published between July 1986 and March 2016. The abstracts were evaluated based on the following inclusion criteria: written in English, reporting original work, focus on general surgery operations, and with explicit statistical methods. Twenty-six full-length articles were included in final analysis. The articles described the learning curves in colorectal (9 articles, 35%), foregut/bariatric (8, 31%), biliary (5, 19%), and solid organ (4, 15%) surgery. Eighteen of 26 (69%) articles report single-surgeon experiences. Time was used as a measure of the learning curve in all studies (100%); outcomes were examined in 10 (38%). In 12 studies (46%), the authors identified three phases of the learning curve. Numbers of cases needed to achieve plateau performance were wide-ranging but overlapping for different kinds of operations: 19-128 cases for colorectal, 8-95 for foregut/bariatric, 20-48 for biliary, and 10-80 for solid organ surgery. Although robotic surgery is increasingly utilized in general surgery, the literature provides few guidelines on the learning curve for adoption. In this heterogeneous sample of reviewed articles, the number of cases needed to achieve plateau performance varies by case type and the learning curve may have multiple phases as surgeons add more complex cases to their case mix with growing experience. Time is the most common determinant for the learning curve. The literature lacks a uniform assessment of outcomes and complications, which would arguably reflect expertise in a more meaningful way than time to perform the operation alone.

Microvascular Anastomosis: Proposition of a Learning Curve.

Science.gov (United States)

Mokhtari, Pooneh; Tayebi Meybodi, Ali; Benet, Arnau; Lawton, Michael T

2018-04-14

Learning to perform a microvascular anastomosis is one of the most difficult tasks in cerebrovascular surgery. Previous studies offer little regarding the optimal protocols to maximize learning efficiency. This failure stems mainly from lack of knowledge about the learning curve of this task. To delineate this learning curve and provide information about its various features including acquisition, improvement, consistency, stability, and recall. Five neurosurgeons with an average surgical experience history of 5 yr and without any experience in bypass surgery performed microscopic anastomosis on progressively smaller-caliber silastic tubes (Biomet, Palm Beach Gardens, Florida) during 24 consecutive sessions. After a 1-, 2-, and 8-wk retention interval, they performed recall test on 0.7-mm silastic tubes. The anastomoses were rated based on anastomosis patency and presence of any leaks. Improvement rate was faster during initial sessions compared to the final practice sessions. Performance decline was observed in the first session of working on a smaller-caliber tube. However, this rapidly improved during the following sessions of practice. Temporary plateaus were seen in certain segments of the curve. The retention interval between the acquisition and recall phase did not cause a regression to the prepractice performance level. Learning the fine motor task of microvascular anastomosis adapts to the basic rules of learning such as the "power law of practice." Our results also support the improvement of performance during consecutive sessions of practice. The objective evidence provided may help in developing optimized learning protocols for microvascular anastomosis.

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia.

Science.gov (United States)

Yano, Fumiaki; Omura, Nobuo; Tsuboi, Kazuto; Hoshino, Masato; Yamamoto, Seryung; Akimoto, Shunsuke; Masuda, Takahiro; Kashiwagi, Hideyuki; Yanaga, Katsuhiko

2017-01-01

Although laparoscopic Heller myotomy and Dor fundoplication (LHD) is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD. Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC) curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve. We defined the completion of the learning curve when the following 3 conditions were satisfied. 1) The operation time was less than 165 minutes. 2) There was no blood loss. 3) There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001). Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646). Learning curve seems to complete after performing 16 cases.

Learning curve for laparoscopic Heller myotomy and Dor fundoplication for achalasia.

Directory of Open Access Journals (Sweden)

Fumiaki Yano

Full Text Available Although laparoscopic Heller myotomy and Dor fundoplication (LHD is widely performed to address achalasia, little is known about the learning curve for this technique. We assessed the learning curve for performing LHD.Of the 514 cases with LHD performed between August 1994 and March 2016, the surgical outcomes of 463 cases were evaluated after excluding 50 cases with reduced port surgery and one case with the simultaneous performance of laparoscopic distal partial gastrectomy. A receiver operating characteristic (ROC curve analysis was used to identify the cut-off value for the number of surgical experiences necessary to become proficient with LHD, which was defined as the completion of the learning curve.We defined the completion of the learning curve when the following 3 conditions were satisfied. 1 The operation time was less than 165 minutes. 2 There was no blood loss. 3 There was no intraoperative complication. In order to establish the appropriate number of surgical experiences required to complete the learning curve, the cut-off value was evaluated by using a ROC curve (AUC 0.717, p < 0.001. Finally, we identified the cut-off value as 16 surgical cases (sensitivity 0.706, specificity 0.646.Learning curve seems to complete after performing 16 cases.

The learning curve for hip arthroscopy: a systematic review.

Science.gov (United States)

Hoppe, Daniel J; de Sa, Darren; Simunovic, Nicole; Bhandari, Mohit; Safran, Marc R; Larson, Christopher M; Ayeni, Olufemi R

2014-03-01

The learning curve for hip arthroscopy is consistently characterized as "steep." The purpose of this systematic review was to (1) identify the various learning curves reported in the literature, (2) examine the evidence supporting these curves, and (3) determine whether this evidence supports an accepted number of cases needed to achieve proficiency. The electronic databases Embase and Medline were screened for any clinical studies reporting learning curves in hip arthroscopy. Two reviewers conducted a full-text review of eligible studies and a hand search of conference proceedings and reference sections of the included articles. Inclusion/exclusion criteria were applied, and a quality assessment was completed for each included article. Descriptive statistics were compiled. We identified 6 studies with a total of 1,063 patients. Studies grouped surgical cases into "early" versus "late" in a surgeon's experience, with 30 cases being the most common cutoff used. Most of these studies used descriptive statistics and operative time and complication rates as measures of competence. Five of 6 studies showed improvement in these measures between early and late experience, but only one study proposed a bona fide curve. This review shows that when 30 cases was used as the cutoff point to differentiate between early and late cases in a surgeon's experience, there were significant reductions in operative time and complication rates. However, there was insufficient evidence to quantify the learning curve and validate 30, or any number of cases, as the point at which the learning curve plateaus. As a result, this number should be interpreted with caution. Level IV, systematic review of Level IV studies. Copyright © 2014 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Defining the learning curve of laparoendoscopic single-site Heller myotomy.

Science.gov (United States)

Ross, Sharona B; Luberice, Kenneth; Kurian, Tony J; Paul, Harold; Rosemurgy, Alexander S

2013-08-01

Initial outcomes suggest laparoendoscopic single-site (LESS) Heller myotomy with anterior fundoplication provides safe, efficacious, and cosmetically superior outcomes relative to conventional laparoscopy. This study was undertaken to define the learning curve of LESS Heller myotomy with anterior fundoplication. One hundred patients underwent LESS Heller myotomy with anterior fundoplication. Symptom frequency and severity were scored using a Likert scale (0 = never/not bothersome to 10 = always/very bothersome). Symptom resolution, additional trocars, and complications were compared among patient quartiles. Median data are presented. Preoperative frequency/severity scores were: dysphagia = 10/8 and regurgitation = 8/7. Additional trocars were placed in 12 patients (10%), of whom all were in the first two quartiles. Esophagotomy/gastrotomy occurred in three patients. Postoperative complications occurred in 9 per cent. No conversions to "open" operations occurred. Length of stay was 1 day. Postoperative frequency/severity scores were: dysphagia = 2/0 and regurgitation = 0/0; scores were less than before myotomy (P Heller myotomy with anterior fundoplication well palliates symptoms of achalasia with no apparent scar. Placement of additional trocars only occurred early in the experience. For surgeons proficient with the conventional laparoscopic approach, the learning curve of LESS Heller myotomy with anterior fundoplication is short and safe, because proficiency is quickly attained.

A learning curve for solar thermal power

Science.gov (United States)

Platzer, Werner J.; Dinter, Frank

2016-05-01

Photovoltaics started its success story by predicting the cost degression depending on cumulated installed capacity. This so-called learning curve was published and used for predictions for PV modules first, then predictions of system cost decrease also were developed. This approach is less sensitive to political decisions and changing market situations than predictions on the time axis. Cost degression due to innovation, use of scaling effects, improved project management, standardised procedures including the search for better sites and optimization of project size are learning effects which can only be utilised when projects are developed. Therefore a presentation of CAPEX versus cumulated installed capacity is proposed in order to show the possible future advancement of the technology to politics and market. However from a wide range of publications on cost for CSP it is difficult to derive a learning curve. A logical cost structure for direct and indirect capital expenditure is needed as the basis for further analysis. Using derived reference cost for typical power plant configurations predictions of future cost have been derived. Only on the basis of that cost structure and the learning curve levelised cost of electricity for solar thermal power plants should be calculated for individual projects with different capacity factors in various locations.

The learning curve of robot-assisted laparoscopic aortofemoral bypass grafting for aortoiliac occlusive disease.

Science.gov (United States)

Novotný, Tomáš; Dvorák, Martin; Staffa, Robert

2011-02-01

Since the end of the 20th century, robot-assisted surgery has been finding its role among other minimally invasive methods. Vascular surgery seems to be another specialty in which the benefits of this technology can be expected. Our objective was to assess the learning curve of robot-assisted laparoscopic aortofemoral bypass grafting for aortoiliac occlusive disease in a group of 40 patients. Between May 2006 and January 2010, 40 patients (32 men, 8 women), who were a median age of 58 years (range, 48-75 years), underwent 40 robot-assisted laparoscopic aortofemoral reconstructions. Learning curve estimations were used for anastomosis, clamping, and operative time assessment. For conversion rate evaluation, the cumulative summation (CUSUM) technique was used. Statistical analysis comparing the first and second half of our group, and unilateral-to-bilateral reconstructions were performed. We created 21 aortofemoral and 19 aortobifemoral bypasses. The median proximal anastomosis time was 23 minutes (range, 18-50 minutes), median clamping time was 60 minutes (range, 40-95 minutes), and median operative time was 295 minutes (range, 180-475 minutes). The 30-day mortality rate was 0%, and no graft or wound infection or cardiopulmonary or hepatorenal complications were observed. During the median 18-month follow-up (range, 2-48 months), three early graft occlusions occurred (7%). After reoperations, the secondary patency of reconstructions was 100%. Data showed a typical short learning curve for robotic proximal anastomosis creation with anastomosis and clamping time reduction. The operative time learning curve was flat, confirming the procedure's complexity. There were two conversions to open surgery. CUSUM analysis confirmed that an acceptable conversion rate set at 5% was achieved. Comparing the first and second half of our group, all recorded times showed statistically significant improvements. Differences between unilateral and bilateral reconstructions were not

A Literature-Based Analysis of the Learning Curves of Laparoscopic Radical Prostatectomy

Directory of Open Access Journals (Sweden)

Daniel W. Good

2014-05-01

Full Text Available There is a trend for the increased adoption of minimally invasive techniques of radical prostatectomy (RP – laparoscopic (LRP and robotic assisted (RARP – from the traditional open radical retropubic prostatectomy (ORP, popularised by Partin et al. Recently there has been a dramatic expansion in the rates of RARP being performed, and there have been many early reports postulating that the learning curve for RARP is shorter than for LRP. The aim of this study was to review the literature and analyse the length of the LRP learning curves for the various outcome measures: perioperative, oncologic, and functional outcomes. A broad search of the literature was performed in November 2013 using the PubMed database. Only studies of real patients and those from 2004 until 2013 were included; those on simulators were excluded. In total, 239 studies were identified after which 13 were included. The learning curve is a heterogeneous entity, depending entirely on the criteria used to define it. There is evidence of multiple learning curves; however the length of these is dependent on the definitions used by the authors. Few studies use the more rigorous definition of plateauing of the curve. Perioperative learning curve takes approximately 150-200 cases to plateau, oncologic curve approximately 200 cases, and the functional learning curve up to 700 cases to plateau (700 for potency, 200 cases for continence. In this review, we have analysed the literature with respect to the learning curve for LRP. It is clear that the learning curve is long. This necessitates centralising LRP to high volume centres such that surgeons, trainees, and patients are able to utilise the benefits of LRP.

The learning curve: implications of a quantitative analysis.

Science.gov (United States)

Gallistel, Charles R; Fairhurst, Stephen; Balsam, Peter

2004-09-07

The negatively accelerated, gradually increasing learning curve is an artifact of group averaging in several commonly used basic learning paradigms (pigeon autoshaping, delay- and trace-eye-blink conditioning in the rabbit and rat, autoshaped hopper entry in the rat, plus maze performance in the rat, and water maze performance in the mouse). The learning curves for individual subjects show an abrupt, often step-like increase from the untrained level of responding to the level seen in the well trained subject. The rise is at least as abrupt as that commonly seen in psychometric functions in stimulus detection experiments. It may indicate that the appearance of conditioned behavior is mediated by an evidence-based decision process, as in stimulus detection experiments. If the appearance of conditioned behavior is taken instead to reflect the increase in an underlying associative strength, then a negligible portion of the function relating associative strength to amount of experience is behaviorally visible. Consequently, rate of learning cannot be estimated from the group-average curve; the best measure is latency to the onset of responding, determined for each subject individually.

The Short- and Long-Run Marginal Cost Curve: A Pedagogical Note.

Science.gov (United States)

Sexton, Robert L.; And Others

1993-01-01

Contends that the standard description of the relationship between the long-run marginal cost curve and the short-run marginal cost curve is often misleading and imprecise. Asserts that a sampling of college-level textbooks confirms this confusion. Provides a definition and instructional strategy that can be used to promote student understanding…

The Predictive Value of Ultrasound Learning Curves Across Simulated and Clinical Settings

DEFF Research Database (Denmark)

Madsen, Mette E; Nørgaard, Lone N; Tabor, Ann

2017-01-01

OBJECTIVES: The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. METHODS: Twenty midwives completed a simulation-based tra......OBJECTIVES: The aim of the study was to explore whether learning curves on a virtual-reality (VR) sonographic simulator can be used to predict subsequent learning curves on a physical mannequin and learning curves during clinical training. METHODS: Twenty midwives completed a simulation......-based training program in transvaginal sonography. The training was conducted on a VR simulator as well as on a physical mannequin. A subgroup of 6 participants underwent subsequent clinical training. During each of the 3 steps, the participants' performance was assessed using instruments with established...... settings. RESULTS: A good correlation was found between time needed to achieve predefined performance levels on the VR simulator and the physical mannequin (Pearson correlation coefficient .78; P VR simulator correlated well to the clinical performance scores (Pearson...

Learning curve for intracranial angioplasty and stenting in single center.

Science.gov (United States)

Cai, Qiankun; Li, Yongkun; Xu, Gelin; Sun, Wen; Xiong, Yunyun; Sun, Wenshan; Bao, Yuanfei; Huang, Xianjun; Zhang, Yao; Zhou, Lulu; Zhu, Wusheng; Liu, Xinfeng

2014-01-01

To identify the specific caseload to overcome learning curve effect based on data from consecutive patients treated with Intracranial Angioplasty and Stenting (IAS) in our center. The Stenting and Aggressive Medical Management for Preventing Recurrent Stroke and Intracranial Stenosis trial was prematurely terminated owing to the high rate of periprocedural complications in the endovascular arm. To date, there are no data available for determining the essential caseload sufficient to overcome the learning effect and perform IAS with an acceptable level of complications. Between March 2004 and May 2012, 188 consecutive patients with 194 lesions who underwent IAS were analyzed retrospectively. The outcome variables used to assess the learning curve were periprocedural complications (included transient ischemic attack, ischemic stroke, vessel rupture, cerebral hyperperfusion syndrome, and vessel perforation). Multivariable logistic regression analysis was employed to illustrate the existence of learning curve effect on IAS. A risk-adjusted cumulative sum chart was performed to identify the specific caseload to overcome learning curve effect. The overall rate of 30-days periprocedural complications was 12.4% (24/194). After adjusting for case-mix, multivariate logistic regression analysis showed that operator experience was an independent predictor for periprocedural complications. The learning curve of IAS to overcome complications in a risk-adjusted manner was 21 cases. Operator's level of experience significantly affected the outcome of IAS. Moreover, we observed that the amount of experience sufficient for performing IAS in our center was 21 cases. Copyright © 2013 Wiley Periodicals, Inc.

Learning curve for radical retropubic prostatectomy

Directory of Open Access Journals (Sweden)

Fernando J. A. Saito

2011-02-01

Full Text Available PURPOSE: The learning curve is a period in which the surgical procedure is performed with difficulty and slowness, leading to a higher risk of complications and reduced effectiveness due the surgeon's inexperience. We sought to analyze the residents' learning curve for open radical prostatectomy (RP in a training program. MATERIALS AND METHODS: We conducted a prospective study from June 2006 to January 2008 in the academic environment of the University of São Paulo. Five residents operated on 184 patients during a four-month rotation in the urologic oncology division, mentored by the same physician assistants. We performed sequential analyses according to the number of surgeries, as follows: = 10, 11 to 19, 20 to 28, and = 29. RESULTS: The residents performed an average of 37 RP each. The average psa was 9.3 ng/mL and clinical stage T1c in 71% of the patients. The pathological stage was pT2 (73%, pT3 (23%, pT4 (4%, and 46% of the patients had a Gleason score 7 or higher. In all surgeries, the average operative time and estimated blood loss was 140 minutes and 488 mL. Overall, 7.2% of patients required blood transfusion, and 23% had positive surgical margins. CONCLUSION: During the initial RP learning curve, we found a significant reduction in the operative time; blood transfusion during the procedures and positive surgical margin rate were stable in our series.

Endoscopic sleeve gastroplasty: the learning curve.

Science.gov (United States)

Hill, Christine; El Zein, Mohamad; Agnihotri, Abhishek; Dunlap, Margo; Chang, Angela; Agrawal, Alison; Barola, Sindhu; Ngamruengphong, Saowanee; Chen, Yen-I; Kalloo, Anthony N; Khashab, Mouen A; Kumbhari, Vivek

2017-09-01

 Endoscopic sleeve gastroplasty (ESG) is gaining traction as a minimally invasive bariatric treatment. Concern that the learning curve may be slow, even among those proficient in endoscopic suturing, is a barrier to widespread implementation of the procedure. Therefore, we aimed to define the learning curve for ESG in a single endoscopist experienced in endoscopic suturing who participated in a 1-day ESG training program.  Consecutive patients who underwent ESG between February 2016 and November 2016 were included. The performing endoscopist, who is proficient in endoscopic suturing for non-ESG procedures, participated in a 1-day ESG training session before offering ESG to patients. The outcome measurements were length of procedure (LOP) and number of plications per procedure. Nonlinear regression was used to determine the learning plateau and calculate the learning rate.  Twenty-one consecutive patients (8 males), with mean age 47.7 ± 11.2 years and mean body mass index 41.8 ± 8.5 kg/m 2 underwent ESG. LOP decreased significantly across consecutive procedures, with a learning plateau at 101.5 minutes and a learning rate of 7 cases ( P  = 0.04). The number of plications per procedure also decreased significantly across consecutive procedures, with a plateau at 8 sutures and a learning rate of 9 cases ( P  < 0.001). Further, the average time per plication decreased significantly with consecutive procedures, reaching a plateau at 9 procedures ( P  < 0.001).  Endoscopists experienced in endoscopic suturing are expected to achieve a reduction in LOP and number of plications per procedure in successive cases, with progress plateauing at 7 and 9 cases, respectively.

Learning curves for mutual information maximization

International Nuclear Information System (INIS)

Urbanczik, R.

2003-01-01

An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed [S. Becker and G. Hinton, Nature (London) 355, 161 (1992)]. For a generic data model, I show that in the large sample limit the structure in the data is recognized by mutual information maximization. For a more restricted model, where the networks are similar to perceptrons, I calculate the learning curves for zero-temperature Gibbs learning. These show that convergence can be rather slow, and a way of regularizing the procedure is considered

Robotic Mitral Valve Repair: The Learning Curve.

Science.gov (United States)

Goodman, Avi; Koprivanac, Marijan; Kelava, Marta; Mick, Stephanie L; Gillinov, A Marc; Rajeswaran, Jeevanantham; Brzezinski, Anna; Blackstone, Eugene H; Mihaljevic, Tomislav

Adoption of robotic mitral valve surgery has been slow, likely in part because of its perceived technical complexity and a poorly understood learning curve. We sought to correlate changes in technical performance and outcome with surgeon experience in the "learning curve" part of our series. From 2006 to 2011, two surgeons undertook robotically assisted mitral valve repair in 458 patients (intent-to-treat); 404 procedures were completed entirely robotically (as-treated). Learning curves were constructed by modeling surgical sequence number semiparametrically with flexible penalized spline smoothing best-fit curves. Operative efficiency, reflecting technical performance, improved for (1) operating room time for case 1 to cases 200 (early experience) and 400 (later experience), from 414 to 364 to 321 minutes (12% and 22% decrease, respectively), (2) cardiopulmonary bypass time, from 148 to 102 to 91 minutes (31% and 39% decrease), and (3) myocardial ischemic time, from 119 to 75 to 68 minutes (37% and 43% decrease). Composite postoperative complications, reflecting safety, decreased from 17% to 6% to 2% (63% and 85% decrease). Intensive care unit stay decreased from 32 to 28 to 24 hours (13% and 25% decrease). Postoperative stay fell from 5.2 to 4.5 to 3.8 days (13% and 27% decrease). There were no in-hospital deaths. Predischarge mitral regurgitation of less than 2+, reflecting effectiveness, was achieved in 395 (97.8%), without correlation to experience; return-to-work times did not change substantially with experience. Technical efficiency of robotic mitral valve repair improves with experience and permits its safe and effective conduct.

From Curve Fitting to Machine Learning

CERN Document Server

Zielesny, Achim

2011-01-01

The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital computers that allowed the execution of highly non-linear and increasingly complex data analysis procedures - methods that were completely unfeasible before. Non-linear curve fitting, clustering and machine learning belong to these modern techniques which are a further step towards computational intelligence. The goal of this book is to provide an interactive and illustrative guide to these topics. It concentrates on the road from two dimensional curve fitting to multidimensional clus

Statistical assessment of the learning curves of health technologies.

Science.gov (United States)

Ramsay, C R; Grant, A M; Wallace, S A; Garthwaite, P H; Monk, A F; Russell, I T

2001-01-01

(1) To describe systematically studies that directly assessed the learning curve effect of health technologies. (2) Systematically to identify 'novel' statistical techniques applied to learning curve data in other fields, such as psychology and manufacturing. (3) To test these statistical techniques in data sets from studies of varying designs to assess health technologies in which learning curve effects are known to exist. METHODS - STUDY SELECTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): For a study to be included, it had to include a formal analysis of the learning curve of a health technology using a graphical, tabular or statistical technique. METHODS - STUDY SELECTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): For a study to be included, it had to include a formal assessment of a learning curve using a statistical technique that had not been identified in the previous search. METHODS - DATA SOURCES: Six clinical and 16 non-clinical biomedical databases were searched. A limited amount of handsearching and scanning of reference lists was also undertaken. METHODS - DATA EXTRACTION (HEALTH TECHNOLOGY ASSESSMENT LITERATURE REVIEW): A number of study characteristics were abstracted from the papers such as study design, study size, number of operators and the statistical method used. METHODS - DATA EXTRACTION (NON-HEALTH TECHNOLOGY ASSESSMENT LITERATURE SEARCH): The new statistical techniques identified were categorised into four subgroups of increasing complexity: exploratory data analysis; simple series data analysis; complex data structure analysis, generic techniques. METHODS - TESTING OF STATISTICAL METHODS: Some of the statistical methods identified in the systematic searches for single (simple) operator series data and for multiple (complex) operator series data were illustrated and explored using three data sets. The first was a case series of 190 consecutive laparoscopic fundoplication procedures performed by a single surgeon; the second

Hysteroscopic sterilization using a virtual reality simulator: assessment of learning curve.

Science.gov (United States)

Janse, Juliënne A; Goedegebuure, Ruben S A; Veersema, Sebastiaan; Broekmans, Frank J M; Schreuder, Henk W R

2013-01-01

To assess the learning curve using a virtual reality simulator for hysteroscopic sterilization with the Essure method. Prospective multicenter study (Canadian Task Force classification II-2). University and teaching hospital in the Netherlands. Thirty novices (medical students) and five experts (gynecologists who had performed >150 Essure sterilization procedures). All participants performed nine repetitions of bilateral Essure placement on the simulator. Novices returned after 2 weeks and performed a second series of five repetitions to assess retention of skills. Structured observations on performance using the Global Rating Scale and parameters derived from the simulator provided measurements for analysis. The learning curve is represented by improvement per procedure. Two-way repeated-measures analysis of variance was used to analyze learning curves. Effect size (ES) was calculated to express the practical significance of the results (ES ≥ 0.50 indicates a large learning effect). For all parameters, significant improvements were found in novice performance within nine repetitions. Large learning effects were established for six of eight parameters (p learning curve established in this study endorses future implementation of the simulator in curricula on hysteroscopic skill acquisition for clinicians who are interested in learning this sterilization technique. Copyright © 2013 AAGL. Published by Elsevier Inc. All rights reserved.

Learning curves for solid oxide fuel cells

International Nuclear Information System (INIS)

Rivera-Tinoco, Rodrigo; Schoots, Koen; Zwaan, Bob van der

2012-01-01

Highlights: ► We present learning curves for fuel cells based on empirical data. ► We disentangle different cost reduction mechanisms for SOFCs. ► We distinguish between learning-by-doing, R and D, economies-of-scale and automation. - Abstract: In this article we present learning curves for solid oxide fuel cells (SOFCs). With data from fuel cell manufacturers we derive a detailed breakdown of their production costs. We develop a bottom-up model that allows for determining overall SOFC manufacturing costs with their respective cost components, among which material, energy, labor and capital charges. The results obtained from our model prove to deviate by at most 13% from total cost figures quoted in the literature. For the R and D stage of development and diffusion, we find local learning rates between 13% and 17% and we demonstrate that the corresponding cost reductions result essentially from learning-by-searching effects. When considering periods in time that focus on the pilot and early commercial production stages, we find regional learning rates of 27% and 1%, respectively, which we assume derive mainly from genuine learning phenomena. These figures turnout significantly higher, approximately 44% and 12% respectively, if also effects of economies-of-scale and automation are included. When combining all production stages we obtain lr = 35%, which represents a mix of cost reduction phenomena. This high learning rate value and the potential to scale up production suggest that continued efforts in the development of SOFC manufacturing processes, as well as deployment and use of SOFCs, may lead to substantial further cost reductions.

Prospects for PV: a learning curve analysis

International Nuclear Information System (INIS)

Zwaan, Bob van der; Rabi, A.

2003-01-01

This article gives an overview of the current state-of-the-art of photovoltaic electricity technology, and addresses its potential for cost reductions over the first few decades of the 21st century. Current PV production cost ranges are presented, both in terms of capacity installation and electricity generation, of single crystalline silicon, multi-crystalline silicon, amorphous silicon and other thin film technologies. Possible decreases of these costs are assessed, as expected according to the learning-curve methodology. We also estimate how much PV could gain if external costs (due to environmental and health damage) of energy were internalised, for example by an energy tax. Our conclusions are that, (1) mainly due its high costs, PV electricity is unlikely to play a major role in global energy supply and carbon emissions abatement before 2020, (2) extrapolating learning curves observed in the past, one can expect its costs to decrease significantly over the coming years, so that a considerable PV electricity share world-wide could materialise after 2020, (3) niche-market applications, e.g. using stand-alone systems in remote areas, are crucial for continuing 'the ride along the learning curve', (4) damage costs of conventional (fossil) power sources are considerable, and their internalisation would improve the competitiveness of PV, although probably not enough to close the current cost gap. (author)

Total hip arthroplasty by the direct anterior approach using a neck-preserving stem: Safety, efficacy and learning curve

Directory of Open Access Journals (Sweden)

Aditya Khemka

2018-01-01

Full Text Available Background: The concept of femoral neck preservation in total hip replacement (THR was introduced in 1993. It is postulated that retaining cortical bone of the femoral neck offers triplanar stability, uniform stress distribution, and accommodates physiological anteversion. However, data on safety, efficacy and learning curve are lacking. Materials and Methods: We prospectively assessed all patients who were operated for a THR with a short neck preserving stem (MiniHip between 2012 and 2014. The safety and learning curve were assessed by recording operative time; stem size; and adverse events including periprosthetic fracture; paresthesia; and limb length discrepancy (LLD. The cohort was divided into equal groups to assess the learning curve effect, and the cumulative sums (CUSUM test was performed to monitor intraoperative neck fractures. For assessment of efficacy, Oxford Hip Score (OHS and Short Form-36 (SF-36 scores were compared preoperatively and postoperatively. Results: 138 patients with median age 62 years (range 35–82 years were included with a median followup of 42 months (range 30–56 months. The minimum followup was 2.5 years. The OHS, SF-36 (physical and mental component scores improved by a mean score of 26, 28, and 27 points, respectively. All patients had LLD of <10 mm (1.9 mm ± 1.3. Adverse events included intraoperative neck fracture (n = 6, subsidence (n = 1, periprosthetic fracture (n = 1, paresthesia (n = 12, and trochanteric bursitis (n = 2. After early modification of the technique to use a smaller finishing broach, the CUSUM test demonstrated acceptable intraoperative neck fracture risk. The second surgery group had a reduced risk of intraoperative neck fracture (5/69 vs. 1/69 P = 0.2, reduced operative time (66 vs. 61 min, P = 0.06, and increased stem size (5 vs. 6, P = 0.09 although these differences were not statistically significant. Conclusions: The MiniHip stem is safe alternative to standard THR with good

Learning Curves of Virtual Mastoidectomy in Distributed and Massed Practice

DEFF Research Database (Denmark)

Andersen, Steven Arild Wuyts; Konge, Lars; Cayé-Thomasen, Per

2015-01-01

IMPORTANCE: Repeated and deliberate practice is crucial in surgical skills training, and virtual reality (VR) simulation can provide self-directed training of basic surgical skills to meet the individual needs of the trainee. Assessment of the learning curves of surgical procedures is pivotal...... in understanding skills acquisition and best-practice implementation and organization of training. OBJECTIVE: To explore the learning curves of VR simulation training of mastoidectomy and the effects of different practice sequences with the aim of proposing the optimal organization of training. DESIGN, SETTING...... plateaued on a score of 16.0 (15.3-16.7) at approximately the ninth repetition, but the individual learning curves were highly variable. CONCLUSIONS AND RELEVANCE: Novices can acquire basic mastoidectomy competencies with self-directed VR simulation training. Training should be organized with distributed...

Application of Learning Curves for Didactic Model Evaluation: Case Studies

Directory of Open Access Journals (Sweden)

Felix Mödritscher

2013-01-01

Full Text Available The success of (online courses depends, among other factors, on the underlying didactical models which have always been evaluated with qualitative and quantitative research methods. Several new evaluation techniques have been developed and established in the last years. One of them is ‘learning curves’, which aim at measuring error rates of users when they interact with adaptive educational systems, thereby enabling the underlying models to be evaluated and improved. In this paper, we report how we have applied this new method to two case studies to show that learning curves are useful to evaluate didactical models and their implementation in educational platforms. Results show that the error rates follow a power law distribution with each additional attempt if the didactical model of an instructional unit is valid. Furthermore, the initial error rate, the slope of the curve and the goodness of fit of the curve are valid indicators for the difficulty level of a course and the quality of its didactical model. As a conclusion, the idea of applying learning curves for evaluating didactical model on the basis of usage data is considered to be valuable for supporting teachers and learning content providers in improving their online courses.

Teaching Learning Curves in an Undergraduate Economics or Operations Management Course

Science.gov (United States)

Naidu, Jaideep T.; Sanford, John F.

2012-01-01

Learning Curves has its roots in economics and behavioral psychology. Learning Curves theory has several business applications and is widely used in the industry. As faculty of Operations Management courses, we cover this topic in some depth in the classroom. In this paper, we present some of our teaching methods and material that have helped us…

Training in robotics: The learning curve and contemporary concepts in training.

Science.gov (United States)

Bach, Christian; Miernik, Arkadiusz; Schönthaler, Martin

2014-03-01

To define the learning curve of robot-assisted laparoscopic surgery for prostatectomy (RALP) and upper tract procedures, and show the differences between the classical approach to training and the new concept of parallel learning. This mini-review is based on the results of a Medline search using the keywords 'da Vinci', 'robot-assisted laparoscopic surgery', 'training', 'teaching' and 'learning curve'. For RALP and robot-assisted upper tract surgery, a learning curve of 8-150 procedures is quoted, with most articles proposing that 30-40 cases are needed to carry out the procedure safely. There is no consensus about which endpoints should be measured. In the traditional proctored training model, the surgeon learns the procedure linearly, following the sequential order of the surgical steps. A more recent approach is to specify the relative difficulty of each step and to train the surgeon simultaneously in several steps of equal difficulty. The entire procedure is only performed after all the steps are mastered in a timely manner. Recently, a 'warm-up' before robotic surgery has been shown to be beneficial for successful surgery in the operating room. There is no clear definition of the duration of the effective learning curve for RALP and robotic upper tract surgery. The concept of stepwise, parallel learning has the potential to accelerate the learning process and to make sure that initial cases are not too long. It can also be assumed that a preoperative 'warm up' could help significantly to improve the progress of the trainee.

Learning curves for ultrasound guided lung biopsy in the hands of respiratory physicians

DEFF Research Database (Denmark)

Laursen, Christian; Naur, Therese Maria Henriette; Bodtger, Uffe

2016-01-01

are depicted in figure 1. Six of the physicians had learning curves with a relatively downward or stable projection as a sign of developing competence. Three physicians, however, had learning curves with an upward projection indicating unacceptable competence in performing the procedure......Background: The aim of this study was to determine learning curves for ultrasound guided transthoracic needle biopsies (US-TTNB) performed by respiratory physicians after implementation at three different centers.Methods: During January 2012 to August 2014 patients were included if they had...... a registered US-TTNB procedure at any of the three centers. The US-TTNB was defined as being successful if the result was diagnostic and otherwise as being unsuccessful. Histology or cytology results and clinical follow-up were used as a reference tests. The learning curves for physicians having performed...

Colorectal Stenting in Malignant Large Bowel Obstruction: The Learning Curve

Directory of Open Access Journals (Sweden)

D. Williams

2011-01-01

Full Text Available Aim. Self-expanding metal stents (SEMSs are increasingly used for the palliation of metastatic colorectal cancer and as a bridge to surgery for obstructing tumours. This case series analyses the learning curve and changes in practice of colorectal stenting over a three year period. Methods. A study of 40 patients who underwent placement of SEMS for the management of colorectal cancer. Patients spanned the learning curve of a single surgeon endoscopist. Results. Technical success rates increased from 82% initially, using an average of 1.7 stents per procedure, to a 94% success rate where all patients were stented using a single stent. There has been a change in practice from elective palliative stenting toward emergency preoperative stenting. Conclusion. There is a steep learning curve for the use of SEMS in the management of malignant colorectal bowel obstruction. We suggest that at least 20 cases are required for an operator to be considered experienced.

The Quantitative Evaluation of Functional Neuroimaging Experiments: Mutual Information Learning Curves

DEFF Research Database (Denmark)

Kjems, Ulrik; Hansen, Lars Kai; Anderson, Jon

2002-01-01

Learning curves are presented as an unbiased means for evaluating the performance of models for neuroimaging data analysis. The learning curve measures the predictive performance in terms of the generalization or prediction error as a function of the number of independent examples (e.g., subjects......) used to determine the parameters in the model. Cross-validation resampling is used to obtain unbiased estimates of a generic multivariate Gaussian classifier, for training set sizes from 2 to 16 subjects. We apply the framework to four different activation experiments, in this case \\$\\backslash......\\$[/sup 15/ O]water data sets, although the framework is equally valid for multisubject fMRI studies. We demonstrate how the prediction error can be expressed as the mutual information between the scan and the scan label, measured in units of bits. The mutual information learning curve can be used...

SILC for SILC: Single Institution Learning Curve for Single-Incision Laparoscopic Cholecystectomy

Directory of Open Access Journals (Sweden)

Chee Wei Tay

2013-01-01

Full Text Available Objectives. We report the single-incision laparoscopic cholecystectomy (SILC learning experience of 2 hepatobiliary surgeons and the factors that could influence the learning curve of SILC. Methods. Patients who underwent SILC by Surgeons A and B were studied retrospectively. Operating time, conversion rate, reason for conversion, identity of first assistants, and their experience with previous laparoscopic cholecystectomy (LC were analysed. CUSUM analysis is used to identify learning curve. Results. Hundred and nineteen SILC cases were performed by Surgeons A and B, respectively. Eight cases required additional port. In CUSUM analysis, most conversion occurred during the first 19 cases. Operating time was significantly lower (62.5 versus 90.6 min, P = 0.04 after the learning curve has been overcome. Operating time decreases as the experience increases, especially Surgeon B. Most conversions are due to adhesion at Calot’s triangle. Acute cholecystitis, patients’ BMI, and previous surgery do not seem to influence conversion rate. Mean operating times of cases assisted by first assistant with and without LC experience were 48 and 74 minutes, respectively (P = 0.004. Conclusion. Nineteen cases are needed to overcome the learning curve of SILC. Team work, assistant with CLC experience, and appropriate equipment and technique are the important factors in performing SILC.

Learning curves for solid oxide fuel cells

Energy Technology Data Exchange (ETDEWEB)

Rivera-Tinoco, R.; Schoots, K. [Energy research Centre of the Netherlands (Netherlands). Policy Studies; Zwaan, B.C.C. van der [Energy research Centre of the Netherlands (Netherlands). Policy Studies; Columbia Univ., New York City, NY (United States). Lenfest Center for Sustainable Energy

2010-07-01

We present learning curves for solid oxide fuel cells (SOFCs) and combined heat and power (CHP) SOFC systems with an electric capacity between 1 and 250 kW. On the basis of the cost breakdown of production cost data from fuel cell manufacturers, we developed a bottom-up model that allows for determining overall manufacturing costs from their respective cost components, among which material, energy, labor, and capital charges. The results obtained from our model prove to deviate by at most 13% from total cost figures quoted in the literature. For the early pilot stage of development, we find for SOFC manufacturing a learning rate between 14% and 17%, and for total SOFC system fabrication between 16% and 19%. We argue that the corresponding cost reductions result largely from learning-by-searching effects (R and D) rather than learning-by-doing. When considering a longer time frame that includes the early commercial production stage, we find learning rates between 14% and 39%, which represent a mix of phenomena such as learning-by-doing, learning-by-searching, economies-of-scale and automation. (orig.)

Climbing the health learning curve together | IDRC - International ...

International Development Research Centre (IDRC) Digital Library (Canada)

2011-01-25

Jan 25, 2011 ... Climbing the health learning curve together ... Many of the projects are creating master's programs at their host universities ... Formerly based in the high Arctic, Atlantis is described by Dr Martin Forde of St George's University ...

Laparoscopic colorectal surgery in learning curve: Role of implementation of a standardized technique and recovery protocol. A cohort study

Science.gov (United States)

Luglio, Gaetano; De Palma, Giovanni Domenico; Tarquini, Rachele; Giglio, Mariano Cesare; Sollazzo, Viviana; Esposito, Emanuela; Spadarella, Emanuela; Peltrini, Roberto; Liccardo, Filomena; Bucci, Luigi

2015-01-01

Background Despite the proven benefits, laparoscopic colorectal surgery is still under utilized among surgeons. A steep learning is one of the causes of its limited adoption. Aim of the study is to determine the feasibility and morbidity rate after laparoscopic colorectal surgery in a single institution, “learning curve” experience, implementing a well standardized operative technique and recovery protocol. Methods The first 50 patients treated laparoscopically were included. All the procedures were performed by a trainee surgeon, supervised by a consultant surgeon, according to the principle of complete mesocolic excision with central vascular ligation or TME. Patients underwent a fast track recovery programme. Recovery parameters, short-term outcomes, morbidity and mortality have been assessed. Results Type of resections: 20 left side resections, 8 right side resections, 14 low anterior resection/TME, 5 total colectomy and IRA, 3 total panproctocolectomy and pouch. Mean operative time: 227 min; mean number of lymph-nodes: 18.7. Conversion rate: 8%. Mean time to flatus: 1.3 days; Mean time to solid stool: 2.3 days. Mean length of hospital stay: 7.2 days. Overall morbidity: 24%; major morbidity (Dindo–Clavien III): 4%. No anastomotic leak, no mortality, no 30-days readmission. Conclusion Proper laparoscopic colorectal surgery is safe and leads to excellent results in terms of recovery and short term outcomes, even in a learning curve setting. Key factors for better outcomes and shortening the learning curve seem to be the adoption of a standardized technique and training model along with the strict supervision of an expert colorectal surgeon. PMID:25859386

LEARNING CURVE IN SINGLE-LEVEL MINIMALLY INVASIVE TLIF: EXPERIENCE OF A NEUROSURGEON

Directory of Open Access Journals (Sweden)

Samuel Romano-Feinholz

Full Text Available ABSTRACT Objective: To describe the learning curve that shows the progress of a single neurosurgeon when performing single-level MI-TLIF. Methods: We included 99 consecutive patients who underwent single-level MI-TLIF by the same neurosurgeon (JASS. Patient’s demographic characteristics were analyzed. In addition, surgical time, intraoperative blood loss and hospital stay were evaluated. The learning curves were calculated with a piecewise regression model. Results: The mean age was 54.6 years. The learning curves showed an inverse relationship between the surgical experience and the variable analyzed, reaching an inflection point for surgical time in case 43 and for blood loss in case 48. The mean surgical time was 203.3 minutes (interquartile range [IQR] 150-240 minutes, intraoperative bleeding was 97.4ml (IQR 40-100ml and hospital stay of four days (IQR 3-5 days. Conclusions: MI-TLIF is a very frequent surgical procedure due to its effectiveness and safety, which has shown similar results to open procedure. According to this study, the required learning curve is slightly higher than for open procedures, and is reached after about 45 cases.

Learning Curves of Virtual Mastoidectomy in Distributed and Massed Practice.

Science.gov (United States)

Andersen, Steven Arild Wuyts; Konge, Lars; Cayé-Thomasen, Per; Sørensen, Mads Sølvsten

2015-10-01

Repeated and deliberate practice is crucial in surgical skills training, and virtual reality (VR) simulation can provide self-directed training of basic surgical skills to meet the individual needs of the trainee. Assessment of the learning curves of surgical procedures is pivotal in understanding skills acquisition and best-practice implementation and organization of training. To explore the learning curves of VR simulation training of mastoidectomy and the effects of different practice sequences with the aim of proposing the optimal organization of training. A prospective trial with a 2 × 2 design was conducted at an academic teaching hospital. Participants included 43 novice medical students. Of these, 21 students completed time-distributed practice from October 14 to November 29, 2013, and a separate group of 19 students completed massed practice on May 16, 17, or 18, 2014. Data analysis was performed from June 6, 2014, to March 3, 2015. Participants performed 12 repeated virtual mastoidectomies using a temporal bone surgical simulator in either a distributed (practice blocks spaced in time) or massed (all practice in 1 day) training program with randomization for simulator-integrated tutoring during the first 5 sessions. Performance was assessed using a modified Welling Scale for final product analysis by 2 blinded senior otologists. Compared with the 19 students in the massed practice group, the 21 students in the distributed practice group were older (mean age, 25.1 years), more often male (15 [62%]), and had slightly higher mean gaming frequency (2.3 on a 1-5 Likert scale). Learning curves were established and distributed practice was found to be superior to massed practice, reported as mean end score (95% CI) of 15.7 (14.4-17.0) in distributed practice vs. 13.0 (11.9-14.1) with massed practice (P = .002). Simulator-integrated tutoring accelerated the initial performance, with mean score for tutored sessions of 14.6 (13.9-15.2) vs. 13.4 (12.8-14.0) for

Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects

International Nuclear Information System (INIS)

Yu, C.F.; van Sark, W.G.J.H.M.; Alsema, E.A.

2011-01-01

In a large number of energy models, the use of learning curves for estimating technological improvements has become popular. This is based on the assumption that technological development can be monitored by following cost development as a function of market size. However, recent data show that in some stages of photovoltaic technology (PV) production, the market price of PV modules stabilizes even though the cumulative capacity increases. This implies that no technological improvement takes place in these periods: the cost predicted by the learning curve in the PV study is lower than the market one. We propose that this bias results from ignoring the effects of input prices and scale effects, and that incorporating the input prices and scale effects into the learning curve theory is an important issue in making cost predictions more reliable. In this paper, a methodology is described to incorporate the scale and input-prices effect as the additional variables into the one factor learning curve, which leads to the definition of the multi-factor learning curve. This multi-factor learning curve is not only derived from economic theories, but also supported by an empirical study. The results clearly show that input prices and scale effects are to be included, and that, although market prices are stabilizing, learning is still taking place. (author)

Construction of long-term isochronous stress-strain curves by a modeling of short-term creep curves for a Grade 9Cr-1Mo steel

International Nuclear Information System (INIS)

Kim, Woo-Gon; Yin, Song-Nan; Koo, Gyeong-Hoi

2009-01-01

This study dealt with the construction of long-term isochronous stress-strain curves (ISSC) by a modeling of short-term creep curves for a Grade 9Cr-1Mo steel (G91) which is a candidate material for structural applications in the next generation nuclear reactors as well as in fusion reactors. To do this, tensile material data used in the inelastic constitutive equations was obtained by tensile tests at 550degC. Creep curves were obtained by a series of creep tests with different stress levels of 300MPa to 220MPa at an identical controlled temperature of 550degC. On the basis of these experimental data, the creep curves were characterized by Garofalo's creep model. Three parameters of P 1 , P 2 and P 3 in Garofalo's model were properly optimized by a nonlinear least square fitting (NLSF) analysis. The stress dependency of the three parameters was found to be a linear relationship. But, the P 3 parameter representing the steady state creep rate exhibited a two slope behavior with different stress exponents at a transient stress of about 250 MPa. The long-term creep curves of the G91 steel was modeled by Garofalo's model with only a few short-term creep data. Using the modeled creep curves, the long-term isochronous curves up to 10 5 hours were successfully constructed. (author)

LEARNING CURVE IN ENDOSCOPIC TRANSNASAL SELLAR REGION SURGERY

Directory of Open Access Journals (Sweden)

Ananth G

2016-07-01

Full Text Available BACKGROUND The endoscopic endonasal approach for the sellar region lesions is a novel technique and an effective surgical option. The evidence thus far has been conflicting with reports in favour and against a learning curve. We attempt to determine the learning curve associated with this approach. METHODS Retrospective and prospective data of the patients who were surgically treated for sellar region lesions between the year 2013 and 2016 was collected, 32 patients were operated by the endoscopic endonasal approach at Vydehi Institute of Medical Sciences and Research Centre, Bangalore. Age, sex, presenting symptoms, length of hospital stay, surgical approach, type of dissection, duration of surgery, sellar floor repair, intraoperative and postoperative complications were noted. All the procedures were performed by a single neurosurgeon. RESULTS A total of 32 patients were operated amongst which 21 patients were non-functioning pituitary adenomas, 2 were growth hormone secreting functional adenomas, 1 was an invasive pituitary adenoma, 4 were craniopharyngiomas, 2 were meningiomas, 1 was Rathke’s cleft cyst and 1 was a clival chordoma. Headache was the mode of presentation in 12 patients, 12 patients had visual deficits, 6 patients presented with hormonal disturbances amongst which 4 patients presented with features of panhypopituitarism and 2 with acromegaly. Amongst the 4 patients with panhypopituitarism, 2 also had DI, two patients presented with CSF rhinorrhoea. There was a 100% improvement in the patients who presented with visual symptoms. Gross total resection was achieved in all 4 cases of craniopharyngiomas and 13 cases of pituitary adenomas. Postoperative CSF leak was seen in 4 patients who underwent re-exploration and sellar floor repair, 9 patients had postoperative Diabetes Insipidus (DI which was transient, the incidence of DI reduced towards the end of the study. There was a 25% decrease in the operating time towards the end of

Certificateless short sequential and broadcast multisignature schemes using elliptic curve bilinear pairings

Directory of Open Access Journals (Sweden)

SK Hafizul Islam

2014-01-01

Full Text Available Several certificateless short signature and multisignature schemes based on traditional public key infrastructure (PKI or identity-based cryptosystem (IBC have been proposed in the literature; however, no certificateless short sequential (or serial multisignature (CL-SSMS or short broadcast (or parallel multisignature (CL-SBMS schemes have been proposed. In this paper, we propose two such new CL-SSMS and CL-SBMS schemes based on elliptic curve bilinear pairing. Like any certificateless public key cryptosystem (CL-PKC, the proposed schemes are free from the public key certificate management burden and the private key escrow problem as found in PKI- and IBC-based cryptosystems, respectively. In addition, the requirements of the expected security level and the fixed length signature with constant verification time have been achieved in our schemes. The schemes are communication efficient as the length of the multisignature is equivalent to a single elliptic curve point and thus become the shortest possible multisignature scheme. The proposed schemes are then suitable for communication systems having resource constrained devices such as PDAs, mobile phones, RFID chips, and sensors where the communication bandwidth, battery life, computing power and storage space are limited.

Learning curve for laparoendoscopic single-site surgery for an experienced laparoscopic surgeon

OpenAIRE

Pao-Ling Torng; Kuan-Hung Lin; Jing-Shiang Hwang; Hui-Shan Liu; I-Hui Chen; Chi-Ling Chen; Su-Cheng Huang

2013-01-01

Objectives: To assess the learning curve and safety of laparoendoscopic single-site (LESS) surgery of gynecological surgeries. Materials and methods: Sixty-three women who underwent LESS surgery by a single experienced laparoscopic surgeon from February 2011 to August 2011 were included. Commercialized single-incision laparoscopic surgery homemade ports were used, along with conventional straight instruments. The learning curve has been defined as the additional surgical time with respect ...

Training, Simulation, the Learning Curve, and How to Reduce Complications in Urology.

Science.gov (United States)

Brunckhorst, Oliver; Volpe, Alessandro; van der Poel, Henk; Mottrie, Alexander; Ahmed, Kamran

2016-04-01

Urology is at the forefront of minimally invasive surgery to a great extent. These procedures produce additional learning challenges and possess a steep initial learning curve. Training and assessment methods in surgical specialties such as urology are known to lack clear structure and often rely on differing operative flow experienced by individuals and institutions. This article aims to assess current urology training modalities, to identify the role of simulation within urology, to define and identify the learning curves for various urologic procedures, and to discuss ways to decrease complications in the context of training. A narrative review of the literature was conducted through December 2015 using the PubMed/Medline, Embase, and Cochrane Library databases. Evidence of the validity of training methods in urology includes observation of a procedure, mentorship and fellowship, e-learning, and simulation-based training. Learning curves for various urologic procedures have been recommended based on the available literature. The importance of structured training pathways is highlighted, with integration of modular training to ensure patient safety. Valid training pathways are available in urology. The aim in urology training should be to combine all of the available evidence to produce procedure-specific curricula that utilise the vast array of training methods available to ensure that we continue to improve patient outcomes and reduce complications. The current evidence for different training methods available in urology, including simulation-based training, was reviewed, and the learning curves for various urologic procedures were critically analysed. Based on the evidence, future pathways for urology curricula have been suggested to ensure that patient safety is improved. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Industrial Learning Curves Series Production of the LHC Main Superconduting Dipoles

CERN Document Server

Fessia, Paolo; Rossi, Lucio

2007-01-01

By mid August 2006, 1160 of the 1232 of LHC main dipoles have been delivered to CERN by the three suppliers in charge of the production. The training of the staff, mostly hired just for this manufacture, and the improvement of the procedures with the acquired experience, naturally decrease the time necessary for the assembly of a unit. The aim of this paper is to apply methodologies like the cost-based learning curves and the time-based learning curves to the LHC Main Dipole production comparing the estimated learning percentage to the ones experienced in other industries. This type of analysis, already presented on 500 units is here extended to more than 1000 completed units. The work also tries to identify which type of industry presents the learning percentages that are the most similar to our case and to investigate the impact of the production strategy on the process efficiency.

Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

Science.gov (United States)

Hsu, Pi-Shan

2012-01-01

This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

Learning-curve estimation techniques for nuclear industry

Energy Technology Data Exchange (ETDEWEB)

Vaurio, J.K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on acturial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year.

Learning-curve estimation techniques for nuclear industry

International Nuclear Information System (INIS)

Vaurio, J.K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on acturial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

Learning curve estimation techniques for nuclear industry

International Nuclear Information System (INIS)

Vaurio, Jussi K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on actuarial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

Beyond the learning curve: factors influencing cost reductions in photovoltaics

International Nuclear Information System (INIS)

Nemet, Gregory F.

2006-01-01

The extent and timing of cost-reducing improvements in low-carbon energy systems are important sources of uncertainty in future levels of greenhouse-gas emissions. Models that assess the costs of climate change mitigation policy, and energy policy in general, rely heavily on learning curves to include technology dynamics. Historically, no energy technology has changed more dramatically than photovoltaics (PV), the cost of which has declined by a factor of nearly 100 since the 1950s. Which changes were most important in accounting for the cost reductions that have occurred over the past three decades? Are these results consistent with the notion that learning from experience drove technical change? In this paper, empirical data are assembled to populate a simple model identifying the most important factors affecting the cost of PV. The results indicate that learning from experience, the theoretical mechanism used to explain learning curves, only weakly explains change in the most important factors-plant size, module efficiency, and the cost of silicon. Ways in which the consideration of a broader set of influences, such as technical barriers, industry structure, and characteristics of demand, might be used to inform energy technology policy are discussed

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis

Science.gov (United States)

Tabelow, Karsten; König, Reinhard; Polzehl, Jörg

2016-01-01

Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning. PMID:27303809

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis.

Directory of Open Access Journals (Sweden)

Matthias Deliano

Full Text Available Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning.

An exploratory analysis of personality, attitudes, and study skills on the learning curve within a team-based learning environment.

Science.gov (United States)

Persky, Adam M; Henry, Teague; Campbell, Ashley

2015-03-25

To examine factors that determine the interindividual variability of learning within a team-based learning environment. Students in a pharmacokinetics course were given 4 interim, low-stakes cumulative assessments throughout the semester and a cumulative final examination. Students' Myers-Briggs personality type was assessed, as well as their study skills, motivations, and attitudes towards team-learning. A latent curve model (LCM) was applied and various covariates were assessed to improve the regression model. A quadratic LCM was applied for the first 4 assessments to predict final examination performance. None of the covariates examined significantly impacted the regression model fit except metacognitive self-regulation, which explained some of the variability in the rate of learning. There were some correlations between personality type and attitudes towards team learning, with introverts having a lower opinion of team-learning than extroverts. The LCM could readily describe the learning curve. Extroverted and introverted personality types had the same learning performance even though preference for team-learning was lower in introverts. Other personality traits, study skills, or practice did not significantly contribute to the learning variability in this course.

Hydrogen technologies and the technology learning curve

International Nuclear Information System (INIS)

Rogner, H.-H.

1998-01-01

On their bumpy road to commercialization, hydrogen production, delivery and conversion technologies not only require dedicated research, development and demonstration efforts, but also protected niche markets and early adopters. While niche markets utilize the unique technological properties of hydrogen, adopters exhibit a willingness to pay a premium for hydrogen fueled energy services. The concept of the technology learning curve is applied to estimate the capital requirements associated with the commercialization process of several hydrogen technologies. (author)

The learning curve associated with the introduction of the subcutaneous implantable defibrillator

NARCIS (Netherlands)

Knops, Reinoud E.; Brouwer, Tom F.; Barr, Craig S.; Theuns, Dominic A.; Boersma, Lucas; Weiss, Raul; Neuzil, Petr; Scholten, Marcoen; Lambiase, Pier D.; Leon, Angel R.; Hood, Margaret; Jones, Paul W.; Wold, Nicholas; Grace, Andrew A.; Olde Nordkamp, Louise R. A.; Burke, Martin C.

2016-01-01

Aims The subcutaneous implantable cardioverter defibrillator (S-ICD) was introduced to overcome complications related to transvenous leads. Adoption of the S-ICD requires implanters to learn a new implantation technique. The aim of this study was to assess the learning curve for S-ICD implanters

The learning curve associated with the introduction of the subcutaneous implantable defibrillator

NARCIS (Netherlands)

R.E. Knops (Reinoud); T.F. Brouwer (Tom F.); C.S. Barr (Craig); D.A.M.J. Theuns (Dominic); L. Boersma (Lucas); R. Weiss (Ram); P. Neuzil (Petr); M.F. Scholten (Marcoen); P.D. Lambiase (Pier); A. Leon (Angel); A.M. Hood (Margaret); P. Jones; Wold, N. (Nicholas); Grace, A.A. (Andrew A.); L.R.A. Olde Nordkamp (Louise R.A.); M.C. Burke (Martin)

2016-01-01

textabstractAims: The subcutaneous implantable cardioverter defibrillator (S-ICD) was introduced to overcome complications related to transvenous leads. Adoption of the S-ICD requires implanters to learn a new implantation technique. The aim of this study was to assess the learning curve for S-ICD

Carbon Intensities of Economies from the Perspective of Learning Curves

Directory of Open Access Journals (Sweden)

Henrique Pacini

2014-03-01

Full Text Available While some countries have achieved considerable development, many others still lack accessto the goods and services considered standard in the modern society. As CO2 emissions and development are often correlated, this paper employs the theoretical background of the Environmental Kuznets Curve (EKC and the learning curves toolkit to analyze how carbon intensities have changed as countries move towards higher development (and cumulative wealth levels. The EKC concept is then tested with the methodology of learning curves for the period between 1971 and 2010, so as to capture a dynamic picture of emissions trends and development. Results of both analyses reveal that empirical data fails to provide direct evidence of an EKC for emissions and development. The data does show, however, an interesting pattern in the dispersion of emissions levels for countries within the same HDI categories. While data does not show that countries grow more polluting during intermediary development stages, it does provide evidence that countries become more heterogeneous in their emission intensities as they develop, later re-converging to lower emission intensities at higher HDI levels. Learning rates also indicate heterogeneity among developing countries and relative convergence among developed countries. Given the heterogeneity of development paths among countries, the experiences of those which are managing to develop at low carbon intensities can prove valuable examples for ongoing efforts in climate change mitigation, especially in the developing world.

Measuring the surgical 'learning curve': methods, variables and competency.

Science.gov (United States)

Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

2014-03-01

To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.

A Primer on the Statistical Modelling of Learning Curves in Health Professions Education

Science.gov (United States)

Pusic, Martin V.; Boutis, Kathy; Pecaric, Martin R.; Savenkov, Oleksander; Beckstead, Jason W.; Jaber, Mohamad Y.

2017-01-01

Learning curves are a useful way of representing the rate of learning over time. Features include an index of baseline performance (y-intercept), the efficiency of learning over time (slope parameter) and the maximal theoretical performance achievable (upper asymptote). Each of these parameters can be statistically modelled on an individual and…

Evaluation of the learning curve for external cephalic version using cumulative sum analysis.

Science.gov (United States)

Kim, So Yun; Han, Jung Yeol; Chang, Eun Hye; Kwak, Dong Wook; Ahn, Hyun Kyung; Ryu, Hyun Mi; Kim, Moon Young

2017-07-01

We evaluated the learning curve for external cephalic version (ECV) using learning curve-cumulative sum (LC-CUSUM) analysis. This was a retrospective study involving 290 consecutive cases between October 2013 and March 2017. We evaluated the learning curve for ECV on nulli and over para 1 group using LC-CUSUM analysis on the assumption that 50% and 70% of ECV procedures succeeded by description a trend-line of quadratic function with reliable R 2 values. The overall success rate for ECV was 64.8% (188/290), while the success rate for nullipara and over para 1 groups was 56.2% (100/178) and 78.6% (88/112), respectively. 'H' value, that the actual failure rate does not differ from the acceptable failure rate, was -3.27 and -1.635 when considering ECV success rates of 50% and 70%, respectively. Consequently, in order to obtain a consistent 50% success rate, we would require 57 nullipara cases, and in order to obtain a consistent 70% success rate, we would require 130 nullipara cases. In contrast, 8 to 10 over para 1 cases would be required for an expected success rate of 50% and 70% on over para 1 group. Even a relatively inexperienced physician can experience success with multipara and after accumulating experience, they will manage nullipara cases. Further research is required for LC-CUSUM involving several practitioners instead of a single practitioner. This will lead to the gradual implementation of standard learning curve guidelines for ECV.

Using learning curves on energy-efficient technologies to estimate future energy savings and emission reduction potentials in the U.S. iron and steel industry

Energy Technology Data Exchange (ETDEWEB)

Karali, Nihan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Park, Won Young [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); McNeil, Michael A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-06-18

Increasing concerns on non-sustainable energy use and climate change spur a growing research interest in energy efficiency potentials in various critical areas such as industrial production. This paper focuses on learning curve aspects of energy efficiency measures in the U.S iron and steel sector. A number of early-stage efficient technologies (i.e., emerging or demonstration technologies) are technically feasible and have the potential to make a significant contribution to energy saving and CO₂ emissions reduction, but fall short economically to be included. However, they may also have the cost effective potential for significant cost reduction and/or performance improvement in the future under learning effects such as ‘learning-by-doing’. The investigation is carried out using ISEEM, a technology oriented, linear optimization model. We investigated how steel demand is balanced with/without the availability learning curve, compared to a Reference scenario. The retrofit (or investment in some cases) costs of energy efficient technologies decline in the scenario where learning curve is applied. The analysis also addresses market penetration of energy efficient technologies, energy saving, and CO₂ emissions in the U.S. iron and steel sector with/without learning impact. Accordingly, the study helps those who use energy models better manage the price barriers preventing unrealistic diffusion of energy-efficiency technologies, better understand the market and learning system involved, predict future achievable learning rates more accurately, and project future savings via energy-efficiency technologies with presence of learning. We conclude from our analysis that, most of the existing energy efficiency technologies that are currently used in the U.S. iron and steel sector are cost effective. Penetration levels increases through the years, even though there is no price reduction. However, demonstration technologies are not economically

Detection of player learning curve in a car driving game

NARCIS (Netherlands)

Bontchev, Boyan; Vassileva, Dessislava

2018-01-01

Detection of learning curves of player metrics is very important for the serious (or so called applied) games, because it provides an indicator representing how players master the game tasks by acquiring cognitive abilities, knowledge, and necessary skills for solving the game challenges. Real

Learning curve estimation techniques for the nuclear industry

International Nuclear Information System (INIS)

Vaurio, J.K.

1983-01-01

Statistical techniques are developed to estimate the progress made by the nuclear industry in learning to prevent accidents. Learning curves are derived for accident occurrence rates based on actuarial data, predictions are made for the future, and compact analytical equations are obtained for the statistical accuracies of the estimates. Both maximum likelihood estimation and the method of moments are applied to obtain parameters for the learning models, and results are compared to each other and to earlier graphical and analytical results. An effective statistical test is also derived to assess the significance of trends. The models used associate learning directly to accidents, to the number of plants and to the cumulative number of operating years. Using as a data base nine core damage accidents in electricity-producing plants, it is estimated that the probability of a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year

Prototype-based active learning for lemmatization

CSIR Research Space (South Africa)

Daelemans, W

2009-09-01

Full Text Available ] and Word Length [Long to Short] with the prototypical curves (e.g. Word Frequency [High to Low] and [Word Length Short to Long]). (With regard to the learning curves representing word frequency, refer to 4.1 for an explanation of why [High to Low... of language usage [15]. Secondly, in memory-based language processing [16] it has been argued, on the basis of com- parative machine learning experiments on natural lan- guage processing data, that exceptions are crucial for obtaining high generalization...

Learning curve for robotic-assisted surgery for rectal cancer: use of the cumulative sum method.

Science.gov (United States)

Yamaguchi, Tomohiro; Kinugasa, Yusuke; Shiomi, Akio; Sato, Sumito; Yamakawa, Yushi; Kagawa, Hiroyasu; Tomioka, Hiroyuki; Mori, Keita

2015-07-01

Few data are available to assess the learning curve for robotic-assisted surgery for rectal cancer. The aim of the present study was to evaluate the learning curve for robotic-assisted surgery for rectal cancer by a surgeon at a single institute. From December 2011 to August 2013, a total of 80 consecutive patients who underwent robotic-assisted surgery for rectal cancer performed by the same surgeon were included in this study. The learning curve was analyzed using the cumulative sum method. This method was used for all 80 cases, taking into account operative time. Operative procedures included anterior resections in 6 patients, low anterior resections in 46 patients, intersphincteric resections in 22 patients, and abdominoperineal resections in 6 patients. Lateral lymph node dissection was performed in 28 patients. Median operative time was 280 min (range 135-683 min), and median blood loss was 17 mL (range 0-690 mL). No postoperative complications of Clavien-Dindo classification Grade III or IV were encountered. We arranged operative times and calculated cumulative sum values, allowing differentiation of three phases: phase I, Cases 1-25; phase II, Cases 26-50; and phase III, Cases 51-80. Our data suggested three phases of the learning curve in robotic-assisted surgery for rectal cancer. The first 25 cases formed the learning phase.

Long-term associative learning predicts verbal short-term memory performance

OpenAIRE

Jones, Gary; Macken, Bill

2017-01-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term...

Medical learning curves and the Kantian ideal.

Science.gov (United States)

Le Morvan, P; Stock, B

2005-09-01

A hitherto unexamined problem for the "Kantian ideal" that one should always treat patients as ends in themselves, and never only as a means to other ends, is explored in this paper. The problem consists of a prima facie conflict between this Kantian ideal and the reality of medical practice. This conflict arises because, at least presently, medical practitioners can only acquire certain skills and abilities by practising on live, human patients, and given the inevitability and ubiquity of learning curves, this learning requires some patients to be treated only as a means to this end. A number of ways of attempting to establish the compatibility of the Kantian Ideal with the reality of medical practice are considered. Each attempt is found to be unsuccessful. Accordingly, until a way is found to reconcile them, we conclude that the Kantian ideal is inconsistent with the reality of medical practice.

Robotic partial nephrectomy - Evaluation of the impact of case mix on the procedural learning curve.

Science.gov (United States)

Roman, A; Ahmed, K; Challacombe, B

2016-05-01

Although Robotic partial nephrectomy (RPN) is an emerging technique for the management of small renal masses, this approach is technically demanding. To date, there is limited data on the nature and progression of the learning curve in RPN. To analyse the impact of case mix on the RPN LC and to model the learning curve. The records of the first 100 RPN performed, were analysed at our institution that were carried out by a single surgeon (B.C) (June 2010-December 2013). Cases were split based on their Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score into the following groups: 6-7, 8-9 and >10. Using a split group (20 patients in each group) and incremental analysis, the mean, the curve of best fit and R(2) values were calculated for each group. Of 100 patients (F:28, M:72), the mean age was 56.4 ± 11.9 years. The number of patients in each PADUA score groups: 6-7, 8-9 and >10 were 61, 32 and 7 respectively. An increase in incidence of more complex cases throughout the cohort was evident within the 8-9 group (2010: 1 case, 2013: 16 cases). The learning process did not significantly affect the proxies used to assess surgical proficiency in this study (operative time and warm ischaemia time). Case difficulty is an important parameter that should be considered when evaluating procedural learning curves. There is not one well fitting model that can be used to model the learning curve. With increasing experience, clinicians tend to operate on more difficult cases. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Long-term associative learning predicts verbal short-term memory performance.

Science.gov (United States)

Jones, Gary; Macken, Bill

2018-02-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

Learning curve for laparoendoscopic single-site surgery for an experienced laparoscopic surgeon

Directory of Open Access Journals (Sweden)

Pao-Ling Torng

2013-11-01

Conclusion: LESS is a safe and feasible alternative to conventional laparoscopic surgery for adnexal and uterine diseases. A learning curve is not required for LESS surgery for experienced laparoscopic surgeons.

Learning curve of thyroid fine-needle aspiration biopsy.

Science.gov (United States)

Penín, Manuel; Martín, M Ángeles; San Millán, Beatriz; García, Juana

2017-12-01

Fine-needle aspiration biopsy (FNAB) is the reference procedure for thyroid nodule evaluation. Its main limitation are inadequate samples, which should be less than 20%. To analyze the learning curve of the procedure by comparing the results of a non-experienced endocrinologist (endocrinologist 2) to those of an experienced one (endocrinologist 1). Sixty FNABs were analyzed from February to June 2016. Each endocrinologist made 2punctures of every nodule in a random order. This order and the professional making every puncture were unknown to the pathologist who examined the samples. Endocrinologist 1 had a higher percentage of diagnoses than endocrinologist 2 (82% vs. 72%, P=.015). In the first 20 FNABs, the difference between both physicians was remarkable and statistically significant (80% vs. 50%, P=.047). In the following 20 FNABs, the difference narrowed and was not statistically significant (90% vs. 65%, P=.058). In the final 20 FNABs, the difference was minimal and not statistically significant (75% vs. 70%, P=.723). The learning curve of ultrasound-guided FNAB may be completed in a suitable environment by performing it at least 60 times. Although the guidelines recommend at least 3punctures per nodule, 2are enough to achieve an accurate percentage of diagnoses. Copyright © 2017 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.

Learning curve analysis of mitral valve repair using telemanipulative technology.

Science.gov (United States)

Charland, Patrick J; Robbins, Tom; Rodriguez, Evilio; Nifong, Wiley L; Chitwood, Randolph W

2011-08-01

To determine if the time required to perform mitral valve repairs using telemanipulation technology decreases with experience and how that decrease is influenced by patient and procedure variables. A single-center retrospective review was conducted using perioperative and outcomes data collected contemporaneously on 458 mitral valve repair surgeries using telemanipulative technology. A regression model was constructed to assess learning with this technology and predict total robot time using multiple predictive variables. Statistical analysis was used to determine if models were significantly useful, to rule out correlation between predictor variables, and to identify terms that did not contribute to the prediction of total robot time. We found a statistically significant learning curve (P learning percentage∗ derived from total robot times† for the first 458 recorded cases of mitral valve repair using telemanipulative technology is 95% (R(2) = .40). More than one third of the variability in total robot time can be explained through our model using the following variables: type of repair (chordal procedures, ablations, and leaflet resections), band size, use of clips alone in band implantation, and the presence of a fellow at bedside (P Learning in mitral valve repair surgery using telemanipulative technology occurs at the East Carolina Heart Institute according to a logarithmic curve, with a learning percentage of 95%. From our regression output, we can make an approximate prediction of total robot time using an additive model. These metrics can be used by programs for benchmarking to manage the implementation of this new technology, as well as for capacity planning, scheduling, and capital budget analysis. Copyright © 2011 The American Association for Thoracic Surgery. All rights reserved.

Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

Directory of Open Access Journals (Sweden)

Federico Divina

2018-04-01

Full Text Available The ability to predict short-term electric energy demand would provide several benefits, both at the economic and environmental level. For example, it would allow for an efficient use of resources in order to face the actual demand, reducing the costs associated to the production as well as the emission of CO 2 . To this aim, in this paper we propose a strategy based on ensemble learning in order to tackle the short-term load forecasting problem. In particular, our approach is based on a stacking ensemble learning scheme, where the predictions produced by three base learning methods are used by a top level method in order to produce final predictions. We tested the proposed scheme on a dataset reporting the energy consumption in Spain over more than nine years. The obtained experimental results show that an approach for short-term electricity consumption forecasting based on ensemble learning can help in combining predictions produced by weaker learning methods in order to obtain superior results. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that using an ensemble scheme can achieve very accurate predictions, and thus that it is a suitable approach for addressing the short-term load forecasting problem.

Laparoscopy Instructional Videos : The Effect of Preoperative Compared With Intraoperative Use on Learning Curves

NARCIS (Netherlands)

Broekema, Theo H.; Talsma, Aaldert K.; Wevers, Kevin P.; Pierie, Jean-Pierre E. N.

OBJECTIVE: Previous studies have shown that the use of intraoperative instructional videos has a positive effect on learning laparoscopic procedures. This study investigated the effect of the timing of the instructional videos on learning curves in laparoscopic skills training. DESIGN: After

Verbal short-term memory and vocabulary learning in polyglots.

Science.gov (United States)

Papagno, C; Vallar, G

1995-02-01

Polyglot and non-polyglot Italian subjects were given tests assessing verbal (phonological) and visuo-spatial short-term and long-term memory, general intelligence, and vocabulary knowledge in their native language. Polyglots had a superior level of performance in verbal short-term memory tasks (auditory digit span and nonword repetition) and in a paired-associate learning test, which assessed the subjects' ability to acquire new (Russian) words. By contrast, the two groups had comparable performance levels in tasks assessing general intelligence, visuo-spatial short-term memory and learning, and paired-associate learning of Italian words. These findings, which are in line with neuropsychological and developmental evidence, as well as with data from normal subjects, suggest a close relationship between the capacity of phonological memory and the acquisition of foreign languages.

Non-Constant Learning Rates in Retrospective Experience Curve Analyses and their Correlation to Deployment Programs

Energy Technology Data Exchange (ETDEWEB)

Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-07-16

A key challenge for policy-makers and technology market forecasters is to estimate future technology costs and in particular the rate of cost reduction versus production volume. A related, critical question is what role should state and federal governments have in advancing energy efficient and renewable energy technologies? This work provides retrospective experience curves and learning rates for several energy-related technologies, each of which have a known history of federal and state deployment programs. We derive learning rates for eight technologies including energy efficient lighting technologies, stationary fuel cell systems, and residential solar photovoltaics, and provide an overview and timeline of historical deployment programs such as state and federal standards and state and national incentive programs for each technology. Piecewise linear regimes are observed in a range of technology experience curves, and public investments or deployment programs are found to be strongly correlated to an increase in learning rate across multiple technologies. A downward bend in the experience curve is found in 5 out of the 8 energy-related technologies presented here (electronic ballasts, magnetic ballasts, compact fluorescent lighting, general service fluorescent lighting, and the installed cost of solar PV). In each of the five downward-bending experience curves, we believe that an increase in the learning rate can be linked to deployment programs to some degree. This work sheds light on the endogenous versus exogenous contributions to technological innovation and highlights the impact of exogenous government sponsored deployment programs. This work can inform future policy investment direction and can shed light on market transformation and technology learning behavior.

Learning Curve for Seawater Reverse Osmosis Desalination Plants: Capital Cost Trend of the Past, Present, and Future

Science.gov (United States)

Caldera, Upeksha; Breyer, Christian

2017-12-01

Seawater reverse osmosis (SWRO) desalination is expected to play a pivotal role in helping to secure future global water supply. While the global reliance on SWRO plants for water security increases, there is no consensus on how the capital costs of SWRO plants will vary in the future. The aim of this paper is to analyze the past trends of the SWRO capital expenditures (capex) as the historic global cumulative online SWRO capacity increases, based on the learning curve concept. The SWRO capex learning curve is found based on 4,237 plants that came online from 1977 to 2015. A learning rate of 15% is determined, implying that the SWRO capex reduced by 15% when the cumulative capacity was doubled. Based on SWRO capacity annual growth rates of 10% and 20%, by 2030, the global average capex of SWRO plants is found to fall to 1,580 USD/(m3/d) and 1,340 USD/(m3/d), respectively. A learning curve for SWRO capital costs has not been presented previously. This research highlights the potential for decrease in SWRO capex with the increase in installation of SWRO plants and the value of the learning curve approach to estimate future SWRO capex.

The learning curve of laparoscopic holecystectomy in general surgery resident training: old age of the patient may be a risk factor?

Science.gov (United States)

Ferrarese, Alessia; Gentile, Valentina; Bindi, Marco; Rivelli, Matteo; Cumbo, Jacopo; Solej, Mario; Enrico, Stefano; Martino, Valter

2016-01-01

A well-designed learning curve is essential for the acquisition of laparoscopic skills: but, are there risk factors that can derail the surgical method? From a review of the current literature on the learning curve in laparoscopic surgery, we identified learning curve components in video laparoscopic cholecystectomy; we suggest a learning curve model that can be applied to assess the progress of general surgical residents as they learn and master the stages of video laparoscopic cholecystectomy regardless of type of patient. Electronic databases were interrogated to better define the terms "surgeon", "specialized surgeon", and "specialist surgeon"; we surveyed the literature on surgical residency programs outside Italy to identify learning curve components, influential factors, the importance of tutoring, and the role of reference centers in residency education in surgery. From the definition of acceptable error, self-efficacy, and error classification, we devised a learning curve model that may be applied to training surgical residents in video laparoscopic cholecystectomy. Based on the criteria culled from the literature, the three surgeon categories (general, specialized, and specialist) are distinguished by years of experience, case volume, and error rate; the patients were distinguished for years and characteristics. The training model was constructed as a series of key learning steps in video laparoscopic cholecystectomy. Potential errors were identified and the difficulty of each step was graded using operation-specific characteristics. On completion of each procedure, error checklist scores on procedure-specific performance are tallied to track the learning curve and obtain performance indices of measurement that chart the trainee's progress. The concept of the learning curve in general surgery is disputed. The use of learning steps may enable the resident surgical trainee to acquire video laparoscopic cholecystectomy skills proportional to the instructor

A New Proposal for Learning Curve of TEP Inguinal Hernia Repair: Ability to Complete Operation Endoscopically as a First Phase of Learning Curve

Directory of Open Access Journals (Sweden)

Mustafa Hasbahceci

2014-01-01

Full Text Available Background. The exact nature of learning curve of totally extraperitoneal inguinal hernia and the number required to master this technique remain controversial. Patients and Methods. We present a retrospective review of a single surgeon experience on patients who underwent totally extraperitoneal inguinal hernia repair. Results. There were 42 hernias (22 left- and 20 right-sided in 39 patients with a mean age of 48.8±15.1 years. Indirect, direct, and combined hernias were present in 18, 12, and 12 cases, respectively. The mean operative time was 55.1±22.8 minutes. Peritoneal injury occurred in 9 cases (21.4%. Conversion to open surgery was necessitated in 7 cases (16.7%. After grouping of all patients into two groups as cases between 1–21 and 22–42, it was seen that the majority of peritoneal injuries (7 out of 9, 77.8%, P=0.130 and all conversions (P=0.001 occurred in the first 21 cases. Conclusions. Learning curve of totally extraperitoneal inguinal hernia repair can be divided into two consequent steps: immediate and late. At least 20 operations are required for gaining anatomical knowledge and surgical pitfalls based on the ability to perform this operation without conversion during immediate phase.

Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea

International Nuclear Information System (INIS)

Hong, Sungjun; Chung, Yanghon; Woo, Chungwon

2015-01-01

South Korea, as the 9th largest energy consuming in 2013 and the 7th largest greenhouse gas emitting country in 2011, established ‘Low Carbon Green Growth’ as the national vision in 2008, and is announcing various active energy policies that are set to gain the attention of the world. In this paper, we estimated the decrease of photovoltaic power generation cost in Korea based on the learning curve theory. Photovoltaic energy is one of the leading renewable energy sources, and countries all over the world are currently expanding R and D, demonstration and deployment of photovoltaic technology. In order to estimate the learning rate of photovoltaic energy in Korea, both conventional 1FLC (one-factor learning curve), which considers only the cumulative power generation, and 2FLC, which also considers R and D investment were applied. The 1FLC analysis showed that the cost of power generation decreased by 3.1% as the cumulative power generation doubled. The 2FCL analysis presented that the cost decreases by 2.33% every time the cumulative photovoltaic power generation is doubled and by 5.13% every time R and D investment is doubled. Moreover, the effect of R and D investment on photovoltaic technology took after around 3 years, and the depreciation rate of R and D investment was around 20%. - Highlights: • We analyze the learning effects of photovoltaic energy technology in Korea. • In order to calculate the learning rate, we use 1FLC (one-factor learning curve) and 2FLC methods, respectively. • 1FLC method considers only the cumulative power generation. • 2FLC method considers both cumulative power generation and knowledge stock. • We analyze a variety of scenarios by time lag and depreciation rate of R and D investment

Learning Curve Analysis and Surgical Outcomes of Single-port Laparoscopic Myomectomy.

Science.gov (United States)

Lee, Hee Jun; Kim, Ju Yeong; Kim, Seul Ki; Lee, Jung Ryeol; Suh, Chang Suk; Kim, Seok Hyun

2015-01-01

To identify learning curves for single-port laparoscopic myomectomy (SPLM) and evaluate surgical outcomes according to the sequence of operation. A retrospective study. A university-based hospital (Canadian Task Force classification II-2). The medical records from 205 patients who had undergone SPLM from October 2009 to May 2013 were reviewed. Because the myomectomy time was significantly affected by the size and number of myomas removed by SPLM, cases in which 2 or more of the myomas removed were >7 cm in diameter were excluded. Furthermore, cases involving additional operations performed simultaneously (e.g., ovarian or hysteroscopic surgery) were also excluded. A total of 161 cases of SPLM were included. None. We assessed the SPLM learning curve via a graph based on operation time versus sequence of cases. Patients were chronologically arranged according to their surgery dates and were then placed into 1 of 4 groups according to their operation sequence. SPLM was completed successfully in 160 of 161 cases (99.4%). One case was converted to multiport surgery. Basal characteristics of the patients between the 4 groups did not differ. The median operation times for the 4 groups were 112.0, 92.8, 83.7, and 90.0 minutes, respectively. Operation time decreased significantly in the second, third, and fourth groups compared with that in the first group (p learning curve became less steep, was evident after about 45 operations. Results from the current study suggested that proficiency for SPLM was achieved after about 45 operations. Additionally, operation time decreased with experience without an increase in complication rate. Copyright © 2015 AAGL. Published by Elsevier Inc. All rights reserved.

Displays mounted on cutting blocks reduce the learning curve in navigated total knee arthroplasty.

Science.gov (United States)

Schnurr, Christoph; Eysel, Peer; König, Dietmar Pierre

2011-01-01

The use of computer navigation in total knee arthroplasty (TKA) improves the implant alignment but increases the operation time. Studies have shown that the operation time is further prolonged due to the surgeon's learning curve, and longer operation times have been associated with higher morbidity risks. It has been our hypothesis that an improvement in the human-machine interface might reduce the time required during the learning curve. Accordingly, we asked whether the use of navigation devices with a display fixed on the surgical instruments would reduce the operation time in navigated TKAs performed by navigation beginners. Thirty medical students were randomized and used two navigation devices in rotation: these were the Kolibri® device with an external display and the Dash® device with a display that was fixed on the cutting blocks. The time for adjustment of the tibial and femoral cutting blocks on knee models while using these devices was measured. A significant time reduction was demonstration when the Dash® device was used: The time reduction was 21% for the tibial block (p = 0.007), 40% for the femoral block (p learning curve may be diminished.

Short-radius horizontal well re-entry learning curve: prize, cost and operational experience

Energy Technology Data Exchange (ETDEWEB)

Boote, K. [Ocelot Energy Inc., Calgary, AB (Canada); MacDonald, R. [Lauron Engineering Ltd, Calgary, AB (Canada)

1997-12-01

Six mature vertical wells in Alberta belonging to Ocelot Energy Inc., were reentered and drilled horizontally. Experiences gained, the modifications made to the drilling program and the rewards in the form of incremental oil, were discussed. Details of pre- and post-performance, operational experiences with exiting the casing, building the curve, overbalance versus underbalanced drilling, motors, directional equipment, setting liners, remedial workovers and the cost of the operation were part of the discussion.

Application of the Learning Curve Analysis to the LHC Main Dipole Production First Assessment

CERN Document Server

Fessia, P; Rossi, L

2006-01-01

About two third of the LHC main dipoles have been delivered by the three suppliers charged of the production. The training of the staff, mostly hired just for this manufacture, and the natural improvement of the procedures with the acquired experience, decrease naturally the time necessary for the assembly of a unit. The aim of this paper is to apply methodologies like the cost-based learning curves and the time-based learning curves to the LHC Main Dipole comparing the estimated learning percentage to the ones experienced in other industries. This type of analysis, still in a preliminary phase and here applied to about 40% of the total production of the LHC magnets that will end by 2006, shows that our production has a relatively high learning percentage and it is similar to aerospace and complex machine tools for new models. Therefore with the LHC project, accelerator magnets seem to have reached industrial maturity and this production can be used as bench mark for other large scientific projects implying s...

Learning Curves and Bootstrap Estimates for Inference with Gaussian Processes: A Statistical Mechanics Study

DEFF Research Database (Denmark)

Malzahn, Dorthe; Opper, Manfred

2003-01-01

We employ the replica method of statistical physics to study the average case performance of learning systems. The new feature of our theory is that general distributions of data can be treated, which enables applications to real data. For a class of Bayesian prediction models which are based...... on Gaussian processes, we discuss Bootstrap estimates for learning curves....

Environmental management by the learning curve

International Nuclear Information System (INIS)

Fehr, M.

2003-01-01

This is a futuristic appreciation of waste management challenges and their solution by means of good management models. A literature review, administrative initiatives, research results, and experiences from practice are combined in this study to render an evolutionary picture of the change in paradigm relative to municipal solid waste possible to occur between 2000 and 2025. The principal stages of progress in the 25 years studied were: the correct characterization of municipal solid waste as a function of geographical location and recycling potential, the divided collection model and its corresponding learning curve, correct opportunity cost accounting tools, and the generally admitted and accepted changeover of municipal solid waste treatment from a technical to a management problem. It is reported that as a result of this progress, the municipal landfill is a species in extinction. Regional landfills with long life spans are the rule in 2025

Systematic review of learning curves for minimally invasive abdominal surgery: a review of the methodology of data collection, depiction of outcomes, and statistical analysis.

Science.gov (United States)

Harrysson, Iliana J; Cook, Jonathan; Sirimanna, Pramudith; Feldman, Liane S; Darzi, Ara; Aggarwal, Rajesh

2014-07-01

To determine how minimally invasive surgical learning curves are assessed and define an ideal framework for this assessment. Learning curves have implications for training and adoption of new procedures and devices. In 2000, a review of the learning curve literature was done by Ramsay et al and it called for improved reporting and statistical evaluation of learning curves. Since then, a body of literature is emerging on learning curves but the presentation and analysis vary. A systematic search was performed of MEDLINE, EMBASE, ISI Web of Science, ERIC, and the Cochrane Library from 1985 to August 2012. The inclusion criteria are minimally invasive abdominal surgery formally analyzing the learning curve and English language. 592 (11.1%) of the identified studies met the selection criteria. Time is the most commonly used proxy for the learning curve (508, 86%). Intraoperative outcomes were used in 316 (53%) of the articles, postoperative outcomes in 306 (52%), technical skills in 102 (17%), and patient-oriented outcomes in 38 (6%) articles. Over time, there was evidence of an increase in the relative amount of laparoscopic and robotic studies (P statistical evidence of a change in the complexity of analysis (P = 0.121). Assessment of learning curves is needed to inform surgical training and evaluate new clinical procedures. An ideal analysis would account for the degree of complexity of individual cases and the inherent differences between surgeons. There is no single proxy that best represents the success of surgery, and hence multiple outcomes should be collected.

Stenting for curved lesions using a novel curved balloon: Preliminary experimental study.

Science.gov (United States)

Tomita, Hideshi; Higaki, Takashi; Kobayashi, Toshiki; Fujii, Takanari; Fujimoto, Kazuto

2015-08-01

Stenting may be a compelling approach to dilating curved lesions in congenital heart diseases. However, balloon-expandable stents, which are commonly used for congenital heart diseases, are usually deployed in a straight orientation. In this study, we evaluated the effect of stenting with a novel curved balloon considered to provide better conformability to the curved-angled lesion. In vitro experiments: A Palmaz Genesis(®) stent (Johnson & Johnson, Cordis Co, Bridgewater, NJ, USA) mounted on the Goku(®) curve (Tokai Medical Co. Nagoya, Japan) was dilated in vitro to observe directly the behavior of the stent and balloon assembly during expansion. Animal experiment: A short Express(®) Vascular SD (Boston Scientific Co, Marlborough, MA, USA) stent and a long Express(®) Vascular LD stent (Boston Scientific) mounted on the curved balloon were deployed in the curved vessel of a pig to observe the effect of stenting in vivo. In vitro experiments: Although the stent was dilated in a curved fashion, stent and balloon assembly also rotated conjointly during expansion of its curved portion. In the primary stenting of the short stent, the stent was dilated with rotation of the curved portion. The excised stent conformed to the curved vessel. As the long stent could not be negotiated across the mid-portion with the balloon in expansion when it started curving, the mid-portion of the stent failed to expand fully. Furthermore, the balloon, which became entangled with the stent strut, could not be retrieved even after complete deflation. This novel curved balloon catheter might be used for implantation of the short stent in a curved lesion; however, it should not be used for primary stenting of the long stent. Post-dilation to conform the stent to the angled vessel would be safer than primary stenting irrespective of stent length. Copyright © 2014 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Short-range quantitative precipitation forecasting using Deep Learning approaches

Science.gov (United States)

Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

The Simulation Computer Based Learning (SCBL) for Short Circuit Multi Machine Power System Analysis

Science.gov (United States)

Rahmaniar; Putri, Maharani

2018-03-01

Strengthening Competitiveness of human resources become the reply of college as a conductor of high fomal education. Electrical Engineering Program UNPAB (Prodi TE UNPAB) as one of the department of electrical engineering that manages the field of electrical engineering expertise has a very important part in preparing human resources (HR), Which is required by where graduates are produced by DE UNPAB, Is expected to be able to compete globally, especially related to the implementation of Asean Economic Community (AEC) which requires the active participation of graduates with competence and quality of human resource competitiveness. Preparation of HR formation Competitive is done with the various strategies contained in the Seven (7) Higher Education Standard, one part of which is the implementation of teaching and learning process in Electrical system analysis with short circuit analysis (SCA) This course is a course The core of which is the basis for the competencies of other subjects in the advanced semester at Development of Computer Based Learning model (CBL) is done in the learning of interference analysis of multi-machine short circuit which includes: (a) Short-circuit One phase, (B) Two-phase Short Circuit Disruption, (c) Ground Short Circuit Disruption, (d) Short Circuit Disruption One Ground Floor Development of CBL learning model for Electrical System Analysis course provides space for students to be more active In learning in solving complex (complicated) problems, so it is thrilling Ilkan flexibility of student learning how to actively solve the problem of short-circuit analysis and to form the active participation of students in learning (Student Center Learning, in the course of electrical power system analysis.

Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis

Directory of Open Access Journals (Sweden)

Igor I. Stepanov

2012-01-01

Full Text Available The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1–5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males. A group of MS patients included 365 patients (266 females and 99 males with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients 3 and 4 of our mathematical model 3∗exp(−2∗(−1+4∗(1−exp(−2∗(−1 because discriminant functions, calculated separately for 3 and 4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both.

Blended Learning Approach of the Flipped Model for Partograph Short Course

Directory of Open Access Journals (Sweden)

Linawati Linawati

2016-08-01

Full Text Available Crucial demand of professional and well-trained midwives, midwifery lecturers, general practitioner, and OBGYN in Indonesia could be fulfilled by providing effective learning process to them. Udayana University through its Distance Learning Centre has offered Partograph short course in order to respond the demand. The short course has implemented blended learning approach of the flipped classroom with international collaboration. The course was joint by participants from 11 countries through video conference.  The course was well designed, conducted follow Global Development Learning Network standard, and then it was evaluated.  The course yielded high impact to the participants which could be seen from the participants’ feedback. They testified that the course was marvelous, effective and informative. Finally the evaluation results showed that all components of the learning process have significant result to the overall learning quality which was shown by their correlation coefficients.

Short-Term Memory, Executive Control, and Children's Route Learning

Science.gov (United States)

Purser, Harry R. M.; Farran, Emily K.; Courbois, Yannick; Lemahieu, Axelle; Mellier, Daniel; Sockeel, Pascal; Blades, Mark

2012-01-01

The aim of this study was to investigate route-learning ability in 67 children aged 5 to 11 years and to relate route-learning performance to the components of Baddeley's model of working memory. Children carried out tasks that included measures of verbal and visuospatial short-term memory and executive control and also measures of verbal and…

Melatonin Secretion during a Short Nap Fosters Subsequent Feedback Learning

Directory of Open Access Journals (Sweden)

Christian D. Wiesner

2018-01-01

Full Text Available Sleep helps to protect and renew hippocampus-dependent declarative learning. Less is known about forms of learning that mainly engage the dopaminergic reward system. Animal studies showed that exogenous melatonin modulates the responses of the dopaminergic reward system and acts as a neuroprotectant promoting memory. In humans, melatonin is mainly secreted in darkness during evening hours supporting sleep. In this study, we investigate the effects of a short period of daytime sleep (nap and endogenous melatonin on reward learning. Twenty-seven healthy, adult students took part in an experiment, either taking a 90-min afternoon nap or watching videos (within-subject design. Before and after the sleep vs. wake interval, saliva melatonin levels and reward learning were measured, and in the nap condition, a polysomnogram was obtained. Reward learning was assessed using a two-alternative probabilistic reinforcement-learning task. Sleep itself and subjective arousal or valence had no significant effects on reward learning. However, this study showed for the first time that an afternoon nap can elicit a small but significant melatonin response in about 41% of the participants and that the magnitude of the melatonin response predicts subsequent reward learning. Only in melatonin responders did a short nap improve reward learning. The difference between melatonin-responders and non-responders occurred very early during learning indicating that melatonin might have improved working memory rather than reward learning. Future studies should use paradigms differentiating working memory and reward learning to clarify which aspect of human feedback learning might profit from melatonin.

Does my high blood pressure improve your survival? Overall and subgroup learning curves in health.

Science.gov (United States)

Van Gestel, Raf; Müller, Tobias; Bosmans, Johan

2017-09-01

Learning curves in health are of interest for a wide range of medical disciplines, healthcare providers, and policy makers. In this paper, we distinguish between three types of learning when identifying overall learning curves: economies of scale, learning from cumulative experience, and human capital depreciation. In addition, we approach the question of how treating more patients with specific characteristics predicts provider performance. To soften collinearity problems, we explore the use of least absolute shrinkage and selection operator regression as a variable selection method and Theil-Goldberger mixed estimation to augment the available information. We use data from the Belgian Transcatheter Aorta Valve Implantation (TAVI) registry, containing information on the first 860 TAVI procedures in Belgium. We find that treating an additional TAVI patient is associated with an increase in the probability of 2-year survival by about 0.16%-points. For adverse events like renal failure and stroke, we find that an extra day between procedures is associated with an increase in the probability for these events by 0.12%-points and 0.07%-points, respectively. Furthermore, we find evidence for positive learning effects from physicians' experience with defibrillation, treating patients with hypertension, and the use of certain types of replacement valves during the TAVI procedure. Copyright © 2017 John Wiley & Sons, Ltd.

The development of automaticity in short-term memory search: Item-response learning and category learning.

Science.gov (United States)

Cao, Rui; Nosofsky, Robert M; Shiffrin, Richard M

2017-05-01

In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across trials. In item-response learning, subjects learn long-term mappings between individual items and target versus foil responses. In category learning, subjects learn high-level codes corresponding to separate sets of items and learn to attach old versus new responses to these category codes. To distinguish between these 2 forms of learning, we tested subjects in categorized varied mapping (CV) conditions: There were 2 distinct categories of items, but the assignment of categories to target versus foil responses varied across trials. In cases involving arbitrary categories, CV performance closely resembled standard varied-mapping performance without categories and departed dramatically from CM performance, supporting the item-response-learning hypothesis. In cases involving prelearned categories, CV performance resembled CM performance, as long as there was sufficient practice or steps taken to reduce trial-to-trial category-switching costs. This pattern of results supports the category-coding hypothesis for sufficiently well-learned categories. Thus, item-response learning occurs rapidly and is used early in CM training; category learning is much slower but is eventually adopted and is used to increase the efficiency of search beyond that available from item-response learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Short-term memory, executive control, and children's route learning

OpenAIRE

Purser, H. R.; Farran, E. K.; Courbois, Y.; Lemahieu, A.; Mellier, D.; Sockeel, P.; Blades, M.

2012-01-01

The aim of this study was to investigate route-learning ability in 67 children aged 5 to 11years and to relate route-learning performance to the components of Baddeley's model of working memory. Children carried out tasks that included measures of verbal and visuospatial short-term memory and executive control and also measures of verbal and visuospatial long-term memory; the route-learning task was conducted using a maze in a virtual environment. In contrast to previous research, correlation...

Why the Kantian ideal survives medical learning curves, and why it matters.

Science.gov (United States)

Brecher, B

2006-09-01

The "Kantian ideal" is often misunderstood as invoking individual autonomy rather than rational self legislation. Le Morvan and Stock's otherwise insightful discussion of "Medical learning curves and the Kantian ideal"--for example--draws the mistaken inference that that ideal is inconsistent with the realities of medical practice. But it is not. Rationally to be a patient entails accepting its necessary conditions.

Preliminary Results and Learning Curve of the Minimally Invasive Chevron Akin Operation for Hallux Valgus.

Science.gov (United States)

Jowett, Charlie R J; Bedi, Harvinder S

Minimally invasive surgery is increasing in popularity. It is relevant in hallux valgus surgery owing to the potential for reduced disruption of the soft tissues and improved wound healing. We present our results and assess the learning curve of the minimally invasive Chevron Akin operation for hallux valgus. A total of 120 consecutive feet underwent minimally invasive Chevron Akin for symptomatic hallux valgus, of which 14 were excluded. They were followed up for a mean of 25 (range 18 to 38) months. The patients were clinically assessed using the American Orthopaedic Foot and Ankle Society score. Complications and patient satisfaction were recorded. The radiographs were analyzed and measurements recorded for hallux valgus and intermetatarsal angle correction. The mean age of the patients undergoing surgery was 55 (range 25 to 81) years. Of the 78 patients, 76 (97.4%) were female and 2 (2.6%) were male; 28 (35.9%) cases were bilateral. The mean American Orthopaedic Foot and Ankle Society score improved from 56 (range 23 to 76) preoperatively to 87 (range 50 to 100) postoperatively (p technique. They display a steep associated learning curve. However, the results are promising, and the learning curve is comparable to that for open hallux valgus surgery. Copyright © 2017 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis

Science.gov (United States)

Stepanov, Igor I.; Abramson, Charles I.; Hoogs, Marietta; Benedict, Ralph H. B.

2012-01-01

The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1–5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males). A group of MS patients included 365 patients (266 females and 99 males) with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients B3 and B4 of our mathematical model B3 ∗ exp(−B2  ∗  (X − 1)) + B4  ∗  (1 − exp(−B2  ∗  (X − 1))) because discriminant functions, calculated separately for B3 and B4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both. PMID:22745911

Analysis of the learning curve for peroral endoscopic myotomy for esophageal achalasia: Single-center, two-operator experience.

Science.gov (United States)

Lv, Houning; Zhao, Ningning; Zheng, Zhongqing; Wang, Tao; Yang, Fang; Jiang, Xihui; Lin, Lin; Sun, Chao; Wang, Bangmao

2017-05-01

Peroral endoscopic myotomy (POEM) has emerged as an advanced technique for the treatment of achalasia, and defining the learning curve is mandatory. From August 2011 to June 2014, two operators in our institution (A&B) carried out POEM on 35 and 33 consecutive patients, respectively. Moving average and cumulative sum (CUSUM) methods were used to analyze the POEM learning curve for corrected operative time (cOT), referring to duration of per centimeter myotomy. Additionally, perioperative outcomes were compared among distinct learning curve phases. Using the moving average method, cOT reached a plateau at the 29th case and at the 24th case for operators A and B, respectively. CUSUM analysis identified three phases: initial learning period (Phase 1), efficiency period (Phase 2) and mastery period (Phase 3). The relatively smooth state in the CUSUM graph occurred at the 26th case and at the 24th case for operators A and B, respectively. Mean cOT of distinct phases for operator A were 8.32, 5.20 and 3.97 min, whereas they were 5.99, 3.06 and 3.75 min for operator B, respectively. Eckardt score and lower esophageal sphincter pressure significantly decreased during the 1-year follow-up period. Data were comparable regarding patient characteristics and perioperative outcomes. This single-center study demonstrated that expert endoscopists with experience in esophageal endoscopic submucosal dissection reached a plateau in learning of POEM after approximately 25 cases. © 2016 Japan Gastroenterological Endoscopy Society.

Does Prior Laparoscopic and Open Surgery Experience Have Any Impact on Learning Curve in Transition to Robotic Surgery?

Directory of Open Access Journals (Sweden)

Cüneyt Adayener

2016-12-01

Full Text Available It has been 15 years since the Food And Drug Administration approved the Da Vinci® robotic surgery system. Robotic applications are being used extensively in urology, particularly in radical prostatectomy. Like all high-tech products, this system also has a high cost and a steep learning curve, therefore, preventing it from becoming widespread. There are various studies on the effect of open surgery or laparoscopy experience on the learning curve of robotic surgery. Analyzing these interactions well will provide valuable information on making the training period of robotic system more efficient.

Music Learning with Long Short Term Memory Networks

OpenAIRE

Colombo, Florian François

2015-01-01

Humans are able to learn and compose complex, yet beautiful, pieces of music as seen in e.g. the highly complicated works of J.S. Bach. However, how our brain is able to store and produce these very long temporal sequences is still an open question. Long short-term memory (LSTM) artificial neural networks have been shown to be efficient in sequence learning tasks thanks to their inherent ability to bridge long time lags between input events and their target signals. Here, I investigate the po...

The Development of Automaticity in Short-Term Memory Search: Item-Response Learning and Category Learning

Science.gov (United States)

Cao, Rui; Nosofsky, Robert M.; Shiffrin, Richard M.

2017-01-01

In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across…

Short Project-Based Learning with MATLAB Applications to Support the Learning of Video-Image Processing

Science.gov (United States)

Gil, Pablo

2017-10-01

University courses concerning Computer Vision and Image Processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the development, implementation and assessment of a short project-based engineering course with MATLAB applications Multimedia Engineering being taken by Bachelor's degree students. The principal goal of all course lectures and hands-on laboratory activities was for the students to not only acquire image-specific technical skills but also a general knowledge of data analysis so as to locate phenomena in pixel regions of images and video frames. This would hopefully enable the students to develop skills regarding the implementation of the filters, operators, methods and techniques used for image processing and computer vision software libraries. Our teaching-learning process thus permits the accomplishment of knowledge assimilation, student motivation and skill development through the use of a continuous evaluation strategy to solve practical and real problems by means of short projects designed using MATLAB applications. Project-based learning is not new. This approach has been used in STEM learning in recent decades. But there are many types of projects. The aim of the current study is to analyse the efficacy of short projects as a learning tool when compared to long projects during which the students work with more independence. This work additionally presents the impact of different types of activities, and not only short projects, on students' overall results in this subject. Moreover, a statistical study has allowed the author to suggest a link between the students' success ratio and the type of content covered and activities completed on the course. The results described in this paper show that those students who took part

Designing learning curves for carbon capture based on chemical absorption according to the minimum work of separation

International Nuclear Information System (INIS)

Rochedo, Pedro R.R.; Szklo, Alexandre

2013-01-01

Highlights: • This work defines the minimum work of separation (MWS) for a capture process. • Findings of the analysis indicated a MWS of 0.158 GJ/t for post-combustion. • A review of commercially available processes based on chemical absorption was made. • A review of learning models was conducted, with the addition on a novel model. • A learning curve for post-combustion carbon capture was successfully designed. - Abstract: Carbon capture is one of the most important alternatives for mitigating greenhouse gas emissions in energy facilities. The post-combustion route based on chemical absorption with amine solvents is the most feasible alternative for the short term. However, this route implies in huge energy penalties, mainly related to the solvent regeneration. By defining the minimum work of separation (MWS), this study estimated the minimum energy required to capture the CO 2 emitted by coal-fired thermal power plants. Then, by evaluating solvents and processes and comparing it to the MWS, it proposes the learning model with the best fit for the post-combustion chemical absorption of CO 2 . Learning models are based on earnings from experience, which can include the intensity of research and development. In this study, three models are tested: Wright, DeJong and D and L. Findings of the thermochemical analysis indicated a MWS of 0.158 GJ/t for post-combustion. Conventional solvents currently present an energy penalty eight times the MWS. By using the MWS as a constraint, this study found that the D and L provided the best fit to the available data of chemical solvents and absorption plants. The learning rate determined through this model is very similar to the ones found in the literature

Learning curve of hysteroscopic placement of tubal sterilization microinserts in 15 gynecologists in the Netherlands.

Science.gov (United States)

Janse, Juliënne A; Pattij, Thyrza O S; Eijkemans, Marinus J C; Broekmans, Frank J; Veersema, Sebastiaan; Schreuder, Henk W R

2013-09-01

To evaluate the learning curve of hysteroscopic placement of tubal sterilization microinserts by gynecologists in the Netherlands. Prospective multicenter study (Canadian Task Force II-2). Ten community (teaching) hospitals in the Netherlands. A total of 631 women who underwent permanent sterilization by tubal microinserts. Hysteroscopic placement of tubal sterilization microinserts performed by 15 gynecologists experienced in performing operative hysteroscopy, starting from their very first placement. Effect of increasing experience in time on procedure time, pain score, successful bilateral placement, and complications. Bilateral successful placement with confirmation of adequate positioning at follow-up evaluation was achieved in 480 (76.1%) patients at first attempt and in 44 (7.0%) at second attempt. Median procedure time was 8.0 minutes (range: 3-40), and 31 (4.9%) patients were lost to follow-up evaluation. Gravidity showed to be a confounding factor and was consequently adjusted for. A learning curve was seen in a statistically significant decrease of procedure time with increasing experience. The decrease in procedure time extended to 11 to 15 cases and was followed by a plateau phase of the subsequent 60 cases. In contrast, pain scores, successful placement, and complication rate appeared not to improve with increasing experience. A learning curve for hysteroscopic tubal sterilization was seen for procedure time, but successful placement, pain score, and complication rate were not clearly influenced by increasing experience. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

In the Way of Peacemaker Guide Curve between Water Supply and Flood Control for Short Term Reservoir Operation

Science.gov (United States)

Uysal, G.; Sensoy, A.; Yavuz, O.; Sorman, A. A.; Gezgin, T.

2012-04-01

Effective management of a controlled reservoir system where it involves multiple and sometimes conflicting objectives is a complex problem especially in real time operations. Yuvacık Dam Reservoir, located in the Marmara region of Turkey, is built to supply annual demand of 142 hm3 water for Kocaeli city requires such a complex management strategy since it has relatively small (51 hm3) effective capacity. On the other hand, the drainage basin is fed by both rainfall and snowmelt since the elevation ranges between 80 - 1548 m. Excessive water must be stored behind the radial gates between February and May in terms of sustainability especially for summer and autumn periods. Moreover, the downstream channel physical conditions constraint the spillway releases up to 100 m3/s although the spillway is large enough to handle major floods. Thus, this situation makes short term release decisions the challenging task. Long term water supply curves, based on historical inflows and annual water demand, are in conflict with flood regulation (control) levels, based on flood attenuation and routing curves, for this reservoir. A guide curve, that is generated using both water supply and flood control of downstream channel, generally corresponds to upper elevation of conservation pool for simulation of a reservoir. However, sometimes current operation necessitates exceeding this target elevation. Since guide curves can be developed as a function of external variables, the water potential of a basin can be an indicator to explain current conditions and decide on the further strategies. Besides, releases with respect to guide curve are managed and restricted by user-defined rules. Although the managers operate the reservoir due to several variable conditions and predictions, still the simulation model using variable guide curve is an urgent need to test alternatives quickly. To that end, using HEC-ResSim, the several variable guide curves are defined to meet the requirements by

The contribution of phonological short-term memory to artificial grammar learning.

Science.gov (United States)

Andrade, Jackie; Baddeley, Alan

2011-05-01

Three experiments investigated the contribution of phonological short-term memory (STM) to grammar learning by manipulating rehearsal during study of an auditory artificial grammar made up from a vocabulary of spoken Mandarin syllables. Experiment 1 showed that concurrent, irrelevant articulation impaired grammar learning compared with a nonverbal control task. Experiment 2 replicated and extended this finding, showing that repeating the grammatical strings at study improved grammar learning compared with suppressing rehearsal or remaining silent during learning. Experiment 3 found no effects of rehearsal on grammar learning once participants had learned the component syllables. The findings suggest that phonological STM aids artificial grammar learning via effects on vocabulary learning.

Automated Blazar Light Curves Using Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Johnson, Spencer James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-07-27

This presentation describes a problem and methodology pertaining to automated blazar light curves. Namely, optical variability patterns for blazars require the construction of light curves and in order to generate the light curves, data must be filtered before processing to ensure quality.

[Evaluation of the learning curve of residents in localizing a phantom target with ultrasonography].

Science.gov (United States)

Dessieux, T; Estebe, J-P; Bloc, S; Mercadal, L; Ecoffey, C

2008-10-01

Few information are available regarding the learning curve in ultrasonography and even less for ultrasound-guided regional anesthesia. This study aimed to evaluate in a training program the learning curve on a phantom of 12 residents novice in ultrasonography. Twelve trainees inexperienced in ultrasonography were given introductory training consisting of didactic formation on the various components of the portable ultrasound machine (i.e. on/off button, gain, depth, resolution, and image storage). Then, students performed three trials, in two sets of increased difficulty, at executing these predefined tasks: adjustments of the machine, then localization of a small plastic piece introduced into roasting pork (3 cm below the surface). At the end of the evaluation, the residents were asked to insert a 22 G needle into an exact predetermined target (i.e. point of fascia intersection). The progression of the needle was continuously controlled by ultrasound visualization using injection of a small volume of water (needle perpendicular to the longitudinal plane of the ultrasound beam). Two groups of two different examiners evaluated for each three trials the skill of the residents (quality, time to perform the machine adjustments, to localize the plastic target, and to hydrolocalize, and volume used for hydrolocalization). After each trial, residents evaluated their performance using a difficulty scale (0: easy to 10: difficult). All residents performed the adjustments from the last trial of each set, with a learning curve observed in terms of duration. Localization of the plastic piece was achieved by all residents at the 6th trial, with a shorter duration of localization. Hydrolocalization was achieved after the 4th trial by all subjects. Difficulty scale was correlated to the number of trials. All these results were independent of the experience of residents in regional anesthesia. Four trials were necessary to adjust correctly the machine, to localize a target, and to

Utility of Interobserver Agreement Statistics in Establishing Radiology Resident Learning Curves During Self-directed Radiologic Anatomy Training.

Science.gov (United States)

Tureli, Derya; Altas, Hilal; Cengic, Ismet; Ekinci, Gazanfer; Baltacioglu, Feyyaz

2015-10-01

The aim of the study was to ascertain the learning curves for the radiology residents when first introduced to an anatomic structure in magnetic resonance images (MRI) to which they have not been previously exposed to. The iliolumbar ligament is a good marker for testing learning curves of radiology residents because the ligament is not part of a routine lumbar MRI reporting and has high variability in detection. Four radiologists, three residents without previous training and one mentor, studied standard axial T1- and T2-weighted images of routine lumbar MRI examinations. Radiologists had to define iliolumbar ligament while blinded to each other's findings. Interobserver agreement analyses, namely Cohen and Fleiss κ statistics, were performed for groups of 20 cases to evaluate the self-learning curve of radiology residents. Mean κ values of resident-mentor pairs were 0.431, 0.608, 0.604, 0.826, and 0.963 in the analysis of successive groups (P 0.8). Therefore, a junior radiology resident can obtain enough experience in identifying a rather ambiguous anatomic structure in routine MRI after a brief instruction of a few minutes by a mentor and studying approximately 80 cases by oneself. Implementing this methodology will help radiology educators obtain more concrete ideas on the optimal time and effort required for supported self-directed visual learning processes in resident education. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Optimizing area under the ROC curve using semi-supervised learning.

Science.gov (United States)

Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M

2015-01-01

Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.

Development of a precipitation-area curve for warning criteria of short-duration flash flood

Science.gov (United States)

Bae, Deg-Hyo; Lee, Moon-Hwan; Moon, Sung-Keun

2018-01-01

This paper presents quantitative criteria for flash flood warning that can be used to rapidly assess flash flood occurrence based on only rainfall estimates. This study was conducted for 200 small mountainous sub-catchments of the Han River basin in South Korea because South Korea has recently suffered many flash flood events. The quantitative criteria are calculated based on flash flood guidance (FFG), which is defined as the depth of rainfall of a given duration required to cause frequent flooding (1-2-year return period) at the outlet of a small stream basin and is estimated using threshold runoff (TR) and antecedent soil moisture conditions in all sub-basins. The soil moisture conditions were estimated during the flooding season, i.e., July, August and September, over 7 years (2002-2009) using the Sejong University Rainfall Runoff (SURR) model. A ROC (receiver operating characteristic) analysis was used to obtain optimum rainfall values and a generalized precipitation-area (P-A) curve was developed for flash flood warning thresholds. The threshold function was derived as a P-A curve because the precipitation threshold with a short duration is more closely related to basin area than any other variables. For a brief description of the P-A curve, generalized thresholds for flash flood warnings can be suggested for rainfall rates of 42, 32 and 20 mm h-1 in sub-basins with areas of 22-40, 40-100 and > 100 km2, respectively. The proposed P-A curve was validated based on observed flash flood events in different sub-basins. Flash flood occurrences were captured for 9 out of 12 events. This result can be used instead of FFG to identify brief flash flood (less than 1 h), and it can provide warning information to decision-makers or citizens that is relatively simple, clear and immediate.

Learning from uncertain curves

DEFF Research Database (Denmark)

Mallasto, Anton; Feragen, Aasa

2017-01-01

We introduce a novel framework for statistical analysis of populations of nondegenerate Gaussian processes (GPs), which are natural representations of uncertain curves. This allows inherent variation or uncertainty in function-valued data to be properly incorporated in the population analysis. Us...

Robust short-term memory without synaptic learning.

Directory of Open Access Journals (Sweden)

Samuel Johnson

Full Text Available Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds. The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust short-term memory without synaptic learning.

Science.gov (United States)

Johnson, Samuel; Marro, J; Torres, Joaquín J

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust Short-Term Memory without Synaptic Learning

Science.gov (United States)

Johnson, Samuel; Marro, J.; Torres, Joaquín J.

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

Learning Curve Characteristics for Caesarean Section Among Associate Clinicians : A Prospective Study from Sierra Leone

NARCIS (Netherlands)

Waalewijn, B.P.; van Duinen, A.; Koroma, A. P.; Rijken, M. J.; Elhassein, M.; Bolkan, H. A.

2017-01-01

Background: In response to the high maternal mortality ratio, Sierra Leone has adopted an associate clinician postgraduate surgical task-sharing training programme. Little is known about learning curve characteristics for caesarean sections among associate clinicians. The aim of this study is to

Virtual reality cataract surgery training: learning curves and concurrent validity.

Science.gov (United States)

Selvander, Madeleine; Åsman, Peter

2012-08-01

To investigate initial learning curves on a virtual reality (VR) eye surgery simulator and whether achieved skills are transferable between tasks. Thirty-five medical students were randomized to complete ten iterations on either the VR Caspulorhexis module (group A) or the Cataract navigation training module (group B) and then two iterations on the other module. Learning curves were compared between groups. The second Capsulorhexis video was saved and evaluated with the performance rating tool Objective Structured Assessment of Cataract Surgical Skill (OSACSS). The students' stereoacuity was examined. Both groups demonstrated significant improvements in performance over the 10 iterations: group A for all parameters analysed including score (p < 0.0001), time (p < 0.0001) and corneal damage (p = 0.0003), group B for time (p < 0.0001), corneal damage (p < 0.0001) but not for score (p = 0.752). Training on one module did not improve performance on the other. Capsulorhexis score correlated significantly with evaluation of the videos using the OSACSS performance rating tool. For stereoacuity < and ≥120 seconds of arc, sum of both modules' second iteration score was 73.5 and 41.0, respectively (p = 0.062). An initial rapid improvement in performance on a simulator with repeated practice was shown. For capsulorhexis, 10 iterations with only simulator feedback are not enough to reach a plateau for overall score. Skills transfer between modules was not found suggesting benefits from training on both modules. Stereoacuity may be of importance in the recruitment and training of new cataract surgeons. Additional studies are needed to investigate this further. Concurrent validity was found for Capsulorhexis module. © 2010 The Authors. Acta Ophthalmologica © 2010 Acta Ophthalmologica Scandinavica Foundation.

Learning curves of theta/beta neurofeedback in children with ADHD.

Science.gov (United States)

Janssen, Tieme W P; Bink, Marleen; Weeda, Wouter D; Geladé, Katleen; van Mourik, Rosa; Maras, Athanasios; Oosterlaan, Jaap

2017-05-01

Neurofeedback is widely applied as non-pharmacological intervention aimed at reducing symptoms of ADHD, even though efficacy has not been unequivocally established. Neuronal changes during the neurofeedback intervention that resemble learning can provide crucial evidence for the feasibility and specificity of this intervention. A total of 38 children (aged between 7 and 13 years) with a DSM-IV-TR diagnosis of ADHD, completed on average 29 sessions of theta (4-8 Hz)/beta (13-20 Hz) neurofeedback training. Dependent variables included training-related measures as well as theta and beta power during baseline and training runs for each session. Learning effects were analyzed both within and between sessions. To further specify findings, individual learning curves were explored and correlated with behavioral changes in ADHD symptoms. Over the course of the training, there was a linear increase in participants' mean training level, highest obtained training level and the number of earned credits (range b = 0.059, -0.750, p neurofeedback, although a lack of behavioral correlates may indicate insufficient transfer to daily functioning, or to confounding reinforcement of electromyographic activity. This trial is registered at the US National Institutes of Health (ClinicalTrials.gov, ref. no: NCT01363544); https://clinicaltrials.gov/show/NCT01363544 .

Descemet Membrane Endothelial Keratoplasty Learning Curve for Graft Preparation in an Eye Bank Using 645 Donor Corneas.

Science.gov (United States)

Parekh, Mohit; Ruzza, Alessandro; Romano, Vito; Favaro, Elisa; Baruzzo, Mattia; Salvalaio, Gianni; Grassetto, Andrea; Ferrari, Stefano; Ponzin, Diego

2018-03-01

To investigate the learning curve of Descemet membrane endothelial keratoplasty (DMEK) graft preparation in an eye bank. Four operators prepared 645 DMEK grafts using the stripping technique between 2014 and 2017 at the Veneto Eye Bank Foundation, Italy. Endothelial cell loss (ECL) and tissue wastage were recorded retrospectively after DMEK preparation and correlated with the number of tissues prepared each year by each operator. On average, our operators performed 1 donor preparation a week over the course of this study. Only donors older than 60 years were used in this study, and approximately 10% of donors had diabetes. The Wilcoxon test for paired data and 1-way ANOVA were used for checking statistical significance with the Tukey test as post hoc analysis. P 0.05). There is a learning curve for DMEK graft preparation. ECL and tissue wastage can be reduced with practice and skills. However, each operator may be limited to his or her own learning capability.

Innovation and learning curves. Report on knowledge questions of the Working Group Energy and Climate

International Nuclear Information System (INIS)

Schoots, K.

2010-05-01

This report has been written on account of knowledge questions formulated by the Working Group Energy and Climate. This Working Group has been established in the framework of the Broad Reconsideration of Dutch government policy caused by the economic crisis of 2008-2009. Its task is to investigate the possibilities for a structural reduction of government spending by 20% on sustainable energy, energy saving and fiscal advantages carrying non-sustainable incentives. Apart from that, spending on policies aimed at mitigating climate change are scrutinized. In connection with this task, the working group has formulated knowledge questions which refer to cost effectiveness and possibilities for target achievement, possibilities within the European Renewables Directive and learning curves and innovation. This report addresses the latter two themes: learning curves and innovation. The selection of technologies assessed is not all-embracing, but based on the technologies within the SDE regulation (Dutch regulation on support for sustainable energy) supplemented by some promising innovations. [nl

Transforaminal Lumbar Interbody Fusion with Rigid Interspinous Process Fixation: A Learning Curve Analysis of a Surgeon Team's First 74 Cases.

Science.gov (United States)

Doherty, Patrick; Welch, Arthur; Tharpe, Jason; Moore, Camille; Ferry, Chris

2017-05-30

Studies have shown that a significant learning curve may be associated with adopting minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) with bilateral pedicle screw fixation (BPSF). Accordingly, several hybrid TLIF techniques have been proposed as surrogates to the accepted BPSF technique, asserting that less/fewer fixation(s) or less disruptive fixation may decrease the learning curve while still maintaining the minimally disruptive benefits. TLIF with interspinous process fixation (ISPF) is one such surrogate procedure. However, despite perceived ease of adaptability given the favorable proximity of the spinous processes, no evidence exists demonstrating whether or not the technique may possess its own inherent learning curve. The purpose of this study was to determine whether an intraoperative learning curve for one- and two-level TLIF + ISPF may exist for a single lead surgeon. Seventy-four consecutive patients who received one- or two-Level TLIF with rigid ISPF by a single lead surgeon were retrospectively reviewed. It was the first TLIF + ISPF case series for the lead surgeon. Intraoperative blood loss (EBL), hospitalization length-of-stay (LOS), fluoroscopy time, and postoperative complications were collected. EBL, LOS, and fluoroscopy time were modeled as a function of case number using multiple linear regression methods. A change point was included in each model to allow the trajectory of the outcomes to change during the duration of the case series. These change points were determined using profile likelihood methods. Models were fit using the maximum likelihood estimates for the change points. Age, sex, body mass index (BMI), and the number of treated levels were included as covariates. EBL, LOS, and fluoroscopy time did not significantly differ by age, sex, or BMI (p ≥ 0.12). Only EBL differed significantly by the number of levels (p = 0.026). The case number was not a significant predictor of EBL, LOS, or fluoroscopy time (p ≥ 0

Hebb learning, verbal short-term memory, and the acquisition of phonological forms in children.

Science.gov (United States)

Mosse, Emma K; Jarrold, Christopher

2008-04-01

Recent work using the Hebb effect as a marker for implicit long-term acquisition of serial order has demonstrated a functional equivalence across verbal and visuospatial short-term memory. The current study extends this observation to a sample of five- to six-year-olds using verbal and spatial immediate serial recall and also correlates the magnitude of Hebb learning with explicit measures of word and nonword paired-associate learning. Comparable Hebb effects were observed in both domains, but only nonword learning was significantly related to the magnitude of Hebb learning. Nonword learning was also independently related to individuals' general level of verbal serial recall. This suggests that vocabulary acquisition depends on both a domain-specific short-term memory system and a domain-general process of learning through repetition.

Learning curves and long-term outcome of simulation-based thoracentesis training for medical students

Science.gov (United States)

2011-01-01

Background Simulation-based medical education has been widely used in medical skills training; however, the effectiveness and long-term outcome of simulation-based training in thoracentesis requires further investigation. The purpose of this study was to assess the learning curve of simulation-based thoracentesis training, study skills retention and transfer of knowledge to a clinical setting following simulation-based education intervention in thoracentesis procedures. Methods Fifty-two medical students were enrolled in this study. Each participant performed five supervised trials on the simulator. Participant's performance was assessed by performance score (PS), procedure time (PT), and participant's confidence (PC). Learning curves for each variable were generated. Long-term outcome of the training was measured by the retesting and clinical performance evaluation 6 months and 1 year, respectively, after initial training on the simulator. Results Significant improvements in PS, PT, and PC were noted among the first 3 to 4 test trials (p 0.05). Clinical competency in thoracentesis was improved in participants who received simulation training relative to that of first year medical residents without such experience (p simulation-based thoracentesis training can significantly improve an individual's performance. The saturation of learning from the simulator can be achieved after four practice sessions. Simulation-based training can assist in long-term retention of skills and can be partially transferred to clinical practice. PMID:21696584

Retrospective analysis of the learning curve associated with laparoscopic ovariectomy in dogs and associated perioperative complication rates.

Science.gov (United States)

Pope, Juliet Frances Anne; Knowles, Toby Grahame

2014-08-01

To assess the learning curve associated with laparoscopic ovariectomy (LOE) in 618 dogs and to report perioperative complication rates. Case series. Dogs (n = 618). Data retrieved from the medical records of bitches admitted for LOE over 42 months included date of surgery, breed, weight (kg), age (months), surgeon, suture material used, intraoperative complications and postoperative complications. Each LOE was defined as "successful" or "unsuccessful" by the absence or presence of an intraoperative complication and "failure" rate described using a CUSUM technique. Follow-up time ranged from 152 to 1,435 days (median, 737 days). Intraoperative complications occurred in 10 dogs (1.6%) and included: splenic laceration (6 dogs; 1%), urinary bladder perforation (3 dogs; 0.5%), and subcutaneous emphysema (1 dog; 0.2%). Postoperative complications occurred in 99 dogs (16%) and included: incisional inflammation treated with antibiotics (87 dogs [14%]; 96/1,854 incisions; 5.1%), incisional seroma (5 dogs [0.8%]; 5/1,854 incisions, 0.3%), incisional hernia (4 dogs [0.6%]; 4/1,854 incisions, 0.2%), and ovarian remnant syndrome (3 dogs; 0.5%). CUSUM charts indicated an initial "learning curve" of ∼80 LOE. LOE is a technique with an initial learning curve but once surgical proficiency is reached after ∼80 procedures then intraoperative complication rates associated with the procedure can be low. © Copyright 2014 by The American College of Veterinary Surgeons.

Enucleation ratio efficacy might be a better predictor to assess learning curve of holmium laser enucleation of the prostate

Directory of Open Access Journals (Sweden)

Chang Wook Jeong

2012-06-01

Full Text Available PURPOSE: To appraise the evaluation methods for learning curve and to analyze the non-mentor-aided learning curve and early complications following the holmium laser enucleation of the prostate. MATERIALS AND METHODS:One-hundred and forty (n=140 consecutive patients who underwent HoLEP from July 2008 to July 2010 by a single surgeon (SJO were enrolled. Perioperative clinical variables, including enucleation time, morcellation time, enucleation ratio (enucleation weight/transitional zone volume, enucleation efficacy (enucleated weight/enucleation time, enucleation ratio efficacy (enucleation ratio/enucleation time, and early complication rate were analyzed. RESULTS: Mean prostate volume was 62.7 mL (range 21-162 and preoperative International Prostate Symptom Score (IPSS was 19.0 (4-35. Mean enucleation time and morcellation time were 49.9±23.8 (S.D. min and 11.0±9.7 min, respectively. Median duration of postoperative indwelling catheter was 1 (1-7 day and median hospital stay was 1 (1-6 day. There were a total of 31 surgery-related complications in 27 patients (19.3%, and all were manageable. There was an increasing trend of enucleation efficacy in the first 50 cases. However, enucleation efficacy was linearly correlated with the prostate size (correlation coefficients, R=0.701, p<0.001. But, enucleation ratio efficacy could eliminate the confounding effect of the prostate size (R=-0.101, p=0.233. The plateau of enucleation ratio efficacy was reached around the twenty-fifth case. CONCLUSIONS: Our results demonstrated that the operative learning curve plateau is reached after about 25 cases. We propose that a more appropriate parameter for estimating the operative learning curve is enucleation ratio efficacy, rather than enucleation efficacy.

[Individual learning curve for radical robot-assisted prostatectomy based on the example of three professionals working in one clinic].

Science.gov (United States)

Rasner, P I; Pushkar', D Iu; Kolontarev, K B; Kotenkov, D V

2014-01-01

The appearance of new surgical technique always requires evaluation of its effectiveness and ease of acquisition. A comparative study of the results of the first three series of successive robot-assisted radical prostatectomy (RARP) performed on at time by three surgeons, was conducted. The series consisted of 40 procedures, and were divided into 4 groups of 10 operations for the analysis. When comparing data, statistically significant improvement of intra- and postoperative performance in each series was revealed, with increase in the number of operations performed, and in each subsequent series compared with the preceding one. We recommend to perform the planned conversion at the first operation. In our study, previous laparoscopic experience did not provide any significant advantages in the acquisition of robot-assisted technology. To characterize the individual learning curve, we recommend the use of the number of operations that the surgeon looked in the life-surgery regimen and/or in which he participated as an assistant before his own surgical activity, as well as the indicator "technical defect". In addition to the term "individual learning curve", we propose to introduce the terms "surgeon's individual training phase", and "clinic's learning curve".

Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling

International Nuclear Information System (INIS)

Kahouli, Sondes

2011-01-01

This paper studies the effects of returns to scale, technological learning, i.e. learning-by-doing and learning-by-searching, and uranium price on the prospects of nuclear cost decrease. We use an extended learning curve specification, named multiple factors learning curve (MFLC). In a first stage, we estimate a single MFLC. In a second stage, we estimate the MFLC under the framework of simultaneous system of equations which takes into account the uranium supply and demand. This permits not only to enhance the reliability of the estimation by incorporating the uranium price formation mechanisms in the MFLC via the price variable, but also to give preliminary insights about uranium supply and demand behaviors and the associated effects on the nuclear expansion. Results point out that the nuclear cost has important prospects for decrease via capacity expansion, i.e. learning-by-doing effects. In contrast, they show that the learning-by-searching as well as the scale effects have a limited effect on the cost decrease prospects. Conversely, results also show that uranium price exerts a positive and significant effect on nuclear cost, implying that when the uranium price increases, the nuclear power generation cost decreases. Since uranium is characterized by important physical availability, and since it represents only a minor part in the total nuclear cost, we consider that in a context of increasing demand for nuclear energy the latter result can be explained by the fact that the positive learning effects on the cost of nuclear act in a way to dissipate the negative ones that an increase in uranium price may exert. Further, results give evidence of important inertia in the supply and demand sides as well as evidence of slow correlation between the uranium market and oil market which may limit the inter-fuels substituability effects, that is, nuclear capacity expansion and associated learning-by-doing benefits. - Highlights: → We study the prospects of nuclear cost

Provincial carbon intensity abatement potential estimation in China: A PSO–GA-optimized multi-factor environmental learning curve method

International Nuclear Information System (INIS)

Yu, Shiwei; Zhang, Junjie; Zheng, Shuhong; Sun, Han

2015-01-01

This study aims to estimate carbon intensity abatement potential in China at the regional level by proposing a particle swarm optimization–genetic algorithm (PSO–GA) multivariate environmental learning curve estimation method. The model uses two independent variables, namely, per capita gross domestic product (GDP) and the proportion of the tertiary industry in GDP, to construct carbon intensity learning curves (CILCs), i.e., CO 2 emissions per unit of GDP, of 30 provinces in China. Instead of the traditional ordinary least squares (OLS) method, a PSO–GA intelligent optimization algorithm is used to optimize the coefficients of a learning curve. The carbon intensity abatement potentials of the 30 Chinese provinces are estimated via PSO–GA under the business-as-usual scenario. The estimation reveals the following results. (1) For most provinces, the abatement potentials from improving a unit of the proportion of the tertiary industry in GDP are higher than the potentials from raising a unit of per capita GDP. (2) The average potential of the 30 provinces in 2020 will be 37.6% based on the emission's level of 2005. The potentials of Jiangsu, Tianjin, Shandong, Beijing, and Heilongjiang are over 60%. Ningxia is the only province without intensity abatement potential. (3) The total carbon intensity in China weighted by the GDP shares of the 30 provinces will decline by 39.4% in 2020 compared with that in 2005. This intensity cannot achieve the 40%–45% carbon intensity reduction target set by the Chinese government. Additional mitigation policies should be developed to uncover the potentials of Ningxia and Inner Mongolia. In addition, the simulation accuracy of the CILCs optimized by PSO–GA is higher than that of the CILCs optimized by the traditional OLS method. - Highlights: • A PSO–GA-optimized multi-factor environmental learning curve method is proposed. • The carbon intensity abatement potentials of the 30 Chinese provinces are estimated by

Intact Acquisition and Short-Term Retention of Non-Motor Procedural Learning in Parkinson's Disease.

Directory of Open Access Journals (Sweden)

Muriel T N Panouillères

Full Text Available Procedural learning is a form of memory where people implicitly acquire a skill through repeated practice. People with Parkinson's disease (PD have been found to acquire motor adaptation, a form of motor procedural learning, similarly to healthy older adults but they have deficits in long-term retention. A similar pattern of normal learning on initial exposure with a deficit in retention seen on subsequent days has also been seen in mirror-reading, a form of non-motor procedural learning. It is a well-studied fact that disrupting sleep will impair the consolidation of procedural memories. Given the prevalence of sleep disturbances in PD, the lack of retention on following days seen in these studies could simply be a side effect of this well-known symptom of PD. Because of this, we wondered whether people with PD would present with deficits in the short-term retention of a non-motor procedural learning task, when the test of retention was done the same day as the initial exposure. The aim of the present study was then to investigate acquisition and retention in the immediate short term of cognitive procedural learning using the mirror-reading task in people with PD. This task involved two conditions: one where triads of mirror-inverted words were always new that allowed assessing the learning of mirror-reading skill and another one where some of the triads were presented repeatedly during the experiment that allowed assessing the word-specific learning. People with PD both ON and OFF their normal medication were compared to healthy older adults and young adults. Participants were re-tested 50 minutes break after initial exposure to probe for short-term retention. The results of this study show that all groups of participants acquired and retained the two skills (mirror-reading and word-specific similarly. These results suggest that neither healthy ageing nor the degeneration within the basal ganglia that occurs in PD does affect the mechanisms

Simultaneous development of laparoscopy and robotics provides acceptable perioperative outcomes and shows robotics to have a faster learning curve and to be overall faster in rectal cancer surgery: analysis of novice MIS surgeon learning curves.

Science.gov (United States)

Melich, George; Hong, Young Ki; Kim, Jieun; Hur, Hyuk; Baik, Seung Hyuk; Kim, Nam Kyu; Sender Liberman, A; Min, Byung Soh

2015-03-01

Laparoscopy offers some evidence of benefit compared to open rectal surgery. Robotic rectal surgery is evolving into an accepted approach. The objective was to analyze and compare laparoscopic and robotic rectal surgery learning curves with respect to operative times and perioperative outcomes for a novice minimally invasive colorectal surgeon. One hundred and six laparoscopic and 92 robotic LAR rectal surgery cases were analyzed. All surgeries were performed by a surgeon who was primarily trained in open rectal surgery. Patient characteristics and perioperative outcomes were analyzed. Operative time and CUSUM plots were used for evaluating the learning curve for laparoscopic versus robotic LAR. Laparoscopic versus robotic LAR outcomes feature initial group operative times of 308 (291-325) min versus 397 (373-420) min and last group times of 220 (212-229) min versus 204 (196-211) min-reversed in favor of robotics; major complications of 4.7 versus 6.5 % (NS), resection margin involvement of 2.8 versus 4.4 % (NS), conversion rate of 3.8 versus 1.1 (NS), lymph node harvest of 16.3 versus 17.2 (NS), and estimated blood loss of 231 versus 201 cc (NS). Due to faster learning curves for extracorporeal phase and total mesorectal excision phase, the robotic surgery was observed to be faster than laparoscopic surgery after the initial 41 cases. CUSUM plots demonstrate acceptable perioperative surgical outcomes from the beginning of the study. Initial robotic operative times improved with practice rapidly and eventually became faster than those for laparoscopy. Developing both laparoscopic and robotic skills simultaneously can provide acceptable perioperative outcomes in rectal surgery. It might be suggested that in the current milieu of clashing interests between evolving technology and economic constrains, there might be advantages in embracing both approaches.

Unsupervised learning in neural networks with short range synapses

Science.gov (United States)

Brunnet, L. G.; Agnes, E. J.; Mizusaki, B. E. P.; Erichsen, R., Jr.

2013-01-01

Different areas of the brain are involved in specific aspects of the information being processed both in learning and in memory formation. For example, the hippocampus is important in the consolidation of information from short-term memory to long-term memory, while emotional memory seems to be dealt by the amygdala. On the microscopic scale the underlying structures in these areas differ in the kind of neurons involved, in their connectivity, or in their clustering degree but, at this level, learning and memory are attributed to neuronal synapses mediated by longterm potentiation and long-term depression. In this work we explore the properties of a short range synaptic connection network, a nearest neighbor lattice composed mostly by excitatory neurons and a fraction of inhibitory ones. The mechanism of synaptic modification responsible for the emergence of memory is Spike-Timing-Dependent Plasticity (STDP), a Hebbian-like rule, where potentiation/depression is acquired when causal/non-causal spikes happen in a synapse involving two neurons. The system is intended to store and recognize memories associated to spatial external inputs presented as simple geometrical forms. The synaptic modifications are continuously applied to excitatory connections, including a homeostasis rule and STDP. In this work we explore the different scenarios under which a network with short range connections can accomplish the task of storing and recognizing simple connected patterns.

Assessing the impact of windfarms - the learning curve in Cornwall

International Nuclear Information System (INIS)

Hull, A.

1998-01-01

This paper uses windfarm application decisions in Cornwall between 1989 and 1995 to illustrate the learning curve of planners in assessing appropriate windfarm locations, and in particular how the process of knowledge construction is constantly reviewed and modified in the light of experience and circumstance. One of the accepted purposes of Environmental Impact Assessment is to predict the possible effects, both beneficial and adverse, of the development on the environment. In practice what is beneficial and what is adverse can be a matter of dispute. The paper draws out the role of the planning system in assessing what is problematic or benign, and the practical strategies and procedures used to assess and control the environmental impacts of wind energy schemes. (Author)

Short communication Estimation of growth curve parameters in ...

African Journals Online (AJOL)

ikeskin

The shape of growth curves has been reported to vary according to the species of .... a,b,c The means within columns with different superscripts are significantly .... J. Anim. Sci. 84, 2642-2654. The South African Journal of Animal Science is ...

Using a high-fidelity patient simulator with first-year medical students to facilitate learning of cardiovascular function curves.

Science.gov (United States)

Harris, David M; Ryan, Kathleen; Rabuck, Cynthia

2012-09-01

Students are relying on technology for learning more than ever, and educators need to adapt to facilitate student learning. High-fidelity patient simulators (HFPS) are usually reserved for the clinical years of medical education and are geared to improve clinical decision skills, teamwork, and patient safety. Finding ways to incorporate HFPS into preclinical medical education represents more of a challenge, and there is limited literature regarding its implementation. The main objective of this study was to implement a HFPS activity into a problem-based curriculum to enhance the learning of basic sciences. More specifically, the focus was to aid in student learning of cardiovascular function curves and help students develop heart failure treatment strategies based on basic cardiovascular physiology concepts. Pretests and posttests, along with student surveys, were used to determine student knowledge and perception of learning in two first-year medical school classes. There was an increase of 21% and 22% in the percentage of students achieving correct answers on a posttest compared with their pretest score. The median number of correct questions increased from pretest scores of 2 and 2.5 to posttest scores of 4 and 5 of a possible total of 6 in each respective year. Student survey data showed agreement that the activity aided in learning. This study suggests that a HFPS activity can be implemented during the preclinical years of medical education to address basic science concepts. Additionally, it suggests that student learning of cardiovascular function curves and heart failure strategies are facilitated.

Education Isn’t Education: The Creativity Response or How to Improve the Learning Curve in Our Society

Directory of Open Access Journals (Sweden)

Stefan Brunnhuber

2017-06-01

Full Text Available Despite rising expenditure and general enrolment rates on a global level, educational output is stagnating, if not declining. There is increasing empirical evidence that we need a completely different approach to enhancing the learning curve; this holds true for early childhood, primary education, secondary education and higher education. Most existing educational programs do not tap into the full creative potential of our minds and our brains and often lead to suboptimal outcomes both for the individual and for society as a whole. Findings in clinical psychology, neurobiology and social psychology are not sufficiently considered when setting up appropriate educational programs. It is not the cognitive part of the curriculum that makes a difference, but rather the non-cognitive features (including stress management, impulse control, self-regulation, emotional attachment etc. that improve creativity. A ‘six-pack’ of features, including exercise, nutrition, social contact, mindfulness-based practices, sleeping well, and multi-sensory learning, is introduced as part of a ‘creativity response’. They are simple, affordable, evidence-based and efficient strategies that can be implemented promptly without additional costs, increasing our learning curve.

Balloon dilation of the eustachian tube in a cadaver model: technical considerations, learning curve, and potential barriers.

Science.gov (United States)

McCoul, Edward D; Singh, Ameet; Anand, Vijay K; Tabaee, Abtin

2012-04-01

The surgical management options for eustachian tube dysfunction have historically been limited. The goal of the current study was to evaluate the technical considerations, learning curve, and potential barriers for balloon dilation of the eustachian tube (BDET) as an alternative treatment modality. Prospective preclinical trial of BDET in a cadaver model. A novel balloon catheter device was used for eustachian tube dilation. Twenty-four BDET procedures were performed by three independent rhinologists with no prior experience with the procedure (eight procedures per surgeon). The duration and number of attempts of the individual steps and overall procedure were recorded. Endoscopic examination of the eustachian tube was performed after each procedure, and the surgeon was asked to rate the subjective difficulty on a five-point scale. Successful completion of the procedure occurred in each case. The overall mean duration of the procedure was 284 seconds, and a mean number of 1.15 attempts were necessary to perform the individual steps. The mean subjective procedure difficulty was noted as somewhat easy. Statistically shorter duration and subjectively easier procedure were noted in the second compared to the first half of the series, indicating a favorable learning curve. Linear fissuring within the eustachian tube lumen without submucosal disruption (nine procedures, 37%) and with submucosal disruption (five procedures, 21%) were noted. The significance of these physical findings is unclear. Preclinical testing of BDET is associated with favorable duration, learning curve, and overall ease of completion. Clinical trials are necessary to evaluate safety and efficacy. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

LHC Run 2 – reaching the top of the learning curve

CERN Multimedia

2015-01-01

As the LHC Physics conference gets underway in St Petersburg, it’s a good time to take stock of where things stand with Run 2.    For all those involved with operating the LHC and its experiments in this new energy and intensity regime, 2015 was always going to be a learning curve. And learning we most certainly are. The main objective for this year has always been to set up the machine and experiments for production running at high energy and high intensity in 2016, 17 and 18.  That said, the experiments have all been able to collect quality data at 13 TeV, with the first Run 2 papers and conference presentations being written and delivered this summer. It would be unfair of me, however, to give the impression that it’s all been plain sailing. As well as the highs: smooth recommissioning of the machine, physics getting underway, and a successful transition to 25-nanosecond bunch spacing, we’ve also had our fair share of lows. There have been no sho...

Short-term delayed recall of auditory verbal learning test is equivalent to long-term delayed recall for identifying amnestic mild cognitive impairment.

Directory of Open Access Journals (Sweden)

Qianhua Zhao

Full Text Available Delayed recall of words in a verbal learning test is a sensitive measure for the diagnosis of amnestic mild cognitive impairment (aMCI and early Alzheimer's disease (AD. The relative validity of different retention intervals of delayed recall has not been well characterized. Using the Auditory Verbal Learning Test-Huashan version, we compared the differentiating value of short-term delayed recall (AVL-SR, that is, a 3- to 5-minute delay time and long-term delayed recall (AVL-LR, that is, a 20-minute delay time in distinguishing patients with aMCI (n = 897 and mild AD (n = 530 from the healthy elderly (n = 1215. In patients with aMCI, the correlation between AVL-SR and AVL-LR was very high (r = 0.94, and the difference between the two indicators was less than 0.5 points. There was no difference between AVL-SR and AVL-LR in the frequency of zero scores. In the receiver operating characteristic curves analysis, although the area under the curve (AUC of AVL-SR and AVL-LR for diagnosing aMCI was significantly different, the cut-off scores of the two indicators were identical. In the subgroup of ages 80 to 89, the AUC of the two indicators showed no significant difference. Therefore, we concluded that AVL-SR could substitute for AVL-LR in identifying aMCI, especially for the oldest patients.

Uniportal video-assisted thoracoscopic surgery: safety, efficacy and learning curve during the first 250 cases in Quebec, Canada.

Science.gov (United States)

Drevet, Gabrielle; Ugalde Figueroa, Paula

2016-03-01

Video-assisted thoracoscopic surgery (VATS) using a single incision (uniportal) may result in better pain control, earlier mobilization and shorter hospital stays. Here, we review the safety and efficiency of our initial experience with uniportal VATS and evaluate our learning curve. We conducted a retrospective review of uniportal VATS using a prospectively maintained departmental database and analyzed patients who had undergone a lung anatomic resection separately from patients who underwent other resections. To assess the learning curve, we compared the first 10 months of the study period with the second 10 months. From January 2014 to August 2015, 250 patients underwent intended uniportal VATS, including 180 lung anatomic resections (72%) and 70 other resections (28%). Lung anatomic resection was successfully completed using uniportal VATS in 153 patients (85%), which comprised all the anatomic segmentectomies (29 patients), 80% (4 of 5) of the pneumonectomies and 82% (120 of 146) of the lobectomies attempted. The majority of lung anatomic resections that required conversion to thoracotomy occurred in the first half of our study period. Seventy patients underwent other uniportal VATS resections. Wedge resections were the most common of these procedures (25 patients, 35.7%). Although 24 of the 70 patients (34%) required the placement of additional ports, none required conversion to thoracotomy. Uniportal VATS was safe and feasible for both standard and complex pulmonary resections. However, when used for pulmonary anatomic resections, uniportal VATS entails a steep learning curve.

Single-centre experience of retroperitoneoscopic approach in urology with tips to overcome the steep learning curve

Directory of Open Access Journals (Sweden)

Aneesh Srivastava

2016-01-01

Full Text Available Context: The retroperitoneoscopic or retroperitoneal (RP surgical approach has not become as popular as the transperitoneal (TP one due to the steeper learning curve. Aims: Our single-institution experience focuses on the feasibility, advantages and complications of retroperitoneoscopic surgeries (RS performed over the past 10 years. Tips and tricks have been discussed to overcome the steep learning curve and these are emphasised. Settings and Design: This study made a retrospective analysis of computerised hospital data of patients who underwent RP urological procedures from 2003 to 2013 at a tertiary care centre. Patients and Methods: Between 2003 and 2013, 314 cases of RS were performed for various urological procedures. We analysed the operative time, peri-operative complications, time to return of bowel sound, length of hospital stay, and advantages and difficulties involved. Post-operative complications were stratified into five grades using modified Clavien classification (MCC. Results: RS were successfully completed in 95.5% of patients, with 4% of the procedures electively performed by the combined approach (both RP and TP; 3.2% required open conversion and 1.3% were converted to the TP approach. The most common cause for conversion was bleeding. Mean hospital stay was 3.2 ± 1.2 days and the mean time for returning of bowel sounds was 16.5 ± 5.4 h. Of the patients, 1.4% required peri-operative blood transfusion. A total of 16 patients (5% had post-operative complications and the majority were grades I and II as per MCC. The rates of intra-operative and post-operative complications depended on the difficulty of the procedure, but the complications diminished over the years with the increasing experience of surgeons. Conclusion: Retroperitoneoscopy has proven an excellent approach, with certain advantages. The tips and tricks that have been provided and emphasised should definitely help to minimise the steep learning curve.

Short-term perceptual learning in visual conjunction search.

Science.gov (United States)

Su, Yuling; Lai, Yunpeng; Huang, Wanyi; Tan, Wei; Qu, Zhe; Ding, Yulong

2014-08-01

Although some studies showed that training can improve the ability of cross-dimension conjunction search, less is known about the underlying mechanism. Specifically, it remains unclear whether training of visual conjunction search can successfully bind different features of separated dimensions into a new function unit at early stages of visual processing. In the present study, we utilized stimulus specificity and generalization to provide a new approach to investigate the mechanisms underlying perceptual learning (PL) in visual conjunction search. Five experiments consistently showed that after 40 to 50 min of training of color-shape/orientation conjunction search, the ability to search for a certain conjunction target improved significantly and the learning effects did not transfer to a new target that differed from the trained target in both color and shape/orientation features. However, the learning effects were not strictly specific. In color-shape conjunction search, although the learning effect could not transfer to a same-shape different-color target, it almost completely transferred to a same-color different-shape target. In color-orientation conjunction search, the learning effect partly transferred to a new target that shared same color or same orientation with the trained target. Moreover, the sum of transfer effects for the same color target and the same orientation target in color-orientation conjunction search was algebraically equivalent to the learning effect for trained target, showing an additive transfer effect. The different transfer patterns in color-shape and color-orientation conjunction search learning might reflect the different complexity and discriminability between feature dimensions. These results suggested a feature-based attention enhancement mechanism rather than a unitization mechanism underlying the short-term PL of color-shape/orientation conjunction search.

The learning curve for narrow-band imaging in the diagnosis of precancerous gastric lesions by using Web-based video.

Science.gov (United States)

Dias-Silva, Diogo; Pimentel-Nunes, Pedro; Magalhães, Joana; Magalhães, Ricardo; Veloso, Nuno; Ferreira, Carlos; Figueiredo, Pedro; Moutinho, Pedro; Dinis-Ribeiro, Mário

2014-06-01

A simplified narrow-band imaging (NBI) endoscopy classification of gastric precancerous and cancerous lesions was derived and validated in a multicenter study. This classification comes with the need for dissemination through adequate training. To address the learning curve of this classification by endoscopists with differing expertise and to assess the feasibility of a YouTube-based learning program to disseminate it. Prospective study. Five centers. Six gastroenterologists (3 trainees, 3 fully trained endoscopists [FTs]). Twenty tests provided through a Web-based program containing 10 randomly ordered NBI videos of gastric mucosa were taken. Feedback was sent 7 days after every test submission. Measures of accuracy of the NBI classification throughout the time. From the first to the last 50 videos, a learning curve was observed with a 10% increase in global accuracy, for both trainees (from 64% to 74%) and FTs (from 56% to 65%). After 200 videos, sensitivity and specificity of 80% and higher for intestinal metaplasia were observed in half the participants, and a specificity for dysplasia greater than 95%, along with a relevant likelihood ratio for a positive result of 7 to 28 and likelihood ratio for a negative result of 0.21 to 0.82, were achieved by all of the participants. No constant learning curve was observed for the identification of Helicobacter pylori gastritis and sensitivity to dysplasia. The trainees had better results in all of the parameters, except specificity for dysplasia, compared with the FTs. Globally, participants agreed that the program's structure was adequate, except on the feedback, which should have consisted of a more detailed explanation of each answer. No formal sample size estimate. A Web-based learning program could be used to teach and disseminate classifications in the endoscopy field. In this study, an NBI classification for gastric mucosal features seems to be easily learned for the identification of gastric preneoplastic

Short-Term Reproducibility of Twenty-Four-Hour Intraocular Pressure Curves in Untreated Patients with Primary Open-Angle Glaucoma and Ocular Hypertension.

Directory of Open Access Journals (Sweden)

Shuo Xu

Full Text Available To assess the short-term day-to-day reproducibility of 24-hour intraocular pressure (IOP curves in various respects in untreated primary open-angle glaucoma (POAG and ocular hypertension (OHT patients.47 subjects with POAG and 34 subjects with OHT underwent IOP measurements every 2 hours in both eyes for consecutive 48 hours by a non-contact tonometer (NCT. IOP values at each time point were recorded. Mean IOP, peak IOP, time difference of peak IOP between two days and IOP fluctuation were also calculated. Intraclass correlation coefficients (ICCs and Bland-Altman plots were used to evaluate reproducibility.ICCs of the entire IOP values for a complete 24-hour curve were 0.577 and 0.561 in POAG and OHT patients, respectively. ICCs of IOP values at different time points ranged from 0.384 (10am to 0.686 (4am in POAG patients and from 0.347 (6am to 0.760 (4am in OHT patients. ICCs of mean IOP, peak IOP and IOP fluctuation were respectively 0.832, 0.704, 0.367 in POAG patients and 0.867, 0.816 0.633 in OHT patients. Only 37.23% and 35.29% of the peak IOP time points appeared within the time difference of 2 hours in POAG and OHT patients, respectively, while 53.19% and 48.53% appeared within 4 hours in POAG and OHT patients, respectively.A 24-hour IOP curve in a single day is not highly reproducible in short-term and has limited use for evaluating individual IOP condition. Mean IOP and peak IOP for a 24-hour IOP curve are useful parameters in clinical follow-up, while IOP value at a certain time point, IOP fluctuation and peak IOP time point should be interpreted with caution.

Direct current induced short-term modulation of the left dorsolateral prefrontal cortex while learning auditory presented nouns

Directory of Open Access Journals (Sweden)

Meyer Martin

2009-07-01

Full Text Available Abstract Background Little is known about the contribution of transcranial direct current stimulation (tDCS to the exploration of memory functions. The aim of the present study was to examine the behavioural effects of right or left-hemisphere frontal direct current delivery while committing to memory auditory presented nouns on short-term learning and subsequent long-term retrieval. Methods Twenty subjects, divided into two groups, performed an episodic verbal memory task during anodal, cathodal and sham current application on the right or left dorsolateral prefrontal cortex (DLPFC. Results Our results imply that only cathodal tDCS elicits behavioural effects on verbal memory performance. In particular, left-sided application of cathodal tDCS impaired short-term verbal learning when compared to the baseline. We did not observe tDCS effects on long-term retrieval. Conclusion Our results imply that the left DLPFC is a crucial area involved in short-term verbal learning mechanisms. However, we found further support that direct current delivery with an intensity of 1.5 mA to the DLPFC during short-term learning does not disrupt longer lasting consolidation processes that are mainly known to be related to mesial temporal lobe areas. In the present study, we have shown that the tDCS technique has the potential to modulate short-term verbal learning mechanism.

Training anesthesiology residents in providing anesthesia for awake craniotomy: learning curves and estimate of needed case load.

Science.gov (United States)

Bilotta, Federico; Titi, Luca; Lanni, Fabiana; Stazi, Elisabetta; Rosa, Giovanni

2013-08-01

To measure the learning curves of residents in anesthesiology in providing anesthesia for awake craniotomy, and to estimate the case load needed to achieve a "good-excellent" level of competence. Prospective study. Operating room of a university hospital. 7 volunteer residents in anesthesiology. Residents underwent a dedicated training program of clinical characteristics of anesthesia for awake craniotomy. The program was divided into three tasks: local anesthesia, sedation-analgesia, and intraoperative hemodynamic management. The learning curve for each resident for each task was recorded over 10 procedures. Quantitative assessment of the individual's ability was based on the resident's self-assessment score and the attending anesthesiologist's judgment, and rated by modified 12 mm Likert scale, reported ability score visual analog scale (VAS). This ability VAS score ranged from 1 to 12 (ie, very poor, mild, moderate, sufficient, good, excellent). The number of requests for advice also was recorded (ie, resident requests for practical help and theoretical notions to accomplish the procedures). Each task had a specific learning rate; the number of procedures necessary to achieve "good-excellent" ability with confidence, as determined by the recorded results, were 10 procedures for local anesthesia, 15 to 25 procedures for sedation-analgesia, and 20 to 30 procedures for intraoperative hemodynamic management. Awake craniotomy is an approach used increasingly in neuroanesthesia. A dedicated training program based on learning specific tasks and building confidence with essential features provides "good-excellent" ability. © 2013 Elsevier Inc. All rights reserved.

Spatial short-term memory in children with nonverbal learning disabilities: impairment in encoding spatial configuration.

Science.gov (United States)

Narimoto, Tadamasa; Matsuura, Naomi; Takezawa, Tomohiro; Mitsuhashi, Yoshinori; Hiratani, Michio

2013-01-01

The authors investigated whether impaired spatial short-term memory exhibited by children with nonverbal learning disabilities is due to a problem in the encoding process. Children with or without nonverbal learning disabilities performed a simple spatial test that required them to remember 3, 5, or 7 spatial items presented simultaneously in random positions (i.e., spatial configuration) and to decide if a target item was changed or all items including the target were in the same position. The results showed that, even when the spatial positions in the encoding and probe phases were similar, the mean proportion correct of children with nonverbal learning disabilities was 0.58 while that of children without nonverbal learning disabilities was 0.84. The authors argue with the results that children with nonverbal learning disabilities have difficulty encoding relational information between spatial items, and that this difficulty is responsible for their impaired spatial short-term memory.

The role of experience curves for setting MEPS for appliances

International Nuclear Information System (INIS)

Siderius, Hans-Paul

2013-01-01

Minimum efficiency performance standards (MEPS) are an important policy instrument to raise the efficiency of products. In most schemes the concept of life cycle costs (LCC) is used to guide setting the MEPS levels. Although a large body of literature shows that product cost is decreasing with increasing cumulative production, the experience curve, this is currently not used for setting MEPS. This article shows how to integrate the concept of the experience curve into LCC calculations for setting MEPS in the European Union and applies this to household laundry driers, refrigerator-freezers and televisions. The results indicate that for driers and refrigerator-freezers at least twice the energy savings compared to the current approach can be achieved. These products also show that energy label classes can successfully be used for setting MEPS. For televisions an experience curve is provided, showing a learning rate of 29%. However, television prices do not show a relation with energy efficiency but are to a large extent determined by the time the product is placed on the market. This suggests to policy makers that for televisions and other products with a short (re)design and market cycle timing is more important than the MEPS levels itself. - Highlights: • We integrate experience curves into life cycle cost calculations for MEPS. • For driers and refrigerators this results in at least twice the energy savings. • For flat panel televisions an experience curve is provided

C. elegans positive butanone learning, short-term, and long-term associative memory assays.

Science.gov (United States)

Kauffman, Amanda; Parsons, Lance; Stein, Geneva; Wills, Airon; Kaletsky, Rachel; Murphy, Coleen

2011-03-11

The memory of experiences and learned information is critical for organisms to make choices that aid their survival. C. elegans navigates its environment through neuron-specific detection of food and chemical odors, and can associate nutritive states with chemical odors, temperature, and the pathogenicity of a food source. Here, we describe assays of C. elegans associative learning and short- and long-term associative memory. We modified an aversive olfactory learning paradigm to instead produce a positive response; the assay involves starving ~400 worms, then feeding the worms in the presence of the AWC neuron-sensed volatile chemoattractant butanone at a concentration that elicits a low chemotactic index (similar to Toroyama et al.). A standard population chemotaxis assay1 tests the worms' attraction to the odorant immediately or minutes to hours after conditioning. After conditioning, wild-type animals' chemotaxis to butanone increases ~0.6 Chemotaxis Index units, its "Learning Index". Associative learning is dependent on the presence of both food and butanone during training. Pairing food and butanone for a single conditioning period ("massed training") produces short-term associative memory that lasts ~2 hours. Multiple conditioning periods with rest periods between ("spaced training") yields long-term associative memory (long-term memory across species. Our protocol also includes image analysis methods for quick and accurate determination of chemotaxis indices. High-contrast images of animals on chemotaxis assay plates are captured and analyzed by worm counting software in MatLab. The software corrects for uneven background using a morphological tophat transformation. Otsu's method is then used to determine a threshold to separate worms from the background. Very small particles are removed automatically and larger non-worm regions (plate edges or agar punches) are removed by manual selection. The software then estimates the size of single worm by ignoring

Colorectal endoscopic submucosal dissection (ESD) in the West - when can satisfactory results be obtained? A single-operator learning curve analysis.

Science.gov (United States)

Spychalski, Michał; Skulimowski, Aleksander; Dziki, Adam; Saito, Yutaka

2017-12-01

Up to date we lack a detailed description of the colorectal endoscopic submucosal dissection (ESD) learning curve, that would represent the experience of the Western center. The aim of this study was to define the critical points of the learning curve and to draw up lesions qualification guidelines tailored to the endoscopists experience. We have carried out a single center prospective study. Between June 2013 and December 2016, 228 primary colorectal lesions were managed by ESD procedure. In order to create a learning curve model and to carry out the analysis the cases were divided into six periods, each consisting of 38 cases. The overall en bloc resection rate was 79.39%. The lowest en bloc resection rate (52.36%) was observed in the first period. After completing 76 procedures, the resection rate surged to 86% and it was accompanied by the significant increase in the mean procedure speed of ≥9 cm 2 /h. Lesions localization and diameter had a signification impact on the outcomes. After 76 procedures, en bloc resection rate of 90.9 and 90.67% were achieved for the left side of colon and rectum, respectively. In the right side of colon statistically significant lower resection rate of 67.57% was observed. We have proved that in the setting of the Western center, colorectal ESD can yield excellent results. It seems that the key to the success during the learning period is 'tailoring' lesions qualification guidelines to the experience of the endoscopist, as lesions diameter and localization highly influence the outcomes.

The value of using short-format podcasts to enhance learning and teaching

Directory of Open Access Journals (Sweden)

Catherine Sutton-Brady

2009-12-01

Full Text Available This paper presents the findings of a podcasting trial held in 2007–2008 within the Faculty of Economics and Business at the University of Sydney, Australia. The trial investigates the value of using short-format podcasts to support assessment for postgraduate and undergraduate students. A multi-method approach is taken in investigating perceptions of the benefits of podcasting, incorporating surveys, focus groups and interviews. The results show that a majority of students believe they gained learning benefits from the podcasts and appreciated the flexibility of the medium to support their learning, and the lecturers felt the innovation helped diversify their pedagogical approach and support a diverse student population. Three primary conclusions are presented: (1 most students reject the mobile potential of podcasting in favour of their traditional study space at home; (2 what students and lecturers value about this podcasting design overlap; (3 the assessment-focussed, short-format podcast design may be considered a successful podcasting model. The paper finishes by identifying areas for future research on the effective use of podcasting in learning and teaching.

Experience curve for natural gas production by hydraulic fracturing

International Nuclear Information System (INIS)

Fukui, Rokuhei; Greenfield, Carl; Pogue, Katie; Zwaan, Bob van der

2017-01-01

From 2007 to 2012 shale gas production in the US expanded at an astounding average growth rate of over 50%/yr, and thereby increased nearly tenfold over this short time period alone. Hydraulic fracturing technology, or “fracking”, as well as new directional drilling techniques, played key roles in this shale gas revolution, by allowing for extraction of natural gas from previously unviable shale resources. Although hydraulic fracturing technology had been around for decades, it only recently became commercially attractive for large-scale implementation. As the production of shale gas rapidly increased in the US over the past decade, the wellhead price of natural gas dropped substantially. In this paper we express the relationship between wellhead price and cumulative natural gas output in terms of an experience curve, and obtain a learning rate of 13% for the industry using hydraulic fracturing technology. This learning rate represents a measure for the know-how and skills accumulated thus far by the US shale gas industry. The use of experience curves for renewable energy options such as solar and wind power has allowed analysts, practitioners, and policy makers to assess potential price reductions, and underlying cost decreases, for these technologies in the future. The reasons for price reductions of hydraulic fracturing are fundamentally different from those behind renewable energy technologies – hence they cannot be directly compared – and hydraulic fracturing may soon reach, or maybe has already attained, a lower bound for further price reductions, for instance as a result of its water requirements or environmental footprint. Yet, understanding learning-by-doing phenomena as expressed by an industry-wide experience curve for shale gas production can be useful for strategic planning in the gas sector, as well as assist environmental policy design, and serve more broadly as input for projections of energy system developments. - Highlights: • Hydraulic

Distinct cerebellar engrams in short-term and long-term motor learning.

Science.gov (United States)

Wang, Wen; Nakadate, Kazuhiko; Masugi-Tokita, Miwako; Shutoh, Fumihiro; Aziz, Wajeeha; Tarusawa, Etsuko; Lorincz, Andrea; Molnár, Elek; Kesaf, Sebnem; Li, Yun-Qing; Fukazawa, Yugo; Nagao, Soichi; Shigemoto, Ryuichi

2014-01-07

Cerebellar motor learning is suggested to be caused by long-term plasticity of excitatory parallel fiber-Purkinje cell (PF-PC) synapses associated with changes in the number of synaptic AMPA-type glutamate receptors (AMPARs). However, whether the AMPARs decrease or increase in individual PF-PC synapses occurs in physiological motor learning and accounts for memory that lasts over days remains elusive. We combined quantitative SDS-digested freeze-fracture replica labeling for AMPAR and physical dissector electron microscopy with a simple model of cerebellar motor learning, adaptation of horizontal optokinetic response (HOKR) in mouse. After 1-h training of HOKR, short-term adaptation (STA) was accompanied with transient decrease in AMPARs by 28% in target PF-PC synapses. STA was well correlated with AMPAR decrease in individual animals and both STA and AMPAR decrease recovered to basal levels within 24 h. Surprisingly, long-term adaptation (LTA) after five consecutive daily trainings of 1-h HOKR did not alter the number of AMPARs in PF-PC synapses but caused gradual and persistent synapse elimination by 45%, with corresponding PC spine loss by the fifth training day. Furthermore, recovery of LTA after 2 wk was well correlated with increase of PF-PC synapses to the control level. Our findings indicate that the AMPARs decrease in PF-PC synapses and the elimination of these synapses are in vivo engrams in short- and long-term motor learning, respectively, showing a unique type of synaptic plasticity that may contribute to memory consolidation.

Laparoscopy Instructional Videos: The Effect of Preoperative Compared With Intraoperative Use on Learning Curves.

Science.gov (United States)

Broekema, Theo H; Talsma, Aaldert K; Wevers, Kevin P; Pierie, Jean-Pierre E N

Previous studies have shown that the use of intraoperative instructional videos has a positive effect on learning laparoscopic procedures. This study investigated the effect of the timing of the instructional videos on learning curves in laparoscopic skills training. After completing a basic skills course on a virtual reality simulator, medical students and residents with less than 1 hour experience using laparoscopic instruments were randomized into 2 groups. Using an instructional video either preoperatively or intraoperatively, both groups then performed 4 repetitions of a standardized task on the TrEndo augmented reality. With the TrEndo, 9 motion analysis parameters (MAPs) were recorded for each session (4 MAPs for each hand and time). These were the primary outcome measurements for performance. The time spent watching the instructional video was also recorded. Improvement in performance was studied within and between groups. Medical Center Leeuwarden, a secondary care hospital located in Leeuwarden, The Netherlands. Right-hand dominant medical student and residents with more than 1 hour experience operating any kind of laparoscopic instruments were participated. A total of 23 persons entered the study, of which 21 completed the study course. In both groups, at least 5 of 9 MAPs showed significant improvements between repetition 1 and 4. When both groups were compared after completion of repetition 4, no significant differences in improvement were detected. The intraoperative group showed significant improvement in 3 MAPs of the left-nondominant-hand, compared with one MAP for the preoperative group. No significant differences in learning curves could be detected between the subjects who used intraoperative instructional videos and those who used preoperative instructional videos. Intraoperative video instruction may result in improved dexterity of the nondominant hand. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc

Irregularities in the dendrochronological calibration curve

International Nuclear Information System (INIS)

Ottaway, J.H.; Ottaway, B.

1975-01-01

A discussion is presented on the reality or otherwise of short-term deviations from a linear or smooth curve relating conventional C-14 dates to dendrochronological measurements. The possibility of the effect of short-term changes in the earth's atmosphere and in the oceans, and particularly in their temperature, is considered. (U.K.)

Analyzing the Learning Path of US Shale Players by Using the Learning Curve Method

Directory of Open Access Journals (Sweden)

Jong-Hyun Kim

2017-12-01

Full Text Available The US shale exploration and production (E&P industry has grown since 2007 due to the development of new techniques such as hydraulic fracturing and horizontal drilling. As a result, the share of shale gas in the US natural gas production is almost 50%, and the share of tight oil in the US crude oil production is almost 52%. Even though oil and gas prices decreased sharply in 2014, the production amounts of shale gas and tight oil increased between 2014 and 2015. We show that many players in the US shale E&P industry succeeded in decreasing their production costs to maintain their business activity and production. However, most of the companies in the US petroleum E&P industry incurred losses in 2015 and 2016. Furthermore, crude oil and natural gas prices could not rebound to their 2015 price levels. Therefore, many companies in the US petroleum E&P industry need to increase their productivity to overcome the low commodity prices situation. Hence, to test the change in their productivity and analyze their ability to survive in the petroleum industry, this study calculates the learning rate using the US shale E&P players’ annual report data from 2008 to 2016. The result of the calculation is that the long-term learning rate is 1.87% and the short-term learning rate is 3.16%. This indicates a change in the technological development trend.

Adolescent Idiopathic Scoliosis Surgery by a Neurosurgeon: Learning Curve for Neurosurgeons.

Science.gov (United States)

Hyun, Seung-Jae; Han, Sanghyun; Kim, Ki-Jeong; Jahng, Tae-Ahn; Kim, Yongjung J; Rhim, Seung-Chul; Kim, Hyun-Jib

2018-02-01

To determine a neurosurgeon's learning curve of surgical treatment for adolescent idiopathic scoliosis (AIS) patients. This study is a retrospective analysis. Forty-six patients were treated by a single neurosurgeon between 2011 and 2017 using posterior segmental instrumentation and fusion. According to the time period, the former and latter 23 patients were divided into group 1 and group 2, respectively. Patients' demographic data, curve magnitude, number of levels treated, amount of correction achieved, radiographic/clinical outcomes, and complications were compared between the groups. The majority were females (34 vs. 12) with average ages of 15.0 versus 15.6, respectively. The mean follow-up period was 24.6 months. The average number of fusion levels was similar with 10.3 and 11.5 vertebral bodies in groups 1 and 2, respectively. The average Cobb angle of major curvature was 59.8° and 58.5° in groups 1 and 2, respectively. There observed significant reductions of operative time (324.4 vs. 224.7 minutes, P = 0.007) and estimated blood loss (648.3 vs. 438.0 mL, P = 0.027) in group 2. The correction rate of the major structural curve was greater in group 2 (70.7% vs. 81.0%, P = 0.001). There was no case of neurologic deficit, infection, and revision for screw malposition. One patient of group 1 underwent fusion extension surgery for shoulder asymmetry. Radiographic and clinical outcomes of AIS patients treated by a neurosurgeon were acceptable. AIS surgery may be performed with an acceptable rate of complications after about 20 surgeries. With acquisition of surgical experiences, neurosurgeons could perform deformity surgery for AIS effectively and safely. Copyright © 2017 Elsevier Inc. All rights reserved.

A minicourse on moduli of curves

International Nuclear Information System (INIS)

Looijenga, E.

2000-01-01

These are notes that accompany a short course given at the School on Algebraic Geometry 1999 at the ICTP, Trieste. A major goal is to outline various approaches to moduli spaces of curves. In the last part I discuss the algebraic classes that naturally live on these spaces; these can be thought of as the characteristic classes for bundles of curves. (author)

Deep-learnt classification of light curves

DEFF Research Database (Denmark)

Mahabal, Ashish; Gieseke, Fabian; Pai, Akshay Sadananda Uppinakudru

2017-01-01

is to derive statistical features from the time series and to use machine learning methods, generally supervised, to separate objects into a few of the standard classes. In this work, we transform the time series to two-dimensional light curve representations in order to classify them using modern deep......Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and techniques to classify light curves. A common approach...... learning techniques. In particular, we show that convolutional neural networks based classifiers work well for broad characterization and classification. We use labeled datasets of periodic variables from CRTS survey and show how this opens doors for a quick classification of diverse classes with several...

PV experience curves for the Netherlands

International Nuclear Information System (INIS)

Gerwig, R.

2005-01-01

Experience curves are one of several tools used by policy makers to take a look at market development. Numerous curves have been constructed for PV but none specific to the Netherlands. The objective of this report is to take a look at the price development of grid-connected PV systems in the Netherlands using the experience curve theory. After a literature and internet search and attempts to acquire information from PV companies information on 51% of the totally installed capacity was found. Curves for the period 1991-2001 were constructed based on system price, BOS (balance-of-system) price and inverter price. The progress ratio of the locally learning BOS was similar to the globally learning module market. This indicates that the pace of development of the Dutch PV market is similar to the globally followed pace. Improvement of the detail of the data might help to get a better idea of which BOS components have declined most. The similar progress ratio also shows the importance of investing both in module and system research as is the case in the Netherlands

Phonon transport in a curved aluminum thin film due to laser short pulse irradiation

Science.gov (United States)

Mansoor, Saad Bin; Yilbas, Bekir Sami

2018-05-01

Laser short-pulse heating of a curved aluminum thin film is investigated. The Boltzmann transport equation is incorporated to formulate the heating situation. A Gaussian laser intensity distribution is considered along the film arc and time exponentially decaying of pulse intensity is incorporated in the analysis. The governing equations of energy transport in the electron and lattice sub-systems are coupled through the electron-phonon coupling parameter. To quantify the phonon intensity distribution in the thin film, equivalent equilibrium temperature is introduced, which is associated with the average energy of all phonons around a local point when the phonon energies are redistributed adiabatically to an equilibrium state. It is found the numerical simulations that electron temperature follows similar trend to the spatial distribution of the laser pulse intensity at the film edge. Temporal variation of electron temperature does not follow the laser pulse intensity distribution. The rise of temperature in the electron sub-system is fast while it remains slow in the lattice sub-system.

Rational points, rational curves, and entire holomorphic curves on projective varieties

CERN Document Server

Gasbarri, Carlo; Roth, Mike; Tschinkel, Yuri

2015-01-01

This volume contains papers from the Short Thematic Program on Rational Points, Rational Curves, and Entire Holomorphic Curves and Algebraic Varieties, held from June 3-28, 2013, at the Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada. The program was dedicated to the study of subtle interconnections between geometric and arithmetic properties of higher-dimensional algebraic varieties. The main areas of the program were, among others, proving density of rational points in Zariski or analytic topology on special varieties, understanding global geometric properties of rationally connected varieties, as well as connections between geometry and algebraic dynamics exploring new geometric techniques in Diophantine approximation.

Diffusion of robotics into clinical practice in the United States: process, patient safety, learning curves, and the public health.

Science.gov (United States)

Mirheydar, Hossein S; Parsons, J Kellogg

2013-06-01

Robotic technology disseminated into urological practice without robust comparative effectiveness data. To review the diffusion of robotic surgery into urological practice. We performed a comprehensive literature review focusing on diffusion patterns, patient safety, learning curves, and comparative costs for robotic radical prostatectomy, partial nephrectomy, and radical cystectomy. Robotic urologic surgery diffused in patterns typical of novel technology spreading among practicing surgeons. Robust evidence-based data comparing outcomes of robotic to open surgery were sparse. Although initial Level 3 evidence for robotic prostatectomy observed complication outcomes similar to open prostatectomy, subsequent population-based Level 2 evidence noted an increased prevalence of adverse patient safety events and genitourinary complications among robotic patients during the early years of diffusion. Level 2 evidence indicated comparable to improved patient safety outcomes for robotic compared to open partial nephrectomy and cystectomy. Learning curve recommendations for robotic urologic surgery have drawn exclusively on Level 4 evidence and subjective, non-validated metrics. The minimum number of cases required to achieve competency for robotic prostatectomy has increased to unrealistically high levels. Most comparative cost-analyses have demonstrated that robotic surgery is significantly more expensive than open or laparoscopic surgery. Evidence-based data are limited but suggest an increased prevalence of adverse patient safety events for robotic prostatectomy early in the national diffusion period. Learning curves for robotic urologic surgery are subjective and based on non-validated metrics. The urological community should develop rigorous, evidence-based processes by which future technological innovations may diffuse in an organized and safe manner.

Assessing Global Learning in Short-Term Study Abroad: Population, Environment, and Society in Shanghai

Science.gov (United States)

Core, Rachel S.

2017-01-01

This teaching note suggests that a short-term study abroad program embedded within a longer course can be a tool for enhancing global learning. The work uses the Association of American Colleges and Universities (AAC&U) Global Learning VALUE rubric to evaluate student work from a spring break seminar to Shanghai, China. The seminar was…

Protocol for Short- and Longer-term Spatial Learning and Memory in Mice

Directory of Open Access Journals (Sweden)

Emily F. Willis

2017-10-01

Full Text Available Studies on the role of the hippocampus in higher cognitive functions such as spatial learning and memory in rodents are reliant upon robust and objective behavioral tests. This protocol describes one such test—the active place avoidance (APA task. This behavioral task involves the mouse continuously integrating visual cues to orientate itself within a rotating arena in order to actively avoid a shock zone, the location of which remains constant relative to the room. This protocol details the step-by-step procedures for a novel paradigm of the hippocampal-dependent APA task, measuring acquisition of spatial learning during a single 20-min trial (i.e., short-term memory, with spatial memory encoding and retrieval (i.e., long-term memory assessed by trials conducted over consecutive days. Using the APA task, cognitive flexibility can be assessed using the reversal learning paradigm, as this increases the cognitive load required for efficient performance in the task. In addition to a detailed experimental protocol, this paper also describes the range of its possible applications, the expected key results, as well as the analytical methods to assess the data, and the pitfalls/troubleshooting measures. The protocol described herein is highly robust and produces replicable results, thus presenting an important paradigm that enables the assessment of subtle short-term changes in spatial learning and memory, such as those observed for many experimental interventions.

Contrast agents provide a faster learning curve in dipyridamole stress echocardiography.

Science.gov (United States)

Zamorano, Jose; Sánchez, Violeta; Moreno, Raúl; Almería, Carlos; Rodrigo, Jose; Serra, Viviana; Azcona, Luis; Aubele, Adalia; Mataix, Luis; Sánchez-Harguindey, Luis

2002-12-01

Interobserver variability is an important limitation of the stress echocardiography and depends on the echocardiographer training. Our aim was to evaluate if the use of contrast agents during dipyridamole stress echocardiography would improve the agreement between an experienced and a non-experienced observer in stress echo and therefore if contrast would affect the learning period of dypyridamole stress echo. Two independent observers without knowledge of any patient data interpreted all stress studies. One observer was an experienced one and the other had experience in echocardiography but not in stress echo. Two observers analysed 87 non-selected and consecutive studies. Out of the 87 studies, 46 were performed without contrast administration, whereas i.v. contrast (2.5 g Levovist by two bolus at rest and at peak stress) was administered in 41. In all cases, second harmonic imaging and stress digitalisation pack was used. The agreement between observers showed a kappa index of 0.58 and 0.83 without and with contrast administration, respectively. The use of contrast agents provides a better agreement in the evaluation of stress echo between an experienced and a non-experienced observer in stress echo. Adding routinely contrast agents could probably reduce the number of exams required for the necessary learning curve in stress echocardiography.

The learning curve of the three-port two-instrument complete thoracoscopic lobectomy for lung cancer—A feasible technique worthy of popularization

Directory of Open Access Journals (Sweden)

Yu-Jen Cheng

2015-07-01

Conclusion: Three-port complete thoracoscopic lobectomy with the two-instrument technique is feasible for lung cancer treatment. The length of the learning curve consisted of 28 cases. This TPTI technique should be popularized.

Development Process and Technical Aspects of Laparoscopic Hepatectomy: Learning Curve Based on 15 Years of Experience.

Science.gov (United States)

Komatsu, Shohei; Scatton, Olivier; Goumard, Claire; Sepulveda, Ailton; Brustia, Raffaele; Perdigao, Fabiano; Soubrane, Olivier

2017-05-01

Laparoscopic hepatectomy continues to be a challenging operation associated with a steep learning curve. This study aimed to evaluate the learning process during 15 years of experience with laparoscopic hepatectomy and to identify approaches to standardization of this procedure. Prospectively collected data of 317 consecutive laparoscopic hepatectomies performed from January 2000 to December 2014 were reviewed retrospectively. The operative procedures were classified into 4 categories (minor hepatectomy, left lateral sectionectomy [LLS], left hepatectomy, and right hepatectomy), and indications were classified into 5 categories (benign-borderline tumor, living donor, metastatic liver tumor, biliary malignancy, and hepatocellular carcinoma). During the first 10 years, the procedures were limited mainly to minor hepatectomy and LLS, and the indications were limited to benign-borderline tumor and living donor. Implementation of major hepatectomy rapidly increased the proportion of malignant tumors, especially hepatocellular carcinoma, starting from 2011. Conversion rates decreased with experience for LLS (13.3% vs 3.4%; p = 0.054) and left hepatectomy (50.0% vs 15.0%; p = 0.012), but not for right hepatectomy (41.4% vs 35.7%; p = 0.661). Our 15-year experience clearly demonstrates the stepwise procedural evolution from LLS through left hepatectomy to right hepatectomy, as well as the trend in indications from benign-borderline tumor/living donor to malignant tumors. In contrast to LLS and left hepatectomy, a learning curve was not observed for right hepatectomy. The ongoing development process can contribute to faster standardization necessary for future advances in laparoscopic hepatectomy. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Experience Curves: A Tool for Energy Policy Assessment

Energy Technology Data Exchange (ETDEWEB)

Neij, Lena; Helby, Peter [Lund Univ. (Sweden). Environmental and Energy Systems Studies; Dannemand Andersen, Per; Morthorst, Poul Erik [Riso National Laboratory, Roskilde (Denmark); Durstewitz, Michael; Hoppe-Kilpper, Martin [Inst. fuer Solare Energieversorgungstechnik e.V., Kassel (DE); and others

2003-07-01

The objective of the project, Experience curves: a tool for energy policy assessment (EXTOOL), was to analyse the experience curve as a tool for the assessment of energy policy measures. This is of special interest, since the use of experience curves for the assessment of energy policy measures requires the development of the established experience curve methodology. This development raises several questions which have been addressed and analysed in this project. The analysis is based on case studies of wind power, an area with considerable experience in technology development, deployment and policy measures. Therefore, a case study based on wind power provides a good opportunity to study the usefulness of experience curves as a tool for the assessment of energy policy measures. However, the results are discussed in terms of using experience curves for the assessment of any energy technology. The project shows that experience curves can be used to assess the effect of combined policy measures in terms of cost reductions. Moreover, the result of the project show that experience curves could be used to analyse international 'learning systems', i.e. cost reductions brought about by the development of wind power and policy measures used in other countries. Nevertheless, the use of experience curves for the assessment of policy programmes has several limitations. First, the analysis and assessment of policy programmes cannot be achieved unless relevant experience curves based on good data can be developed. The authors are of the opinion that only studies that provide evidence of the validity, reliability and relevance of experience curves should be taken into account in policy making. Second, experience curves provide an aggregated picture of the situation and more detailed analysis of various sources of cost reduction, and cost reductions resulting from individual policy measures, requires additional data and analysis tools. Third, we do not recommend the use of

Deficits in verbal long-term memory and learning in children with poor phonological short-term memory skills.

Science.gov (United States)

Gathercole, Susan E; Briscoe, Josie; Thorn, Annabel; Tiffany, Claire

2008-03-01

Possible links between phonological short-term memory and both longer term memory and learning in 8-year-old children were investigated in this study. Performance on a range of tests of long-term memory and learning was compared for a group of 16 children with poor phonological short-term memory skills and a comparison group of children of the same age with matched nonverbal reasoning abilities but memory scores in the average range. The low-phonological-memory group were impaired on longer term memory and learning tasks that taxed memory for arbitrary verbal material such as names and nonwords. However, the two groups performed at comparable levels on tasks requiring the retention of visuo-spatial information and of meaningful material and at carrying out prospective memory tasks in which the children were asked to carry out actions at a future point in time. The results are consistent with the view that poor short-term memory function impairs the longer-term retention and ease of learning of novel verbal material.

A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs

International Nuclear Information System (INIS)

Smith, Sarah Josephine; Wei, Max; Sohn, Michael D.

2016-01-01

Experience curves are useful for understanding technology development and can aid in the design and analysis of market transformation programs. Here, we employ a novel approach to create experience curves, to examine both global and North American compact fluorescent lamp (CFL) data for the years 1990–2007. We move away from the prevailing method of fitting a single, constant, exponential curve to data and instead search for break points where changes in the learning rate may have occurred. Our analysis suggests a learning rate of approximately 21% for the period of 1990–1997, and 51% and 79% in global and North American datasets, respectively, after 1998. We use price data for this analysis; therefore our learning rates encompass developments beyond typical “learning by doing”, including supply chain impacts such as market competition. We examine correlations between North American learning rates and the initiation of new programs, abrupt technological advances, and economic and political events, and find an increased learning rate associated with design advancements and federal standards programs. Our findings support the use of segmented experience curves for retrospective and prospective technology analysis, and may imply that investments in technology programs have contributed to an increase of the CFL learning rate. - Highlights: • We develop a segmented regression technique to estimate historical CFL learning curves. • CFL experience curves do not have a constant learning rate. • CFLs exhibited a learning rate of approximately 21% from 1990 to 1997. • The CFL learning rate significantly increased after 1998. • Increased CFL learning rate is correlated to technology deployment programs.

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

Science.gov (United States)

Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

2017-01-01

The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.

Impact of cap-assisted colonoscopy on the learning curve and quality in colonoscopy: a randomized controlled trial.

Science.gov (United States)

Tang, Zhouwen; Zhang, Daniel S; Thrift, Aaron P; Patel, Kalpesh K

2018-03-01

Colonoscopy competency assessment in trainees traditionally has been informal. Comprehensive metrics such as the Assessment of Competency in Endoscopy (ACE) tool suggest that competency thresholds are higher than assumed. Cap-assisted colonoscopy (CAC) may improve competency, but data regarding novice trainees are lacking. We compared CAC versus standard colonoscopy (SC) performed by novice trainees in a randomized controlled trial. All colonoscopies performed by 3 gastroenterology fellows without prior experience were eligible for the study. Exclusion criteria included patient age 90 years, pregnancy, prior colon resection, diverticulitis, colon obstruction, severe hematochezia, referral for EMR, or a procedure done without patient sedation. Patients were randomized to either CAC or SC in a 1:1 fashion. The primary outcome was the independent cecal intubation rate (ICIR). Secondary outcomes were cecal intubation time, polyp detection rate, polyp miss rate, adenoma detection rate, ACE tool scores, and cumulative summation learning curves. A total of 203 colonoscopies were analyzed, 101 in CAC and 102 in SC. CAC resulted in a significantly higher cecal intubation rate, at 79.2% in CAC compared with 66.7% in SC (P = .04). Overall cecal intubation time was significantly shorter at 13.7 minutes for CAC versus 16.5 minutes for SC (P =.02). Cecal intubation time in the case of successful independent fellow intubation was not significantly different between CAC and SC (11.6 minutes vs 12.7 minutes; P = .29). Overall ACE tool motor and cognitive scores were higher with CAC. Learning curves for ICIR approached the competency threshold earlier with cap use but reached competency for only 1 fellow. The polyp detection rate, polyp miss rate, and adenoma detection rate were not significantly different between groups. CAC resulted in significant improvement in ICIR, overall ACE tool scores, and trend toward competency on learning curves when compared with SC in colonoscopy

Development of the Mathematics of Learning Curve Models for Evaluating Small Modular Reactor Economics

Energy Technology Data Exchange (ETDEWEB)

Harrison, T. J. [ORNL

2014-02-01

The cost of nuclear power is a straightforward yet complicated topic. It is straightforward in that the cost of nuclear power is a function of the cost to build the nuclear power plant, the cost to operate and maintain it, and the cost to provide fuel for it. It is complicated in that some of those costs are not necessarily known, introducing uncertainty into the analysis. For large light water reactor (LWR)-based nuclear power plants, the uncertainty is mainly contained within the cost of construction. The typical costs of operations and maintenance (O&M), as well as fuel, are well known based on the current fleet of LWRs. However, the last currently operating reactor to come online was Watts Bar 1 in May 1996; thus, the expected construction costs for gigawatt (GW)-class reactors in the United States are based on information nearly two decades old. Extrapolating construction, O&M, and fuel costs from GW-class LWRs to LWR-based small modular reactors (SMRs) introduces even more complication. The per-installed-kilowatt construction costs for SMRs are likely to be higher than those for the GW-class reactors based on the property of the economy of scale. Generally speaking, the economy of scale is the tendency for overall costs to increase slower than the overall production capacity. For power plants, this means that doubling the power production capacity would be expected to cost less than twice as much. Applying this property in the opposite direction, halving the power production capacity would be expected to cost more than half as much. This can potentially make the SMRs less competitive in the electricity market against the GW-class reactors, as well as against other power sources such as natural gas and subsidized renewables. One factor that can potentially aid the SMRs in achieving economic competitiveness is an economy of numbers, as opposed to the economy of scale, associated with learning curves. The basic concept of the learning curve is that the more a

Search for the signatures of a new-born black hole from the collapse of a supra-massive millisecond magnetar in short GRB light curves

Science.gov (United States)

Zhang, Q.; Lei, W. H.; Zhang, B. B.; Chen, W.; Xiong, S. L.; Song, L. M.

2018-03-01

`Internal plateau' followed by a sharp decay is commonly seen in short gamma-ray burst (GRB) light curves. The plateau component is usually interpreted as the dipole emission from a supra-massive magnetar, and the sharp decay may imply the collapse of the magnetar to a black hole (BH). Fall-back accretion on to the new-born BH could produce long-lasting activities via the Blandford-Znajek (BZ) process. The magnetic flux accumulated near the BH would be confined by the accretion discs for a period of time. As the accretion rate decreases, the magnetic flux is strong enough to obstruct gas infall, leading to a magnetically arrested disc. Within this scenario, we show that the BZ process could produce two types of typical X-ray light curves: type I exhibits a long-lasting plateau, followed by a power-law (PL) decay with slopes ranging from 5/3 to 40/9; type II shows roughly a single PL decay with a slope of 5/3. The former requires low magnetic field strength, while the latter corresponds to relatively high values. We search for such signatures of the new-born BH from a sample of short GRBs with an internal plateau, and find two candidates: GRB 101219A and GRB 160821B, corresponding to type II and type I light curves, respectively. It is shown that our model can explain the data very well.

The Impact of Learning Curve Model Selection and Criteria for Cost Estimation Accuracy in the DoD

Science.gov (United States)

2016-04-30

different in the future due to machines” • Heightened scrutiny of cost estimates • Budget Control Act of 2011 seeks to reduce federal deficit ...qÜáêíÉÉåíÜ=^ååì~ä= ^Åèìáëáíáçå=oÉëÉ~êÅÜ= póãéçëáìã= qÜìêëÇ~ó=pÉëëáçåë= sçäìãÉ=ff= = The Impact of Learning Curve Model Selection and Criteria for Cost...Assistant Division Director, Institute for Defense Analyses Bruce Harmon, Research Staff Member, Institute for Defense Analyses The Impact of Learning

Taking the brakes off the learning curve.

Science.gov (United States)

Gheysen, Freja; Lasne, Gabriel; Pélégrini-Issac, Mélanie; Albouy, Genevieve; Meunier, Sabine; Benali, Habib; Doyon, Julien; Popa, Traian

2017-03-01

Motor learning is characterized by patterns of cerebello-striato-cortical activations shifting in time, yet the early dynamic and function of these activations remains unclear. Five groups of subjects underwent either continuous or intermittent theta-burst stimulation of one cerebellar hemisphere, or no stimulation just before learning a new motor sequence during fMRI scanning. We identified three phases during initial learning: one rapid, one slow, and one quasi-asymptotic performance phase. These phases were not changed by left cerebellar stimulation. Right cerebellar inhibition, however, accelerated learning and enhanced brain activation in critical motor learning-related areas during the first phase, continuing with reduced brain activation but high-performance in late phase. Right cerebellar excitation did not affect the early learning process, but slowed learning significantly in late phase, along with increased brain activation. We conclude that the right cerebellum is a key factor coordinating other neuronal loops in the early acquisition of an explicit motor sequential skill. Hum Brain Mapp 38:1676-1691, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The learning curve to achieve satisfactory completion rates in upper GI endoscopy: an analysis of a national training database.

Science.gov (United States)

Ward, S T; Hancox, A; Mohammed, M A; Ismail, T; Griffiths, E A; Valori, R; Dunckley, P

2017-06-01

The aim of this study was to determine the number of OGDs (oesophago-gastro-duodenoscopies) trainees need to perform to acquire competency in terms of successful unassisted completion to the second part of the duodenum 95% of the time. OGD data were retrieved from the trainee e-portfolio developed by the Joint Advisory Group on GI Endoscopy (JAG) in the UK. All trainees were included unless they were known to have a baseline experience of >20 procedures or had submitted data for 90% trainees had attained a 95% completion rate. Total number of OGDs performed, trainee age and experience in lower GI endoscopy were factors independently associated with OGD completion. There are limited published data on the OGD learning curve. This is the largest study to date analysing the learning curve for competency acquisition. The JAG competency requirement for 200 procedures appears appropriate. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Super-quantum curves from super-eigenvalue models

Energy Technology Data Exchange (ETDEWEB)

Ciosmak, Paweł [Faculty of Mathematics, Informatics and Mechanics, University of Warsaw,ul. Banacha 2, 02-097 Warsaw (Poland); Hadasz, Leszek [M. Smoluchowski Institute of Physics, Jagiellonian University,ul. Łojasiewicza 11, 30-348 Kraków (Poland); Manabe, Masahide [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Sułkowski, Piotr [Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Walter Burke Institute for Theoretical Physics, California Institute of Technology,1200 E. California Blvd, Pasadena, CA 91125 (United States)

2016-10-10

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Super-quantum curves from super-eigenvalue models

International Nuclear Information System (INIS)

Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr

2016-01-01

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Super-quantum curves from super-eigenvalue models

Science.gov (United States)

Ciosmak, Paweł; Hadasz, Leszek; Manabe, Masahide; Sułkowski, Piotr

2016-10-01

In modern mathematical and theoretical physics various generalizations, in particular supersymmetric or quantum, of Riemann surfaces and complex algebraic curves play a prominent role. We show that such supersymmetric and quantum generalizations can be combined together, and construct supersymmetric quantum curves, or super-quantum curves for short. Our analysis is conducted in the formalism of super-eigenvalue models: we introduce β-deformed version of those models, and derive differential equations for associated α/ β-deformed super-matrix integrals. We show that for a given model there exists an infinite number of such differential equations, which we identify as super-quantum curves, and which are in one-to-one correspondence with, and have the structure of, super-Virasoro singular vectors. We discuss potential applications of super-quantum curves and prospects of other generalizations.

Evaluation of learning curves for ovariohysterectomy of dogs and cats and castration of dogs.

Science.gov (United States)

Freeman, Lynetta J; Ferguson, Nancy; Fellenstein, Carol; Johnson, Ron; Constable, Peter D

2017-08-01

OBJECTIVE To define learning curves for fourth-year veterinary students performing ovariohysterectomy procedures in dogs and cats and castration in dogs. DESIGN Retrospective study. SAMPLE 3,196 ovariohysterectomies or castrations performed in dogs and cats by 88 veterinary students during a spay-neuter surgery and animal shelter rotation (n = 3,056) or by 1 experienced general practitioner (n = 140). PROCEDURES Data collected from medical records included patient signalment, type and duration of procedure, and sequence (by date and time) of the procedure within a list of procedures of the same type generated for each student. For each procedure type, geometric mean surgery time and 95% confidence intervals were determined for each number of surgeries completed by ≥ 10 students. Median surgery times for the same procedure types were determined for the experienced practitioner. The learning curve for each procedure was modeled with nonlinear (3-factor exponential equation with a nonzero asymptote) and linear regression. For each procedure, the asymptote (optimal surgery time) for students was compared with the experienced practitioner's median surgery time. RESULTS 2,945 surgeries (mean, 33/student) performed by ≥ 10 students were analyzed. Surgery time decreased in a nonlinear manner as student experience increased for castration of adult or pediatric dogs and ovariohysterectomy of pediatric dogs and adult or pediatric cats. Surgery time decreased in a linear manner as experience increased for ovariohysterectomy of adult dogs. CONCLUSIONS AND CLINICAL RELEVANCE To the authors' knowledge, this was the first study to map surgery times for common surgical procedures consecutively performed by veterinary students. Results clearly indicated the value of repetition to improve surgical skills (as measured by surgery time) during a 3-week period.

Effects of Pathologic Stage on the Learning Curve for Radical Prostatectomy: Evidence That Recurrence in Organ-Confined Cancer Is Largely Related to Inadequate Surgical Technique

Science.gov (United States)

Vickers, Andrew J.; Bianco, Fernando J.; Gonen, Mithat; Cronin, Angel M.; Eastham, James A.; Schrag, Deborah; Klein, Eric A.; Reuther, Alwyn M.; Kattan, Michael W.; Pontes, J. Edson; Scardino, Peter T.

2008-01-01

Objectives We previously demonstrated that there is a learning curve for open radical prostatectomy. We sought to determine whether the effects of the learning curve are modified by pathologic stage. Methods The study included 7765 eligible prostate cancer patients treated with open radical prostatectomy by one of 72 surgeons. Surgeon experience was coded as the total number of radical prostatectomies conducted by the surgeon prior to a patient’s surgery. Multivariable regression models of survival time were used to evaluate the association between surgeon experience and biochemical recurrence, with adjustment for PSA, stage, and grade. Analyses were conducted separately for patients with organ-confined and locally advanced disease. Results Five-year recurrence-free probability for patients with organ-confined disease approached 100% for the most experienced surgeons. Conversely, the learning curve for patients with locally advanced disease reached a plateau at approximately 70%, suggesting that about a third of these patients cannot be cured by surgery alone. Conclusions Excellent rates of cancer control for patients with organ-confined disease treated by the most experienced surgeons suggest that the primary reason such patients recur is inadequate surgical technique. PMID:18207316

The future role of photovoltaics: A learning curve versus portfolio perspective

International Nuclear Information System (INIS)

Albrecht, Johan

2007-01-01

The current cost disadvantage of photovoltaics (PV) risks to reduce its relevance in climate policy strategies. Depending on the used assumptions, electricity from PV can become competitive between 2015 and 2040. Cost competitiveness is, however, a conditional criterion and as an alternative to the learning curve perspective, the future role of PV in electricity production is assessed from a portfolio theory or Capital Asset Pricing Model perspective. In this analysis, the focus is on the input price risks. Fossil fuel price volatility can strongly reduce the financial return of conventional generating technologies. From a welfare perspective, energy planners should try to minimise this risk by adding risk-neutral or no-risk technologies to their portfolio. With an analysis for the year 2025, we illustrate how the addition of renewable capacity to an existing portfolio can lower total portfolio risk without a significant reduction of profitability. PV then emerges as an attractive technology, especially once the best locations for wind energy are already developed

The future role of photovoltaics: a learning curve versus portfolio perspective

International Nuclear Information System (INIS)

Albrecht, J.

2007-01-01

The current cost disadvantage of photovoltaics (PV) risks to reduce its relevance in climate policy strategies. Depending on the used assumptions, electricity from PV can become competitive between 2015 and 2040. Cost competitiveness is, however, a conditional criterion and as an alternative to the learning curve perspective, the future role of PV in electricity production is assessed from a portfolio theory or Capital Asset Pricing Model perspective. In this analysis, the focus is on the input price risks. Fossil fuel price volatility can strongly reduce the financial return of conventional generating technologies. From a welfare perspective, energy planners should try to minimise this risk by adding risk-neutral or no-risk technologies to their portfolio. With an analysis for the year 2025, we illustrate how the addition of renewable capacity to an existing portfolio can lower total portfolio risk without a significant reduction of profitability. PV then emerges as an attractive technology, especially once the best locations for wind energy are already developed. (author)

Learning from the Sun. Analysis of the use of experience curves for energy policy purposes. The case of photovoltaic power. Final report of the Photex project

International Nuclear Information System (INIS)

Schaeffer, G.J.; Seebregts, A.J.; Beurskens, L.W.M.; De Moor, H.H.C.; Alsema, E.; Sark, W.; Durstewicz, M.; Perrin, M.; Boulanger, P.; Laukamp, H.; Zuccaro, C.

2004-08-01

Since the 1990s energy policy scientists have started to explore the possibilities of using the experience curve approach for energy policy making. The concept of the experience curve is simple, at least in principle. It states that, for every doubling of cumulative produced capacity of a product or technology, the cost for making it declines with a fixed percentage (learning rate). Historical statistical analysis can be used to define this percentage. Extrapolating the trend thus found, into the future will then give relevant information about future cost developments and will also give information how much 'learning money' will be needed to get to the break-even point. The Photex project used the development of solar PV as a case to further explore this approach, and also to deduce lessons for PV policy. Other aims were to look at learning rates of the different components of PV-systems and to combine the experience curve analyses with bottom-up engineering studies. The main conclusion with regard to the use of experience curves for energy policy making is that this is an interesting approach, but that such an analysis should be done with much care. For the historical analysis the availability of reliable and firm data is essential. As cost data often are not available, price data could be used as a proxy, as long as sufficient long time ranges are used. Also, the analyst should take care he considers the right learning system boundaries. Furthermore the number of years to be included in the statistical analysis should at least be 10 years and this period sample should not over-represent stable price periods or periods of steep price decline. If possible, data uncertainties should be taken into account as well. An interesting finding was that, at least in the case of PV, the learning rate is not a constant, but can vary over time. In the case of PV it improved from 20% to 23%. Extrapolations into the future should take uncertainties into account and always be

Implications Of Aggregate Demand Elasticity For The Phillips Curve

OpenAIRE

Ben L. Kyer; Gary E. Maggs

2004-01-01

While the general relationship between the aggregate supply curve and the Phillips curve is recognized, the importance of aggregate demand and, in particular, aggregate demand elasticity, for the inflation-unemployment relationship has been untreated. We believe, however, that the elasticity of aggregate demand with respect to the general price level does have some significance for the short-run Phillips curve since, on a general level, the economy's equilibrium price level, inflation rate, r...

The learning curve of laparoscopic treatment of rectal cancer does not increase morbidity.

Science.gov (United States)

Luján, Juan; Gonzalez, Antonio; Abrisqueta, Jesús; Hernandez, Quiteria; Valero, Graciela; Abellán, Israel; Frutos, María Dolores; Parrilla, Pascual

2014-01-01

The treatment of rectal cancer via laparoscopy is controversial due to its technical complexity. Several randomized prospective studies have demonstrated clear advantages for the patient with similar oncological results to those of open surgery, although during the learning of this surgical technique there may be an increase in complications and a worse prognosis. Our aim is to analyze how the learning curve for rectal cancer via laparoscopy influences intra- and postoperative results and oncological markers. A retrospective review was conducted of the first 120 patients undergoing laparoscopic surgery for rectal neoplasia. The operations were performed by the same surgical team with a wide experience in the treatment of open colorectal cancer and qualified to perform advanced laparoscopic surgery. We analyzed sex, ASA, tumour location, neoadjuvant treatment, surgical technique, operating time, conversion, postoperative complications, length of hospital stay, number of lymph nodes, stage and involvement of margins. Significant differences were observed with regard to surgical time (224 min in the first group, 204 min in the second group), with a higher rate of conversion in the first group (22.5%) than in the second (11.3%). No significant differences were noted for rate of conservative sphincter surgery, length of hospital stay, post-surgical complications, number of affected/isolated lymph nodes or affected circumferential and distal margins. It is possible to learn this complex surgical technique without compromising the patient's safety and oncological outcome. Copyright © 2013 AEC. Published by Elsevier Espana. All rights reserved.

A randomized control trial to evaluate the importance of pre-training basic laparoscopic psychomotor skills upon the learning curve of laparoscopic intra-corporeal knot tying.

Science.gov (United States)

Molinas, Carlos Roger; Binda, Maria Mercedes; Sisa, Cesar Manuel; Campo, Rudi

2017-01-01

Training of basic laparoscopic psychomotor skills improves the acquisition of more advanced laparoscopic tasks, such as laparoscopic intra-corporeal knot tying (LICK). This randomized controlled trial was designed to evaluate whether pre-training of basic skills, as laparoscopic camera navigation (LCN), hand-eye coordination (HEC), and bimanual coordination (BMC), and the combination of the three of them, has any beneficial effect upon the learning curve of LICK. The study was carried out in a private center in Asunción, Paraguay, by 80 medical students without any experience in surgery. Four laparoscopic tasks were performed in the ENCILAP model (LCN, HEC, BMC, and LICK). Participants were allocated to 5 groups (G1-G5). The study was structured in 5 phases. In phase 1, they underwent a base-line test ( T 1 ) for all tasks (1 repetition of each task in consecutive order). In phase 2, participants underwent different training programs (30 consecutive repetitions) for basic tasks according to the group they belong to (G1: none; G2: LCN; G3: HEC; G4: BMC; and G5: LCN, HEC, and BMC). In phase 3, they were tested again ( T 2 ) in the same manner than at T 1 . In phase 4, they underwent a standardized training program for LICK (30 consecutive repetitions). In phase 5, they were tested again ( T 3 ) in the same manner than at T 1 and T 2 . At each repetition, scoring was based on the time taken for task completion system. The scores were plotted and non-linear regression models were used to fit the learning curves to one- and two-phase exponential decay models for each participant (individual curves) and for each group (group curves). The LICK group learning curves fitted better to the two-phase exponential decay model. From these curves, the starting points ( Y 0), the point after HEC training/before LICK training ( Y 1), the Plateau, and the rate constants ( K ) were calculated. All groups, except for G4, started from a similar point ( Y 0). At Y 1, G5 scored already

CSI 2264: CHARACTERIZING YOUNG STARS IN NGC 2264 WITH SHORT-DURATION PERIODIC FLUX DIPS IN THEIR LIGHT CURVES

Energy Technology Data Exchange (ETDEWEB)

Stauffer, John; Cody, Ann Marie; Rebull, Luisa; Plavchan, Peter; Carey, Sean [Spitzer Science Center, California Institute of Technology, Pasadena, CA 91125 (United States); McGinnis, Pauline; Alencar, Silvia H. P. [Departamento de Física—ICEx—UFMG, Av. Antônio Carlos, 6627, 30270-901, Belo Horizonte, MG (Brazil); Hillenbrand, Lynne A.; Carpenter, John [Astronomy Department, California Institute of Technology, Pasadena, CA 91125 (United States); Turner, Neal J. [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States); Terebey, Susan [Department of Physics and Astronomy, 5151 State University Drive, California State University at Los Angeles, Los Angeles, CA 90032 (United States); Morales-Calderón, María [Centro de Astrobiología, Dpto. de Astrofísica, INTA-CSIC, PO BOX 78, E-28691, ESAC Campus, Villanueva de la Cañada, Madrid (Spain); Bouvier, Jerome; Venuti, Laura [Université de Grenoble, Institut de Planétologie et d’Astrophysique de Grenoble (IPAG), F-38000 Grenoble (France); CNRS, IPAG, F-38000 Grenoble (France); Hartmann, Lee; Calvet, Nuria [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48105 (United States); Micela, Giusi; Flaccomio, Ettore [INAF—Osservatorio Astronomico di Palermo, Piazza del Parlamento 1, I-90134, Palermo (Italy); Song, Inseok [Department of Physics and Astronomy, The University of Georgia, Athens, GA 30602–2451 (United States); Gutermuth, Rob, E-mail: stauffer@ipac.caltech.edu [Department of Astronomy, University of Massachusetts, Amherst, MA 01003 (United States); and others

2015-04-15

We identify nine young stellar objects (YSOs) in the NGC 2264 star-forming region with optical CoRoT light curves exhibiting short-duration, shallow periodic flux dips. All of these stars have infrared excesses that are consistent with their having inner disk walls near the Keplerian co-rotation radius. The repeating photometric dips have FWHMs generally less than 1 day, depths almost always less than 15%, and periods (3 < P < 11 days) consistent with dust near the Keplerian co-rotation period. The flux dips vary considerably in their depth from epoch to epoch, but usually persist for several weeks and, in two cases, were present in data collected in successive years. For several of these stars, we also measure the photospheric rotation period and find that the rotation and dip periods are the same, as predicted by standard “disk-locking” models. We attribute these flux dips to clumps of material in or near the inner disk wall, passing through our line of sight to the stellar photosphere. In some cases, these dips are also present in simultaneous Spitzer IRAC light curves at 3.6 and 4.5 microns. We characterize the properties of these dips, and compare the stars with light curves exhibiting this behavior to other classes of YSOs in NGC 2264. A number of physical mechanisms could locally increase the dust scale height near the inner disk wall, and we discuss several of those mechanisms; the most plausible mechanisms are either a disk warp due to interaction with the stellar magnetic field or dust entrained in funnel-flow accretion columns arising near the inner disk wall.

CSI 2264: CHARACTERIZING YOUNG STARS IN NGC 2264 WITH SHORT-DURATION PERIODIC FLUX DIPS IN THEIR LIGHT CURVES

International Nuclear Information System (INIS)

Stauffer, John; Cody, Ann Marie; Rebull, Luisa; Plavchan, Peter; Carey, Sean; McGinnis, Pauline; Alencar, Silvia H. P.; Hillenbrand, Lynne A.; Carpenter, John; Turner, Neal J.; Terebey, Susan; Morales-Calderón, María; Bouvier, Jerome; Venuti, Laura; Hartmann, Lee; Calvet, Nuria; Micela, Giusi; Flaccomio, Ettore; Song, Inseok; Gutermuth, Rob

2015-01-01

We identify nine young stellar objects (YSOs) in the NGC 2264 star-forming region with optical CoRoT light curves exhibiting short-duration, shallow periodic flux dips. All of these stars have infrared excesses that are consistent with their having inner disk walls near the Keplerian co-rotation radius. The repeating photometric dips have FWHMs generally less than 1 day, depths almost always less than 15%, and periods (3 < P < 11 days) consistent with dust near the Keplerian co-rotation period. The flux dips vary considerably in their depth from epoch to epoch, but usually persist for several weeks and, in two cases, were present in data collected in successive years. For several of these stars, we also measure the photospheric rotation period and find that the rotation and dip periods are the same, as predicted by standard “disk-locking” models. We attribute these flux dips to clumps of material in or near the inner disk wall, passing through our line of sight to the stellar photosphere. In some cases, these dips are also present in simultaneous Spitzer IRAC light curves at 3.6 and 4.5 microns. We characterize the properties of these dips, and compare the stars with light curves exhibiting this behavior to other classes of YSOs in NGC 2264. A number of physical mechanisms could locally increase the dust scale height near the inner disk wall, and we discuss several of those mechanisms; the most plausible mechanisms are either a disk warp due to interaction with the stellar magnetic field or dust entrained in funnel-flow accretion columns arising near the inner disk wall

From curve fitting to machine learning an illustrative guide to scientific data analysis and computational intelligence

CERN Document Server

Zielesny, Achim

2016-01-01

This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence. All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with M...

Playing off the curve - testing quantitative predictions of skill acquisition theories in development of chess performance.

Science.gov (United States)

Gaschler, Robert; Progscha, Johanna; Smallbone, Kieran; Ram, Nilam; Bilalić, Merim

2014-01-01

Learning curves have been proposed as an adequate description of learning processes, no matter whether the processes manifest within minutes or across years. Different mechanisms underlying skill acquisition can lead to differences in the shape of learning curves. In the current study, we analyze the tournament performance data of 1383 chess players who begin competing at young age and play tournaments for at least 10 years. We analyze the performance development with the goal to test the adequacy of learning curves, and the skill acquisition theories they are based on, for describing and predicting expertise acquisition. On the one hand, we show that the skill acquisition theories implying a negative exponential learning curve do a better job in both describing early performance gains and predicting later trajectories of chess performance than those theories implying a power function learning curve. On the other hand, the learning curves of a large proportion of players show systematic qualitative deviations from the predictions of either type of skill acquisition theory. While skill acquisition theories predict larger performance gains in early years and smaller gains in later years, a substantial number of players begin to show substantial improvements with a delay of several years (and no improvement in the first years), deviations not fully accounted for by quantity of practice. The current work adds to the debate on how learning processes on a small time scale combine to large-scale changes.

Augmented Reality in Informal Learning Environments: Investigating Short-term and Long-term Effects

DEFF Research Database (Denmark)

Sommerauer, Peter; Müller, Oliver

2018-01-01

field experiment with 24 participants at a mathematics exhibition to measure the effect of AR on acquiring and retaining mathematical knowledge in an informal learning environment, both short-term (i.e., directly after visiting the exhibition) and long-term (i.e., two months after the museum visit). Our...

Establishing the minimal number of virtual reality simulator training sessions necessary to develop basic laparoscopic skills competence: evaluation of the learning curve

Directory of Open Access Journals (Sweden)

Ricardo Jordao Duarte

2013-09-01

Full Text Available Introduction Medical literature is scarce on information to define a basic skills training program for laparoscopic surgery (peg and transferring, cutting, clipping. The aim of this study was to determine the minimal number of simulator sessions of basic laparoscopic tasks necessary to elaborate an optimal virtual reality training curriculum. Materials and Methods Eleven medical students with no previous laparoscopic experience were spontaneously enrolled. They were submitted to simulator training sessions starting at level 1 (Immersion Lap VR, San Jose, CA, including sequentially camera handling, peg and transfer, clipping and cutting. Each student trained twice a week until 10 sessions were completed. The score indexes were registered and analyzed. The total of errors of the evaluation sequences (camera, peg and transfer, clipping and cutting were computed and thereafter, they were correlated to the total of items evaluated in each step, resulting in a success percent ratio for each student for each set of each completed session. Thereafter, we computed the cumulative success rate in 10 sessions, obtaining an analysis of the learning process. By non-linear regression the learning curve was analyzed. Results By the non-linear regression method the learning curve was analyzed and a r2 = 0.73 (p < 0.001 was obtained, being necessary 4.26 (∼five sessions to reach the plateau of 80% of the estimated acquired knowledge, being that 100% of the students have reached this level of skills. From the fifth session till the 10th, the gain of knowledge was not significant, although some students reached 96% of the expected improvement. Conclusions This study revealed that after five simulator training sequential sessions the students' learning curve reaches a plateau. The forward sessions in the same difficult level do not promote any improvement in laparoscopic basic surgical skills, and the students should be introduced to a more difficult training

Establishing the minimal number of virtual reality simulator training sessions necessary to develop basic laparoscopic skills competence: evaluation of the learning curve.

Science.gov (United States)

Duarte, Ricardo Jordão; Cury, José; Oliveira, Luis Carlos Neves; Srougi, Miguel

2013-01-01

Medical literature is scarce on information to define a basic skills training program for laparoscopic surgery (peg and transferring, cutting, clipping). The aim of this study was to determine the minimal number of simulator sessions of basic laparoscopic tasks necessary to elaborate an optimal virtual reality training curriculum. Eleven medical students with no previous laparoscopic experience were spontaneously enrolled. They were submitted to simulator training sessions starting at level 1 (Immersion Lap VR, San Jose, CA), including sequentially camera handling, peg and transfer, clipping and cutting. Each student trained twice a week until 10 sessions were completed. The score indexes were registered and analyzed. The total of errors of the evaluation sequences (camera, peg and transfer, clipping and cutting) were computed and thereafter, they were correlated to the total of items evaluated in each step, resulting in a success percent ratio for each student for each set of each completed session. Thereafter, we computed the cumulative success rate in 10 sessions, obtaining an analysis of the learning process. By non-linear regression the learning curve was analyzed. By the non-linear regression method the learning curve was analyzed and a r2 = 0.73 (p sessions) to reach the plateau of 80% of the estimated acquired knowledge, being that 100% of the students have reached this level of skills. From the fifth session till the 10th, the gain of knowledge was not significant, although some students reached 96% of the expected improvement. This study revealed that after five simulator training sequential sessions the students' learning curve reaches a plateau. The forward sessions in the same difficult level do not promote any improvement in laparoscopic basic surgical skills, and the students should be introduced to a more difficult training tasks level.

Retrospective North American CFL Experience Curve Analysis and Correlation to Deployment Programs

Energy Technology Data Exchange (ETDEWEB)

Smith, Sarah J. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Wei, Max [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sohn, Michael D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-07-01

Retrospective experience curves are a useful tool for understanding historic technology development, and can contribute to investment program analysis and future cost estimation efforts. This work documents our development of an analysis approach for deriving retrospective experience curves with a variable learning rate, and its application to develop an experience curve for compact fluorescent lamps for the global and North American markets over the years 1990-2007. Uncertainties and assumptions involved in interpreting data for our experience curve development are discussed, including the processing and transformation of empirical data, the selection of system boundaries, and the identification of historical changes in the learning rate over the course of 15 years. In the results that follow, we find that that the learning rate has changed at least once from 1990-2007. We also explore if, and to what degree, public deployment programs may have contributed to an increased technology learning rate in North America. We observe correlations between the changes in the learning rate and the initiation of new policies, abrupt technological advances, including improvements to ballast technology, and economic and political events such as trade tariffs and electricity prices. Finally, we discuss how the findings of this work (1) support the use of segmented experience curves for retrospective and prospective analysis and (2) may imply that investments in technological research and development have contributed to a change in market adoption and penetration.

Fluoroscopy Learning Curve in Hip Arthroscopy-A Single Surgeon's Experience.

Science.gov (United States)

Smith, Kevin M; Duplantier, Neil L; Crump, Kimbelyn H; Delgado, Domenica A; Sullivan, Stephanie L; McCulloch, Patrick C; Harris, Joshua D

2017-10-01

To determine if (1) absorbed radiation dose and (2) fluoroscopy time decreased with experience over the first 100 cases of a single surgeon's hip arthroscopy practice. Subjects who underwent hip arthroscopy for symptomatic femoroacetabular impingement and labral injury were eligible for analysis. Inclusion criteria included the first 100 subjects who underwent hip arthroscopy by a single surgeon (December 2013 to December 2014). Subject demographics, procedure details, fluoroscopy absorbed dose (milligray [mGy]), and time were recorded. Subjects were categorized by date of surgery to one of 4 possible groups (25 per group). One-way analysis of variance was used to determine if a significant difference in dose (mGy) or time was present between groups. Simple linear regression analysis was performed to determine the relation between case number and both radiation dose and fluoroscopy time. Subjects underwent labral repair (n = 93), cam osteoplasty (n = 90), and pincer acetabuloplasty (n = 65). There was a significant (P arthroscopy practice learning curve. Level IV, therapeutic, retrospective, noncomparative case series. Copyright © 2017 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

The Roles of Phonological Short-Term Memory and Working Memory in L2 Grammar and Vocabulary Learning

Science.gov (United States)

Martin, Katherine I.; Ellis, Nick C.

2012-01-01

This study analyzed phonological short-term memory (PSTM) and working memory (WM) and their relationship with vocabulary and grammar learning in an artificial foreign language. Nonword repetition, nonword recognition, and listening span were used as memory measures. Participants learned the singular forms of vocabulary for an artificial foreign…

The Learning Curve in neurofeedback of Peter Van Deusen: A review article

Directory of Open Access Journals (Sweden)

Valdenilson Ribeiro Ribas

Full Text Available ABSTRACT The Learning Curve (TLC in neurofeedback concept emerged after Peter Van Deusen compiled the results of articles on the expected electrical activity of the brain. This concept was subsequently tested on patients at four clinics in Atlanta between 1994 and 2001. The aim of this paper was to report the historical aspects of TLC. Articles published on the electronic databases MEDLINE/PubMed and Web of Science were reviewed. During patient evaluation, TLC investigates categories called disconnected, hot temporal lobes, reversal of alpha and beta waves, blocking, locking, and filtering or processing. This enables neuroscientists to use their training designs and, by means of behavioral psychology, to work on neuroregulation, as self-regulation for patients. TLC shows the relationships between electrical, mental and behavioral activity in patients. It also identifies details of patterns that can assist physicians in their choice of treatment.

The New Keynesian Phillips Curve

DEFF Research Database (Denmark)

Ólafsson, Tjörvi

This paper provides a survey on the recent literature on the new Keynesian Phillips curve: the controversies surrounding its microfoundation and estimation, the approaches that have been tried to improve its empirical fit and the challenges it faces adapting to the open-economy framework. The new......, learning or state-dependant pricing. The introduction of openeconomy factors into the new Keynesian Phillips curve complicate matters further as it must capture the nexus between price setting, inflation and the exchange rate. This is nevertheless a crucial feature for any model to be used for inflation...... forecasting in a small open economy like Iceland....

How Good Is Good: Improved Tracking and Managing of Safety Goals, Performance Indicators, Production Targets and Significant Events Using Learning Curves

International Nuclear Information System (INIS)

Duffey, Rommey B.; Saull, John W.

2002-01-01

We show a new way to track and measure safety and performance using learning curves derived on a mathematical basis. When unusual or abnormal events occur in plants and equipment, the regulator and good management practice requires they be reported, investigated, understood and rectified. In addition to reporting so-called 'significant events', both management and the regulator often set targets for individual and collective performance, which are used for both reward and criticism. For almost completely safe systems, like nuclear power plants, commercial aircraft and chemical facilities, many parameters are tracked and measured. Continuous improvement has to be demonstrated, as well as meeting reduced occurrence rates, which are set as management goals or targets. This process usually takes the form of statistics for availability of plant and equipment, forced or unplanned maintenance outage, loss of safety function, safety or procedural violations, etc. These are often rolled up into a set of so-called 'Performance Indicators' as measures of how well safety and operation is being managed at a given facility. The overall operating standards of an industry are also measured. A whole discipline is formed of tracking, measuring, reporting, managing and understanding the plethora of indicators and data. Decreasing occurrence rates and meeting or exceeding goals are seen and rewarded as virtues. Managers and operators need to know how good is their safety management system that has been adopted and used (and paid for), and whether it can itself be improved. We show the importance of accumulated experience in correctly measuring and tracking the decreasing event and error rates speculating a finite minimum rate. We show that the rate of improvement constitutes a measurable 'learning curve', and the attainment of the goals and targets can be affected by the adopted measures. We examine some of the available data on significant events, reportable occurrences, and loss of

Auditory verbal learning in drug-free Ecstasy polydrug users.

Science.gov (United States)

Fox, H. C.; Toplis, A. S.; Turner, J. J. D.; Parrott, A. C.

2001-12-01

Drug-free Ecstasy polydrug users have shown impairment on tasks of verbal working memory and memory span. Current research aims to investigate how these deficits may affect the learning of verbal material by administration of the Auditory Verbal Learning Task (AVLT) (Rey, 1964). The task provides a learning curve by assessing immediate memory span over multiple trials. Learning strategies are further analysed by tendencies to confabulate as well as demonstrate either proactive or retroactive interference elicited by a novel 'distractor' list. Three groups completed the task: two groups of 14 Ecstasy users (short- and long-term) and one group of 14 polydrug controls. Compared with controls both Ecstasy groups recalled significantly fewer words and made more confabulation errors on the initial three recall trials as well as a delayed recall trial. Long-term users demonstrated increased confabulation on the initial trials and the novel 'distractor7' trial, compared with short-term users. Only following repeated presentations were both short- and long-term users shown to perform at control levels. As such, deficits in verbal learning may be more related to storage and/or retrieval problems than problems associated with capacity per se. No interference errors were demonstrated by either of the Ecstasy groups. However, a high level of intrusion errors may indicate selective working memory problems associated with longer-term use of the drug. Copyright 2001 John Wiley & Sons, Ltd.

Learning curves of basic laparoscopic psychomotor skills in SINERGIA VR simulator.

Science.gov (United States)

Sánchez-Peralta, L F; Sánchez-Margallo, F M; Moyano-Cuevas, J L; Pagador, J B; Enciso, S; Gómez-Aguilera, E J; Usón-Gargallo, J

2012-11-01

Surgical simulators are currently essential within any laparoscopic training program because they provide a low-stakes, reproducible and reliable environment to acquire basic skills. The purpose of this study is to determine the training learning curve based on different metrics corresponding to five tasks included in SINERGIA laparoscopic virtual reality simulator. Thirty medical students without surgical experience participated in the study. Five tasks of SINERGIA were included: Coordination, Navigation, Navigation and touch, Accurate grasping and Coordinated pulling. Each participant was trained in SINERGIA. This training consisted of eight sessions (R1-R8) of the five mentioned tasks and was carried out in two consecutive days with four sessions per day. A statistical analysis was made, and the results of R1, R4 and R8 were pair-wise compared with Wilcoxon signed-rank test. Significance is considered at P value psychomotor skills that can be trained in SINERGIA. Therefore, and based on these results together with previous works, SINERGIA could be used as training tool with a properly designed training program.

Digital tomosynthesis for evaluating metastatic lung nodules: Nodule visibility, learning curves, and reading times

International Nuclear Information System (INIS)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyung Jin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, < or = 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Digital tomosynthesis for evaluating metastatic lung nodules: Nodule visibility, learning curves, and reading times

Energy Technology Data Exchange (ETDEWEB)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyung Jin; Song, Yong Sub; Hwang, Eui Jin [Dept. of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul (Korea, Republic of)

2015-04-15

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, < or = 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Comparison of Short vs Long Anti-rotation in Treating Trochanteric Fractures

Directory of Open Access Journals (Sweden)

Raval P

2016-03-01

Full Text Available Introduction: A comparative evaluation of the surgical treatment and outcome of patients with pertrochanteric fractures treated with short versus long proximal femoral nail antirotation. Materials and methods: A retrospective review was conducted of patients with pertrochanteric fractures treated between January 2011 and June 2012. In all 80 patients were enrolled in the study, of which 40 were treated with short PFNA and the remaining with long PFNA. Comparative analyses of demographic data, peri-operative outcome and complications were carried out. Results: There was no significant difference noted in the two groups with regards to Arbeitsgemeinschaft fur Osteosynthesefragen (AO fracture classification, time from injury to surgery, blood transfusion post surgery and hospital stay. The surgical duration for a short PFNA procedure was significantly less (58 minutes when compared to that of a long PFNA (87 minutes. Similarly intra-operative blood loss was significantly higher in the long PFNA group as compared to the short PFNA. Conclusions: A relatively quicker surgical time of just under an hour , lesser blood loss and better learning curve with trainee surgeons make short PFNA a better implant choice in the treatment of pertrochanteric fractures.

Learning curve of laparoscopy-assisted distal gastrectomy with systemic lymphadenectomy for early gastric cancer

Institute of Scientific and Technical Information of China (English)

Min-Chan Kim; Ghap-Joong Jung; Hyung-Ho Kim

2005-01-01

AIM: To evaluate the nature of the "learning curve" for laparoscopy-assisted distal gastrectomy (LADG) with systemic lymphadenectomy for early gastric cancer. METHODS: The data of 90 consecutive patients with early gastric cancer who underwent LADG with systemic lymphadenectomy between April 2003 and November 2004 were reviewed. The 90 patients were divided into 9 sequential groups of 10 cases in each group and the average operative time of these 9 groups were determined. Other learning indicators, such as transfusion requirements, conversion rates to open surgery, postoperative complication, time to first flatus, and postoperative hospital stay, were evaluated. RESULTS: After the first 10 LADGs, the operative time reached its first plateau (230-240 min/operation) and then reached a second plateau (＜200 min/operation) for the final 30 cases. Although a significant improvement in the operative time was noted after the first 50 cases, there were no significant differences in transfusion requirements, conversion rates to open surgery, postoperative complications, time to first flatus, or postoperative hospital stay between the groups. CONCLUSION: Based on operative time analysis, this study show that experience of 50 cases of LADG with systemic lymphadenectomy for early gastric cancer is required to achieve optimum proficiency.

Rapid learning curve assessment in an ex vivo training system for microincisional glaucoma surgery.

Science.gov (United States)

Dang, Yalong; Waxman, Susannah; Wang, Chao; Parikh, Hardik A; Bussel, Igor I; Loewen, Ralitsa T; Xia, Xiaobo; Lathrop, Kira L; Bilonick, Richard A; Loewen, Nils A

2017-05-09

Increasing prevalence and cost of glaucoma have increased the demand for surgeons well trained in newer, microincisional surgery. These procedures occur in a highly confined space, making them difficult to learn by observation or assistance alone as is currently done. We hypothesized that our ex vivo outflow model is sensitive enough to allow computing individual learning curves to quantify progress and refine techniques. Seven trainees performed nine trabectome-mediated ab interno trabeculectomies in pig eyes (n = 63). An expert surgeon rated the procedure using an Operating Room Score (ORS). The extent of outflow beds accessed was measured with canalograms. Data was fitted using mixed effect models. ORS reached a half-maximum on an asymptote after only 2.5 eyes. Surgical time decreased by 1.4 minutes per eye in a linear fashion. The ablation arc followed an asymptotic function with a half-maximum inflection point after 5.3 eyes. Canalograms revealed that this progress did not correlate well with improvement in outflow, suggesting instead that about 30 eyes are needed for true mastery. This inexpensive pig eye model provides a safe and effective microsurgical training model and allows objective quantification of outcomes for the first time.

Environmental Kuznets Curve for carbon emissions in Pakistan: An empirical investigation

Energy Technology Data Exchange (ETDEWEB)

Nasir, Muhammad, E-mail: nasirawan84@yahoo.co [Staff Economist, Pakistan Institute of Development Economics, 44000 Islamabad (Pakistan); Ur Rehman, Faiz, E-mail: faizeconomist@yahoo.co [Department of Economics, Quaid-i-Azam University, Islamabad (Pakistan)

2011-03-15

This study investigates the relationship between carbon emissions, income, energy consumption, and foreign trade in Pakistan for the period 1972-2008. By employing the Johansen method of cointegration, the study finds that there is a quadratic long-run relationship between carbon emissions and income, confirming the existence of Environmental Kuznets Curve for Pakistan. Moreover, both energy consumption and foreign trade are found to have positive effects on emissions. The short-run results have, however, denied the existence of the Environmental Kuznets Curve. The short-run results are unique to the existing literature in the sense that none of the long-run determinants of emissions is significant. The contradictory results of short- and long-run give policy makers the opportunity to formulate different types of growth policies for the two terms taking environmental issues into consideration. In addition, the uni-directional causality from growth to energy consumption suggests that the policy makers should not only focus on forecasting future demand for energy with different growth scenarios but also on obtaining the least cost energy. Furthermore, the absence of causality from emissions to growth suggests that Pakistan can curb its carbon emissions without disturbing its economic growth. - Research highlights: {yields} Environmental Kuznets Curve exists only in the long-run in Pakistan. {yields} Both energy consumption and trade openness also affect carbon emissions positively in the long run. {yields} The short-run results have, however, denied the existence of the Environmental Kuznets Curve. {yields} None of the explanatory variables affect emissions in short-run. {yields} There is uni-directional causality from growth to energy consumption. {yields} There is uni-directional causality from growth to emissions.

Environmental Kuznets Curve for carbon emissions in Pakistan: An empirical investigation

International Nuclear Information System (INIS)

Nasir, Muhammad; Ur Rehman, Faiz

2011-01-01

This study investigates the relationship between carbon emissions, income, energy consumption, and foreign trade in Pakistan for the period 1972-2008. By employing the Johansen method of cointegration, the study finds that there is a quadratic long-run relationship between carbon emissions and income, confirming the existence of Environmental Kuznets Curve for Pakistan. Moreover, both energy consumption and foreign trade are found to have positive effects on emissions. The short-run results have, however, denied the existence of the Environmental Kuznets Curve. The short-run results are unique to the existing literature in the sense that none of the long-run determinants of emissions is significant. The contradictory results of short- and long-run give policy makers the opportunity to formulate different types of growth policies for the two terms taking environmental issues into consideration. In addition, the uni-directional causality from growth to energy consumption suggests that the policy makers should not only focus on forecasting future demand for energy with different growth scenarios but also on obtaining the least cost energy. Furthermore, the absence of causality from emissions to growth suggests that Pakistan can curb its carbon emissions without disturbing its economic growth. - Research highlights: → Environmental Kuznets Curve exists only in the long-run in Pakistan. → Both energy consumption and trade openness also affect carbon emissions positively in the long run. → The short-run results have, however, denied the existence of the Environmental Kuznets Curve. → None of the explanatory variables affect emissions in short-run. → There is uni-directional causality from growth to energy consumption. → There is uni-directional causality from growth to emissions.

Learning curve for the management of tyrosine kinase inhibitors as the first line of treatment for patients with metastatic renal cancer.

Science.gov (United States)

Lendínez-Cano, G; Osman García, I; Congregado Ruiz, C B; Conde Sánchez, J M; Medina López, R A

2018-03-07

To analyse the learning curve for the management of tyrosine kinase inhibitors as the first line of treatment for patients with metastatic renal cancer. We evaluated 32 consecutive patients treated in our department for metastatic renal cancer with tyrosine kinase inhibitors (pazopanib or sunitinib) as first-line treatment between September 2012 and November 2015. We retrospectively analysed this sample. We measured the time to the withdrawal of the first-line treatment, the time to progression and overall survival using Kaplan-Meier curves. The learning curve was analysed with the cumulative sum (CUSUM) methodology. In our series, the median time to the withdrawal of the first-line treatment was 11 months (95% CI 4.9-17.1). The mean time to progression was 30.4 months (95% CI 22.7-38.1), and the mean overall survival was 34.9 months (95% CI 27.8-42). By applying the CUSUM methodology, we obtained a graph for the CUSUM value of the time to withdrawal of the first-line treatment (CUSUM TW), observing 3 well-differentiated phases: phase 1 or initial learning phase (1-15), phase 2 (16-26) in which the management of the drug progressively improved and phase 3 (27-32) of maximum experience or mastery of the management of these drugs. The number of treated patients needed to achieve the proper management of these patients was estimated at 15. Despite the limitations of the sample size and follow-up time, we estimated (in 15 patients) the number needed to reach the necessary experience in the management of these patients with tyrosine kinase inhibitors. We observed no relationship between the time to the withdrawal of the first-line treatment for any cause and progression. Copyright © 2018 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

Preoperative risk factors for conversion and learning curve of minimally invasive distal pancreatectomy.

Science.gov (United States)

Hua, Yongfei; Javed, Ammar A; Burkhart, Richard A; Makary, Martin A; Weiss, Matthew J; Wolfgang, Christopher L; He, Jin

2017-11-01

Although laparoscopic distal pancreatectomy is considered a standard approach, 10% to 40% of these are converted. The preoperative risk factors for conversion are not well described. The aim of this study was to identify risk factors associated with conversion. Clinicopathological variables of 211 consecutive patients who underwent laparoscopic distal pancreatectomy between January 2007 and December 2015 at Johns Hopkins were analyzed to identify factors associated with conversion. Furthermore, the learning curve for laparoscopic distal pancreatectomy was studied. On univariate analysis of diabetes mellitus, preoperative diagnosis of malignant disease, multiorgan resection, surgeons' years and case experience were significantly associated with conversion (all P pancreatectomy with a preoperative diagnosis of malignant disease or possible multiorgan resection are at a higher risk of conversion. Surgeon experience of performing >15 procedures significantly reduces the risk of conversion. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of the radial distribution curves of partially ordered condensed carbon films

International Nuclear Information System (INIS)

Palatnik, L.S.; Derevyanchenko, A.S.; Nechitajlo, A.A.; Stetsenko, A.N.; Gorbenko, N.I.

1977-01-01

The Fourier analysis of the electron scattering curves has been carried out to determine the short-range order structure of carbon condensates. The intensity curves for carbon films condensed in a approximately 10 -6 Torr vacuum upon a substrate heated up to 600 deg C were obtained by diffraction techniques with filtration of the inelastic scattered electron background. The radial distribution curve errors were analyzed and quantified with the aid of a computer to determine the short-range order of the condensed carbon. It has been shown that carbon films consist of regions measuring approximately 20 A formed by parallelly packed graphite nets with azimuthal orientation different from that in ideal graphite crystals

Femtosecond laser-assisted cataract surgery with bimanual technique: learning curve for an experienced cataract surgeon.

Science.gov (United States)

Cavallini, Gian Maria; Verdina, Tommaso; De Maria, Michele; Fornasari, Elisa; Volpini, Elisa; Campi, Luca

2017-11-29

To describe the intraoperative complications and the learning curve of microincision cataract surgery assisted by femtosecond laser (FLACS) with bimanual technique performed by an experienced surgeon. It is a prospective, observational, comparative case series. A total of 120 eyes which underwent bimanual FLACS by the same experienced surgeon during his first experience were included in the study; we considered the first 60 cases as Group A and the second 60 cases as Group B. In both groups, only nuclear sclerosis of grade 2 or 3 was included; an intraocular lens was implanted through a 1.4-mm incision. Best-corrected visual acuity (BCVA), surgically induced astigmatism (SIA), central corneal thickness and endothelial cell loss (ECL) were evaluated before and at 1 and 3 months after surgery. Intraoperative parameters, and intra- and post-operative complications were recorded. In Group A, we had femtosecond laser-related minor complications in 11 cases (18.3%) and post-operative complications in 2 cases (3.3%); in Group B, we recorded 2 cases (3.3%) of femtosecond laser-related minor complications with no post-operative complications. Mean effective phaco time (EPT) was 5.32 ± 3.68 s in Group A and 4.34 ± 2.39 s in Group B with a significant difference (p = 0.046). We recorded a significant mean BCVA improvement at 3 months in both groups (p  0.05). Finally, we found significant ECL in both groups with a significant difference between the two groups (p = 0.042). FLACS with bimanual technique and low-energy LDV Z8 is associated with a necessary initial learning curve. After the first adjustments in the surgical technique, this technology seems to be safe and effective with rapid visual recovery and it helps surgeons to standardize the crucial steps of cataract surgery.

Lexical Learning in Bilingual Adults: The Relative Importance of Short-Term Memory for Serial Order and Phonological Knowledge

Science.gov (United States)

Majerus, Steve; Poncelet, Martine; Van der Linden, Martial; Weekes, Brendan S.

2008-01-01

Studies of monolingual speakers have shown a strong association between lexical learning and short-term memory (STM) capacity, especially STM for serial order information. At the same time, studies of bilingual speakers suggest that phonological knowledge is the main factor that drives lexical learning. This study tested these two hypotheses…

Randomized controlled trial evaluating the temporal effects of high-intensity exercise on learning, short-term and long-term memory, and prospective memory.

Science.gov (United States)

Frith, Emily; Sng, Eveleen; Loprinzi, Paul D

2017-11-01

The broader purpose of this study was to examine the temporal effects of high-intensity exercise on learning, short-term and long-term retrospective memory and prospective memory. Among a sample of 88 young adult participants, 22 were randomized into one of four different groups: exercise before learning, control group, exercise during learning, and exercise after learning. The retrospective assessments (learning, short-term and long-term memory) were assessed using the Rey Auditory Verbal Learning Test. Long-term memory including a 20-min and 24-hr follow-up assessment. Prospective memory was assessed using a time-based procedure by having participants contact (via phone) the researchers at a follow-up time period. The exercise stimulus included a 15-min bout of progressive maximal exertion treadmill exercise. High-intensity exercise prior to memory encoding (vs. exercise during memory encoding or consolidation) was effective in enhancing long-term memory (for both 20-min and 24-h follow-up assessments). We did not observe a differential temporal effect of high-intensity exercise on short-term memory (immediate post-memory encoding), learning or prospective memory. The timing of high-intensity exercise may play an important role in facilitating long-term memory. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Bypassing the learning curve in permanent seed implants using state-of-the-art technology

International Nuclear Information System (INIS)

Beaulieu, Luc; Evans, Dee-Ann Radford; Aubin, Sylviane; Angyalfi, Steven; Husain, Siraj; Kay, Ian; Martin, Andre-Guy; Varfalvy, Nicolas; Vigneault, Eric; Dunscombe, Peter

2007-01-01

Purpose: The aim of this study was to demonstrate, based on clinical postplan dose distributions, that technology can be used efficiently to eliminate the learning curve associated with permanent seed implant planning and delivery. Methods and Materials: Dose distributions evaluated 30 days after the implant of the initial 22 consecutive patients treated with permanent seed implants at two institutions were studied. Institution 1 (I1) consisted of a new team, whereas institution 2 (I2) had performed more than 740 preplanned implantations over a 9-year period before the study. Both teams had adopted similar integrated systems based on three-dimensional (3D) transrectal ultrasonography, intraoperative dosimetry, and an automated seed delivery and needle retraction system (FIRST, Nucletron). Procedure time and dose volume histogram parameters such as D90, V100, V150, V200, and others were collected in the operating room and at 30 days postplan. Results: The average target coverage from the intraoperative plan (V100) was 99.4% for I1 and 99.9% for I2. D90, V150, and V200 were 191.4 Gy (196.3 Gy), 75.3% (73.0%), and 37.5% (34.1%) for I1 (I2) respectively. None of these parameters shows a significant difference between institutions. The postplan D90 was 151.2 Gy for I1 and 167.3 Gy for I2, well above the 140 Gy from the Stock et al. analysis, taking into account differences at planning, results in a p value of 0.0676. The procedure time required on average 174.4 min for I1 and 89 min for I2. The time was found to decrease with the increasing number of patients. Conclusion: State-of-the-art technology enables a new brachytherapy team to obtain excellent postplan dose distributions, similar to those achieved by an experienced team with proven long-term clinical results. The cost for bypassing the usual dosimetry learning curve is time, with increasing team experience resulting in shorter treatment times

Supply-cost curves for geographically distributed renewable-energy resources

International Nuclear Information System (INIS)

Izquierdo, Salvador; Dopazo, Cesar; Fueyo, Norberto

2010-01-01

The supply-cost curves of renewable-energy sources are an essential tool to synthesize and analyze large-scale energy-policy scenarios, both in the short and long terms. Here, we suggest and test a parametrization of such curves that allows their representation for modeling purposes with a minimal set of information. In essence, an economic potential is defined based on the mode of the marginal supply-cost curves; and, using this definition, a normalized log-normal distribution function is used to model these curves. The feasibility of this proposal is assessed with data from a GIS-based analysis of solar, wind and biomass technologies in Spain. The best agreement is achieved for solar energy.

Generalization of drying curves in conductive/convective drying of cellulose

Directory of Open Access Journals (Sweden)

M. Stenzel

2003-03-01

Full Text Available The objective of this work is to analyze the possibility of applying the drying curves generalization methodology to the conductive/convective hot plate drying of cellulose. The experiments were carried out at different heated plate temperatures and air velocities over the surface of the samples. This kind of approach is very interesting because it permits comparison of the results of different experiments by reducing them to only one set, which can be divided into two groups: the generalized drying curves and the generalized drying rate curves. The experimental apparatus is an attempt to reproduce the operational conditions of conventional paper dryers (ratio of paper/air movement and consists of a metallic box heated by a thermostatic bath containing an upper surface on which the cellulose samples are placed. Sample material is short- and long-fiber cellulose sheets, about 1 mm thick, and ambient air was introduced into the system by a adjustable blower under different conditions. Long-fiber cellulose generalized curves were obtained and analyzed first individually and then together with the short-fiber cellulose results from Motta Lima et al. (2000 a,b. Finally, a set of equations to fit the generalized curves obtained was proposed and discussed.

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

Kant, curves and medical learning practice: a reply to Le Morvan and Stock.

Science.gov (United States)

Ives, J

2007-02-01

In a recent paper published in the Journal of Medical Ethics, Le Morvan and Stock claim that the kantian ideal of treating people always as ends in themselves and never merely as a means is in direct and insurmountable conflict with the current medical practice of allowing practitioners at the bottom of their "learning curve" to "practise their skills" on patients. In this response, I take up the challenge they issue [corrected] and try to reconcile this conflict. The kantian ideal offered in the paper is an incomplete characterisation of Kant's moral philosophy, and the formula of humanity is considered in isolation without taking into account other salient kantian principles. I also suggest that their argument based on "necessary for the patient" assumes too narrow a reading of "necessary". This reply is intended as an extension to, rather than a criticism of, their work.

A variation reduction allocation model for quality improvement to minimize investment and quality costs by considering suppliers’ learning curve

Science.gov (United States)

Rosyidi, C. N.; Jauhari, WA; Suhardi, B.; Hamada, K.

2016-02-01

Quality improvement must be performed in a company to maintain its product competitiveness in the market. The goal of such improvement is to increase the customer satisfaction and the profitability of the company. In current practice, a company needs several suppliers to provide the components in assembly process of a final product. Hence quality improvement of the final product must involve the suppliers. In this paper, an optimization model to allocate the variance reduction is developed. Variation reduction is an important term in quality improvement for both manufacturer and suppliers. To improve suppliers’ components quality, the manufacturer must invest an amount of their financial resources in learning process of the suppliers. The objective function of the model is to minimize the total cost consists of investment cost, and quality costs for both internal and external quality costs. The Learning curve will determine how the employee of the suppliers will respond to the learning processes in reducing the variance of the component.

Thermodynamic properties of short-range square well fluid

Science.gov (United States)

López-Rendón, R.; Reyes, Y.; Orea, P.

2006-08-01

The interfacial properties of short-range square well fluid with λ =1.15, 1.25, and 1.375 were determined by using single canonical Monte Carlo simulations. Simulations were carried out in the vapor-liquid region. The coexistence curves of these models were calculated and compared to those previously reported in the literature and good agreement was found among them. We found that the surface tension curves for any potential model of short range form a single master curve when we plot γ* vs T /Tc. It is demonstrated that the critical reduced second virial coefficient B2* as a function of interaction range or Tc* is not constant.

Tibiotalocalcaneal arthrodesis with a curved, interlocking, intramedullary nail.

Science.gov (United States)

Budnar, Vijaya M; Hepple, Steve; Harries, William G; Livingstone, James A; Winson, Ian

2010-12-01

Tibiotalocalcaneal fusion with a straight rod has a risk of damaging the lateral plantar neurovascular structures and may interfere with maintaining normal heel valgus position.We report the results of a prospective study of tibiotalocalcaneal (TTC) arthrodesis with a short, anatomically curved interlocking, intramedullary nail. Forty-five arthrodesis in 42 patients, performed between Jan 2003 and Oct 2008, were prospectively followed. The mean followup was 48 (range, 10 to 74) months. The main indications for the procedure were failed ankle arthrodesis with progressive subtalar arthritis, failed ankle arthroplasty and complex hindfoot deformity. The outcome was measured by a combination of pre and postoperative clinical examination, AOFAS hindfoot scores, SF-12 scores and radiological assessment. Union rate was 89% (40/45). Eighty-two percent (37/45) reported improvement in pain and 73% (33/45) had improved foot function. Satisfactory hindfoot alignment was achieved in 84% (38/45). Postoperatively there was a mean improvement in the AOFAS score of 37. Complications included a below knee amputation for persistent deep infection, five nonunions, and three delayed unions. Four nails, six proximal and six distal locking screws were removed for various causes. Other complications included two perioperative fractures, four superficial wound infections and one case of lateral plantar nerve irritation. With a short, anatomically curved intramedullary nail, we had a high rate of tibiotalocalcaneal fusion with minimal plantar neurovascular complications. We believe a short, curved intramedullary nail, with its more lateral entry point, helped maintain hindfoot alignment.

An application of the learning curve-cumulative summation test to evaluate training for endotracheal intubation in emergency medicine.

Science.gov (United States)

Je, Sangmo; Cho, Youngsuk; Choi, Hyuk Joong; Kang, Boseung; Lim, Taeho; Kang, Hyunggoo

2015-04-01

The learning curve-cumulative summation (LC-CUSUM) test allows for quantitative and individual assessments of the learning process. In this study, we evaluated the process of skill acquisition for performing endotracheal intubation (ETI) in three emergency medicine (EM) residents over a 2 year period in their first 2 years of their EM residency. We evaluated 342 ETI cases performed by three EM residents using the LC-CUSUM test according to their rate of success or failure of ETI. A 90% success rate (SR) was chosen to define adequate performance and an SR of 80% was considered inadequate. After the learning phase, the standard CUSUM test was applied to ensure that performance was maintained. The mean number of ETI cases required to reach the predefined level of performance was 74.7 (95% CI 62.0 to 87.3). CUSUM tests confirmed that performance was maintained after the learning phase. By using the LC-CUSUM test, we were able to quantitatively monitor the acquisition of the skill of ETI by EM residents. The LC-CUSUM could be useful for monitoring the learning process for the training of airway management in the practice of EM. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Rational points on elliptic curves

CERN Document Server

Silverman, Joseph H

2015-01-01

The theory of elliptic curves involves a pleasing blend of algebra, geometry, analysis, and number theory. This book stresses this interplay as it develops the basic theory, thereby providing an opportunity for advanced undergraduates to appreciate the unity of modern mathematics. At the same time, every effort has been made to use only methods and results commonly included in the undergraduate curriculum. This accessibility, the informal writing style, and a wealth of exercises make Rational Points on Elliptic Curves an ideal introduction for students at all levels who are interested in learning about Diophantine equations and arithmetic geometry. Most concretely, an elliptic curve is the set of zeroes of a cubic polynomial in two variables. If the polynomial has rational coefficients, then one can ask for a description of those zeroes whose coordinates are either integers or rational numbers. It is this number theoretic question that is the main subject of this book. Topics covered include the geometry and ...

Is there a learning curve for the TVT-O procedure? A prospective single-surgeon study of 372 consecutive cases.

Science.gov (United States)

Serati, Maurizio; Bogani, Giorgio; Braga, Andrea; Sorice, Paola; Salvatore, Stefano; Uccella, Stefano; Ghezzi, Fabio

2015-03-01

To evaluate for the first time in the literature the learning curve of Inside-out transobturator tape (TVT-O™). A prospective observational study was conducted in a tertiary reference center. Consecutive women treated by TVT-O™ performed by one surgeon were included. Data regarding subjective, objective cure rates, and adverse events were collected. Trends, over the number of procedures, were estimated using assay analyses. Number of procedures and variables were interpolating in standard curves using linear lines. Three hundred and seventy two procedures were included. Postoperative pain levels decreased with the increase in the level of expertise (pain levels: 1-day: from 6.6 (±3.3) to 4.3 (±3.1); 95%CI: -0.01603 to 0.001235, p=0.04; 2-day: from 5.6 (±4.1) to 3.6 (±3.7); 95%CI: -0.02092 to -0.002497, p=0.01; 12-month: from 0.1 (±0.7) to 0 (±0); 95%CI: -0.001814 to 0.05019, p=0.07). Overall, objective cure rate was achieved in 93.5% of patients. Additionally, 88.2% and 88.7% patients reported "much better" feeling at PGI-I scale and 80% reduction in UDI score, respectively. We observed, that delta ICIQ-sf (from 12 (±8.7) to 14 (±6.0); p=0.04) and delta-UDI (from 91% to 97%; p=0.04) improved over the time. TVT-O procedure offers excellent outcomes with high objective and subjective cure rates and low complications rate, even at the beginning of the surgeon's learning curve. However, a high experience of the surgeon could significantly improve the subjective cure rate and could reduce postoperative the groin pain. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Análise de conglomerados em curvas de aprendizado para formação de agrupamentos homogêneos de trabalhadores Cluster analysis of learning curves for grouping workers with homogeneous learning profiles

Directory of Open Access Journals (Sweden)

Renato Eduardo Stroieke

2012-01-01

Full Text Available Em diversos setores da indústria é desejado que trabalhadores reunidos em uma estação de trabalho apresentem perfil de aprendizado similar. O presente artigo apresenta um método de agrupamento de trabalhadores utilizando modelagem por curva de aprendizado e técnicas de clusterização. O método modela dados de desempenho de trabalhadores por intermédio de diversos modelos de curvas de aprendizado; os parâmetros de aprendizado dos modelos testados permitem predizer o desempenho dos trabalhadores em intervalos de tempo pré-determinados. Os valores preditos são agrupados através de ferramentas de clusterização. O maior índice de ajuste (IA, gerado a partir do Silhouette Index e do coeficiente de determinação, indica o modelo de curva mais consistente em termos de aderência aos dados e qualidade de agrupamento de perfis de aprendizado. Ao ser aplicado em dados de uma indústria de calçados, o método gerou agrupamentos consistentes de trabalhadores com base nos distintos perfis de aprendizado.In many industrial segments, it is desirable to allocate workers with similar learning profiles in the same workstation. This paper presents a method that groups workers based on learning curve modeling and clustering techniques. Workers' performance data are modeled through several learning curve models; learning parameters allow for workers' performance prediction at intervals of predetermined time. The predicted values are then grouped by clustering techniques. The largest Adjustment Index (AI, derived from the Silhouette Index and Coefficient of Determination, indicates the model yielding superior adherence to data and better clustering of learning profiles. When applied to a shoe manufacturing process, the method generated consistent groups of workers based on their learning profiles.

Searching for the Hebb effect in Down syndrome: evidence for a dissociation between verbal short-term memory and domain-general learning of serial order.

Science.gov (United States)

Mosse, E K; Jarrold, C

2010-04-01

The Hebb effect is a form of repetition-driven long-term learning that is thought to provide an analogue for the processes involved in new word learning. Other evidence suggests that verbal short-term memory also constrains now vocabulary acquisition, but if the Hebb effect is independent of short-term memory, then it may be possible to demonstrate its preservation in a sample of individuals with Down syndrome, who typically show a verbal short-term memory deficit alongside surprising relative strengths in vocabulary. In two experiments, individuals both with and without Down syndrome (matched for receptive vocabulary) completed immediate serial recall tasks incorporating a Hebb repetition paradigm in either verbal or visuospatial conditions. Both groups demonstrated equivalent benefit from Hebb repetition, despite individuals with Down syndrome showing significantly lower verbal short-term memory spans. The resultant Hebb effect was equivalent across verbal and visuospatial domains. These studies suggest that the Hebb effect is essentially preserved within Down syndrome, implying that explicit verbal short-term memory is dissociable from potentially more implicit Hebb learning. The relative strength in receptive vocabulary observed in Down syndrome may therefore be supported by largely intact long-term as opposed to short-term serial order learning. This in turn may have implications for teaching methods and interventions that present new phonological material to individuals with Down syndrome.

Estimating zonal electricity supply curves in transmission-constrained electricity markets

International Nuclear Information System (INIS)

Sahraei-Ardakani, Mostafa; Blumsack, Seth; Kleit, Andrew

2015-01-01

Many important electricity policy initiatives would directly affect the operation of electric power networks. This paper develops a method for estimating short-run zonal supply curves in transmission-constrained electricity markets that can be implemented quickly by policy analysts with training in statistical methods and with publicly available data. Our model enables analysis of distributional impacts of policies affecting operation of electric power grid. The method uses fuel prices and zonal electric loads to determine piecewise supply curves, identifying zonal electricity price and marginal fuel. We illustrate our methodology by estimating zonal impacts of Pennsylvania's Act 129, an energy efficiency and conservation policy. For most utilities in Pennsylvania, Act 129 would reduce the influence of natural gas on electricity price formation and increase the influence of coal. The total resulted savings would be around 267 million dollars, 82 percent of which would be enjoyed by the customers in Pennsylvania. We also analyze the impacts of imposing a $35/ton tax on carbon dioxide emissions. Our results show that the policy would increase the average prices in PJM by 47–89 percent under different fuel price scenarios in the short run, and would lead to short-run interfuel substitution between natural gas and coal. - Highlights: • We develop a method to estimate of zonal supply curves in electricity markets. • The model estimates zonal electricity prices and zonal fuel utilization. • The model implicitly captures the average impacts of transmission constraints. • Using the method, we project supply curves for the seventeen utility zones of PJM. • We use the estimated supply curves to study the impacts of Pennsylvania's Act 129 and a carbon tax of $35 per ton

Methods for predicting isochronous stress-strain curves

International Nuclear Information System (INIS)

Kiyoshige, Masanori; Shimizu, Shigeki; Satoh, Keisuke.

1976-01-01

Isochronous stress-strain curves show the relation between stress and total strain at a certain temperature with time as a parameter, and they are drawn up from the creep test results at various stress levels at a definite temperature. The concept regarding the isochronous stress-strain curves was proposed by McVetty in 1930s, and has been used for the design of aero-engines. Recently the high temperature characteristics of materials are shown as the isochronous stress-strain curves in the design guide for the nuclear energy equipments and structures used in high temperature creep region. It is prescribed that these curves are used as the criteria for determining design stress intensity or the data for analyzing the superposed effects of creep and fatigue. In case of the isochronous stress-strain curves used for the design of nuclear energy equipments with very long service life, it is impractical to determine the curves directly from the results of long time creep test, accordingly the method of predicting long time stress-strain curves from short time creep test results must be established. The method proposed by the authors, for which the creep constitution equations taking the first and second creep stages into account are used, and the method using Larson-Miller parameter were studied, and it was found that both methods were reliable for the prediction. (Kako, I.)

Initial laparoscopic basic skills training shortens the learning curve of laparoscopic suturing and is cost-effective.

Science.gov (United States)

Stefanidis, Dimitrios; Hope, William W; Korndorffer, James R; Markley, Sarah; Scott, Daniel J

2010-04-01

Laparoscopic suturing is an advanced skill that is difficult to acquire. Simulator-based skills curricula have been developed that have been shown to transfer to the operating room. Currently available skills curricula need to be optimized. We hypothesized that mastering basic laparoscopic skills first would shorten the learning curve of a more complex laparoscopic task and reduce resource requirements for the Fundamentals of Laparoscopic Surgery suturing curriculum. Medical students (n = 20) with no previous simulator experience were enrolled in an IRB-approved protocol, pretested on the Fundamentals of Laparoscopic Surgery suturing model, and randomized into 2 groups. Group I (n = 10) trained (unsupervised) until proficiency levels were achieved on 5 basic tasks; Group II (n = 10) received no basic training. Both groups then trained (supervised) on the Fundamentals of Laparoscopic Surgery suturing model until previously reported proficiency levels were achieved. Two weeks later, they were retested to evaluate their retention scores, training parameters, instruction requirements, and cost between groups using t-test. Baseline characteristics and performance were similar for both groups, and 9 of 10 subjects in each group achieved the proficiency levels. The initial performance on the simulator was better for Group I after basic skills training, and their suturing learning curve was shorter compared with Group II. In addition, Group I required less active instruction. Overall time required to finish the curriculum was similar for both groups; but the Group I training strategy cost less, with a savings of $148 per trainee. Teaching novices basic laparoscopic skills before a more complex laparoscopic task produces substantial cost savings. Additional studies are needed to assess the impact of such integrated curricula on ultimate educational benefit. Copyright (c) 2010 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Transcatheter closure of patent ductus arteriosus: Evaluating the effect of the learning curve on the outcome

Directory of Open Access Journals (Sweden)

Azhar Ahmad

2009-01-01

Full Text Available Background and Objectives : Initial experience with transcatheter closure of patent ductus arteriosus (PDA using detachable coils and Amplatzer duct occluder devices is reported. We evaluated the outcome, complications, and influence of the learning curve, and also assessed the need of surgical backup for such interventional procedures. Methods: From January 2000 to December 2004, 121 patients underwent transcatheter closure of PDA. Aortic angiogram was performed to evaluate the size, position, and shape of the duct for appropriately choosing the occluder device type and size. A second aortic angiogram was performed 10 minutes after device deployment. Echocardiography was repeated at intervals of 24 hours, then at 1, 3, and 6 months after the procedure to assess complications. Stepwise multiple regression analysis was used to assess the role of experience in improving the outcome of the procedure. Results: Of 121 cases, four patients had pulmonary artery embolization of the occluder device which was successfully retrieved in the catheterization laboratory, while two others had embolization that required surgical intervention. Four patients had temporary residual leak, nine had protrusion of the device into the aorta without significant Doppler pressure gradient or hemolysis on follow-up, and five had partial hemodynamically insignificant obstruction to the left pulmonary artery. Statistical analysis showed that the effect of the learning curve and experience was responsible for 93% improvement in the procedural outcome over the five-year study period. Conclusion: Transcatheter occlusion of PDA is safe and effective alternative to surgery. Complications occurred in those with unfavorable duct anatomy and with the use of multiple coils. Surgical backup was important for such interventional procedures. Experience played a major role in the proper choice of device type and size which greatly influenced the outcome of the procedure.

Searching for the Hebb Effect in down Syndrome: Evidence for a Dissociation between Verbal Short-Term Memory and Domain-General Learning of Serial Order

Science.gov (United States)

Mosse, E. K.; Jarrold, C.

2010-01-01

Background: The Hebb effect is a form of repetition-driven long-term learning that is thought to provide an analogue for the processes involved in new word learning. Other evidence suggests that verbal short-term memory also constrains now vocabulary acquisition, but if the Hebb effect is independent of short-term memory, then it may be possible…

Modelling the benchmark spot curve for the Serbian

Directory of Open Access Journals (Sweden)

Drenovak Mikica

2010-01-01

Full Text Available The objective of this paper is to estimate Serbian benchmark spot curves using the Svensson parametric model. The main challenges that we tackle are: sparse data, different currency denominations of short and longer term maturities, and infrequent transactions in the short-term market segment vs daily traded medium and long-term market segment. We find that the model is flexible enough to account for most of the data variability. The model parameters are interpreted in economic terms.

W-curve alignments for HIV-1 genomic comparisons.

Directory of Open Access Journals (Sweden)

Douglas J Cork

2010-06-01

Full Text Available The W-curve was originally developed as a graphical visualization technique for viewing DNA and RNA sequences. Its ability to render features of DNA also makes it suitable for computational studies. Its main advantage in this area is utilizing a single-pass algorithm for comparing the sequences. Avoiding recursion during sequence alignments offers advantages for speed and in-process resources. The graphical technique also allows for multiple models of comparison to be used depending on the nucleotide patterns embedded in similar whole genomic sequences. The W-curve approach allows us to compare large numbers of samples quickly.We are currently tuning the algorithm to accommodate quirks specific to HIV-1 genomic sequences so that it can be used to aid in diagnostic and vaccine efforts. Tracking the molecular evolution of the virus has been greatly hampered by gap associated problems predominantly embedded within the envelope gene of the virus. Gaps and hypermutation of the virus slow conventional string based alignments of the whole genome. This paper describes the W-curve algorithm itself, and how we have adapted it for comparison of similar HIV-1 genomes. A treebuilding method is developed with the W-curve that utilizes a novel Cylindrical Coordinate distance method and gap analysis method. HIV-1 C2-V5 env sequence regions from a Mother/Infant cohort study are used in the comparison.The output distance matrix and neighbor results produced by the W-curve are functionally equivalent to those from Clustal for C2-V5 sequences in the mother/infant pairs infected with CRF01_AE.Significant potential exists for utilizing this method in place of conventional string based alignment of HIV-1 genomes, such as Clustal X. With W-curve heuristic alignment, it may be possible to obtain clinically useful results in a short time-short enough to affect clinical choices for acute treatment. A description of the W-curve generation process, including a comparison

W-curve alignments for HIV-1 genomic comparisons.

Science.gov (United States)

Cork, Douglas J; Lembark, Steven; Tovanabutra, Sodsai; Robb, Merlin L; Kim, Jerome H

2010-06-01

The W-curve was originally developed as a graphical visualization technique for viewing DNA and RNA sequences. Its ability to render features of DNA also makes it suitable for computational studies. Its main advantage in this area is utilizing a single-pass algorithm for comparing the sequences. Avoiding recursion during sequence alignments offers advantages for speed and in-process resources. The graphical technique also allows for multiple models of comparison to be used depending on the nucleotide patterns embedded in similar whole genomic sequences. The W-curve approach allows us to compare large numbers of samples quickly. We are currently tuning the algorithm to accommodate quirks specific to HIV-1 genomic sequences so that it can be used to aid in diagnostic and vaccine efforts. Tracking the molecular evolution of the virus has been greatly hampered by gap associated problems predominantly embedded within the envelope gene of the virus. Gaps and hypermutation of the virus slow conventional string based alignments of the whole genome. This paper describes the W-curve algorithm itself, and how we have adapted it for comparison of similar HIV-1 genomes. A treebuilding method is developed with the W-curve that utilizes a novel Cylindrical Coordinate distance method and gap analysis method. HIV-1 C2-V5 env sequence regions from a Mother/Infant cohort study are used in the comparison. The output distance matrix and neighbor results produced by the W-curve are functionally equivalent to those from Clustal for C2-V5 sequences in the mother/infant pairs infected with CRF01_AE. Significant potential exists for utilizing this method in place of conventional string based alignment of HIV-1 genomes, such as Clustal X. With W-curve heuristic alignment, it may be possible to obtain clinically useful results in a short time-short enough to affect clinical choices for acute treatment. A description of the W-curve generation process, including a comparison technique of

Boiling curve in high quality flow boiling

International Nuclear Information System (INIS)

Shiralkar, B.S.; Hein, R.A.; Yadigaroglu, G.

1980-01-01

The post dry-out heat transfer regime of the flow boiling curve was investigated experimentally for high pressure water at high qualities. The test section was a short round tube located downstream of a hot patch created by a temperature controlled segment of tubing. Results from the experiment showed that the distance from the dryout point has a significant effect on the downstream temperatures and there was no unique boiling curve. The heat transfer coefficients measured sufficiently downstream of the dryout point could be correlated using the Heineman correlation for superheated steam, indicating that the droplet deposition effects could be neglected in this region

KNOWLEDGE TRANSFER AND LEARNING: PROBLEMS OF KNOWLEDGE TRANSFER ASSOCIATED WITH TRYING TO SHORT-CIRCUIT THE LEARNING CYCLE

Directory of Open Access Journals (Sweden)

Sue Newell

2006-11-01

Full Text Available Knowledge is considered to be a key organizational resource in the 21st century and the knowledge management ‘movement’ has alerted organizations to the fact that they should more strategically exploit their knowledge assets. Companies are thus lured by the suggestion that they can gain competitive advantage by the more astute management of their knowledge base and in particular, by the transfer of knowledge across individuals, groups and organizational units, using IT to accomplish this. In this paper, we reflect on this common view of knowledge transfer. More specifically, we question an implication of this view - essentially the possibility of short-circuiting the learning cycle, so that individuals do not have to rely on their personal or shared experiences to identify better practices, but can learn from the codified lessons of others in IT systems. More importantly, we consider the characteristics of knowledge – that knowledge is distributed, ambiguous and disruptive – that makes its transfer highly problematic. Drawing on case research, we relate this to the learning cycle (Kolb 1984 and thereby identify barriers to knowledge transfer. We conclude by considering ways of overcoming these barriers by emphasizing the importance of social systems alongside technical systems.

Technology learning in a global - local perspective: - the interplay between technology diffusion, niche markets and experience curves

International Nuclear Information System (INIS)

Martinsen, Thomas

2010-01-01

Preventing dangerous global climate change requires timely deployment of nascent energy technologies with zero or low Co2 emissions. Managing the shift to a common sustainable technology path calls for insight about the influence of global technological change on the national energy system. Moreover, national policies are required to promote the shift to the new technology path. This calls for methods to analyse the national energy system within a global perspective. The objective of the work presented in this thesis was to investigate interplay between technology diffusion, niche markets and technology learning from the perspective of a small open economy like Norway. More specifically, develop methods to include the influence of technology learning manifested in experience and learning curves into national energy-economy-environment models. Moreover, apply the methods to investigate the potential influence and sensitivity to technology learning in a small open economy. In this thesis three such methods have been developed, applied and its importance assessed using Norway as an example. In this work three models have been linked. They are the global Energy Technology Perspectives model operated by the International Energy Agency, the Norwegian Markal model at the Institute for Energy Technology and the macro economic model MSG6 at Statistics Norway. Method one and two has been developed to manage the interplay between the models. In a local perspective technology learning in the global market is perceived as spillover. Based upon a review of the characteristics of technological change and learning curves and its application to energy system modelling some criteria important for the parameterization and modelling of spillover in a small open economy are suggested. The first method incorporates spillover into the national Markal model. The second method establishes a soft-link between the national models. The soft-link served two purposes; to provide input on demand

Fast algorithm selection using learning curves

NARCIS (Netherlands)

Rijn, van J.N.; Abdulrahman, S.M.; Brazdil, P.; Vanschoren, J.; Fromont, E.; De Bie, T.; Leeuwen, van M.

2015-01-01

One of the challenges in Machine Learning to find a classifier and parameter settings that work well on a given dataset. Evaluating all possible combinations typically takes too much time, hence many solutions have been proposed that attempt to predict which classifiers are most promising to try. As

Assessment of performance measures and learning curves for use of a virtual-reality ultrasound simulator in transvaginal ultrasound examination

DEFF Research Database (Denmark)

Madsen, M E; Konge, L; Nørgaard, L N

2014-01-01

OBJECTIVE: To assess the validity and reliability of performance measures, develop credible performance standards and explore learning curves for a virtual-reality simulator designed for transvaginal gynecological ultrasound examination. METHODS: A group of 16 ultrasound novices, along with a group......-6), corresponding to an average of 219 min (range, 150-251 min) of training. The test/retest reliability was high, with an intraclass correlation coefficient of 0.93. CONCLUSIONS: Competence in the performance of gynecological ultrasound examination can be assessed in a valid and reliable way using virtual-reality...

Short-term memory development: differences in serial position curves between age groups and latent classes.

Science.gov (United States)

Koppenol-Gonzalez, Gabriela V; Bouwmeester, Samantha; Vermunt, Jeroen K

2014-10-01

In studies on the development of cognitive processes, children are often grouped based on their ages before analyzing the data. After the analysis, the differences between age groups are interpreted as developmental differences. We argue that this approach is problematic because the variance in cognitive performance within an age group is considered to be measurement error. However, if a part of this variance is systematic, it can provide very useful information about the cognitive processes used by some children of a certain age but not others. In the current study, we presented 210 children aged 5 to 12 years with serial order short-term memory tasks. First we analyze our data according to the approach using age groups, and then we apply latent class analysis to form latent classes of children based on their performance instead of their ages. We display the results of the age groups and the latent classes in terms of serial position curves, and we discuss the differences in results. Our findings show that there are considerable differences in performance between the age groups and the latent classes. We interpret our findings as indicating that the latent class analysis yielded a much more meaningful way of grouping children in terms of cognitive processes than the a priori grouping of children based on their ages. Copyright © 2014 Elsevier Inc. All rights reserved.

Equilibrium spherically curved two-dimensional Lennard-Jones systems

NARCIS (Netherlands)

Voogd, J.M.; Sloot, P.M.A.; van Dantzig, R.

2005-01-01

To learn about basic aspects of nano-scale spherical molecular shells during their formation, spherically curved two-dimensional N-particle Lennard-Jones systems are simulated, studying curvature evolution paths at zero-temperature. For many N-values (N < 800) equilibrium configu- rations are traced

Short-Term Solar Forecasting Performance of Popular Machine Learning Algorithms: Preprint

Energy Technology Data Exchange (ETDEWEB)

Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Elgindy, Tarek [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dobbs, Alex [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-10-03

A framework for assessing the performance of short-term solar forecasting is presented in conjunction with a range of numerical results using global horizontal irradiation (GHI) from the open-source Surface Radiation Budget (SURFRAD) data network. A suite of popular machine learning algorithms is compared according to a set of statistically distinct metrics and benchmarked against the persistence-of-cloudiness forecast and a cloud motion forecast. Results show significant improvement compared to the benchmarks with trade-offs among the machine learning algorithms depending on the desired error metric. Training inputs include time series observations of GHI for a history of years, historical weather and atmospheric measurements, and corresponding date and time stamps such that training sensitivities might be inferred. Prediction outputs are GHI forecasts for 1, 2, 3, and 4 hours ahead of the issue time, and they are made for every month of the year for 7 locations. Photovoltaic power and energy outputs can then be made using the solar forecasts to better understand power system impacts.

DEEP LEARNING MODEL FOR BILINGUAL SENTIMENT CLASSIFICATION OF SHORT TEXTS

Directory of Open Access Journals (Sweden)

Y. B. Abdullin

2017-01-01

Full Text Available Sentiment analysis of short texts such as Twitter messages and comments in news portals is challenging due to the lack of contextual information. We propose a deep neural network model that uses bilingual word embeddings to effectively solve sentiment classification problem for a given pair of languages. We apply our approach to two corpora of two different language pairs: English-Russian and Russian-Kazakh. We show how to train a classifier in one language and predict in another. Our approach achieves 73% accuracy for English and 74% accuracy for Russian. For Kazakh sentiment analysis, we propose a baseline method, that achieves 60% accuracy; and a method to learn bilingual embeddings from a large unlabeled corpus using a bilingual word pairs.

A JET BREAK IN THE X-RAY LIGHT CURVE OF SHORT GRB 111020A: IMPLICATIONS FOR ENERGETICS AND RATES

International Nuclear Information System (INIS)

Fong, W.; Berger, E.; Margutti, R.; Zauderer, B. A.; Czekala, I.; Chornock, R.; Troja, E.; Gehrels, N.; Sakamoto, T.; Fox, D. B.; Podsiadlowski, P.

2012-01-01

We present broadband observations of the afterglow and environment of the short GRB 111020A. An extensive X-ray light curve from Swift/XRT, XMM-Newton, and Chandra, spanning ∼100 s to 10 days after the burst, reveals a significant break at δt ≈ 2 days with pre- and post-break decline rates of α X,1 ≈ –0.78 and α X,2 ∼ j ≈ 3°-8°. The resulting beaming-corrected γ-ray (10-1000 keV band) and blast-wave kinetic energies are (2-3) × 10 48 erg and (0.3-2) × 10 49 erg, respectively, with the range depending on the unknown redshift of the burst. We report a radio afterglow limit of c X , constrains the circumburst density to n 0 ∼ 0.01-0.1 cm –3 . Optical observations provide an afterglow limit of i ∼> 24.4 mag at 18 hr after the burst and reveal a potential host galaxy with i ≈ 24.3 mag. The subarcsecond localization from Chandra provides a precise offset of 0.''80 ± 0.''11 (1σ) from this galaxy corresponding to an offset of 5-7 kpc for z 0.5-1.5. We find a high excess neutral hydrogen column density of (7.5 ± 2.0) × 10 21 cm –2 (z = 0). Our observations demonstrate that a growing fraction of short gamma-ray bursts (GRBs) are collimated, which may lead to a true event rate of ∼> 100-1000 Gpc –3 yr –1 , in good agreement with the NS-NS merger rate of ≈200-3000 Gpc –3 yr –1 . This consistency is promising for coincident short GRB-gravitational wave searches in the forthcoming era of Advanced LIGO/VIRGO.

Motor Habits in Visuo-manual Tracking: Manifestation of an Unconscious Short-Term Motor Memory?

Directory of Open Access Journals (Sweden)

Andreas Hufschmidt

1990-01-01

Full Text Available Normal subjects were tested in short, repetitive trials of a tracking task, with an identical shape of target movement being used throughout one session. Analysis of the net error curves (pursuit minus target movement revealed that subjects regularly exhibit a remoteness effect: neighbouring trials were more similar than distant ones. The effect is demonstrated to be stronger in the absence of visual cues, and was found to be absent in a patient with complete loss of proprioception when he was performing without visual feedback as well. The results are discussed in terms of a short term memory store contributing to unconscious movement habits in tracking. This may represent part of the motor learning process working together with conscious visuo-motor control mechanisms. Its function is probably related to the acquisition of automatic movements.

Facilitating students' application of the integral and the area under the curve concepts in physics problems

Science.gov (United States)

Nguyen, Dong-Hai

This research project investigates the difficulties students encounter when solving physics problems involving the integral and the area under the curve concepts and the strategies to facilitate students learning to solve those types of problems. The research contexts of this project are calculus-based physics courses covering mechanics and electromagnetism. In phase I of the project, individual teaching/learning interviews were conducted with 20 students in mechanics and 15 students from the same cohort in electromagnetism. The students were asked to solve problems on several topics of mechanics and electromagnetism. These problems involved calculating physical quantities (e.g. velocity, acceleration, work, electric field, electric resistance, electric current) by integrating or finding the area under the curve of functions of related quantities (e.g. position, velocity, force, charge density, resistivity, current density). Verbal hints were provided when students made an error or were unable to proceed. A total number of 140 one-hour interviews were conducted in this phase, which provided insights into students' difficulties when solving the problems involving the integral and the area under the curve concepts and the hints to help students overcome those difficulties. In phase II of the project, tutorials were created to facilitate students' learning to solve physics problems involving the integral and the area under the curve concepts. Each tutorial consisted of a set of exercises and a protocol that incorporated the helpful hints to target the difficulties that students expressed in phase I of the project. Focus group learning interviews were conducted to test the effectiveness of the tutorials in comparison with standard learning materials (i.e. textbook problems and solutions). Overall results indicated that students learning with our tutorials outperformed students learning with standard materials in applying the integral and the area under the curve

Digital tomosynthesis for evaluating metastatic lung nodules: nodule visibility, learning curves, and reading times.

Science.gov (United States)

Lee, Kyung Hee; Goo, Jin Mo; Lee, Sang Min; Park, Chang Min; Bahn, Young Eun; Kim, Hyungjin; Song, Yong Sub; Hwang, Eui Jin

2015-01-01

To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computer-aided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, ≤ 5 mm). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

Characterizing time series via complexity-entropy curves

Science.gov (United States)

Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

Optimisation of CERN tools & methods for e-learning The case of short online tutorials

CERN Document Server

AUTHOR|(CDS)2133881; Dimou, Maria

2016-12-08

The term “e-learning” is directly related to the practice of distance education, which started about one hundred and fifty years ago. At this time, it was possible for lecturers to teach using means such as mail, phone, radio or television. With the progress made in the field of telecommunications, the Internet and the web allowed people to drastically extend their ability to learn through various means, avoiding the constraints of location and time. It is often difficult to know exactly what is covered by the word “e-learning”. The concepts of MOOC or blended learning are very popular nowadays, whereas fewer people know precisely what rapid e-learning is. This particular type of distance education is often used for quickly teaching procedures to people, using, for example, short online video tutorials. This form of education will be the one focused on for this thesis. We collaborated for six months with the European Organisation for Nuclear Research (CERN), to provide an analysis and recommendations ...

The Relationships among Verbal Short-Term Memory, Phonological Awareness, and New Word Learning: Evidence from Typical Development and Down Syndrome

Science.gov (United States)

Jarrold, Christopher; Thorn, Annabel S. C.; Stephens, Emma

2009-01-01

This study examined the correlates of new word learning in a sample of 64 typically developing children between 5 and 8 years of age and a group of 22 teenagers and young adults with Down syndrome. Verbal short-term memory and phonological awareness skills were assessed to determine whether learning new words involved accurately representing…

LCC: Light Curves Classifier

Science.gov (United States)

Vo, Martin

2017-08-01

Light Curves Classifier uses data mining and machine learning to obtain and classify desired objects. This task can be accomplished by attributes of light curves or any time series, including shapes, histograms, or variograms, or by other available information about the inspected objects, such as color indices, temperatures, and abundances. After specifying features which describe the objects to be searched, the software trains on a given training sample, and can then be used for unsupervised clustering for visualizing the natural separation of the sample. The package can be also used for automatic tuning parameters of used methods (for example, number of hidden neurons or binning ratio). Trained classifiers can be used for filtering outputs from astronomical databases or data stored locally. The Light Curve Classifier can also be used for simple downloading of light curves and all available information of queried stars. It natively can connect to OgleII, OgleIII, ASAS, CoRoT, Kepler, Catalina and MACHO, and new connectors or descriptors can be implemented. In addition to direct usage of the package and command line UI, the program can be used through a web interface. Users can create jobs for ”training” methods on given objects, querying databases and filtering outputs by trained filters. Preimplemented descriptors, classifier and connectors can be picked by simple clicks and their parameters can be tuned by giving ranges of these values. All combinations are then calculated and the best one is used for creating the filter. Natural separation of the data can be visualized by unsupervised clustering.

The trade-off between short- and long-lived greenhouse gases under uncertainty and learning

International Nuclear Information System (INIS)

Aaheim, H. Asbjoern; Brekke, Kjell Arne; Lystad, Terje; Torvanger, Asbjoern

2001-01-01

To find an optimal climate policy we must balance abatement of different greenhouse gases. There is substantial uncertainty about future damages from climate change, but we will learn more over the next few decades. Gases vary in terms of how long they remain in the atmosphere, which means that equivalent pulse emissions have very different climate impacts. Such differences between gases are important in consideration of uncertainty and learning about future damages, but they are disregarded by the conventional concept of Global Warming Potential We have developed a numerical model to analyze how uncertainty and learning affect optimal emissions of both CO 2 and CH 4 . In the model, emissions of these greenhouse gases lead to global temperature increases and production losses. New information about the severity of the climate problem arrives either in 2010 or in 2020. We find that uncertainty causes increased optimal abatement of both gases, compared to the certainty case. This effect amounts to 0.08 o C less expected temperature increase by year 2200. Learning leads to less abatement for both gases since expected future marginal damages from emissions are reduced. This effect is less pronounced for the short-lived CH 4 . (author)

What have we learned from quantum field theory in curved space-time

International Nuclear Information System (INIS)

Fulling, S.A.

1984-01-01

The paper reviews the quantum field theory in curved space-time. Field quantization in gravitational backgrounds; particle creation by black holes; Hawking radiation; quantum field theory in curved space-time; covariant renormalization of the stress-energy-momentum tensor; quantum field theory and quantum gravity; are all discussed. (U.K.)

NEPTUNE'S DYNAMIC ATMOSPHERE FROM KEPLER K2 OBSERVATIONS: IMPLICATIONS FOR BROWN DWARF LIGHT CURVE ANALYSES.

Science.gov (United States)

Simon, Amy A; Rowe, Jason F; Gaulme, Patrick; Hammel, Heidi B; Casewell, Sarah L; Fortney, Jonathan J; Gizis, John E; Lissauer, Jack J; Morales-Juberias, Raul; Orton, Glenn S; Wong, Michael H; Marley, Mark S

2016-02-01

Observations of Neptune with the Kepler Space Telescope yield a 49 day light curve with 98% coverage at a 1 minute cadence. A significant signature in the light curve comes from discrete cloud features. We compare results extracted from the light curve data with contemporaneous disk-resolved imaging of Neptune from the Keck 10-m telescope at 1.65 microns and Hubble Space Telescope visible imaging acquired nine months later. This direct comparison validates the feature latitudes assigned to the K2 light curve periods based on Neptune's zonal wind profile, and confirms observed cloud feature variability. Although Neptune's clouds vary in location and intensity on short and long timescales, a single large discrete storm seen in Keck imaging dominates the K2 and Hubble light curves; smaller or fainter clouds likely contribute to short-term brightness variability. The K2 Neptune light curve, in conjunction with our imaging data, provides context for the interpretation of current and future brown dwarf and extrasolar planet variability measurements. In particular we suggest that the balance between large, relatively stable, atmospheric features and smaller, more transient, clouds controls the character of substellar atmospheric variability. Atmospheres dominated by a few large spots may show inherently greater light curve stability than those which exhibit a greater number of smaller features.

The learning curve, interobserver, and intraobserver agreement of endoscopic confocal laser endomicroscopy in the assessment of mucosal barrier defects.

Science.gov (United States)

Chang, Jeff; Ip, Matthew; Yang, Michael; Wong, Brendon; Power, Theresa; Lin, Lisa; Xuan, Wei; Phan, Tri Giang; Leong, Rupert W

2016-04-01

Confocal laser endomicroscopy can dynamically assess intestinal mucosal barrier defects and increased intestinal permeability (IP). These are functional features that do not have corresponding appearance on histopathology. As such, previous pathology training may not be beneficial in learning these dynamic features. This study aims to evaluate the diagnostic accuracy, learning curve, inter- and intraobserver agreement for identifying features of increased IP in experienced and inexperienced analysts and pathologists. A total of 180 endoscopic confocal laser endomicroscopy (Pentax EC-3870FK; Pentax, Tokyo, Japan) images of the terminal ileum, subdivided into 6 sets of 30 were evaluated by 6 experienced analysts, 13 inexperienced analysts, and 2 pathologists, after a 30-minute teaching session. Cell-junction enhancement, fluorescein leak, and cell dropout were used to represent increased IP and were either present or absent in each image. For each image, the diagnostic accuracy, confidence, and quality were assessed. Diagnostic accuracy was significantly higher for experienced analysts compared with inexperienced analysts from the first set (96.7% vs 83.1%, P 0.86 for experienced observers. Features representative of increased IP can be rapidly learned with high inter- and intraobserver agreement. Confidence and image quality were significant predictors of accurate interpretation. Previous pathology training did not have an effect on learning. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

Science.gov (United States)

Piastra, Marco

2013-05-01

Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

Lagrangian Curves on Spectral Curves of Monopoles

International Nuclear Information System (INIS)

Guilfoyle, Brendan; Khalid, Madeeha; Ramon Mari, Jose J.

2010-01-01

We study Lagrangian points on smooth holomorphic curves in TP 1 equipped with a natural neutral Kaehler structure, and prove that they must form real curves. By virtue of the identification of TP 1 with the space LE 3 of oriented affine lines in Euclidean 3-space, these Lagrangian curves give rise to ruled surfaces in E 3 , which we prove have zero Gauss curvature. Each ruled surface is shown to be the tangent lines to a curve in E 3 , called the edge of regression of the ruled surface. We give an alternative characterization of these curves as the points in E 3 where the number of oriented lines in the complex curve Σ that pass through the point is less than the degree of Σ. We then apply these results to the spectral curves of certain monopoles and construct the ruled surfaces and edges of regression generated by the Lagrangian curves.

A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

Directory of Open Access Journals (Sweden)

Qiang Shang

Full Text Available Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS. Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM is proposed based on singular spectrum analysis (SSA and kernel extreme learning machine (KELM. SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

Quantifying and Reducing Curve-Fitting Uncertainty in Isc

Energy Technology Data Exchange (ETDEWEB)

Campanelli, Mark; Duck, Benjamin; Emery, Keith

2015-06-14

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.

Contrasting contributions of phonological short-term memory and long-term knowledge to vocabulary learning in a foreign language.

Science.gov (United States)

Masoura, Elvira V; Gathercole, Susan E

2005-01-01

The contributions of phonological short-term memory and existing foreign vocabulary knowledge to the learning of new words in a second language were compared in a sample of 40 Greek children studying English at school. The children's speed of learning new English words in a paired-associate learning task was strongly influenced by their current English vocabulary, but was independent of phonological memory skill, indexed by nonword repetition ability. However, phonological memory performance was closely linked to English vocabulary scores. The findings suggest that in learners with considerable familiarity with a second language, foreign vocabulary acquisition is mediated largely by use of existing knowledge representations.

Empirical Analysis on The Existence of The Phillips Curve

Directory of Open Access Journals (Sweden)

Shaari Mohd Shahidan

2018-01-01

Full Text Available The Phillips curve shows the trade-off relationship between the inflation and unemployment rates. A rise in inflation due to the high economic growth, more jobs are available and therefore unemployment will fall. However, the existence of the Phillips curve in high-income countries has not been much discussed. Countries with high income should have low unemployment rate, suggesting a high inflation. However, some high-income countries, the United States in 1970s for example, could not avert stagflation whereby high unemployment rate and inflation occurred in the same time. This situation is contrary to the Phillips curve. Therefore, this study aims to investigate the existence of the Phillips curve in high-income countries for the period 1990-2014 using the panel data analysis. The most interesting finding of this study is the existence of a bidirectional relationship between unemployment rate and inflation rate in both long and short runs. Therefore, the governments should choose to stabilize inflation rate or reduce unemployment rate

An initial investigation on developing a new method to predict short-term breast cancer risk based on deep learning technology

Science.gov (United States)

Qiu, Yuchen; Wang, Yunzhi; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Liu, Hong; Zheng, Bin

2016-03-01

In order to establish a new personalized breast cancer screening paradigm, it is critically important to accurately predict the short-term risk of a woman having image-detectable cancer after a negative mammographic screening. In this study, we developed and tested a novel short-term risk assessment model based on deep learning method. During the experiment, a number of 270 "prior" negative screening cases was assembled. In the next sequential ("current") screening mammography, 135 cases were positive and 135 cases remained negative. These cases were randomly divided into a training set with 200 cases and a testing set with 70 cases. A deep learning based computer-aided diagnosis (CAD) scheme was then developed for the risk assessment, which consists of two modules: adaptive feature identification module and risk prediction module. The adaptive feature identification module is composed of three pairs of convolution-max-pooling layers, which contains 20, 10, and 5 feature maps respectively. The risk prediction module is implemented by a multiple layer perception (MLP) classifier, which produces a risk score to predict the likelihood of the woman developing short-term mammography-detectable cancer. The result shows that the new CAD-based risk model yielded a positive predictive value of 69.2% and a negative predictive value of 74.2%, with a total prediction accuracy of 71.4%. This study demonstrated that applying a new deep learning technology may have significant potential to develop a new short-term risk predicting scheme with improved performance in detecting early abnormal symptom from the negative mammograms.

Sustained Cortical and Subcortical Measures of Auditory and Visual Plasticity following Short-Term Perceptual Learning.

Science.gov (United States)

Lau, Bonnie K; Ruggles, Dorea R; Katyal, Sucharit; Engel, Stephen A; Oxenham, Andrew J

2017-01-01

Short-term training can lead to improvements in behavioral discrimination of auditory and visual stimuli, as well as enhanced EEG responses to those stimuli. In the auditory domain, fluency with tonal languages and musical training has been associated with long-term cortical and subcortical plasticity, but less is known about the effects of shorter-term training. This study combined electroencephalography (EEG) and behavioral measures to investigate short-term learning and neural plasticity in both auditory and visual domains. Forty adult participants were divided into four groups. Three groups trained on one of three tasks, involving discrimination of auditory fundamental frequency (F0), auditory amplitude modulation rate (AM), or visual orientation (VIS). The fourth (control) group received no training. Pre- and post-training tests, as well as retention tests 30 days after training, involved behavioral discrimination thresholds, steady-state visually evoked potentials (SSVEP) to the flicker frequencies of visual stimuli, and auditory envelope-following responses simultaneously evoked and measured in response to rapid stimulus F0 (EFR), thought to reflect subcortical generators, and slow amplitude modulation (ASSR), thought to reflect cortical generators. Enhancement of the ASSR was observed in both auditory-trained groups, not specific to the AM-trained group, whereas enhancement of the SSVEP was found only in the visually-trained group. No evidence was found for changes in the EFR. The results suggest that some aspects of neural plasticity can develop rapidly and may generalize across tasks but not across modalities. Behaviorally, the pattern of learning was complex, with significant cross-task and cross-modal learning effects.

Modeling Patterns of Activities using Activity Curves.

Science.gov (United States)

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-06-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

Growth curve models and statistical diagnostics

CERN Document Server

Pan, Jian-Xin

2002-01-01

Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.

Clinical experience with the first 40 cases with femtosecond laser cataract surgery technology: safety of the learning curve

Directory of Open Access Journals (Sweden)

Joao Crispim

2015-10-01

Full Text Available ABSTRACT Objective: To evaluate the introduction of the femtosecond laser (FSL to perform the key steps of the traditional cataract surgery process and the operational difficulties and safety of this new technology during routine use in an operating room in Brazil. Methods A retrospective study was conducted using the first cases operated on at a single center using the laser platform LenSx/Alcon with a soft contact lens patient interface.All patients underwent a detailed preoperative assessment.The anterior capsulotomy, nuclear fragmentation, and corneal incisions were created with the FSL; then, the surgery was completed following the standard phacoemulsification procedure. The main outcome measurements were difficulties and complications related to the learning curve and an analysis of postoperative uncorrected distance visual acuity (UDVA. Results: Of 31 patients (40 eyes, 9 patients had FSL cataract surgery in both eyes.The mean age was 64 ± 12 years (ranging from 42 to 82, the mean cataract nuclear sclerosis was grading 2 ± 0.6 (ranging from 1 to 4, and the preoperative mean UDVA in logMAR was 0.4 ± 0.2 (ranging from 0.1 to 1.3. Anterior capsulotomy was complete in all patients, and scissors were not needed to cut off any intact portion. The postoperative corneal incisions were not completely linear and showed some irregularities. Laser phaco-fragmentation was effective, with the division of the nucleus into smaller segments easily performed before phacoemulsification.After 1 month, the postoperative mean UDVA in logMAR was 0.1 ± 0.1 (ranging from 0.0 to 0.4 (P < 0.0001. Conclusion: With increasing surgical cases and experience, the phacoemulsification steps are performed precisely and effectively with FSL pretreatment, resulting in a safe learning curve.

The integration of computerised accounting in the accounting curriculum as an educational learning curve for students entering the business world

Directory of Open Access Journals (Sweden)

Elmarie Papageorgiou

2014-06-01

Full Text Available At universities, educating students on real-life practices is one of the key drivers in a changing academic environment. Academic institutions encourage the study of the learning environment and ensure that appropriate strategies are in place for educating students. A first-year Accounting I student stated the importance of computerised accounting: ‘Computerised accounting is used in the workplace and therefore using it in varsity, grants students a view on how things will be after completion of their respective degrees.’ Accordingly, the purpose of this study was to empirically investigate the perceived acquisition of information technology (IT knowledge and determine the skills required for students to convert the knowledge gained into actions as a learning curve for accounting students entering the business world. The results indicated that students’ knowledge of Accounting I increased with the integration of computerised Accounting in the Accounting I Curriculum.

The Effects of Age on Short-Term Memory Loss due to Proactive Interference

Directory of Open Access Journals (Sweden)

Alisha Berkauzer

2011-01-01

Full Text Available This project focused on how proactive interference affects the short-term memory of people based on their age. The goal was to find the prime age for learning information and storing it in one's memory. Seven people from ages fifteen to forty were tested individually, using a set color pattern, in order to see how well each individual could remember the different color patterns as difficulty of the pattern increased. The obtained data was fitted by the polynomial regression. The “fitted” curve shows that as age increases, the individual's performance in memorizing the more difficult patterns decreases. Also, the peaked level of memory performance was found to be 24 for our experimental data.

The trade-off between short- and long-lived greenhouse gases under uncertainty and learning

Energy Technology Data Exchange (ETDEWEB)

Aaheim, H. Asbjoern; Brekke, Kjell Arne; Lystad, Terje; Torvanger, Asbjoern

2001-07-01

To find an optimal climate policy we must balance abatement of different greenhouse gases. There is substantial uncertainty about future damages from climate change, but we will learn more over the next few decades. Gases vary in terms of how long they remain in the atmosphere, which means that equivalent pulse emissions have very different climate impacts. Such differences between gases are important in consideration of uncertainty and learning about future damages, but they are disregarded by the conventional concept of Global Warming Potential We have developed a numerical model to analyze how uncertainty and learning affect optimal emissions of both CO{sub 2} and CH{sub 4}. In the model, emissions of these greenhouse gases lead to global temperature increases and production losses. New information about the severity of the climate problem arrives either in 2010 or in 2020. We find that uncertainty causes increased optimal abatement of both gases, compared to the certainty case. This effect amounts to 0.08 {sup o}C less expected temperature increase by year 2200. Learning leads to less abatement for both gases since expected future marginal damages from emissions are reduced. This effect is less pronounced for the short-lived CH{sub 4}. (author)

Evaluating the Learning Curve for Percutaneous Nephrolithotomy under Total Ultrasound Guidance.

Directory of Open Access Journals (Sweden)

Yan Song

Full Text Available To investigate the learning curve of percutaneous nephrolithotomy under total ultrasound guidance.One hundred and twenty consecutive PCNL operations under total ultrasound guidance performed by a novice surgeon in a tertiary referral center were studied. Operations were analyzed in cohorts of 15 to determine when a plateau was reached for the variables such as operation duration, ultrasound screening time, tract dilation time, stone-free rate and complication rate. Comparison was made with the results of a surgeon who had performed more than 1000 PCNLs. Fluoroscopy was not used at all during procedure.The mean operation time dropped from 82.5 min for the first 15 patients to a mean of 64.7 min for cases 46 through 60(P = 0.047. The ultrasound screening time was a peak of 6.4 min in the first 15 cases, whereas it dropped to a mean of 3.9 min for cases 46 through 60(P = 0.01. The tract dilation time dropped from 4.9 min for the first 15 patients to a mean of 3.8 min for cases 46 through 60(P = 0.036. The senior surgeon had a mean operating time, screening time and tract dilation time equivalent to those of the novice surgeon after 60 cases. There was no significant difference in stone free rate and complication rate.The competence of ultrasound guided PCNL is reached after 60 cases with good stone free rate and without major complications.

Intensive Monitoring Survey of Nearby Galaxies (IMSNG): Catching Early Light Curves of Supernovae

Science.gov (United States)

Im, Myungshin; IMSNG Team

2018-01-01

SNe light curves have been used to study the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). This poster outlines this project, and present a few scientific highlights, such as the early light curve of SN 2015F in NGC 2442.

Effects of short-term training on behavioral learning and skill acquisition during intraoral fine motor task

DEFF Research Database (Denmark)

Kumar, Abhishek; Grigoriadis, Joannis; Trulsson, Mats

2015-01-01

Sensory information from the orofacial mechanoreceptors are used by the nervous system to optimize the positioning of food, determine the force levels, and force vectors involved in biting of food morsels. Moreover, practice resulting from repetition could be a key to learning and acquiring a motor...... movements. Thirty healthy volunteers were asked to intraorally manipulate and split a chocolate candy, into two equal halves. The participants performed three series (with ten 10 trials) of the task before and after a short-term (approximately 30min) training. The accuracy of the split and vertical jaw...... task induces behavior learning, skill acquisition and optimization of jaw movements in terms of better performance and reduction in the duration of jaw movements, during the task. The finding of the present study provides insights on into how humans learn oral motor behaviors or the kind of adaptation...

TMI-2 Lessons Learned Task Force status report and short-term recommendations

International Nuclear Information System (INIS)

1979-07-01

Review of the Three Mile Island accident by the TMI-2 Lessons Learned Task Force has disclosed a number of actions in the areas of design and analysis and plant operations that the Task Force recommends be required in the short term to provide substantial additional protection which is required for the public health and safety. All nuclear power plants in operation or in various stages of construction or licensing action are affected to varying degrees by the specific recommendations. The Task Force is continuing work in areas of general safety criteria, systems design requirements, nuclear power plant operations, and nuclear power plant licensing

Internal attention to features in visual short-term memory guides object learning.

Science.gov (United States)

Fan, Judith E; Turk-Browne, Nicholas B

2013-11-01

Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of the learning curve of non-penetrating glaucoma surgery.

Science.gov (United States)

Aslan, Fatih; Yuce, Berna; Oztas, Zafer; Ates, Halil

2017-08-11

To evaluate the learning curve of non-penetrating glaucoma surgery (NPGS). The study included 32 eyes of 27 patients' (20 male and 7 female) with medically uncontrolled glaucoma. Non-penetrating glaucoma surgeries performed by trainees under control of an experienced surgeon between 2005 and 2007 at our tertiary referral hospital were evaluated. Residents were separated into two groups. Humanistic training model applied to the one in the first group, he studied with experimental models before performing NPGS. Two residents in the second group performed NPGS after a conventional training model. Surgeries of the residents were recorded on video and intraoperative parameters were scored by the experienced surgeon at the end of the study. Postoperative intraocular pressure, absolute and total success rates were analyzed. In the first group 19 eyes of 16 patients and in the second group 13 eyes of 11 patients had been operated by residents. Intraoperative parameters and complication rates were not statistically significant between groups (p > 0.05, Chi-square). The duration of surgery was 32.7 ± 5.6 min in the first group and 45 ± 3.8 min in the second group. The difference was statistically significant (p < 0.001, Student's t test). Absolute and total success was 68.8 and 93.8% in the first group and 62.5 and 87.5% in the second group, respectively. The difference was not statistically significant. Humanistic and conventional training models under control of an experienced surgeon are safe and effective for senior residents who manage phacoemulsification surgery in routine cataract cases. Senior residents can practice these surgical techniques with reasonable complication rates.

Discriminating Children with Autism from Children with Learning Difficulties with an Adaptation of the Short Sensory Profile

Science.gov (United States)

O'Brien, Justin; Tsermentseli, Stella; Cummins, Omar; Happe, Francesca; Heaton, Pamela; Spencer, Janine

2009-01-01

In this article, we examine the extent to which children with autism and children with learning difficulties can be discriminated from their responses to different patterns of sensory stimuli. Using an adapted version of the Short Sensory Profile (SSP), sensory processing was compared in 34 children with autism to 33 children with typical…

Learning curve of robot-assisted laparoscopic radical prostatectomy for a single experienced surgeon: comparison with simultaneous laparoscopic radical prostatectomy.

Science.gov (United States)

Ku, Ja Yoon; Ha, Hong Koo

2015-04-01

Despite the large number of analytical reports regarding the learning curve in the transition from open to robot-assisted radical prostatectomy (RARP), few comparative results with laparoscopic radical prostatectomy (LRP) have been reported. Thus, we evaluated operative and postoperative outcomes in RARP versus 100 simultaneously performed LRPs. A single surgeon had performed more than 1,000 laparoscopic operations, including 415 cases of radical nephrectomy, 85 radical cystectomies, 369 radical prostatectomies, and treatment of 212 other urological tumors, since 2009. We evaluated operative (operation time, intraoperative transfusion, complications, hospital stay, margin status, pathological stage, Gleason score) and postoperative (continence and erectile function) parameters in initial cases of RARP without tutoring compared with 100 recently performed LRPs. Mean operation time and length of hospital stay for RARP and LRP were 145.5±43.6 minutes and 118.1±39.1 minutes, and 6.4±0.9 days and 6.6±1.1 days, respectively (p=0.003 and p=0.721). After 17 cases, the mean operation time for RARP was similar to LRP (less than 2 hours). Positive surgical margins in localized cancer were seen in 11.1% and 8.9% of cases in RARP and LRP, respectively (p=0.733). At postoperative 3 months, sexual intercourse was reported in 14.0% and 12.0%, and pad-free continence in 96.0% and 81.0% in patients with RARP and LRP, respectively (p=0.796 and p=0.012). Previous large-volume experience of LRPs may shorten the learning curve for RARP in terms of oncological outcome. Additionally, previous experience with laparoscopy may improve the functional outcomes of RARP.

Reliability assessment of a manual-based procedure towards learning curve modeling and fmea analysis

Directory of Open Access Journals (Sweden)

Gustavo Rech

2013-03-01

Full Text Available Separation procedures in drug Distribution Centers (DC are manual-based activities prone to failures such as shipping exchanged, expired or broken drugs to the customer. Two interventions seem as promising in improving the reliability in the separation procedure: (i selection and allocation of appropriate operators to the procedure, and (ii analysis of potential failure modes incurred by selected operators. This article integrates Learning Curves (LC and FMEA (Failure Mode and Effect Analysis aimed at reducing the occurrence of failures in the manual separation of a drug DC. LCs parameters enable generating an index to identify the recommended operators to perform the procedures. The FMEA is then applied to the separation procedure carried out by the selected operators in order to identify failure modes. It also deployed the traditional FMEA severity index into two sub-indexes related to financial issues and damage to company´s image in order to characterize failures severity. When applied to a drug DC, the proposed method significantly reduced the frequency and severity of failures in the separation procedure.

Prediction of long-term creep curves

International Nuclear Information System (INIS)

Oikawa, Hiroshi; Maruyama, Kouichi

1992-01-01

This paper aims at discussing how to predict long-term irradiation enhanced creep properties from short-term tests. The predictive method based on the θ concept was examined by using creep data of ferritic steels. The method was successful in predicting creep curves including the tertiary creep stage as well as rupture lifetimes. Some material constants involved in the method are insensitive to the irradiation environment, and their values obtained in thermal creep are applicable to irradiation enhanced creep. The creep mechanisms of most engineering materials definitely change at the athermal yield stress in the non-creep regime. One should be aware that short-term tests must be carried out at stresses lower than the athermal yield stress in order to predict the creep behavior of structural components correctly. (orig.)

Validation of the NASA-TLX Score in Ongoing Assessment of Mental Workload During a Laparoscopic Learning Curve in Bariatric Surgery.

Science.gov (United States)

Ruiz-Rabelo, Juan Francisco; Navarro-Rodriguez, Elena; Di-Stasi, Leandro Luigi; Diaz-Jimenez, Nelida; Cabrera-Bermon, Juan; Diaz-Iglesias, Carlos; Gomez-Alvarez, Manuel; Briceño-Delgado, Javier

2015-12-01

Fatigue and mental workload are directly associated with high-complexity tasks. In general, difficult tasks produce a higher mental workload, leaving little opportunity to deal with new/unexpected events and increasing the likelihood of performance errors. The laparoscopic Roux-en-Y gastric bypass (LRYGB) learning curve is considered to be one of the most difficult to complete in laparoscopic surgery. We wished to validate the National Aeronautics and Space Administration Task Load Index (NASA-TLX) in LRYGB and identify factors that could provoke a higher mental workload for surgeons during the learning curve. A single surgeon was enrolled to undertake 70 consecutive LRYGB procedures with two internal surgeons mentoring the first 35 cases. Patients were consecutive and ranked from case 35 to case 105 according to the date of the surgical procedure ("case rank"). Self-ratings of satisfaction, performance, and fatigue were measured at the end of surgery using a validated NASA-TLX questionnaire. The procedure was recorded for later viewing by two external evaluators. General data for patients and surgical variables were collected prospectively. A moderate correlation between the NASA-TLX score, BMI, operative time, and volumes of blood drainage was observed. There was no correlation between the NASA-TLX score and duration of hospital stay or time of drain removal. BMI ≥50 kg/m(2), male sex, inexperienced first assistant, and type 2 diabetes mellitus were identified as independent predictive factors of a higher NASA-TLX score. The NASA-TLX is a valid tool to gauge mental workload in LRYGB.

Depletion of Serotonin Selectively Impairs Short-Term Memory without Affecting Long-Term Memory in Odor Learning in the Terrestrial Slug "Limax Valentianus"

Science.gov (United States)

Santa, Tomofumi; Kirino, Yutaka; Watanabe, Satoshi; Shirahata, Takaaki; Tsunoda, Makoto

2006-01-01

The terrestrial slug "Limax" is able to acquire short-term and long-term memories during aversive odor-taste associative learning. We investigated the effect of the selective serotonergic neurotoxin 5,7-dihydroxytryptamine (5,7-DHT) on memory. Behavioral studies indicated that 5,7-DHT impaired short-term memory but not long-term memory. HPLC…

Order short-term memory is not specifically impaired in dyslexia and does not affect orthographic learning

Directory of Open Access Journals (Sweden)

Eva eStaels

2014-09-01

Full Text Available This article reports two studies that investigate short-term memory (STM deficits in dyslexic children and explores the relationship between short-term memory and reading acquisition. In the first experiment, thirty-six dyslexic children and sixty-one control children performed an item STM task and a serial order STM task. The results of this experiment show that dyslexic children do not suffer from a specific serial order STM deficit. In addition, the results demonstrate that phonological processing skills are as closely related to both item STM and serial order STM. However, nonverbal intelligence was more strongly involved in serial order STM than in item STM. In the second experiment, the same two STM tasks were administered and reading acquisition was assessed by measuring orthographic learning in a group of one hundred and eighty-eight children. The results of this study show that orthographic learning is exclusively related to item STM and not to order STM. It is concluded that serial order STM is not the right place to look for a causal explanation of reading disability, nor for differences in word reading acquisition.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

Science.gov (United States)

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Study and program implementation of transient curves' piecewise linearization

International Nuclear Information System (INIS)

Shi Yang; Zu Hongbiao

2014-01-01

Background: Transient curves are essential for the stress analysis of related equipment in nuclear power plant (NPP). The actually operating data or the design transient data of a NPP usually consist of a large number of data points with very short time intervals. To simplify the analysis, transient curves are generally piecewise linearized in advance. Up to now, the piecewise linearization of transient curves is accomplished manually, Purpose: The aim is to develop a method for the piecewise linearization of transient curves, and to implement it by programming. Methods: First of all, the fitting line of a number of data points was obtained by the least square method. The segment of the fitting line is set while the accumulation error of linearization exceeds the preset limit with the increasing number of points. Then the linearization of subsequent data points was begun from the last point of the preceding curve segment to get the next segment in the same way, and continue until the final data point involved. Finally, averaging of junction points is taken for the segment connection. Results: A computer program named PLTC (Piecewise Linearization for Transient Curves) was implemented and verified by the linearization of the standard sine curve and typical transient curves of a NPP. Conclusion: The method and the PLTC program can be well used to the piecewise linearization of transient curves, with improving efficiency and precision. (authors)

"Short Courses Shouldn't Be Short-Lived!" Enhancing Longer-Term Impact of Short English as a Foreign Language INSET Initiatives in China

Science.gov (United States)

Yan, Chunmei; He, Chuanjun

2015-01-01

Short in-service teacher development (INSET) programmes have been globally used as a form of teacher development, but their impact has been under question. This study sought to examine teacher participants' perceptions of short INSET programmes to come up with better solutions to enhancing their effect on teachers' professional learning. A…

Role of olfaction in the foraging behavior and trial-and-error learning in short-nosed fruit bat, Cynopterus sphinx.

Science.gov (United States)

Zhang, Wei; Zhu, Guangjian; Tan, Liangjing; Yang, Jian; Chen, Yi; Liu, Qi; Shen, Qiqi; Chen, Jinping; Zhang, Libiao

2014-03-01

We observed the foraging behavior of short-nosed fruit bats, Cynopterus sphinx, in captivity. The role of olfaction in their foraging behavior was examined using real fruit, mimetic fruit, and mimetic fruit soaked in the juice of real fruit. The results showed that C. sphinx visited the real fruit more often than the mimetic fruit, but they had no preference between real fruit and treated mimetic fruit. Our experiment indicates that this bat has the ability to find and identify fruit by olfaction. We also tested for behavior of trial-and-error learning. Our observations revealed that the bats could form a sensory memory of the olfactory cue (cedar wood oil) after five days of training because they responded to the olfactory cues. Our results provide the evidence that C. sphinx can establish the connection between the fruit and a non-natural odor through learning and memory with the assistance of olfaction, and can thus recognize a variety of odors by trial-and-error learning. This behavioral flexibility based on olfactory cues will be beneficial for the short-nosed fruit bat in foraging. Copyright © 2013 Elsevier B.V. All rights reserved.

Quantifying and Reducing Curve-Fitting Uncertainty in Isc: Preprint

Energy Technology Data Exchange (ETDEWEB)

Campanelli, Mark; Duck, Benjamin; Emery, Keith

2015-09-28

Current-voltage (I-V) curve measurements of photovoltaic (PV) devices are used to determine performance parameters and to establish traceable calibration chains. Measurement standards specify localized curve fitting methods, e.g., straight-line interpolation/extrapolation of the I-V curve points near short-circuit current, Isc. By considering such fits as statistical linear regressions, uncertainties in the performance parameters are readily quantified. However, the legitimacy of such a computed uncertainty requires that the model be a valid (local) representation of the I-V curve and that the noise be sufficiently well characterized. Using more data points often has the advantage of lowering the uncertainty. However, more data points can make the uncertainty in the fit arbitrarily small, and this fit uncertainty misses the dominant residual uncertainty due to so-called model discrepancy. Using objective Bayesian linear regression for straight-line fits for Isc, we investigate an evidence-based method to automatically choose data windows of I-V points with reduced model discrepancy. We also investigate noise effects. Uncertainties, aligned with the Guide to the Expression of Uncertainty in Measurement (GUM), are quantified throughout.

Push-off forces in elite short-track speed skating.

Science.gov (United States)

van der Kruk, Eline; Reijne, Marco M; de Laat, Bjorn; Veeger, DirkJan H E J

2018-05-30

This study performed an analysis of the push-off forces of elite-short-track speed skaters using a new designed instrumented short-track speed skate with the aim to improve short-track skating performance. Four different skating strokes were distinguished for short-track speed skaters at speed. The strokes differed in stroke time, force level in both normal and lateral directions, and the centre of pressure (COP) on the blade. Within the homogeneous group of male elite speed skaters (N = 6), diversity of execution of the force patterns in the four phases of skating was evident, while skating at the same velocities. The male participants (N = 6) with a better personal record (PR) kept the COP more to the rear of their blades while hanging into the curve (r = 0.82, p < 0.05), leaving the curve (r = 0.86, p < 0.05), and entering the straight (r = 0.76, p < 0.10). Furthermore, the male skaters with a better PR showed a trend of a lower lateral peak force while entering the curve (r = 0.74, p < 0.10). Females showed a trend towards applying higher body weight normalised lateral forces than the males, while skating at imposed lower velocities.

Analytical studies by activation. Part A and B: Counting of short half-life radio-nuclides. Part C: Analytical programs for decay curves

International Nuclear Information System (INIS)

Junod, E.

1966-03-01

Part A and B: Since a radio-nuclide of short half-life is characterized essentially by the decrease in its activity even while it is being measured, the report begins by recalling the basic relationships linking the half-life the counting time, the counting rate and the number of particles recorded. The second part is devoted to the problem of corrections for counting losses due to the idle period of multichannel analyzers. Exact correction formulae have been drawn up for the case where the short half-life radionuclide is pure or contains only a long half-life radio-nuclide. By comparison, charts have been drawn up showing the approximations given by the so-called 'active time' counting and by the counting involving the real time associated with a measurement of the overall idle period, this latter method proving to be more valid than the former. A method is given for reducing the case of a complex mixture to that of a two-component mixture. Part C: The problems connected with the qualitative and quantitative analysis of the decay curves of a mixture of radioactive sources of which one at least has a short half-life are presented. A mathematical description is given of six basic processes for which some elements of Fortran programs are proposed. Two supplementary programs are drawn up for giving an overall treatment of problems of dosage in activation analysis: one on the basis of a simultaneous irradiation of the sample and of one or several known samples, the other with separate irradiation of the unknown and known samples, a dosimeter (activation, or external) being used for normalizing the irradiation flux conditions. (author) [fr

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

Science.gov (United States)

Bao, Wei; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

Directory of Open Access Journals (Sweden)

Wei Bao

Full Text Available The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT, stacked autoencoders (SAEs and long-short term memory (LSTM are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Mild decentration measured by a Scheimpflug camera and its impact on visual quality following SMILE in the early learning curve.

Science.gov (United States)

Li, Meiyan; Zhao, Jing; Miao, Huamao; Shen, Yang; Sun, Ling; Tian, Mi; Wadium, Elizabeth; Zhou, Xingtao

2014-05-20

To measure decentration following femtosecond laser small incision lenticule extraction (SMILE) for the correction of myopia and myopic astigmatism in the early learning curve, and to investigate its impact on visual quality. A total of 55 consecutive patients (100 eyes) who underwent the SMILE procedure were included. Decentration was measured using a Scheimpflug camera 6 months after surgery. Uncorrected and corrected distance visual acuity (UDVA, CDVA), manifest refraction, and wavefront errors were also measured. Associations between decentration and the preoperative spherical equivalent were analyzed, as well as the associations between decentration and wavefront aberrations. Regarding efficacy and safety, 40 eyes (40%) had an unchanged CDVA; 32 eyes (32%) gained one line; and 11 eyes (11%) gained two lines. Fifteen eyes (15%) lost one line of CDVA, and two eyes (2%) lost two lines. Ninety-nine of the treated eyes (99%) had a postoperative UDVA better than 1.0, and 100 eyes (100%) had a UDVA better than 0.8. The mean decentered displacement was 0.17 ± 0.09 mm. The decentered displacement of all treated eyes (100%) was within 0.50 mm; 70 eyes (70%) were within 0.20 mm; and 90 eyes (90%) were within 0.30 mm. The vertical coma showed the greatest increase in magnitude. The magnitude of horizontal decentration was found to be associated with an induced horizontal coma. This study suggests that, although mild decentration occurred in the early learning curve, good visual outcomes were achieved after the SMILE surgery. Special efforts to minimize induced vertical coma are necessary. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Retrieval practice with short-answer, multiple-choice, and hybrid tests.

Science.gov (United States)

Smith, Megan A; Karpicke, Jeffrey D

2014-01-01

Retrieval practice improves meaningful learning, and the most frequent way of implementing retrieval practice in classrooms is to have students answer questions. In four experiments (N=372) we investigated the effects of different question formats on learning. Students read educational texts and practised retrieval by answering short-answer, multiple-choice, or hybrid questions. In hybrid conditions students first attempted to recall answers in short-answer format, then identified answers in multiple-choice format. We measured learning 1 week later using a final assessment with two types of questions: those that could be answered by recalling information verbatim from the texts and those that required inferences. Practising retrieval in all format conditions enhanced retention, relative to a study-only control condition, on both verbatim and inference questions. However, there were little or no advantages of answering short-answer or hybrid format questions over multiple-choice questions in three experiments. In Experiment 4, when retrieval success was improved under initial short-answer conditions, there was an advantage of answering short-answer or hybrid questions over multiple-choice questions. The results challenge the simple conclusion that short-answer questions always produce the best learning, due to increased retrieval effort or difficulty, and demonstrate the importance of retrieval success for retrieval-based learning activities.

Marginal abatement cost curves and the optimal timing of mitigation measures

International Nuclear Information System (INIS)

Vogt-Schilb, Adrien; Hallegatte, Stéphane

2014-01-01

Decision makers facing abatement targets need to decide which abatement measures to implement, and in which order. Measure-explicit marginal abatement cost curves depict the cost and abating potential of available mitigation options. Using a simple intertemporal optimization model, we demonstrate why this information is not sufficient to design emission reduction strategies. Because the measures required to achieve ambitious emission reductions cannot be implemented overnight, the optimal strategy to reach a short-term target depends on longer-term targets. For instance, the best strategy to achieve European's −20% by 2020 target may be to implement some expensive, high-potential, and long-to-implement options required to meet the −75% by 2050 target. Using just the cheapest abatement options to reach the 2020 target can create a carbon-intensive lock-in and make the 2050 target too expensive to reach. Designing mitigation policies requires information on the speed at which various measures to curb greenhouse gas emissions can be implemented, in addition to the information on the costs and potential of such measures provided by marginal abatement cost curves. - Highlights: • Classification of existing Marginal Abatement Cost Curves (MACC). • MACCs do not provide separated data on the speed at which measures can be implemented. • Optimal measures to reach a short-term target depend on longer-term targets. • Unique carbon price or aggregated emission-reduction target may be insufficient. • Room for short-term sectoral policies if agents are myopic or governments cannot commit

Learning From Short Text Streams With Topic Drifts.

Science.gov (United States)

Li, Peipei; He, Lu; Wang, Haiyan; Hu, Xuegang; Zhang, Yuhong; Li, Lei; Wu, Xindong

2017-09-18

Short text streams such as search snippets and micro blogs have been popular on the Web with the emergence of social media. Unlike traditional normal text streams, these data present the characteristics of short length, weak signal, high volume, high velocity, topic drift, etc. Short text stream classification is hence a very challenging and significant task. However, this challenge has received little attention from the research community. Therefore, a new feature extension approach is proposed for short text stream classification with the help of a large-scale semantic network obtained from a Web corpus. It is built on an incremental ensemble classification model for efficiency. First, more semantic contexts based on the senses of terms in short texts are introduced to make up of the data sparsity using the open semantic network, in which all terms are disambiguated by their semantics to reduce the noise impact. Second, a concept cluster-based topic drifting detection method is proposed to effectively track hidden topic drifts. Finally, extensive studies demonstrate that as compared to several well-known concept drifting detection methods in data stream, our approach can detect topic drifts effectively, and it enables handling short text streams effectively while maintaining the efficiency as compared to several state-of-the-art short text classification approaches.

Deficits in visual short-term memory binding in children at risk of non-verbal learning disabilities.

Science.gov (United States)

Garcia, Ricardo Basso; Mammarella, Irene C; Pancera, Arianna; Galera, Cesar; Cornoldi, Cesare

2015-01-01

It has been hypothesized that learning disabled children meet short-term memory (STM) problems especially when they must bind different types of information, however the hypothesis has not been systematically tested. This study assessed visual STM for shapes and colors and the binding of shapes and colors, comparing a group of children (aged between 8 and 10 years) at risk of non-verbal learning disabilities (NLD) with a control group of children matched for general verbal abilities, age, gender, and socioeconomic level. Results revealed that groups did not differ in retention of either shapes or colors, but children at risk of NLD were poorer than controls in memory for shape-color bindings. Copyright © 2015 Elsevier Ltd. All rights reserved.

IDF-curves for precipitation In Belgium

International Nuclear Information System (INIS)

Mohymont, Bernard; Demarde, Gaston R.

2004-01-01

The Intensity-Duration-Frequency (IDF) curves for precipitation constitute a relationship between the intensity, the duration and the frequency of rainfall amounts. The intensity of precipitation is expressed in mm/h, the duration or aggregation time is the length of the interval considered while the frequency stands for the probability of occurrence of the event. IDF-curves constitute a classical and useful tool that is primarily used to dimension hydraulic structures in general, as e.g., sewer systems and which are consequently used to assess the risk of inundation. In this presentation, the IDF relation for precipitation is studied for different locations in Belgium. These locations correspond to two long-term, high-quality precipitation networks of the RMIB: (a) the daily precipitation depths of the climatological network (more than 200 stations, 1951-2001 baseline period); (b) the high-frequency 10-minutes precipitation depths of the hydro meteorological network (more than 30 stations, 15 to 33 years baseline period). For the station of Uccle, an uninterrupted time-series of more than one hundred years of 10-minutes rainfall data is available. The proposed technique for assessing the curves is based on maximum annual values of precipitation. A new analytical formula for the IDF-curves was developed such that these curves stay valid for aggregation times ranging from 10 minutes to 30 days (when fitted with appropriate data). Moreover, all parameters of this formula have physical dimensions. Finally, adequate spatial interpolation techniques are used to provide nationwide extreme values precipitation depths for short- to long-term durations With a given return period. These values are estimated on the grid points of the Belgian ALADIN-domain used in the operational weather forecasts at the RMIB.(Author)

Changing the Learning Curve in Novice Laparoscopists: Incorporating Direct Visualization into the Simulation Training Program.

Science.gov (United States)

Dawidek, Mark T; Roach, Victoria A; Ott, Michael C; Wilson, Timothy D

A major challenge in laparoscopic surgery is the lack of depth perception. With the development and continued improvement of 3D video technology, the potential benefit of restoring 3D vision to laparoscopy has received substantial attention from the surgical community. Despite this, procedures conducted under 2D vision remain the standard of care, and trainees must become proficient in 2D laparoscopy. This study aims to determine whether incorporating 3D vision into a 2D laparoscopic simulation curriculum accelerates skill acquisition in novices. Postgraduate year-1 surgical specialty residents (n = 15) at the Schulich School of Medicine and Dentistry, at Western University were randomized into 1 of 2 groups. The control group practiced the Fundamentals of Laparoscopic Surgery peg-transfer task to proficiency exclusively under standard 2D laparoscopy conditions. The experimental group first practiced peg transfer under 3D direct visualization, with direct visualization of the working field. Upon reaching proficiency, this group underwent a perceptual switch, changing to standard 2D laparoscopy conditions, and once again trained to proficiency. Incorporating 3D direct visualization before training under standard 2D conditions significantly (p learning curves for each respective training protocol. An adaptive learning approach, which incorporates 3D direct visualization into a 2D laparoscopic simulation curriculum, accelerates skill acquisition. This is in contrast to previous work, possibly owing to the proficiency-based methodology employed, and has implications for resource savings in surgical training. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Switched-capacitor realization of presynaptic short-term-plasticity and stop-learning synapses in 28 nm CMOS.

Science.gov (United States)

Noack, Marko; Partzsch, Johannes; Mayr, Christian G; Hänzsche, Stefan; Scholze, Stefan; Höppner, Sebastian; Ellguth, Georg; Schüffny, Rene

2015-01-01

Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphic IC. For example, they endow the IC with an ability to adapt and learn from its environment. In order to achieve the millisecond to second time constants required for these synaptic dynamics, analog subthreshold circuits are usually employed. However, due to process variation and leakage problems, it is almost impossible to port these types of circuits to modern sub-100nm technologies. In contrast, we present a neuromorphic system in a 28 nm CMOS process that employs switched capacitor (SC) circuits to implement 128 short term plasticity presynapses as well as 8192 stop-learning synapses. The neuromorphic system consumes an area of 0.36 mm(2) and runs at a power consumption of 1.9 mW. The circuit makes use of a technique for minimizing leakage effects allowing for real-time operation with time constants up to several seconds. Since we rely on SC techniques for all calculations, the system is composed of only generic mixed-signal building blocks. These generic building blocks make the system easy to port between technologies and the large digital circuit part inherent in an SC system benefits fully from technology scaling.

Curved-straight neutron guide system with uniform spatial intensity distribution

International Nuclear Information System (INIS)

Mildner, D.F.R.; Cook, J.C.

2008-01-01

The spatial intensity distribution of neutrons emerging from a curved guide is asymmetric, and straight guide sections are sometimes appended to curved guides to make the intensity distribution more nearly uniform. For idealized uniform illumination and in the perfect reflectivity approximation, the spatial-angular acceptance at the exit of the combination can be made exactly uniform for a range of long wavelengths by using a sufficiently long straight section, together with a curved guide whose outer wall coating has a critical angle slightly greater than those of the other guide walls. We refer to this as a 'phase space tailoring guide' where the coatings on the inner wall and straight section are used to define the required divergence at the end of the guide. Increasing the critical angle of the outer wall of the curved section reduces the characteristic wavelength of the curved guide as well as the wavelength at which ideal uniformity can be obtained. The outer wall coating need only be of sufficiently high critical angle to fill the transmittable phase space area of the straight guide uniformly to adequately short wavelength

Irreversible electroporation ablation (IRE of unresectable soft tissue tumors: learning curve evaluation in the first 150 patients treated.

Directory of Open Access Journals (Sweden)

Prejesh Philips

Full Text Available BACKGROUND: Irreversible electroporation (IRE is a novel technology that uses peri-target discrete probes to deliver high-voltage localized electric current to induce cell death without thermal-induced coagulative necrosis. "Learnability" and consistently effective results by novice practitioners is essential for determining acceptance of novel techniques. This multi-center prospectively-collected database study evaluates the learning curve of IRE. METHODS: Analysis of 150 consecutive patients over 7 institutions from 9/2010-7/2012 was performed with patients treated divided into 3 groups A (1(st 50 patients treated, B (2(nd 50 and C (3(rd 50 patients treated chronologically and analyzed for outcomes. RESULTS: A total of 167 IRE procedures were performed, with a majority being liver(39.5% and pancreatic(35.5% lesions. The three groups were similar with respect to co-morbidities and demographics. Group C had larger lesions (3.9 vs 3 cm,p=0.001, more numerous lesions (3.2 vs 2.2,p=0.07, more vascular invasion(p=0.001, underwent more associated procedures(p=0.001 and had longer operative times(p<0.001. Despite this, they had similar complication and high-grade complication rates(p=0.24. Attributable morbidity rate was 13.3%(total 29.3% and high-grade complications were seen in 4.19%(total 12.6%. Pancreatic lesions(p=0.001 and laparotomy(p=0.001 were associated with complications. CONCLUSION: The review represents that single largest review of IRE soft tissue ablation demonstrating initial patient selection and safety. Over time, complex treatments of larger lesions and lesions with greater vascular involvement were performed without a significant increase in adverse effects or impact on local relapse free survival. This evolution demonstrates the safety profile of IRE and speed of graduation to more complex lesions, which was greater than 5 cases by institution. IRE is a safe and effective alternative to conventional ablation with a demonstrable

Deep ECGNet: An Optimal Deep Learning Framework for Monitoring Mental Stress Using Ultra Short-Term ECG Signals.

Science.gov (United States)

Hwang, Bosun; You, Jiwoo; Vaessen, Thomas; Myin-Germeys, Inez; Park, Cheolsoo; Zhang, Byoung-Tak

2018-02-08

Stress recognition using electrocardiogram (ECG) signals requires the intractable long-term heart rate variability (HRV) parameter extraction process. This study proposes a novel deep learning framework to recognize the stressful states, the Deep ECGNet, using ultra short-term raw ECG signals without any feature engineering methods. The Deep ECGNet was developed through various experiments and analysis of ECG waveforms. We proposed the optimal recurrent and convolutional neural networks architecture, and also the optimal convolution filter length (related to the P, Q, R, S, and T wave durations of ECG) and pooling length (related to the heart beat period) based on the optimization experiments and analysis on the waveform characteristics of ECG signals. The experiments were also conducted with conventional methods using HRV parameters and frequency features as a benchmark test. The data used in this study were obtained from Kwangwoon University in Korea (13 subjects, Case 1) and KU Leuven University in Belgium (9 subjects, Case 2). Experiments were designed according to various experimental protocols to elicit stressful conditions. The proposed framework to recognize stress conditions, the Deep ECGNet, outperformed the conventional approaches with the highest accuracy of 87.39% for Case 1 and 73.96% for Case 2, respectively, that is, 16.22% and 10.98% improvements compared with those of the conventional HRV method. We proposed an optimal deep learning architecture and its parameters for stress recognition, and the theoretical consideration on how to design the deep learning structure based on the periodic patterns of the raw ECG data. Experimental results in this study have proved that the proposed deep learning model, the Deep ECGNet, is an optimal structure to recognize the stress conditions using ultra short-term ECG data.

A systematic methodology for creep master curve construction using the stepped isostress method (SSM): a numerical assessment

Science.gov (United States)

Miranda Guedes, Rui

2018-02-01

Long-term creep of viscoelastic materials is experimentally inferred through accelerating techniques based on the time-temperature superposition principle (TTSP) or on the time-stress superposition principle (TSSP). According to these principles, a given property measured for short times at a higher temperature or higher stress level remains the same as that obtained for longer times at a lower temperature or lower stress level, except that the curves are shifted parallel to the horizontal axis, matching a master curve. These procedures enable the construction of creep master curves with short-term experimental tests. The Stepped Isostress Method (SSM) is an evolution of the classical TSSP method. Higher reduction of the required number of test specimens to obtain the master curve is achieved by the SSM technique, since only one specimen is necessary. The classical approach, using creep tests, demands at least one specimen per each stress level to produce a set of creep curves upon which TSSP is applied to obtain the master curve. This work proposes an analytical method to process the SSM raw data. The method is validated using numerical simulations to reproduce the SSM tests based on two different viscoelastic models. One model represents the viscoelastic behavior of a graphite/epoxy laminate and the other represents an adhesive based on epoxy resin.

Export product diversification and the environmental Kuznets curve: evidence from Turkey.

Science.gov (United States)

Gozgor, Giray; Can, Muhlis

2016-11-01

Countries try to stabilize the demand for energy on one hand and sustain economic growth on the other, but the worsening global warming and climate change problems have put pressure on them. This paper estimates the environmental Kuznets curve over the period 1971-2010 in Turkey both in the short and the long run. For this purpose, the unit root test with structural breaks and the cointegration analysis with multiple endogenous structural breaks are used. The effects of energy consumption and export product diversification on CO 2 emissions are also controlled in the dynamic empirical models. It is observed that the environmental Kuznets curve hypothesis is valid in Turkey in both the short run and the long run. The positive effect on energy consumption on CO 2 emissions is also obtained in the long run. In addition, it is found that a greater product diversification of exports yields higher CO 2 emissions in the long run. Inferences and policy implications are also discussed.

Cooperative learning combined with short periods of lecturing: A good alternative in teaching biochemistry.

Science.gov (United States)

Fernández-Santander, Ana

2008-01-01

The informal activities of cooperative learning and short periods of lecturing has been combined and used in the university teaching of biochemistry as part of the first year course of Optics and Optometry in the academic years 2004-2005 and 2005-2006. The lessons were previously elaborated by the teacher and included all that is necessary to understand the topic (text, figures, graphics, diagrams, pictures, etc.). Additionally, a questionnaire was prepared for every chapter. All lessons contained three parts: objectives, approach and development, and the assessment of the topic. Team work, responsibility, and communication skills were some of the abilities developed with this new methodology. Students worked collaboratively in small groups of two or three following the teacher's instructions with short periods of lecturing that clarified misunderstood concepts. Homework was minimized. On comparing this combined methodology with the traditional one (only lecture), students were found to exhibit a higher satisfaction with the new method. They were more involved in the learning process and had a better attitude toward the subject. The use of this new methodology showed a significant increase in the mean score of the students' academic results. The rate of students who failed the subject was significantly inferior in comparison with those who failed in the previous years when only lecturing was applied. This combined methodology helped the teacher to observe the apprenticeship process of students better and to act as a facilitator in the process of building students' knowledge. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

Questioning short-term memory and its measurement: Why digit span measures long-term associative learning.

Science.gov (United States)

Jones, Gary; Macken, Bill

2015-11-01

Traditional accounts of verbal short-term memory explain differences in performance for different types of verbal material by reference to inherent characteristics of the verbal items making up memory sequences. The role of previous experience with sequences of different types is ostensibly controlled for either by deliberate exclusion or by presenting multiple trials constructed from different random permutations. We cast doubt on this general approach in a detailed analysis of the basis for the robust finding that short-term memory for digit sequences is superior to that for other sequences of verbal material. Specifically, we show across four experiments that this advantage is not due to inherent characteristics of digits as verbal items, nor are individual digits within sequences better remembered than other types of individual verbal items. Rather, the advantage for digit sequences stems from the increased frequency, compared to other verbal material, with which digits appear in random sequences in natural language, and furthermore, relatively frequent digit sequences support better short-term serial recall than less frequent ones. We also provide corpus-based computational support for the argument that performance in a short-term memory setting is a function of basic associative learning processes operating on the linguistic experience of the rememberer. The experimental and computational results raise questions not only about the role played by measurement of digit span in cognition generally, but also about the way in which long-term memory processes impact on short-term memory functioning. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Simulation and analysis of the transmission properties of curved-straight neutron guide systems

International Nuclear Information System (INIS)

Copley, J.R.D.; Mildner, D.F.R.

1992-01-01

This paper reports that the spatial intensity distribution of neutrons emerging from a curved guide is far from uniform, particularly at short wavelengths, and curved guides are sometimes followed by a straight section of guide to make the intensity distribution more uniform. The behavior of neutrons within curved-straight neutron guide systems is examined using both ray-tracing and analytical approaches to the problem. The intensity distribution within the straight guide tends to wash from one side of the guide to the other. The amplitude of this transverse wave decreases with increasing guide length, and the characteristic length of the wave decreases with increasing neutron wavelength

"I know your name, but not your number"--Patients with verbal short-term memory deficits are impaired in learning sequences of digits.

Science.gov (United States)

Bormann, Tobias; Seyboth, Margret; Umarova, Roza; Weiller, Cornelius

2015-06-01

Studies on verbal learning in patients with impaired verbal short-term memory (vSTM) have revealed dissociations among types of verbal information. Patients with impaired vSTM are able to learn lists of known words but fail to acquire new word forms. This suggests that vSTM is involved in new word learning. The present study assessed both new word learning and the learning of digit sequences in two patients with impaired vSTM. In two experiments, participants were required to learn people's names, ages and professions, or their four digit 'phone numbers'. The STM patients were impaired on learning unknown family names and phone numbers, but managed to acquire other verbal information. In contrast, a patient with a severe verbal episodic memory impairment was impaired across information types. These results indicate verbal STM involvement in the learning of digit sequences. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exchange rate and trade balance: J-curve effect

Directory of Open Access Journals (Sweden)

Petrović Pavle

2010-01-01

Full Text Available This paper shows that exchange rate depreciation in Serbia improves trade balance in the long run, while giving rise to a J-curve effect in the short run. These results add to the already existent empirical evidence for a diverse set of other economies. Both Johansen's and autoregressive distributed lag approach are respectively used giving similar long-run estimates showing that real depreciation improves trade balance. Corresponding errorcorrection models as well as impulse response functions indicate that, following currency depreciation, trade balance first deteriorates before it later improves, i.e. exhibiting the J-curve pattern. These results are relevant for policy making both in Serbia and in a number of other emerging Europe countries as they face major current account adjustments after BoP crises of 2009.

Depletion of serotonin selectively impairs short-term memory without affecting long-term memory in odor learning in the terrestrial slug Limax valentianus.

Science.gov (United States)

Shirahata, Takaaki; Tsunoda, Makoto; Santa, Tomofumi; Kirino, Yutaka; Watanabe, Satoshi

2006-01-01

The terrestrial slug Limax is able to acquire short-term and long-term memories during aversive odor-taste associative learning. We investigated the effect of the selective serotonergic neurotoxin 5,7-dihydroxytryptamine (5,7-DHT) on memory. Behavioral studies indicated that 5,7-DHT impaired short-term memory but not long-term memory. HPLC (high-performance liquid chromatography) analysis revealed that 5,7-DHT significantly reduced serotonin content in the central nervous system. The present study suggests that acquisition, retention, and/or retrieval of short-term memory involves serotonin, and neither acquisition nor retrieval of long-term memory requires serotonin at a level as high as that required for short-term memory.

Innovative Training of In-Service Teachers for Active Learning: A Short Teacher Development Course Based on Physics Education Research

Science.gov (United States)

Zavala, Genaro; Alarcon, Hugo; Benegas, Julio

2007-01-01

In this contribution we describe a short development course for in-service physics teachers. The course structure and materials are based on the results of educational research, and its main objective is to provide in-service teachers with a first contact with the active learning strategy "Tutorials in Introductory Physics," developed by…

Treatment of thoraco-lumbar curves in adolescent females affected by idiopathic scoliosis with a progressive action short brace (PASB: assessment of results according to the SRS committee on bracing and nonoperative management standardization criteria

Directory of Open Access Journals (Sweden)

Perisano Carlo

2009-09-01

Full Text Available Abstract Background The effectiveness of conservative treatment of scoliosis is controversial. Some studies suggest that brace is effective in stopping curve progression, whilst others did not report such an effect. The purpose of the present study was to effectiveness of Progressive Action Short Brace (PASB in the correction of thoraco-lumbar curves, in agreement with the Scoliosis Research Society (SRS Committee on Bracing and Nonoperative Management Standardisation Criteria. Methods Fifty adolescent females (mean age 11.8 ± 0.5 years with thoraco-lumbar curve and a pre-treatment Risser score ranging from 0 to 2 have been enrolled. The minimum duration of follow-up was 24 months (mean: 55.4 ± 44.5 months. Antero-posterior radiographs were used to estimate the curve magnitude (CM and the torsion of the apical vertebra (TA at 5 time points: beginning of treatment (t1, one year after the beginning of treatment (t2, intermediate time between t1 and t4 (t3, end of weaning (t4, 2-year minimum follow-up from t4 (t5. Three situations were distinguished: curve correction, curve stabilisation and curve progression. The Kruskal Wallis and Spearman Rank Correlation tests have been used as statistical tests. Results CM mean value was 29,30 ± 5,16 SD at t1 and 14,67 ± 7,65 SD at t5. TA was 12.70 ± 6,14 SD at t1 and 8,95 ± 5,82 at t5. The variation between measures of Cobb and Perdriolle degrees at t1,2,3,4,5 and between CM t5-t1 and TA t5-t1 were significantly different. Curve correction was accomplished in 94% of patients, whereas a curve stabilisation was obtained in 6% of patients. Conclusion The PASB, due to its peculiar biomechanical action on vertebral modelling, is highly effective in correcting thoraco-lumbar curves.

Logistic characteristics of phonon transport in silicon thin film: the S-curve

Energy Technology Data Exchange (ETDEWEB)

Yilbas, B.S., E-mail: bsyilbas@kfupm.edu.sa; Mansoor, S. Bin

2013-10-01

The logistic characteristics of the averaged heat flux are investigated across the thin film incorporating the S-curve. Temporal behaviour of the heat flux vector is computed using the Boltzmann transport equation. The dispersion relations are introduced to account for the frequency dependent phonon transport across the film. The influence of film width on the characteristics of the averaged heat flux is also examined. It is found that temporal behaviour of the averaged heat flux follows the S-curve. The S-curve characteristics change for different film widths. The time to reach 95% steady value of the averaged heat flux is short for the film with small widths, which is attributed to the ballistic behaviour of phonons in the film.

Logistic characteristics of phonon transport in silicon thin film: the S-curve

International Nuclear Information System (INIS)

Yilbas, B.S.; Mansoor, S. Bin

2013-01-01

The logistic characteristics of the averaged heat flux are investigated across the thin film incorporating the S-curve. Temporal behaviour of the heat flux vector is computed using the Boltzmann transport equation. The dispersion relations are introduced to account for the frequency dependent phonon transport across the film. The influence of film width on the characteristics of the averaged heat flux is also examined. It is found that temporal behaviour of the averaged heat flux follows the S-curve. The S-curve characteristics change for different film widths. The time to reach 95% steady value of the averaged heat flux is short for the film with small widths, which is attributed to the ballistic behaviour of phonons in the film

Association of learning styles with research self-efficacy: study of short-term research training program for medical students.

Science.gov (United States)

Dumbauld, Jill; Black, Michelle; Depp, Colin A; Daly, Rebecca; Curran, Maureen A; Winegarden, Babbi; Jeste, Dilip V

2014-12-01

With a growing need for developing future physician scientists, identifying characteristics of medical students who are likely to benefit from research training programs is important. This study assessed if specific learning styles of medical students, participating in federally funded short-term research training programs, were associated with research self-efficacy, a potential predictor of research career success. Seventy-five first-year medical students from 28 medical schools, selected to participate in two competitive NIH-supported summer programs for research training in aging, completed rating scales to evaluate learning styles at baseline, and research self-efficacy before and after training. We examined associations of individual learning styles (visual-verbal, sequential-global, sensing-intuitive, and active-reflective) with students' gender, ranking of medical school, and research self-efficacy. Research self-efficacy improved significantly following the training programs. Students with a verbal learning style reported significantly greater research self-efficacy at baseline, while visual, sequential, and intuitive learners demonstrated significantly greater increases in research self-efficacy from baseline to posttraining. No significant relationships were found between learning styles and students' gender or ranking of their medical school. Assessments of learning styles may provide useful information to guide future training endeavors aimed at developing the next generation of physician-scientists. © 2014 Wiley Periodicals, Inc.

Can CCM law properly represent all extinction curves?

International Nuclear Information System (INIS)

Geminale, Anna; Popowski, Piotr

2005-01-01

We present the analysis of a large sample of lines of sight with extinction curves covering wavelength range from near-infrared (NIR) to ultraviolet (UV). We derive total to selective extinction ratios based on the Cardelli, Clayton and Mathis (1989, CCM) law, which is typically used to fit the extinction data both for diffuse and dense interstellar medium. We conclude that the CCM law is able to fit most of the extinction curves in our sample. We divide the remaining lines of sight with peculiar extinction into two groups according to two main behaviors: a) the optical/IR or/and UV wavelength region cannot be reproduced by the CCM formula; b) the optical/NIR and UV extinction data are best fit by the CCM law with different values of R v . We present examples of such curves. The study of both types of peculiar cases can help us to learn about the physical processes that affect dust in the interstellar medium, e.g., formation of mantles on the surface of grains, evaporation, growing or shattering

Switched-Capacitor Realization of Presynaptic Short-Term Plasticity and Stop-Learning Synapses in 28 nm CMOS

Directory of Open Access Journals (Sweden)

Marko eNoack

2015-02-01

Full Text Available Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphic IC. For example, they endow the IC with an ability to adapt and learn from its environment. In order to achieve the millisecond to second time constants required for these synaptic dynamics, analog subthreshold circuits are usually employed. However, due to process variation and leakage problems, it is almost impossible to port these types of circuits to modern sub-100nm technologies. In contrast, we present a neuromorphic system in a 28 nm CMOS process that employs switched capacitor (SC circuits to implement 128 short-term plasticity presynapses as well as 8192 stop-learning synapses. The neuromorphic system consumes an area of 0.36 mm² and runs at a power consumption of 1.9 mW. The circuit makes use of a technique for minimizing leakage effects allowing for real-time operation with time constants up to several seconds. Since we rely on SC techniques for all calculations, the system is composed of only generic mixed-signal building blocks. These generic building blocks make the system easy to port between technologies and the large digital circuit part inherent in an SC system benefits fully from technology scaling.

Technical Note: Deep learning based MRAC using rapid ultra-short echo time imaging.

Science.gov (United States)

Jang, Hyungseok; Liu, Fang; Zhao, Gengyan; Bradshaw, Tyler; McMillan, Alan B

2018-05-15

In this study, we explore the feasibility of a novel framework for MR-based attenuation correction for PET/MR imaging based on deep learning via convolutional neural networks, which enables fully automated and robust estimation of a pseudo CT image based on ultrashort echo time (UTE), fat, and water images obtained by a rapid MR acquisition. MR images for MRAC are acquired using dual echo ramped hybrid encoding (dRHE), where both UTE and out-of-phase echo images are obtained within a short single acquisition (35 sec). Tissue labeling of air, soft tissue, and bone in the UTE image is accomplished via a deep learning network that was pre-trained with T1-weighted MR images. UTE images are used as input to the network, which was trained using labels derived from co-registered CT images. The tissue labels estimated by deep learning are refined by a conditional random field based correction. The soft tissue labels are further separated into fat and water components using the two-point Dixon method. The estimated bone, air, fat, and water images are then assigned appropriate Hounsfield units, resulting in a pseudo CT image for PET attenuation correction. To evaluate the proposed MRAC method, PET/MR imaging of the head was performed on 8 human subjects, where Dice similarity coefficients of the estimated tissue labels and relative PET errors were evaluated through comparison to a registered CT image. Dice coefficients for air (within the head), soft tissue, and bone labels were 0.76±0.03, 0.96±0.006, and 0.88±0.01. In PET quantification, the proposed MRAC method produced relative PET errors less than 1% within most brain regions. The proposed MRAC method utilizing deep learning with transfer learning and an efficient dRHE acquisition enables reliable PET quantification with accurate and rapid pseudo CT generation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Machine Learning Techniques for Modelling Short Term Land-Use Change

Directory of Open Access Journals (Sweden)

Mileva Samardžić-Petrović

2017-11-01

Full Text Available The representation of land use change (LUC is often achieved by using data-driven methods that include machine learning (ML techniques. The main objectives of this research study are to implement three ML techniques, Decision Trees (DT, Neural Networks (NN, and Support Vector Machines (SVM for LUC modeling, in order to compare these three ML techniques and to find the appropriate data representation. The ML techniques are applied on the case study of LUC in three municipalities of the City of Belgrade, the Republic of Serbia, using historical geospatial data sets and considering nine land use classes. The ML models were built and assessed using two different time intervals. The information gain ranking technique and the recursive attribute elimination procedure were implemented to find the most informative attributes that were related to LUC in the study area. The results indicate that all three ML techniques can be used effectively for short-term forecasting of LUC, but the SVM achieved the highest agreement of predicted changes.

"Alarm-corrected" ergonomic armrest use could improve learning curves of novices on robotic simulator.

Science.gov (United States)

Yang, Kun; Perez, Manuela; Hossu, Gabriela; Hubert, Nicolas; Perrenot, Cyril; Hubert, Jacques

2017-01-01

In robotic surgery, the professional ergonomic habit of using an armrest reduces operator fatigue and increases the precision of motion. We designed and validated a pressure surveillance system (PSS) based on force sensors to investigate armrest use. The objective was to evaluate whether adding an alarm to the PSS system could shorten ergonomic training and improve performance. Twenty robot and simulator-naïve participants were recruited and randomized in two groups (A and B). The PSS was installed on a robotic simulator, the dV-Trainer, to detect contact with the armrest. The Group A members completed three tasks on the dV-Trainer without the alarm, making 15 attempts at each task. The Group B members practiced the first two tasks with the alarm and then completed the final tasks without the alarm. The simulator provided an overall score reflecting the trainees' performance. We used the new concept of an "armrest load" score to describe the ergonomic habit of using the armrest. Group B had a significantly higher performance score (p ergonomic errors and accelerated professional ergonomic habit acquisition. The combination of the PSS and alarm is effective in significantly shortening the learning curve in the robotic training process.

Use long short-term memory to enhance Internet of Things for combined sewer overflow monitoring

Science.gov (United States)

Zhang, Duo; Lindholm, Geir; Ratnaweera, Harsha

2018-01-01

Combined sewer overflow causes severe water pollution, urban flooding and reduced treatment plant efficiency. Understanding the behavior of CSO structures is vital for urban flooding prevention and overflow control. Neural networks have been extensively applied in water resource related fields. In this study, we collect data from an Internet of Things monitoring CSO structure and build different neural network models for simulating and predicting the water level of the CSO structure. Through a comparison of four different neural networks, namely multilayer perceptron (MLP), wavelet neural network (WNN), long short-term memory (LSTM) and gated recurrent unit (GRU), the LSTM and GRU present superior capabilities for multi-step-ahead time series prediction. Furthermore, GRU achieves prediction performances similar to LSTM with a quicker learning curve.

Discrete integrable systems and hodograph transformations arising from motions of discrete plane curves

International Nuclear Information System (INIS)

Feng Baofeng; Maruno, Ken-ichi; Inoguchi, Jun-ichi; Kajiwara, Kenji; Ohta, Yasuhiro

2011-01-01

We consider integrable discretizations of some soliton equations associated with the motions of plane curves: the Wadati-Konno-Ichikawa elastic beam equation, the complex Dym equation and the short pulse equation. They are related to the modified KdV or the sine-Gordon equations by the hodograph transformations. Based on the observation that the hodograph transformations are regarded as the Euler-Lagrange transformations of the curve motions, we construct the discrete analogues of the hodograph transformations, which yield integrable discretizations of those soliton equations. (paper)

Arithmetic fundamental groups and moduli of curves

International Nuclear Information System (INIS)

Makoto Matsumoto

2000-01-01

This is a short note on the algebraic (or sometimes called arithmetic) fundamental groups of an algebraic variety, which connects classical fundamental groups with Galois groups of fields. A large part of this note describes the algebraic fundamental groups in a concrete manner. This note gives only a sketch of the fundamental groups of the algebraic stack of moduli of curves. Some application to a purely topological statement, i.e., an obstruction to the subjectivity of Johnson homomorphisms in the mapping class groups, which comes from Galois group of Q, is explained. (author)

Short Term International Study for Teachers as a Form of Experiential Learning: A Case Study of American Educators in Turkey

Science.gov (United States)

Berk, Zulfikar

2017-01-01

This dissertation is a case study of the experiences and perspectives of nine US teachers who participated in a short-term international study tour to Turkey, from the theoretical perspectives of global education and experiential learning. It examines how that experience shaped the teachers' understandings of global dynamics, cultural differences…

On-line learning through simple perceptron learning with a margin.

Science.gov (United States)

Hara, Kazuyuki; Okada, Masato

2004-03-01

We analyze a learning method that uses a margin kappa a la Gardner for simple perceptron learning. This method corresponds to the perceptron learning when kappa = 0 and to the Hebbian learning when kappa = infinity. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and found that it was the same as for perceptron learning. We also investigated an adaptive margin control method.

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

OpenAIRE

Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

2013-01-01

Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

Placement of central venous port catheters and peripherally inserted central catheters in the routine clinical setting of a radiology department: analysis of costs and intervention duration learning curve.

Science.gov (United States)

Rotzinger, Roman; Gebauer, Bernhard; Schnapauff, Dirk; Streitparth, Florian; Wieners, Gero; Grieser, Christian; Freyhardt, Patrick; Hamm, Bernd; Maurer, Martin H

2017-12-01

Background Placement of central venous port catheters (CVPS) and peripherally inserted central catheters (PICC) is an integral component of state-of-the-art patient care. In the era of increasing cost awareness, it is desirable to have more information to comprehensively assess both procedures. Purpose To perform a retrospective analysis of interventional radiologic implantation of CVPS and PICC lines in a large patient population including a cost analysis of both methods as well as an investigation the learning curve in terms of the interventions' durations. Material and Methods All CVPS and PICC line related interventions performed in an interventional radiology department during a three-year period from January 2011 to December 2013 were examined. Documented patient data included sex, venous access site, and indication for CVPS or PICC placement. A cost analysis including intervention times was performed based on the prorated costs of equipment use, staff costs, and expenditures for disposables. The decrease in intervention duration in the course of time conformed to the learning curve. Results In total, 2987 interventions were performed by 16 radiologists: 1777 CVPS and 791 PICC lines. An average implantation took 22.5 ± 0.6 min (CVPS) and 10.1 ± 0.9 min (PICC lines). For CVPS, this average time was achieved by seven radiologists newly learning the procedures after performing 20 CVPS implantations. Total costs per implantation were €242 (CVPS) and €201 (PICC lines). Conclusion Interventional radiologic implantations of CVPS and PICC lines are well-established procedures, easy to learn by residents, and can be implanted at low costs.

Short educational programs in optical design and engineering

Science.gov (United States)

Voznesenskaya, Anna; Romanova, Galina; Bakholdin, Alexey; Tolstoba, Nadezhda; Ezhova, Kseniia

2016-09-01

Globalization and diversification of education in optical engineering causes a number of new phenomena in students' learning paths. Many students have an interest to get some courses in other universities, to study in international environment, to broaden not only professional skills but social links and see the sights as well etc. Participation in short educational programs (e.g. summer / winter schools, camps etc.) allows students from different universities to learn specific issues in their or in some neighbor field and also earn some ECTS for the transcript of records. ITMO University provides a variety of short educational programs in optical design and engineering oriented for different background level, such are: Introduction into optical engineering, Introduction into applied and computer optics, Optical system design, Image modeling and processing, Design of optical devices and components. Depending on students' educational background these programs are revised and adopted each time. Usually the short educational programs last 4 weeks and provide 4 ECTS. The short programs utilize a set of out-of date educational technologies like problem-based learning, case-study and distance-learning and evaluation. Practically, these technologies provide flexibility of the educational process and intensive growth of the learning outcomes. Students are satisfied with these programs very much. In their feedbacks they point a high level of practical significance, experienced teaching staff, scholarship program, excellent educational environment, as well as interesting social program and organizational support.

Early light curves for Type Ia supernova explosion models

Science.gov (United States)

Noebauer, U. M.; Kromer, M.; Taubenberger, S.; Baklanov, P.; Blinnikov, S.; Sorokina, E.; Hillebrandt, W.

2017-12-01

Upcoming high-cadence transient survey programmes will produce a wealth of observational data for Type Ia supernovae. These data sets will contain numerous events detected very early in their evolution, shortly after explosion. Here, we present synthetic light curves, calculated with the radiation hydrodynamical approach STELLA for a number of different explosion models, specifically focusing on these first few days after explosion. We show that overall the early light curve evolution is similar for most of the investigated models. Characteristic imprints are induced by radioactive material located close to the surface. However, these are very similar to the signatures expected from ejecta-CSM or ejecta-companion interaction. Apart from the pure deflagration explosion models, none of our synthetic light curves exhibit the commonly assumed power-law rise. We demonstrate that this can lead to substantial errors in the determination of the time of explosion. In summary, we illustrate with our calculations that even with very early data an identification of specific explosion scenarios is challenging, if only photometric observations are available.

Analysis of the learning curve for pre-cut corneal specimens in preparation for lamellar transplantation: a prospective, single-centre, consecutive case series prepared at the Lions New South Wales Eye Bank.

Science.gov (United States)

Martin, Aifric Isabel; Devasahayam, Rajnesh; Hodge, Christopher; Cooper, Simon; Sutton, Gerard L

2017-09-01

This study is the first paper to establish a learning curve by a single technician. Preparation of pre-cut corneal endothelial grafts commenced at Lions New South Wales Eye Bank in December 2014. The primary objective of this study was to review the safety and reliability of the preparation method during the first year of production. This is a hospital-based, prospective case series. There were 234 consecutive donor corneal lenticules. Donor lenticules were prepared by a single operator using a linear cutting microkeratome. Immediately prior to cutting, central corneal thickness values were recorded. Measurements of the corneal bed were taken immediately following lenticule preparation. Outcomes were separated by blade sizes, and intended thickness was compared to actual thickness for each setting. Early specimens were compared to later ones to assess for a learning curve within the technique. The main parameter measured is the mean difference from intended lamellar cut thickness. The mean final cut thickness was 122.36 ± 20.35 μm, and the mean difference from intended cut was 30.17 ± 37.45 μm. No significant difference was found between results achieved with early specimens versus those achieved with later specimens (P = 0.425). Thin, reproducible endothelial grafts can routinely be produced by trained technicians at their respective eye banks without significant concerns for an extended learning curve. This service can reduce perioperative surgical complexity, required surgical paraphernalia and theatre times. The consistent preparation of single-pass, ultrathin pre-cut corneas may have additional advantages for surgeons seeking to introduce lamellar techniques. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

Spaghetti Sine Curves: Virtual Environments for Reasoning and Sense Making

Science.gov (United States)

Özgün-Koca, S. Asli; Edwards, Michael Todd; Meagher, Michael

2013-01-01

In a recent collaboration with an area high school teacher, the authors were asked to develop an introductory sinusoidal curves lesson for a group of second-year algebra students. Because the topic was abstract and unfamiliar to these tenth graders, they looked for hands-on lessons to support their learning. One lesson that they found, which they…

Binding of visual and spatial short-term memory in Williams syndrome and moderate learning disability.

Science.gov (United States)

Jarrold, Christopher; Phillips, Caroline; Baddeley, Alan D

2007-04-01

A main aim of this study was to test the claim that individuals with Williams syndrome have selectively impaired memory for spatial as opposed to visual information. The performance of 16 individuals with Williams syndrome (six males, 10 females; mean age 18y 7mo [SD 7y 6mo], range 9y 1mo-30y 7mo) on tests of short-term memory for item and location information was compared with that shown by individuals with moderate learning difficulties (12 males, four females; mean age 10y 3mo [SD 1y], range 8y 6mo-11y 7mo) and typically developing children (six males, 10 females; mean age 6y 8mo [SD 7mo], range 5y 10mo-7y 9mo) of an equivalent level of visuospatial ability. A second aim was to determine whether individuals had impaired ability to 'bind' visual spatial information when required to recall 'item in location' information. In contrast to previous findings, there was no evidence that individuals with Williams syndrome were more impaired in the spatial than the visual memory condition. However, individuals with both Williams syndrome and moderate learning difficulties showed impaired memory for item in location information, suggesting that problems of binding may be generally associated with learning disability.

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

Science.gov (United States)

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

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

Use of the cumulative sum method (CUSUM) to assess the learning curves of ultrasound-guided continuous femoral nerve block.

Science.gov (United States)

Kollmann-Camaiora, A; Brogly, N; Alsina, E; Gilsanz, F

2017-10-01

Although ultrasound is a basic competence for anaesthesia residents (AR) there is few data available on the learning process. This prospective observational study aims to assess the learning process of ultrasound-guided continuous femoral nerve block and to determine the number of procedures that a resident would need to perform in order to reach proficiency using the cumulative sum (CUSUM) method. We recruited 19 AR without previous experience. Learning curves were constructed using the CUSUM method for ultrasound-guided continuous femoral nerve block considering 2 success criteria: a decrease of pain score>2 in a [0-10] scale after 15minutes, and time required to perform it. We analyse data from 17 AR for a total of 237 ultrasound-guided continuous femoral nerve blocks. 8/17 AR became proficient for pain relief, however all the AR who did more than 12 blocks (8/8) became proficient. As for time of performance 5/17 of AR achieved the objective of 12minutes, however all the AR who did more than 20 blocks (4/4) achieved it. The number of procedures needed to achieve proficiency seems to be 12, however it takes more procedures to reduce performance time. The CUSUM methodology could be useful in training programs to allow early interventions in case of repeated failures, and develop competence-based curriculum. Copyright © 2017 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

The effects of short-term and long-term learning on the responses of lateral intraparietal neurons to visually presented objects.

Science.gov (United States)

Sigurdardottir, Heida M; Sheinberg, David L

2015-07-01

The lateral intraparietal area (LIP) is thought to play an important role in the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand to what extent short-term and long-term experience with visual orienting determines the responses of LIP to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred spatial location of a neuron. The training could last for less than a single day or for several months. We found that neural responses to objects are affected by such experience, but that the length of the learning period determines how this neural plasticity manifests. Short-term learning affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the responses to newly learned objects resemble those of familiar objects that share their meaning or arbitrary association. Long-term learning affects the earliest bottom-up responses to visual objects. These responses tend to be greater for objects that have been associated with looking toward, rather than away from, LIP neurons' preferred spatial locations. Responses to objects can nonetheless be distinct, although they have been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore indicate that a complete experience-driven override of LIP object responses may be difficult or impossible. We relate these results to behavioral work on visual attention.

The development and evaluation of mini-GEMs - short, focused, online e-learning videos in geriatric medicine.

Science.gov (United States)

Garside, Mark J; Fisher, James M; Blundell, Adrian G; Gordon, Adam L

2018-01-01

Mini Geriatric E-Learning Modules (Mini-GEMs) are short, focused, e-learning videos on geriatric medicine topics, hosted on YouTube, which are targeted at junior doctors working with older people. This study aimed to explore how these resources are accessed and used. The authors analyzed the viewing data from 22 videos published over the first 18 months of the Mini-GEM project. We conducted a focus group of U.K. junior doctors considering their experiences with Mini-GEMS. The Mini-GEMs were viewed 10,291 times over 18 months, equating to 38,435 minutes of total viewing time. The average viewing time for each video was 3.85 minutes. Learners valued the brevity and focused nature of the Mini-GEMs and reported that they watched them in a variety of settings to supplement clinical experiences and consolidate learning. Watching the videos led to an increase in self-reported confidence in managing older patients. Mini-GEMs can effectively disseminate clinical teaching material to a wide audience. The videos are valued by junior doctors due to their accessibility and ease of use.

Quantized Dirac field in curved Riemann--Cartan background. I. Symmetry properties, Green's function

International Nuclear Information System (INIS)

Nieh, H.T.; Yan, M.L.

1982-01-01

In the present series of papers, we study the properties of quantized Dirac field in curved Riemann--Cartan space, with particular attention on the role played by torsion. In this paper, we give, in the spirit of the original work of Weyl, a systematic presentation of Dirac's theory in curved Riemann--Cartan space. We discuss symmetry properties of the system, and derive conservation laws as direct consequences of these symmetries. Also discussed is conformal gauge symmetry, with torsion effectively playing the role of a conformal gauge field. To obtain short-distance behavior, we calculate the spinor Green's function, in curved Riemann--Cartan background, using the Schwinger--DeWitt method of proper-time expansion. The calculation corresponds to a generalization of DeWitt's calculation for a Riemannian background

Learning representations for the early detection of sepsis with deep neural networks.

Science.gov (United States)

Kam, Hye Jin; Kim, Ha Young

2017-10-01

Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens. This study aimed to develop detection models for the early stage of sepsis using deep learning methodologies, and to compare the feasibility and performance of the new deep learning methodology with those of the regression method with conventional temporal feature extraction. Study group selection adhered to the InSight model. The results of the deep learning-based models and the InSight model were compared. With deep feedforward networks, the area under the ROC curve (AUC) of the models were 0.887 and 0.915 for the InSight and the new feature sets, respectively. For the model with the combined feature set, the AUC was the same as that of the basic feature set (0.915). For the long short-term memory model, only the basic feature set was applied and the AUC improved to 0.929 compared with the existing 0.887 of the InSight model. The contributions of this paper can be summarized in three ways: (i) improved performance without feature extraction using domain knowledge, (ii) verification of feature extraction capability of deep neural networks through comparison with reference features, and (iii) improved performance with feedforward neural networks using long short-term memory, a neural network architecture that can learn sequential patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Handbook of elliptic and hyperelliptic curve cryptography

CERN Document Server

Cohen, Henri; Avanzi, Roberto; Doche, Christophe; Lange, Tanja; Nguyen, Kim; Vercauteren, Frederik

2005-01-01

… very comprehensive coverage of this vast subject area … a useful and essential treatise for anyone involved in elliptic curve algorithms … this book offers the opportunity to grasp the ECC technology with a diversified and comprehensive perspective. … This book will remain on my shelf for a long time and will land on my desk on many occasions, if only because the coverage of the issues common to factoring and discrete log cryptosystems is excellent.-IACR Book Reviews, June 2011… the book is designed for people who are working in the area and want to learn more about a specific issue. The chapters are written to be relatively independent so that readers can focus on the part of interest for them. Such readers will be grateful for the excellent index and extensive bibliography. … the handbook covers a wide range of topics and will be a valuable reference for researchers in curve-based cryptography. -Steven D. Galbraith, Mathematical Reviews, Issue 2007f.

Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models.

Science.gov (United States)

Ledonne, Norman C; Rissolo, Kevin; Bulgarelli, James; Tini, Leonard

2011-02-07

Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI) curves via the SALI curve integral (SCI) as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

Ensemble Learning Method for Outlier Detection and its Application to Astronomical Light Curves

Science.gov (United States)

Nun, Isadora; Protopapas, Pavlos; Sim, Brandon; Chen, Wesley

2016-09-01

Outlier detection is necessary for automated data analysis, with specific applications spanning almost every domain from financial markets to epidemiology to fraud detection. We introduce a novel mixture of the experts outlier detection model, which uses a dynamically trained, weighted network of five distinct outlier detection methods. After dimensionality reduction, individual outlier detection methods score each data point for “outlierness” in this new feature space. Our model then uses dynamically trained parameters to weigh the scores of each method, allowing for a finalized outlier score. We find that the mixture of experts model performs, on average, better than any single expert model in identifying both artificially and manually picked outliers. This mixture model is applied to a data set of astronomical light curves, after dimensionality reduction via time series feature extraction. Our model was tested using three fields from the MACHO catalog and generated a list of anomalous candidates. We confirm that the outliers detected using this method belong to rare classes, like Novae, He-burning, and red giant stars; other outlier light curves identified have no available information associated with them. To elucidate their nature, we created a website containing the light-curve data and information about these objects. Users can attempt to classify the light curves, give conjectures about their identities, and sign up for follow up messages about the progress made on identifying these objects. This user submitted data can be used further train of our mixture of experts model. Our code is publicly available to all who are interested.

In-Time On-Place Learning

Science.gov (United States)

Bauters, Merja; Purma, Jukka; Leinonen, Teemu

2014-01-01

The aim of this short paper is to look at how mobile video recording devices could support learning related to physical practices or places and situations at work. This paper discusses particular kind of workplace learning, namely learning using short video clips that are related to physical environment and tasks preformed in situ. The paper…

Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models

Directory of Open Access Journals (Sweden)

LeDonne Norman C

2011-02-01

Full Text Available Abstract Background Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI curves via the SALI curve integral (SCI as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists. Results The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK in vitro efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from SimulationsPlus and AstraZeneca. Conclusion The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.

Short and long term supply curves for crude oil and the consequences for the market; Kurz- und langfristige Angebotskurven fuer Rohoel und die Konsequenzen fuer den Markt

Energy Technology Data Exchange (ETDEWEB)

Schlothmann, Daniel

2016-03-08

In this work, supply curves for 22 major oil producing countries were identified and then aggregated into global supply curves. According to the identified supply curves, almost all oil-producing oil projects currently under development in the study countries are also profitable at the current oil price of $ 35 to $ 40 per barrel, taking short-term marginal costs into account. However, if the price of oil remains at this level in the coming years, a supply bottleneck on the global oil market will occur until 2024, as the development of cost-intensive, unconventional deposits and of deposits in deep and very deep waters is necessary to meet future demand. In order to avoid such a supply bottleneck by 2024, an oil price of at least US $ 80 per barrel is required, according to the long-term market equilibrium determined. [German] In dieser Arbeit wurden Angebotskurven fuer 22 bedeutende Oelfoerderlaender ermittelt und anschliessend zu globalen Angebotskurven aggregiert. Gemaess den ermittelten Angebotskurven sind nahezu alle gegenwaertig in der Foerderphase befindlichen Oelprojekte in den Untersuchungslaendern auch beim aktuellen Oelpreis von 35 bis 40 US-$ je Barrel unter Beruecksichtigung der kurzfristigen Grenzkosten rentabel. Sollte der Oelpreis jedoch in den kommenden Jahren auf diesem Niveau verharren, wird es bis zum Jahr 2024 zu einem Angebotsengpass auf dem globalen Oelmarkt kommen, da zur Deckung der zukuenftigen Nachfrage die Erschliessung kostenintensiver, unkonventioneller Lagerstaetten und von Lagerstaetten in tiefen und sehr tiefen Gewaessern notwendig ist. Damit es bis zum Jahr 2024 nicht zu einem solchen Angebotsengpass kommt, ist gemaess des ermittelten langfristigen Marktgleichgewichts ein Oelpreis von mindestens 80 (2014er) US-$ je Barrel notwendig.

An introduction to machine learning with Scikit-Learn

CERN Multimedia

CERN. Geneva

2015-01-01

This tutorial gives an introduction to the scientific ecosystem for data analysis and machine learning in Python. After a short introduction of machine learning concepts, we will demonstrate on High Energy Physics data how a basic supervised learning analysis can be carried out using the Scikit-Learn library. Topics covered include data loading facilities and data representation, supervised learning algorithms, pipelines, model selection and evaluation, and model introspection.

The influence of prior multiport experience on the learning curve for single-port thoracoscopic lobectomy: a multicentre comparative study†.

Science.gov (United States)

Martin-Ucar, Antonio E; Aragon, Javier; Bolufer Nadal, Sergio; Galvez Munoz, Carlos; Luo, Qigang; Perez Mendez, Itzel; Sihoe, Alan D L; Socci, Laura

2017-06-01

Competency in video-assisted thoracoscopic (VATS) lobectomy is estimated to be reached after the surgeon completes 50 cases. We wanted to explore the impact of competency in performing multiport VATS lobectomies on completing the needed number of single-port VATS. In a retrospective multicentre study, 6 individual surgeons (3 with previous competency in multiport VATS lobectomy and 3 without) submitted their first 50 cases of single-port VATS lobectomies. Extended and sublobar resections were excluded. Pre-, peri- and postoperative data were compared between the groups of surgeons. Chi-square and Wilcoxon's rank tests were used. The less experienced surgeons had previously attended dedicated training courses and visited with experts. A total of 300 cases were included [150 in Group A (surgeons with previous experience performing multiport VATS) and 150 in Group B (surgeons without extensive experience performing multiport VATS)]. Surgeons in Group B performed significantly more elective open lobectomies during their learning curve period than surgeons of Group A (58 vs 1). Patients in Group B were older and had more risk factors. There were 3 in-hospital deaths (respiratory failure, sepsis and fatal stroke). There were no differences between the groups in operative time, intensive care unit admissions, hospital stay, total complications, tumour size or number of N2 stations explored. Only the duration of intercostal drainage (2 vs 3 days, 0.012), incidence of respiratory tract infections (1% vs 7%, P  = 0.002) and conversion rates (4% vs 12%, P  = 0.018) were better in Group A. Patients characteristics played a role in the development of respiratory infections and longer drainage times but not in the need for conversion. Overall, postoperative outcomes during the learning curve period for single-port VATS lobectomies are not noticeably affected by previous multiport VATS experience. Less experienced surgeons were more selective in order to achieve

Factors contributing to the nuclear caloric curve aspect

International Nuclear Information System (INIS)

Raduta, Al.H.; Raduta, Ad.R.

1999-01-01

leads to the absence of any transition-like region, the 'suppression' of the binding degree of freedom results in the manifestation of a short and prompt back-banding just at the beginning of the caloric curve. (authors)

Action observation versus motor imagery in learning a complex motor task: a short review of literature and a kinematics study.

Science.gov (United States)

Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G

2013-04-12

Both motor imagery and action observation have been shown to play a role in learning or re-learning complex motor tasks. According to a well accepted view they share a common neurophysiological basis in the mirror neuron system. Neurons within this system discharge when individuals perform a specific action and when they look at another individual performing the same or a motorically related action. In the present paper, after a short review of literature on the role of action observation and motor imagery in motor learning, we report the results of a kinematics study where we directly compared motor imagery and action observation in learning a novel complex motor task. This involved movement of the right hand and foot in the same angular direction (in-phase movement), while at the same time moving the left hand and foot in an opposite angular direction (anti-phase movement), all at a frequency of 1Hz. Motor learning was assessed through kinematics recording of wrists and ankles. The results showed that action observation is better than motor imagery as a strategy for learning a novel complex motor task, at least in the fast early phase of motor learning. We forward that these results may have important implications in educational activities, sport training and neurorehabilitation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

International Nuclear Information System (INIS)

Sanders, N. E.; Soderberg, A. M.; Betancourt, M.

2015-01-01

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

Energy Technology Data Exchange (ETDEWEB)

Sanders, N. E.; Soderberg, A. M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Betancourt, M., E-mail: nsanders@cfa.harvard.edu [Department of Statistics, University of Warwick, Coventry CV4 7AL (United Kingdom)

2015-02-10

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST.

Analyzing price and efficiency dynamics of large appliances with the experience curve approach

International Nuclear Information System (INIS)

Weiss, Martin; Patel, Martin K.; Junginger, Martin; Blok, Kornelis

2010-01-01

Large appliances are major power consumers in households of industrialized countries. Although their energy efficiency has been increasing substantially in past decades, still additional energy efficiency potentials exist. Energy policy that aims at realizing these potentials faces, however, growing concerns about possible adverse effects on commodity prices. Here, we address these concerns by applying the experience curve approach to analyze long-term price and energy efficiency trends of three wet appliances (washing machines, laundry dryers, and dishwashers) and two cold appliances (refrigerators and freezers). We identify a robust long-term decline in both specific price and specific energy consumption of large appliances. Specific prices of wet appliances decline at learning rates (LR) of 29±8% and thereby much faster than those of cold appliances (LR of 9±4%). Our results demonstrate that technological learning leads to substantial price decline, thus indicating that the introduction of novel and initially expensive energy efficiency technologies does not necessarily imply adverse price effects in the long term. By extending the conventional experience curve approach, we find a steady decline in the specific energy consumption of wet appliances (LR of 20-35%) and cold appliances (LR of 13-17%). Our analysis suggests that energy policy might be able to bend down energy experience curves. (author)

Perspectives for short timescale variability studies with Gaia

Science.gov (United States)

Roelens, M.; Eyer, L.; Mowlavi, N.; Lecoeur-Taïbi, I.; Rimoldini, L.; Blanco-Cuaresma, S.; Palaversa, L.; Süveges, M.; Charnas, J.; Wevers, T.

2017-12-01

We assess the potential of Gaia for detecting and characterizing short timescale variables, i.e. at timescale from a few seconds to a dozen hours, through extensive light-curve simulations for various short timescale variable types, including both periodic and non-periodic variability. We evidence that the variogram analysis applied to Gaia photometry should enable to detect such fast variability phenomena, down to amplitudes of a few millimagnitudes, with limited contamination from longer timescale variables or constant sources. This approach also gives valuable information on the typical timescale(s) of the considered variation, which could complement results of classical period search methods, and help prepare ground-based follow-up of the Gaia short timescale candidates.

Solar cost reduction through technical improvements: the concepts of learning and experience

Energy Technology Data Exchange (ETDEWEB)

Krawiec, F.; Flaim, T.

1979-10-01

The concepts of learning and experience are reviewed and their usefulness for predicting the future costs of solar technologies are evaluated. The literature review indicated that the cost estimates for solar energy technologies are typically made assuming a fixed production process, characterized by standard capacity factors, overhead, and labor costs. The learning curve is suggested as a generalization of the costs of potential solar energy systems. The concept of experience is too ambiguous to be useful for cost estimation. There is no logical reason to believe that costs will decline purely as a function of cumulative production, and experience curves do not allow the analyst to identify logical sources of cost reduction directly. The procedures for using learning and aggregated cost curves to estimate the costs of solar technologies are outlined. It is recommended that production histories of analogous products and processes are analyzed and the learning and cost curves for these surrogates are estimated. These curves, if judged applicable, can be used to predict the cost reductions in manufacturing solar energy technologies.

The relative kicking frequency of infants born full-term and preterm during learning and short-term and long-term memory periods of the mobile paradigm.

Science.gov (United States)

Heathcock, Jill C; Bhat, Anjana N; Lobo, Michele A; Galloway, James C

2005-01-01

Infants born preterm differ in their spontaneous kicking, as well as their learning and memory abilities in the mobile paradigm, compared with infants born full-term. In the mobile paradigm, a supine infant's ankle is tethered to a mobile so that leg kicks cause a proportional amount of mobile movement. The purpose of this study was to investigate the relative kicking frequency of the tethered (right) and nontethered (left) legs in these 2 groups of infants. Ten infants born full-term and 10 infants born preterm (infants participated in the study. The relative kicking frequencies of the tethered and nontethered legs were analyzed during learning and short-term and long-term memory periods of the mobile paradigm. Infants born full-term showed an increase in the relative kicking frequency of the tethered leg during the learning period and the short-term memory period but not for the long-term memory period. Infants born preterm did not show a change in kicking pattern for learning or memory periods, and consistently kicked both legs in relatively equal amounts. Infants born full-term adapted their baseline kicking frequencies in a task-specific manner to move the mobile and then retained this adaptation for the short-term memory period. In contrast, infants born preterm showed no adaptation, suggesting a lack of purposeful leg control. This lack of control may reflect a general decrease in the ability of infants born preterm to use their limb movements to interact with their environment. As such, the mobile paradigm may be clinically useful in the early assessment and intervention of infants born preterm and at risk for future impairment.

A new approach to the analysis of Mira light curves

International Nuclear Information System (INIS)

Mennessier, M.O.; Barthes, D.; Mattei, J.A.

1990-01-01

Two different but complementary methods for predicting Mira luminosities are presented. One method is derived from a Fourier analysis, it requires performing deconvolution, and its results are not certain due to the inherent instability of deconvolution problems. The other method is a learning method utilizing artificial intelligence techniques where a light curve is presented as an ordered sequence of pseudocycles, and rules are learned by linking the characteristics of several consecutive pseudocycles to one characteristic of the future cycle. It is observed that agreement between these methods is obtainable when it is possible to eliminate similar false frequencies from the preliminary power spectrum and to improve the degree of confidence in the rules

Curve Boxplot: Generalization of Boxplot for Ensembles of Curves.

Science.gov (United States)

Mirzargar, Mahsa; Whitaker, Ross T; Kirby, Robert M

2014-12-01

In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.

Automatic segmentation of left ventricle in cardiac cine MRI images based on deep learning

Science.gov (United States)

Zhou, Tian; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

2017-02-01

In developing treatment of cardiovascular diseases, short axis cine MRI has been used as a standard technique for understanding the global structural and functional characteristics of the heart, e.g. ventricle dimensions, stroke volume and ejection fraction. To conduct an accurate assessment, heart structures need to be segmented from the cine MRI images with high precision, which could be a laborious task when performed manually. Herein a fully automatic framework is proposed for the segmentation of the left ventricle from the slices of short axis cine MRI scans of porcine subjects using a deep learning approach. For training the deep learning models, which generally requires a large set of data, a public database of human cine MRI scans is used. Experiments on the 3150 cine slices of 7 porcine subjects have shown that when comparing the automatic and manual segmentations the mean slice-wise Dice coefficient is about 0.930, the point-to-curve error is 1.07 mm, and the mean slice-wise Hausdorff distance is around 3.70 mm, which demonstrates the accuracy and robustness of the proposed inter-species translational approach.

JUMPING THE CURVE

Directory of Open Access Journals (Sweden)

René Pellissier

2012-01-01

Full Text Available This paper explores the notion ofjump ing the curve,following from Handy 's S-curve onto a new curve with new rules policies and procedures. . It claims that the curve does not generally lie in wait but has to be invented by leadership. The focus of this paper is the identification (mathematically and inferentially ofthat point in time, known as the cusp in catastrophe theory, when it is time to change - pro-actively, pre-actively or reactively. These three scenarios are addressed separately and discussed in terms ofthe relevance ofeach.

Dual Smarandache Curves of a Timelike Curve lying on Unit dual Lorentzian Sphere

OpenAIRE

Kahraman, Tanju; Hüseyin Ugurlu, Hasan

2016-01-01

In this paper, we give Darboux approximation for dual Smarandache curves of time like curve on unit dual Lorentzian sphere. Firstly, we define the four types of dual Smarandache curves of a timelike curve lying on dual Lorentzian sphere.

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

Science.gov (United States)

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Retroperitoneal laparoscopic nephrectomy: the effect of the learning curve, and concentrating expertise, on operating times.

Science.gov (United States)

Skinner, Adrian; Maoate, Kiki; Beasley, Spencer

2010-05-01

Laparoscopic nephrectomy is an accepted alternative to open nephrectomy. We analyzed our first 80 procedures of laparoscopic nephrectomy to evaluate the effect of experience and configuration of service on operative times. A retrospective review of 80 consecutive children who underwent retroperitoneal laparoscopic nephrectomy or heminephrectomy during an 11-year period from 1997 at Christchurch Hospital (Christchurch, New Zealand) was conducted. Operative times, in relation to the experience of the surgeon for this procedure, were analyzed. Four surgeons, assisted by an annually rotating trainee registrar, performed the procedure in 26 girls and 54 boys (range, 8 months to 15 years). Operating times ranged from 38 to 225 minutes (mean, 104). The average operative time fell from 105 to 90 minutes. One surgeon performed 40% of the procedures and assisted with a further 55%. The operative times for all surgeons showed a tendency to reduce, but this was not marked. Most procedures were performed by two surgeons working together, although one surgeon was involved in the majority of cases. The lead surgeon is often assisted by a fellow consultant colleague. Operative times were influenced by experience, but not markedly so. The shorter operative times and minimal "learning curve," compared with other reported series, may, in part, be due to the involvement of two surgeons experienced in laparoscopy for the majority of cases.

Learning and memory

Directory of Open Access Journals (Sweden)

P. A. J. Ryke

1989-03-01

Full Text Available Under various circumstances and in different species the outward expression of learning varies considerably, and this has led to the classification of different categories of learning. Just as there is no generally agreed on definition of learning, there is no one system of classification. Types of learning commonly recognized are: Habituation, sensitization, classical conditioning, operant conditioning, trial and error, taste aversion, latent learning, cultural learning, imprinting, insight learning, learning-set learning and instinct. The term memory must include at least two separate processes. It must involve, on the one hand, that of learning something and on the other, at some later date, recalling that thing. What lies between the learning and (he remembering must be some permanent record — a memory trace — within the brain. Memory exists in at least two forms: memory for very recent events (short-term which is relatively labile and easily disruptable; and long-term memory, which is much more stable. Not everything that gets into short-term memory becomes fixed in the long-term store; a filtering mechanism selects things that might be important and discards the rest.

Accuracy of progress ratios determined from experience curves: the case of photovoltaic technology development

NARCIS (Netherlands)

van Sark, W.G.J.H.M.|info:eu-repo/dai/nl/074628526; Alsema, E.A.|info:eu-repo/dai/nl/073416258; Junginger, H.M.|info:eu-repo/dai/nl/202130703; de Moor, H.H.C.; Schaeffer, G.J.

2008-01-01

Learning curves are extensively used in policy and scenario studies. Progress ratios (PRs) are derived from historical data and are used for forecasting cost development of many technologies, including photovoltaics (PV). Forecasts are highly sensitive to uncertainties in the PR. A PR usually is

Real wage rigidity and the new Phillips curve: the Brazilian case

Directory of Open Access Journals (Sweden)

Antonio Alberto Mazali

2010-09-01

Full Text Available The new Keynesian Phillips curve has been criticized for not explaining the short-run inflation-output gap trade-off. Blanchard and Galí (2007 introduced real wage rigidity and derived a trade-off between stabilizing inflation and the gap between actual and efficient output. This paper estimates the new Phillips curve for the Brazilian economy, computes short-run trade-off, analyzes real wage rigidity, and tests theoretical restrictions imposed by the model. The GMM estimations fit the data very well and all theoretical restrictions are satisfied. There is strong real wage rigidity and a high output-gap cost to stabilize inflation in the short run.A curva de Phillips novo-keynesiana tem sido criticada por não explicar o trade-off de curto prazo entre inflação-hiato do produto. Blanchard e Galí (2007 introduziram a rigidez do salário real e derivaram um trade-off entre estabilizar inflação ou estabilizar hiato entre produto real e eficiente. Neste artigo estima-se essa nova curva para a economia brasileira, calcula-se o trade-off, analisa-se a rigidez do salário real e testa-se restrições teóricas do modelo. Estimações GMM adequam-se bem aos dados e todas as restrições teóricas são satisfeitas. Há forte rigidez do salário real e alto custo de hiato do produto para estabilizar inflação no curto prazo.

ECM using Edwards curves

DEFF Research Database (Denmark)

Bernstein, Daniel J.; Birkner, Peter; Lange, Tanja

2013-01-01

-arithmetic level are as follows: (1) use Edwards curves instead of Montgomery curves; (2) use extended Edwards coordinates; (3) use signed-sliding-window addition-subtraction chains; (4) batch primes to increase the window size; (5) choose curves with small parameters and base points; (6) choose curves with large...

Fitness analysis method for magnesium in drinking water with atomic absorption using quadratic curve calibration

Directory of Open Access Journals (Sweden)

Esteban Pérez-López

2014-11-01

Full Text Available Because of the importance of quantitative chemical analysis in research, quality control, sales of services and other areas of interest , and the limiting of some instrumental analysis methods for quantification with linear calibration curve, sometimes because the short linear dynamic ranges of the analyte, and sometimes by limiting the technique itself, is that there is a need to investigate a little more about the convenience of using quadratic curves for analytical quantification, which seeks demonstrate that it is a valid calculation model for chemical analysis instruments. To this was taken as an analysis method based on the technique and atomic absorption spectroscopy in particular a determination of magnesium in a sample of drinking water Tacares sector Northern Grecia, employing a nonlinear calibration curve and a curve specific quadratic behavior, which was compared with the test results obtained for the same analysis with a linear calibration curve. The results show that the methodology is valid for the determination referred to, with all confidence, since the concentrations are very similar, and as used hypothesis testing can be considered equal.

Efficacy of tension-free vaginal tape compared with transobturator tape in the treatment of stress urinary incontinence in women: analysis of learning curve, perioperative changes of voiding function

Science.gov (United States)

2011-01-01

Background In this study, by comparing TVT surgery and TOT surgery for stress urinary incontinence in women, the characteristics and learning curves of both operative methods were studied. Methods A total of 83 women with stress urinary incontinence treated with tension-free vaginal tape (TVT) (n = 38) or transobturator tape (TOT) (n = 45) at Saiseikai Central Hospital between April 2004 and September 2009 were included. We compare the outcomes and learning curves between TVT surgery and TOT surgery. In statistical analysis, Student's t test, Fisher's exact test, and Mann-Whitney's U test were used. Results The surgical durations were 37.4 ± 15.7 minutes with TVT surgery and 31.0 ± 8.3 minutes with TOT surgery. A longer period of time was required for TVT surgery (p = 0.025). The residual urine at post-operative day 1 was higher in TVT surgery (25.9 ± 44.2 ml) than in TOT surgery (10.6 ± 19.2 ml) (p = 0.0452). The surgical duration of TVT surgery was shortened after the operator had performed 15 operations (p = 0.019). Conclusions In comparison of TVT surgery and TOT surgery, the surgical duration of TVT surgery was longer and the residual urine of TVT surgery was higher at post-operative day 1. Surgical experience could shorten the duration of TVT surgery. PMID:21726448

Efficacy of tension-free vaginal tape compared with transobturator tape in the treatment of stress urinary incontinence in women: analysis of learning curve, perioperative changes of voiding function

Directory of Open Access Journals (Sweden)

Kanai Kunimitsu

2011-07-01

Full Text Available Abstract Background In this study, by comparing TVT surgery and TOT surgery for stress urinary incontinence in women, the characteristics and learning curves of both operative methods were studied. Methods A total of 83 women with stress urinary incontinence treated with tension-free vaginal tape (TVT (n = 38 or transobturator tape (TOT (n = 45 at Saiseikai Central Hospital between April 2004 and September 2009 were included. We compare the outcomes and learning curves between TVT surgery and TOT surgery. In statistical analysis, Student's t test, Fisher's exact test, and Mann-Whitney's U test were used. Results The surgical durations were 37.4 ± 15.7 minutes with TVT surgery and 31.0 ± 8.3 minutes with TOT surgery. A longer period of time was required for TVT surgery (p = 0.025. The residual urine at post-operative day 1 was higher in TVT surgery (25.9 ± 44.2 ml than in TOT surgery (10.6 ± 19.2 ml (p = 0.0452. The surgical duration of TVT surgery was shortened after the operator had performed 15 operations (p = 0.019. Conclusions In comparison of TVT surgery and TOT surgery, the surgical duration of TVT surgery was longer and the residual urine of TVT surgery was higher at post-operative day 1. Surgical experience could shorten the duration of TVT surgery.

Transmission assets investment timing using net present value curves

International Nuclear Information System (INIS)

Garcia, Reinaldo C.; Contreras, Javier; Correia, Pedro F.; Munoz, Jose I.

2010-01-01

Improvement and expansion of the transmission grid is still an unresolved issue in the new competitive environment. In current electricity markets, transmission lines have become assets that need financial instruments for investors who wish to ensure steady long-term returns and to withstand short-term market volatility. The timing and the combination of new transmission investments is key to analyze their long-term effects. This paper presents the concept of net present value (NPV) curve to estimate the best investment time for the investor, where the curve is constructed by calculating the NPVs resulting from the investment in successive years. A specific contract model based on financial transmission rights (FTR) is used for the NPV evaluation of transmission assets, and the stochastic properties of all variables related to the investment market structure are considered. The model is applied to the IEEE 24-bus Reliability Test System (RTS) showing the approach capabilities as a decision-aid tool for transmission investors.

The evaluation process of short training sessions in organizations

NARCIS (Netherlands)

Overschie, M.G.F.; Lukosch, H.K.; De Vries, P.

This paper presents a critical reflection of the evaluation of learning processes in organizations. Based on learning and evaluation theories and concepts we discuss qualitative and quantitative evaluation processes, and its relationship to short training sessions to foster sustainable development.

An Alternative to Wave Mechanics on Curved Spaces

CERN Document Server

Tomaschitz, R

1992-01-01

Geodesic motion in infinite spaces of constant negative curvature provides for the first time an example where a basically quantum mechanical quantity, a ground-state energy, is derived from Newtonian mechanics in a rigorous, non-semiclassical way. The ground state energy emerges as the Hausdorff dimension of a quasi-self-similar curve at infinity of three-dimensional hyperbolic space H in which our manifolds are embedded and where their universal covers are realized. This curve is just the locus of the limit set L(G) of the Kleinian group G of covering transformations, which determines the bounded trajectories in the manifold; all of them lie in the quotient C(L)/G, C(L) being the hyperbolic convex hull of L(G). The three-dimensional hyperbolic manifolds we construct can be visualized as thickened surfaces, topological products I x S, I a finite open interval, the fibers S compact Riemann surfaces. We give a short derivation of the Patterson formula connecting the ground-state energy with the Hausdorff dimen...

The training and learning process of transseptal puncture using a modified technique.

Science.gov (United States)

Yao, Yan; Ding, Ligang; Chen, Wensheng; Guo, Jun; Bao, Jingru; Shi, Rui; Huang, Wen; Zhang, Shu; Wong, Tom

2013-12-01

As the transseptal (TS) puncture has become an integral part of many types of cardiac interventional procedures, its technique that was initial reported for measurement of left atrial pressure in 1950s, continue to evolve. Our laboratory adopted a modified technique which uses only coronary sinus catheter as the landmark to accomplishing TS punctures under fluoroscopy. The aim of this study is prospectively to evaluate the training and learning process for TS puncture guided by this modified technique. Guided by the training protocol, TS puncture was performed in 120 consecutive patients by three trainees without previous personal experience in TS catheterization and one experienced trainer as a controller. We analysed the following parameters: one puncture success rate, total procedure time, fluoroscopic time, and radiation dose. The learning curve was analysed using curve-fitting methodology. The first attempt at TS crossing was successful in 74 (82%), a second attempt was successful in 11 (12%), and 5 patients failed to puncture the interatrial septal finally. The average starting process time was 4.1 ± 0.8 min, and the estimated mean learning plateau was 1.2 ± 0.2 min. The estimated mean learning rate for process time was 25 ± 3 cases. Important aspects of learning curve can be estimated by fitting inverse curves for TS puncture. The study demonstrated that this technique was a simple, safe, economic, and effective approach for learning of TS puncture. Base on the statistical analysis, approximately 29 TS punctures will be needed for trainee to pass the steepest area of learning curve.

Analysis on learning curves of end-use appliances for the establishment of price-sensitivity load model in competitive electricity market

Energy Technology Data Exchange (ETDEWEB)

Hwang, Sung Wook; Kim, Jung Hoon [Hongik University (Korea); Song, Kyung Bin [Keimyung University (Korea); Choi, Joon Young [Jeonju University (Korea)

2001-07-01

The change of the electricity charge from cost base to price base due to the introduction to the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding to-price loads, the price-sensitive load model is needed. And the development of state-of- the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns. (author). 6 refs., 4 figs., 4 tabs.

Learning of couplings for random asymmetric kinetic Ising models revisited: random correlation matrices and learning curves

International Nuclear Information System (INIS)

Bachschmid-Romano, Ludovica; Opper, Manfred

2015-01-01

We study analytically the performance of a recently proposed algorithm for learning the couplings of a random asymmetric kinetic Ising model from finite length trajectories of the spin dynamics. Our analysis shows the importance of the nontrivial equal time correlations between spins induced by the dynamics for the speed of learning. These correlations become more important as the spin’s stochasticity is decreased. We also analyse the deviation of the estimation error (paper)

National proficiency-gain curves for minimally invasive gastrointestinal cancer surgery.

Science.gov (United States)

Mackenzie, H; Markar, S R; Askari, A; Ni, M; Faiz, O; Hanna, G B

2016-01-01

Minimal access surgery for gastrointestinal cancer has short-term benefits but is associated with a proficiency-gain curve. The aim of this study was to define national proficiency-gain curves for minimal access colorectal and oesophagogastric surgery, and to determine the impact on clinical outcomes. All adult patients undergoing minimal access oesophageal, colonic and rectal surgery between 2002 and 2012 were identified from the Hospital Episode Statistics database. Proficiency-gain curves were created using risk-adjusted cumulative sum analysis. Change points were identified, and bootstrapping was performed with 1000 iterations to identify a confidence level. The primary outcome was 30-day mortality; secondary outcomes were 90-day mortality, reintervention, conversion and length of hospital stay. Some 1696, 15 008 and 16 701 minimal access oesophageal, rectal and colonic cancer resections were performed during the study period. The change point in the proficiency-gain curve for 30-day mortality for oesophageal, rectal and colonic surgery was 19 (confidence level 98·4 per cent), 20 (99·2 per cent) and three (99·5 per cent) procedures; the mortality rate fell from 4·0 to 2·0 per cent (relative risk reduction (RRR) 0·50, P = 0·033), from 2·1 to 1·2 per cent (RRR 0·43, P curve for reintervention in oesophageal, rectal and colonic resection was 19 (98·1 per cent), 32 (99·5 per cent) and 26 (99·2 per cent) procedures respectively. There were also significant proficiency-gain curves for 90-day mortality, conversion and length of stay. The introduction of minimal access gastrointestinal cancer surgery has been associated with a proficiency-gain curve for mortality and major morbidity at a national level. Unnecessary patient harm should be avoided by appropriate training and monitoring of new surgical techniques. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.

SUPERNOVA LIGHT CURVES POWERED BY FALLBACK ACCRETION

Energy Technology Data Exchange (ETDEWEB)

Dexter, Jason; Kasen, Daniel, E-mail: jdexter@berkeley.edu [Departments of Physics and Astronomy, University of California, Berkeley, CA 94720 (United States)

2013-07-20

Some fraction of the material ejected in a core collapse supernova explosion may remain bound to the compact remnant, and eventually turn around and fall back. We show that the late time ({approx}>days) power potentially associated with the accretion of this 'fallback' material could significantly affect the optical light curve, in some cases producing super-luminous or otherwise peculiar supernovae. We use spherically symmetric hydrodynamical models to estimate the accretion rate at late times for a range of progenitor masses and radii and explosion energies. The accretion rate onto the proto-neutron star or black hole decreases as M-dot {proportional_to}t{sup -5/3} at late times, but its normalization can be significantly enhanced at low explosion energies, in very massive stars, or if a strong reverse shock wave forms at the helium/hydrogen interface in the progenitor. If the resulting super-Eddington accretion drives an outflow which thermalizes in the outgoing ejecta, the supernova debris will be re-energized at a time when photons can diffuse out efficiently. The resulting light curves are different and more diverse than previous fallback supernova models which ignored the input of accretion power and produced short-lived, dim transients. The possible outcomes when fallback accretion power is significant include super-luminous ({approx}> 10{sup 44} erg s{sup -1}) Type II events of both short and long durations, as well as luminous Type I events from compact stars that may have experienced significant mass loss. Accretion power may unbind the remaining infalling material, causing a sudden decrease in the brightness of some long duration Type II events. This scenario may be relevant for explaining some of the recently discovered classes of peculiar and rare supernovae.

Relationship between spontaneous expiratory flow-volume curve pattern and air-flow obstruction in elderly COPD patients.

Science.gov (United States)

Nozoe, Masafumi; Mase, Kyoshi; Murakami, Shigefumi; Okada, Makoto; Ogino, Tomoyuki; Matsushita, Kazuhiro; Takashima, Sachie; Yamamoto, Noriyasu; Fukuda, Yoshihiro; Domen, Kazuhisa

2013-10-01

Assessment of the degree of air-flow obstruction is important for determining the treatment strategy in COPD patients. However, in some elderly COPD patients, measuring FVC is impossible because of cognitive dysfunction or severe dyspnea. In such patients a simple test of airways obstruction requiring only a short run of tidal breathing would be useful. We studied whether the spontaneous expiratory flow-volume (SEFV) curve pattern reflects the degree of air-flow obstruction in elderly COPD patients. In 34 elderly subjects (mean ± SD age 80 ± 7 y) with stable COPD (percent-of-predicted FEV(1) 39.0 ± 18.5%), and 12 age-matched healthy subjects, we measured FVC and recorded flow-volume curves during quiet breathing. We studied the SEFV curve patterns (concavity/convexity), spirometry results, breathing patterns, and demographics. The SEFV curve concavity/convexity prediction accuracy was examined by calculating the receiver operating characteristic curves, cutoff values, area under the curve, sensitivity, and specificity. Fourteen subjects with COPD had a concave SEFV curve. All the healthy subjects had convex SEFV curves. The COPD subjects who had concave SEFV curves often had very severe airway obstruction. The percent-of-predicted FEV(1)% (32.4%) was the most powerful SEFV curve concavity predictor (area under the curve 0.92, 95% CI 0.83-1.00), and had the highest sensitivity (0.93) and specificity (0.88). Concavity of the SEFV curve obtained during tidal breathing may be a useful test for determining the presence of very severe obstruction in elderly patients unable to perform a satisfactory FVC maneuver.

Evaluation of the learning curve for thulium laser enucleation of the prostate with the aid of a simulator tool but without tutoring: comparison of two surgeons with different levels of endoscopic experience.

Science.gov (United States)

Saredi, Giovanni; Pirola, Giacomo Maria; Pacchetti, Andrea; Lovisolo, Jon Alexander; Borroni, Giacomo; Sembenini, Federico; Marconi, Alberto Mario

2015-06-09

The aim of this study was to determine the learning curve for thulium laser enucleation of the prostate (ThuLEP) for two surgeons with different levels of urological endoscopic experience. From June 2012 to August 2013, ThuLEP was performed on 100 patients in our institution. We present the results of a prospective evaluation during which we analyzed data related to the learning curves for two surgeons of different levels of experience. The prostatic adenoma volumes ranged from 30 to 130 mL (average 61.2 mL). Surgeons A and B performed 48 and 52 operations, respectively. Six months after surgery, all patients were evaluated with the International Prostate Symptom Score questionnaire, uroflowmetry, and prostate-specific antigen test. Introduced in 2010, ThuLEP consists of blunt enucleation of the prostatic apex and lobes using the sheath of the resectoscope. This maneuver allows clearer visualization of the enucleation plane and precise identification of the prostatic capsule. These conditions permit total resection of the prostatic adenoma and coagulation of small penetrating vessels, thereby reducing the laser emission time. Most of the complications in this series were encountered during morcellation, which in some cases was performed under poor vision because of venous bleeding due to surgical perforation of the capsule during enucleation. Based on this analysis, we concluded that it is feasible for laser-naive urologists with endoscopic experience to learn to perform ThuLEP without tutoring. Those statements still require further validation in larger multicentric study cohort by several surgeon. The main novelty during the learning process was the use of a simulator that faithfully reproduced all of the surgical steps in prostates of various shapes and volumes.

From Experiment to Theory: What Can We Learn from Growth Curves?

Science.gov (United States)

Kareva, Irina; Karev, Georgy

2018-01-01

Finding an appropriate functional form to describe population growth based on key properties of a described system allows making justified predictions about future population development. This information can be of vital importance in all areas of research, ranging from cell growth to global demography. Here, we use this connection between theory and observation to pose the following question: what can we infer about intrinsic properties of a population (i.e., degree of heterogeneity, or dependence on external resources) based on which growth function best fits its growth dynamics? We investigate several nonstandard classes of multi-phase growth curves that capture different stages of population growth; these models include hyperbolic-exponential, exponential-linear, exponential-linear-saturation growth patterns. The constructed models account explicitly for the process of natural selection within inhomogeneous populations. Based on the underlying hypotheses for each of the models, we identify whether the population that it best fits by a particular curve is more likely to be homogeneous or heterogeneous, grow in a density-dependent or frequency-dependent manner, and whether it depends on external resources during any or all stages of its development. We apply these predictions to cancer cell growth and demographic data obtained from the literature. Our theory, if confirmed, can provide an additional biomarker and a predictive tool to complement experimental research.

Automated Analysis of Short Responses in an Interactive Synthetic Tutoring System for Introductory Physics

Science.gov (United States)

Nakamura, Christopher M.; Murphy, Sytil K.; Christel, Michael G.; Stevens, Scott M.; Zollman, Dean A.

2016-01-01

Computer-automated assessment of students' text responses to short-answer questions represents an important enabling technology for online learning environments. We have investigated the use of machine learning to train computer models capable of automatically classifying short-answer responses and assessed the results. Our investigations are part…

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program.

Science.gov (United States)

Afouxenidis, D; Polymeris, G S; Tsirliganis, N C; Kitis, G

2012-05-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the GLOw Curve ANalysis INtercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters.

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program

International Nuclear Information System (INIS)

Afouxenidis, D.; Polymeris, G. S.; Tsirliganis, N. C.; Kitis, G.

2012-01-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the Glow Curve Analysis Intercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters. (authors)

Comrades marathon for short-term experiential learning as perceived by physiotherapy students: A short report

Directory of Open Access Journals (Sweden)

U. Useh

2011-01-01

Full Text Available This  study  described  the  learning  experiences  of physiotherapy students during the 2009 comrades marathon. A quali-tative  approach  using  focus  group  discussions  was  employed  for  this study.The population for this study was all the 43 B.Sc. physiotherapy final year students of the university of limpopo, who provided physio-therapy services at the 2009 comrades Marathon. forty (93% students participated in this study. All the participants were black with majo-rity 23 (58% of them from the limpopo province. Twenty one (52% of the participants were females with ages ranging between 21 and 30 years. The field trip provided both sport specific and general learning experiences. participants had the opportunity to handle sports injuries and athletes, work and learn as a team and were quite independent. This trip also provided participants the opportunity experiencing workplace communication and interaction, the reality of the real workplace experience of heavy workload, experience of prejudice, time management and an unsafe environment.Despite organizational challenges of the trip, the event provided an opportunity for the participants to practice sport physiotherapy. Participants appreciated the opportunity to experience the dynamics of team and collaborative learning. To ensure effective use of this event for experiential learning, it is recommended that proper guidance and support be provided by the faculty.

A new method for measuring coronary artery diameters with CT spatial profile curves

International Nuclear Information System (INIS)

Shimamoto, Ryoichi; Suzuki, Jun-ichi; Yamazaki, Tadashi; Tsuji, Taeko; Ohmoto, Yuki; Morita, Toshihiro; Yamashita, Hiroshi; Honye, Junko; Nagai, Ryozo; Akahane, Masaaki; Ohtomo, Kuni

2007-01-01

Purpose: Coronary artery vascular edge recognition on computed tomography (CT) angiograms is influenced by window parameters. A noninvasive method for vascular edge recognition independent of window setting with use of multi-detector row CT was contrived and its feasibility and accuracy were estimated by intravascular ultrasound (IVUS). Methods: Multi-detector row CT was performed to obtain 29 CT spatial profile curves by setting a line cursor across short-axis coronary angiograms processed by multi-planar reconstruction. IVUS was also performed to determine the reference coronary diameter. IVUS diameter was fitted horizontally between two points on the upward and downward slopes of the profile curves and Hounsfield number was measured at the fitted level to test seven candidate indexes for definition of intravascular coronary diameter. The best index from the curves should show the best agreement with IVUS diameter. Results: Of the seven candidates the agreement was the best (agreement: 16 ± 11%) when the two ratios of Hounsfield number at the level of IVUS diameter over that at the peak on the profile curves were used with water and with fat as the background tissue. These edge definitions were achieved by cutting the horizontal distance by the curves at the level defined by the ratio of 0.41 for water background and 0.57 for fat background. Conclusions: Vascular edge recognition of the coronary artery with CT spatial profile curves was feasible and the contrived method could define the coronary diameter with reasonable agreement

Fast Weight Long Short-Term Memory

OpenAIRE

Keller, T. Anderson; Sridhar, Sharath Nittur; Wang, Xin

2018-01-01

Associative memory using fast weights is a short-term memory mechanism that substantially improves the memory capacity and time scale of recurrent neural networks (RNNs). As recent studies introduced fast weights only to regular RNNs, it is unknown whether fast weight memory is beneficial to gated RNNs. In this work, we report a significant synergy between long short-term memory (LSTM) networks and fast weight associative memories. We show that this combination, in learning associative retrie...

Talking Physics: Two Case Studies on Short Answers and Self-explanation in Learning Physics

Science.gov (United States)

Badeau, Ryan C.

This thesis explores two case studies into the use of short answers and self-explanation to improve student learning in physics. The first set of experiments focuses on the role of short answer questions in the context of computer-based instruction. Through a series of six experiments, we compare and evaluate the performance of computer-assessed short answer questions versus multiple choice for training conceptual topics in physics, controlling for feedback between the two formats. In addition to finding overall similar improvements on subsequent student performance and retention, we identify unique differences in how students interact with the treatments in terms of time spent on feedback and performance on follow-up short answer assessment. In addition, we identify interactions between the level of interactivity of the training, question format, and student attitudinal ratings of each respective training. The second case study focuses on the use of worked examples in the context of multi-concept physics problems - which we call "synthesis problems." For this part of the thesis, four experiments were designed to evaluate the effectiveness of two instructional methods employing worked examples on student performance with synthesis problems; these instructional techniques, analogical comparison and self-explanation, have previously been studied primarily in the context of single-concept problems. As such, the work presented here represents a novel focus on extending these two techniques to this class of more complicated physics problem. Across the four experiments, both self-explanation and certain kinds of analogical comparison of worked examples significantly improved student performance on a target synthesis problem, with distinct improvements in recognition of the relevant concepts. More specifically, analogical comparison significantly improved student performance when the comparisons were invoked between worked synthesis examples. In contrast, similar

Short dental implants: A scoping review of the literature for patients with head and neck cancer.

Science.gov (United States)

Edher, Faraj; Nguyen, Caroline T

2017-09-16

Dental implants can be essential in the rehabilitation of various cancer defects, but their ideal placement can be complicated by the limited dimensions of the available host bone. Surgical interventions developed to increase the amount of bone are not all predictable or successful and can sometimes be contraindicated. Short dental implants have been suggested as an alternative option in sites where longer implants are not possible. Whether they provide a successful treatment option is unclear. The purpose of this study was to review the literature on short dental implants and assess whether they are a viable definitive treatment option for rehabilitating cancer patients with deficient bone. A scoping review of the literature was performed, including a search of established periodontal textbooks for articles on short dental implants combined with a search of PubMed, MEDLINE, EMBASE, Web of Science, and Cochrane Database of Systematic Reviews. A search for all literature published before June 2016 was based on the following keywords: ['dental implants' OR 'dental implantation, endosseous' OR 'dental prosthesis, implant supported'] AND [short]. The minimum acceptable implant length has been considered to be 6 mm. The survival rates of short implants varied between 74% and 96% at 5 years, depending on factors such as the quality of the patient's bone, primary stability of the implant, clinician's learning curve, and implant surface. Short implants can achieve results similar to those of longer implants in augmented bone and offer a treatment alternative that could reduce the need for invasive surgery and associated morbidity and be safer and more economical. Short dental implants (6 mm to 8 mm) can be used successfully to support single or multiple fixed reconstructions or overdentures in atrophic maxillae and mandibles. The use of short dental implants lessens the need for advanced and complicated surgical bone augmentation procedures, which reduces complications

Develop a Professional Learning Plan

Science.gov (United States)

Journal of Staff Development, 2013

2013-01-01

A professional learning plan establishes short-and long-term plans for professional learning and implementation of the learning. Such plans guide individuals, schools, districts, and states in coordinating learning experiences designed to achieve outcomes for educators and students. Professional learning plans focus on the program of educator…

Learning curves of theta/beta neurofeedback in children with ADHD

NARCIS (Netherlands)

Janssen, T.W.P.; Bink, M.; Weeda, W.D.; Gelade, K.N.; Van, Mourik R.; Maras, A.; Oosterlaan, J.

2017-01-01

Neurofeedback is widely applied as non-pharmacological intervention aimed at reducing symptoms of ADHD, even though efficacy has not been unequivocally established. Neuronal changes during the neurofeedback intervention that resemble learning can provide crucial evidence for the feasibility and

Approximation by planar elastic curves

DEFF Research Database (Denmark)

Brander, David; Gravesen, Jens; Nørbjerg, Toke Bjerge

2016-01-01

We give an algorithm for approximating a given plane curve segment by a planar elastic curve. The method depends on an analytic representation of the space of elastic curve segments, together with a geometric method for obtaining a good initial guess for the approximating curve. A gradient......-driven optimization is then used to find the approximating elastic curve....

Learn ggplot2 using Shiny App

CERN Document Server

Moon, Keon-Woong

2016-01-01

This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding. In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript. This manual—"integrating" R, ggplot2, and Shiny—introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to bec...

Rapid effects of estrogens on short-term memory: Possible mechanisms.

Science.gov (United States)

Paletta, Pietro; Sheppard, Paul A S; Matta, Richard; Ervin, Kelsy S J; Choleris, Elena

2018-06-01

Estrogens affect learning and memory through rapid and delayed mechanisms. Here we review studies on rapid effects on short-term memory. Estradiol rapidly improves social and object recognition memory, spatial memory, and social learning when administered systemically. The dorsal hippocampus mediates estrogen rapid facilitation of object, social and spatial short-term memory. The medial amygdala mediates rapid facilitation of social recognition. The three estrogen receptors, α (ERα), β (ERβ) and the G-protein coupled estrogen receptor (GPER) appear to play different roles depending on the task and brain region. Both ERα and GPER agonists rapidly facilitate short-term social and object recognition and spatial memory when administered systemically or into the dorsal hippocampus and facilitate social recognition in the medial amygdala. Conversely, only GPER can facilitate social learning after systemic treatment and an ERβ agonist only rapidly improved short-term spatial memory when given systemically or into the hippocampus, but also facilitates social recognition in the medial amygdala. Investigations into the mechanisms behind estrogens' rapid effects on short term memory showed an involvement of the extracellular signal-regulated kinase (ERK) and the phosphoinositide 3-kinase (PI3K) kinase pathways. Recent evidence also showed that estrogens interact with the neuropeptide oxytocin in rapidly facilitating social recognition. Estrogens can increase the production and/or release of oxytocin and other neurotransmitters, such as dopamine and acetylcholine. Therefore, it is possible that estrogens' rapid effects on short-term memory may occur through the regulation of various neurotransmitters, although more research is need on these interactions as well as the mechanisms of estrogens' actions on short-term memory. Copyright © 2018 Elsevier Inc. All rights reserved.

Technological learning in bioenergy systems

International Nuclear Information System (INIS)

Junginger, Martin; Visser, Erika de; Hjort-Gregersen, Kurt; Koornneef, Joris; Raven, Rob; Faaij, Andre; Turkenburg, Wim

2006-01-01

The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90-93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91-92%, i.e. an 8-9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions

Bragg Curve Spectroscopy

International Nuclear Information System (INIS)

Gruhn, C.R.

1981-05-01

An alternative utilization is presented for the gaseous ionization chamber in the detection of energetic heavy ions, which is called Bragg Curve Spectroscopy (BCS). Conceptually, BCS involves using the maximum data available from the Bragg curve of the stopping heavy ion (HI) for purposes of identifying the particle and measuring its energy. A detector has been designed that measures the Bragg curve with high precision. From the Bragg curve the range from the length of the track, the total energy from the integral of the specific ionization over the track, the dE/dx from the specific ionization at the beginning of the track, and the Bragg peak from the maximum of the specific ionization of the HI are determined. This last signal measures the atomic number, Z, of the HI unambiguously

From the curve of the snake, and the scene of the crocodile: musings on learning and losing space, place and body

Directory of Open Access Journals (Sweden)

Susanne Gannon

2012-12-01

Full Text Available Where else can educational research begin and end, if not with the body of the researcher, if not with the particular material/ corporeal/ affective assemblages that this body is and has been part of? This paper traces the mutual constitution of bodies, identities and landscapes through memory as the body of this educator travels through multiple scenes of geo-spatial-temporal movement, and down the east coast of Australia. This movement parallels the movement from being a school teacher to becoming an academic. Throughout the paper landscape is foregrounded, and the body in landscape is evoked through poetic and literary modes of writing around the themes of learning and losing. The body in landscape is not merely the body of the writer. Other bodies in the landscape include ‘the curve of the snake’ - the row of protective hills that were said to protect her tropical home from cyclones – and the ‘scene of the crocodile’ – the rock that hung over the valley she passed on her way to school that she had learned of from Indigenous teachers. The political and ethical consequences of memory work, of body and place writing, and of genres of writing in educational research, are also considered. The paper argues for an embodied and reflexive literacy of place that incorporates multiple modes of knowing, being and writing.

Correlates of individual, and age-related, differences in short-term learning.

Science.gov (United States)

Zhang, Zhiyong; Davis, Hasker P; Salthouse, Timothy A; Tucker-Drob, Elliot M

2007-07-01

Latent growth models were applied to data on multitrial verbal and spatial learning tasks from two independent studies. Although significant individual differences in both initial level of performance and subsequent learning were found in both tasks, age differences were found only in mean initial level, and not in mean learning. In neither task was fluid or crystallized intelligence associated with learning. Although there were moderate correlations among the level parameters across the verbal and spatial tasks, the learning parameters were not significantly correlated with one another across task modalities. These results are inconsistent with the existence of a general (e.g., material-independent) learning ability.

Learning neuroendoscopy with an exoscope system (video telescopic operating monitor): Early clinical results.

Science.gov (United States)

Parihar, Vijay; Yadav, Y R; Kher, Yatin; Ratre, Shailendra; Sethi, Ashish; Sharma, Dhananjaya

2016-01-01

Steep learning curve is found initially in pure endoscopic procedures. Video telescopic operating monitor (VITOM) is an advance in rigid-lens telescope systems provides an alternative method for learning basics of neuroendoscopy with the help of the familiar principle of microneurosurgery. The aim was to evaluate the clinical utility of VITOM as a learning tool for neuroendoscopy. Video telescopic operating monitor was used 39 cranial and spinal procedures and its utility as a tool for minimally invasive neurosurgery and neuroendoscopy for initial learning curve was studied. Video telescopic operating monitor was used in 25 cranial and 14 spinal procedures. Image quality is comparable to endoscope and microscope. Surgeons comfort improved with VITOM. Frequent repositioning of scope holder and lack of stereopsis is initial limiting factor was compensated for with repeated procedures. Video telescopic operating monitor is found useful to reduce initial learning curve of neuroendoscopy.

The new courses of ethanol production in Brazil: an analysis from learning curves; Os novos rumos da producao de alcool combustivel no Brasil: uma analise a partir de curvas de aprendizagem

Energy Technology Data Exchange (ETDEWEB)

Pereira, Junior, Amaro Olimpio [Empresa de Pesquisa Energetica (EPE), Brasilia, DF (Brazil); Pereira, Andre Santos [Centre de Recherche sur Environement et Developement (CIRED), Paris (France); Mendonca, Marco Aurelio [Instituto de Pesquisa Economica Aplicada (IPEA), Brasilia, DF (Brazil); Costa, Ricardo Cunha da [Universidade Federal do Rio de Janeiro (PPE/COPPE/UFRJ), RJ (Brazil). Coordenacao do Programa de Pos-Graduacao em Engenharia. Programa de Pos-Graduacao em Planejamento Energetico

2008-07-01

PROALCOOL is known internationally as the most successful biofuel promotion program. Prior analysis of the effectiveness of such a program is fundamental to formulation of public policy, not only in the area of energy, but in all sectors of the economy. The article applies learning curve methodology to evaluate the ethanol market in Brazil in order to give an idea about the effort, in terms of investments, required for its advancement. (author)

A review of learning rates for electricity supply technologies

International Nuclear Information System (INIS)

Rubin, Edward S.; Azevedo, Inês M.L.; Jaramillo, Paulina; Yeh, Sonia

2015-01-01

A variety of mathematical models have been proposed to characterize and quantify the dependency of electricity supply technology costs on various drivers of technological change. The most prevalent model form, called a learning curve, or experience curve, is a log-linear equation relating the unit cost of a technology to its cumulative installed capacity or electricity generated. This one-factor model is also the most common method used to represent endogenous technical change in large-scale energy-economic models that inform energy planning and policy analysis. A characteristic parameter is the “learning rate,” defined as the fractional reduction in cost for each doubling of cumulative production or capacity. In this paper, a literature review of the learning rates reported for 11 power generation technologies employing an array of fossil fuels, nuclear, and renewable energy sources is presented. The review also includes multi-factor models proposed for some energy technologies, especially two-factor models relating cost to cumulative expenditures for research and development (R&D) as well as the cumulative installed capacity or electricity production of a technology. For all technologies studied, we found substantial variability (as much as an order of magnitude) in reported learning rates across different studies. Such variability is not readily explained by systematic differences in the time intervals, geographic regions, choice of independent variable, or other parameters of each study. This uncertainty in learning rates, together with other limitations of current learning curve formulations, suggests the need for much more careful and systematic examination of the influence of how different factors and assumptions affect policy-relevant outcomes related to the future choice and cost of electricity supply and other energy technologies. - Highlights: • We review models explaining the cost of 11 electricity supply technologies. • The most prevalent model

Contractibility of curves

Directory of Open Access Journals (Sweden)

Janusz Charatonik

1991-11-01

Full Text Available Results concerning contractibility of curves (equivalently: of dendroids are collected and discussed in the paper. Interrelations tetween various conditions which are either sufficient or necessary for a curve to be contractible are studied.

Roc curves for continuous data

CERN Document Server

Krzanowski, Wojtek J

2009-01-01

Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.The fundamental theory of ROC curvesThe book first discusses the relationship between the ROC curve and numerous performance measures and then extends the theory into practice by describing how ROC curves are estimated. Further building on the theory, the authors prese

Learning Curves: Making Quality Online Health Information Available at a Fitness Center

OpenAIRE

Dobbins, Montie T.; Tarver, Talicia; Adams, Mararia; Jones, Dixie A.

2012-01-01

Meeting consumer health information needs can be a challenge. Research suggests that women seek health information from a variety of resources, including the Internet. In an effort to make women aware of reliable health information sources, the Louisiana State University Health Sciences Center – Shreveport Medical Library engaged in a partnership with a franchise location of Curves International, Inc. This article will discuss the project, its goals and its challenges.