Length Of Training Research Articles

Training Toward Our Future: Questions About Length of Training in Family Medicine Programs.

Training Toward Our Future: Questions About Length of Training in Family Medicine Programs.

Regional flood frequency modeling: a comparative study among several data-driven models

Correct prediction of flood discharge is important to design the hydraulic structures, to diminish the danger of its failure, and to minimize the environmental damages of downstream. The present study aims to investigate the application of machine learning methods for regional flood frequency analysis (RFFA). To achieve this aim, a number of 18 parameters of physiographic, climatic, lithology, and land use for the upstream watershed of stations were considered. Then, the best regional probability distribution function (PDF) was determined through the Kolmogorov-Smirnov (KS) test in each station for estimation of flood discharge with a return period of 50 years (Q50). The best input combination and best length of training datasets were determined by Gamma and M tests, respectively. Finally, RFFA was performed using adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM), and genetic expression programming (GEP). Log-Pearson type III was identified as the best regional probability distribution based on the KS test for estimation of Q50. Gamma test results indicated that parameter of the perimeter, basin length, form factor, and mainstream length were selected as best input combination for RFFA. Also, according to the M-test results, the best length of training and testing datasets, 68% and 32% respectively, was determined. RFFA results indicated that the SVM, ANFIS, and GEP models had “good” performance (Nash-Sutcliff coefficient, NSE, equal to 0.75, 0.74, and 0.75, respectively).

Preliminary assessment of differences in completeness of house-training between dogs based on size

Only 25% of dog owners report receiving behavioral advice from their veterinarian. Preadoption counseling and general behavioral information sharing in routine puppy visits have been shown to significantly reduce the number of dogs that are euthanized or surrendered. Clinicians often categorize small dogs as being more difficult to house-train; however, there have been no published studies to date to confirm the veracity of this assumption. Some authors have proposed that smaller dogs have both a higher metabolism and a smaller bladder associated with more frequent urination which may lead to incomplete house-training. It is crucial to elucidate the underlying cause(s) of incomplete house-training because lack of house-training has been identified as a common reason for relinquishment. The purpose of this study was to evaluate the relationship between body size and completeness of house-training. An internet survey was made readily available on www.surveymonkey.com and posted on several general practice and referral center webpages and social media pages encouraging dog owners to participate. Questions regarding age at the time of adoption or purchase, level of obedience training, the role of the pet in the family, and medical disorders were included to rule in or out other contributing factors. Seven hundred thirty-five surveys submitted by private dog owners were fully completed and included in the study. A chi-square test of independence was performed which revealed a statistically significant difference between large dogs and small dogs regarding the completeness of house-training. Specifically, large dogs were more likely to be fully house-trained than small dogs. There was also a correlation between the level of training and completeness of house-training. Further research is warranted to understand why these differences are present. Clinically, this information provides knowledge which animal care professionals can use to advise clients that dogs of different sizes may require varied types and lengths of training to accomplish the goal of complete house-training.

Parallel simulation of railway pneumatic brake using openMP

ABSTRACTThe continuous growth of ore train lengths demands more efficient schedules, improved transit estimations and accident prevention schemes. Braking is a key component in achieving these objectives. Understandably, physical testing is potentially dangerous and costly. Meanwhile, the computational cost of calculating vehicle forces and brake airflow is high, both in computational effort and time. Therefore, strategies to improve analytical and simulation effectiveness efficiency are critical to achieve the goal of transporting more cargo safely and economically. This work implemented and compared the computational cost of a parallelization method against a traditional single-thread approach. The first model is based on lump parameters, while the second use Navier-Stokes conservation equations assuming an isothermal environment. Both models used OpenMP to execute on multiple cores. This implementation resulted in an 80% reduction in model solution time, when compared with the traditional single-thread approach.

Enhanced Avoidance Habits in Relation to History of Early-Life Stress.

The effect of stress on the balance between goal-directed behavior and stimulus–response habits has been demonstrated in a number of studies, but the extent to which stressful events that occur during development affect the balance between these systems later in life is less clear. Here, we examined whether individuals with a history of early-life stress (ELS) show a bias toward avoidance habits on an instrumental learning task as adults. Participants (N = 189 in Experiment 1 and N = 112 in Experiment 2) were undergraduate students at the University of California, Los Angeles. In Experiment 1, we hypothesized that a history of ELS and a longer training phase would be associated with greater avoidance habits. Participants learned to make button-press responses to visual stimuli in order to avoid aversive auditory outcomes. Following a training phase involving extensive practice of the responses, participants were tested for habitual responding using outcome devaluation. After completing the instrumental learning task, participants provided retrospective reports of stressful events they experienced during their first 16 years of life. We did not observe evidence for an effect of the length of training, but we did observe an effect of ELS, with greater stress predicting greater odds of performing the avoidance habit. In Experiment 2, we sought to replicate the effect of ELS observed in Experiment 1, and we also tested whether the presence of distraction during training would increase avoidance habit performance. We replicated the effect of ELS but we did not observe evidence of an effect of distraction. Taken together, these data lend support to the hypothesis that stress occurring during development can have lasting effects on the balance between goal-directed behavior and stimulus–response habits in humans. Enhancement of avoidance habits may help explain the higher levels of negative health outcomes such as heart and liver disease that have been observed in individuals with a history of ELS. Some of the negative health behaviors that contribute to these negative health outcomes, e.g., overeating and substance use, may be performed initially to avoid feelings of distress and then transition to being performed habitually.

Detection Rate Optimization for Swerling Targets in Gaussian Noise

In this paper, we consider a pulse radar and study the tradeoff between integration time and scan rate for diverse target scattering models. At the design stage, we optimize the available degrees of freedom (namely, pulse train length and detection threshold) so as to maximize the detection rate, defined as the average number of detections from the target per unit of time, subject to a constraint on the false alarm rate, which is the average number of false alarms from the monitored area per unit of time. This objective function allows to carefully balance the contrasting needs for a large probability of detection (achievable through a large dwell time) and a short scan time. Closed-form solutions are provided for Swerling's Cases 1 and 3 target fluctuation and for the Marcum nonfluctuating model, while, for the Swerling's Cases 2 and 4, the solution is found with the aid of computer simulation. A thorough performance analysis is given to show the achievable tradeoffs among the principal system parameters under the different target models.

MRI-based iPAGAT polymer gel dosimetry using fast recovery spin echo sequences

In an estimation of iPAGAT polymer gel dosimeters using a magnetic resonance imaging (MRI) system, the dosimetric characteristics were investigated with two echo sequences: a spin echo (SE) and a fast recovery fast spin echo (FRFSE) sequence. FRFSE can shorten total scan time compared to SE because of its short repetition time (TR) and long echo train length (ETL). Although the R2-dose response measured from FRFSE was decreased compared to SE, both responses were fitted quadratic curve with a high correlation coefficient. In addition, their calibrated dose distributions showed high conformity to the planned data in the three-dimensional (3D) gamma index, dose volume histogram (DVH) and surface rendering analyses; however, results of SE were a little superior to FRFSE. In conclusion, it is suggested that FRFSE can present the accurate characteristics of polymer gel dosimeters under the optimum parameters.

The effectivities of zakat productive funds toward zakat recipient income in Palembang

This study to investigate effectivities of zakat productive funds toward zakat recipient income in Palembang. Data using primary data which collect through interviews, observation, and documentation with instruments a questionnaire. The method in this study uses the quantitative approach with applying a regression model. The population in this study are all the recipients who receive the funding of zakat productive from BAZNAS of South Sumatra. The findings of this study indicated that the capital of zakat productive, length of business and training has a significant effect on zakat recipient income in Palembang city.

Implications of the directivity of railway noise sources for their quantification using conventional beamforming

This paper investigates the effect of the directivity of railway noise sources on the results of an identification procedure based on beamforming using a microphone array. Usually when performing pass-by noise tests, a single-microphone noise spectrum is obtained for a time window corresponding to the length of the whole train, or of a single vehicle. In this context, a source quantification algorithm should be able to evaluate the contribution of each noise source over this time window. However, different railway noise sources have different directivities, and it is shown that these need to be taken into account to achieve accurate source quantification. By making use of monopoles, dipoles and quadrupoles, it is shown that a different compensation is needed according to the directivity. For the particular case of the noise radiated by the rail, this has a complex directivity pattern that is only partially captured by a microphone array. It is demonstrated that the overestimation of the wheel contribution found in previous research may be attributed to a misinterpretation of part of the rail contribution from the beamforming map.

A Large-Scale, Cross-Sectional Investigation Into the Efficacy of Brain Training.

Brain training is a large and expanding industry, and yet there is a recurrent and ongoing debate concerning its scientific basis or evidence for efficacy. Much of evidence for the efficacy of brain training within this debate is from small-scale studies that do not assess the type of “brain training,” the specificity of transfer effects, or the length of training required to achieve a generalized effect. To explore these factors, we analyze cross-sectional data from two large Internet-cohort studies (total N = 60,222) to determine whether cognition differs at the population level for individuals who report that they brain train on different devices, and across different timeframes, with programs in common use circa 2010–2013. Examining scores for an assessment of working-memory, reasoning and verbal abilities shows no cognitive advantages for individuals who brain train. This contrasts unfavorably with significant advantages for individuals who regularly undertake other cognitive pursuits such as computer, board and card games. However, finer grained analyses reveal a more complex relationship between brain training and cognitive performance. Specifically, individuals who have just begun to brain train start from a low cognitive baseline compared to individuals who have never engaged in brain training, whereas those who have trained for a year or more have higher working-memory and verbal scores compared to those who have just started, thus suggesting an efficacy for brain training over an extended period of time. The advantages in global function, working memory, and verbal memory after several months of training are plausible and of clinically relevant scale. However, this relationship is not evident for reasoning performance or self-report measures of everyday function (e.g., employment status and problems with attention). These results accord with the view that although brain training programs can produce benefits, these might extend to tasks that are operationally similar to the training regime. Furthermore, the duration of training regime required for effective enhancement of cognitive performance is longer than that applied in most previous studies.

Ranking Programs: Medical Student Strategies.

Selecting a training program is one of the most challenging choices an applicant to the Match has to make. To make an informed decision, applicants should do a comprehensive research and carefully plan their upcoming steps. Factors that might influence the applicants' decision include geography, program reputation, specific areas of academic focus, subspecialty interests, university-versus community-based training, length of training and interest in combined programs. Such information can be gathered from published material, websites, and personal advice (from faculty, residents and advisors). This process is time-consuming and stressful. Therefore, in this article we elaborate on the above to facilitate this process for applicants.

Modular Prosthetic Limb Control by an Individual with Congenital Upper-Limb Amputation: A Case Report

ABSTRACT Introduction This article presents a unique case study of an individual with congenital limb loss and long-time (>56 years) body-powered prosthesis use, who was able to control a sophisticated robotic upper-limb prosthesis using surface electromyography signals and pattern recognition (PR) algorithms. This case demonstrates that individuals with congenital limb amputation are able to learn unique strategies to intuitively control a dexterous prosthetic limb. Materials and Methods After completing four training sessions using a virtual integration environment, a single subject participated in 12 in-laboratory clinical training sessions using the modular prosthetic limb (MPL)—a novel multiple–degree-of-freedom dexterous upper-limb prosthesis prototype. Baseline assessments were made with her body-powered prosthesis, as well as a two-site direct-control myoelectric Bebionic she had recently received. Functional assessments with the MPL were conducted during sessions 6 and 12. Outcome measures included timed box and blocks (BB) test, Assessment of Capacity for Myoelectric Control (ACMC), Jebsen-Taylor Hand Function Test (JTHFT), Trinity Amputation and Prosthesis Experience Scale, Upper Extremity Functional Scale (UEFS), and NASA Task Load Index. Results The subject was able to control two independent wrist degrees of freedom and up to three independent hand grasps of the MPL, using an array of surface electrodes. Improvements in the BB and ACMC were observed, although the total time to complete the JTHFT stayed relatively the same from weeks 6 to 12, using the MPL. While her enpoint perceived funcitonal ability with the MPL was 58% compared with 83% with her personal myoelectric prosthesis (12 hours of use vs 4–5 weeks of use as denoted on the UEFS); the subject reported short length of training, a long-term body-powered prosthetic user with congenital limb loss was able to demonstrate objective improvements in control of a dexterous prosthetic hand over a 12-week period of in-laboratory training, achieving intuitive independent control of a variety of simultaneous individual wrist motions and grasp patterns using PR. Conclusions This case demonstrates that even individuals with congenital amputation may be considered as candidates for upper-limb PR-controlled myoelectric prosthetic devices using surface electrodes.

What Can the Giant Do? Defining the Path to Unsupervised Primary Care Practice by Competence, Not Time.

In this issue of Academic Medicine, Dewan and Norcini examine the significant variability of time-in-training between patient care "giants"-the physicians, nurse practitioners, and physician assistants who practice primary care-and they call for further studies to determine optimal training duration and eventual scope of practice. They ask, what is the minimum education and training required to practice primary care, or "how tall is the shortest giant?" In this Invited Commentary, the authors reframe the question from identifying the minimum length of training required, to identifying desired patient care outcomes. Primary care is not a uniform entity. It ranges from complex elderly chronically ill patients, to twentysomething millennials with acute problems, to pregnant women, to families, and everything in between. The authors argue that training should be fit for purpose and produce high-quality outcomes for patients. Competence should be defined by these outcomes. Drawing parallels with Major League Baseball, the authors note that time to competence development will be variable for different training programs depending on purpose, and also variable for people within those programs, even with shared purpose. While time is a tool for competence attainment, it should not be the metric by which readiness for practice is measured.

Over-selectivity decreases with increased training: A role for within-compound associations

Over-selectivity occurs when one element of a complex-stimulus controls behavior at the expense of other equally elements of that stimulus; a phenomenon common in populations subject to cognitive challenge. However, lack of theoretically-based analysis, may have hindered understanding and remediation of the practically-important over-selectivity phenomena. Current studies examined whether associative theories applied to overshadowing, a similar phenomenon in the context of conditioning experiments, could be applied to over-selectivity effects to open theoretical analysis of over-selectivity. Three experiments investigated whether length of training impacts over-selectivity in the same way as overshadowing, which has theoretical implications for understanding that latter phenomenon. All studies employed variants of a judgment procedure in which participants had to judge the relationship between a predictor and an outcome, and the predictors were presented either on their own, or in compound with another predictor. In all studies, the elemental cue (A) was rated similarly to one of the components of the compound (B), but higher than the other component (C). The difference in the extent to which the components of the compound (B and C) were judged as predictors became smaller as levels of training increased, which is an effect that is also seen in discrimination learning studies of over-selectivity. Moreover, it was apparent that as the strength of the within-compound association increased, the level of over-selectivity decreased. These results are similar to those seen for overshadowing, and are discussed with respect to the possible associative mechanisms controlling over-selectivity.

Construction of a parametric model of competitive access in relational databases by using a random forest method

We have considered the task on modeling a request execution time in autonomous relational databases with competitive queries. The shortcomings of existing approaches have been specified, which ignore the cost of the share of successive operations in the cooperative access to data in a memory hierarchy. We have examined the issue of the application of relative cost for the implementation of components in the operations of a plan of the query, instead of calculating the predicted time of computation. A technique has been proposed for the formal construction of precedents for a training sample, as well as the approach to building a regression model. The developed modification of the machine learning method random forest is used for calculating the request execution time based on their texts and temporary marks of the start, duration of execution. The constructed parametrical model of competitive access to data is required for obtaining accurate estimates of request execution time when using parallel computations. Models with such characteristics are needed to solve the problems on automated management of a physical data scheme, for building self-identifiable DBMS. The key differences from existing approaches are the application of a request execution time as the target value, accounting the values of predicates and mutual influence of requests that are executed in parallel. To confirm the results obtained, a simulation model has been used based on the widely known test TPC-C. The used function of loss, taking into consideration the regression nature of the model, was the ratio of the sum of modules of difference between the actual and obtained time to the actual time. The check itself was carried out based on a reference sample, generated for the increasing length of training at postponed data. In the course of this study we have proved a possibility to apply the machine learning method random forest for processing statistical data on the execution of SQL queries. The result obtained is promising for such an approach and makes it possible to derive the parametric models of competitive request processing.

Evaluation of an Interactive, Online Training for Child Care Providers on Healthy Beverages for Young Children (P16-039-19)

ObjectivesEvaluate if a 30-minute interactive, online training with 6-months of ongoing technical assistance (TA) for early care and education (ECE) providers improves beverage nutrition for young children. The training, developed by health professionals and child development experts, teaches implementation of California’s Healthy Beverages in Child Care Act (AB2084) to 1) serve no beverages with added sweeteners, 2) serve no more than one age-appropriate daily serving of 100% juice, 3) serve unflavored nonfat or low-fat milk to children 2 years and older, and 4) make water readily available at all times. We hypothesize that ECE providers who complete the training will exhibit improved knowledge of and compliance with beverage standards than the control group. MethodsProviders offering care to children age 2–5 years old were recruited from three California counties and randomized to receive the training intervention or no training. Providers complete online and paper surveys at four time-points over six months to assess their training experience, knowledge of healthy beverages, and compliance with AB2084 based on self-reported beverage provision practices. ResultsProviders (N = 66) were mostly English-speaking (97%), female (98%), white (58%), Hispanic or Latino (20%), Asian or Pacific Islander (18%), with a minimum of some college education (97%). Preliminary results of 33 providers who received the training, with no comparison group, show improved compliance with AB2084 at the first time-point, one month post training, compared to baseline for serving no beverages with added sweeteners (100% vs 95%), serving 100% juice no more than once per day (100% vs. 86%), serving only unflavored nonfat or low-fat milk to children 2 years and older (82% vs. 61%), and making water readily available at all times (82% vs. 75%). Providers reported satisfaction with the training (90%), learned something new (95%), understood the training (100%), reported the training length was appropriate (83%) and that the accompanying online resources were helpful (95%). ConclusionsPreliminary analysis suggests that online training and TA can improve ECE provider’s compliance with healthy beverage standards for young children (AB2084). Final process and outcome evaluation results from both groups will be available at the conference. Funding SourcesUC Agriculture & Natural Resources.

Child welfare workers’ knowledge of risk factors for child maltreatment fatalities: a second multi-state assessment

ABSTRACT This paper reports results from a second study which examines the knowledge and training of child welfare professionals with regard to risk factors for fatal child maltreatment. This multi-state, online study (n = 619) shows that workers have gaps in their knowledge of risk factors for maltreatment-related deaths. The majority of workers had received training, but it had little impact on worker knowledge. Workers reported receiving a variety of trainings on risks for fatalities, with different sources, length of training, and foci. Workers who received training that focused on research-based risk factors had higher levels of knowledge than other workers.

A full-scale experimental investigation of passenger and freight train aerodynamics

The movement of a train creates a disturbance to the air through which it passes, known as a slipstream. Such disturbances are characterised by changes in pressure, notably around the vehicle nose/tail, and a highly turbulent boundary growth along the vehicle side with an increasing slipstream velocity magnitude. Although these characteristic features occur in some form for all trains, the flow development associated with various train types can often be very different. Variability in train type makes it difficult to accurately characterise the aerodynamic effects of each individual train. In this paper, a detailed set of tests are undertaken to assess the aerodynamic flow development created around various train types common to the UK railway network. A comparison of the analysed data from different passenger and freight trains was made. The variability of freight train results was larger in comparison to the passenger trains examined, because of the large flow separations around the bluff freight train. Although the speed was lower for freight trains, the slipstream velocity and pressure magnitudes were larger than those observed for passenger trains. Passenger trains could be divided aerodynamically into two main types: long distance passenger trains and commuter trains. Longer train lengths were shown to increase the boundary layer growth: an important feature for long distance passenger trains as it creates an increase in the slipstream velocity peak magnitude at the train tail. Boundary layer stabilisation is not observed as in previous studies. The coupling of two carriage sets together, creating a large V-shaped region at the centre of the train, led to a clear step slipstream velocity peak coinciding with the change in pressure at the coupling region. Cross-correlation of results from measuring positions within the characteristic turbulent length scale range appeared to show similar results to autocorrelation time scales for larger scale separation of turbulent structures from the bogie and inter-carriage regions.

Autistic traits, resting-state connectivity, and absolute pitch in professional musicians: shared and distinct neural features

BackgroundRecent studies indicate increased autistic traits in musicians with absolute pitch and a higher proportion of absolute pitch in people with autism. Theoretical accounts connect both of these with shared neural principles of local hyper- and global hypoconnectivity, enhanced perceptual functioning, and a detail-focused cognitive style. This is the first study to investigate absolute pitch proficiency, autistic traits, and brain correlates in the same study.Sample and methodsGraph theoretical analysis was conducted on resting-state (eyes closed and eyes open) EEG connectivity (wPLI, weighted phase lag index) matrices obtained from 31 absolute pitch (AP) and 33 relative pitch (RP) professional musicians. Small-worldness, global clustering coefficient, and average path length were related to autistic traits, passive (tone identification) and active (pitch adjustment) absolute pitch proficiency, and onset of musical training using Welch two-sample tests, correlations, and general linear models.ResultsAnalyses revealed increased path length (delta 2–4 Hz), reduced clustering (beta 13–18 Hz), reduced small-worldness (gamma 30–60 Hz), and increased autistic traits for AP compared to RP. Only clustering values (beta 13–18 Hz) were predicted by both AP proficiency and autistic traits. Post hoc single connection permutation tests among raw wPLI matrices in the beta band (13–18 Hz) revealed widely reduced interhemispheric connectivity between bilateral auditory-related electrode positions along with higher connectivity between F7–F8 and F8–P9 for AP. Pitch-naming ability and pitch adjustment ability were predicted by path length, clustering, autistic traits, and onset of musical training (for pitch adjustment) explaining 44% and 38% of variance, respectively.ConclusionsResults show both shared and distinct neural features between AP and autistic traits. Differences in the beta range were associated with higher autistic traits in the same population. In general, AP musicians exhibit a widely underconnected brain with reduced functional integration and reduced small-world property during resting state. This might be partly related to autism-specific brain connectivity, while differences in path length and small-worldness reflect other ability-specific influences. This is further evidenced for different pathways in the acquisition and development of absolute pitch, likely influenced by both genetic and environmental factors and their interaction.

Whole-brain B1 -mapping using three-dimensional DREAM.

Demonstration of a 3D version of the DREAM sequence (3DREAM) for rapid 3D flip angle and mapping of the human brain. A rectangular non-selective STE preparation is followed by a 3D readout with a Cartesian center-out spiral phase encoding order. This enables parallel imaging acceleration in both phase encoding dimensions as well as early capture of the prepared magnetization. mapping of the whole human head is demonstrated on a 7T system at a nominal resolution of 5 mm with and without parallel imaging acceleration. Artifacts caused by the different signal decay of the FID and STE signal during the long imaging train is suppressed by appropriate filtering of the FID image. Remaining blurring can be controlled by adjusting the echo train length and readout flip angle. 3DREAM provides a whole-brain flip angle map in a few seconds or individual maps for an 8-channel array in about a minute.