Learning to drive: learners' self-reported cognitive failure level predicts driving instructor's observation rating of driving performance

OBJECTIVES Evidence increases that cognitive failure may be used to screen for drivers at risk. Until now, most studies have relied on driving learners. This exploratory pilot study examines self-report of cognitive failure in driving beginners and error during real driving as observed by driving instructors. METHODS Forty-two driving learners of 14 driving instructors filled out a work-related cognitive failure questionnaire. Driving instructors observed driving errors during the next driving lesson. In multiple linear regression analysis, driving errors were regressed on cognitive failure with the number of driving lessons as an estimator of driving experience controlled. RESULTS Higher cognitive failure predicted more driving errors (p < .01) when age, gender and driving experience were controlled in analysis. CONCLUSIONS Cognitive failure was significantly associated with observed driving errors. Systematic research on cognitive failure in driving beginners is recommended.

Bifurcation and singularity analysis of a molecular network for the induction of long-term memory.

Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying bifurcation analysis, singularity theory, and numerical simulation. Using singularity theory, classification diagrams of parameter space were constructed, identifying regions with qualitatively different steady-state behaviors. The graphical representation of these regions illustrates the robustness of these regions to changes in model parameters. Because persistent protein kinase A (PKA) activity correlates with Aplysia LTM, the analysis focuses on a positive feedback loop in the model that tends to maintain PKA activity. In this loop, PKA phosphorylates a transcription factor (TF-1), thereby increasing the expression of an ubiquitin hydrolase (Ap-Uch). Ap-Uch then acts to increase PKA activity, closing the loop. This positive feedback loop manifests multiple, coexisting steady states, or multiplicity, which provides a mechanism for a bistable switch in PKA activity. After the removal of 5-HT, the PKA activity either returns to its basal level (reversible switch) or remains at a high level (irreversible switch). Such an irreversible switch might be a mechanism that contributes to the persistence of LTM. The classification diagrams also identify parameters and processes that might be manipulated, perhaps pharmacologically, to enhance the induction of memory. Rational drug design, to affect complex processes such as memory formation, can benefit from this type of analysis.

Learning curve for robotic-assisted laparoscopic colorectal surgery.

BACKGROUND: Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. METHODS: A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. RESULTS: The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m(2), and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 31.54 × case number - 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. CONCLUSIONS: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

Envisioning sustainable water futures in a transdisciplinary learning process: combining normative, explorative, and participatory scenario approaches

Competing water demands for household consumption as well as the production of food, energy, and other uses pose challenges for water supply and sustainable development in many parts of the world. Designing creative strategies and learning processes for sustainable water governance is thus of prime importance. While this need is uncontested, suitable approaches still have to be found. In this article we present and evaluate a conceptual approach to scenario building aimed at transdisciplinary learning for sustainable water governance. The approach combines normative, explorative, and participatory scenario elements. This combination allows for adequate consideration of stakeholders’ and scientists’ systems, target, and transformation knowledge. Application of the approach in the MontanAqua project in the Swiss Alps confirmed its high potential for co-producing new knowledge and establishing a meaningful and deliberative dialogue between all actors involved. The iterative and combined approach ensured that stakeholders’ knowledge was adequately captured, fed into scientific analysis, and brought back to stakeholders in several cycles, thereby facilitating learning and co-production of new knowledge relevant for both stakeholders and scientists. However, the approach also revealed a number of constraints, including the enormous flexibility required of stakeholders and scientists in order for them to truly engage in the co-production of new knowledge. Overall, the study showed that shifts from strategic to communicative action are possible in an environment of mutual trust. This ultimately depends on creating conditions of interaction that place scientists’ and stakeholders’ knowledge on an equal footing.

ANALYSIS OF SEROTONERGIC MODULATION OF NEURONS INVOLVED IN TWO DEFENSIVE BEHAVIORS IN APLYSIA CALIFORNICA (CYCLIC-AMP, AROUSAL, CALCIUM, POTASSIUM)

Sensitization is a simple form of learning which refers to an enhancement of a behavioral response resulting from an exposure to a novel stimulus. While sensitization is found throughout the animal world, little is known regarding the underlying neural mechanisms. By taking advantage of the simple nervous system of the marine mollusc Aplysia, I have begun to examine the cellular and molecular mechanisms underlying this simple form of learning. In an attempt to determine the generality of the mechanisms of neuromodulation underlying sensitization, I have investigated and compared the modulation of neurons involved in two defensive behaviors in Aplysia, the defensive inking response and defensive tail withdrawal.^ The motor neurons that produce the defensive release of ink receive a slow decreased conductance excitatory postsynaptic potential (EPSP) in response to sensitizing stimuli. Using electrophysiological techniques, it was found that serotonin (5-HT) mimicked the physiologically produced slow EPSP. 5-HT produced its response through a reduction in a voltage-independent conductance to K('+). The 5-HT sensitive K('+) conductance of the ink motor neurons was separate from the fast K('+), delayed K('+), and Ca('2+)-activated K('+) conductances found in these and other molluscan neurons. 5-HT was shown to produce a decrease in K('+) conductance in the ink motor neurons through an elevation of cellular cAMP.^ The mechanosensory neurons that participate in the defensive tail withdrawal response are also modulated by sensitizing stimuli through the action of 5-HT. Using electrophysiological techniques, it was found that 5-HT modulated the tail sensory neurons through a reduction in a voltage-dependent conductance to K('+). The serotonin-sensitive K('+) conductance was found to be largely a Ca('2+)-activated K('+) conductance. Much like the ink motor neurons, 5-HT produced its modulation through an elevation of cellular cAMP. While the actual K('+) conductance modulated by 5-HT in these two classes of neurons differs, the following generalizations can be made: (1) the effects of sensitizing stimuli are mimicked by 5-HT, (2) 5-HT produces its effect through an elevation of cellular cAMP, and (3) the conductance to K('+) is modulated by 5-HT. ^

Early adolescents' enjoyment experienced in learning situations and its relation to student achievement

While many studies confirm that positive emotions, including enjoyment, lead to better student achievement, less empirical evidence exists about possible mediator variables that link achievement to enjoyment. It is proposed that achievement and enjoyment form a circular dependency; enjoyment in learning leads to higher achievement but a degree of achievement is required to enjoy learning. This study provides insight into the reverse of the much studied enjoyment to achievement link and provides practical recommendations on how to use these findings. Founded in Control-value theory, which suggests that control and value cognitions are important variables that mediate the connection between enjoyment and achievement, this study explores the reciprocal achievement-cognition-enjoyment link. The reciprocal link was investigated by applying a one year longitudinal design to students of grade 6 and 7 (N = 356). This age group was chosen because early adolescence represents a critical period during which a strong decrease in positive learning emotions is observed. Part of the work involved identifying factors that might be responsible for this negative development. Results of cross-lagged path analysis identified reciprocal effects between student achievement and enjoyment with control and value cognitions functioning as partial mediators. High achievement goes with high control and value cognitions, which in turn positively affect enjoyment. However, cross-lagged correlations could only be partly confirmed. The results are discussed in terms of theoretical and practical implications.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

Early adolescents’ enjoyment experienced in learning situations at school and its relation to student achievement

While many studies confirm that positive emotions, including enjoyment, lead to better student achievement, less empirical evidence exists about possible mediator variables that link achievement to enjoyment. It is proposed that achievement and enjoyment form a circular dependency; enjoyment in learning leads to higher achievement but a degree of achievement is required to enjoy learning. This study provides insight into the reverse of the much studied enjoyment to achievement link and provides practical recommendations on how to use these findings. Founded in Control-value theory, which suggests that control and value cognitions are important variables that mediate the connection between enjoyment and achievement, this study explores the reciprocal achievement-cognition-enjoyment link. The reciprocal link was investigated by applying a one year longitudinal design to students of grade 6 and 7 (N = 356). This age group was chosen because early adolescence represents a critical period during which a strong decrease in positive learning emotions is observed. Part of the work involved identifying factors that might be responsible for this negative development. Results of cross-lagged path analysis identified reciprocal effects between student achievement and enjoyment with control and value cognitions functioning as partial mediators. High achievement goes with high control and value cognitions, which in turn positively affect enjoyment. However, cross-lagged correlations could only be partly confirmed. The results are discussed in terms of theoretical and practical implications

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Endoscopic and Open Release Similarly Safe for the Treatment of Carpal Tunnel Syndrome. A Systematic Review and Meta-Analysis.

BACKGROUND The Endoscopic Release of Carpal Tunnel Syndrome (ECTR) is a minimal invasive approach for the treatment of Carpal Tunnel Syndrome. There is scepticism regarding the safety of this technique, based on the assumption that this is a rather "blind" procedure and on the high number of severe complications that have been reported in the literature. PURPOSE To evaluate whether there is evidence supporting a higher risk after ECTR in comparison to the conventional open release. METHODS We searched MEDLINE (January 1966 to November 2013), EMBASE (January 1980 to November 2013), the Cochrane Neuromuscular Disease Group Specialized Register (November 2013) and CENTRAL (2013, issue 11 in The Cochrane Library). We hand-searched reference lists of included studies. We included all randomized or quasi-randomized controlled trials (e.g. study using alternation, date of birth, or case record number) that compare any ECTR with any OCTR technique. Safety was assessed by the incidence of major, minor and total number of complications, recurrences, and re-operations.The total time needed before return to work or to return to daily activities was also assessed. We synthesized data using a random-effects meta-analysis in STATA. We conducted a sensitivity analysis for rare events using binomial likelihood. We judged the conclusiveness of meta-analysis calculating the conditional power of meta-analysis. CONCLUSIONS ECTR is associated with less time off work or with daily activities. The assessment of major complications, reoperations and recurrence of symptoms does not favor either of the interventions. There is an uncertain advantage of ECTR with respect to total minor complications (more transient paresthesia but fewer skin-related complications). Future studies are unlikely to alter these findings because of the rarity of the outcome. The effect of a learning curve might be responsible for reduced recurrences and reoperations with ECTR in studies that are more recent, although formal statistical analysis failed to provide evidence for such an association. LEVEL OF EVIDENCE I.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

Virtual Patients in continuing medical education and residency training: a pilot project for acceptance analysis in the framework of a residency revision course in pediatrics.

AIM Virtual patients (VPs) are a one-of-a-kind e-learning resource, fostering clinical reasoning skills through clinical case examples. The combination with face-to-face teaching is important for their successful integration, which is referred to as "blended learning". So far little is known about the use of VPs in the field of continuing medical education and residency training. The pilot study presented here inquired the application of VPs in the framework of a pediatric residency revision course. METHODS Around 200 participants of a pediatric nephology lecture ('nephrotic and nephritic syndrome in children') were offered two VPs as a wrap-up session at the revision course of the German Society for Pediatrics and Adolescent Medicine (DGKJ) 2009 in Heidelberg, Germany. Using a web-based survey form, different aspects were evaluated concerning the learning experiences with VPs, the combination with the lecture, and the use of VPs for residency training in general. RESULTS N=40 evaluable survey forms were returned (approximately 21%). The return rate was impaired by a technical problem with the local Wi-Fi firewall. The participants perceived the work-up of the VPs as a worthwhile learning experience, with proper preparation for diagnosing and treating real patients with similar complaints. Case presentations, interactivity, and locally and timely independent repetitive practices were, in particular, pointed out. On being asked about the use of VPs in general for residency training, there was a distinct demand for more such offers. CONCLUSION VPs may reasonably complement existing learning activities in residency training.

Undergraduate palliative care teaching in Swiss medical faculties: a nationwide survey and improved learning objectives

BACKGROUND In 2007, a first survey on undergraduate palliative care teaching in Switzerland has revealed major heterogeneity of palliative care content, allocation of hours and distribution throughout the 6 year curriculum in Swiss medical faculties. This second survey in 2012/13 has been initiated as part of the current Swiss national strategy in palliative care (2010 - 2015) to serve as a longitudinal monitoring instrument and as a basis for redefinition of palliative care learning objectives and curriculum planning in our country. METHODS As in 2007, a questionnaire was sent to the deans of all five medical faculties in Switzerland in 2012. It consisted of eight sections: basic background information, current content and hours in dedicated palliative care blocks, current palliative care content in other courses, topics related to palliative care presented in other courses, recent attempts at improving palliative care content, palliative care content in examinations, challenges, and overall summary. Content analysis was performed and the results matched with recommendations from the EAPC for undergraduate training in palliative medicine as well as with recommendations from overseas countries. RESULTS There is a considerable increase in palliative care content, academic teaching staff and hours in all medical faculties compared to 2007. No Swiss medical faculty reaches the range of 40 h dedicated specifically to palliative care as recommended by the EAPC. Topics, teaching methods, distribution throughout different years and compulsory attendance still differ widely. Based on these results, the official Swiss Catalogue of Learning Objectives (SCLO) was complemented with 12 new learning objectives for palliative and end of life care (2013), and a national basic script for palliative care was published (2015). CONCLUSION Performing periodic surveys of palliative care teaching at national medical faculties has proven to be a useful tool to adapt the national teaching framework and to improve the recognition of palliative medicine as an integral part of medical training.

Shallow Dialogue Processing Using Machine Learning Algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.

Context Aware e-Learning Objects and their Types from the Perspective of the Object-Oriented Paradigm

The contribution of this article demonstrates how to identify context-aware types of e-Learning objects (eLOs) derived from the subject domains. This perspective is taken from an engineering point of view and is applied during requirements elicitation and analysis relating to present work in constructing an object-oriented (OO), dynamic, and adaptive model to build and deliver packaged e-Learning courses. Consequently, three preliminary subject domains are presented and, as a result, three primitive types of eLOs are posited. These types educed from the subject domains are of structural, conceptual, and granular nature. Structural objects are responsible for the course itself, conceptual objects incorporate adaptive and logical interoperability, while granular objects congregate granular assets. Their differences, interrelationships, and responsibilities are discussed. A major design challenge relates to adaptive behaviour. Future research addresses refinement on the subject domains and adaptive hypermedia systems.