Adaptive training adjusts a training task with the goal of improving learning outcomes. Adaptive training has been shown to improve human performance in attention, working memory capacity, and motor control tasks. Additionally, correlations have been observed between neural EEG spectral features and the performance of some cognitive tasks. This relationship suggests some EEG features may be useful in adaptive training regimens. Here, we anticipated that adding a neural measure into a behavioral-based adaptive (...) training system would improve human performance on a subsequent transfer task. We designed, developed, and conducted a between-subjects study of 44 participants comparing three training regimens: Single Item Fixed Difficulty, Behaviorally Adaptive Training, and Combined Adaptive Training using both behavioral and EEG measures. Results showed a statistically significant transfer task performance advantage of the CAT-based system relative to SIFD and BAT systems of 6 and 9 percentage points, respectively. Our research shows a promising pathway for designing closed-loop BCI systems based on both users' behavioral performance and neural signals for augmenting human performance. (shrink)

While often presented as promising assistive technologies for motor-impaired users, electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) remain barely used outside laboratories due to low reliability in real-life conditions. There is thus a need to design long-term reliable BCIs that can be used outside-of-the-lab by end-users, e.g., severely motor-impaired ones. Therefore, we propose and evaluate the design of a multi-class Mental Task (MT)-based BCI for longitudinal training (20 sessions over 3 months) of a tetraplegic user for the CYBATHLON BCI series 2019. (...) In this BCI championship, tetraplegic pilots are mentally driving a virtual car in a racing video game. We aimed at combining a progressive user MT-BCI training with a newly designed machine learning pipeline based on adaptive Riemannian classifiers shown to be promising for real-life applications. We followed a two step training process: the first 11 sessions served to train the user to control a 2-class MT-BCI by performing either two cognitive tasks (REST and MENTAL SUBTRACTION) or two motor-imagery tasks (LEFT-HAND and RIGHT-HAND). The second training step (9 remaining sessions) applied an adaptive, session-independent Riemannian classifier that combined all 4 MT classes used before. Moreover, as our Riemannian classifier was incrementally updated in an unsupervised way it would capture both within and between-session non-stationarity. Experimental evidences confirm the effectiveness of this approach. Namely, the classification accuracy improved by about 30% at the end of the training compared to initial sessions. We also studied the neural correlates of this performance improvement. Using a newly proposed BCI user learning metric, we could show our user learned to improve his BCI control by producing EEG signals matching increasingly more the BCI classifier training data distribution, rather than by improving his EEG class discrimination. However, the resulting improvement was effective only on synchronous (cue-based) BCI and it did not translate into improved CYBATHLON BCI game performances. For the sake of overcoming this in the future, we unveil possible reasons for these limited gaming performances and identify a number of promising future research directions. Importantly, we also report on the evolution of the user's neurophysiological patterns and user experience throughout the BCI training and competition. (shrink)

Drawing upon career construction theory, we examined the mediating effect of deliberate practice on career adaptability and the effects of learning goal orientation and supervisor incompetence accusations as well as career development training on DP. Using data collected from 204 Chinese PhD students in three waves over a period of 2 months, we found that individuals who were inclined to learn new skills and obtain new knowledge were more likely to deliberately practice professional activities in their fields. When a (...) PhD student’s professional competence was questioned by his or her supervisor, the student was more prone to negative emotions and would reduce his or her effort in the development of expertise. CDT – contrary to expectations – negatively predicted DP of professional activities. One possible reason is that the participants in this study have strong autonomy so that those who really struggling are participating in training and seeking help and those who with strong professional abilities are not accessing training programs. Moreover, results showed that DP of professional activities significantly promoted PhD students to adapt to their academic circumstances. Implications for career-related practice within the academic domain are provided. (shrink)

CYBATHLON is an international championship where people with severe physical disabilities compete with the aid of state-of-the-art assistive technology. In one of the disciplines, the BCI Race, tetraplegic pilots compete in a computer game race by controlling an avatar with a brain-computer interface. This competition offers a perfect opportunity for BCI researchers to study long-term training effects in potential end-users, and to evaluate BCI performance in a realistic environment. In this work, we describe the BCI system designed by the (...) team Mirage91 for participation in the CYBATHLON BCI Series 2019, as well as in the CYBATHLON 2020 Global Edition. Furthermore, we present the BCI’s interface with the game and the main methodological strategies, along with a detailed evaluation of its performance over the course of the training period, which lasted 14 months. The developed system was a 4-class BCI relying on task-specific modulations of brain rhythms. We implemented inter-session transfer learning to reduce calibration time, and to reinforce the stability of the brain patterns. Additionally, in order to compensate for potential intra-session shifts in the features’ distribution, normalization parameters were continuously adapted in an unsupervised fashion. Across the aforementioned 14 months, we recorded 26 game-based training sessions. Between the first eight sessions, and the final eight sessions leading up to the CYBATHLON 2020 Global Edition, the runtimes significantly improved from 255 ± 23 s to 225 ± 22 s, respectively. Moreover, we observed a significant increase in the classifier’s accuracy from 46 to 53%, driven by more distinguishable brain patterns. Compared to conventional single session, non-adaptive BCIs, the inter-session transfer learning and unsupervised intra-session adaptation techniques significantly improved the performance. This long-term study demonstrates that regular training helped the pilot to significantly increase the distance between task-specific patterns, which resulted in an improvement of performance, both with respect to class separability in the calibration data, and with respect to the game. Furthermore, it shows that our methodological approaches were beneficial in transferring the performance across sessions, and most importantly to the CYBATHLON competitions. (shrink)

This demonstration recreates an example of introspective training from E.B. Titchener's laboratory manual of 1901-1905. The purpose is to prompt thought about the prospects of introspective training as a means of improving the quality of introspective reports about conscious experience. The demonstration requires speakers or headphones, and a high-speed internet connection is recommended.

Deep Learning has been widely used for tackling challenging natural language processing tasks over the recent years. Similarly, the application of Deep Neural Networks in legal analytics has increased significantly. In this survey, we study the early adaptation of Deep Learning in legal analytics focusing on three main fields; text classification, information extraction, and information retrieval. We focus on the semantic feature representations, a key instrument for the successful application of deep learning in natural language processing. Additionally, we share pre-trained (...) legal word embeddings using the word2vec model over large corpora, comprised legislations from UK, EU, Canada, Australia, USA, and Japan among others. (shrink)

Deep Learning has been widely used for tackling challenging natural language processing tasks over the recent years. Similarly, the application of Deep Neural Networks in legal analytics has increased significantly. In this survey, we study the early adaptation of Deep Learning in legal analytics focusing on three main fields; text classification, information extraction, and information retrieval. We focus on the semantic feature representations, a key instrument for the successful application of deep learning in natural language processing. Additionally, we share pre-trained (...) legal word embeddings using the word2vec model over large corpora, comprised legislations from UK, EU, Canada, Australia, USA, and Japan among others. (shrink)

The study examines the need to train future teachers using modern information and communication technologies in the context of adaptation to the aspects of postmodern society. It was found that contemporary postmodern education is impossible without application of information and communication technologies, the use of which gradually leads to changes in the content, the methods and technologies of training future teachers. The analysis of scientific literature, which confirms recognition of ICT as a key technology of the 21st century and (...) the urgency of the problem of development and application of educational technologies capable of modernizing and reforming traditional forms of education in order to meet the level of education of future teachers to the present-day requirements. The current trends of ICT in the training of future teachers in postmodern times are considered, modern practices of ICT use which are the most popular in the educational process of future teachers are singled out. The content of the following compulsory components, according to the authors, of professional training of future teachers, is generalized and concretized: didactic, legal, social and methodological. Discussion issues and perspective directions of future scientific research related to complex ethical contradictions due to uncertainty or lack of necessary knowledge, unexpected effects and insufficient transparency of functioning of information and communication technologies are outlined. (shrink)

Resilience may be referred to as the capacity for positive adaptation and to quickly recover from difficulties and significant adversity. After examining operational definitions of related concepts, the article discusses resilience building exercises for functional fitness at the individual soldier level, to include among others, self-monitoring, self-evaluation, self-reinforcement, emotional regulation exercises, mindfulness training, relaxation and grounding exercises and importance of maintaining discipline and routine in the military. Using an acronym CARRIES, the article examines efforts to enhance resilience building through (...) empirically validated cognitive, behavioural and intrapersonal skills originating from best practices learned in the military. (shrink)

The 1940s and 1950s were marked by intense debates over the origin of drug resistance in microbes. Bacteriologists had traditionally invoked the notions of ‘training’ and ‘adaptation’ to account for the ability of microbes to acquire new traits. As the field of bacterial genetics emerged, however, its participants rejected ‘Lamarckian’ views of microbial heredity, and offered statistical evidence that drug resistance resulted from the selection of random resistant mutants. Antibiotic resistance became a key issue among those disputing physiological vs. (...) genetic explanations of variation in bacteria. Postwar developments connected with the Lysenko affair gave this debate a new political valence.Proponents of the neo-Darwinian synthesis weighed in with support for the genetic theory. However, certain features of drug resistance seemed inexplicable by mutation and selection, particularly the phenomenon of ‘multiple resistance’—the emergence of resistance in a single strain against several unrelated antibiotics. In the late 1950s, Tsutomu Watanabe and his collaborators solved this puzzle by determining that resistance could be conferred by cytoplasmic resistance factors rather than chromosomal mutation. These R factors could carry resistance to many antibiotics and seemed able to promote their own dissemination in bacterial populations. In the end, the vindication of the genetic view of drug resistance was accompanied by a recasting of the ‘gene’ to include extrachromosomal hereditary units carried on viruses and plasmids. (shrink)

Introduction: The present study aimed to investigate the effects of two high-intensity interval training shuttle-run-based models, over ten weeks on aerobic, anaerobic, and neuromuscular parameters, and the association of the training load and heart rate variability with the change in the measures in young futsal players. Methods: Eleven young male futsal players participated in this study. This pre-post study design was performed during a typical 10 weeks training period. HIIT sessions were conducted at 86% and 100% of (...) peak speed of the FIET. Additionally, friendly and official matches, technical-tactical and strength-power training sessions were performed. Before and after the training period, all players performed the FIET, treadmill incremental, repeated sprint ability, sprint 15-m, and vertical jump tests, and the HRV was measured. Training load was monitored using the session rating of perceived effort. Data analysis was carried out using Bayesian inference methods. Results: The HIIT86 model showed clear improvements for the peak oxygen uptake, peak speed in the treadmill incremental test, first and second ventilatory thresholds, RSA best and mean times, CMJ, and SJ. The HIIT100 model presented distinct advances in VO2peak, peak speed in the treadmill incremental test, RSA mean time, and CMJ. Between HIIT models comparisons showed more favorable probabilities of improvement for HIIT86 than HIIT100 model in all parameters. TL data and HIIT models strongly explained the changes in the RSA mean and best times, as well as HRV changes, and HIIT models explained positively VO2peak changes. All other changes in the parameters were low to moderately explained. Conclusion: The HIIT86 proved to be more effective for improving aerobic, RSA, and neuromuscular parameters than HIIT100 during a typical 10-week futsal training period. So, strength and conditioning specialists prescribing shuttle-run intermittent exercises at submaximal intensities can manage the individual acceleration load imposed on athlete increasing or decreasing either the set duration or the frequency of change of direction during HIIT programming. (shrink)

Making adaptive choices between solution strategies is a central element of contemporary mathematics education. However, previous studies signal that students make suboptimal choices between mental and written strategies to solve division problems. In particular, some students of a lower math ability level appear inclined to use mental strategies that lead to lower performance. The current study uses a pretest-training-posttest design to investigate the extent to which these students’ choices for written strategies and performance may be increased. Sixth graders (...) of below-average mathematics level (N = 147) participated in one of two training conditions: an explicit-scaffolding training designed to promote writing down calculations or a practice-only training where strategy use was not explicitly targeted. Written strategy choices and performance increased considerably from pretest to posttest for students in both training conditions, but not in different amounts. Exploratory results suggest that students’ strategy choices may also be affected by their attitudes and beliefs and the sociocultural context regarding strategy use. (shrink)

Metacognitive training (MCT) was developed to promote awareness of reasoning biases among patients with schizophrenia. While MCT has been translated into 31 languages, most MCT studies were conducted in Europe, including newer evidence recommending an individualized approach of delivery. As reasoning biases covered in MCT are separable processes and are associated with different symptoms, testing the effect of selected MCT modules would help to develop a targeted and cost-effective intervention for specific symptoms and associated mechanisms. This study tested the (...) efficacy of a 4-session metacognitive training for delusions, MCTd (in Traditional Chinese with cultural adaptations, provided individually), as an adjunct to antipsychotics in reducing severity and conviction of delusions, jumping to conclusions bias and belief inflexibility. Forty-four patients with delusions were randomized into the MCTd or the wait-list control condition. Patients on wait-list received the same MCTd after four weeks of treatment as usual. Assessment interviews took place before and after the treatment, and at 4-week follow-up. There was an additional baseline assessment for the controls. Jumping to conclusions and belief flexibility were measured by the beads tasks and the Maudsley Assessment of Delusions Scale. Attendance rate of the MCTd was satisfactory (84.5%). Compared to treatment as usual, there was a greater reduction in psychotic symptoms, delusional severity and conviction following MCTd. There was a large treatment effect size in improvement in belief flexibility. Improvement in reaction to hypothetical contradiction predicted treatment effect in positive symptoms and delusions. Jumping to conclusions bias was reduced following MCTd, although the treatment effect was not significantly larger than TAU. Our results support the use of process-based interventions that target psychological mechanisms underlying specific psychotic symptoms as adjuncts to more conventional approach. (shrink)

We demonstrate the relationships between occupational demands in German vocational education and training (VET) teacher training, stress symptoms, and different behavioral resilience competencies. Taking into account interindividual differences in resilience competencies, we use a typological approach to identify different types of (trainee) teachers classified by their degrees and configurations of resilience competencies. Our empirical analysis is based on questionnaire data from 131 German vocational trainees and qualified teachers. The results reveal, among other things, that all three resilience competencies—resistance, (...) flexibility, and dynamism—are significantly negatively correlated with the demands of working conditions and workload. Via a latent class analysis, we were able to identify three groups of (trainee) teachers who differed in their resilience competencies to adapt appropriately to different situations and their requirements (“behavioral flexibility”), to recover rapidly from setbacks and to defy the expectations of others (“behavioral resistance”), and to initiate changes as soon as they are necessary or desirable (“behavioral dynamics”). More resilient (trainee) teachers show, among other things, lower values for anxiety as an emotional stress symptom and higher values for job engagement. The findings are discussed with regard to implications for VET teacher training and we stress the need for equilibration on a systemic perspective. (shrink)

Ethical challenges are traditionally described in a negative light, even though moral conflict can express the individual ability to perceive when something is not working and promote change. The true question, therefore, is not to how to silence moral conflict but how to educate it. Although the need for ethical support of health- and social-care professionals in elderly care is clearly perceived, there is no universal method for providing effective interventions. The authors hypothesize that adequate training sessions can help (...) care professionals enhance this skill, once clear goals and specific educational techniques are set. This research tests the hypothesis on twenty care professionals working in acute and residential care settings for the elderly, building on the ethics round method. Mixed methods drawn from literature and the experience of educators were adapted to meet different educational goals. Moral issues can hardly be removed from a context characterized by increasing demand and decreasing resources, but they can be recognized and addressed with common efforts, a critical attitude, and a growth mindset. Enhancing these skills in qualified workers can help them accept the reality of work, release pressure, and identify common team goals. Introducing these skills before graduation can help future workers avoid unreal expectations and reduce frustration and early job quit rates. (shrink)

Training on working memory (WM) improves attention and working memory in children with attention-deficit hyperactivity disorder and memory impairments. However, for children with intellectual disabilities (ID), the results have been less encouraging. In this preliminary study it was hypothesized that children with ID would benefit from an extended amount of training and that the level of difficulty during training would affect the outcome. We included 21 children with mild or moderate intellectual disabilities aged 8–13 years. They went (...) through between 37 and 50 training sessions with an adaptive computerized program on WM and non-verbal reasoning (NVR). The children were divided into two subgroups with different difficulty levels during training. The transfer to untrained cognitive tests was compared to the results of 22 children with intellectual disabilities training only 25 sessions, and to a control group. We found that the training group with the extended training program improved significantly on a block design task measuring NVR and on a WM task compared to the control group. There was also a significantly larger improvement on block design relative to the training group with the shorter training time. The children that received easier training tasks also improved significantly more on a verbal WM task compared to children with more demanding tasks. In conclusion, these preliminary data suggest that children with ID might benefit from cognitive training with longer training periods and less demanding tasks, compared to children without disabilities. (shrink)

Spam electronic mails (emails) refer to harmful and unwanted commercial emails sent to corporate bodies or individuals to cause harm. Even though such mails are often used for advertising services and products, they sometimes contain links to malware or phishing hosting websites through which private information can be stolen. This study shows how the adaptive intelligent learning approach, based on the visual anti-spam model for multi-natural language, can be used to detect abnormal situations effectively. The application of this approach (...) is for spam filtering. With adaptive intelligent learning, high performance is achieved alongside a low false detection rate. There are three main phases through which the approach functions intelligently to ascertain if an email is legitimate based on the knowledge that has been gathered previously during the course of training. The proposed approach includes two models to identify the phishing emails. The first model has proposed to identify the type of the language. New trainable model based on Naive Bayes classifier has also been proposed. The proposed model is trained on three types of languages (Arabic, English and Chinese) and the trained model has used to identify the language type and use the label for the next model. The second model has been built by using two classes (phishing and normal email for each language) as a training data. The second trained model (Naive Bayes classifier) has been applied to identify the phishing emails as a final decision for the proposed approach. The proposed strategy is implemented using the Java environments and JADE agent platform. The testing of the performance of the AIA learning model involved the use of a dataset that is made up of 2,000 emails, and the results proved the efficiency of the model in accurately detecting and filtering a wide range of spam emails. The results of our study suggest that the Naive Bayes classifier performed ideally when tested on a database that has the biggest estimate (having a general accuracy of 98.4%, false positive rate of 0.08%, and false negative rate of 2.90%). This indicates that our Naive Bayes classifier algorithm will work viably on the off chance, connected to a real-world database, which is more common but not the largest. (shrink)

In the 1930s and 1940s a research school developed among scientists at the Scripps Institution of Oceanography in La Jolla, California. Although that was due in large part to Harald U. Sverdrup, a prominent Norwegian oceanographer who served as Scripps director from 1936 to 1948, this paper emphasizes the adaptive, evolving character of that research school. Conditions at Scripps prior to Sverdrup's arrival influenced his efforts in successfully organizing a group of scientists. Once at Scripps Sverdrup proved to be (...) an able leader, but he also had to adapt to the local scientific culture. Trained in a tradition that emphasized the study of physics, chemistry and meteorology, Sverdrup's emphasis on dynamical oceanography had a powerful impact on his new colleagues. But in the process his understanding of oceanography also evolved. He became more fully aware of the importance of biological and geological investigations, and it was only through close interaction with and reliance on a diverse group of scientists that there emerged an ecological understanding of the oceans that became a hallmark of Scripps oceanography. Emphasizing the importance of adaptation and interaction, and the work of other scientists in addition to a group leader, this paper offers new insights into the formation of research schools. (shrink)

This paper presents a gamified motor imagery brain-computer interface (MI-BCI) training in immersive virtual reality. Aim of the proposed training method is to increase engagement, attention, and motivation in co-adaptive event-driven MI-BCI training. This was achieved using gamification, progressive increase of the training pace, and virtual reality design reinforcing the body ownership transfer (embodiment) into the avatar. From the 20 healthy participants performing 6 runs of 2-class MI-BCI training (left/right hand), 19 were trained for (...) a basic level of MI-BCI operation, with average peak accuracy in the session equal to 75.84\%. This confirms the proposed training method succeeded in improvement of the MI-BCI skills; moreover, participants were leaving the session in high positive affect. Although the performance was not directly correlated to the degree of embodiment, subjective magnitude of the body ownership transfer illusion correlated with the abilities to modulate the sensorimotor rhythm. (shrink)

ObjectiveCOVID-19 caused a complete stop in non-professional sports. The use of face masks for team sports is not a widely used measure in non-professional sports. The study aimed to evaluate the perception about using the mask and the adaptation difficulties related to training and competition in team sports following the FISICOVID-DXTGALEGO protocol.MethodsSeven hundred eighty-seven handball players from the Galician Handball Federation were followed during their return to participation after months of confinement through an electronic questionnaire of perception and experience (...) on the use of a mask.ResultsThere is an excellent adaptation to the mask in training and competition with medium and high correlations. The 86,41% of players reported an adaptation to the mask in 3 weeks with a three times a week training frequency. The negative opinion on the mask was drastically reduced after use. The 80,44% of players considered the use of a mask as an essential measure to resume competitions.ConclusionsIt is very feasible to adapt to training and compete with a mask in a short period. The use of a mask following these protocols changed previous opinions on the disadvantages of the mask during training and competition. (shrink)

This paper implements the continuous Hindi Automatic Speech Recognition (ASR) system using the proposed integrated features vector with Recurrent Neural Network (RNN) based Language Modeling (LM). The proposed system also implements the speaker adaptation using Maximum-Likelihood Linear Regression (MLLR) and Constrained Maximum likelihood Linear Regression (C-MLLR). This system is discriminatively trained by Maximum Mutual Information (MMI) and Minimum Phone Error (MPE) techniques with 256 Gaussian mixture per Hidden Markov Model(HMM) state. The training of the baseline system has been done (...) using a phonetically rich Hindi dataset. The results show that discriminative training enhances the baseline system performance by up to 3%. Further improvement of ~7% has been recorded by applying RNN LM. The proposed Hindi ASR system shows significant performance improvement over other current state-of-the-art techniques. (shrink)

The radical transformations caused by the rapid development of information and communication technologies in the mid-1990s prompted the transition to the knowledge society which identified the key role of knowledge as the most important and valuable capital of organizations and had a decisive impact on the development of corporate training. In our study, we aimed to analyze the training methods used in American companies in the knowledge society, particularly, their feasibility, features, benefits and possible limitations. The results of (...) our study show that, at present, e-learning is considerably more widely used in American companies than instructor-led classroom training. Most organizations use blended learning which implies the combination of e-learning methods and instructor-led learning methods. A powerful stimulus for the wide implementation of e-learning methods was produced by the COVID-19 pandemic when the use of educational technologies made it possible for the companies not only to continue training and development of their employees but also to implement tactical and strategic practices which will have long-term implications for the future of the training industry. The most widely used e-learning methods in American companies are virtual classroom/webcast, online or computer-based methods, social learning, augmented reality, virtual reality, and artificial intelligence. In spite of certain limitations of e-learning methods, they have a number of important benefits which allow companies to expand access to training, save costs, increase adaptability and flexibility of learning programs, etc., and thus satisfy their needs in qualified employees. (shrink)

This paper describes an intelligent algorithm for traffic sign recognition which converges quickly, is accurate in its segmentation and adaptive in its behaviour. The proposed approach can segment images of traffic signs in different lighting and environmental conditions and in different countries. It is based on using Kohonen's Self-Organizing Maps as a clustering tool and it is developed for Intelligent Vehicle applications. The current approach does not need any prior training. Instead, a slight portion, which is about 1% (...) of the image under investigation, is used for training. This is a key issue to ensure fast convergence and high adaptability. The current approach was tested by using 442 images which were collected under different environmental conditions and from different countries. The proposed approach shows promising results; good improvement of 73% is observed in faded traffic sign images compared with 53.3% using the traditional algorithm. The adaptability of the system is evident from the segmentation of the traffic sign images from various countries where the result is 96% for the nine countries included in the test. (shrink)

The aim of the experiment was to evaluate the adaptive responses of biomechanical and electromyographic parameters to vertical unloading when walking during the 4-month isolation experiment SIRIUS-19 in the ground-based space station model. The study involved 6 healthy international crew members of the SIRIUS-19 project aged 34 ± 6.2 years. Body Weight Unloading conditions was created by the h/p/cosmos airwalk system. The locomotor test included walking with a sequential change of BWU modes: 5-min walking with 0% BWU, 5-min walking (...) with 65% BWU and 5-min walking with 85% BWU. Ground Reaction Force was recorded by the h/p/cosmos treadmill device. Muscle Lab Model 4000e device was used to record the electromyographic signals of the hip and shin muscles. The locomotor test was performed twice before GBI, monthly during GBI and 1 week after leaving isolation. The results obtained before GBI demonstrate that the changes of support and proprioceptive afferentation signals play significant role in reorganizing of the biomechanical structure of motor acts and the development of new movement patterns. The results of the study are consistent with the previously obtained results of other studies in this direction. Despite the fact that during the GBI the participants of the experiment performed regular physical training, a decrease in the performance indicators values was detected, especially pronounced after 100 days of GBI. This is probably due to limited space of a space station model, as well as the development of a special motor stereotype in it. Noteworthy are the results obtained after the 4th session of the experiment, indicating the effect of sensorimotor learning. We think that the data obtained in this study will be useful in research both in gravitational physiology and in clinical medicine. (shrink)

The article summarizes the theoretical and methodological knowledge about ecotourism as one of the viable types of tourism in the postmodern era, clarifies the patterns of its formation and development, a variety of approaches to its interpretation, interaction with other types of tourism, features of motivation and management in ecotourism. On the basis of the generalized data a number of perspective educational conditions is modeled: the orientation of the maintenance of pedagogical education on formation of steady positive motivation; updating the (...) content of professional training; availability of educational and methodical support; interrelation of competence, system and personal-activity approaches. Diagnostic methods relevant for postmodern education are selected: methods of diagnosing students' learning motivation; methods of diagnosis of value orientations in career; tests to determine the levels of formation of the components of professional competence. It is proved that the professional training of teachers who are able to use ecological tourism in their professional activities at a high level is one of the important conditions for increasing the interest of children and young people in physical education, tourism and sports, ensuring the necessary physical activity, developing, maintaining and strengthening their health, adaptation to the flexible postmodern society. (shrink)

Most binaural speech source localization models perform poorly in unprecedentedly noisy and reverberant situations. Here, this issue is approached by modelling a multiscale dilated convolutional neural network. The time-related crosscorrelation function and energy-related interaural level differences are preprocessed in separate branches of dilated convolutional network. The multiscale dilated CNN can encode discriminative representations for CCF and ILD, respectively. After encoding, the individual interaural representations are fused to map source direction. Furthermore, in order to improve the parameter adaptation, a novel semiadaptive (...) entropy is proposed to train the network under directional constraints. Experimental results show the proposed method can adaptively locate speech sources in simulated noisy and reverberant environments. (shrink)

ContextBehavioral observation scales are important for understanding and assessing social skills. In the context of collaborative problem-solving skills, considered essential in the 21st century, there are no validated scales in French that can be adapted to different CPS tasks. The aim of this study is to adapt and validate, by annotating a new video corpus of dyadic interactions that we have collected, two observational scales allowing us to qualitatively assess CPS skills: the Social Performance Rating Scale and the Social Skills (...) of Collaboration Scale.MethodThe construct validity of these two scales was assessed by exploratory factor analysis and inter-item correlations. We also checked inter-judge agreement using inter-class correlation coefficients. Internal consistency was determined using Cronbach’s alpha and convergent and divergent validity by assessing correlations between the two scales and measures of depression and alexithymia. Finally, the discriminative properties of the two scales were analyzed by comparing the scores obtained by a group of anxious individuals and a non-anxious control group.ResultsThe results show that our two scales have excellent inter-item correlations. Internal consistency is excellent. Inter-rater agreement ranged from moderate to high. Finally, convergent validity was significant with the alexithymia scale, as was divergent validity with the depression scale. Anxious individuals had lower scores on both scales than non-anxious individuals.ConclusionBoth scales show good psychometric properties for assessing social skills relevant to different collaborative tasks. They also identify individuals with difficulties in social interaction. Thus, they could allow monitoring the effectiveness of training social skills useful in CPS. (shrink)

ObjectiveMost young adults diagnosed with breast or gynecologic cancers experience adverse reproductive or sexual health outcomes due to cancer and its treatment. However, evidence-based interventions that specifically address the RSH concerns of young adult and/or LGBTQ+ survivor couples are lacking. Our goal is to develop a feasible and acceptable couple-based intervention to reduce reproductive and sexual distress experience by young adult breast and gynecologic cancer survivor couples with diverse backgrounds.MethodsWe systematically adapted an empirically supported, theoretically grounded couple-based intervention to address (...) the RSH concerns of young couples coping with breast or gynecologic cancer through integration of stakeholder perspectives. We interviewed 11 couples with a history of breast or gynecologic cancer to review and pretest intervention materials. Three of these couples were invited to review and comment on intervention modifications. Content experts in RSH and dyadic coping, clinicians, and community advisors participated throughout the adaptation process.ResultsFindings confirmed the need for an online, couple-based intervention to support young couples experiencing RSH concerns after breast or gynecologic cancer. Qualitative themes suggested intervention preferences for: A highly flexible intervention that can be tailored to couples’ specific RSH concerns; Active steps to help members of a dyad “get on the same page” in their relationship and family building plans; A specific focus on raising partners’ awareness about how cancer can affect body image and physical intimacy; and Accessible, evidence-based information about RSH for both partners. These results, along with feedback from stakeholders, informed adaptation and finalization of the intervention content and format. The resulting virtual intervention, Opening the Conversation, includes five weekly sessions offering training to couples in communication and dyadic coping skills for addressing RSH concerns.ConclusionThe systematic adaptation process yielded a theory-informed intervention for young adult couples facing breast and gynecological cancers, which will be evaluated in a randomized controlled trial. The long-term goal is to implement and disseminate Opening the Conversation broadly to reach young adult couples with diverse backgrounds who are experiencing RSH concerns in cancer survivorship. (shrink)

In this article, a new adaptive fuzzy wavelet neural network model is proposed for nonlinear function approximation problems. The AFWNN model is based on the traditional Takagi-Sugeno-Kang fuzzy system. Specifically, this model replaces the membership functions of fuzzy rules with wavelet basis functions, which are known to have time and frequency localization properties, i.e., they can approximate patterns both in the time and frequency domains. The structure of the AFWNN model is derived from that of the adaptive neuro-fuzzy (...) inference system. However, the AFWNN improves over the ANFIS by replacing Gaussian functions in the hidden layer with wavelet basis functions. The AFWNN model is trained using a gradient-based optimization algorithm. The AFWNN is then tested on three function approximation problems of time series prediction. For certain types of nonlinear time series, for instance fractal processes, the AFWNN is found to be substantially more accurate than alternative methods. (shrink)

Native language listeners engage in predictive processing in many processing situations and adapt their predictive processing to the statistics of the input. In contrast, second language listeners engage in predictive processing in fewer processing situations. The current study uses eye-tracking data from two experiments in bilinguals’ native language and second language to explore their predictive processing based on contrastive pitch accent cues, and their adaptation in the face of prediction errors. The results of the first experiment show inhibition effects for (...) unpredicted referents in both the L1 and the L2 that can be modeled with a Bayesian adaptation model, suggesting that bilinguals adapt their prediction in the face of prediction errors in a way that is compatible with the model. In contrast, the results of the second experiment, after a training phase that increased the predictive validity of the cue, show inhibition effects for unpredicted referents only in the L1, but not in the L2. In addition, the Bayesian adaptation model significantly predicts only the L1, but not the L2 data. The results are discussed with respect to adaptation to the statistical properties of the input. (shrink)

Social scientists and computer scientist are divided by small differences in perspective and not by any significant disciplinary divide. In the field of text analysis, several such differences are noted: social scientists often use unsupervised models to explore corpora, whereas many computer scientists employ supervised models to train data; social scientists hold to more conventional causal notions than do most computer scientists, and often favor intense exploitation of existing algorithms, whereas computer scientists focus more on developing new models; and computer (...) scientists tend to trust human judgment more than social scientists do. These differences have implications that potentially can improve the practice of social science. (shrink)

This paper firstly designs a five-dimensional model of learners’ characteristics and a three-dimensional model of English reading resources’ characteristics in a fragmented learning environment through literature research. At the same time, to make the learning resources meet the characteristics of fragmented learning time and space, the English Level 4 reading resources are reasonably designed and segmented to adapt to the needs of learners’ mobile fragmented learning. Then, combined with machine learning algorithms, an adaptive recommendation model of learning resources in (...) English fragmented reading is constructed. The algorithm-based adaptive recommendation algorithm for English fragmented reading resources is designed. Based on the generated decision trees, the expression rules are parsed to achieve adaptive pushing of resources. The results of this study show that adaptive recommendation of learning resources in English fragmented reading can help teachers to develop future resource recommendation strategies through effective data collection to adaptively push resources that are close to learners’ individual needs. The use of mobile by English learners to learn to read in a fragmented learning context enables targeted training in weak areas of English reading, thus enhancing different aspects of learners’ reading skills. (shrink)

GoalThis paper presents an immersive Virtual Reality system to analyze and train Executive Functions of soccer players. EFs are important cognitive functions for athletes. They are a relevant quality that distinguishes amateurs from professionals.MethodThe system is based on immersive technology, hence, the user interacts naturally and experiences a training session in a virtual world. The proposed system has a modular design supporting the extension of various so-called game modes. Game modes combine selected game mechanics with specific simulation content to (...) target particular training aspects. The system architecture decouples selection/parameterization and analysis of training sessions via a coaching app from an Unity3D-based VR simulation core. Monitoring of user performance and progress is recorded by a database that sends the necessary feedback to the coaching app for analysis.ResultsThe system is tested for VR-critical performance criteria to reveal the usefulness of a new interaction paradigm in the cognitive training and analysis of EFs. Subjective ratings for overall usability show that the design as VR application enhances the user experience compared to a traditional desktop app; whereas the new, unfamiliar interaction paradigm does not negatively impact the effort for using the application.ConclusionThe system can provide immersive training of EF in a fully virtual environment, eliminating potential distraction. It further provides an easy-to-use analyzes tool to compare user but also an automatic, adaptive training mode. (shrink)

Adaptation can optimize information processing by allowing the visual system to always adjust to the environment. However, only a few studies have investigated how the visual system makes adjustments to repeatedly occurring changes in the input, still less about the related neural mechanism. Our previous study found that contrast adaptation attenuated after multiple daily sessions of repeated adaptation, which was explained by the habituation of either the adapter’s effective strength or the adaptation mechanisms. To examine the former hypothesis, in the (...) present study we used the frequency tagging technique to measure the adapter-elicited steady-state visual evoked potential amplitudes. Participants repeatedly adapted to the same contrast adapter in a top-up manner for six continuous days, which was called training of adaptation. The behavioral adaptation effect and SSVEP response to the trained adapter and an untrained control adapter were measured before and after training. The psychophysical results showed that the effect of adaptation in the trained condition significantly reduced after training, replicating our previous finding. Contradicting the prediction of the hypothesis that repeated adaptation attenuated the effective strength of the adapter, the SSVEP amplitude was unchanged after training, which was further confirmed by an equivalence test. Taken together, the results challenge the account of habituation of adapter in repeated adaptation, while leaving the account of habituation of adaptation mechanism to be tested. (shrink)