Semantic Verbal Fluency in Youth with Down Syndrome: Analysis of Conventional and Contextual Cluster Formation

Expressive language delays and executive functioning challenges are common in youth with Down syndrome (DS). Verbal fluency is one method to investigate these constructs. We examined semantic verbal fluency responses to determine patterns in response generation and the psychometric properties of coded cluster formations. Participants were 97 children and adolescents with DS ranging in age from 6 to 19 years old. The semantic verbal fluency task was administered at two time points, two weeks apart. Heterogeneity in performance was observed for responses when coded either with conventional or contextual classifications. Overall, the number of switches in conventional classifications was greater than contextual classifications. This implies that participants did not use traditional (conventional) categories to organize their semantic verbal fluency responses, but may have been using contextual strategies. However, the number of switches and cluster size variables had poor to moderate test–retest reliability, which indicated that participants did not stay consistent with their performance over the two-week testing interval, regardless of the strategies used. Therefore, conventional and contextual clusters and switches as a measure of executive control may not be appropriate for all individuals with DS and additional attention is warranted to determine the utility of response coding in this population.

Classifying clinically actionable genetic mutations using KNN and SVM

Cancer is one of the major causes of death in humans. Early diagnosis of genetic mutations that cause cancer tumor growth leads to personalized medicine to the decease and can save the life of majority of patients. With this aim, Kaggle has conducted a competition to classify clinically actionable gene mutations based on clinical evidence and some other features related to gene mutations. The dataset contains 3321 training data points that can be classified into 9 classes. In this work, an attempt is made to classify these data points using K-nearest neighbors (KNN) and linear support vector machines (SVM) in a multi class environment. As the features are categorical, one hot encoding as well as response coding are applied to make them suitable to the classifiers. The prediction performance is evaluated using log loss and KNN has performed better with a log loss value of 1.10 compared to that of SVM 1.24.

Production of nitrogen-doped carbon quantum dots with controllable emission wavelength, excellent sensing of Fe3+ in aqueous solution, and potential application for stealth quick response coding in the visible regime

Carbon quantum dots have received attention due to their environmental friendliness, low biological toxicity and production cost. Polymer–CQD composite fibers, detection of Fe3+, and stealthy fluorescent labels made by thermal transfer printing are potential applications.

Spatial–numerical associations in the presence of an avatar

When we interact with other people or avatars, they often provide an alternative spatial frame of reference compared to our own. Previous studies introduced avatars into stimulus–response compatibility tasks and demonstrated compatibility effects as if the participant was viewing the task from the avatar’s point of view. However, the origin of this effect of perspective taking remained unclear. To distinguish changes in stimulus coding from changes in response coding, caused by the avatar, two experiments were conducted that combined a SNARC task and a spontaneous visual perspective taking task to specify the role of response coding. We observed compatibility effects that were based on the avatar’s perspective rather than the participants’ own. Because number magnitude was independent of the avatar’s perspective, the observed changes in compatibility caused by different perspectives indicate changes in response coding. These changes in response coding are only significant when they are accompanied by visual action effects.

Development and Validation of an Interdisciplinary Worker’s Health Approach Instrument (IWHAI)

The present study aimed to develop and validate an Interdisciplinary Worker’s Health Approach Instrument (IWHAI). The development stage comprised a group of 10 professionals, including physicians, nurses, nutritionists, dentists and physical educators, as well as a judges’ committee, composed by 19 recognized experts in the area of worker’s health (WH). For the validation of the IWHAI, the Spearman’s correlation coefficient (rs) was calculated, the factor analysis to the instrument was applied, and the Cronbach’s alpha (α) and the Intraclass correlation coefficient (ICC) were calculated. The IWHAI was structured in five dimensions, integrating 43 health indicators, on a scale of 0–4, totalling 215 sub-indices with closed response coding. The instrument was validated with a Kappa coefficient (KAPPA) (k), with excellent agreement for all attributes, i.e., k = 0.88 for applicability, k = 0.80 for clarity and k = 0.82 for relevance. p > 0.05 results reveal moderate to strong positive correlations between some variables, i.e., pests, vectors and air quality/drinking water quality (rs = 0.69). A total of 14 components of the factor analysis, explaining 62.6% of the data variance, were extracted. α value is considered moderate to high, α = 0.61, the ICC value also being considered moderate to high, with ICC = 0.61. The IWHAI is considered validated, constituting a technological innovation for an interdisciplinary approach in the field of WH, enabling the prevention and integral promotion of health.

Autocorrelation Structure in the Macaque Dorsolateral, But not Orbital or Polar, Prefrontal Cortex Predicts Response-Coding Strength in a Visually Cued Strategy Task

In previous work, we studied the activity of neurons in the dorsolateral (PFdl), orbital (PFo), and polar (PFp) prefrontal cortex while monkeys performed a strategy task with 2 spatial goals. A cue instructed 1 of 2 strategies in each trial: stay with the previous goal or shift to the alternative goal. Each trial started with a fixation period, followed by a cue. Subsequently, a delay period was followed by a “go” signal that instructed the monkeys to choose one goal. After each choice, feedback was provided. In this study, we focused on the temporal receptive fields of the neurons, as measured by the decay in autocorrelation (time constant) during the fixation period, and examined the relationship with response and strategy coding. The temporal receptive field in PFdl correlated with the response-related but not with the strategy-related modulation in the delay and the feedback periods: neurons with longer time constants in PFdl tended to show stronger and more prolonged response coding. No such correlation was found in PFp or PFo. These findings demonstrate that the temporal specialization of neurons for temporally extended computations is predictive of response coding, and neurons in PFdl, but not PFp or PFo, develop such predictive properties.