Probabilistic harm does not increase selfish behavior in a bribe-taking laboratory task

Negative consequences of dishonest behavior prevent people from breaking rules for selfish gains. However, harm caused by many kinds of dishonest behavior is uncertain. In the present study, we let participants to break rules in a sorting task in order to increase their rewards while simultaneously harming a third party, simulating a bribe-taking. We varied the probability with which the harm occurred while keeping the expected size of harm constant across experimental conditions. We found that uncertainty of negative consequences of corrupt behavior had no effect on bribe-taking.

Sentimental Tweets Classification of Symptomatic COVID 19

The approach I described is straightforward, related to COVID-19 SARS based tweets and the symptoms, that people tweet about. Also, social media mining for health application reports was shared in many different tasks of 2021. The motto at the back of this observe is to analyses tweets of COVID-19 based symptoms. By performing BERT model and text classification with XLNET with which uses to classify text and purpose of the texts (i.e.) tweets. So that I can get a deep understanding of the texts. When developing the system, I used two models the XLNet and DistilBERT for the text sorting task, but the outcome was XLNET out-performs the given approach to the best accuracy achieved. Now I discover a whole lot vital for as it should be categorizing tweets as encompassing self-said COVID-19 indications. Whether or not a tweets associated with COVID-19 is a non-public report or an information point out to the virus. Which gives test accuracy to an F1 score of 96%.

Impact of two yeast strains on Tempranillo red wine aroma profiles throughout accelerated ageing

This study aimed at determining the changes induced by two S. cerevisiae strains, (IONYS wf™ and Lalvin ICV D254™) on the sensory and chemical aroma profiles of Tempranillo wine, after fermentation and after ageing. The 64 aroma molecules determined were grouped attending to sensory and chemical similarity into 17 aroma vectors. Sensory studies included a sorting task and a descriptive analysis by flash profile with a trained panel. Results revealed that, even if ageing is the dominant factor, the strain of yeast introduces significant and consistent differences, both in sensory and aroma vector profiles (11 out of 17 affected). Wines made with D254 contained higher levels of ethyl esters, acetic acid, cinnamates and ethyl acetate and lower levels of linear fatty acids, β-damascenone, acetaldehyde, higher alcohols and lactones than those made with IONYS. The first profile was related to black and fresh fruit notes, while the second to white and compote fruits.

Effects of Inositol-Enhanced Bonded Arginine Silicate Ingestion on Cognitive and Executive Function in Gamers

Inositol stabilized arginine silicate (ASI) ingestion has been reported to increase nitric oxide levels while inositol (I) has been reported to enhance neurotransmission. The current study examined whether acute ASI + I (Inositol-enhanced bonded arginine silicate) ingestion affects cognitive function in e-sport gamers. In a double blind, randomized, placebo controlled, and crossover trial, 26 healthy male (n = 18) and female (n = 8) experienced gamers (23 ± 5 years, 171 ± 11 cm, 71.1 ± 14 kg, 20.7 ± 3.5 kg/m2) were randomly assigned to consume 1600 mg of ASI + I (nooLVL®, Nutrition 21) or 1600 mg of a maltodextrin placebo (PLA). Prior to testing, participants recorded their diet, refrained from consuming atypical amounts of stimulants and foods high in arginine and nitrates, and fasted for 8 h. During testing sessions, participants completed stimulant sensitivity questionnaires and performed cognitive function tests (i.e., Berg-Wisconsin Card Sorting task test, Go/No-Go test, Sternberg Task Test, Psychomotor Vigilance Task Test, Cambridge Brain Sciences Reasoning and Concentration test) and a light reaction test. Participants then ingested treatments in a randomized manner. Fifteen minutes following ingestion, participants repeated tests (Pre-Game). Participants then played their favorite video game for 1-h and repeated the battery of tests (Post-Game). Participants observed a 7–14-day washout period and then replicated the study with the alternative treatment. Data were analyzed by General Linear Model (GLM) univariate analyses with repeated measures using weight as a covariate, paired t-tests (not adjusted to weight), and mean changes from baseline with 95% Confidence Intervals (CI). Pairwise comparison revealed that there was a significant improvement in Sternberg Mean Present Reaction Time (ASI + I vs. PLA; p < 0.05). In Post-Game assessments, 4-letter Absent Reaction Time (p < 0.05), 6-letter Present Reaction Time (p < 0.01), 6-letter Absent Reaction Time (p < 0.01), Mean Present Reaction Time (p < 0.02), and Mean Absent Reaction Time (p < 0.03) were improved with ASI + I vs. PLA. There was a non-significant trend in Pre-Game Sternberg 4-letter Present Reaction time in ASI + I vs. PLA (p < 0.07). ASI + I ingestion better maintained changes in Go/No-Go Mean Accuracy and Reaction Time, Psychomotor Vigilance Task Reaction Time, and Cambridge Post-Game Visio-spatial Processing and Planning. Results provide evidence that ASI + I ingestion prior to playing video games may enhance some measures of short-term and working memory, reaction time, reasoning, and concentration in experienced gamers.

Roles of verb and construction cues

This study investigates how speakers of English and Korean, two typologically distinct languages, derive information from a verb and a construction to achieve sentence comprehension. In a sentence-sorting task, we manipulated verb semantics (real versus nonce) in each language. The results showed that participants from both languages were less inclined to sort sentences by a verb cue when the lexical-semantic information about a verb was obscured (i.e., nonce verb). In addition, the Korean-speaking participants were less likely affected by the verb semantics conditions than the English-speaking participants. These findings suggest the role of an argument structure construction in sentence comprehension as a co-contributor of sentence meaning, supporting the constructionist approach. The findings also imply language-specific mechanisms of sentence comprehension, contingent upon the varied impact of a verb on sentence meaning in English and Korean.

Optimization of Machine Online Translation System Based on Deep Convolution Neural Network Algorithm

In order to effectively optimize the machine online translation system and improve its translation efficiency and translation quality, this study uses the deep separable convolution neural network algorithm to construct a machine online translation model and evaluates the quality on the basis of pseudo data learning. In order to verify the performance of the model, the regression performance experiment of the model, the method performance experiment of generating pseudo data for specific tasks, the sorting task performance experiment of the model, and the machine translation quality comparison experiment are designed. RMSE and MAE were used to evaluate the regression task performance of the model. Spearman rank correlation coefficient and delta AVG value were used to evaluate the sorting task performance of the model. The experimental results show that the MAE and RMSE values of the model are decreased by 2.28% and 1.39%, respectively, compared with the baseline system under the same experimental conditions, and the Spearman and delta AVG values are increased by 132% and 100.7%, respectively, compared with the baseline system. The method of generating pseudo data for specific tasks needs less data and can make the translation system reach a better level faster. When the number of instances is more than 10, the quality score of the model output is higher than that of Google translation whose similarity is more than 0.8.

Drivers Glance Like Lizards during Cell Phone Distraction in Assisted Driving

Head pose has been proposed as a surrogate for eye movement to predict areas of interest (AOIs) where drivers allocate their attention. However, head pose may disassociate with AOIs in glance behavior involving zero or subtle head movements, commonly known as “lizard” glance pattern. In contrast, “owl” glance pattern is used to describe glance behavior along with larger head movements. It remains unclear which glance pattern is prevalent during driver cell phone distraction and what are appropriate metrics to detect such distraction. To address this gap, we analyzed the gaze direction and head pose of 36 participants who completed an email-sorting task using a cell phone while driving a Tesla on the test track in Autopilot mode. The dispersion-threshold algorithm identified driver gaze fixations and synchronized them with head movements. The results showed that when using a cell phone either near the lap or behind the steering wheel, participants exhibited a dominant lizard-type glance pattern with minimal shift in head position. As a result, head pose alone may not provide sufficient information for cell phone distraction detection, and gaze metrics should be involved in enhancing this application.

Robot Manipulator Control with Inverse Kinematics PD-Pseudoinverse Jacobian and Forward Kinematics Denavit Hartenberg

This paper presents the development of vision-based robotic arm manipulator control by applying Proportional Derivative-Pseudoinverse Jacobian (PD-PIJ) kinematics and Denavit Hartenberg forward kinematics. The task of sorting objects based on color is carried out to observe error propagation in the implementation of manipulator on real system. The objects image captured by the digital camera were processed based on HSV-color model and the centroid coordinate of each object detected were calculated. These coordinates are end effector position target to pick each object and were placed to the right position based on its color. Based on the end effector position target, PD-PIJ inverse kinematics method was used to determine the right angle of each joint of manipulator links. The angles found by PD-PIJ is the input of DH forward kinematics. The process was repeated until the square end effector reached the target. The experiment of model and implementation to actual manipulator were analyzed using Probability Density Function (PDF) and Weibull Probability Distribution. The result shows that the manipulator navigation system had a good performance. The real implementation of color sorting task on manipulator shows the probability of success rate cm is 94.46% for euclidian distance error less than 1.2 cm.