According to the similarity-attraction theory, humans respond more positively to people who are similar in personality. This observation also holds true between humans and robots, as shown by recent studies that examined human-robot interactions. Thus, it would be conducive for robots to be able to capture the user personality and adjust the interactional patterns accordingly. The present study is intended to identify significant speech characteristics such as sound and lexical features between the two different personality groups (introverts vs. extroverts), so that a robot can distinguish a user's personality by observing specific speech characteristics. Twenty-four male participants took the Myers-Briggs Type Indicator (MBTI) test for personality screening. The speech data of those participants (identified as 12 introvertive males and 12 extroversive males through the MBTI test) were recorded while they were verbally responding to the eight Walk-in-the-Wood questions. After that, speech, sound, and lexical features were extracted. Averaged reaction time (1.200 s for introversive and 0.762 s for extroversive; p = 0.01) and total reaction time (9.39 s for introversive and 6.10 s for extroversive; p = 0.008) showed significant differences between the two groups. However, averaged pitch frequency, sound power, and lexical features did not show significant differences between the two groups. A binary logistic regression developed to classify two different personalities showed 70.8% of classification accuracy. Significant speech features between introversive and extroversive individuals have been identified, and a personality classification model has been developed. The identified features would be applicable for designing or programming a social robot to promote human-robot interaction by matching the robot's behaviors toward a user's personality estimated.Notch3 is one of four mammalian Notch proteins, which act as signalling receptors to control cell fate in many developmental and adult tissue contexts. Notch signalling continues to be important in the adult organism for tissue maintenance and renewal and mis-regulation of Notch is involved in many diseases. Genetic studies have shown that Notch3 gene knockouts are viable and have limited developmental defects, focussed mostly on defects in the arterial smooth muscle cell lineage. Additional studies have revealed overlapping roles for Notch3 with other Notch proteins, which widen the range of developmental functions. In the adult, Notch3, in collaboration with other Notch proteins, is involved in stem cell regulation in different tissues in stem cell regulation in different tissues, and it also controls the plasticity of the vascular smooth muscle phenotype involved in arterial vessel remodelling. Overexpression, gene amplification and mis-activation of Notch3 are associated with different cancers, in particular triple negative breast cancer and ovarian cancer. Mutations of Notch3 are associated with a dominantly inherited disease CADASIL (cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy), and there is further evidence linking Notch3 misregulation to hypertensive disease. Here we discuss the distinctive roles of Notch3 in development, health and disease, different views as to the underlying mechanisms of its activation and misregulation in different contexts and potential for therapeutic intervention.The quick sepsis-related organ failure assessment (qSOFA) score has been introduced to predict the likelihood of organ dysfunction in patients with suspected infection. We hypothesized that machine-learning models using qSOFA variables for predicting three-day mortality would provide better accuracy than the qSOFA score in the emergency department (ED). Between January 2016 and December 2018, the medical records of patients aged over 18 years with suspected infection were retrospectively obtained from four EDs in Korea. Data from three hospitals (n = 19,353) were used as training-validation datasets and data from one (n = 4234) as the test dataset.  https://www.selleckchem.com/products/gs-9973.html  Machine-learning algorithms including extreme gradient boosting, light gradient boosting machine, and random forest were used. We assessed the prediction ability of machine-learning models using the area under the receiver operating characteristic (AUROC) curve, and DeLong's test was used to compare AUROCs between the qSOFA scores and qSOFA-based machine-learning models. A total of 447,926 patients visited EDs during the study period. We analyzed 23,587 patients with suspected infection who were admitted to the EDs. The median age of the patients was 63 years (interquartile range 43-78 years) and in-hospital mortality was 4.0% (n = 941). For predicting three-day mortality among patients with suspected infection in the ED, the AUROC of the qSOFA-based machine-learning model (0.86 [95% CI 0.85-0.87]) for three -day mortality was higher than that of the qSOFA scores (0.78 [95% CI 0.77-0.79], p less then 0.001). For predicting three-day mortality in patients with suspected infection in the ED, the qSOFA-based machine-learning model was found to be superior to the conventional qSOFA scores.Phosphorus transporter (PHT) genes encode H2PO4-/H+ co-transporters that absorb and transport inorganic nutrient elements required for plant development and growth and protect plants from heavy metal stress. However, little is known about the roles of PHTs in Brassica compared to Arabidopsis thaliana. In this study, we identified and extensively analyzed 336 PHTs from three diploid (B. rapa, B. oleracea, and B. nigra) and two allotetraploid (B. juncea and B. napus) Brassica species. We categorized the PHTs into five phylogenetic clusters (PHT1-PHT5), including 201 PHT1 homologs, 15 PHT2 homologs, 40 PHT3 homologs, 54 PHT4 homologs, and 26 PHT5 homologs, which are unevenly distributed on the corresponding chromosomes of the five Brassica species. All PHT family genes from Brassica are more closely related to Arabidopsis PHTs in the same vs. other clusters, suggesting they are highly conserved and have similar functions. Duplication and synteny analysis revealed that segmental and tandem duplications led to the expansion of the PHT gene family during the process of polyploidization and that members of this family have undergone purifying selection during evolution based on Ka/Ks values.