Hope, exploration, and equilibrated action schemes

2019 ◽  
Vol 42 ◽  
Author(s):  
Davood G. Gozli ◽  
Ci Jun Gao
Keyword(s):  
Single Type ◽  
Reward Seeking ◽  
Stable Scheme

AbstractThe concepts want, hope, and exploration cannot be organized in relation to a single type of motive (e.g., motive for food). They require, in addition, the motive for acquiring and maintaining a stable scheme that enables reward-directed activity. Facing unpredictability, the animal has to seek not only reward, but also a new equilibrated state within which reward seeking is possible.

A Multifactorial Conceptualization of Impulsivity

2015 ◽  
Vol 36 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Bojana Knezevic-Budisin ◽  
Vanessa Pedden ◽  
Andrew White ◽  
Carlin J. Miller ◽  
Peter N. S. Hoaken
Keyword(s):  
Sensation Seeking ◽  
Adult Adhd ◽  
Principal Component ◽  
Executive Dysfunction ◽  
Single Type ◽  
Control Factor ◽  
Behavioral Measures ◽  
Organizational Skills ◽  
Reward Seeking ◽  
Two Samples

Abstract. Despite the multiple phenotypic presentations of impulsivity, the underlying factor structure of the construct has yet to be settled. The aim of this study, with two multimethod, multisource datasets, was to further explore the multifactorial nature of impulsivity and propose a measure-selection approach. Unlike previous studies that relied on a single type of statistical analysis, the current study explored the relations between personality and behavioral measures of impulsivity utilizing exploratory factor analysis (EFA) and principal component analysis (PCA). Participants comprised two samples of young adults (n(study 1) = 175 and n(study 2) = 118) from separate communities in southwestern Ontario, Canada. Various facets of impulsivity were assessed including adult ADHD symptoms, planning and organizational skills, executive dysfunction, impulsive personality traits (i.e., sensation-seeking), risk-taking behavior, disinhibition, cognitive flexibility, and delay discounting. Both statistical analyses yielded two-factor models. The Dysexecutive Control factor reflected a tendency to act without thinking or planning, and difficulty focusing for a sustained period of time. The Reward-Seeking factor reflected a general need for excitement, and a preference for novel situations despite adverse consequences. For the purposes of standardized assessment of cognitive, emotional, and behavioral manifestations of impulsivity, trans-theoretical measure selection for research and clinical purposes is discussed.

Microscopic Structure of Er-Related Optically Active Centers in Si

2003 ◽  
Vol 770 ◽  
Author(s):  
H. Przybylinska ◽  
N. Q. Vinh ◽  
B.A. Andreev ◽  
Z. F. Krasil'nik ◽  
T. Gregorkiewicz
Keyword(s):  
Ground State ◽  
Photoluminescence Spectrum ◽  
Zeeman Effect ◽  
Optically Active ◽  
Single Type ◽  
Active Centers ◽  
Mbe Growth ◽  
Spectral Components ◽  
Er Doped ◽  
Successful Observation

AbstractA successful observation and analysis of the Zeeman effect on the near 1.54 μm photoluminescence spectrum in Er-doped crystalline MBE-grown silicon are reported. A clearly resolved splitting of 5 major spectral components was observed in magnetic fields up to 5.5 T. Based on the analysis of the data the symmetry of the dominant optically active center was conclusively established as orthorhombic I (C2v), with g‼≈18.4 and g⊥≈0 in the ground state. The fact that g⊥≈0 explains why EPR detection of Er-related optically active centers in silicon may be difficult. Preferential generation of a single type of an optically active Er-related center in MBE growth confirmed in this study is essential for photonic applications of Si:Er.

Prediction of Nitration Sites Based on FCBF Method and Stacking Ensemble Model

2021 ◽  
Vol 18 ◽  
Author(s):  
Min Liu ◽  
Lu Zhang ◽  
Xinyi Qin ◽  
Tao Huang ◽  
Ziwei Xu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Protein Sequence ◽  
Cross Validation ◽  
Transplant Rejection ◽  
Sampling Technique ◽  
Single Type ◽  
Post Translational Modification ◽  
Tyrosine Residues ◽  
Under Sampling ◽  
Fusion Features

Background: Nitration is one of the important Post-Translational Modification (PTM) occurring on the tyrosine residues of proteins. The occurrence of protein tyrosine nitration under disease conditions is inevitable and represents a shift from the signal transducing physiological actions of -NO to oxidative and potentially pathogenic pathways. Abnormal protein nitration modification can lead to serious human diseases, including neurodegenerative diseases, acute respiratory distress, organ transplant rejection and lung cancer. Objective: It is necessary and important to identify the nitration sites in protein sequences. Predicting that which tyrosine residues in the protein sequence are nitrated and which are not is of great significance for the study of nitration mechanism and related diseases. Methods: In this study, a prediction model of nitration sites based on the over-under sampling strategy and the FCBF method was proposed by stacking ensemble learning and fusing multiple features. Firstly, the protein sequence sample was encoded by 2701-dimensional fusion features (PseAAC, PSSM, AAIndex, CKSAAP, Disorder). Secondly, the ranked feature set was generated by the FCBF method according to the symmetric uncertainty metric. Thirdly, in the process of model training, use the over- and under- sampling technique was used to tackle the imbalanced dataset. Finally, the Incremental Feature Selection (IFS) method was adopted to extract an optimal classifier based on 10-fold cross-validation. Results and Conclusion: Results show that the model has significant performance advantages in indicators such as MCC, Recall and F1-score, no matter in what way the comparison was conducted with other classifiers on the independent test set, or made by cross-validation with single-type feature or with fusion-features on the training set. By integrating the FCBF feature ranking methods, over- and under- sampling technique and a stacking model composed of multiple base classifiers, an effective prediction model for nitration PTM sites was build, which can achieve a better recall rate when the ratio of positive and negative samples is highly imbalanced.

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