Cognitive Control in Majority Search: A Computational Modeling Approach

Despite the importance of cognitive control in many cognitive tasks involving uncertainty, the computational mechanisms of cognitive control in response to uncertainty remain unclear. In this study, we develop biologically realistic neural network models to investigate the instantiation of cognitive control in a majority function task, where one determines the category to which the majority of items in a group belong. Two models are constructed, both of which include the same set of modules representing task-relevant brain functions and share the same model structure. However, with a critical change of a model parameter setting, the two models implement two different underlying algorithms: one for grouping search (where a subgroup of items are sampled and re-sampled until a congruent sample is found) and the other for self-terminating search (where the items are scanned and counted one-by-one until the majority is decided). The two algorithms hold distinct implications for the involvement of cognitive control. The modeling results show that while both models are able to perform the task, the grouping search model fit the human data better than the self-terminating search model. An examination of the dynamics underlying model performance reveals how cognitive control might be instantiated in the brain for computing the majority function

Observer design based on nonlinear suspension model with unscented Kalman filter

This paper presents a new approach to estimating suspension state information and parameter in real-time. An observer with unscented Kalman filter is designed based on a nonlinear quarter car model. The proposed observer could estimate the sprung mass, vertical velocity of sprung and unsprung mass for the nonlinear suspension systems with vehicle load variation. The designed observer has low sensitivity and robust to unknown road surfaces. The efficiency of the estimator is validated through the simulations with two different types of road excitation and payload variations. The simulation results clearly indicate that compared with the extended Kalman filter estimator, the unscented Kalman filter is more accurate and robust. The estimated state information and parameters could be used in the design of suspension control systems

A New Comparative Definition of Community and Corresponding Identifying Algorithm

In this paper, a new comparative definition for community in networks is proposed and the corresponding detecting algorithm is given. A community is defined as a set of nodes, which satisfy that each node's degree inside the community should not be smaller than the node's degree toward any other community. In the algorithm, the attractive force of a community to a node is defined as the connections between them. Then employing attractive force based self-organizing process, without any extra parameter, the best communities can be detected. Several artificial and real-world networks, including Zachary Karate club network and College football network are analyzed. The algorithm works well in detecting communities and it also gives a nice description for network division and group formation.Comment: 11 pages, 4 fihure

Genetic Relationships of Ethnic Minorities in Southwest China Revealed by Microsatellite Markers

Population migrations in Southwest and South China have played an important role in the formation of East Asian populations and led to a high degree of cultural diversity among ethnic minorities living in these areas. To explore the genetic relationships of these ethnic minorities, we systematically surveyed the variation of 10 autosomal STR markers of 1,538 individuals from 30 populations of 25 ethnic minorities, of which the majority were chosen from Southwest China, especially Yunnan Province. With genotyped data of the markers, we constructed phylogenies of these populations with both DA and DC measures and performed a principal component analysis, as well as a clustering analysis by structure. Results showed that we successfully recovered the genetic structure of analyzed populations formed by historical migrations. Aggregation patterns of these populations accord well with their linguistic affiliations, suggesting that deciphering of genetic relationships does in fact offer clues for study of ethnic differentiation

An Hα\alpha Imaging Survey of the Low-surface-brightness Galaxies Selected from the Fall Sky Region of the 40%\% ALFALFA \ion{H}{1} Survey

We present the observed H$\alpha$ flux and derived star formation rates (SFRs) for a fall sample of low$-$surface$-$brightness galaxies (LSBGs). The sample is selected from the fall sky region of the 40$\%$ ALFALFA {\ion{H}{1}} survey $-$ SDSS DR7 photometric data, and all the $H\alpha$ images were obtained using the 2.16 m telescope, operated by the National Astronomy Observatories, Chinese Academy of Sciences. A total of 111 LSBGs were observed and $H\alpha$ flux was measured in 92 of them. Though almost all the LSBGs in our sample are {\ion{H}{1}}$-$rich, their SFRs derived from the extinction and filter$-$transmission$-$corrected $H\alpha$ flux, are less than 1M_{\sun}$yr^{-1}$. LSBGs and star forming galaxies have similar {\ion{H}{1}} surface densities, but LSBGs have much lower SFRs and SFR surface densities than star$-$forming galaxies. Our results show that LSBGs deviate from the Kennicutt-Schmidt law significantly, which indicate that they have low star formation efficiency. The SFRs of LSBGs are close to average SFRs in Hubble time and support the previous arguments that most of the LSBGs are stable systems and they tend to seldom contain strong interactions or major mergers during their star formation histories

An Hα\alpha Imaging Survey of the Low-surface-brightness Galaxies Selected from the Fall Sky Region of the 40%\% ALFALFA \ion{H}{1} Survey

We present the observed H$\alpha$ flux and derived star formation rates (SFRs) for a fall sample of low$-$surface$-$brightness galaxies (LSBGs). The sample is selected from the fall sky region of the 40$\%$ ALFALFA {\ion{H}{1}} survey $-$ SDSS DR7 photometric data, and all the $H\alpha$ images were obtained using the 2.16 m telescope, operated by the National Astronomy Observatories, Chinese Academy of Sciences. A total of 111 LSBGs were observed and $H\alpha$ flux was measured in 92 of them. Though almost all the LSBGs in our sample are {\ion{H}{1}}$-$rich, their SFRs derived from the extinction and filter$-$transmission$-$corrected $H\alpha$ flux, are less than 1M_{\sun}$yr^{-1}$. LSBGs and star forming galaxies have similar {\ion{H}{1}} surface densities, but LSBGs have much lower SFRs and SFR surface densities than star$-$forming galaxies. Our results show that LSBGs deviate from the Kennicutt-Schmidt law significantly, which indicate that they have low star formation efficiency. The SFRs of LSBGs are close to average SFRs in Hubble time and support the previous arguments that most of the LSBGs are stable systems and they tend to seldom contain strong interactions or major mergers during their star formation histories

Searching for the Majority: Algorithms of Voluntary Control

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search). The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations

Isolation and identification of Tete virus group (Peribunyaviridae: Orthobunyavirus) from Culicoides biting midges collected in Lichuan County, China

In July 2018, a virus (JXLC1806-2) was isolated from Culicoides biting midges collected in Lichuan County, Jiangxi Province, China. The virus isolate showed significant cytopathic effects within 48 hours after inoculation with mammalian cells (BHK-21). JXLC1806-2 virus could form plaques in BHK-21 cells, and the virus titer was 1×105.6 pfu/mL. After inoculation with the virus, suckling mice developed disease and died. The nucleotide and amino sequence analysis showed that the JXLC1806-2 virus genome was composed of S, M and L segments. Phylogenetic analysis showed that the S, M and L genes of JXLC1806-2 virus belonged to the Tete serogroup, Orthobunyavirus, but formed an independent evolutionary branch from the other members of the Tete serogroup. The results showed that the JXLC1806-2 virus, which was named as Lichuan virus, is a new member of Tete serogroup, and this is the first time that a Tete serogroup virus has been isolated in China