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

Orthonormal basis of the octonionic analytic functions

AbstractBy confirming a conjecture proposed in Li and Peng (2001) [1], we obtain the orthonormal basis for the octonionic analytic functions

Acupuncture in Treatment of Chronic Functional Constipation

Constipation is not only a symptom but is a predominant presenting symptom in many diseases. The prevalence is between 3 and 27% worldwide, and is especially prevalent in the elderly population. The aetiology is multifactorial. Laxative abuse or enema use are usually a norm in patients’ constipation. Patients tend not to seek further medical aid after several unsuccessful therapies and this can seriously affect their quality of life

Quarter-wave Resonator Based Tunable Coupler for Xmon Qubits

We propose a scheme of tunable coupler based on quarter-wave resonator for scalable quantum integrated circuits. The open end of the T-type resonator is capacitively coupled to two Xmon qubits, while another end is an asymmetric dc-SQUID which dominates the inductive energy of coupler resonator. The dc-Current applied through the flux bias line could change the magnetic flux inside the dc-SQUID, so the frequency of coupler resonator can be effectively tuned and the qubit-qubit coupling can be totally switched off. As the increase of junction asymmetry for the dc-SQUID, the coupling of SQUID's effective phase difference and cavity modes become smaller at required working frequency regime of coupler resonator, and this could reduce the descent of the resonator's quality factor. The separation between two cross-capacitor can be larger with help of transverses width of the T-shape resonator, and then the ZZ crosstalk coupling can be effectively suppressed. The asymmetric dc-SQUID is about 5 millimeters away from the Xmon qubits and only needs a small current on the flux bias line, which in principle creates less flux noises to superconducting Xmon qubits.Comment: 8 pages, 5 figure

Computing solution space properties of combinatorial optimization problems via generic tensor networks

We introduce a unified framework to compute the solution space properties of a broad class of combinatorial optimization problems. These properties include finding one of the optimum solutions, counting the number of solutions of a given size, and enumeration and sampling of solutions of a given size. Using the independent set problem as an example, we show how all these solution space properties can be computed in the unified approach of generic tensor networks. We demonstrate the versatility of this computational tool by applying it to several examples, including computing the entropy constant for hardcore lattice gases, studying the overlap gap properties, and analyzing the performance of quantum and classical algorithms for finding maximum independent sets.Comment: Github repo: https://github.com/QuEraComputing/GenericTensorNetworks.j

Association of Combined Maternal-Fetal TNF-α Gene G308A Genotypes with Preterm Delivery: A Gene-Gene Interaction Study

Preterm delivery (PTD) is a complicated perinatal adverse event. We were interested in association of G308A polymorphism in tumor necrosis factor-α (TNF-α) gene with PTD; so we conducted a genetic epidemiology study in Anqing City, Anhui Province, China. Case families and control families were all collected between July 1999 and June 2002. To control potential population stratification as we could, all eligible subjects were ethnic Han Chinese. 250 case families and 247 control families were included in data analysis. A hybrid design which combines case-parent triads and control parents was employed, to test maternal-fetal genotype (MFG) incompatibility. The method is based on a log-linear modeling approach. In summary, we found that when the mother's or child's genotype was G/A, there was a reduced risk of PTD; however when the mother's or child's genotype was genotype A/A, there was a relatively higher risk of PTD. Combined maternal-fetal genotype GA/GA showed the most reduced risk of PTD. Comparison of the LRTs showed that the model with maternal-fetal genotype effects fits significantly better than the model with only maternal and fetal genotype main effects (log-likelihood = −719.4, P = .023, significant at 0.05 level). That means that the combined maternal-fetal genotype incompatibility was significantly associated with PTD. The model with maternal-fetal genotype effects can be considered a gene-gene interaction model. We claim that both maternal effects and fetal effects should be considered together while investigating genetic factors of certain perinatal diseases

Optimization of Clostridium tyrobutyricum encapsulation by extrusion method and characterization of the formulation

Purpose: To optimize the process parameters for the encapsulation of Clostridium tyrobutyricum (Ct) and to determine its in vitro characteristics.Methods: The process parameters, including the concentration of the wall and hardening material, Ct to gelatin ratio and hardening time, were studied by single factor analysis, while optimization was performed by orthogonal experimental design for the encapsulation rate of Ct.Results: Optimal conditions exhibited by orthogonal experimental design at a 92.17 % encapsulation rate with a viable count of 9.61 ± 0.06 lgCFU/g were: 6 % modified starch, 3 % sodium alginate, and 2 % CaCl2 at a Ct to gelatin ratio of 1:1 with a hardening time of 30 min. The survival rates of encapsulated Ct were higher than free Ct in simulated gastric (6.22 %) and intestinal juices (15.55 %). Reduction in viable counts of Ct at 90 °C were higher for free cells (44.76 %) than encapsulated cells (28.09 %) after 30 min of heat treatment. Correspondingly, encapsulation boosted the capacity of Ct to withstand the strong acidic conditions of the stomach and improved the storage properties of Ct.Conclusion: The results suggested that extrusion is a good technique for the encapsulation of Ct, as it enhances the viability of Ct during their transit through the gastrointestinal tract. Furthermore, encapsulation is favorable for Ct if planned for use in formulations where high temperature treatment is required