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

Transmission line condition prediction based on semi-supervised learning

Transmission line state assessment and prediction are of great significance for the rational formulation of operation and maintenance strategy and improvement of operation and maintenance level. Aiming at the problem that existing models cannot take into account the robustness and data demand, this paper proposes a state prediction method based on semi-supervised learning. Firstly, for the expanded feature vector, the regular matrix is used to fill in the missing data, and the sparse coding problem is solved by representation learning. Then, with the help of a small number of labelled samples to initially determine the category centers of line segments in different defective states. Finally, the estimated parameters of the model are corrected using unlabeled samples. Example analysis shows that this method can improve the recognition accuracy and use data more efficiently than the existing models

Specific siRNA Targeting the Receptor for Advanced Glycation End Products Inhibits Experimental Hepatic Fibrosis in Rats

Receptor for advanced glycation end products (RAGE) was studied in different stages of carbon tetrachloride induced hepatic fibrosis (HF), and effect of its gene silencing in the HF development was evaluated in rats. Silencing RAGE expression by specific siRNA effectively suppressed NF-κB activity, hepatic stellate cell activation, and accumulation of extracellular matrix proteins in the fibrotic liver, and also greatly improved the histopathology and the ultrastructure of liver cells. These effects may be partially mediated by the inhibition on IκBα degradation. RAGE gene silencing effectively prevented liver from fibrosis, therefore it offers a potential pharmacological tool for anti-HF gene therapy

Braiding higher-order Majorana corner states through their spin degree of freedom

In this work, we study the spin texture of a class of higher-order topological superconductors (HOTSC) and show how it can be used to detect and braid Majorana corner modes (MCMs). This class of HOTSC is composed of two-dimensional topological insulators with s-wave superconductivity and in-plane magnetic fields, which offers advantages in experimental implementation. The spin polarization of the MCMs in this class is perpendicular with the applied magnetic field direction and is opposite on intrinsic orbitals, resulting in an overall ferrimagnetic spin texture. As a result, we find that the spin-selective Andreev reflection can be observed in a transverse instead of parallel direction to the applied magnetic field. Meanwhile, this spin texture leads to the gate-tunable $4\pi$ periodic $\phi_0$ Josephson current that performs qualitatively different behavior from the topologically trivial $\phi_0$-junction under rotating the in-plane magnetic field. Meanwhile, the existence of the MCMs in this class does not depend on the in-plane magnetic field direction. This gives rise to great advantage in constructing all electronically controlled Majorana network for braiding, which is confirmed through our numerical simulation. We thus provide a comprehensive scheme for probing non-Abelian statistics in this class of HOTSCs.Comment: 6 pages, 4 figure

Clinical analysis of high myopia in 320 cases in Ningxia Hui Autonomous Region

AIM: To analyze the clinical manifestations and etiological factors of high myopia in 320 cases. <p>METHODS:A total of 320 patients(640 eyes)with high myopia treated in Ningxia Eye Hospital from January 2011 to November 2012 were studied. All of them underwent thorough eye examination and relevant environmental factors were recorded. The following data were analyzed, including gender, ethnicity, age of onset, refractive error, axial length, best corrected visual acuity(BCVA), educational level and living environment. <p>RESULTS: Bilateral high myopia was present in 320 patients(130 men and 190 women; 250 being of Han nationality and 70 of Hui nationality)with a mean age of 42.65±16.51 years(range: 3-80 years); the male to female ratio was 1:1.5. The age of onset was lower than 20 years in 237 patients, higher than 21 yeas in 83 patients, the difference was statistically significant(<i>P</i><0.001). There was no significant difference between diopter and educational level(<i>P</i>>0.05). The patients with BCVA higher than 0.3 increased with diopter increased, while BCVA lower than 0.8 and between 0.4～0.7 reduced. Refraction was significantly negatively correlated with BCVA(<i>r</i>=-0.196, <i>P</i><0.05)and positive correlated with axial length(<i>r</i>=0.681, <i>P</i><0.05). <p>CONCLUSION: In the study, patients with high myopia tend to have early onset, low educational level, and spacious living environment. Such results indicate that the genetic factors may be the main cause of high myopia in this group. The higher the degree of myopia was, the worse BCVA and the longer AL would be

Pressure dependence and mechanism of Mn promotion of silica-supported Co catalyst in the Fischer-Tropsch reaction

The mechanism of Mn promotion of a silica-supported Co catalyst in the Fischer-Tropsch reaction has been studied at varying pressures up to 20 bar. IR spectroscopy in combination with DFT calculations suggest adsorbed CO is activated by reaction with an oxygen vacancy in the MnO, which covers the Co surface. This leads to a higher activity, higher CHx coverage and thus higher C5+ and lower CH4 selectivity. Increasing the pressure magnifies the selectivity differences. However, above around 4 bar, the effect of Mn on the selectivities is reversed and the C5+ selectivity is decreased by Mn addition. This is tentatively attributed to Mn promoting the C-O bond dissociation but not the chain growth. Formed monomers have to migrate to stepped sites for chain growth on the Co surface. Whilst this is migration is not impeded by co-adsorbates at low pressure, migration could be hindered by especially the high CO coverage at high pressure

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

Screening high potassium efficiency potato genotypes and physiological responses at different potassium levels

Potato (Solanum tuberosum L.) growth and production is highly dependent on potassium (K) levels in the soil. Southwest China is the largest potato production region but it has low availability of soil potassium. To assess the genetic variation in K use efficiency, 20 potato genotypes were collected to compare the yield and K content in a pot experiment. Moreover, ‘Huayu-5’ and ‘Zhongshu-19’ were cultivated in five K applications to investigate the K distribution and sucrose in different organs. The results indicated that there were highly significant effects of K, genotype and K×G interactions on tuber yield, plant and tuber K content, plant K uptake efficiency and K harvest index. Cluster analysis classified 20 potato genotypes into four types: DH (high efficiency at low and high K application), LKH (high efficiency at low K application), HKH (high efficiency at high K application) and DL (low efficiency at low and high K application). The potassium distribution percentage in the tubers of the potassium-efficient genotype was higher than that of the potassium-inefficient genotype under low potassium application. The sucrose content in the tuber gently declined as the application of K rose in both cultivars, and that in the tuber of ‘Huayu-5’ was higher than that in ‘Zhongshu-19’. ‘Huayu-5’ reached the highest yield when the potassium application was 159.45 kg ha-1, and ‘Zhongshu-19’ reached the highest yield when the potassium application was 281.4 kg ha-1. This study indicated that genetic variation for K utilization efficiency existed among 20 genotypes, and yield in low K application and relative yield were suitable criteria for screening K utilization efficiency genotypes

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