Quantum walks on two kinds of two-dimensional models

In this paper, we numerically study quantum walks on two kinds of two-dimensional graphs: cylindrical strip and Mobius strip. The two kinds of graphs are typical two-dimensional topological graph. We study the crossing property of quantum walks on these two models. Also, we study its dependence on the initial state, size of the model. At the same time, we compare the quantum walk and classical walk on these two models to discuss the difference of quantum walk and classical walk

TMEM16B regulates anxiety-related behavior and GABAergic neuronal signaling in the central lateral amygdala.

TMEM16B (ANO2) is the Ca2+-activated chloride channel expressed in multiple brain regions, including the amygdala. Here we report that Ano2 knockout mice exhibit impaired anxiety-related behaviors and context-independent fear memory, thus implicating TMEM16B in anxiety modulation. We found that TMEM16B is expressed in somatostatin-positive (SOM+) GABAergic neurons of the central lateral amygdala (CeL), and its activity modulates action potential duration and inhibitory postsynaptic current (IPSC). We further provide evidence for TMEM16B actions not only in the soma but also in the presynaptic nerve terminals of GABAergic neurons. Our study reveals an intriguing role for TMEM16B in context-independent but not context-dependent fear memory, and supports the notion that dysfunction of the amygdala contributes to anxiety-related behaviors

RNase P Ribozymes Inhibit the Replication of Human Cytomegalovirus by Targeting Essential Viral Capsid Proteins.

An engineered RNase P-based ribozyme variant, which was generated using the in vitro selection procedure, was used to target the overlapping mRNA region of two proteins essential for human cytomegalovirus (HCMV) replication: capsid assembly protein (AP) and protease (PR). In vitro studies showed that the generated variant, V718-A, cleaved the target AP mRNA sequence efficiently and its activity was about 60-fold higher than that of wild type ribozyme M1-A. Furthermore, we observed a reduction of 98%-99% in AP/PR expression and an inhibition of 50,000 fold in viral growth in cells with V718-A, while a 75% reduction in AP/PR expression and a 500-fold inhibition in viral growth was found in cells with M1-A. Examination of the antiviral effects of the generated ribozyme on the HCMV replication cycle suggested that viral DNA encapsidation was inhibited and as a consequence, viral capsid assembly was blocked when the expression of AP and PR was inhibited by the ribozyme. Thus, our study indicates that the generated ribozyme variant is highly effective in inhibiting HCMV gene expression and blocking viral replication, and suggests that engineered RNase P ribozyme can be potentially developed as a promising gene-targeting agent for anti-HCMV therapy

Unidirectional anisotropy in cubic FeGe with antisymmetric spin-spin-coupling

We report strong unidirectional anisotropy in bulk polycrystalline B20 FeGe measured by ferromagnetic resonance spectroscopy. Bulk and micron-sized samples were produced and analytically characterized. FeGe is a B20 compound with inherent Dzyaloshinskii-Moriya interaction. Lorenz microscopy confirms a skyrmion lattice at $190 \; \text{K}$ in a magnetic field of 150 mT. Ferromagnetic resonance was measured at $276 \; \text{K} \pm 1 \; \text{K}$, near the Curie temperature. Two resonance modes were observed, both exhibit a unidirectional anisotropy of $K=1153 \; \text{J/m}^3 \pm 10 \; \text{J/m}^3$ in the primary, and $K=28 \; \text{J/m}^3 \pm 2 \; \text{J/m}^3$ in the secondary mode, previously unknown in bulk ferromagnets. Additionally, about 25 standing spin wave modes are observed inside a micron-sized FeGe wedge, measured at room temperature ($\sim \; 293$ K). These modes also exhibit unidirectional anisotropy

Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance

ROC is usually used to analyze the performance of classifiers in data mining. ROC convex hull (ROCCH) is the least convex major-ant (LCM) of the empirical ROC curve, and covers potential optima for the given set of classifiers. Generally, ROC performance maximization could be considered to maximize the ROCCH, which also means to maximize the true positive rate (tpr) and minimize the false positive rate (fpr) for each classifier in the ROC space. However, tpr and fpr are conflicting with each other in the ROCCH optimization process. Though ROCCH maximization problem seems like a multi-objective optimization problem (MOP), the special characters make it different from traditional MOP. In this work, we will discuss the difference between them and propose convex hull-based multi-objective genetic programming (CH-MOGP) to solve ROCCH maximization problems. Convex hull-based sort is an indicator based selection scheme that aims to maximize the area under convex hull, which serves as a unary indicator for the performance of a set of points. A selection procedure is described that can be efficiently implemented and follows similar design principles than classical hyper-volume based optimization algorithms. It is hypothesized that by using a tailored indicator-based selection scheme CH-MOGP gets more efficient for ROC convex hull approximation than algorithms which compute all Pareto optimal points. To test our hypothesis we compare the new CH-MOGP to MOGP with classical selection schemes, including NSGA-II, MOEA/D) and SMS-EMOA. Meanwhile, CH-MOGP is also compared with traditional machine learning algorithms such as C4.5, Naive Bayes and Prie. Experimental results based on 22 well-known UCI data sets show that CH-MOGP outperforms significantly traditional EMOAs

Bridging the Preference Gap between Retrievers and LLMs

Large Language Models (LLMs) have demonstrated superior results across a wide range of tasks, and Retrieval-augmented Generation (RAG) is an effective way to enhance the performance by locating relevant information and placing it into the context window of the LLM. However, the relationship between retrievers and LLMs in a RAG is still under-investigated. Most existing work treats the retriever and the LLM as independent components and leaves a gap between retrieving human-"friendly" information and assembling a LLM-"friendly" context. In this work, we examine a novel bridge mechanism. We validate the ranking and selection assumptions of retrievers in the context of RAG and propose a framework that chains together supervised and reinforcement learning to train a bridge model that optimizes the connection between the retriever and the LLM. Empirical results demonstrate the effectiveness of our method in both question-answering and personalized generation tasks

Lepton-flavored electroweak baryogenesis

We explore lepton-flavored electroweak baryogenesis, driven by CP-violation in leptonic Yukawa sector, using the τ−μ system in the two Higgs doublet model as an example. This setup generically yields, together with the flavor-changing decay h→τμ, a tree-level Jarlskog invariant that can drive dynamical generation of baryon asymmetry during a first-order electroweak phase transition and results in CP-violating effects in the decay h→ττ. We find that the observed baryon asymmetry can be generated in parameter space compatible with current experimental results for the decays h→τμ, h→ττ, and τ→μγ, as well as the present bound on the electric dipole moment of the electron. The baryon asymmetry generated is intrinsically correlated with the CP-violating decay h→ττ and the flavor-changing decay h→τμ, which thus may serve as “smoking guns” to test lepton-flavored electroweak baryogenesis