Stability of braneworlds with non-minimally coupled multi-scalar fields

Linear stability of braneworld models constructed with multi-scalar fields is very different from that of single-scalar field models. It is well known that both the tensor and scalar perturbation equations of the later can always be written as a supersymmetric Schr\"{o}dinger equation, so it can be shown that the perturbations are stable at linear level. However, in general it is not true for multi-scalar field models and especially there is no effective method to deal with the stability problem of the scalar perturbations for braneworld models constructed with non-minimally coupled multi-scalar fields. In this paper we present a method to investigate the stability of such braneworld models. It is easy to find that the tensor perturbations are stable. For the stability problem of the scalar perturbations, we present a systematic covariant approach. The covariant quadratic order action and the corresponding first-order perturbed equations are derived. By introducing the orthonormal bases in field space and making the Kaluza-Klein decomposition, we show that the Kaluza-Klein modes of the scalar perturbations satisfy a set of coupled Schr\"{o}dinger-like equations, with which the stability of the scalar perturbations and localization of the scalar zero modes can be analyzed according to nodal theorem. The result depends on the explicit models. For superpotential derived barane models, the scalar perturbations are stable, but there exist normalizable scalar zero modes, which will result in unaccepted fifth force on the brane. We also use this method to analyze the $f(R)$ braneworld model with an explicit solution and find that the scalar perturbations are stable and the scalar zero modes can not be localized on the brane, which ensure that there is no extra long-range force and the Newtonian potential on the brane can be recovered.Comment: 13 pages, 3 figure

Voxel selection in fMRI data analysis based on sparse representation

Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI) data with task relevant information. In each iteration of the algorithm, a linear programming problem is solved and a sparse weight vector is subsequently obtained. The final weight vector is the mean of those obtained in all iterations. The characteristics of our algorithm are as follows: 1) the weight vector (output) is sparse; 2) the magnitude of each entry of the weight vector represents the significance of its corresponding variable or feature in a classification or regression problem; and 3) due to the convergence of this algorithm, a stable weight vector is obtained. To demonstrate the validity of our algorithm and illustrate its application, we apply the algorithm to the Pittsburgh Brain Activity Interpretation Competition 2007 functional fMRI dataset for selecting the voxels, which are the most relevant to the tasks of the subjects. Based on this dataset, the aforementioned characteristics of our algorithm are analyzed, and a comparison between our method with the univariate general-linear-model-based statistical parametric mapping is performed. Using our method, a combination of voxels are selected based on the principle of effective/sparse representation of a task. Data analysis results in this paper show that this combination of voxels is suitable for decoding tasks and demonstrate the effectiveness of our method

Parallel phonological processing of Chinese characters revealed by flankers tasks

An important and extensively researched question in the field of reading is whether readers can process multiple words in parallel. An unresolved issue regarding this question is whether the phonological information from foveal and parafoveal words can be processed in parallel, i.e., parallel phonological processing. The present study aims to investigate whether there is parallel phonological processing of Chinese characters. The original and the revised flankers tasks were applied. In both tasks, a foveal target character was presented in isolation in the no-flanker condition, flanked on both sides by a parafoveal homophone in the homophone-flanker condition, and by a non-homophonic character in the unrelated-flanker condition. Participants were instructed to fixate on the target characters and press two keys to indicate whether they knew the target characters (lexical vs. non-lexical). In the original flankers task, the stimuli were presented for 150 ms without a post-mask. In the revised flankers task, we set the stimulus exposure time (duration of the stimuli plus the blank interval between the stimuli and the post-mask) to each participant’s lexical decision threshold to prevent participants from processing the target and flanker characters serially. In both tasks, reaction times to the lexical targets were significantly shorter in the homophone-flanker condition than in the unrelated-flanker condition, suggesting parallel phonological processing of Chinese characters. In the revised flankers task, accuracy rates to the lexical targets were significantly lower in the unrelated-flanker condition compared to the homophone-flanker condition, further supporting parallel phonological processing of Chinese characters. Moreover, reaction times to the lexical targets were the shortest in the no-flanker condition in both tasks, reflecting the attention distribution over both the target and flanker characters. The findings of this study provide valuable insights into the parallel processing mechanisms involved in reading

Conformational change of the AcrR regulator reveals a possible mechanism of induction

The Escherichia coli AcrR multidrug-binding protein represses transcription of acrAB and is induced by many structurally unrelated cytotoxic compounds. The crystal structure of AcrR in space group P2221 has been reported previously. This P2221 structure has provided direct information about the multidrug-binding site and important residues for drug recognition. Here, a crystal structure of this regulator in space group P31 is presented. Comparison of the two AcrR structures reveals possible mechanisms of ligand binding and AcrR regulation