Effect of Rydberg-atom-based sensor performance on different Rydberg atom population at one atomic-vapor cell

The atomic-vapor cell is a vital component for Rydberg atomic microwave sensors, and impacts on overall capability of Rydberg sensor. However, the conventional analysis approach on effect of vapor-cell length contains two implicit assumptions, that is, the same atomic population density and buffer gas pressure, which make it unable to accurately capture actual response about effect of Rydberg-atom-based sensor performance on different Rydberg atom population. Here, utilizing a stepped cesium atomic-vapor cell with five different dimensions at the same atomic population density and buffer gas pressure, the height and full width at half maximum of Electromagnetically Induced Transparency(EIT) signal, and the sensitivity of the atomic superheterodyne sensor are comprehensively investigated at the same Rabi frequences(saturated laser power) conditions. It is identified that EIT signal height is proportional to the cell length, full width at half maximum and sensitivity grow with the increment of cell length to a certain extent. Based on the coherent integration signal theory and atomic linear expansion coefficient method, theoretical analysis of the EIT height and sensitivity are further investigated. The results could shed new light on the understanding and design of ultrahigh-sensitivity Rydberg atomic microwave sensors and find promising applications in quantum measurement, communication, and imaging

Wind effects on a long span steel roof structure: numerical simulation and equivalent static wind loads

A wind tunnel test is conducted in this study on the scaled model of the Guangzhou International Sports Arena (GISA). Simultaneous pressure measurements are conducted in a simulated suburban boundary layer flow field. A numerical simulation approach using Fuzzy Neural Networks (FNNs) is developed for the predictions of wind-induced pressure time series at roof locations which are not covered in the wind tunnel measurements. On the other hand, the wind-induced response of the roof are presented and discussed, which are directly calculated by the Complete Quadratic Combination (CQC) approach. Furthermore, the correlations between the background and resonant response components are discussed in detail, and the results show that neglecting the correlations between the two components would result in considerable error in the response estimation. Finally, the Equivalent Static Wind Load (ESWL) approach is used to estimate the wind-induced responses of the roof, which are compared with those obtained from the CQC approach to examine the effectiveness of the proposed ESWL approach in the design and analysis of large-span roof structures. It is shown through the example that the FNN and ESWL approaches can successfully predict the wind-induced pressures and responses respectively

Hexyl (E)-3-(3,4-dihy­droxy­phen­yl)acrylate

The title mol­ecule, C15H20O4, has an E conformation about its C=C bond and is almost planar (r.m.s. deviation of all non-H atoms = 0.04 Å). The crystal structurere features O—H⋯O and C—H⋯O hydrogen bonds

A Nonlinear Crack Model for Concrete Structure based on an Extended Scaled Boundary Finite Element Method

Fracture mechanics is one of the most important approaches to structural safety analysis. Modeling the fracture process zone (FPZ) is critical to understand the nonlinear cracking behavior of heterogeneous quasi-brittle materials such as concrete. In this work, a nonlinear extended scaled boundary finite element method (X-SBFEM) was developed incorporating the cohesive fracture behavior of concrete. This newly developed model consists of an iterative procedure to accurately model the traction distribution within the FPZ accounting for the cohesive interactions between crack surfaces. Numerical validations were conducted on both of the concrete beam and dam structures with various loading conditions. The results show that the proposed nonlinear X-SBFEM is capable of modeling the nonlinear fracture propagation process considering the effect of cohesive interactions, thereby yielding higher precisions than the linear X-SBFEM approach

(E)-Isopentyl 3-(3,4-dihy­droxy­phen­yl)­acrylate

The title compound, C14H18O4, a derivative of caffeic acid, has an E configuration about the C=C bond. The benzene ring is almost coplanar with the C=C—C(O)—O—C linker [maximum deviation = 0.050 (2) Å], making a dihedral angle of only 4.53 (2)°. In the mol­ecule, the adjacent hy­droxy groups form an O—H⋯O inter­action. In the crystal, mol­ecules are linked by O—H⋯O hydrogen bonds, generating a chain propagating in the [110] direction

A Hierarchical Context-aware Modeling Approach for Multi-aspect and Multi-granular Pronunciation Assessment

Automatic Pronunciation Assessment (APA) plays a vital role in Computer-assisted Pronunciation Training (CAPT) when evaluating a second language (L2) learner's speaking proficiency. However, an apparent downside of most de facto methods is that they parallelize the modeling process throughout different speech granularities without accounting for the hierarchical and local contextual relationships among them. In light of this, a novel hierarchical approach is proposed in this paper for multi-aspect and multi-granular APA. Specifically, we first introduce the notion of sup-phonemes to explore more subtle semantic traits of L2 speakers. Second, a depth-wise separable convolution layer is exploited to better encapsulate the local context cues at the sub-word level. Finally, we use a score-restraint attention pooling mechanism to predict the sentence-level scores and optimize the component models with a multitask learning (MTL) framework. Extensive experiments carried out on a publicly-available benchmark dataset, viz. speechocean762, demonstrate the efficacy of our approach in relation to some cutting-edge baselines.Comment: Accepted to Interspeech 202

Decision ambiguity is mediated by a late positive potential originating from cingulate cortex

People often make decisions in the face of ambiguous information, but it remains unclear how ambiguity is represented in the brain. We used three types of ambiguous stimuli and combined EEG and fMRI to examine the neural representation of perceptual decisions under ambiguity. We identified a late positive potential, the LPP, which differentiated levels of ambiguity, and which was specifically associated with behavioral judgments about choices that were ambiguous, rather than passive perception of ambiguous stimuli. Mediation analyses together with two further control experiments confirmed that the LPP was generated only when decisions are made (not during mere perception of ambiguous stimuli), and only when those decisions involved choices on a dimension that is ambiguous. A further control experiment showed that a stronger LPP arose in the presence of ambiguous stimuli compared to when only unambiguous stimuli were present. Source modeling suggested that the LPP originated from multiple loci in cingulate cortex, a finding we further confirmed using fMRI and fMRI-guided ERP source prediction. Taken together, our findings argue for a role of an LPP originating from cingulate cortex in encoding decisions based on task-relevant perceptual ambiguity, a process that may in turn influence confidence judgment, response conflict, and error correction

Single-Neuron Correlates of Error Monitoring and Post-Error Adjustments in Human Medial Frontal Cortex

Humans can self-monitor errors without explicit feedback, resulting in behavioral adjustments on subsequent trials such as post-error slowing (PES). The error-related negativity (ERN) is a well-established macroscopic scalp EEG correlate of error self-monitoring, but its neural origins and relationship to PES remain unknown. We recorded in the frontal cortex of patients performing a Stroop task and found neurons that track self-monitored errors and error history in dorsal anterior cingulate cortex (dACC) and pre-supplementary motor area (pre-SMA). Both the intracranial ERN (iERN) and error neuron responses appeared first in pre-SMA, and ∼50 ms later in dACC. Error neuron responses were correlated with iERN amplitude on individual trials. In dACC, such error neuron-iERN synchrony and responses of error-history neurons predicted the magnitude of PES. These data reveal a human single-neuron correlate of the ERN and suggest that dACC synthesizes error information to recruit behavioral control through coordinated neural activity