Constrained structure of ancient Chinese poetry facilitates speech content grouping

Ancient Chinese poetry is constituted by structured language that deviates from ordinary language usage [1, 2]; its poetic genres impose unique combinatory constraints on linguistic elements [3]. How does the constrained poetic structure facilitate speech segmentation when common linguistic [4, 5, 6, 7, 8] and statistical cues [5, 9] are unreliable to listeners in poems? We generated artificial Jueju, which arguably has the most constrained structure in ancient Chinese poetry, and presented each poem twice as an isochronous sequence of syllables to native Mandarin speakers while conducting magnetoencephalography (MEG) recording. We found that listeners deployed their prior knowledge of Jueju to build the line structure and to establish the conceptual flow of Jueju. Unprecedentedly, we found a phase precession phenomenon indicating predictive processes of speech segmentation—the neural phase advanced faster after listeners acquired knowledge of incoming speech. The statistical co-occurrence of monosyllabic words in Jueju negatively correlated with speech segmentation, which provides an alternative perspective on how statistical cues facilitate speech segmentation. Our findings suggest that constrained poetic structures serve as a temporal map for listeners to group speech contents and to predict incoming speech signals. Listeners can parse speech streams by using not only grammatical and statistical cues but also their prior knowledge of the form of language

Consistent analysis of neutral- and charged-current neutrino scattering off carbon

Background: Good understanding of the cross sections for (anti)neutrino scattering off nuclear targets in the few-GeV energy region is a prerequisite for correct interpretation of results of ongoing and planned oscillation experiments. Purpose: Clarify possible source of disagreement between recent measurements of the cross sections on carbon. Method: Nuclear effects in (anti)neutrino scattering off carbon nucleus are described using the spectral function approach. The effect of two- and multi-nucleon final states is accounted for by applying an effective value of the axial mass, fixed to 1.23 GeV. Neutral-current elastic (NCE) and charged-current quasielastic (CCQE) processes are treated on equal footing. Results: The differential and total cross sections for the energy ranging from a few hundreds of MeV to 100 GeV are obtained and compared to the available data from the BNL E734, MiniBooNE, and NOMAD experiments. Conclusions: Nuclear effects in NCE and CCQE scattering seem to be very similar. Within the spectral function approach, the axial mass from the shape analysis of the MiniBooNE data is in good agreement with the results reported by the BNL E734 and NOMAD Collaborations. However, the combined analysis of NCE and CCQE data does not seem to support the contribution of multi-nucleon final states being large enough to explain the normalization of the MiniBooNE-reported cross sections.Comment: 14 pages, 9 figures, detailed discussion of the role of FSI is adde

Critical Current Density and Resistivity of MgB2 Films

The high resistivity of many bulk and film samples of MgB2 is most readily explained by the suggestion that only a fraction of the cross-sectional area of the samples is effectively carrying current. Hence the supercurrent (Jc) in such samples will be limited by the same area factor, arising for example from porosity or from insulating oxides present at the grain boundaries. We suggest that a correlation should exist, Jc ~ 1/{Rho(300K) - Rho(50K)}, where Rho(300K) - Rho(50K) is the change in the apparent resistivity from 300 K to 50 K. We report measurements of Rho(T) and Jc for a number of films made by hybrid physical-chemical vapor deposition which demonstrate this correlation, although the "reduced effective area" argument alone is not sufficient. We suggest that this argument can also apply to many polycrystalline bulk and wire samples of MgB2.Comment: 11 pages, 3 figure

Scheduling Dynamic OpenMP Applications over Multicore Architectures

International audienceApproaching the theoretical performance of hierarchical multicore machines requires a very careful distribution of threads and data among the underlying non-uniform architecture in order to minimize cache misses and NUMA penalties. While it is acknowledged that OpenMP can enhance the quality of thread scheduling on such architectures in a portable way, by transmitting precious information about the affinities between threads and data to the underlying runtime system, most OpenMP runtime systems are actually unable to efficiently support highly irregular, massively parallel applications on NUMA machines. In this paper, we present a thread scheduling policy suited to the execution of OpenMP programs featuring irregular and massive nested parallelism over hierarchical architectures. Our policy enforces a distribution of threads that maximizes the proximity of threads belonging to the same parallel section, and uses a NUMA-aware work stealing strategy when load balancing is needed. It has been developed as a plug-in to the ForestGOMP OpenMP platform. We demonstrate the efficiency of our approach with a highly irregular recursive OpenMP program resulting from the generic parallelization of a surface reconstruction application. We achieve a speedup of 14 on a 16-core machine with no application-level optimization

Numerical Study on Indoor Wideband Channel Characteristics with Different Internal Wall

Effects of material and configuration of the internal wall on the performance of wideband channel are investigated by using the Finite Difference Time-Domain (FDTD) method. The indoor wideband channel characteristics, such as the path-loss, Root-Mean-Square (RMS) delay spread and number of the multipath components (MPCs), are presented. The simulated results demonstrate that the path-loss and MPCs are affected by the permittivity, dielectric loss tangent and thickness of the internal wall, while the RMS delay spread is almost not relevant with the dielectric permittivity. Furthermore, the comparison of simulated result with the measured one in a simple scenario has validated the simulation study

Large step ratio input-series-output-parallel chain-link DC-DC converter

High-voltage and high-power dc-dc conversion is key to dc transmission, distribution and generation, which require compact and efficient dc transformers with large step ratios. This paper introduces a dc-dc converter with the input-series-output-parallel (ISOP) arrangement of multiple high step ratio sub-converter units. Each sub-converter unit is an isolated modular dcdc converter with a stack of half-bridge cells chopping the dc down to low voltage level. The transformer provides galvanic isolation and additional step ratio. The converter achieves a large step ratio due to the combination of the series-parallel configuration, the modular cells, and the isolation transformer. The proposed dc-dc converter is analyzed in a 30 kV to 1 kV, 1 MW application to discuss the operation performance, trade-offs, power efficiency and selection of components. Finally, the converter is validated through a laboratory down-scaled prototype

Exploring data-driven building energy-efficient design of envelopes based on their quantified impacts

Building performance design plays a key role in reducing the energy consumption of buildings. However, the widely used simulation-based design is facing several challenges, such as the labor-intensive modeling process and the performance gaps between design stage estimations and operational energy use. For these reasons, artificial intelligent methods are expected by designers to improve the efficiency and reliability of building energy-efficient design. To date, there has not been a practical data-driven design method of envelopes. This study aimed at exploring data-driven building energy-efficient design of envelopes based on their quantified impacts. A feature selection method and a game-theoretic method were applied to quantify the impacts of envelopes on space heating and cooling energy, which were performed on two building datasets, one of which is from the U.S. and the other from China. Random forest classifiers were developed to conduct the study. Based on discovered energy patterns and quantified impacts of envelopes on energy consumption, a rectified linear design method of envelopes was proposed with the idea of improving the performance of high-impact envelopes. Besides, a validation study was conducted on two office buildings in the hot-summer cold-winter region. To design the envelopes of a building, the data-driven analysis was driven by its similar buildings other than the whole dataset. Moreover, a detailed energy simulation was conducted to evaluate the energy performance of different design solutions. The results showed that compared with baseline design solutions, new strategies could save 1.05%–21.2% energy for space heating and cooling for these two case buildings. The proposed method is a general building envelope design approach and allows designers to easily find an energy-efficient configuration of envelopes. This study demonstrated the feasibility and effectiveness of the data-driven energy-efficient design of building envelopes