Computer Vision System for Expressing Texture Using Sound-Symbolic Words.

The major goals of texture research in computer vision are to understand, model, and process texture and ultimately simulate human visual information processing using computer technologies. The field of computer vision has witnessed remarkable advancements in material recognition using deep convolutional neural networks (DCNNs), which have enabled various computer vision applications, such as self-driving cars, facial and gesture recognition, and automatic number plate recognition. However, for computer vision to "express" texture like human beings is still difficult because texture description has no correct or incorrect answer and is ambiguous. In this paper, we develop a computer vision method using DCNN that expresses texture of materials. To achieve this goal, we focus on Japanese "sound-symbolic" words, which can describe differences in texture sensation at a fine resolution and are known to have strong and systematic sensory-sound associations. Because the phonemes of Japanese sound-symbolic words characterize categories of texture sensations, we develop a computer vision method to generate the phonemes and structure comprising sound-symbolic words that probabilistically correspond to the input images. It was confirmed that the sound-symbolic words output by our system had about 80% accuracy rate in our evaluation.

Automatic Estimation of Multidimensional Personality From a Single Sound-Symbolic Word.

Researchers typically use the "big five" traits (Extroversion, Agreeableness, Conscientiousness, Neuroticism, and Openness) as a standard way to describe personality. Evaluation of personality is generally conducted using self-report questionnaires that require participants to respond to a large number of test items. To minimize the burden on participants, this paper proposes an alternative method of estimating multidimensional personality traits from only a single word. We constructed a system that can convert a sound-symbolic word (SSW) that intuitively expresses personality traits into information expressed by 50 personality-related adjective pairs. This system can obtain information equivalent to the adjective scales using only a single word instead of asking many direct questions. To achieve this, we focused on SSWs in Japanese that have the association between linguistic sounds and meanings and express diverse and complex aspects of personality traits. We evaluated the prediction accuracy of the system and found that the multiple correlation coefficients for 48 personality-related adjective pairs exceeded 0.75, indicating that the model could explain more than half of the variations in the data. In addition, we conducted an evaluation experiment in which participants rated the appropriateness of the system output using a seven-point scale (with -3 as absolutely inappropriate and +3 as completely appropriate). The average score for 50 personality-related adjective pairs was 1.25. Thus, we believe that this system can contribute to the field of personality computing, particularly in terms of personality evaluation and communication.

Information Geometry of Randomized Quantum State Tomography.

Suppose that a d-dimensional Hilbert space H ≃ C d admits a full set of mutually unbiased bases | 1 ( a ) 〉 , ⋯ , | d ( a ) 〉 , where a = 1 , ⋯ , d + 1 . A randomized quantum state tomography is a scheme for estimating an unknown quantum state on H through iterative applications of measurements M ( a ) = | 1 ( a ) 〉 〈 1 ( a ) | , ⋯ , | d ( a ) 〉 〈 d ( a ) | for a = 1 , ⋯ , d + 1 , where the numbers of applications of these measurements are random variables. We show that the space of the resulting probability distributions enjoys a mutually orthogonal dualistic foliation structure, which provides us with a simple geometrical insight into the maximum likelihood method for the quantum state tomography.

COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples.

An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis.

A rapid and high-throughput quantitation assay of the nuclear factor κB activity using fluorescence correlation spectroscopy in the setting of clinical laboratories.

BACKGROUND: Transcription factor nuclear factor-κB (NF-κB) plays a key role in the regulation of immune responses to inflammation. However, convenient assay systems to quantitate the NF-κB activity level in a timely manner are not available in the setting of clinical laboratories. Therefore, we developed a novel and high-throughput quantitative assay based on fluorescence correlation spectroscopy (FCS) to detect the NF-κB activity level in cellular nuclear extracts and evaluated the performance of this method. The basic principle of this assay is to calculate the binding fraction of NF-κB to fluorescent-labeled DNA probes, which contain NF-κB binding sites. METHODS: Non-fluorescent competitive probes are employed to normalize the influence of the viscosity of the nuclear extracts between samples and to eliminate the influence of nonspecific binding of the fluorescent probes. To confirm accurate quantitation, human recombinant NF-κB p50 was mixed into U937 cell nuclear extracts, and the binding fraction of the fluorescent probes to NF-κB in the mixture was calculated for quantitation. To evaluate whether this method can be applied to measure the NF-κB activity in human lymphocytes, the NF-κB activity levels of systemic inflammatory response syndrome patients during perioperative periods were measured. RESULTS: The percentage recovery was 88.9%. The coefficients of variation of the intra-assay were approximately 10%. NF-κB activity levels during the perioperative period can were successfully measured. The assay time for the FCS measurement was within 20 minutes. CONCLUSIONS: This assay system can be used to quantitate NF-κB activity levels in a timely manner in the setting of hospital laboratories.

Experimental demonstration of adaptive quantum state estimation.

The first experimental demonstration of an adaptive quantum state estimation (AQSE) is reported. The strong consistency and asymptotic efficiency of AQSE have been mathematically proven [A. Fujiwara, J. Phys. A 39, 12489 (2006)]. In this Letter, the angle of linear polarization of single photons, the phase parameter between the right and the left circularly polarization, is estimated using AQSE, and the strong consistency and asymptotic efficiency are experimentally verified. AQSE will provide a general useful method in both quantum information processing and metrology.

Evaluation of dynamic features of Escherichia coli 16S ribosomal RNA in homogeneous physiological solution.

There is no methodology for the estimation of the dynamic features of large-molecular-weight RNAs in homogeneous physiological media. In this report, a luminescence anisotropy-based method using a long-lifetime luminescent oligonucleotide probe for the estimation of the dynamic features of large-molecular-weight RNA is described. As a luminescent probe, Ru(II) complex-labeled oligonucleotides, which have a complementary sequence to the single-stranded regions of Escherichia coli 16S rRNA, were synthesized. After the hybridization of the probe to single-stranded regions of 16S rRNA, the segmental motions of the regions were evaluated by time-resolved luminescence anisotropy analysis. In 16S rRNA, the L2 site (323-332 nt) was found to be the most flexible among the seven sites chosen. From a comparison between the hybridization kinetics of oligonucleotides to these single-stranded regions and the rotational correlation times, it was suggested that the flexibility of the single-stranded region was closely correlated with the hybridization kinetics. Furthermore, results of the luminescence lifetime measurement and luminescence quenching experiments suggested that the highly flexible region was located on the surface of the 16S rRNA and that the less flexible region was located in the depths of 16S rRNA.