PrDOS is a server that predicts the disordered regions of a protein from its amino acid sequence (http://prdos.hgc.jp). The server accepts a single protein amino acid sequence, in either plain text ...or FASTA format. The prediction system is composed of two predictors: a predictor based on local amino acid sequence information and one based on template proteins. The server combines the results of the two predictors and returns a two-state prediction (order/disorder) and a disorder probability for each residue. The prediction results are sent by e-mail, and the server also provides a web-interface to check the results.
A speech signal captured by a distant microphone is generally smeared by reverberation, which severely degrades automatic speech recognition (ASR) performance. One way to solve this problem is to ...dereverberate the observed signal prior to ASR. In this paper, a room impulse response is assumed to consist of three parts: a direct-path response, early reflections and late reverberations. Since late reverberations are known to be a major cause of ASR performance degradation, this paper focuses on dealing with the effect of late reverberations. The proposed method first estimates the late reverberations using long-term multi-step linear prediction, and then reduces the late reverberation effect by employing spectral subtraction. The algorithm provided good dereverberation with training data corresponding to the duration of one speech utterance, in our case, less than 6 s. This paper describes the proposed framework for both single-channel and multichannel scenarios. Experimental results showed substantial improvements in ASR performance with real recordings under severe reverberant conditions.
We present a measurement of R_{K^{*}}, the branching fraction ratio B(B→K^{*}μ^{+}μ^{-})/B(B→K^{*}e^{+}e^{-}), for both charged and neutral B mesons. The ratio for the charged case R_{K^{*+}} is the ...first measurement ever performed. In addition, we report absolute branching fractions for the individual modes in bins of the squared dilepton invariant mass q^{2}. The analysis is based on a data sample of 711 fb^{-1}, containing 772×10^{6} BBover ¯ events, recorded at the ϒ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e^{+}e^{-} collider. The obtained results are consistent with standard model expectations.
Objectives
The aim of this study was to examine whether older users of information and communicative technology (ICT) participate in active behaviors, such as voluntary exercise, to maintain health, ...even under community containment to suppress the coronavirus disease 2019 (COVID-19) pandemic.
Design
Cross-sectional study.
Setting
Community setting.
Participants
Independent community-dwelling older residents aged ≥75 years.
Measurements
The municipality sent the Kihon Checklist (KCL) and Simplified Nutritional Appetite Questionnaire (SNAQ) with several questions on lifestyle and health conditions under social restriction.
Results
Among 3199 responders (72.1%), we analyzed the data of 2304 residents who provided complete answers to the KCL and SNAQ and on ICT use, voluntary exercise, polypharmacy, and families. The mean age was 79.7 years (51.3% male). The percentages of frailty assessed by the KCL, voluntary exercise, and low SNAQ scores (≤14) were 16.0%, 61.4%, and 43.8% in 808 ICT users and 30.3%, 47.2%, and 54.1% in 1496 ICT non-users, respectively (p<0.001). ICT use was significantly associated with voluntary exercise even during social restriction, independent of age, sex, polypharmacy, low SNAQ scores, and frailty status (odds ratio, 1.503; 95% confidential interval, 1.246–1.813).
Conclusion
Older ICT users are more active to maintain health even during social restriction, independent of frailty status.
Information regarding gene coexpression is useful to predict gene function. Several databases have been constructed for gene coexpression in model organisms based on a large amount of publicly ...available gene expression data measured by GeneChip platforms. In these databases, Pearson's correlation coefficients (PCCs) of gene expression patterns are widely used as a measure of gene coexpression. Although the coexpression measure or GeneChip summarization method affects the performance of the gene coexpression database, previous studies for these calculation procedures were tested with only a small number of samples and a particular species. To evaluate the effectiveness of coexpression measures, assessments with large-scale microarray data are required. We first examined characteristics of PCC and found that the optimal PCC threshold to retrieve functionally related genes was affected by the method of gene expression database construction and the target gene function. In addition, we found that this problem could be overcome when we used correlation ranks instead of correlation values. This observation was evaluated by large-scale gene expression data for four species: Arabidopsis, human, mouse and rat.
Abstract
Screening for drug discovery targeting the central nervous system requires the establishment of efficient and highly accurate toxicity test methods that can reduce costs and time while ...maintaining high throughput using the function of an in vitro neural network. In particular, an evaluation system using a human-derived neural network is desirable in terms of species difference. Despite the attention, the microelectrode array (MEA) is attracting among the evaluation systems that can measure in vitro neural activity, an effective analysis method for evaluation of toxicity and mechanism of action has not yet been established. Here we established analytical parameters and multivariate analysis method capable of detecting seizure liability of drugs using MEA measurement of human iPS cell-derived neurons. Using the spike time series data of all drugs, we established periodicity as a new analytical parameter. Periodicity has facilitated the detection of responses to seizurogenic drugs, previously difficult to detect with conventional analytical parameters. By constructing a multivariate analytical method that identifies a parameter set that achieves an arbitrary condition, we found that the parameter set comprising total spikes, maximum frequency (MF), inter- MF interval (IMFI), coefficient of variance of IMFI, and periodicity can uniformly detect the seizure liability of seizurogenic drugs with different mechanisms of action. Seizurogenic drugs were suggested to increase the regularity of the network burst in MEA measurements in human iPS cell-derived neurons.
In vitro microelectrode array (MEA) assessment using human induced pluripotent stem cell (iPSC)-derived neurons holds promise as a method of seizure and toxicity evaluation. However, there are still ...issues surrounding the analysis methods used to predict seizure and toxicity liability as well as drug mechanisms of action. In the present study, we developed an artificial intelligence (AI) capable of predicting the seizure liability of drugs and identifying drugs using deep learning based on raster plots of neural network activity. The seizure liability prediction AI had a prediction accuracy of 98.4% for the drugs used to train it, classifying them correctly based on their responses as either seizure-causing compounds or seizure-free compounds. The AI also made concentration-dependent judgments of the seizure liability of drugs that it was not trained on. In addition, the drug identification AI implemented using the leave-one-sample-out scheme could distinguish among 13 seizure-causing compounds as well as seizure-free compound responses, with a mean accuracy of 99.9 ± 0.1% for all drugs. These AI prediction models are able to identify seizure liability concentration-dependence, rank the level of seizure liability based on the seizure liability probability, and identify the mechanism of the action of compounds. This holds promise for the future of in vitro MEA assessment as a powerful, high-accuracy new seizure liability prediction method.
We investigated how the scanning strategy (SS) influences the magnetic properties of ferromagnetic metal specimens additively manufactured using 630 stainless steel powder and a directed energy ...deposition machine. The magnetization curves were measured by using B and H coils and a magnetic flux meter. The specific saturation magnetization, coercivity, and specific magnetic susceptibility were calculated from the magnetization curves obtained. Moreover, the martensite fraction, magnetization structure, and martensite structure were measured and visualized using X-ray diffraction, the Bitter method, and electron backscatter diffraction, respectively. The magnetic properties and martensite fraction depended on the SS, and magnetic poles were generated in each sub-block structure. Furthermore, a numerical analysis using a magnetic micromechanics model indicated that the variation in the martensite structure due to the SS produced differences in the magnetic properties.
We investigated whether the association between sarcopenia and fall risk (FR) differs according to the muscle mass adjustment method in 357 outpatients who were not disabled in the activities of ...daily living or indicated for orthopedic surgery. Sarcopenia was diagnosed by the Asian Working Group for Sarcopenia (AWGS) 2019 criteria, using adjusting methods of muscle mass by height squared (ht
2
), body mass index (BMI), or any of these (i.e., ht
2
-adjusted Sarc”, “BMI-adjusted Sarc”, or “ht
2
and/or BMI-adjusted Sarc, respectively). FR was defined by FR index ≥10. There were 111, 105, and 157 participants with ht
2
-adjusted, BMI-adjusted, and ht
2
and/or BMI-adjusted Sarc, respectively. After multivariable adjustment, ht
2
and/or BMI-adjusted Sarc was the most closely associated with FR odds ratio and 95% confidence interval: 2.94, 1.75–4.93. Our data suggest that the sarcopenia definition using low ASM/ht
2
and/or ASM/BMI muscle mass might better predict adverse outcomes in older patients.
In this study, the magnetic properties of a single martensite particle were investigated using type 304 stainless wire, which can reduce the number of crystal grains per unit area. First, the ...magnetization curve of wire specimens with different martensite fractions was measured by a SQUID magnetic flux meter. Then, the coercivity and susceptibility parameters were evaluated from the magnetization curve and factors contributing to these parameters were discussed. It was found that the coercivity values along the long and short axes of wire specimens with a diameter of 0.4 mm increased and subsequently decreased with an increase in the martensite fraction. Further, the susceptibility values of the same specimen along the long axis increased and along the short axis decreased with increasing martensite fractions. The results indicate that the coercivity and susceptibility of a martensite particle are affected by the size of variant clusters and the shape anisotropy of the martensite particle.
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