It has been suggested that humans discriminate different frequency sounds with greater selectivity than other mammals. However, mechanisms that could underlie higher frequency selectivity in humans are unclear. Recent...
It has been suggested that humans discriminate different frequency sounds with greater selectivity than other mammals. However, mechanisms that could underlie higher frequency selectivity in humans are unclear. Recent studies show that the tectorial membrane (TM) supports longitudinally propagating waves, and the spread of excitation of these TM waves has been implicated in controlling the tuning properties in a mutant mouse model of hearing. Here we compare TM morphology and waves in humans and mice and show that despite some differences in morphology, the spread of excitation of TM waves is similar in spatial extent. However, the cochlear maps of humans and mice differ significantly, with similar cochlear distances mapping to a narrower range of best frequencies in humans than in mice. By coupling different frequency ranges, TM waves could contribute to differences in frequency tuning in mammals, with the smaller human range of frequencies corresponding to sharper frequency tuning.
Controlling functionalities, such as magnetism or ferroelectricity, by means of oxygen vacancies (VO) is a key issue for the future development of transition metal oxides. Progress in this field is currently addressed...
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Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalen...
Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am
This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal.Retraction published: 8 February 2019
This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal.
Retraction published: 8 February 2019
The CD-DNN-HMM system has became the state-of-art system for large vocabulary continuous speech recognition (LVCSR) tasks, in which deep neural networks (DNN) plays a key role. However, DNN training suffers from the v...
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ISBN:
(纸本)9781479999897
The CD-DNN-HMM system has became the state-of-art system for large vocabulary continuous speech recognition (LVCSR) tasks, in which deep neural networks (DNN) plays a key role. However, DNN training suffers from the vanishing gradient problem, limiting training of deep models. In this work, we address this problem by incorporating the successful long-short term memory (LSTM) structure, which has been proposed to help recurrent neural network (RNN) to remember long term dependencies, into DNN. Also, we propose a generalized formulation of the LSTM block, which we name general LSTM(GLSTM). In our experiments, it is shown that our proposed (G)LSTM-DNN scales well with more layers, and achieves 8.2% relative word error rate reduction on the 2000-hour Switchboard data set.
Since the comfort feeling and satisfaction of a toilet seat is important for the defecation, we investigated the design parameters and affective attributes for toilet seats, and developed the affective model that expl...
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ISBN:
(纸本)9781509036660
Since the comfort feeling and satisfaction of a toilet seat is important for the defecation, we investigated the design parameters and affective attributes for toilet seats, and developed the affective model that explains the level of customer satisfaction. To achieve, objective measurements of design parameters and total 19 number of relevant affective attributes including appropriateness of each design parameter were collected from literature review and user interview. Then, a subjective experiment was conducted on five different toilet seat samples. As a result, 6 factors of surface and fatigue, appropriateness of toilet size, accessibility, immaculateness, centroid, and physical tensity were revealed by factor analysis. An affective model for seat comfort was also developed by regression analysis, and the relationships between each factor and design parameters were investigated through correlation analysis. This study is expected to contribute in improvement of toilet seat comfort as a preliminary study.
We consider the problem of sequentially making decisions that are rewarded by "successes" and "failures" which can be predicted through an unknown relationship that depends on a partially controlla...
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ISBN:
(纸本)9781510829008
We consider the problem of sequentially making decisions that are rewarded by "successes" and "failures" which can be predicted through an unknown relationship that depends on a partially controllable vector of attributes for each instance. The learner takes an active role in selecting samples from the instance pool. The goal is to maximize the probability of success, either after the offline training phase or minimizing regret in online learning. Our problem is motivated by real-world applications where observations are time consuming and/or expensive. With the adaptation of an online Bayesian linear classifier, we develop a knowledge-gradient type policy to guide the experiment by maximizing the expected value of information of labeling each alternative, in order to reduce the number of expensive physical experiments. We provide a finite-time analysis of the estimated error and demonstrate the performance of the proposed algorithm on both synthetic problems and benchmark UCI datasets.
To address the growing concern of small unmanned aircraft systems (sUAS) entering the airspace over a public event, building, or other protected spaces (whether for recreational purposes or with malicious intent), we ...
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Symmetry breaking is a fundamental concept in condensed matter physics whose presence often heralds new phases of matter. For instance, the breaking of time reversal symmetry is traditionally linked to magnetic phases...
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