22 research outputs found

    TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challenge

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    This paper describes the TSUP team's submission to the ISCSLP 2022 conversational short-phrase speaker diarization (CSSD) challenge which particularly focuses on short-phrase conversations with a new evaluation metric called conversational diarization error rate (CDER). In this challenge, we explore three kinds of typical speaker diarization systems, which are spectral clustering(SC) based diarization, target-speaker voice activity detection(TS-VAD) and end-to-end neural diarization(EEND) respectively. Our major findings are summarized as follows. First, the SC approach is more favored over the other two approaches under the new CDER metric. Second, tuning on hyperparameters is essential to CDER for all three types of speaker diarization systems. Specifically, CDER becomes smaller when the length of sub-segments setting longer. Finally, multi-system fusion through DOVER-LAP will worsen the CDER metric on the challenge data. Our submitted SC system eventually ranks the third place in the challenge

    Population dynamical behavior of Lotka-Volterra system under regime switching

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    In this paper, we investigate a Lotka-Volterra system under regime switching dx(t) = diag(x1(t); : : : ; xn(t))[(b(r(t)) + A(r(t))x(t))dt + (r(t))dB(t)]; where B(t) is a standard Brownian motion. The aim here is to find out what happens under regime switching. We first obtain the sufficient conditions for the existence of global positive solutions, stochastic permanence and extinction. We find out that both stochastic permanence and extinction have close relationships with the stationary probability distribution of the Markov chain. The limit of the average in time of the sample path of the solution is then estimated by two constants related to the stationary distribution and the coefficients. Finally, the main results are illustrated by several examples

    Insights into the genetic influences of the microbiota on the life span of a host

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    Escherichia coli (E. coli) mutant strains have been reported to extend the life span of Caenorhabditis elegans (C. elegans). However, the specific mechanisms through which the genes and pathways affect aging are not yet clear. In this study, we fed Drosophila melanogaster (fruit fly) various E. coli single-gene knockout strains to screen mutant strains with an extended lifespan. The results showed that D. melanogaster fed with E. coli purE had the longest mean lifespan, which was verified by C. elegans. We conducted RNA-sequencing and analysis of C. elegans fed with E. coli purE (a single-gene knockout mutant) to further explore the underlying molecular mechanism. We used differential gene expression (DGE) analysis, enrichment analysis, and gene set enrichment analysis (GSEA) to screen vital genes and modules with significant changes in overall expression. Our results suggest that E. coli mutant strains may affect the host lifespan by regulating the protein synthesis rate (cfz-2) and ATP level (catp-4). To conclude, our study could provide new insights into the genetic influences of the microbiota on the life span of a host and a basis for developing anti-aging probiotics and drugs

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

    The Influence of Working Memory Load of Binding on Selective Attention

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    PURPOSE: Ample studies have documented that working memory (WM) load has a comprehensive influence on selective attention in perception. Moreover, the influence of WM on selective attention is modulated by the type of WM subsystem, by revealing opposite modulation by central executive and visual WM. However,&nbsp; no study so far has examined the influence of WM load of binding on selective attention. Moreover, there are two opposite views as to this issue: On the one hand, an independent episodic buffer is suggested to be in charge of binding with the attention from of central executive, suggesting that binding load will functions as a type of central executive; on the other hand, recent studies revealed that object-based attention plays a key role in both visual WM and binding representation in WM, implying that binding load will serve as a type of visual WM load. To this end, we examined the influence of WM load of binding on selective attention by requiring the participants to memorize two or five bindings in WM. METHODS: Critically, a low load perceptual task was interpolated in the maintenance phase of WM. The low load perceptual task contained either a low-priority target or was an response competition task. RESULTS: In three experiments, we found that high WM load of binding led to reduced detection of low-priority target (Experiments 1-2), and less interference from the distractor in the response competition task (Experiment 3). CONCLUSION: These results suggest that WM load of binding is similar to visual WM load, serving as a type of perceptual load and hence competing resources with the perceptual task.&nbsp;</p

    Deep learning in object detection and recognition

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    System Performance and Empathetic Design Enhance User Experience for Fault Diagnosis Expert System

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    The fault diagnosis task in factories is technically demanding and time-consuming, especially for the green hands. In order to assist mechanicians to detect the fault parts, the fault diagnosis expert system is introduced to support decision-making and problem-solving processes. In this vision, how to enhance mechanicians&rsquo; willingness to use such a system becomes a key issue to the industry. The present study aims to find out the elements that affect the user experience of the fault diagnosis expert system. We carried out an experiment to investigate how system performance and empathetic design promotes user experience, and we also explored how those factors apply to different users with high and low expertise. Fourteen participants who majored in automatic control with a basic understanding of industrial automation devices took part in the study. During the experiment, the participants were instructed to repair a UV control cabinet with the help of the fault diagnosis expert system. The system has four levels of system performance (high, medium, low, and all-errors) * two levels of empathetic feature (standard design vs. empathetic design). After each task, the participants filled out a questionnaire to evaluate their experience. The results showed a beneficial effect of both system performance and empathetic design. Also, the interactive effect indicates that for the system with qualified performance, the empathetic design enhanced user experience; while for the system with all-error performance, the empathetic design no longer helped. In addition, the empathetic design played a better role among inexperienced users, while experienced users tended to be more sensitive to changes in system performance. &nbsp;</p

    The Cueing Effect in Retrieval of Expertise: Designing for Future Intelligent Knowledge Management System.

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    Along with the rapid technological developments in the past few decades, human work is becoming more knowledge-based, and professional expertise is becoming even more important. In this way, effective methods to retrieve and transfer such expertise are greatly needed. Prior research has found that pictures can be used as visual cues for supporting general memory retrieval, but whether this effect can be used to support professional expertise retrieval is not fully understood. The aim of the present study is to explore whether the picture cues can support the retrieval of professional expertise in a typical mechanical fault diagnosis task. Sixteen postgraduates who majored in mechanics with vehicle repair experience took part in the study. On the first day, they were trained for 1.5&nbsp;h on a simulated vehicle maintenance and repair task. After that, they were asked to accomplish three fault diagnosis tasks. On the next day, they participated in a 30-min expertise retrieval test. In the test, they were presented with or without picture cues (i.e., key-picture-cue, random-picture-cue, and without cues) and then answered questions to measure their memory over yesterday&rsquo;s operations. The results showed that participants retrieved more accurately with picture-cues compared to the scenario without the cues, and the accuracy in the key-picture-cues scenario was higher than the random-picture-cues scenario. These results show a robust cueing effect in the retrieval of expertise in fault diagnosis operations and indicated a potential application of expertise retrieval and transfer when designing an intelligent knowledge management system in the future.</p

    Carbon nanotubes/carbon paper composite electrode for sensitive detection of catechol in the presence of hydroquinone

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    The fabrication and application of carbon nanotubes/carbon paper (CNTs/CP) composite electrochemical sensors are reported. This sensing platform allows the sensitive determination of catechol in the range of 1 μM to 100 μM with a detection limit of 0.29 μM. The catechol detection in tea samples demonstrates the applicability of this method. The present study explores an interesting and significant application of CNTs/CP composite in electroanalysis. Keywords: Carbon nanotubes/carbon paper, Electrochemical sensor, Catechol, Tea sample
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