Metrical Ambiguity in the Scherzo of Brahms's String Sextet, Op. 18

2021 ◽  
Vol 8 (1) ◽  
pp. 41-60
Author(s):  
Clifton Boyd
Keyword(s):  
Analysis Model ◽  
Metrical Structure ◽  
Chamber Ensembles ◽  
Multiple Analysis ◽  
Over Time

This article explores the metrical and hypermetrical ambiguities present in the Scherzo of Brahms's String Sextet in B♭ major, Op. 18 (1859–60). Drawing upon Lerdahl and Jackendoff's metrical preference rules, Mirka's parallel multiple-analysis model, and Ito's fractional notation, I argue that each hearing of material from the opening phrase (at the beginning, during its first repeat, after the Trio, etc.) affords the possibility of a different hypermetrical experience. Furthermore, rather than the metrical structure becoming increasingly clear over time, there are a number of hypermetrical irregularities that can lead listeners to question their previous interpretations. The article concludes with suggestions on how chamber ensembles can utilize metrical analyses of this movement to inform their performances and create varied listening experiences.

scholarly journals BDS Satellite Clock Prediction Considering Periodic Variations

2021 ◽  
Vol 13 (20) ◽  
pp. 4058
Author(s):  
Lin Zhao ◽  
Nan Li ◽  
Hui Li ◽  
Renlong Wang ◽  
Menghao Li
Keyword(s):  
Fourier Transform ◽  
Prediction Model ◽  
Prediction Accuracy ◽  
Analysis Model ◽  
Satellite Clock ◽  
Periodic Term ◽  
Periodic Noise ◽  
Clock Prediction ◽  
The Impact ◽  
Over Time

The periodic noise exists in BeiDou navigation satellite system (BDS) clock offsets. As a commonly used satellite clock prediction model, the spectral analysis model (SAM) typically detects and identifies the periodic terms by the Fast Fourier transform (FFT) according to long-term clock offset series. The FFT makes an aggregate assessment in frequency domain but cannot characterize the periodic noise in a time domain. Due to space environment changes, temperature variations, and various disturbances, the periodic noise is time-varying, and the spectral peaks vary over time, which will affect the prediction accuracy of the SAM. In this paper, we investigate the periodic noise and its variations present in BDS clock offsets, and improve the clock prediction model by considering the periodic variations. The periodic noise and its variations over time are analyzed and quantified by short time Fourier transform (STFT). The results show that both the amplitude and frequency of the main periodic term in BDS clock offsets vary with time. To minimize the impact of periodic variations on clock prediction, a time frequency analysis model (TFAM) based on STFT is constructed, in which the periodic term can be quantified and compensated accurately. The experiment results show that both the fitting and prediction accuracy of TFAM are better than SAM. Compared with SAM, the average improvement of the prediction accuracy using TFAM of the 6 h, 12 h, 18 h and 24 h is in the range of 6.4% to 10% for the GNSS Research Center of Wuhan University (WHU) clock offsets, and 11.1% to 14.4% for the Geo Forschungs Zentrum (GFZ) clock offsets. For the satellites C06, C14, and C32 with marked periodic variations, the prediction accuracy is improved by 26.7%, 16.2%, and 16.3% for WHU clock offsets, and 29.8%, 16.0%, 21.0%, and 9.0% of C06, C14, C28, and C32 for GFZ clock offsets.

scholarly journals A longitudinal study of the stress of poor glucose control and diabetes distress

2019 ◽  
pp. 135910531989300
Author(s):  
Christina M Marengo ◽  
Benjamin D Aronson ◽  
Kelley J Sittner ◽  
Melissa L Walls
Keyword(s):  
Longitudinal Study ◽  
Indirect Effects ◽  
Glucose Control ◽  
Perceived Control ◽  
Blood Glucose Control ◽  
Diabetes Distress ◽  
Analysis Model ◽  
The Relationship ◽  
Over Time ◽  
Path Analysis Model

Poor glucose control can be viewed as a stressor, possibly promulgating diabetes distress. We examined the relationship between perceived blood glucose control and diabetes distress over time using a partially controlled cross-lagged path analysis model. After controlling for demographics, control at 6 months was directly related to change in distress at 12 months. Subsequently, distress at 12 months was directly related to change in control at 18 months. Both 6-month control and distress had significant indirect effects on 18-month control and distress. This demonstrates the nuanced bi-directional relationship between the stress of poor perceived control and diabetes distress.

scholarly journals Evaluation of DNA degradation and establishment of a degradation analysis model for Lepidoptera specimens

BioTechniques ◽  
2020 ◽  
Vol 68 (3) ◽  
pp. 138-147
Author(s):  
Yao Xu ◽  
XueYu Ren ◽  
HongBin Wang ◽  
Mei Wang ◽  
GuoHong Li
Keyword(s):  
Dna Sequences ◽  
Dna Degradation ◽  
Museum Specimens ◽  
Analysis Model ◽  
Preservation Method ◽  
Degradation Analysis ◽  
Fragment Distribution ◽  
Dna Fragment ◽  
Formalin Fixed ◽  
Over Time

Millions of museum specimens are integral to biodiversity studies; however, DNA degradation may limit the ability to obtain DNA sequences. In this study, a degradation analysis model for Lepidoptera specimens was established. Based on this model, we revealed the characteristics of DNA fragment distribution caused by external DNA damage factors during specimen preservation. We found that the degree of DNA degradation increased over time; DNA degradation of spread and dried adult specimens was significantly higher than that in the folded and formalin-fixed larval specimens. However, the effects of folding wings on DNA degradation and the effects of the preservation method/stage (formalin-fixed larval vs air-dried adult specimens) were different for different species.

scholarly journals Finding and Keeping the Beat: Neural Mechanisms Differ as Beat Perception Unfolds

2021 ◽  
Author(s):  
Daniel J. Cameron ◽  
Jessica A. Grahn
Keyword(s):  
Temporal Structure ◽  
Superior Temporal Gyrus ◽  
Anterior Insula ◽  
Neural Mechanisms ◽  
Prediction Errors ◽  
Dynamic Adjustment ◽  
Metrical Structure ◽  
Cortical Oscillations ◽  
Over Time

AbstractPerception of a regular beat is essential to our ability to synchronize movements to music in an anticipatory fashion. Beat perception requires multiple, distinct neural functions, corresponding to the perceptual stages that occur over time, including 1) detection that regularity is present (beat finding), 2) prediction of future regular events to enable anticipation (beat continuation), and 3) dynamic adjustment of predictions as the rhythmic stimulus changes (beat adjustment). The striatum has been shown to be crucial for beat perception generally, although it is unclear how, or whether, distinct regions of the striatum contribute to these different stages of beat perception. Here, we used fMRI to investigate the activity of striatal subregions during the different stages of beat perception. Participants listened to pairs of rhythms (polyrhythms) whose temporal structure induced distinct perceptual stages—finding, continuation, and adjustment of the beat. Dorsal putamen was preferentially active during beat finding, whereas the ventral putamen was preferentially active during beat adjustment. We also observed that anterior insula activity was sensitive to metrical structure (greater when polyrhythms were metrically incongruent than when they were congruent). These data implicate the dorsal putamen in the detection of regularity, possibly by detection of coincidences between cortical oscillations, and the ventral putamen in the adjustment of regularity perception, possibly by integration of prediction errors in ongoing beat predictions. Additionally, activity in the supramarginal and superior temporal gyri correlated with beat tapping performance, and activity in the superior temporal gyrus correlated with beat perception (performance on the Beat Alignment Test).

scholarly journals Metrical Rhythm Implicitly Orients Attention in Time as Indexed by Improved Target Detection and Left Inferior Parietal Activation

2014 ◽  
Vol 26 (3) ◽  
pp. 593-605 ◽  
Author(s):  
Deirdre Bolger ◽  
Jennifer T. Coull ◽  
Daniele Schön
Keyword(s):  
Parietal Cortex ◽  
Visual Target ◽  
Relative Strength ◽  
Metrical Structure ◽  
Attentional Resources ◽  
Inferior Parietal Cortex ◽  
Independent Variable ◽  
Auditory Cortices ◽  
And Behavior ◽  
Over Time

When we direct attentional resources to a certain point in time, expectation and preparedness is heightened and behavior is, as a result, more efficient. This future-oriented attending can be guided either voluntarily, by externally defined cues, or implicitly, by perceived temporal regularities. Inspired by dynamic attending theory, our aim was to study the extent to which metrical structure, with its beats of greater or lesser relative strength, modulates attention implicitly over time and to uncover the neural circuits underlying this process of dynamic attending. We used fMRI to investigate whether auditory meter generated temporal expectancies and, consequently, how it affected processing of auditory and visual targets. Participants listened to a continuous auditory metrical sequence and pressed a button whenever an auditory or visual target was presented. The independent variable was the time of target presentation with respect to the metrical structure of the sequence. Participants' RTs to targets occurring on strong metrical positions were significantly faster than responses to events falling on weak metrical positions. Events falling on strong beats were accompanied by increased activation of the left inferior parietal cortex, a region crucial for orienting attention in time, and, by greater functional connectivity between the left inferior parietal cortex and the visual and auditory cortices, the SMA and the cerebellum. These results support the predictions of the dynamic attending theory that metrical structure with its relative strong and weak beats modulates attentional resources over time and, in turn, affects the functioning of both perceptual and motor preparatory systems.

scholarly journals Microblog topic evolution computing based on LDA algorithm

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 509-516 ◽  
Author(s):  
Feng Jian ◽  
Wang Yajiao ◽  
Ding Yuanyuan
Keyword(s):  
Latent Dirichlet Allocation ◽  
Evolutionary Relationship ◽  
Analysis Model ◽  
Calculation Algorithm ◽  
Topic Extraction ◽  
Topic Evolution ◽  
Evolution Analysis ◽  
Similarity Calculation ◽  
Relationship Of ◽  
Over Time

Abstract Research on topic evolution of Microblog is an effective way to analyze network public opinions. This paper proposes a method for mining changing of Microblog topics with time, and realizes topic evolution through topic extraction and topic relevance calculation. Firstly, latent Dirichlet allocation (LDA) model is used to automatically extract topics from different time slices; secondly, a similarity calculation algorithm is designed to calculate relevance of topic content through normalization of similarities among characteristic words and co-occurrence relations, to get evolutionary relationship among sub-topics of different time slices; thirdly, using probability distribution of blog article-topic to calculate topic intensity in each time slice, and then gets evolutionary relationship of topic intensity over time. Experiments show that the proposed topic evolution analysis model can effectively detect the evolution of topic content and intensity of real blogs.

scholarly journals Patent Keyword Analysis using Time Series and Copula Models

2019 ◽  
Vol 9 (19) ◽  
pp. 4071 ◽  
Author(s):  
Kim ◽  
Yoon ◽  
Hwang ◽  
Jun
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Patent Data ◽  
Analysis Model ◽  
Copula Models ◽  
Keyword Analysis ◽  
Logit Function ◽  
Patent Documents ◽  
Major Factors ◽  
Over Time

The technological keywords extracted from patent documents have much information about a developed technology. We can understand the technological structure of a product by examining the results of patent analysis. So far, much research has been done on patent data analysis. The technological keywords of patent documents contain representative information on the developed technology. As such, the patent keyword is one of the most important factors in patent data analysis. In this paper, we propose a patent data analysis model combining a integer valued time series model and copula direction dependence for integer valued patent keyword analysis over time. Most patent keywords are frequency values and keywords often change over time. However, the existing patent keywords analysis works do not account for two major factors: integer value and time. For modeling integer valued keyword data with time factor, we use a copula directional dependence model based on marginal regression with a beta logit function and integer valued generalized autoregressive conditional heteroskedasticity model. Using the proposed model, we find technological trends and relations in the target technological domain. To illustrate the performance and implication of our paper, we carry out experiments using the patent documents applied and registered by Apple company. This study contributes to the effective planning for the research and development of technologies by utilizing the evolution of technology over time.

scholarly journals Prevalence of Differentiated Thyroid Cancer in Autopsy Studies Over Six Decades: A Meta-Analysis

2016 ◽  
Vol 34 (30) ◽  
pp. 3672-3679 ◽  
Author(s):  
Luis Furuya-Kanamori ◽  
Katy J.L. Bell ◽  
Justin Clark ◽  
Paul Glasziou ◽  
Suhail A.R. Doi
Keyword(s):  
Thyroid Cancer ◽  
Regression Model ◽  
Fixed Effects ◽  
Differentiated Thyroid Cancer ◽  
Meta Analysis ◽  
Error Variance ◽  
Time Effect ◽  
Analysis Model ◽  
Prevalence Odds Ratio ◽  
Over Time

Purpose Differentiated thyroid cancer (DTC) incidence has been reported to have increased three- to 15-fold in the past few decades. It is unclear whether this represents overdiagnosis or a true increase in incidence. Therefore, the current study aimed to estimate the prevalence of incidental DTC in published autopsy series and determine whether this prevalence has been increasing over time. Materials and Methods PubMed, Embase, and Web of Science were searched from inception to December 2015 for relevant studies. Two authors searched for all autopsy studies that had included patients with no known history of thyroid pathology and reported the prevalence of incidental DTC (iDTC). Two authors independently extracted the data, and discrepancies were resolved by another author. The pooled prevalence of iDTC was assessed using a fixed-effects meta-analysis model with robust error variance. The time effect was studied using an inverse-variance weighted logit-linear regression model with robust error variance and a time variable. Results Thirty-five studies, conducted between 1949 and 2007, met the inclusion criteria and contributed 42 data sets and 12,834 autopsies. The prevalence of iDTC among the partial and whole examination subgroups was 4.1% (95% CI, 3.0% to 5.4%) and 11.2% (95% CI, 6.7% to 16.1%), respectively. Once the intensiveness of thyroid examination was accounted for in the regression model, the prevalence odds ratio stabilized from 1970 onward, and no time effect was observed. Conclusion The current study confirms that iDTC is common, but the observed increasing incidence is not mirrored by prevalence within autopsy studies and, therefore, is unlikely to reflect a true population-level increase in tumorigenesis. This strongly suggests that the current increasing incidence of iDTC most likely reflects diagnostic detection increasing over time.

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