Variance In Frequency Research Articles

Tachycardias Classification via the Generalized Mean Frequency and Generalized Frequency Variance of Electrocardiograms

Tachycardias Classification via the Generalized Mean Frequency and Generalized Frequency Variance of Electrocardiograms

Men’s participation in anti-violence activism: frequency and relationships with demographic characteristics and history of sexual harassment perpetration

PurposeThe purpose of this study is to examine men’s engagement in anti-sexual violence activism, including the frequency of their participation, whether demographic correlates, as well as a history of sexual harassment perpetration, relate to frequency, and the extent to which those correlates explain variation in frequency.Design/methodology/approachData for this cross-sectional study were collected in 2020; participants were 474 men, 18–40 years of age, who live in the USA.FindingsDescriptive findings show that in the past year, about two-thirds of the men engaged in at least one of the behaviors related to anti-violence activism examined here but with relatively low frequency. Hierarchical regression modeling showed that several of men’s demographic characteristics were significantly related to an increase in frequency, including sexual minoritized identity, education, mother’s education and being a father/parent, as well as past year sexual harassment perpetration in a fourth model. Overall, these variables explained approximately 22% of the variance in frequency of activism.Research limitations/implicationsThe sample is not representative of the US population. There is potential for the frequency of activism and engagement to be explained by individuals’ access to opportunities for activism.Practical implicationsThis paper discusses implications for practitioners who want to engage men in anti-violence activism.Social implicationsEngaging men in anti-violence activism is critical to end sexual violence.Originality/valueThis study responds to the call for investigations of bystander intervention to include pro-active helping, outside of intervention in high-risk situations for violence and to examine such beyond college students.

The influence of environmental and task constraint interaction on skilled behaviour in Australian Football

ABSTRACT The design of sports practice environments can be informed through data collected and analysed according to principles of the constraints-led approach. In this study, three manipulated environmental (area per player, number of players and team outnumber) and two task (activity objective and disposal limitations) constraints were measured during professional Australian Football training activities (n = 112) to determine their relationship with skilled behaviour. Linear regression modelling of the five manipulated constraints explained 68% of the variance in disposal frequency but only 22% in skill efficiency. Activities with scoring objectives, limited to kicking or which permitted all disposals, reduced the disposal frequency per player. Activities which permitted all disposals were also weakly, negatively associated with skill efficiency. A Classification Based on Association analysis measured the interaction between manipulated constraints and their relationships with possession time and pressure. When compared to the null model, the analysis improved pressure classification accuracy by 5.9% and did not improve possession time classification accuracy. This indicates skills were often performed under varying spatial and temporal constraints during many of the training activities. This study presents multivariate analytical methods which consider constraint interaction, enhancing how practitioners can evaluate and inform training design in sport.

Recognition of Fault State of RV Reducer Based on self-organizing feature map Neural Network

In order to accurately evaluate the working state of RV reducer, a fault identification method based on the fault identification model established by Self-Organizing Feature Map (SOM) Neural Network is proposed. Firstly, the data measured by the RV reducer test platform are analyzed by wavelet to obtain the wavelet coefficient. Then, combined with the efficiency data of RV reducer, the mean square frequency, center of gravity frequency and frequency variance of the two groups of data are calculated after Fourier transform and power spectrum analysis. After optimization, several eigenvalues are obtained. The eigenvalues are input into the competitive neural network and SOM neural network to establish the fault identification model. Finally, the results of the fault identification model established by the competitive neural network and SOM neural network are compared. The prediction results show that the fault identification model established by SOM neural network can effectively determine the working state of RV reducer.

Emotion classification on eye-tracking and electroencephalograph fused signals employing deep gradient neural networks

Emotion produces complex neural processes and physiological changes under appropriate event stimulation. Physiological signals have the advantage of better reflecting a person’s actual emotional state than facial expressions or voice signals. An electroencephalogram (EEG) is a signal obtained by collecting, amplifying, and recording the human brain’s weak bioelectric signals on the scalp. The eye-tracking (E.T.) signal records the potential difference between the retina and the cornea and the potential generated by the eye movement muscle. Furthermore, the different modalities of physiological signals will contain various information representations of human emotions. Finding this different modal information is of great help to get higher recognition accuracy. The E.T. and EEG signals are synchronized and fused in this research, and an effective deep learning (DL) method was used to combine different modalities. This article proposes a technique based on a fusion model of the Gaussian mixed model (GMM) with the Butterworth and Chebyshev signal filter. Features extraction on EEG and E.T. are subsequently calculated. Secondly, the self-similarity (SSIM), energy (E), complexity (C), high order crossing (HOC), and power spectral density (PSD) for EGG, and electrooculography power density estimation ((EOG-PDE), center gravity frequency (CGF), frequency variance (F.V.), root mean square frequency (RMSF) for E.T. are selected hereafter; the max–min method is applied for vector normalization. Finally, a deep gradient neural network (DGNN) for EEG and E.T. multimodal signal classification is proposed. The proposed neural network predicted the emotions under the eight emotions event stimuli experiment with 88.10% accuracy. For the evaluation indices of accuracy (Ac), precision (Pr), recall (Re), F-measurement (Fm), precision–recall (P.R.) curve, true-positive rate (TPR) of receiver operating characteristic curve (ROC), the area under the curve (AUC), true-accept rate (TAR), and interaction on union (IoU), the proposed method also performs with high efficiency compared with several typical neural networks including the artificial neural network (ANN), SqueezeNet, GoogleNet, ResNet-50, DarkNet-53, ResNet-18, Inception-ResNet, Inception-v3, and ResNet-101.

Brainstem Correlates of Pathological Laughter and Crying Frequency in ALS.

Pseudobulbar affect is a disorder of emotional expression commonly observed in amyotrophic lateral sclerosis (ALS), presenting as episodes of involuntary laughter, or crying. The objective of the current study was to determine the association between frequency of pathological laughter and crying (PLC) episodes with clinical features, cognitive impairment, and brainstem pathology. Thirty-five sporadic ALS patients underwent neuropsychological assessment, with a subset also undergoing brain imaging. The Center for Neurological Study Lability Scale (CNS-LS) was used to screen for presence and severity of pseudobulbar affect (CNS-LS ≥ 13) and frequency of PLC episodes. Presence of pseudobulbar affect was significantly higher in bulbar onset ALS (p = 0.02). Frequency of PLC episodes was differentially associated with cognitive performance and brainstem integrity. Notably pathological laughter frequency, but not crying, showed a significant positive association with executive dysfunction on the Trail Making Test B-A (R2 = 0.14, p = 0.04). Similarly, only pathological laughter frequency demonstrated a significant negative correlation with gray matter volume of the brainstem (R2 = 0.46, p < 0.01), and mean fractional anisotropy of the superior cerebellar peduncles (left: R2 = 0.44, p < 0.01; right: R2 = 0.44, p < 0.01). Hierarchical regression indicated brainstem imaging in combination with site of symptom onset explained 73% of the variance in pathological laughter frequency in ALS. The current findings suggest emotional lability is underpinned by degeneration across distinct neural circuits, with brainstem integrity critical in the emergence of pathological laughter.

Building a Model to Predict Sexual Assault Victimization Frequency Among Undergraduate Women.

Previous research has identified several factors, including sexual risk behaviors, alcohol consumption, sexual refusal assertiveness, impulse control difficulties, drinking to cope, and sex to cope, as being associated with sexual assault victimization. Data were collected from 465 adult, undergraduate women, and analyzed using structural equation modeling to determine how these variables related to one another. Results showed that together, these factors predicted 17.1% of the variance in victimization frequency. These findings may help future researchers better understand the etiology of sexual assault victimization on college campuses and prove crucial to the development of future intervention programs which reduce victimization.

Otantik Liderliğin Örgütsel Vatandaşlık ve ÖrgütselAdanmışlık Üzerindeki Etkisinin İncelenmesi: Trabzon Örneği (Investigation of the Effect of Authentic Leadership on Organizational Citizenship and Organizational Commitment: Case of Trabzon)

Purpose - The aim of this study is to examine the effect of authentic leadership perceptions of hotel business employees on organizational citizenship and organizational commitment behaviors, which are deemed as the positive organizational behaviors. Design/methodology/approach – Within the scope of the study, a field research was carried out in the municipality certified hotel businesses operating in Trabzon and data were collected with the help of survey technique. The survey consists of three scales, authentic leadership, organizational citizenship, and organizational commitment and demographic questions. The research sample consists of 303 employees. Frequency distribution, T-test, variance analysis, factor analysis, correlation and simple linear regression analysis were performed on the data. Findings - As a result of correlation analysis, it was found out that there is a low-level significant relationship between authentic leadership, organizational citizenship, and organizational commitment. As a result of the regression analysis, it was detected that authentic leadership perception has a positive effect on organizational citizenship behavior and organizational commitment behavior. Additionally, according to the results of the T-test and analysis of variance, there are significant differences between marital status and age groups and organizational commitment behavior, and there are significant differences between receiving tourism education and organizational citizenship behavior. Discussion - According to the findings, there is a positive and significant relationship between authentic leadership, organizational citizenship, and organizational commitment. In this context, it may be commented that as the authentic leadership perception levels of the employees working in the municipality certified hotel businesses in Trabzon increase, so do the levels of organizational citizenship and organizational commitment behavior. The results obtained in this study support the findings of studies conducted in different fields in the literature.

Divergence of a genomic island leads to the evolution of melanization in a halophyte root fungus

Understanding how organisms adapt to extreme living conditions is central to evolutionary biology. Dark septate endophytes (DSEs) constitute an important component of the root mycobiome and they are often able to alleviate host abiotic stresses. Here, we investigated the molecular mechanisms underlying the beneficial association between the DSE Laburnicola rhizohalophila and its host, the native halophyte Suaeda salsa, using population genomics. Based on genome-wide Fst (pairwise fixation index) and Vst analyses, which compared the variance in allele frequencies of single-nucleotide polymorphisms (SNPs) and copy number variants (CNVs), respectively, we found a high level of genetic differentiation between two populations. CNV patterns revealed population-specific expansions and contractions. Interestingly, we identified a ~20 kbp genomic island of high divergence with a strong sign of positive selection. This region contains a melanin-biosynthetic polyketide synthase gene cluster linked to six additional genes likely involved in biosynthesis, membrane trafficking, regulation, and localization of melanin. Differences in growth yield and melanin biosynthesis between the two populations grown under 2% NaCl stress suggested that this genomic island contributes to the observed differences in melanin accumulation. Our findings provide a better understanding of the genetic and evolutionary mechanisms underlying the adaptation to saline conditions of the L. rhizohalophila–S. salsa symbiosis.

Genetic diversity and effective population sizes of thirteen Indian cattle breeds

BackgroundThe genetic structure of a diverse set of 15 Indian indigenous breeds and non-descript indigenous cattle sampled from eight states was examined, based on 777 k single nucleotide polymorphism (SNP) genotypes obtained on 699 animals, with sample sizes ranging from 17 to 140 animals per breed. To date, this is the largest and most detailed assessment of the genetic diversity of Indian cattle breeds.ResultsAdmixture analyses revealed that 109 of the indigenous animals analyzed had more than 1% Bos taurus admixture of relatively recent origin. Pure indigenous animals were defined as having more than 99% Bos indicus ancestry. Assessment of the genetic diversity within and between breeds using principal component analyses, F statistics, runs of homozygosity, the genomic relationship matrix, and maximum likelihood clustering based on allele frequencies revealed a low level of genetic diversity among the indigenous breeds compared to that of Bos taurus breeds. Correlations of SNP allele frequencies between breeds indicated that the genetic variation among the Bos indicus breeds was remarkably low. In addition, the variance in allele frequencies represented less than 1.5% between the Indian indigenous breeds compared to about 40% between Bos taurus dairy breeds. Effective population sizes (Ne) increased during a period post-domestication, notably for Ongole cattle, and then declined during the last 100 generations. Although we found that most of the identified runs of homozygosity are short in the Indian indigenous breeds, indicating no recent inbreeding, the high FROH coefficients and low FIS values point towards small population sizes. Nonetheless, the Ne of the Indian indigenous breeds is currently still larger than that of Bos taurus dairy breeds.ConclusionsThe changes in the estimates of effective population size are consistent with domestication from a large native population followed by consolidation into breeds with a more limited population size. The surprisingly low genetic diversity among Indian indigenous cattle breeds might be due to their large Ne since their domestication, which started to decline only 100 generations ago, compared to approximately 250 to 500 generations for Bos taurus dairy cattle.

Co-ordinated grid forming control of AC-side-connected energy storage systems for converter-interfaced generation

Grid forming control of converter interfaced generation (CIG) requires some form of energy storage to be coupled with the generation. Energy storage systems (ESSs) can be coupled to the CIG either on the DC or the AC side of the power converter. When placed on the DC side, the ESS can provide damping of the variability in the generation but would require significant modification to the wind turbine hardware. The solution with an ESS connected to the AC side is simpler to implement with existing wind turbines but fails to provide damping of the CIG generation. This paper proposes a grid forming control strategy, based on virtual synchronous generator (VSG) control, which allows the ESS installed at the AC-side of the converter to have the same features and dynamic behaviour as those obtained from placement on the DC-side of the converter. In addition, the proposed control can also limit the exchanged power of the ESS within its rating for a safe operation. The proposed control is validated via a detailed Electro-Magnetic Transient (EMT) model and its impact on the grid is quantified via the case study of the All-Island Irish transmission system. Simulation results show that only a small ESS capacity can ensure that the frequency variance satisfies the grid code requirement even in the situation of a very high CIG penetration.

New Approach to Laser Characterization Using Delayed Self-Heterodyne Interferometry

A new technique to measure phase noise properties of highly coherent lasers based on delayed self-heterodyne interferometer (DSHI) is suggested where the Allan variance of the beat note frequency is obtained via digital signal processing and then used to determine laser linewidth and phase noise properties. This method is capable of determining both white frequency noise and flicker-noise contributions and has been used to characterize various types of lasers. A simple numerical model generalizing previous analytical results has been developed and verified. The corresponding requirements imposed on the DSHI optical delay are consistent with numerical modeling results. The measurement results are in agreement with our previous experiments based on direct heterodyning of the same lasers. The technique is particularly suitable for real-time monitoring of the laser phase noise over long periods of time, which is useful for testing and engineering of highly coherent lasers.

Respiratory gating in patients with lung carcinoma undergoing radiotherapy

AbstractAim:This study aims to compare the gating signals of patients with lung cancer recorded during the planning computed tomography scan with the ones recorded during treatment fractions. The results provide insights into how representative the respiratory signals from the planning scan are for radiation dose partitioning.Materials and methods:The amplitude and frequency of the respiratory signals of 29 patients with lung carcinoma were analysed and compared with the amplitude and frequency of those recorded during their planning scans. Moreover, a cross-correlation analysis was performed between the difference between the planning scan and fractions and features from the planning scan.Results:Two patients showed significantly different amplitude and frequency during treatment fractions compared to those from the planning scan. These patients showed low variances in frequency and amplitude during the different fractions. The difference between planning scan and fractions is correlated with the variances within the planning scan.Findings:Respiratory signals can differ between the planning scan and the fractions. In this case, a new planning scan may be beneficial. The respiratory signals from the planning scan may be predictive of whether the planning scan will be representative and usable as a control measure during radiotherapy fractions.

Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes

Self-paced treadmills are being used more frequently to study humans walking with their self-selected gaits on a range of slopes. There are multiple options to purchase a treadmill with a built-in controller, or implement a custom written self-paced controller, which raises questions about how self-paced controller affect treadmill speed and gait biomechanics on multiple slopes. This study investigated how different self-paced treadmill controller sensitivities affected gait parameters and variability on decline, level, and incline slopes. We hypothesized that increasing self-paced controller sensitivity would increase gait variability on each slope. We also hypothesized that detrended variability could help mitigate differences in variability that arise from differences in speed fluctuations created by the self-paced controllers. Ten young adults walked on a self-paced treadmill using three controller sensitivities (low, medium, and high) and fixed speeds at three slopes (decline, -10°; level, 0°; incline, +10°). Within each slope, average walking speeds and spatiotemporal gait parameters were similar regardless of self-paced controller sensitivity. With higher controller sensitivities on each slope, speed fluctuations, speed variance, and step length variance increased whereas step frequency variance and step width variance were unaffected. Detrended variance was not affected by controller sensitivity suggesting that detrending variability helps mitigate differences associated with treadmill speed fluctuations. Speed-trend step length variances, however, increased with more sensitive controllers. Further, detrended step length variances were similar for self-paced and fixed speed walking, whereas self-paced walking included substantial speed-trend step length variance not present in fixed speed walking. In addition, regardless of the self-paced controller, subjects walked fastest on the level slope with the longest steps, narrowest steps, and least variance. Overall, our findings suggest that separating gait variability into speed-trend and detrended variability could be beneficial for interpreting gait variability among multiple self-paced treadmill studies and when comparing self-paced walking with fixed speed walking.

The timing of human adaptation from Neanderthal introgression.

Admixture has the potential to facilitate adaptation by providing alleles that are immediately adaptive in a new environment or by simply increasing the long-term reservoir of genetic diversity for future adaptation. A growing number of cases of adaptive introgression are being identified in species across the tree of life, however the timing of selection, and therefore the importance of the different evolutionary roles of admixture, is typically unknown. Here, we investigate the spatio-temporal history of selection favoring Neanderthal-introgressed alleles in modern human populations. Using both ancient and present-day samples of modern humans, we integrate the known demographic history of populations, namely population divergence and migration, with tests for selection. We model how a sweep placed along different branches of an admixture graph acts to modify the variance and covariance in neutral allele frequencies among populations at linked loci. Using a method based on this model of allele frequencies, we study previously identified cases of adaptive Neanderthal introgression. From these, we identify cases in which Neanderthal-introgressed alleles were quickly beneficial and other cases in which they persisted at low frequency for some time. For some of the alleles that persisted at low frequency, we show that selection likely independently favored them later on in geographically separated populations. Our work highlights how admixture with ancient hominins has contributed to modern human adaptation and contextualizes observed levels of Neanderthal ancestry in present-day and ancient samples.

The motivation and factors influencing visits to small urban parks in Shanghai, China

In densely populated cities with high-rise buildings, large green spaces are a limited resource, and it is hard to visit large green spaces frequently due to long distance from places of residence. Small Urban Green Space (SUGS) in dense city areas might contribute to satisfy the need for everyday experiences of outdoor areas, but the study on SUGS use is limited, in particular in Asian contexts.The purpose of the study is to examine the effects of socio-demographic factors, personal factors, spatial attributes of residence, and satisfaction with park features on the use of SUGS and sources of motivation for visiting SUGS. Data were collected through face-to-face survey, and were analyzed using a hierarchical regression model. Results showed that relaxation and rest (36 %), physical exercise (23 %), and meeting friends (21 %) were the three most widespread reasons for SUGS use. The results indicated that socio-demographic factors, personal factors, spatial attributes of residence and park features factors explained 23 %, 2%, 25.6 % and 3% of the total variance in frequency of park visitation, respectively. Age, being willing to spend time in nature, with child under 7 years, noise and facility were positively correlated with SUGS use. Income,distance from home to the park, and residential green spaces were negatively correlated with SUGS use.Our findings are expected to assist urban planners in creating guidelines to better utilize SUGS.

Text Classification Using Novel Term Weighting Scheme-Based Improved TF-IDF for Internet Media Reports

With the rapid development of the internet technology, a large amount of internet text data can be obtained. The text classification (TC) technology plays a very important role in processing massive text data, but the accuracy of classification is directly affected by the performance of term weighting in TC. Due to the original design of information retrieval (IR), term frequency-inverse document frequency (TF-IDF) is not effective enough for TC, especially for processing text data with unbalanced distributions in internet media reports. Therefore, the variance between the DF value of a particular term and the average of all DFsDF¯, namely, the document frequency variance (ADF), is proposed to enhance the ability in processing text data with unbalanced distribution. Then, the normal TF-IDF is modified by the proposed ADF for processing unbalanced text collection in four different ways, namely, TF-IADF, TF-IADF+, TF-IADFnorm, and TF-IADF+norm. As a result, an effective model can be established for the TC task of internet media reports. A series of simulations have been carried out to evaluate the performance of the proposed methods. Compared with TF-IDF on state-of-the-art classification algorithms, the effectiveness and feasibility of the proposed methods are confirmed by simulation results.

Global adaptation complicates the interpretation of genome scans for local adaptation.

Spatially varying selection promotes variance in allele frequencies, increasing genetic differentiation between the demes of a metapopulation. For that reason, outliers in the genome‐wide distribution of summary statistics measuring genetic differentiation, such as FST, are often interpreted as evidence for alleles that contribute to local adaptation. However, theoretical studies have shown that in spatially structured populations the spread of beneficial mutations with spatially uniform fitness effects can also induce transient genetic differentiation. In recent years, numerous empirical studies have suggested that such species‐wide, or global, adaptation makes a substantial contribution to molecular evolution. In this perspective, we discuss how commonly such global adaptation may influence the genome‐wide distribution of FST and generate genetic differentiation patterns, which could be mistaken for local adaptation. To illustrate this, we use forward‐in‐time population genetic simulations assuming parameters for the rate and strength of beneficial mutations consistent with estimates from natural populations. We demonstrate that the spread of globally beneficial mutations in parapatric populations may frequently generate FST outliers, which could be misinterpreted as evidence for local adaptation. The spread of beneficial mutations causes selective sweeps at flanking sites, so in some cases, the effects of global versus local adaptation may be distinguished by examining patterns of nucleotide diversity within and between populations in addition to FST. However, when local adaptation has been only recently established, it may be much more difficult to distinguish from global adaptation, due to less accumulation of linkage disequilibrium at flanking sites. Through our discussion, we conclude that a large fraction of FST outliers that are presumed to arise from local adaptation may instead be due to global adaptation.

Variance Normalised Features for Language and Dialect Discrimination

This paper proposes novel features for automated language and dialect identification that aim to improve discriminative power by ensuring that each element of the feature vector has a normalised contribution to inter-class variance. The method firstly computes inter- and intra-class frequency variance statistics and then distributes the overall spectral variance across spectral regions which are sized to contain near-equal-variance difference. Spectral features are average pooled within regions to obtain variance normalised features (VNFs). The proposed VNFs are low complexity drop-in replacements for MFCC, SDC, PLP or other input features used for speech-related tasks. In this paper, they are evaluated in three types of system, against MFCCs, for two data-constrained language and dialect identification tasks. VNFs demonstrate good results, comfortably outperforming MFCCs at most dimension sizes, and yielding particularly good performance for the most challenging data-constrained 3s utterance length in the LID task.

An Islanded Microgrid Droop Control using Henry Gas Solubility Optimization

Coordination of various distributed generation (DG) units is required to meet the growing demand for electricity. Several control strategies have been developed to operate parallel-connected inverters for microgrid load sharing. Among these techniques, due to the lack of essential communication links between parallel-connected inverters to coordinate the DG units within a microgrid, the droop control method has been generally accepted in the scientific community. This paper discusses the microgrid droop controller during islanding using the Henry Gas Solubility Optimization (HGSO). The most important goals of droop control in the islanded mode of operation are the frequency and voltage control of microgrid and proper power sharing between distributed generations. The droop controller has been designed using HGSO to optimally choose PI gains and droop control coefficients in order to obtain a better microgrid output response during islanding. Simulation results indicate that the droop controller using HGSO improves the efficiency of micro-grid power by ensuring that variance in microgrid frequency and voltage regulation and effective power sharing occurs whenever micro-grid island mode or when variation in load occurs.