Evaluation of the Importance of Time-Frequency Contributions to Speech Intelligibility in Noise

Recent studies on binary masking techniques make the assumption that each time-frequency (T-F) unit contributes an equal amount to the overall intelligibility of speech. The present study demonstrated that the importance of each T-F unit to speech intelligibility varies in accordance with speech content. Specifically, T-F units are categorized into two classes, speech-present T-F units and speech-absent T-F units. Results indicate that the importance of each speech-present T-F unit to speech intelligibility is highly related to the loudness of its target component, while the importance of each speech-absent T-F unit varies according to the loudness of its masker component. Two types of mask errors are also considered, which include miss and false alarm errors. Consistent with previous work, false alarm errors are shown to be more harmful to speech intelligibility than miss errors when the mixture signal-to-noise ratio (SNR) is below 0 dB. However, the relative importance between the two types of error is conditioned on the SNR level of the input speech signal. Based on these observations, a mask-based objective measure, the loudness weighted hit-false, is proposed for predicting speech intelligibility. The proposed objective measure shows significantly higher correlation with intelligibility compared to two existing mask-based objective measures

A stochastic model for the evolution of the web allowing link deletion

Recently several authors have proposed stochastic evolutionary models for the growth of the web graph and other networks that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the ``rich get richer'' phenomenon. We present a generalisation of the basic model by allowing deletion of individual links and show that it also gives rise to a power-law distribution. We derive the mean-field equations for this stochastic model and show that by examining a snapshot of the distribution at the steady state of the model, we are able to tell whether any link deletion has taken place and estimate the link deletion probability. Our model enables us to gain some insight into the distribution of inlinks in the web graph, in particular it suggests a power-law exponent of approximately 2.15 rather than the widely published exponent of 2.1

Molecular origins of transcriptional heterogeneity in diazotrophic Klebsiella oxytoca.

Phenotypic heterogeneity in clonal bacterial batch cultures has been shown for a range of bacterial systems; however, the molecular origins of such heterogeneity and its magnitude are not well understood. Under conditions of extreme low-nitrogen stress in the model diazotroph Klebsiella oxytoca, we found remarkably high heterogeneity of nifHDK gene expression, which codes for the structural genes of nitrogenase, one key enzyme of the global nitrogen cycle. This heterogeneity limited the bulk observed nitrogen-fixing capacity of the population. Using dual-probe, single-cell RNA fluorescent in situ hybridization, we correlated nifHDK expression with that of nifLA and glnK-amtB, which code for the main upstream regulatory components. Through stochastic transcription models and mutual information analysis, we revealed likely molecular origins for heterogeneity in nitrogenase expression. In the wild type and regulatory variants, we found that nifHDK transcription was inherently bursty, but we established that noise propagation through signaling was also significant. The regulatory gene glnK had the highest discernible effect on nifHDK variance, while noise from factors outside the regulatory pathway were negligible. Understanding the basis of inherent heterogeneity of nitrogenase expression and its origins can inform biotechnology strategies seeking to enhance biological nitrogen fixation. Finally, we speculate on potential benefits of diazotrophic heterogeneity in natural soil environments

Unique terminal regions and specific deletions of the segmented double-stranded RNA genome of Alternaria alternata virus 1, in the proposed family Alternaviridae

Alternaria alternata virus 1 (AaV1) has been identified in the saprophytic fungus Alternaria alternata strain EGS 35-193. AaV1 has four genomic double-stranded (ds)RNA segments (dsRNA1-4) packaged in isometric particles. The 3' end of each coding strand is polyadenylated (36-50nt), but the presence of a cap structure at each 5' end has not previously been investigated. Here, we have characterized the AaV1 genome and found that it has unique features among the mycoviruses. We confirmed the existence of cap structures on the 5' ends of the AaV1 genomic dsRNAs using RNA dot blots with anti-cap antibodies and the oligo-capping method. Polyclonal antibodies against purified AaV1 particles specifically bound to an 82kDa protein, suggesting that this protein is the major capsid component. Subsequent Edman degradation indicated that the AaV1 dsRNA3 segment encodes the major coat protein. Two kinds of defective AaV1 dsRNA2, which is 2,794bp (844 aa) in length when intact, appeared in EGS 35-193 during subculturing, as confirmed by RT-PCR and northern hybridization. Sequence analysis revealed that one of the two defective dsRNA2s contained a 231bp deletion, while the other carried both the 231bp deletion and an additional 465bp deletion in the open reading frame. Both deletions occurred in-frame, resulting in predicted proteins of 767 aa and 612 aa. The fungal isolates carrying virions with the defective dsRNA2s showed impaired growth and abnormal pigmentation. To our best knowledge, AaV1 is the first dsRNA virus to be identified with both 5' cap and 3'poly(A) structures on its genomic segments, as well as the specific deletions of dsRNA2

Interactive effects of video, priming, and music on emotions and the needs underlying intrinsic motivation

Objectives: Emotions can enhance motivation towards a particular goal (Brehm, 1999), while activation of human motivation does not necessarily involve conscious processes (Bargh, 1990). The main purpose of the present study was to explore the impact of video, priming, and music on a range of emotion- and motivation-related variables, while the secondary purpose was to conduct a cross-cultural comparison. Design: A randomized controlled design was employed to address the interactive effects of video, priming, and music on emotions and motivation with reference to the circumplex theory of emotion. Methods: Participants comprised a convenience sample of 210 volunteers (English, n = 128; M = 20.0, SD = 4.7 years; Male, n = 65; Female, n = 63; Greek, n = 82, M = 23.3, SD = 2.4 years; Male, n = 59; Female, n = 23). A control condition and five experimental conditions were presented to participants in a counterbalanced order. The needs underlying intrinsic motivation were accessed using the Activity Feeling-state Scales (AFS; Reeve & Sickenius, 1994), while emotional states were assessed using adjectives from the Circumplex Model of Affect (Russell, 1980). Results: Findings showed that music had positive effects on emotional states and the psychological needs underlying intrinsic motivation. They also highlighted the positive effects of priming as a psychological intervention – particularly when presented through video and coupled with music. Conclusions: The study presents the state-of-the-art for the use of video, priming, and music in sport and includes recommendations for sport psychology practitioners and researchers

Clinical Significance and Biological Role of HuR in Head and Neck Carcinomas

Background. Hu-antigen R (HuR) is a posttranscriptional regulator of several target mRNAs, implicated in carcinogenesis. This review aims to present the current evidence regarding the biological role and potential clinical significance of HuR in head and neck carcinomas. Methods. The existing literature concerning HuR expression and function in head and neck carcinomas is critically presented and summarised. Results. HuR is expressed in the majority of the examined samples, showing higher cytoplasmic levels in malignant or premalignant cases. Moreover, HuR modulates several genes implicated in biological processes important for malignant transformation, growth, and invasiveness. HuR seems to be an adverse prognosticator in patients with OSCCs, whereas a correlation with a more aggressive phenotype is reported in several types of carcinomas. Conclusions. A consistent role of HuR in the carcinogenesis and progression of head and neck carcinomas is suggested; nevertheless, further studies are warranted to expand the present information

A stochastic evolutionary model for capturing human dynamics

The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in various contexts. Here we propose a generative model to capture the dynamics of survival analysis, traditionally employed in clinical trials and reliability analysis in engineering. We derive a general solution for the model in the form of a product, and then a continuous approximation to the solution via the renewal equation describing age-structured population dynamics. This enables us to model a wide range of survival distributions, according to the choice of the mortality distribution. We provide empirical evidence for the validity of the model from a longitudinal data set of popular search engine queries over 114 months, showing that the survival function of these queries is closely matched by the solution for our model with power-law mortality

Comparing Aspects Of The Process Quality In Six European Early Childhood Educational Settings

The European project ‘Early Change’ (http://earlychange.teithe.gr) attempts to evaluate the quality of early childhood education (ECE) environments of six European countries, Greece, Portugal, Finland, Denmark, Cyprus and Romania. The purpose of this paper is to compare the level of two dimensions of the process quality of these environments a) Space & Furnishings, and b) Personal Care Routines. Theorists, practitioners and researchers agree that in order to provide qualitative education to young children, one of the basic needs of all children must be met; that need is the protection of their health and their safety. A high quality early childhood education program must contain a safe and stimulating environment for the child (Lindsey, 1998). Such an environment includes indoor space, outdoor space, furniture, and room arrangement, and it is considered an integral part of a high quality early childhood program. 117 early educators from the six participating countries attended the training seminars about the evaluation of ECE quality using the Early Childhood Environmental Rating Scale-R (ECERS-R). The trained educators evaluated the 8 indicators of the subscale ‘space & furnishings’ and the six indicators of the subscale ‘personal care routines’ in approximately 600 early childhood classrooms from six European countries. The results of this study highlight the similarities and differences concerning the specific dimensions of the process quality of ECE environments in six European countries, and reflect the diversity of ECE environment across these countries. The findings of this study may provide a valuable insight to researchers and educational policy makers for an enhanced understanding of the cultural diversities and the strengthening of the common values and targets of the European Union

Developing Prognosis Tools to Identify Learning Difficulties in Children Using Machine Learning Technologies

The Mental Attributes Profiling System was developed in 2002 (Laouris and Makris, Proceedings of multilingual & cross-cultural perspectives on Dyslexia, Omni Shoreham Hotel, Washington, D.C, 2002), to provide a multimodal evaluation of the learning potential and abilities of young children’s brains. The method is based on the assessment of non-verbal abilities using video-like interfaces and was compared to more established methodologies in (Papadopoulos, Laouris, Makris, Proceedings of IDA 54th annual conference, San Diego, 2003), such as the Wechsler Intelligence Scale for Children (Watkins et al., Psychol Sch 34(4):309–319, 1997). To do so, various tests have been applied to a population of 134 children aged 7–12 years old. This paper addresses the issue of identifying a minimal set of variables that are able to accurately predict the learning abilities of a given child. The use of Machine Learning technologies to do this provides the advantage of making no prior assumptions about the nature of the data and eliminating natural bias associated with data processing carried out by humans. Kohonen’s Self Organising Maps (Kohonen, Biol Cybern 43:59–69, 1982) algorithm is able to split a population into groups based on large and complex sets of observations. Once the population is split, the individual groups can then be probed for their defining characteristics providing insight into the rationale of the split. The characteristics identified form the basis of classification systems that are able to accurately predict which group an individual will belong to, using only a small subset of the tests available. The specifics of this methodology are detailed herein, and the resulting classification systems provide an effective tool to prognose the learning abilities of new subjects