Speech Enhancement Using Modulation-Domain Kalman Filtering with Active Speech Level Normalized Log-Spectrum Global Priors

We describe a single-channel speech enhancement algorithm that is based on modulation-domain Kalman filtering that tracks the inter-frame time evolution of the speech logpower spectrum in combination with the long-term average speech log-spectrum. We use offline-trained log-power spectrum global priors incorporated in the Kalman filter prediction and update steps for enhancing noise suppression. In particular, we train and utilize Gaussian mixture model priors for speech in the log-spectral domain that are normalized with respect to the active speech level. The Kalman filter update step uses the log-power spectrum global priors together with the local priors obtained from the Kalman filter prediction step. The logspectrum Kalman filtering algorithm, which uses the theoretical phase factor distribution and improves the modeling of the modulation features, is evaluated in terms of speech quality. Different algorithm configurations, dependent on whether global priors and/or Kalman filter noise tracking are used, are compared in various noise types

Blended learning in undergraduate dental education: a global pilot study.

AIMS: To explore the global trends in blended learning in undergraduate dental education during the COVID pandemic and during the recovery phase by engaging with the students and faculty and evaluate the implications for dental education in the post-COVID era. METHODS: It was a pilot cross-sectional study which employed a convenience sampling technique to recruit representatives of dental faculty and undergraduate students in 80 dental institutions globally. A previously validated questionnaire consisting of a combination of closed and open-ended items was used for data collection. Responses to these online questionnaires were processed and analysed using the R statistical computing environment. RESULTS: A total of 320 dental students and 169 faculty members from 47 different dental institutions participated in the study. Video and Live Online Tutorials were considered to be the most effective method of online learning followed by online question banks by both groups. Significant differences were noted between faculty and students regarding time spent and effectiveness of online teaching and learning, respectively, both before and after the start of COVID. The results highlight the faculty need to engage more closely with the students to address their learning needs. Finally, the participants provided several recommendations regarding the future development of teaching and learning strategies as well as assessments in the post-pandemic era. CONCLUSIONS: This is the first study which explores blended learning in dental education with participants from multiple institutions in different regions of the globe. Compared to the faculty, students considered online learning to be less interactive and preferred learning activities and all assessments to be delivered face-to-face. The results underscore the need to adapt teaching practices to suit the learning needs of the students

A mean field model for movement induced changes in the beta rhythm

In electrophysiological recordings of the brain, the transition from high amplitude to low amplitude signals are most likely caused by a change in the synchrony of underlying neuronal population firing patterns. Classic examples of such modulations are the strong stimulus-related oscillatory phenomena known as the movement related beta decrease (MRBD) and post-movement beta rebound (PMBR). A sharp decrease in neural oscillatory power is observed during movement (MRBD) followed by an increase above baseline on movement cessation (PMBR). MRBD and PMBR represent important neuroscientific phenomena which have been shown to have clinical relevance. Here, we present a parsimonious model for the dynamics of synchrony within a synaptically coupled spiking network that is able to replicate a human MEG power spectrogram showing the evolution from MRBD to PMBR. Importantly, the high-dimensional spiking model has an exact mean field description in terms of four ordinary differential equations that allows considerable insight to be obtained into the cause of the experimentally observed time-lag from movement termination to the onset of PMBR (~ 0.5 s), as well as the subsequent long duration of PMBR (~ 1-10 s). Our model represents the first to predict these commonly observed and robust phenomena and represents a key step in their understanding, in health and disease

Factors associated with timeliness of post-primary care referral, diagnosis and treatment for lung cancer: population-based, data-linkage study

BACKGROUND: The NHS Cancer Plan for England set waiting time targets for cancer referral (14 days from GP referral to first hospital appointment) and treatment (31 days from diagnosis, 62 days from urgent GP referral). Interim diagnostic intervals can also be calculated. The factors that influence timely post-primary care referral, diagnosis and treatment for lung cancer are not known. METHODS: Northern and Yorkshire Cancer Registry, Hospital Episode Statistics and lung cancer audit data sets were linked. Logistic regression was used to investigate the factors (socioeconomic position, age, sex, histology, co-morbidity, year of diagnosis, stage and performance status (PS)) that may influence the likelihood of referral, diagnosis and treatment within target, for 28 733 lung cancer patients diagnosed in 2006–2010. RESULTS: Late-stage, poor PS and small-cell histology were associated with a higher likelihood of post-primary care referral, diagnosis and treatment within target. Older patients were significantly less likely to receive treatment within the 31-day (odds ratio (OR)=0.79, 95% confidence interval (CI) 0.69–0.91) and 62-day target (OR=0.80, 95% CI 0.67–0.95) compared with younger patients. CONCLUSIONS: Older patients waited longer for treatment and this may be unjustified. Patients who appeared ill were referred, diagnosed and treated more quickly and this ‘sicker quicker’ effect may cancel out system socioeconomic inequalities that might result in longer time intervals for more deprived patients

Asteroseismology and Interferometry

Asteroseismology provides us with a unique opportunity to improve our understanding of stellar structure and evolution. Recent developments, including the first systematic studies of solar-like pulsators, have boosted the impact of this field of research within Astrophysics and have led to a significant increase in the size of the research community. In the present paper we start by reviewing the basic observational and theoretical properties of classical and solar-like pulsators and present results from some of the most recent and outstanding studies of these stars. We centre our review on those classes of pulsators for which interferometric studies are expected to provide a significant input. We discuss current limitations to asteroseismic studies, including difficulties in mode identification and in the accurate determination of global parameters of pulsating stars, and, after a brief review of those aspects of interferometry that are most relevant in this context, anticipate how interferometric observations may contribute to overcome these limitations. Moreover, we present results of recent pilot studies of pulsating stars involving both asteroseismic and interferometric constraints and look into the future, summarizing ongoing efforts concerning the development of future instruments and satellite missions which are expected to have an impact in this field of research.Comment: Version as published in The Astronomy and Astrophysics Review, Volume 14, Issue 3-4, pp. 217-36

Uncoupling Protein-4 (UCP4) Increases ATP Supply by Interacting with Mitochondrial Complex II in Neuroblastoma Cells

Mitochondrial uncoupling protein-4 (UCP4) protects against Complex I deficiency as induced by 1-methyl-4-phenylpyridinium (MPP+), but how UCP4 affects mitochondrial function is unclear. Here we investigated how UCP4 affects mitochondrial bioenergetics in SH-SY5Y cells. Cells stably overexpressing UCP4 exhibited higher oxygen consumption (10.1%, p<0.01), with 20% greater proton leak than vector controls (p<0.01). Increased ATP supply was observed in UCP4-overexpressing cells compared to controls (p<0.05). Although state 4 and state 3 respiration rates of UCP4-overexpressing and control cells were similar, Complex II activity in UCP4-overexpressing cells was 30% higher (p<0.05), associated with protein binding between UCP4 and Complex II, but not that of either Complex I or IV. Mitochondrial ADP consumption by succinate-induced respiration was 26% higher in UCP4-overexpressing cells, with 20% higher ADP:O ratio (p<0.05). ADP/ATP exchange rate was not altered by UCP4 overexpression, as shown by unchanged mitochondrial ADP uptake activity. UCP4 overexpression retained normal mitochondrial morphology in situ, with similar mitochondrial membrane potential compared to controls. Our findings elucidate how UCP4 overexpression increases ATP synthesis by specifically interacting with Complex II. This highlights a unique role of UCP4 as a potential regulatory target to modulate mitochondrial Complex II and ATP output in preserving existing neurons against energy crisis

Thigh-length compression stockings and DVT after stroke

Controversy exists as to whether neoadjuvant chemotherapy improves survival in patients with invasive bladder cancer, despite randomised controlled trials of more than 3000 patients. We undertook a systematic review and meta-analysis to assess the effect of such treatment on survival in patients with this disease