Time-scale and pitch modifications of speech signals and resynthesis from the discrete short-time Fourier transform

The modification methods described in this paper combine characteristics of PSOLA-based methods and algorithms that resynthesize speech from its short-time Fourier magnitude only. The starting point is a short-time Fourier representation of the signal. In the case of duration modification, portions, in voiced speech corresponding to pitch periods, are removed from or inserted in this representation. In the case of pitch modification, pitch periods are shortened or extended in this representation, and a number of pitch periods is inserted or removed, respectively. Since it is an important tool for both duration and pitch modification, the resynthesis-from-short-time-Fourier-magnitude-only method of Griffin and Lim (1984) and Griffin et al. (1984) is reviewed and adapted. Duration and pitch modification methods and their results are presented.\ud \u

The Analysis of Factors and Levels Associated with Lecturers’ Motivation and Job Satisfaction in University of Rwanda

It is difficult to expect good performance of students in universities without having a motivated lecturing staff. The study aimed to correlate the levels of lecturers’ motivation and job satisfaction and find out factors associated with. A cross-sectional study was conducted between February and April 2016. Structured online questionnaires of the content validity index of 0.9625 for Lecturers’ motivation and job satisfaction were used for data collection.  Seventy Lecturers from university of Rwanda participated in study. Collected data were organized and encoded into computer using the statistical package for social sciences (SPSS) 19th version. Frequencies, percentages, means and Pearson’ Linear Correlation Coefficient were used to analyze data. Means were interpreted as poor, fair, satisfactory and very satisfactory.  Lecturers’ motivation was fair and firstly affected by salary, classroom environment, incentives &promotions, code of conduct, social factors and cheer love of career. Job satisfaction was fair and highly affected by working conditions, financial rewards, workload and stress level, relation with supervisors, opportunity for advancement and respect co-workers. The correlation between levels of lecturers’ motivation and job satisfaction was significant with positive relationship of 82.1%. Lecturers’ Motivation and Job satisfaction were found to be low; all analyzed factors would be taken into consideration. Keywords: Lecturers’ motivation; Job satisfaction; Professional development; Learning environment

Induction of release and up-regulated gene expression of interleukin (IL)-8 in A549 cells by serine proteinases

BACKGROUND: Hypersecretion of cytokines and serine proteinases has been observed in asthma. Since protease-activated receptors (PARs) are receptors of several serine proteinases and airway epithelial cells are a major source of cytokines, the influence of serine proteinases and PARs on interleukin (IL)-8 secretion and gene expression in cultured A549 cells was examined. RESULTS: A549 cells express all four PARs at both protein and mRNA levels as assessed by flow cytometry, immunofluorescence microscopy and reverse transcription polymerase chain reaction (PCR). Thrombin, tryptase, elastase and trypsin induce a up to 8, 4.3, 4.4 and 5.1 fold increase in IL-8 release from A549 cells, respectively following 16 h incubation period. The thrombin, elastase and trypsin induced secretion of IL-8 can be abolished by their specific inhibitors. Agonist peptides of PAR-1, PAR-2 and PAR-4 stimulate up to 15.6, 6.6 and 3.5 fold increase in IL-8 secretion, respectively. Real time PCR shows that IL-8 mRNA is up-regulated by the serine proteinases tested and by agonist peptides of PAR-1 and PAR-2. CONCLUSION: The proteinases, possibly through activation of PARs can stimulate IL-8 release from A549 cells, suggesting that they are likely to contribute to IL-8 related airway inflammatory disorders in man

Molecular mechanisms of synaptic plasticity in adult mammalian sensory cortex

Experience-dependent changes in synaptic composition and function (synaptic plasticity) underlie many brain functions including learning and memory, formation of sensory maps, as well as the capability to recover from injury. Most of these functions decline with age, supporting the observation that synaptic plasticity is greater in juveniles than in adults. However, it has been known for some time that peripheral deafferentation in adult animals can induce large-scale reorganization of sensory cortex, which suggests that the adult cortex retains a level of synaptic plasticity that is typically masked by normal activity inputs. Here I present a series of experiments in the adult mammalian sensory cortex that examine the mechanisms and methods to enhance experience-dependent synaptic plasticity. The results showed: 1. Peripheral deafferentation of a single digit in the adult raccoon induces progressive modulation of excitation and inhibition in the deafferented somatosensory cortex that might be needed for the reorganization of receptive fields; 2. Visual deprivation in adult rats reverses three molecular mechanisms that have been correlated with the decrease in synaptic plasticity in adult cortex. These include the developmental increase in the level of inhibition relative to excitation, the development switch in NMDA receptor subunit composition from NR2b to NR2a, and the developmental decrease in tPA activity in visual cortex; 3.Visual deprivation rejuvenates ocular dominance plasticity in the adult visual cortex, and promotes the functional recovery of an eye deprived of vision from birth in adulthood. This work provides further understanding of the molecular mechanisms underlying experience-dependent cortical plasticity. In addition, it demonstrates that ocular dominance plasticity can be regulated throughout life, and proposes a non-invasive method to enhance synaptic plasticity in adult cortex

The Trapping and Characterization of a Single Hydrogen Molecule in a Continuously Tunable Nanocavity

Using inelastic electron tunneling spectroscopy with the scanning tunneling microscope (STM-IETS) and density functional theory calculations (DFT), we investigated properties of a single H2 molecule trapped in nanocavities with controlled shape and separation between the STM tip and the Au (110) surface. The STM tip not only serves for the purpose of characterization, but also is directly involved in modification of chemical environment of molecule. The bond length of H2 expands in the atop cavity, with a tendency of dissociation when the gap closes, whereas it remains unchanged in the trough cavity. The availability of two substantially different cavities in the same setup allows understanding of H2 adsorption on noble metal surfaces and sets a path for manipulating a single chemical bond by design.Comment: 11 pages, 4 figure

Integrated Sensing, Computation, and Communication: System Framework and Performance Optimization

Integrated sensing, computation, and communication (ISCC) has been recently considered as a promising technique for beyond 5G systems. In ISCC systems, the competition for communication and computation resources between sensing tasks for ambient intelligence and computation tasks from mobile devices becomes an increasingly challenging issue. To address it, we first propose an efficient sensing framework with a novel action detection module. It can reduce the overhead of computation resource by detecting whether the sensing target is static. Subsequently, we analyze the sensing performance of the proposed framework and theoretically prove its effectiveness with the help of the sampling theorem. Then, we formulate a sensing accuracy maximization problem while guaranteeing the quality-of-service (QoS) requirements of tasks. To solve it, we propose an optimal resource allocation strategy, in which the minimal resource is allocated to computation tasks, and the rest is devoted to sensing tasks. Besides, a threshold selection policy is derived. Compared with the conventional schemes, the results further demonstrate the necessity of the proposed sensing framework. Finally, a real-world test of action recognition tasks based on USRP B210 is conducted to verify the sensing performance analysis, and extensive experiments demonstrate the performance improvement of our proposal by comparing it with some benchmark schemes

Dramatic Increases of Soil Microbial Functional Gene Diversity at the Treeline Ecotone of Changbai Mountain.

The elevational and latitudinal diversity patterns of microbial taxa have attracted great attention in the past decade. Recently, the distribution of functional attributes has been in the spotlight. Here, we report a study profiling soil microbial communities along an elevation gradient (500-2200 m) on Changbai Mountain. Using a comprehensive functional gene microarray (GeoChip 5.0), we found that microbial functional gene richness exhibited a dramatic increase at the treeline ecotone, but the bacterial taxonomic and phylogenetic diversity based on 16S rRNA gene sequencing did not exhibit such a similar trend. However, the β-diversity (compositional dissimilarity among sites) pattern for both bacterial taxa and functional genes was similar, showing significant elevational distance-decay patterns which presented increased dissimilarity with elevation. The bacterial taxonomic diversity/structure was strongly influenced by soil pH, while the functional gene diversity/structure was significantly correlated with soil dissolved organic carbon (DOC). This finding highlights that soil DOC may be a good predictor in determining the elevational distribution of microbial functional genes. The finding of significant shifts in functional gene diversity at the treeline ecotone could also provide valuable information for predicting the responses of microbial functions to climate change

Mitigating Shortcuts in Language Models with Soft Label Encoding

Recent research has shown that large language models rely on spurious correlations in the data for natural language understanding (NLU) tasks. In this work, we aim to answer the following research question: Can we reduce spurious correlations by modifying the ground truth labels of the training data? Specifically, we propose a simple yet effective debiasing framework, named Soft Label Encoding (SoftLE). We first train a teacher model with hard labels to determine each sample's degree of relying on shortcuts. We then add one dummy class to encode the shortcut degree, which is used to smooth other dimensions in the ground truth label to generate soft labels. This new ground truth label is used to train a more robust student model. Extensive experiments on two NLU benchmark tasks demonstrate that SoftLE significantly improves out-of-distribution generalization while maintaining satisfactory in-distribution accuracy