Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting

Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today’s automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database—a corpus containing emotionally colored conversations with a cognitive system for “Sensitive Artificial Listening”.     

Improvement of the muscle fractional multimodel for low-rate stimulation

Modeling of isometric contractions, due to motor unit (MU) stimulations of Peroneus digiti quarti and peroneus brevis rat muscles, is presented. The modeling is realized through a multimodel, which allows distinguishing asymmetric contractions and relaxation mechanisms for time domain identification. First, this paper compares two fractional functions and a rational transfer function that model each phase of IIA and IIB MU twitch. The advantages of using fractional functions are underlined, since the number of parameters are minimized. Indeed, fractional models, due to its infinite dimension nature, are particularly adapted not only to model complex systems with few parameters but also to obtain a real time exploitable model for a salamander robot simulator. Finally, muscle response for 10 Hz pulse stimulation shows non-stationary characteristics. A method, modeling the transient state of muscle responses and introducing time varying parameters, is presented.     

Recent advances in DNA sequencing methods - general principles of sample preparation

DNA sequencing has revolutionized biomedicine, and progress in the field has been unrelenting since it was invented over 30 years ago. The complete DNA sequence of the human genome was obtained as the culmination of a decade of work by a large number of scientists. Less than ten years later, so-called ‘next-generation’ instruments now make it possible for a single lab to produce the same amount of data in a week. But while the instruments are increasingly automated, upstream sample processing remains a challenge. Here I review the current state of the art in preparing genomic and RNA samples for high throughput sequencing.     

Statistical properties of the dichotomous noise generated in biochemical processes

Dichotomous noise detected with the help of various single-molecule techniques convincingly reveals the actual occurrence of a multitude of conformational substates composing the native state of proteins. The nature of the stochastic dynamics of transitions between these substates is determined by the particular statistical properties of the noise observed. These involve nonexponential and possibly oscillatory time decay of the second order autocorrelation function, its relation to the third order autocorrelation function, and a relationship to dwell-time distribution densities and their correlations. Processes gated by specific conformational substates are distinguished from those with fluctuating barriers. This study throws light on the intriguing matter of the possibility of multiple stepping of the myosin motor along the actin filament per ATP molecule hydrolyzed. Paper authored by participants of the international conference: International Workshop on Ionic Channels, Szczyrk, Poland, May 27 – June 01, 2007. Publication cost was covered by the organisers of this meeting.     

Determination of nitrie in human blood by combination of a specific sample preparation with high-performance anion-exchange chromatography and electrochemical detection

All photometric or HPLC methods described to date have been unable to detect nitrite, a reliable marker of NO synthase activity, in human blood because of its rapid metabolism within the erythrocytes. We now elaborate on method to prevent nitrite degradation during sample preparation which in combination with high-performance anion-exchange chromatography and electrochemical detection allows a sensitive measurement of nitrite. A linear current response in the concentration range of 10–1000 nmol/l nitrite was observed yielding a correlation coefficient of 0.99. In addition, the combination of the electrochemical with a UV detector allowed us to simultaneously quantify nitrate one analytical run, which is the end product of NO/nitrite metabolism. Basal levels for nitrate and nitrite in human blood were determined with 25±4 μmol/l and 578±116 nmol/l (n=8), respectively and thus were in the same concentration range as expected from NO measurement in saline perfused isolated organs or cultured endothelial cells. Therefore, the presented method may be used to assess activity of endothelial constitutive NO synthase in humans under physiological and pathophysiological conditions.     

Effect of different sample pretreatment methods on the concentrations of excitatory amino acids in cerebrospinal fluid determined by high-performance liquid chromatography

Using high-performance liquid chromatography (HPLC), the effect of different sample pretreatment methods on the concentrations of excitatory amino acids (EAAs, glutamate and aspartate) measured in cerebrospinal fluid (CSF) was investigated. The results showed that the measured values of glutamate and aspartate were constant when the samples were stored at -80 degrees C and then methanol was used for CSF deproteinization before assay; the values of glutamate (Glu) increased when 0.3 M perchloric acid was used for CSF deproteinization with the CSF subsequently being stored at -20 degrees C; the values of Glu changed when the samples were stored at -20 degrees C over 8 weeks with methanol subsequently being used for CSF deproteinization before assay. This reference data suggested that the CSF sample would be better stored at -80 degrees C. If the sample is stored at -20 degrees C over 8 weeks, the Glu values change with the storage time. If strong acidic reagents are used for precipitation of protein in the CSF sample and then stored at -20 degrees C, Glu values are abnormally increased. From this study, an accurate and sensitive reversed-phase high-performance liquid chromatographic method has been developed for anti-excitotoxicity therapy and thorough study of EAAs in a clinical setting.     

Semi-automated liquid--liquid back-extraction in a 96-well format to decrease sample preparation time for the determination of dextromethorphan and dextrorphan in human plasma

A semi-automated, 96-well based liquid-liquid back-extraction (LLE) procedure was developed and used for sample preparation of dextromethorphan (DEX), an active ingredient in many over-the-counter cough formulations, and dextrorphan (DOR), an active metabolite of DEX, in human plasma. The plasma extracts were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS-MS). The analytes were isolated from human plasma using an initial ether extraction, followed by a back extraction from the ether into a small volume of acidified water. The acidified water isolated from the back extraction was analyzed directly by LC-MS-MS, eliminating the need for a dry down step. A liquid handling system was utilized for all aspects of liquid transfers during the LLE procedure including the transfer of samples from individual tubes into a 96-well format, preparation of standards, addition of internal standard and the addition and transfer of the extraction solvents. The semi-automated, 96-well based LLE procedure reduced sample preparation time by a factor of four versus a comparable manually performed LLE procedure.     

Estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean

The use of small sample sizes in human and primate evolutionary research is commonplace. Estimating how well small samples represent the underlying population, however, is not commonplace. Because the accuracy of determinations of taxonomy, phylogeny, and evolutionary process are dependant upon how well the study sample represents the population of interest, characterizing the uncertainty, or potential error, associated with analyses of small sample sizes is essential. We present a method for estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean using small (n < 10) or very small (n ≤ 5) sample sizes. This method can be used by researchers to determine post hoc the probability that their sample is a meaningful approximation of the population parameter. We tested the method using a large craniometric data set commonly used by researchers in the field. Given our results, we suggest that sample estimates of the population mean can be reasonable and meaningful even when based on small, and perhaps even very small, sample sizes.     

Ultrasound-assisted digestion: a useful alternative in sample preparation

Ultrasound-assisted digestion is a promising alternative in the analysis of solid samples when either simple dissolution or direct analysis is not applicable. However, the field of application of ultrasonic sample digestion is still small in comparison with classical digestion alternatives and, particularly, with microwave-assisted digestion. This fact can be justified by the scant knowledge analytical chemists have about the advantages ultrasonic energy provides to digestion. Among these, the strict control at low temperatures of ultrasound applications allows the implementation of ultrasonic-assisted steps in biochemical analyses. In this connection, two specific biological applications, ultrasonic enzymatic digestion and assistance of ultrasound for cell disruption, are also reviewed.     

Relative importance of within-habitat environment,land use and spatial autocorrelations for determining odonate assemblages in rural reservoir ponds in Japan

To clarify the major factors affecting odonate assemblages in rural reservoir ponds among within-habitat environments, land use around ponds and spatial autocorrelation, we surveyed odonate adults (Zygoptera and Anisoptera) in 70 study ponds in Ibaraki Prefecture, Japan, during three sampling periods in 2005. Redundancy analyses (RDA) for these three factor groups were executed to determine their strength in explaining the odonate species composition. Their relative contributions were also evaluated by the method of variation partitioning. A total of 41 odonate species were recorded in the study ponds, and 24 of them, excluding rare species, were used for our analysis. Summed effects including all three factor groups explained approximately 39% of the variation in odonate species composition. We found that spatial autocorrelation was the most important, though the within-habitat environment and land use had comparable effects. We conclude that spatial autocorrelation should be considered in this type of analysis, though we could not clearly explain what caused such a spatial structure. Pond area and debris that had accumulated at the bottom of ponds were selected as the within-habitat environment, and the forests and paddy fields around ponds were selected for land use after the procedure of forward stepwise selection. These results suggest that the recent decrease of forests around the ponds has had a negative effect on the odonate assemblages.     

种群微卫星DNA分析中样本量对各种遗传多样性度量指标的影响

我们以中国飞蝗种群的微卫星遗传分析数据为例 ,评估了取样对种群遗传多样性指标的影响 ,结果显示 :样本大小与所观测到的每位点等位基因数、平均等位基因数及基因丰富度指数均呈显著正相关 ,而与期望杂合度无显著相关 ;微卫星位点多态性的高低直接影响所观测到的种群基因丰富度及其检测所需的样本量 ;对大多数种群遗传和分子生态学研究而言 ,30 - 5 0个个体是微卫星DNA分析所需要的最小样本量。基因丰富度经过稀疏法或多次随机抽样法校正后 ,可适用于瓶颈效应等种群历史数量变动的检测。另外 ,在研究中 ,还应避免采集时间的不同及样本的性比构成所可能造成的对种群遗传结构的影响     

Power analysis to determine sample size for monitoring vegetation change in salt marsh habitats

Numerous initiatives are underway throughout New England and elsewhere to quantify salt marsh vegetation change, mostly in response to habitat restoration, sea level rise, and nutrient enrichment. To detect temporal changes in vegetation at a marsh or to compare vegetation among different marshes with a degree of statistical certainty an adequate sample size is required. Based on sampling 1 m² vegetation plots from 11 New England salt marsh data sets, we conducted a power analysis to determine the minimum number of samples that were necessary to detect change between vegetation communities. Statistical power was determined for sample sizes of 5, 10, 15, and 20 vegetation plots at an alpha level of 0.05. Detection of subtle differences between vegetation data sets (e.g., comparing vegetation in the same marsh over two consecutive years) can be accomplished using a sample size of 20 plots with a reasonable probability of detecting a difference when one truly exists. With a lower sample size, and thus lower power, there is an increased probability of not detecting a difference when one exists (e.g., Type II error). However, if investigators expect to detect major changes in vegetation (e.g., such as those between an un-impacted and a highly impacted marsh) then a sample size of 5, 10, or 15 plots may be appropriate while still maintaining adequate power. Due to the relative ease of collecting vegetation data, we suggest a minimum sample size of 20 randomly located 1 m² plots when developing monitoring designs to detect vegetation community change of salt marshes. The sample size of 20 plots per New England salt marsh is appropriate regardless of marsh size or permanency (permanent or non-permanent) of the plots.