New Directions in Subband Coding

Two very different subband coders are described. The first is a modified dynamic bit-allocation-subband coder (D-SBC) designed for variable rate coding situations and easily adaptable to noisy channel environments. It can operate at rates as low as 12 kb/s and still give good quality speech. The second coder is a 16-kb/s waveform coder, based on a combination of subband coding and vector quantization (VQ-SBC). The key feature of this coder is its short coding delay, which makes it suitable for real-time communication networks. The speech quality of both coders has been enhanced by adaptive postfiltering. The coders have been implemented on a single AT&T DSP32 signal processo

Alaskan mammoth expeditions

p. 87-130, [9] leaves of plates (3 folded) : ill., maps ; 24 cm.Introduction -- Itinerary -- Fox Gulch, Klondike District -- The Palisades, Yukon River -- Nome coastal plain -- Keewalik River. Alder Creek. Native Gulch -- Eschscholtz Bay -- Fossil remains found imbedded in the historic bluff -- Remarks on the occurrence of fossils and recent bones on the shores of Eschscholtz Bay -- Ah-weeng-nuk River -- Buckland River -- Hotham Inlet and Selawik Lake -- Summary and conclusions. List of Pleistocene mammals."Literature on the Pleistocene mammals of, and their occurrence in, Alaska and the Klondike region, Canada": p. 128-130

Predicting growth rates of adult working boars in a commercial boar stud

There is almost no information on ideal growth rates for adult boars, but estimates can be made if the relationship between boar weight and age is known. Therefore, this study was aimed to predict growth rates in adult working boars in a commercial boar stud. A total of 214 adult working boars from two genetic lines in a commercial boar stud were individually weighed on a platform scale. Age of the boar was recorded at the time of weighing. A regression equation to predict boar weight as a function of age was developed by using PROC REG of SAS. The model was used to predict BW on a daily basis, and ADG was derived as the difference between two predicted BW values. Factorial estimates of daily ME requirement and feeding rates were determined. The energy requirement for weight gain was computed by using the predicted ADG as a guide in setting target weight gains. Results showed a positive curvilinear response (P\u3c0.01) to describe the relationship between boar weight and age. Predicted ADG decreased in a curvilinear manner as the boars aged. In conclusion, on-farm growth rates can be predicted effectively by relating weight with age, taken from a representative number of boars in a given farm population. These data can then be used to develop farm specific feeding programs or to set different growth curves for experimental purposes.; Swine Day, 2006, Kansas State University, Manhattan, KS, 200

Reflections on good practice in evaluating Violence Reduction Units: Experiences from across England and Wales

Internationally, interpersonal violence places huge burdens on the health, wellbeing and prosperity of society. In response to a notable increase in serious knife crime, in 2019, the UK Government awarded £35 million for the establishment of 18 Violence Reduction Units (VRUs) across England and Wales. There has been limited evaluation of community-level approaches for violence, with almost no published literature on the impact of VRUs. The article presents the approaches and experiences of two interdisciplinary teams of researchers from public health, psychology, criminology, and systems change, working as evaluators of four VRUs in England and Wales. The article describes the value of adopting a whole-system approach to evaluations, outlines good practice in evaluating VRUs, and elicits challenges to developing and embedding evaluation within complex systems

Assessing unmodified 70-mer oligonucleotide probe performance on glass-slide microarrays

BACKGROUND: Long oligonucleotide microarrays are potentially more cost- and management-efficient than cDNA microarrays, but there is little information on the relative performance of these two probe types. The feasibility of using unmodified oligonucleotides to accurately measure changes in gene expression is also unclear. RESULTS: Unmodified sense and antisense 70-mer oligonucleotides representing 75 known rat genes and 10 Arabidopsis control genes were synthesized, printed and UV cross-linked onto glass slides. Printed alongside were PCR-amplified cDNA clones corresponding to the same genes, enabling us to compare the two probe types simultaneously. Our study was designed to evaluate the mRNA profiles of heart and brain, along with Arabidopsis cRNA spiked into the labeling reaction at different relative copy number. Hybridization signal intensity did not correlate with probe type but depended on the extent of UV irradiation. To determine the effect of oligonucleotide concentration on hybridization signal, 70-mers were serially diluted. No significant change in gene-expression ratio or loss in hybridization signal was detected, even at the lowest concentration tested (6.25 μm). In many instances, signal intensity actually increased with decreasing concentration. The correlation coefficient between oligonucleotide and cDNA probes for identifying differentially expressed genes was 0.80, with an average coefficient of variation of 13.4%. Approximately 8% of the genes showed discordant results with the two probe types, and in each case the cDNA results were more accurate, as determined by real-time PCR. CONCLUSIONS: Microarrays of UV cross-linked unmodified oligonucleotides provided sensitive and specific measurements for most of the genes studied

Evaluation of clustering algorithms for gene expression data

BACKGROUND: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped together according to their expression profiles using one of numerous clustering algorithms that exist in the statistics and machine learning literature. A closely related problem is that of selecting a clustering algorithm that is "optimal" in some sense from a rather impressive list of clustering algorithms that currently exist. RESULTS: In this paper, we propose two validation measures each with two parts: one measuring the statistical consistency (stability) of the clusters produced and the other representing their biological functional congruence. Smaller values of these indices indicate better performance for a clustering algorithm. We illustrate this approach using two case studies with publicly available gene expression data sets: one involving a SAGE data of breast cancer patients and the other involving a time course cDNA microarray data on yeast. Six well known clustering algorithms UPGMA, K-Means, Diana, Fanny, Model-Based and SOM were evaluated. CONCLUSION: No single clustering algorithm may be best suited for clustering genes into functional groups via expression profiles for all data sets. The validation measures introduced in this paper can aid in the selection of an optimal algorithm, for a given data set, from a collection of available clustering algorithms

μ-CS: An extension of the TM4 platform to manage Affymetrix binary data

<p>Abstract</p> <p>Background</p> <p>A main goal in understanding cell mechanisms is to explain the relationship among genes and related molecular processes through the combined use of technological platforms and bioinformatics analysis. High throughput platforms, such as microarrays, enable the investigation of the whole genome in a single experiment. There exist different kind of microarray platforms, that produce different types of binary data (images and raw data). Moreover, also considering a single vendor, different chips are available. The analysis of microarray data requires an initial preprocessing phase (i.e. normalization and summarization) of raw data that makes them suitable for use on existing platforms, such as the TIGR M4 Suite. Nevertheless, the annotations of data with additional information such as gene function, is needed to perform more powerful analysis. Raw data preprocessing and annotation is often performed in a manual and error prone way. Moreover, many available preprocessing tools do not support annotation. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of microarray data are needed.</p> <p>Results</p> <p>The paper presents <it>μ</it>-CS (Microarray Cel file Summarizer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix binary data. <it>μ</it>-CS is based on a client-server architecture. The <it>μ</it>-CS client is provided both as a plug-in of the TIGR M4 platform and as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data, avoiding the manual invocation of external tools (e.g. the Affymetrix Power Tools), the manual loading of preprocessing libraries, and the management of intermediate files. The <it>μ</it>-CS server automatically updates the references to the summarization and annotation libraries that are provided to the <it>μ</it>-CS client before the preprocessing. The <it>μ</it>-CS server is based on the web services technology and can be easily extended to support more microarray vendors (e.g. Illumina).</p> <p>Conclusions</p> <p>Thus <it>μ</it>-CS users can directly manage binary data without worrying about locating and invoking the proper preprocessing tools and chip-specific libraries. Moreover, users of the <it>μ</it>-CS plugin for TM4 can manage Affymetrix binary files without using external tools, such as APT (Affymetrix Power Tools) and related libraries. Consequently, <it>μ</it>-CS offers four main advantages: (i) it avoids to waste time for searching the correct libraries, (ii) it reduces possible errors in the preprocessing and further analysis phases, e.g. due to the incorrect choice of parameters or the use of old libraries, (iii) it implements the annotation of preprocessed data, and finally, (iv) it may enhance the quality of further analysis since it provides the most updated annotation libraries. The <it>μ</it>-CS client is freely available as a plugin of the TM4 platform as well as a standalone application at the project web site (<url>http://bioingegneria.unicz.it/M-CS</url>).</p