6,608 research outputs found

    DISCUSSION OF THE EFFECTS OF RECESSION ON THE RURAL-FARM ECONOMY

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    Community/Rural/Urban Development,

    Quantization Noise Shaping for Information Maximizing ADCs

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    ADCs sit at the interface of the analog and digital worlds and fundamentally determine what information is available in the digital domain for processing. This paper shows that a configurable ADC can be designed for signals with non constant information as a function of frequency such that within a fixed power budget the ADC maximizes the information in the converted signal by frequency shaping the quantization noise. Quantization noise shaping can be realized via loop filter design for a single channel delta sigma ADC and extended to common time and frequency interleaved multi channel structures. Results are presented for example wireline and wireless style channels.Comment: 4 pages, 6 figure

    Communicating You Are Worth It in a Noisy Marketplace

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    This paper provides guidance and specific examples of common elements needed for communicating the value proposition of liberal arts colleges to prospective students and families. In an environment where the worth of a college degree is questioned daily by the public and the mainstream media, this paper demonstrates how strategies that are distinctive, rooted in research and complementary to the institutional brand are imperative for communicating the worth of an institution. The paper suggests tactics to develop the key partnerships needed and provides metrics for how leaders can assess their value proposition initiatives

    Caring for traumatised looked-after children: the costs and gains of caring

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    Research has evidenced variously the impact on those caring for traumatised people, such as wives of distressed police officers, partners of war veterans and trauma counsellors. However, there is a lack of research exploring the impact on foster parents (FPs) caring for traumatised looked-after children (LAC). This study aimed to explore FPs’ experiences of caring for traumatised LAC, including their understanding of the impact the trauma has on the young person and on themselves and their biological family. Eleven FPs were interviewed to elicit their personal experiences of caring for traumatised LAC and its impact on them, the young people and the FPs’ families. Transcripts were analysed using Interpretative Phenomenological Analysis (IPA). Six master-themes emerged from the data: emotional impact on foster parents, cognitive impact on foster parents, impact from the wider fostering system, impact on foster parents’ family and friends, foster parent coping and perceived understanding of the impact of trauma on LAC. These themes were linked to previous research and existing theoretical constructs, such as secondary trauma (ST), vicarious trauma (VT) and compassion satisfaction. Whilst all related experiences within each of the themes, participants differed between which themes dominated. FPs experience a variety of complex negative impacts from caring for traumatised LAC, that warrants further investigation and development of screening tools to measure potential ST/VT symptoms. However, several FPs reported a wealth of positive experiences from their role, which may or may not counteract these symptoms

    Exploring the lived experiences of suicide attempt survivors

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    Suicide is a major problem in society and remains a challenge for services. Approaches to suicidality occur across individual, inter-personal and socio-cultural levels. However, the dominant narrative remains a biomedical one. Excessive reliance on a biomedical approach is problematic as complex phenomena may be reduced to linear causes. Service user perspectives may highlight alternative understandings and interventions but can also be constrained by dominant cultural constructions. Accordingly, this study aimed to explore the cultural constructions which survivors drew on in narrating their experiences of suicidality. 11 attempt survivors who had recovered from suicidality were interviewed. A narrative analysis was conducted and highlighted a polyphony of survivor voices and cultural constructions. Attempt survivors drew on the dominant biomedical model to varying degrees, and accounts could be placed on a continuum of acceptance/rejection of this model. 6 stories (one for each point of the continuum) were explored in detail. All participants also related to alternative constructions of suicide including psychological, situational, interpersonal, moral, public and spiritual. Participants used constructions of suicide to justify their experiences. One previously unexplored voice to emerge was of suicidality as having been a positive experience. Results are discussed with respect to previous studies, narrative typologies of illness, clinical implications, limitations and future research

    Outlier Detection and Missing Value Estimation in Time Series Traffic Count Data: Final Report of SERC Project GR/G23180.

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    A serious problem in analysing traffic count data is what to do when missing or extreme values occur, perhaps as a result of a breakdown in automatic counting equipment. The objectives of this current work were to attempt to look at ways of solving this problem by: 1)establishing the applicability of time series and influence function techniques for estimating missing values and detecting outliers in time series traffic data; 2)making a comparative assessment of new techniques with those used by traffic engineers in practice for local, regional or national traffic count systems Two alternative approaches were identified as being potentially useful and these were evaluated and compared with methods currently employed for `cleaning' traffic count series. These were based on evaluating the effect of individual or groups of observations on the estimate of the auto-correlation structure and events influencing a parametric model (ARIMA). These were compared with the existing methods which included visual inspection and smoothing techniques such as the exponentially weighted moving average in which means and variances are updated using observations from the same time and day of week. The results showed advantages and disadvantages for each of the methods. The exponentially weighted moving average method tended to detect unreasonable outliers and also suggested replacements which were consistently larger than could reasonably be expected. Methods based on the autocorrelation structure were reasonably successful in detecting events but the replacement values were suspect particularly when there were groups of values needing replacement. The methods also had problems in the presence of non-stationarity, often detecting outliers which were really a result of the changing level of the data rather than extreme values. In the presence of other events, such as a change in level or seasonality, both the influence function and change in autocorrelation present problems of interpretation since there is no way of distinguishing these events from outliers. It is clear that the outlier problem cannot be separated from that of identifying structural changes as many of the statistics used to identify outliers also respond to structural changes. The ARIMA (1,0,0)(0,1,1)7 was found to describe the vast majority of traffic count series which means that the problem of identifying a starting model can largely be avoided with a high degree of assurance. Unfortunately it is clear that a black-box approach to data validation is prone to error but methods such as those described above lend themselves to an interactive graphics data-validation technique in which outliers and other events are highlighted requiring acceptance or otherwise manually. An adaptive approach to fitting the model may result in something which can be more automatic and this would allow for changes in the underlying model to be accommodated. In conclusion it was found that methods based on the autocorrelation structure are the most computationally efficient but lead to problems of interpretation both between different types of event and in the presence of non-stationarity. Using the residuals from a fitted ARIMA model is the most successful method at finding outliers and distinguishing them from other events, being less expensive than case deletion. The replacement values derived from the ARIMA model were found to be the most accurate

    Vegetation analysis in the Laramie Basin, Wyoming from ERTS-1 imagery

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    The author has identified the following significant results. The application of ERTS-1 imagery to vegetation mapping and identification was tested and confirmed by field checking. ERTS-1 imagery interpretation and density contour mapping allows definition of minute vegetation features and estimation of vegetative biomass and species composition. Large- and small-scale vegetation maps were constructed for test areas in the Laramie Basin and Laramie mountains of Wyoming. Vegetative features reflecting grazing intensity, moisture availability, changes within the growing season, cutting of hay crops, and plant community constituents in forest and grassland are discussed and illustrated. Theoretical considerations of scattering, sun angle, slope, and instrument aperture upon image and map resolution were investigated. Future suggestions for applications of ERTS-1 data to vegetative analysis are included

    Setar Modelling of Traffic Count Data.

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    As part of a SERC funded project investigating outlier detection and replacement with transport data, univariate Box-Jenkins (1976) models have already been successfully applied to traffic count series (see Redfern et al, 1992). However, the underlying assumption of normality for ARIMA models implies they are not ideally suited for time series exhibiting certain behavioural characteristics. The limitations of ARIMA models are discussed in some detail by Tong (1983), including problems with time irreversibility, non-normality, cyclicity and asymmetry. Data with irregularly spaced extreme values are unlikely to be modelled well by ARIMA models, which are better suited to data where the probability of a very high value is small. Tong (1983) argues that one way of modelling such non-normal behaviour might be to retain the general ARIMA framework and allow the white noise element to be non-gaussian. As an alternative he proposes abandoning the linearity assumption and defines a group of non linear structures, one of which is the Self-Exciting Threshold Autoregressive (SETAR) model. The model form is described in more detail below but basically consists of two (or more) piecewise linear models, with the time series "tripping" between each model according to its value with respect to a threshold point. The model is called "Self-Exciting" because the indicator variable determining the appropriate linear model for each piece of data is itself a function of the data series. Intuitively this means the mechanism driving the alternation between each model form is not an external input such as a related time series (other models can be defined where this exists), but is actually contained within the series itself. The series is thus Self-Exciting. The three concepts embedded within the SETAR model structure are those of the threshold, limit cycle and time delay, each of which can be illustrated by the diverse applications such models can take. The threshold can be defined as some point beyond which, if the data falls, the series structure changes inherently and so an alternative linear model form would be appropriate. In hydrology this is seen as the non-linearity of soil infiltration, where at the soil saturation point (threshold) a new model for infiltration would become appropriate. Limit cycles describe the stable cyclical phenomena which we sometimes observe within time series. The cyclical behaviour is stationary, ie consists of regular, sustained oscillations and is an intrinsic property of the data. The limit cycle phenomena is physically observable in the field of radio-engineering where a triode valve is used to generate oscillations (see Tong, 1983 for a full description). Essentially the triode value produces self-sustaining oscillations between emitting and collecting electrons, according to the voltage value of a grid placed between the anode and cathode (thereby acting as the threshold indicator). The third essential concept within the SETAR structure is that of the time delay and is perhaps intuitively the easiest to grasp. It can be seen within the field of population biology where many types of non-linear model may apply. For example within the cyclical oscillations of blowfly population data there is an inbuilt "feedback" mechanism given by the hatching period for eggs, which would give rise to a time delay parameter within the model. For some processes this inherent delay may be so small as to be virtually instantaneous and so the delay parameter could be omitted. In general time series Tong (1983) found the SETAR model well suited to the cyclical nature of the Canadian Lynx trapping series and for modelling riverflow systems (Tong, Thanoon & Gudmundsson, 1984). Here we investigate their applicability with time series traffic counts, some of which have exhibited the type of non-linear and cyclical characteristics which could undermine a straightforward linear modelling process

    Assessing functional novelty of PSI structures via structure-function analysis of large and diverse superfamilies

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    The structural genomics initiatives have had as one of their aims to improve our understanding of protein function by providing representative structures for many structurally uncharacterised protein families. As suggested by the recent assessment of the Protein Structure Initiative (Structural Genomics Initiative, funded by the NIH), doubts have arisen as to whether Structural Genomics as initially planned were really beneficial to our understanding of biological issues, and in particular of protein function.
A few protein domain superfamilies have been shown to account for unexpectedly large numbers of proteins encoded in fully sequenced genomes. These large superfamilies are generally very diverse, spanning a wide range of functions, both in terms of molecular activities and biological processes. Some of these superfamilies, such as the Rossmann-fold P-loop nucleotide hydrolases or the TIM-barrel glycosidases, have been the subject of extensive structural studies which in turn have shed light on how evolution of the sequence and structure properties produce functional diversity amongst homologues. Recently, the Structure-Function Linkage Database (SFLD) has been setup with the aim of helping the study of structure-function correlations in such superfamilies. Since the evolutionary success of these large superfamilies suggests biological importance, several Structural Genomics Centers have focused on providing full structural coverage for representatives of all sequence families in these superfamilies.
In this work we evaluate structure/function diversity in a set of these large superfamilies and attempt to assess the quality and quantity of biological information gained from Structural Genomics.
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    FUEL-INSULATION TRADEOFFS FOR ARKANSAS BROILER HOUSES

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    Livestock Production/Industries,
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