Daily light on the daily path;

Mode of access: Internet.

Andy the acrobat : or, Out with the greatest show on earth.

Mode of access: Internet.

Gleams from Paul's prison, or, Studies for the daily life in the Epistle to the Philippians /

Includes bibliographical references.

The Daily union history of Atlantic City and County, New Jersey. Containing sketches of the past and present of Atlantic City and County ...

"Biographies": p. 443-517.

Planning and producing the musical show.

Mode of access: Internet.

Public knowledge beyond journalism : infotainment, satire and Australian television

This thesis examines the changing relationships between television, politics, audiences and the public sphere. Premised on the notion that mediated politics is now understood “in new ways by new voices” (Jones, 2005: 4), and appropriating what McNair (2003) calls a “chaos theory” of journalism sociology, this thesis explores how two different contemporary Australian political television programs (Sunrise and The Chaser’s War on Everything) are viewed, understood, and used by audiences. In analysing these programs from textual, industry and audience perspectives, this thesis argues that journalism has been largely thought about in overly simplistic binary terms which have failed to reflect the reality of audiences’ news consumption patterns. The findings of this thesis suggest that both ‘soft’ infotainment (Sunrise) and ‘frivolous’ satire (The Chaser’s War on Everything) are used by audiences in intricate ways as sources of political information, and thus these TV programs (and those like them) should be seen as legitimate and valuable forms of public knowledge production. It therefore might be more worthwhile for scholars to think about, research and teach journalism in the plural: as a series of complementary or antagonistic journalisms, rather than as a single coherent entity.

News blogs and citizen journalism : new directions for e-journalism

Even for a casual observer of the journalistic industry it is becoming difficult to escape the conclusion that journalism is entering a time of crisis. At the same time that revenues and readerships for traditional publications from newspapers to broadcast news are declining, journalistic content is being overtaken by a flotilla of alternative options ranging from the news satire of The Daily Show in the United States to the citizen journalism of South Korea’s OhmyNews and a myriad of other news blogs and citizen journalism Websites. Worse still, such new competitors with the products of the journalism industry frequently take professional journalists themselves to task where their standards have appeared to have slipped, and are beginning to match the news industry’s incumbents in terms of insight and informational value: recent studies have shown, for example, that avid Daily Show viewers are as if not better informed about the U.S. political process as those who continue to follow mainstream print or television news (see e.g. Fox et al., 2007). The show’s host Jon Stewart – who has consistently maintained his self-description as a comedian, not a journalist – even took the fight directly to the mainstream with his appearance on CNN’s belligerent talk show Crossfire, repeatedly making the point that the show’s polarised and polarising ‘left vs. right’ format was “hurting” politics in America (the show disappeared from CNN’s line-up a few months after Stewart’s appearance; Stewart, 2004). Similarly, news bloggers and citizen journalists have shown persistence and determination both in uncovering political and other scandals, and in highlighting the shortcomings of professional journalism as it investigates and reports on such scandals.

On display : Ravensthorpe Wildflower Show and the assembly of place

Each September since 1983 in the rural Shire of Ravensthorpe, Western Australia, volunteers collect samples of up to 700 wildfl ower species which are then displayed in the Ravensthorpe Senior Citizens Centre from 9.00 am to 4.00 pm daily over a two-week period. This chapter offers an ethnographic interpretation of this enduring annual event focusing on the 25th show held in 2007. The study contributes to understanding the complex and nuanced role of local wildflower shows in shaping and supporting rural senses of place and of community. Importantly, this particular type of festival, and more specifically this local instance, foregrounds a less-remarked aspect of festivals, namely the (re)production and celebration of place-specific knowledge through validations of, and interconnections between, scientific flower classification and emotive experience. This feature, encapsulated in Laurel Lamperd’s poem above, invites consideration of the ways in which local place knowledge and the simultaneous (re)production of ‘place’ are constituted by a complex layering of rational, objective ways of knowing and those which emphasize emotions, aesthetics and memories. This rural wildflower show not only mobilises both the rational and the emotional in ‘making sense of the world’ for local residents and for tourists, but also offers insights into the production of place as constituted in and through relations between humans and non-human life forms (Cloke & Jones, 2001; Conradson, 2005; see also Chapter 6).

CBCT image guidance in head and neck irradiation: The impact of daily and weekly imaging protocols

Purpose This study evaluated the impact of a daily and weekly image-guided radiotherapy protocols in reducing setup errors and setting of appropriate margins in head and neck cancer patients. Materials and methods Interfraction and systematic shifts for the hypothetical day 1–3 plus weekly imaging were extrapolated from daily imaging data from 31 patients (964 cone beam computed tomography (CBCT) scans). In addition, residual setup errors were calculated by taking the average shifts in each direction for each patient based on the first three shifts and were presumed to represent systematic setup error. The clinical target volume (CTV) to planning target volume (PTV) margins were calculated using van Herk formula and analysed for each protocol. Results The mean interfraction shifts for daily imaging were 0·8, 0·3 and 0·5 mm in the S-I (superior-inferior), L-R (left-right) and A-P (anterior-posterior) direction, respectively. On the other hand the mean shifts for day 1–3 plus weekly imaging were 0·9, 1·8 and 0·5 mm in the S-I, L-R and A-P direction, respectively. The mean day 1–3 residual shifts were 1·5, 2·1 and 0·7 mm in the S-I, L-R and A-P direction, respectively. No significant difference was found in the mean setup error for the daily and hypothetical day 1–3 plus weekly protocol. However, the calculated CTV to PTV margins for the daily interfraction imaging data were 1·6, 3·8 and 1·4 mm in the S-I, L-R and A-P directions, respectively. Hypothetical day 1–3 plus weekly resulted in CTV–PTV margins of 5, 4·2 and 5 mm in the S-I, L-R and A-P direction. Conclusions The results of this study show that a daily CBCT protocol reduces setup errors and allows setup margin reduction in head and neck radiotherapy compared to a weekly imaging protocol.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5A degrees x 2.5A degrees grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO - June to October), non-monsoon season (JFMAMND - January to May, November, December) and for the entire year (''Annual''). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5A degrees grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.