Ruminations on war, culture war

To descry that this generation of artists has been in the midst of a war, a cultural war, sounds so obvious. After all, what generation in deeply reactionary times could not claim the same? However, who is struggling with whom and over what can often prove far more open than the popular polarities which pitch government, business, bureaucracy on one side and artists, performers, intellectuals on the other.  But what is it to say we on the one side are at war with the other? Is the war, culturally as much as militarily, limited or unconditional, intermittent or continuous, external or internal, declared or undeclared, defensive or aggressive? Is it a warfare aiming to annihilate or to annex, to conquer or to cleanse, to dominate or to displace, to eliminate or to expel, to impregnate or to enslave. In brief, warfare is waged in diverse ways with diverse goals as the brutally concise words of Thoukydides reveal when brooding upon stasis--the strife from 427 B.C. convulsing city after city in the great war between Athens and Sparta--as  the cause of many calamities--as happens and will always happen while human nature is what it is, though there may be different degrees of savagery, and, as different circumstances arise, the general rules will admit of some variety [Bk 3.82; 1972: 242).

Automatic rule induction in Arabic to English machine translation framework

This chapter addresses the exploitation of a supervised machine learning technique to automatically induce Arabic-to-English transfer rules from chunks of parallel aligned linguistic resources. The induced structural transfer rules encode the linguistic translation knowledge for converting an Arabic syntactic structure into a target English syntactic structure. These rules are going to be an integral part of an Arabic-English transfer-based machine translation. Nevertheless, a novel morphological rule induction method is employed for learning Arabic morphological rules that are applied in our Arabic morphological analyzer. To demonstrate the capability of the automated rule induction technique, we conducted rule-based translation experiments that use induced rules from a relatively small data set. The translation quality of the hybrid translation experiments achieved good results in terms of WER.

Focused ion beam milling of carbon nanotube yarns and bucky-papers : correlating their internal structure with their macro-properties

Focused ion beam (FIB) milling through carbon nanotube (CNT) yarns and bucky-papers followed by scanning electron microscopy has recently emerged as a powerful tool for eliciting details of their internal structure. The internal arrangement of CNTs in bucky-papers and yarns directly affects their performance and characteristics. Consequently this information is critical for further optimisation of these structures and to tailor their properties for specific applications. This chapter describes in detail FIB milling of CNT yarns and bucky-papers and gives a range of examples where FIB milling has enabled a better understanding of how processing conditions and treatments affect the internal structure. Emphasis is placed on how FIB milling elucidates the influence of fabrication conditions on the internal arrangement of CNTs and how this influences the material's macroscopic properties.

Effects of bone-specific physical activity, gender and maturity on tibial cross-sectional bone material distribution; a cross-sectional pQCT comparison of children and young adults aged 5-29 years

Growth is the opportune time to modify bone accrual. While bone adaptation is known to be dependent on local loading and consequent deformations (strain) of bone, little is known about the effects of sex, and bone-specific physical activity on location-specific cross-sectional bone geometry during growth. To provide more insight we examined bone traits at different locations around tibial cross sections, and along the tibia between individuals who vary in terms of physical activity exposure, sex, and pubertal status. Data from 304 individuals aged 5-29 years (172 male, 132 female) were examined. Peripheral quantitative computed tomography (pQCT) was applied at 4%, 14%, 38%, and 66% of tibial length. Maturity was established by estimating age at peak height velocity (APHV). Loading history was quantified with the bone-specific physical activity questionnaire (BPAQ). Comparisons, adjusted for height, weight and age were made between sex, maturity, and BPAQ tertile groups. Few to no differences were observed between sexes or BPAQ tertiles prior to APHV, whereas marked sexual dimorphism and differences between BPAQ tertiles were observed after APHV. Cross-sectional location-specific differences between BPAQ tertiles were not evident prior to APHV, whereas clear location-specificity was observed after APHV. In conclusion, the skeletal benefits of physical activity are location-specific in the tibia. The present results indicate that the peri- or post-pubertal period is likely a more favourable window of opportunity for enhancing cross-sectional bone geometry than pre puberty. Increased loading during the peri-pubertal period may enhance the bone of both sexes.

Affective, linguistic and topic patterns in online autism communities

Online communities offer a platform to support and discuss health issues. They provide a more accessible way to bring people of the same concerns or interests. This paper aims to study the characteristics of online autism communities (called Clinical) in comparison with other online communities (called Control) using data from 110 Live Journal weblog communities. Using machine learning techniques, we comprehensively analyze these online autism communities. We study three key aspects expressed in the blog posts made by members of the communities: sentiment, topics and language style. Sentiment analysis shows that the sentiment of the clinical group has lower valence, indicative of poorer moods than people in control. Topics and language styles are shown to be good predictors of autism posts. The result shows the potential of social media in medical studies for a broad range of purposes such as screening, monitoring and subsequently providing supports for online communities of individuals with special needs.

Ipoll: Automatic polling using online search

For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable human involvement is still needed for the selection of search indices, a task that requires knowledge of both the target issue and how search terms are used by the online community. The robustness of such manually selected search indices can be questionable. In this paper, we propose an automatic polling system through a novel application of machine learning. In this system, the needs for examining, comparing, and selecting search indices have been eliminated through automatic generation of candidate search indices and intelligent combination of the indices. The results include a publicly accessible web application that provides real-time, robust, and accurate measurements of public opinions on several subjects of general interest.