“Hanging Out”: Cultivating Writing Groups Online

In this narrative, we describe the process and value of meeting in online writing groups via google hangouts. These groups offer a range of benefits, including just-in-time support, mentoring, and processing of the clamorous, eventful life of the writer. These groups also serve as a life-giving writing environment where we can think out loud and share spoken and written ideas with engaged, supportive, and sympathetic readers

Alendronate treatment results in similar levels of trabecular bone remodeling in the femoral neck and vertebra

Introduction Bone turnover suppression in sites that already have a low surface-based remodeling rate may lead to oversuppression that could have negative effects on the biomechanical properties of bone. The goal was to determine how alendronate suppresses bone turnover at sites with different surface-based remodeling rates. Methods Dynamic histomorphometric parameters were assessed in trabecular bone of the femoral neck and lumbar vertebrae obtained from skeletally mature beagles treated with saline (1 ml/kg/day) or alendronate (ALN 0.2 or 1.0 mg/kg/day). The ALN0.2 and ALN1.0 doses approximate, on a milligram per kilogram basis, the clinical doses used for the treatment of postmenopausal osteoporosis and Paget’s disease, respectively. Results Alendronate treatment resulted in similar absolute levels of bone turnover in the femoral neck and vertebrae, although the femoral neck had 33% lower pre-treatment surface-based remodeling rate than the vertebra (p < 0.05). Additionally, the high dose of alendronate (ALN 1.0) suppressed bone turnover to similar absolute levels as the low dose of alendronate (ALN 0.2) in both sites. Conclusions Alendronate treatment may result in a lower limit of trabecular bone turnover suppression, suggesting that sites of low pre-treatment remodeling rate are not more susceptible to oversuppression than those of high pre-treatment remodeling rate

Rapid prototype fabrication processes for high-performance thrust cells

The Thrust Cell Technologies Program (Air Force Phillips Laboratory Contract No. F04611-92-C-0050) is currently being performed by Rocketdyne to demonstrate advanced materials and fabrication technologies which can be utilized to produce low-cost, high-performance thrust cells for launch and space transportation rocket engines. Under Phase 2 of the Thrust Cell Technologies Program (TCTP), rapid prototyping and investment casting techniques are being employed to fabricate a 12,000-lbf thrust class combustion chamber for delivery and hot-fire testing at Phillips Lab. The integrated process of investment casting directly from rapid prototype patterns dramatically reduces design-to-delivery cycle time, and greatly enhances design flexibility over conventionally processed cast or machined parts

Phenomenology of strangeness production at high energies

The strange-quark occupation factor ($\gamma_s$) is determined from the statistical fit of the multiplicity ratio $\mathrm{K}^+/\pi^+$ in a wide range of nucleon-nucleon center-of-mass energies ($\sqrt{s_{NN}}$). From this single-strange-quark-subsystem, $\gamma_s(\sqrt{s_{NN}})$ was parametrized as a damped trigonometric functionality and successfully implemented to the hadron resonance gas model, at chemical semi-equilibrium. Various particle ratios including $\mathrm{K}^-/\pi^-$, $\mathrm{\Lambda}/\pi^-$, and $\mathrm{\bar{\Lambda}}/\pi^-$ are well reproduced. The phenomenology of $\gamma_s(\sqrt{s_{NN}})$ suggests that, the hadrons ($\gamma_s$ raises) at $\sqrt{s_{NN}} \simeq 7~$GeV seems to undergo a phase transition to a mixed phase ($\gamma_s$ declines), which is then derived into partons ($\gamma_s$ remains unchanged with increasing $\sqrt{s_{NN}}$), at $\sqrt{s_{NN}} \simeq 20~$GeV.Comment: 6 pages, 2 figures, accepted for publication in EP

Classification of tropospheric ozone profiles over Johannesburg based on MOZAIC aircraft data

International audienceEach ozone profile is a unique response to the photochemical and dynamic processes operating in the troposphere and hence is critical to our understanding of processes and their relative contributions to the tropospheric ozone budget. Traditionally, mean profiles, together with some measure of variability, averaged by season or year at a particular location have been presented as a climatology. However, the mean profile is difficult to interpret because of the counteracting influences present in the micro-structure. On the other hand, case study analysis, whilst revealing, only applies to isolated conditions. In a search for pattern and order within ozone profiles, a classification based on a cluster analysis technique has been applied in this study. Ozone profiles are grouped according to the magnitude and altitude of ozone concentration. This technique has been tested with 56 ozone profiles at Johannesburg, South Africa, recorded by aircraft as part of the MOZAIC (Measurement of Ozone and Water Vapor aboard Airbus In-service Aircraft) program. Six distinct groups of ozone profiles have been identified and their characteristics described. The widely recognized spring maximum in tropospheric ozone is identified through the classification, but a new summertime mid-tropospheric enhancement due to the penetration of tropical air masses from continental regions in central Africa has been identified. Back trajectory modeling is used to provide evidence of the different origins of ozone enhancements in each of the classes. Continental areas over central Africa are shown to be responsible for the low to mid-tropospheric enhancement in spring and the mid-tropospheric peak in summer, whereas the winter low-tropospheric enhancement is attributed to local sources. The dominance of westerly winds through the troposphere associated with the passage of a mid-latitude cyclone gives rise to reduced ozone values

Subgroup Detection in Ideological Discussions

The rapid and continuous growth of social networking sites has led to the emergence of many communities of communicating groups. Many of these groups discuss ideological and political topics. It is not uncommon that the participants in such discussions split into two or more subgroups. The members of each subgroup share the same opinion toward the discussion topic and are more likely to agree with members of the same subgroup and disagree with members from opposing subgroups. In this paper, we propose an unsupervised approach for automatically detecting discussant subgroups in online communities. We analyze the text exchanged between the participants of a discussion to identify the attitude they carry toward each other and towards the various aspects of the discussion topic. We use attitude predictions to construct an attitude vector for each discussant. We use clustering techniques to cluster these vectors and, hence, determine the subgroup membership of each participant. We compare our methods to text clustering and other baselines, and show that our method achieves promising results