Making Small Claims Courts Work in Montana: Recommendations for Legislative and Judicial Action

Making Small Claims Courts Wor

Small Claims Courts in Montana: A Statistical Study

Small Claims Court

Small Claims Courts in Montana: A Statistical Study

Small Claims Court

F stars, metallicity, and the ages of red galaxies at z > 1

We explore whether the rest-frame near-UV spectral region, observable in high-redshift galaxies via optical spectroscopy, contains sufficient information to allow the degeneracy between age and metallicity to be lifted. We do this by testing the ability of evolutionary synthesis models to reclaim the correct metallicity when fitted to the near-UV spectra of F stars of known (sub-solar and super-solar) metallicity. F stars are of particular interest because the rest-frame near-UV spectra of the oldest known elliptical galaxies at z > 1 appear to be dominated by F stars near to the main-sequence turnoff. We find that, in the case of the F stars, where the HST ultraviolet spectra have high signal:noise, model-fitting with metallicity allowed to vary as a free parameter is rather successful at deriving the correct metallicity. As a result, the estimated turnoff ages of these stars yielded by the model fitting are well constrained. Encouraged by this we have fitted these same variable- metallicity models to the deep, optical spectra of the z \simeq 1.5 mJy radio galaxies 53W091 and 53W069 obtained with the Keck telescope. While the age-metallicity degeneracy is not so easily lifted for these galaxies, we find that even when metallicity is allowed as a free parameter, the best estimates of their ages are still \geq 3 Gyr, with ages younger than 2 Gyr now strongly excluded. Furthermore, we find that a search of the entire parameter space of metallicity and star formation history using MOPED (Heavens et al., 2000) leads to the same conclusion. Our results therefore continue to argue strongly against an Einstein-de Sitter universe, and favour a lambda-dominated universe in which star formation in at least these particular elliptical galaxies was completed somewhere in the redshift range z = 3 - 5.Comment: 10 pages, LaTeX, uses MNRAS style file, incorporates 14 postscript figures, submitted to MNRAS. Changes include: inclusion of single stellar atmosphere model fits; more rigorous calculation of confidence regions; some re-structurin

Prospectus, April 28, 1982

BOARD PLANS FOR COLLEGE EXPANSION; News Digest; Candidates present views; Previewing really is censorship; Second StuGo forum flops on its back; ERA supporters rally together at capital; Don\u27t push your opinions, beliefs on others; Variety of students enroll in art transfer program; P.C. Happenings...: May Day festival to be featured, Music program to be performed, Phi Beta Lambda attends convention, Walks planned through woods, Help yourself to health, Learning to adjust to newborn baby; Parkland serves area through TV classes; Event offers chance to sell food; Origin of Arbor Day hazy; Parkland plans for Arbor Day activity; Soft pretzels make good party snacks; Rathskeller jams at 1st Parkland outdoor concert; Classifieds; Gettin\u27 lucky rocking with Loverboy; \u27Swamp Thing\u27 nothing but entertainment; Talking with the roadies; Tornado Shelter Guide; Mother Nature at her worst...: Watch for tornadoes; Mayor discusses Champaign projectshttps://spark.parkland.edu/prospectus_1982/1020/thumbnail.jp

Spectral Energy Distributions of type 2 QSOs: obscured star formation at high redshifts

We present new mid-infrared and submillimetre observations for a sample of eight high redshift type-2 QSOs located in the Chandra Deep Field South. The sources are X-ray absorbed with luminosities in excess of 10^44 erg/s. Two of the targets have robust detections, S/N > 4, while a further three targets are marginally detected with S/N > =2.5. All sources are detected in multiple mid-infrared bands with the Spitzer Space Telescope. The multiwavelength spectral energy distributions (SEDs) of the type-2 QSOs are compared to those of two local ultraluminous galaxies (Arp220 and IR22491) in order to assess contributions from a star-forming component in various parts of the SED. We suggest that their submillimetre emission is possibly due to a starburst while a large fraction of the mid-infrared energy is likely to originate in the obscured central quasar. Using the mid-infrared and submm observations we derive infrared luminosities which are found to be in excess of L>10^12Lsun. The submillimetre (850micron) to X-ray (2 keV) spectral indices (alpha_SX) span a wide range. About half of the type-2 QSOs have values typical for a Compton-thick AGN with only 1 per cent of the nuclear emission seen through scattering and, the remaining with values typical of submm-bright galaxies. Combining the available observational evidence we outline a possible scenario for the early stages of evolution of these sources.Comment: Accepted for publication in MNRA

Air quality evaluation of London Paddington train station

Enclosed railway stations hosting diesel trains are at risk of reduced air quality as a result of exhaust emissions that may endanger passengers and workers. Air quality measurements were conducted inside London Paddington Station, a semi-enclosed railway station where 70% of trains are powered by diesel engines. Particulate matter (PM2.5) mass was measured at five station locations. PM size, PM number, oxides of nitrogen (NOx), and sulfur dioxide (SO2) were measured at two station locations. Paddington Station’s hourly mean PM2.5 mass concentrations averaged 16 μg/m3 [min 2, max 68]. Paddington Station’s hourly mean NO2 concentrations averaged 73 ppb [49, 120] and SO2 concentrations averaged 25 ppb [15, 37]. While UK train stations are not required to comply with air quality standards, there were five instances where the hourly mean NO2 concentrations exceeded the EU hourly mean limits (106 ppb) for outdoor air quality. PM2.5, SO2, and NO2 concentrations were compared against Marylebone, a busy London roadside 1.5 km from the station. The comparisons indicated that train station air quality was more polluted than the nearby roadside. PM2.5 for at least one measurement location within Paddington Station was shown to be statistically higher (P-value < 0.05) than Marylebone on 3 out of 4 days. Measured NO2 within Paddington Station was statistically higher than Marylebone on 4 out of 5 days. Measured SO2 within Paddington Station was statistically higher than Marylebone on all 3 days.We thank the Engineering and Physical Sciences Research Council (EP/F034350/1) for funding the Energy Efficient Cities Initiative and the Schiff Foundation for doctoral studentship funding.This is the final version of the article. It first appeared from IOP via http://dx.doi.org/10.1088/1748-9326/10/9/09401

Predicting Hospital-Acquired Infections by Scoring System with Simple Parameters

BACKGROUND: Hospital-acquired infections (HAI) are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR) and validated by Artificial Neural Networks (ANN) simultaneously. METHODOLOGY/PRINCIPAL FINDINGS: A total of 476 patients from all the 806 HAI inpatients were included for the study between 2004 and 2005. A sample of 1,376 non-HAI inpatients was randomly drawn from all the admitted patients in the same period of time as the control group. External validation of 2,500 patients was abstracted from another academic teaching center. Sixteen variables were extracted from the Electronic Health Records (EHR) and fed into ANN and LR models. With stepwise selection, the following seven variables were identified by LR models as statistically significant: Foley catheterization, central venous catheterization, arterial line, nasogastric tube, hemodialysis, stress ulcer prophylaxes and systemic glucocorticosteroids. Both ANN and LR models displayed excellent discrimination (area under the receiver operating characteristic curve [AUC]: 0.964 versus 0.969, p = 0.507) to identify infection in internal validation. During external validation, high AUC was obtained from both models (AUC: 0.850 versus 0.870, p = 0.447). The scoring system also performed extremely well in the internal (AUC: 0.965) and external (AUC: 0.871) validations. CONCLUSIONS: We developed a scoring system to predict HAI with simple parameters validated with ANN and LR models. Armed with this scoring system, infectious disease specialists can more efficiently identify patients at high risk for HAI during hospitalization. Further, using parameters either by observation of medical devices used or data obtained from EHR also provided good prediction outcome that can be utilized in different clinical settings