The performance of interferon-gamma release assays in tuberculosis patients with type II diabetes

The sensitivity of Interferon-γ release assays for detection of Mycobacterium tuberculosis (MTB) infection or disease is affected by conditions that depress host immunity (such as HIV). It is critical to determine whether these assays are affected by diabetes and related conditions (i.e. hyperglycemia, chronic hyperglycemia, or being overweight/obese) given that immune impairment is thought to underline susceptibility to tuberculosis (TB) in people with diabetes. This is important for tuberculosis control due to the millions of type 2 diabetes patients at risk for tuberculosis worldwide.^ The objective of this study was to identify host characteristics, including diabetes, that may affect the sensitivity of two commercially available Interferon-γ (IFN-γ) release assays (IGRA), the QuantiFERON®-TB Gold (QFT-G) and the T-SPOT®.TB in active TB patients. We further explored whether IFN-γ secretion in response to MTB antigens (ESAT-6 and CFP-10) is associated with diabetes and its defining characteristics (high blood glucose, high HbA1c, high BMI). To achieve these objectives, the sensitivity of QFT-G and T-SPOT. TB assays were evaluated in newly diagnosed, tuberculosis confirmed (by positive smear for acid fast bacilli and/or positive culture for MTB) adults enrolled at Texas and Mexico study sites between March 2006 and April 2009. Univariate and multivariate models were constructed to identify host characteristics associated with IGRA result and level of IFN-γ secretion.^ QFT-G was positive in 68% of tuberculosis patients. Those with diabetes, chronic hyperglycemia or obesity were more likely to have a positive QFT-G result, and to secrete higher levels of IFN-γ in response to the mycobacterial antigens (p<0.05). Previous history of BCG vaccination was the only other host characteristic associated with QFT-G result, whereby a higher proportion of non-BCG vaccinated persons were QFT-G positive, in comparison to vaccinated persons. In a separate group of patients, the T-SPOT.TB was 94% sensitive, with similar performance in all tuberculosis patients, regardless of host characteristics.^ In summary, we have demonstrated the validity of QFT-G and T-SPOT. TB to support the diagnosis of TB in patients with a range of host characteristics, but most notably in patients with diabetes. We also confirmed that TB patients with diabetes and associated characteristics (chronic hyperglycemia or BMI) secreted higher titers of IFN-γ when stimulated with MTB specific antigens, in comparison to patients without these characteristics. Together, these findings suggest that the mechanism by which diabetes increases risk to TB may not be explained by the inability to secrete IFN-γ, a key cytokine for TB control.^

Comparison of financial trends in small rural and urban hospitals in Texas, 1983--1985

The purpose of this study was to compare the financial performance of small rural hospitals to that of small urban hospitals in Texas. Hospital-specific and environmental factors were studied as control variables.^ Small rural hospitals were found to be financially stronger on measures of liquidity but weaker on measures of profitability. Small urban hospitals performed better on measures of profitability and long-range solvency. When all measures in the five dimensions of financial performance were analyzed, no significant difference was found between the two groups of hospitals. None of the control variables included in the study was significantly associated with financial performance both for rural and urban hospitals. Conclusions were that small rural hospitals in Texas are experiencing a deterioration in financial condition but small, rural hospitals are not doing any worse than small urban hospitals; and that the financial hardship which rural hospitals suffer may be inherent in the nature of the institutions themselves, and not as a result of their smallness nor their rural settings. ^

International comparison of wait times and quality of care: A pilot study

During the healthcare reform debate in the United States in 2009/2010, many health policy experts expressed a concern that expanding coverage would increase waiting times for patients to obtain care. Many complained that delays in obtaining care in turn would compromise the quality of healthcare in the United States. Using data from The Commonwealth Fund 2010 International Health Policy Survey in Eleven Countries, this study explored the relationship between wait times and quality of care, employing a wait time scale and several quality of care indicators present in the dataset. The impact of wait times on quality was assessed. Increased wait time was expected to reduce quality of care. However, this study found that wait times correlated with better health outcomes for some measures, and had no association with others. Since this is a pilot study and statistical significance was not achieved for any of the correlations, further research is needed to confirm and deepen the findings. However, if future studies confirm this finding, an emphasis on reducing wait times at the expense of other health system level performance variables may be inappropriate. ^

COMPARISON OF THE ORGANIZATIONAL STRUCTURES AND EFFECTIVENESS OF THE INVESTOR-OWNED AND VOLUNTARY MULTIHOSPITAL SECTORS

Objectives. The central objective of this study was to systematically examine the internal structure of multihospital systems, determining the management principles used and the performance levels achieved in medical care and administrative areas.^ The Universe. The study universe consisted of short-term general American hospitals owned and operated by multihospital corporations. Corporations compared were the investor-owned (for-profit) and the voluntary multihospital systems. The individual hospital was the unit of analysis for the study.^ Theoretical Considerations. The contingency theory, using selected aspects of the classical and human relations schools of thought, seemed well suited to describe multihospital organization and was used in this research.^ The Study Hypotheses. The main null hypotheses generated were that there are no significant differences between the voluntary and the investor-owned multihospital sectors in their (1) hospital structures and (2) patient care and administrative performance levels.^ The Sample. A stratified random sample of 212 hospitals owned by multihospital systems was selected to equally represent the two study sectors. Of the sampled hospitals approached, 90.1% responded.^ The Analysis. Sixteen scales were constructed in conjunction with 16 structural variables developed from the major questions and sub-items of the questionnaire. This was followed by analysis of an additional 7 structural and 24 effectiveness (performance) measures, using frequency distributions. Finally, summary statistics and statistical testing for each variable and sub-items were completed and recorded in 38 tables.^ Study Findings. While it has been argued that there are great differences between the two sectors, this study found that with a few exceptions the null hypotheses of no difference in organizational and operational characteristics of non-profit and for-profit hospitals was accepted. However, there were several significant differences found in the structural variables: functional specialization, and autonomy were significantly higher in the voluntary sector. Only centralization was significantly different in the investor owned. Among the effectiveness measures, occupancy rate, cost of data processing, total manhours worked, F.T.E. ratios, and personnel per occupied bed were significantly higher in the voluntary sector. The findings indicated that both voluntary and for-profit systems were converging toward a common hierarchical corporate management approach. Factors of size and management style may be better descriptors to characterize a specific multihospital group than its profit or nonprofit status. (Abstract shortened with permission of author.) ^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Second Year Performance of Honeycrisp on 31 Dwarfing Rootstocks in the Iowa Planting of the NC-140 2010 Regional Apple Rootstock Trial

To evaluate the adaptability and performance of new and promising apple rootstocks in the dwarfing size-control category, a NC-140 regional rootstock trial was established in 2010 at 12 sites in the United States (CO, IA, IL, IN, MA, MI, MN, NJ, NY, OH, UT, WI), two sites in Canada (BC, NS), and one site in Mexico (CHIH) with Honeycrisp serving as the test cultivar. The Iowa planting, located at the ISU Horticulture Research Station, includes 31 rootstocks with new selections from the Cornell-Geneva breeding program (G, CG.), Russia (Bud), Germany (PiAu), and Japan (Supp), with M.26, M.9 Pajam 2, and M.9 T337 serving as industry standards. Tissue cultured propagated (TC) rootstocks of G.41, G.202, and G.935 were included for comparison with normal (N) stool bed propagated rootstocks. This report summarizes the tree-growth characteristics of the Iowa planting during the 2011 growing season.

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Has Low Productivity Constrained Competitiveness of African Firms? : Comparison of the Firm Performances with Asian Firms

It has been argued that poor productive performance is one of critical sources of stagnation of the African manufacturing sector, but firm-level empirical supports are limited. Using the inter-regional firm data of the garment industry, technical efficiency and its contribution to competitiveness measured as unit costs were compared between Kenyan and Bangladeshi firms. Our estimates indicated that there is no significant gap in the average technical efficiency of the two industries despite conservative estimation, although unit costs greatly differ between the two industries. Higher unit cost in Kenyan firms mainly stems from high labour cost, while impact of inefficiency is quite small. Productivity accounts little for the stagnation of garment industry in several African countries.

Improving runoff estimates from regional climate models: a performance analysis in Spain

An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the “best estimator” of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results

Comparison of different stomatal conductance algorithms for ozone flux modelling

A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatalconductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221–224.] algorithm for calculating stomatalconductance (gs) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of gs, whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (An)

Comparison of vibration and rolling noise emission of resilient and solid monobloc railway wheels in underground lines

Flat or worn wheels rolling on rough or corrugated tracks can provoke airborne noise and ground-borne vibration, which can be a serious concern for nearby neighbours of urban rail transit lines. Among the various treatments used to reduce vibration and noise, resilient wheels play an important role. In conventional resilient wheels, a slightly prestressed V­shaped rubber ring is mounted between the steel wheel centre and tyre. The elastic layer enhances rolling noise and vibration suppression, as well as impact reduction on the track. In this paper the effectiveness of resilient wheels in underground lines, in comparison to monobloc ones, is assessed. The analysed resilient wheel is able to carry greater loads than standard resilient wheels used for light vehicles. It also presents a greater radial resiliency and a higher axial stiffness than conventional V­wheels. The finite element method was used in this study. A quarter car model was defined, in which the wheelset was modelled as an elastic body. Several simulations were performed in order to assess the vibrational behaviour of elastic wheels, including modal, harmonic and random vibration analysis, the latter allowing the introduction of realistic vertical track irregularities, as well as the influence of the running speed. Due to numerical problems some simplifications were needed. Parametric variations were also performed, in which the sensitivity of the whole system to variations of rubber prestress and Poisson’s ratio of the elastic material was assessed.Results are presented in the frequency domain, showing a better performance of the resilient wheels for frequencies over 200 Hz. This result reveals the ability of the analyzed design to mitigate rolling noise, but not structural vibrations, which are primarily found in the lower frequency range.

Performance Modeling of Fresnel-Based CPV Systems: Effects of Deformations under Real Operation Conditions

Getting a lower energy cost has always been a challenge for concentrated photovoltaic. The FK concentrator enhances the performance (efficiency, acceptance angle and manufacturing tolerances) of the conventional CPV system based on a Fresnel primary stage and a secondary lens, while keeping its simplicity and potentially low‐cost manufacturing. At the same time F‐XTP (Fresnel lens+reflective prism), at the first glance has better cost potential but significantly higher sensitivity to manufacturing errors. This work presents comparison of these two approaches applied to two main technologies of Fresnel lens production (PMMA and Silicone on Glass) and effect of standard deformations that occur under real operation conditions

Sewage sludge gasification. Dolomite performance under different operating conditions

Gasification is a technology that can replace traditional management alternatives used up to date to deal with this waste (landfilling, composting and incineration) and which fulfils the social, environmental and legislative requirements. The main products of sewage sludge gasification are permanent gases (useful to generate energy or to be used as raw material in chemical synthesis processes), liquids (tars) and char. One of the main problems to be solved in gasification is tar production. Tars are organic impurities which can condense at relatively high temperatures making impossible to use the produced gases for most applications. This work deals with the effect of some primary tar removal processes (performed inside the gasifier) on sewage sludge gasification products. For this purpose, analysis of the gas composition, tar production, cold gas efficiency and carbon conversion were carried out. The tests were performed with air in a laboratory scale plant consisting mainly of a bubbling bed gasifier. No catalyzed and catalyzed (10% wt of dolomite in the bed and in the feeding) tests were carried out at different temperatures (750ºC, 800ºC and 850ºC) in order to know the effect of these parameters in the gasification products. As far as tars were concerned, qualitative and quantitative tar composition was determined. In all tests the Equivalence Ratio (ER) was kept at 0.3. Temperature is one of the most influential variables in sewage sludge gasification. Higher temperatures favoured hydrogen and CO production while CO2 content decreased, which might be partially explained by the effect of the cracking, Boudouard and CO2 reforming reactions. At 850ºC, cold gas efficiency and carbon conversion reached 49% and 76%, respectively. The presence of dolomite as catalyst increased the production of H2 reaching contents of 15.5% by volume at 850 °C. Similar behaviour was found for CO whereas CO2 and CnHm (light hydrocarbons) production decreased. In the presence of dolomite, a tar reduction of up to 51% was reached in comparison with no catalyzed tests, as well as improvements on cold gas efficiency and carbon conversion. Several assays were developed in order to test catalyst performance under more rough gasification conditions. For this purpose, the throughput value (TR), defined as kg sludge “as received” fed to the gasifier per hour and per m2 of cross sectional area of the gasifier, was modified. Specifically, the TR values used were 110 (reference value), 215 and 322 kg/h·m2. When TR increased, the H2, CO and CH4 production decreased while the CO2 and the CnHm production increased. Tar production increased drastically with TR during no catalysed tests what is related to the lower residence time of the gas inside the reactor. Nevertheless, even at TR=322 kg/h·m2, tar production decreased by nearly 50% with in-bed use of dolomite in comparison with no catalyzed assays under the same operating conditions. Regarding relative tar composition, there was an increase in benzene and naphthalene content when temperature increased while the content of the rest of compounds decreased. The dolomite seemed to be effective all over the range of molecular weight studied showing tar removal efficiencies between 35-55% in most cases. High values of the TR caused a significant increase in tar production but a slight effect on tar composition.

Energy payback time of grid connected pv systems: comparison between tracking and fixed systems

A review of existing studies about LCA of PV systems has been carried out. The data from this review have been completed with our own figures in order to calculate the Energy Payback Time of double and horizontal axis tracking and fixed systems. The results of this metric span from 2 to 5 years for the latitude and global irradiation ranges of the geographical area comprised between −10◦ to 10◦ of longitude, and 30◦ to 45◦ of latitude. With the caution due to the uncertainty of the sources of information, these results mean that a GCPVS is able to produce back the energy required for its existence from 6 to 15 times during a life cycle of 30 years. When comparing tracking and fixed systems, the great importance of the PV generator makes advisable to dedicate more energy to some components of the system in order to increase the productivity and to obtain a higher performance of the component with the highest energy requirement. Both double axis and horizontal axis trackers follow this way, requiring more energy in metallic structure, foundations and wiring, but this higher contribution is widely compensated by the improved productivity of the system.

Improving the low-wind performance of the AERMOD atmospheric dispersion model for predicting short-range impacts of livestock ammonia emissions.

Short-range impacts to sensitive ecosystems as a result of ammonia emitted by livestock farms are often assessed using atmospheric dispersion modelling systems such as AERMOD. These assessments evaluate mean annual atmospheric concentrations of ammonia and nitrogen deposition rates at the ecosystem location for comparison with ecosystem damage thresholds. However, predictions of mean annual atmospheric concentrations can be dominated by periods of stable night-time conditions, which can contribute significantly to mean concentrations. AERMOD has been demonstrated to overestimate concentrations in certain stable low-wind conditions and so the model could potentially overestimate the short-range impacts of livestock ammonia emissions. This paper tests several modifications to the parameterisation of AERMOD (v12345) that aim to improve model predictions in low-wind conditions. The modifications are first described and then are applied to three pig farm case studies in the USA, Denmark and Spain to assess whether the modifications improve long-term mean ammonia concentration predictions through improved model performance. For these three case studies, most of the modifications tested improved model performance as a result of reducing the long-term mean concentration predictions, with the largest effect for low- or ground-level sources (e.g. slurry lagoons or naturally ventilated housing).