Evaluation of low density spine software for the assessment of bone mineral density in children

Pediatric dual-energy X-ray absorptiometry spine scans often cannot be analyzed with standard software due to a failure to identify the bone edges of low density vertebrae. Low density spine (LDS) software improves bone detection compared with standard software. The objective of this study was to compare bone mineral density (BMD) measurements obtained with the standard and LDS software in 27 healthy nonobese, 32 obese, and 41 chronically ill children, ages 2-18 years. Lumbar spine (L1-L4) BMD, measured by standard analysis, ranged from 0.531-1.244 gm/cm2. Reanalysis with the LDS software resulted in a systematic increase (mean +/- SD) in estimated bone area of 17.0+/-5.0%, an increase in bone mineral content of 6.1+/-6.3%, and a mean decrease in BMD of 8.7+/-1.7% (all p < 0.001). This resulted in a mean decrease in BMD Z score of 0.7+/-0.2. Linear regression models, predicting standard BMD from LDS BMD, were fit for the three subject groups (R2 = 0.993-0.995). Small differences in slopes were detected across groups (p = 0.07); LDS BMD predicted higher standard BMD in obese subjects. In conclusion, LDS analysis resulted in a clinically significant decrease in measured BMD. The association between analysis methods was exceptionally high (R2 > 0.99), indicating that LDS BMD accurately predicts standard BMD. Although LDS BMD in obese subjects predicts higher standard BMD results than in nonobese subjects, the small difference is of questionable clinical significance. LDS software is a useful tool for the assessment of BMD in children.     

Structural studies of ribosomal proteins

Crystal and solution structures of fourteen ribosomal proteins from thermophilic bacteria have been determined during the last decade. This paper reviews structural studies of ribosomal proteins from Thermus thermophilus carried out at the Institute of Protein Research (Pushchino, Russia) in collaboration with the University of Lund (Lund, Sweden) and the Center of Structural Biochemistry (Karolinska Institute, Huddinge, Sweden). New experimental data on the crystal structure of the ribosomal protein L30 from T. thermophilus are also included.     

Electrical characteristics of a dc superconducting cable

A dc superconducting cable is ideal for transmitting large blocks of electrical power over a long distance. However, it must be designed to operate reliably within the constraints of the electrical system. Therefore, system analysis must be performed for each application. The conductor losses caused by the harmonics on the dc must be within the design goals; a system fault should not drive the cable normal with eventual damage to the cable and interruption of power flow; and, the dielectric system of the cable must be designed to be compatible with the expected transient voltages by proper insulation coordination. Transient overvoltages are of concern to electrical power systems; these are especially critical to cryogenic cables because of the susceptibility of the cryogenic enclosures to these transients. This paper discusses the electrical system constraints which are particularly applicable to a dc superconducting cable and shows how such a cable can be designed to be compatible with the electrical system.This paper also summarizes the work on low temperature dielectrics performed at Los Alamos. It shows the variation of break down voltage of dielectric materials, in sheet form and cable configuration, with temperature and pressure under dc and impulse voltage. The surface flashover characteristics with large creepage distance as well as electrical conductivity of dielectric materials at cryogenic temperatures are discussed. These studies are essential for the design of high voltage apparatus operating in cryogenic environments.     

Environmental ethics]

A study of a variety of stationary phases and elution conditions for the liquid chromatographic (LC) determination of six biologically active green tea catechins has resulted in the development of two well-defined, reproducible systems for such analyses which overcome limitations of previously described methods. Comparison of six reversed-phase columns indicates that deactivated stationary phases, which utilize ultrapure silica and maximize coverage of the silica support, provide significantly improved separation and chromatographic efficiencies for catechin analyses using LC, compared to conventional monomeric or polymeric C18 columns. Evaluation of elution conditions used for the separations reveals that the presence of acid in the mobile phase (0.05% trifluoroacetic acid) is essential for both the complete resolution of the catechins present in tea and the efficient chromatography of these compounds. The efficacy of one of the developed systems was demonstrated by the quantitative measurement of the six biologically active catechins in aqueous infusions of green tea (Camellia sinensis). Overall precision values for the analyses were within the range 0.3-1% (relative standard deviation).     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.