Bone health after menopause: effect of surgical menopaus on bone mineral density and osteoporosis

Background: Natural menopause or surgical menopause is associated with endocrinological changes and alteration in bone and mineral metabolism. Hence this study was conducted to assess the bone mineral density changes in women with surgical menopause. Methods: This is a prospective observational study conducted in the department of obstetrics and gynaecology at Sri Ramachandra medical college, which is a tertiary care teaching hospital. 60 women with surgical menopause were included in the study. BMD was assessed by dual energy X-ray absorptiometry at the lumbar spine and hip joint. All the data was entered in Microsoft excel spread sheet and analysed by using SPSS software.Results: Among 60 study subjects, 41 individuals had a normal BMD, 16 had osteopenia, and 3 were diagnosed with osteoporosis. Osteopenia and osteoporosis is significantly higher in patients who had undergone hysterectomy with removal of ovaries. Observations of osteopenia and osteoporosis were significantly higher with increasing number of years post hysterectomy.Conclusions: Prevalence of osteoporosis is high in patients who undergo hysterectomy. Oophorectomy is associated with postoperative bone loss. Targeted management strategies should include routine BMD assessment and hormone therapy improves management of bone health in this population. Further more studies are needed in large populations to test alternative treatments for post oophorectomy osteoporosis

Evaluation of Single-Cell Cavities Made of Forged Ingot Niobium at Jefferson Lab

Currently, fine grain niobium (Nb) (grain size ∼ 50 µm) and large grain Nb (grain size of a few cm) are being used for the fabrication of superconducting radio frequency (SRF) cavities. Medium grain forged ingot with grain size of a few hundred µm may be beneficial for cost-effectiveness as well as providing better performance for future SRF-based accelerators. Forged ingot Nb with medium grain size is a novel production method to obtain Nb discs used for the fabrication of superconducting radio frequency cavities. We have fabricated two 1.5 GHz single cell cavities made from forged Nb ingot with a residual resistivity ratio of ∼ 100. The cavities were chemically and mechanically polished and heat-treated in the temperature range of 650-1000 C before the rf test. One of the cavities reached an accelerating gradient of ∼34 MV/m with a quality factor Q \u3e 1e10, while the second cavity was limited at 14 MV/m, likely due to a weld defect at the equator

Effect of high temperature heat treatments on the quality factor of a large-grain superconducting radio-frequency niobium cavity

Large-grain Nb has become a viable alternative to fine-grain Nb for the fabrication of superconducting radio-frequency cavities. In this contribution we report the results from a heat treatment study of a large-grain 1.5 GHz single-cell cavity made of "medium purity" Nb. The baseline surface preparation prior to heat treatment consisted of standard buffered chemical polishing. The heat treatment in the range 800 - 1400 C was done in a newly designed vacuum induction furnace. Q0 values of the order of 2x1010 at 2.0 K and peak surface magnetic field (Bp) of 90 mT were achieved reproducibly. A Q0-value of (5+-1)1010 at 2.0 K and Bp = 90 mT was obtained after heat treatment at 1400 C. This is the highest value ever reported at this temperature, frequency and field. Samples heat treated with the cavity at 1400 C were analyzed by secondary ion mass spectrometry, secondary electron microscopy, energy dispersive X-ray, point contact tunneling and X-ray diffraction and revealed a complex surface composition which includes titanium oxide, increased carbon and nitrogen content but reduced hydrogen concentration compared to a non heat-treated sample

Effect of High Temperature Heat Treatments on the Quality Factor of a Large-grain Superconducting Radio-frequency Niobium Cavity

Large-grain Nb has become a viable alternative to fine-grain Nb for the fabrication of superconducting radio-frequency cavities. In this contribution we report the results from a heat treatment study of a large-grain 1.5 GHz single-cell cavity made of “medium purity” Nb. The baseline surface preparation prior to heat treatment consisted of standard buffered chemical polishing. The heat treatment in the range 800–1400°C was done in a newly designed vacuum induction furnace. Q0 values of the order of 2×1010 at 2.0 K and peak surface magnetic field (Bp) of 90 mT were achieved reproducibly. A Q0 value of (5±1)×1010 at 2.0 K and Bp=90  mT was obtained after heat treatment at 1400°C. This is the highest value ever reported at this temperature, frequency, and field. Samples heat treated with the cavity at 1400°C were analyzed by secondary ion mass spectrometry, x-ray photoelectron spectroscopy, energy dispersive x ray, point-contact tunneling, and x-ray diffraction, and revealed a complex surface composition which includes titanium oxide, increased carbon, and nitrogen content but reduced hydrogen concentration compared to a non-heat-treated sample

Early spatial and temporal validation of MODIS LAI product in the Southern Africa Kalahari

We evaluate the operational MODIS Leaf Area Index (LAI) product using field-sampled data collected at five sites in southern Africa in March 2000. One site (Mongu, Zambia) was sampled monthly throughout the year. All sites were along the International Geosphere Biosphere Programme’s (IGBP) Kalahari Transect, which features progressively lower annual precipitation, and hence, lower vegetation productivity, from north to south. The soils are consistently sandy. At each site, we sampled the vegetation overstory along three 750-m transects using the Tracing Radiation and Architecture in Canopies (TRAC) instrument. The resulting plant area index values were adjusted with ancillary stem area data to estimate LAI. Despite some instrument characterization and production issues in the first year of MODIS operations, our results suggest the first-year MODIS LAI algorithm correctly accommodates structural and phenological variability in semiarid woodlands and savannas, and is accurate to within the uncertainty of the validation approach used here. Limitations of this study and its conclusions are also discussed

Early spatial and temporal validation of MODIS LAI product in the Southern Africa Kalahari

We evaluate the operational MODIS Leaf Area Index (LAI) product using field-sampled data collected at five sites in southern Africa in March 2000. One site (Mongu, Zambia) was sampled monthly throughout the year. All sites were along the International Geosphere Biosphere Programme’s (IGBP) Kalahari Transect, which features progressively lower annual precipitation, and hence, lower vegetation productivity, from north to south. The soils are consistently sandy. At each site, we sampled the vegetation overstory along three 750-m transects using the Tracing Radiation and Architecture in Canopies (TRAC) instrument. The resulting plant area index values were adjusted with ancillary stem area data to estimate LAI. Despite some instrument characterization and production issues in the first year of MODIS operations, our results suggest the first-year MODIS LAI algorithm correctly accommodates structural and phenological variability in semiarid woodlands and savannas, and is accurate to within the uncertainty of the validation approach used here. Limitations of this study and its conclusions are also discussed

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling

Local time and the pricing of time-dependent barrier options

A time-dependent double-barrier option is a derivative security that delivers the terminal value $\phi(S_T)$ at expiry $T$ if neither of the continuous time-dependent barriers b_\pm:[0,T]\to \RR_+ have been hit during the time interval $[0,T]$. Using a probabilistic approach we obtain a decomposition of the barrier option price into the corresponding European option price minus the barrier premium for a wide class of payoff functions $\phi$, barrier functions $b_\pm$ and linear diffusions $(S_t)_{t\in[0,T]}$. We show that the barrier premium can be expressed as a sum of integrals along the barriers $b_\pm$ of the option's deltas \Delta_\pm:[0,T]\to\RR at the barriers and that the pair of functions $(\Delta_+,\Delta_-)$ solves a system of Volterra integral equations of the first kind. We find a semi-analytic solution for this system in the case of constant double barriers and briefly discus a numerical algorithm for the time-dependent case.Comment: 32 pages, to appear in Finance and Stochastic

Reducing uncertainties in decadal variability of the global carbon budget with multiple datasets

Conventional calculations of the global carbon budget infer the land sink as a residual between emissions, atmospheric accumulation, and the ocean sink. Thus, the land sink accumulates the errors from the other flux terms and bears the largest uncertainty. Here, we present a Bayesian fusion approach that combines multiple observations in different carbon reservoirs to optimize the land (B) and ocean (O) carbon sinks, land use change emissions (L), and indirectly fossil fuel emissions (F) from 1980 to 2014. Compared with the conventional approach, Bayesian optimization decreases the uncertainties in B by 41% and in O by 46%. The L uncertainty decreases by 47%, whereas F uncertainty is marginally improved through the knowledge of natural fluxes. Both ocean and net land uptake (B + L) rates have positive trends of 29 ± 8 and 37 ± 17 Tg C⋅y−2 since 1980, respectively. Our Bayesian fusion of multiple observations reduces uncertainties, thereby allowing us to isolate important variability in global carbon cycle processes