AN EVALUATION OF THE PRIA GRAZING FEE FORMULA

The federal grazing fee is currently set using the Public Rangeland Improvement Act (PRIA) fee formula established in 1978 and modified in 1986. The formula is adjusted annually using indices of private land grazing lease rates (Forage Value Index, FVI), prices received for beef cattle (Beef Cattle Price Index, BCPI), and costs of beef production (Prices Paid Index, PPI). The FVI tracks price movement in the private forage market and was the only index originally proposed to be included in the fee formula. Public land ranchers and an Interdepartmental Grazing Fee Technical Committee assigned to study grazing fee alternatives in the 1960s questioned the ability of the FVI to account for short-term demand, supply, and price equilibrium, and, for this reason, the BCPI and PPI were added to the fee formula. Over 30 years of data are now available to evaluate whether adding the BCPI and PPI did, in fact, help explain short-term market fluctuations. This analysis shows, as earlier studies did, that, if tracking the private forage market is the primary objective, then the fee formula should have included only the FVI. Including the BCPI and, especially, the PPI has caused calculated grazing fees to fall further and further behind private land lease rates. Had the $1.23 base fee in the PRIA formula been indexed by only the FVI, the federal grazing fee would have been$3.84/AUM instead of $1.35/AUM in 2000. It is time to consider the feasibility of a competitive bid system for public lands, or, at the very least, adopt a new fee formula that generates more equitable grazing fees.Land Economics/Use,

Learning Implicit Brain MRI Manifolds with Deep Learning

An important task in image processing and neuroimaging is to extract quantitative information from the acquired images in order to make observations about the presence of disease or markers of development in populations. Having a lowdimensional manifold of an image allows for easier statistical comparisons between groups and the synthesis of group representatives. Previous studies have sought to identify the best mapping of brain MRI to a low-dimensional manifold, but have been limited by assumptions of explicit similarity measures. In this work, we use deep learning techniques to investigate implicit manifolds of normal brains and generate new, high-quality images. We explore implicit manifolds by addressing the problems of image synthesis and image denoising as important tools in manifold learning. First, we propose the unsupervised synthesis of T1-weighted brain MRI using a Generative Adversarial Network (GAN) by learning from 528 examples of 2D axial slices of brain MRI. Synthesized images were first shown to be unique by performing a crosscorrelation with the training set. Real and synthesized images were then assessed in a blinded manner by two imaging experts providing an image quality score of 1-5. The quality score of the synthetic image showed substantial overlap with that of the real images. Moreover, we use an autoencoder with skip connections for image denoising, showing that the proposed method results in higher PSNR than FSL SUSAN after denoising. This work shows the power of artificial networks to synthesize realistic imaging data, which can be used to improve image processing techniques and provide a quantitative framework to structural changes in the brain.Comment: SPIE Medical Imaging 201

Risk of Heart Failure in Breast Cancer Patients After Anthracycline and Trastuzumab Treatment: A Retrospective Cohort Study

Background: Clinical trials demonstrated that women treated for breast cancer with anthracycline or trastuzumab are at increased risk for heart failure and/or cardiomyopathy (HF/CM), but the generalizability of these findings is unknown. We estimated real-world adjuvant anthracycline and trastuzumab use and their associations with incident HF/CM. Methods We conducted a population-based, retrospective cohort study of 12 500 women diagnosed with incident, invasive breast cancer from January 1, 1999 through December 31, 2007, at eight integrated Cancer Research Network health systems. Using administrative procedure and pharmacy codes, we identified anthracycline, trastuzumab, and other chemotherapy use. We identified incident HF/CM following chemotherapy initiation and assessed risk of HF/CM with time-varying chemotherapy exposures vs no chemotherapy. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age at diagnosis, stage, Cancer Research Network site, year of diagnosis, radiation therapy, and comorbidities. Results: Among 12 500 women (mean age = 60 years, range = 22–99 years), 29.6% received anthracycline alone, 0.9% received trastuzumab alone, 3.5% received anthracycline plus trastuzumab, 19.5% received other chemotherapy, and 46.5% received no chemotherapy. Anthracycline and trastuzumab recipients were younger, with fewer comorbidities than recipients of other chemotherapy or none. Compared with no chemotherapy, the risk of HF/CM was higher in patients treated with anthracycline alone (adjusted HR = 1.40, 95% CI = 1.11 to 1.76), although the increased risk was similar to other chemotherapy (adjusted HR = 1.49, 95% CI = 1.25 to 1.77); the risk was highly increased in patients treated with trastuzumab alone (adjusted HR = 4.12, 95% CI = 2.30 to 7.42) or anthracycline plus trastuzumab (adjusted HR = 7.19, 95% CI = 5.00 to 10.35). Conclusions: Anthracycline and trastuzumab were primarily used in younger, healthier women and associated with increased HF/CM risk compared with no chemotherapy. This population-based observational study complements findings from clinical trials on cancer treatment safety

Discordance Between Patient-Predicted and Model-Predicted Life Expectancy Among Ambulatory Patients With Heart Failure

Patients with chronic heart failure have impaired long-term survival, but their own expectations regarding prognosis have not been well studied

Is There an Association between Advanced Paternal Age and Endophenotype Deficit Levels in Schizophrenia?

The children of older fathers have increased risks of developing schizophrenia spectrum disorders, and among those who develop these disorders, those with older fathers present with more severe clinical symptoms. However, the influence of advanced paternal age on other important domains related to schizophrenia, such as quantitative endophenotype deficit levels, remains unknown. This study investigated the associations between paternal age and level of endophenotypic impairment in a well-characterized family-based sample from the Consortium on the Genetics of Schizophrenia (COGS). All families included at least one affected subject and one unaffected sibling. Subjects met criteria for schizophrenia (probands; n = 293) or were unaffected first-degree siblings of those probands (n = 382). Paternal age at the time of subjects’ birth was documented. Subjects completed a comprehensive clinical assessment and a battery of tests that measured 16 endophenotypes. After controlling for covariates, potential paternal age–endophenotype associations were analyzed using one model that included probands alone and a second model that included both probands and unaffected siblings. Endophenotype deficits in the Identical Pairs version of the 4-digit Continuous Performance Test and in the Penn Computerized Neurocognitive Battery verbal memory test showed significant associations with paternal age. However, after correcting for multiple comparisons, no endophenotype was significantly associated with paternal age. These findings suggest that factors other than advanced paternal age at birth may account for endophenotypic deficit levels in schizophrenia

Attitude Determination by Using Horizon and Sun Sensors

The Pointing and Alignment Workstation (PAWS) developed by Teledyne Brown Engineering (TBE) has successfully supported the first and second Atmospheric Laboratory for Applications and Science (ATLAS 1, 2) spacelab missions for NASA. The primary PAWS objective was to provide realtime pointing information to instruments whose line of-sight is dependent on Shuttle attitude and to study/quantify the causes and effects of Shuttle and payload pointing errors. In addition to Shuttle IMU attitude information, PAWS used atmospheric science sensors data to determine the spacecraft attitude. PAWS successfully achieved these goals by acquiring and processing data during the ATLAS 1, 2 mission. This paper presents the attitude determination algorithm real time processing, and results of post mission analysis. The findings of this study include the quality of the horizon sensor and IMU measurements as well as accuracy of attitude processor algorithm

Custom Integrated Circuits

Contains reports on seven research projects.U.S. Air Force - Office of Scientific Research (Contract F49620-84-C-0004)National Science Foundation (Grant ECS81-18160)Defense Advanced Research Projects Agency (Contract NOO14-80-C-0622)National Science Foundation (Grant ECS83-10941

Age And growth of the giant Sea Bass, Stereolepis gigas

The giant sea bass, Stereolepis gigas, is the largest bony fish that inhabits California shallow rocky reef communities and is listed by IUCN as a critically endangered species, yet little is known about its life history. To address questions of growth and longevity, 64 samples were obtained through collaborative efforts with commercial fish markets and scientific gillnetting. Sagittae (otoliths) were cross-sectioned and analyzed with digital microscopy. Age estimates indicate that S. gigas is a long-lived species attaining at least 76 years of age. Over 90% of the variation between age (years) and standard length (mm) was accounted for in the von Bertalanffy growth model (R2 = 0.911). The calculated von Bertalanffy growth function parameters (K = 0.044, t0 = –0.339, L∞= 2026.2 mm SL) for S. gigas were characteristic of a large, slow-growing, apex predator.California Cooperative Oceanic Fisheries Investigations Reports 55. (2014)0575-331

Custom Integrated Circuits

Contains reports on six research projects.U.S. Air Force - Office of Scientific Research (Contract F49620-84-C-0004)Analog Devices, Inc.Defense Advanced Research Projects Agency (Contract N00014-80-C-0622)National Science Foundation (Grant ECS83-10941