Bone‐specific alkaline phosphatase and bone turnover in African American hemodialysis patients

Introduction: Noninvasive measures of bone activity include intact parathyroid hormone (iPTH) and bone‐specific alkaline phosphatase (BSAP). Whether BSAP measurement alone or in combination with other biochemical data provides more reliable information about bone turnover than iPTH alone in African Americans on hemodialysis is unknown. Methods: This cross‐sectional study aimed to determine the optimal predictor and cutoff points for BSAP, iPTH, calcium and phosphorus in classifying bone biopsy findings. Forty‐three African American hemodialysis patients were available for analysis. Biochemical data on the day of biopsy across a spectrum of qualitative histologic bone features were compared. Classification and regression tree analysis was used to determine both the optimal predictor and cutoff points for BSAP, iPTH, calcium and phosphorus in identifying bone turnover status. Findings: Seven subjects had adynamic disease, 31 had mild/moderate hyperparathyroid bone features, and five had severe hyperparathyroid bone disease. BSAP was the optimal predictor of bone biopsy with a cutoff point of 22 ng/mL. Calcium and phosphorus had no predictive value. At BSAP ≤ 22 ng/mL, subjects had either adynamic bone disease or mild/moderate hyperparathyroid bone disease but iPTH was not useful in further classifying biopsy findings. When BSAP was >22 ng/mL, subjects had either mild/moderate or severe hyperparathyroid bone disease, and iPTH was useful in further classifying biopsy findings. With BSAP > 22 ng/mL and iPTH < 726 pg/mL, all subjects had mild/moderate bone turnover features. Discussion: Compared to iPTH, BSAP was shown to be the optimal predictor of biopsy findings with an optimal cutoff at 22 ng/mL.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135977/1/hdi12454_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135977/2/hdi12454.pd

Water Quality of Stoney Creek and its Effects on Salmon Spawning

Runoff water in urban streams possesses a major threat in salmon spawning. This has been the effect on Burnaby BC\u27s, Stoney Creek. Sample water was retrieved at four sites, with two along Stoney Creek (sites 1 and 4) and two tributaries further upstream (sites 2 and 3). To begin our research we had formulated the hypothesis that tributaries would have lower dissolved oxygen content due to no remediation efforts being applied and downstream sample sites would have higher levels of pollutants due to road runoff accumulation. Multiple means in determining water quality of Stoney Creek were employed; in-stream water quality tests for dissolved oxygen (DO), pH, and temperature were determined using a DO, and pocket pH meter. Water samples were also obtained from each site and were further analyzed for phosphorous, ammonium and chemical oxygen demand levels (COD) using the Hach DR5000 spectrophotometer. Our last means of water quality testing was through the Water Quality TestKit on samples brought from site 1 and 3. In-stream testing resulted in pH levels ranging between 6.4 and 6.7, dissolved oxygen contents of 10.60mg/L and greater, and temperatures of 9.2°C and below. Accordingly, levels in pH, DO and temperature measured are all suitable for salmon spawning. Samples further tested in the lab showed higher ammonium, and phosphate levels that can effect spawning negatively. Lastly the Water Quality TestKit did not demonstrate very good accuracy, and was ruled to be unreliable. Our results indicate that Stoney Creek\u27s conditions are favorable for salmon spawning, and that there is a strong correlation between temperature, pH and dissolved oxygen

GAS: A Gaussian Mixture Distribution-Based Adaptive Sampling Method for PINNs

With recent study of the deep learning in scientific computation, the PINNs method has drawn widespread attention for solving PDEs. Compared with traditional methods, PINNs can efficiently handle high-dimensional problems, while the accuracy is relatively low, especially for highly irregular problems. Inspired by the idea of adaptive finite element methods and incremental learning, we propose GAS, a Gaussian mixture distribution-based adaptive sampling method for PINNs. During the training procedure, GAS uses the current residual information to generate a Gaussian mixture distribution for the sampling of additional points, which are then trained together with history data to speed up the convergence of loss and achieve a higher accuracy. Several numerical simulations on 2d to 10d problems show that GAS is a promising method which achieves the state-of-the-art accuracy among deep solvers, while being comparable with traditional numerical solvers

Spatial and temporal patterns of carbon emissions from forest fires in China from 1950 to 2000

Author Posting. © American Geophysical Union, 2006. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 111 (2006): D05313, doi:10.1029/2005JD006198.We have estimated the emission of carbon (C) and carbon-containing trace gases including CO2, CO, CH4, and NMHC (nonmethane hydrocarbons) from forest fires in China for the time period from 1950 to 2000 by using a combination of remote sensing, forest fire inventory, and terrestrial ecosystem modeling. Our results suggest that mean annual carbon emission from forest fires in China is about 11.31 Tg per year, ranging from a minimum level of 8.55 Tg per year to a maximum level of 13.9 Tg per year. This amount of carbon emission is resulted from the atmospheric emissions of four trace gases as follows: (1) 40.66 Tg CO2 with a range from 29.21 to 47.53 Tg, (2) 2.71 Tg CO with a range from 1.48 to 4.30 Tg, (3) 0.112 Tg CH4 with a range from 0.06 to 0.2 Tg, and (4) 0.113 Tg NMHC with a range from 0.05 to 0.19 Tg. Our study indicates that fire-induced carbon emissions show substantial interannual and decadal variations before 1980 but have remained relatively low and stable since 1980 because of the application of fire suppression. Large spatial variation in fire-induced carbon emissions exists due to the spatial variability of climate, forest types, and fire regimes.This work has been supported by NASA Interdisciplinary Science Program (NNG04GM39C), China’s Ministry of Science and Technology (MOST) 973 Program (2002CB412500), Chinese Academy of Sciences ODS Program, and NSFC International Cooperative Program (40128005)

Simple synthetic data reduces sycophancy in large language models

Sycophancy is an undesirable behavior where models tailor their responses to follow a human user's view even when that view is not objectively correct (e.g., adapting liberal views once a user reveals that they are liberal). In this paper, we study the prevalence of sycophancy in language models and propose a simple synthetic-data intervention to reduce this behavior. First, on a set of three sycophancy tasks (Perez et al., 2022) where models are asked for an opinion on statements with no correct answers (e.g., politics), we observe that both model scaling and instruction tuning significantly increase sycophancy for PaLM models up to 540B parameters. Second, we extend sycophancy evaluations to simple addition statements that are objectively incorrect, finding that despite knowing that these statements are wrong, language models will still agree with them if the user does as well. To reduce sycophancy, we present a straightforward synthetic-data intervention that takes public NLP tasks and encourages models to be robust to user opinions on these tasks. Adding these data in a lightweight finetuning step can significantly reduce sycophantic behavior on held-out prompts. Code for generating synthetic data for intervention can be found at https://github.com/google/sycophancy-intervention

Effects of Germination Season on Life History Traits and on Transgenerational Plasticity in Seed Dormancy in a Cold Desert Annual

The maternal environment can influence the intensity of seed dormancy and thus seasonal germination timing and post-germination life history traits. We tested the hypotheses that germination season influences phenotypic expression of post-germination life history traits in the cold desert annual Isatis violascens and that plants from autumn- and spring-germinating seeds produce different proportions of seeds with nondeep and intermediate physiological dormancy (PD). Seeds were sown in summer and flexibility in various life history traits determined for plants that germinated in autumn and in spring. A higher percentage of spring- than of autumn-germinating plants survived the seedling stage, and all surviving plants reproduced. Number of silicles increased with plant size (autumn- \u3e spring-germinating plants), whereas percent dry mass allocated to reproduction was higher in spring- than in autumn-germinating plants. Autumn-germinating plants produced proportionally more seeds with intermediate PD than spring-germinating plants, while spring-germinating plants produced proportionally more seeds with nondeep PD than autumn-germinating plants. Flexibility throughout the life history and transgenerational plasticity in seed dormancy are adaptations of I. violascens to its desert habitat. Our study is the first to demonstrate that autumn- and spring-germinating plants in a species population differ in proportion of seeds produced with different levels of PD

Effect of Seed Position on Parental Plant on Proportion of Seeds Produced with Nondeep and Intermediate Physiological Dormancy

The position in which seeds develop on the parental plant can have an effect on dormancy-break and germination. We tested the hypothesis that the proportion of seeds with intermediate physiological dormancy (PD) produced in the proximal position on a raceme of Isatis violascens plants is higher than that produced in the distal position, and further that this difference is related to temperature during seed development. Plants were watered at 3-day intervals, and silicles and seeds from the proximal (early) and distal (late) positions of racemes on the same plants were collected separately and tested for germination. After 0 and 6 months dry storage at room temperature (afterripening), silicles and seeds were cold stratified for 0–16 weeks and tested for germination. Mean daily maximum and minimum temperatures during development/maturation of the two groups of seeds did not differ. A higher proportion of seeds with the intermediate level than with the nondeep level of PD was produced by silicles in the proximal position than by those in the distal position, while the proportion of seeds with nondeep PD was higher in the distal than in the proximal position of the raceme. The differences were not due only to seed mass. Since temperature and soil moisture conditions were the same during development of the seeds in the raceme, differences in proportion of seeds with intermediate and nondeep PD are attributed to position on parental plant. The ecological consequence of this phenomenon is that it ensures diversity in dormancy-breaking and germination characteristics within a seed cohort, a probable bet-hedging strategy. This is the first demonstration of position effects on level of PD in the offspring

Query lower bounds for log-concave sampling

Log-concave sampling has witnessed remarkable algorithmic advances in recent years, but the corresponding problem of proving lower bounds for this task has remained elusive, with lower bounds previously known only in dimension one. In this work, we establish the following query lower bounds: (1) sampling from strongly log-concave and log-smooth distributions in dimension $d\ge 2$ requires $\Omega(\log \kappa)$ queries, which is sharp in any constant dimension, and (2) sampling from Gaussians in dimension $d$ (hence also from general log-concave and log-smooth distributions in dimension $d$) requires $\widetilde \Omega(\min(\sqrt\kappa \log d, d))$ queries, which is nearly sharp for the class of Gaussians. Here $\kappa$ denotes the condition number of the target distribution. Our proofs rely upon (1) a multiscale construction inspired by work on the Kakeya conjecture in harmonic analysis, and (2) a novel reduction that demonstrates that block Krylov algorithms are optimal for this problem, as well as connections to lower bound techniques based on Wishart matrices developed in the matrix-vector query literature.Comment: 46 pages, 2 figure

Land carbon sequestration within the conterminous United States : regional- and state-level analyses

Author Posting. © American Geophysical Union, 2015. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 120 (2015): 379–398, doi:10.1002/2014JG002818.A quantitative understanding of the rate at which land ecosystems are sequestering or losing carbon at national-, regional-, and state-level scales is needed to develop policies to mitigate climate change. In this study, a new improved historical land use and land cover change data set is developed and combined with a process-based ecosystem model to estimate carbon sources and sinks in land ecosystems of the conterminous United States for the contemporary period of 2001–2005 and over the last three centuries. We estimate that land ecosystems in the conterminous United States sequestered 323 Tg C yr−1 at the beginning of the 21st century with forests accounting for 97% of this sink. This land carbon sink varied substantially across the conterminous United States, with the largest sinks occurring in the Southeast. Land sinks are large enough to completely compensate fossil fuel emissions in Maine and Mississippi, but nationally, carbon sinks compensate for only 20% of U.S. fossil fuel emissions. We find that regions that are currently large carbon sinks (e.g., Southeast) tend to have been large carbon sources over the longer historical period. Both the land use history and fate of harvested products can be important in determining a region's overall impact on the atmospheric carbon budget. While there are numerous options for reducing fossil fuels (e.g., increase efficiency and displacement by renewable resources), new land management opportunities for sequestering carbon need to be explored. Opportunities include reforestation and managing forest age structure. These opportunities will vary from state to state and over time across the United States.This work was supported by NSF grants 104918, 1137306, and 1237491; EPA grant XA-83600001-1; and DOE grant DE-FG02-94ER61937.2015-08-2