Age and length composition of Columbia Basin chinook, sockeye, and coho salmon at Bonneville Dam in 2002

In 2002, representative samples of migrating Columbia Basin chinook (Oncorhynchus tshawytscha), sockeye (O. nerka), and coho salmon (O. kisutch) adult populations were collected at Bonneville Dam. Fish were trapped, anesthetized, sampled for scales and biological data, revived, and then released. Scales were examined to estimate age composition; the results contributed to an ongoing database for age class structure of Columbia Basin salmon populations. Based on scale analysis of chinook salmon, four-year-old fish (from brood year [BY] 1998) comprised 86% of the spring chinook, 51% of the summer chinook, and 51% of the bright fall chinook salmon population. Five-year-old fish (BY 1997) comprised 13% of the spring chinook, 43% of the summer chinook, and 11% of the bright fall chinook salmon population. The sockeye salmon population at Bonneville was predominantly five-year-old fish (55%), with 40% returning as four-year-olds in 2002. For the coho salmon population, 88% of the population was three-year-old fish of age class 1.1, while 12% were age class 1.0. Length analysis of the 2002 returns indicated that chinook salmon with a stream-type life history are larger (mean length) at age than the chinook salmon with an ocean-type life history. Trends in mean length over the sampling period for returning 2002 chinook salmon were analyzed. Chinook salmon of age classes 1.2 and 1.3 show a significant increase in mean length over the duration of the migration. A year class regression over the past 14 years of data was used to predict spring, summer, and bright fall chinook salmon population sizes for 2003. Based on three-year-old returns, the relationship predicts four-year-old returns of 54,200 (± 66,600, 90% predictive interval [PI]) spring chinook, 23,800 (± 19,100, 90% PI) summer, and 169,100 (± 139,500, 90% PI) bright fall chinook salmon for the 2003 runs. Based on four-year-old returns, the relationship predicts five-year-old returns of 36,300 (± 35,400, 90% PI) spring, 63,800 (± 10,300, 90% PI) summer, and 91,100 (± 69,400, 90% PI) bright fall chinook salmon for the 2003 runs. The 2003 run size predictions should be used with caution; some of these predictions are well beyond the range of previously observed data

Assessing performance of conservation-based Best Management Practices: Coarse vs. fine-scale analysis

Background/Questions/Methods
Animal agriculture in the Spring Creek watershed of central Pennsylvania contributes sediment to the stream and ultimately to the Chesapeake Bay. Best Management Practices (BMPs) such as stream bank buffers are intended to intercept sediment moving from heavy-use areas toward the stream. The placement of BMPs on a farm is generally based on untested assumptions about flow paths. Most often, a straight-line distance from the heavy-use area to the stream is assumed to be correct. Our objective was to compare the straight-line path to hydrologic flow paths calculated from fine-, medium- and coarse-grained Digital Elevation Models (DEMs; 1m, 10m, 30m) for 471 mapped heavy-use points within 100m of the stream. The 30m DEMs are the most widely available and require the least processing time. We anticipated that the flow path distance would be longer than the straight-line distance in all cases, that the finest resolution would lead to the most accurate measurement, but that the difference might not be great enough to justify the increased costs. Understanding the changes in path length and direction calculated using more complex methods and higher-resolution source data will enable us to make recommendations on methods to be used in developing conservation management plans.

Results/Conclusions
The medium-(10m DEM) and fine-resolution data (1m DEM) had the smallest differences between the hydrologic flow path and straight-line path: median differences in path length of 20 m for both the 1m and 10m DEMs, and 51m for the 30m DEM. Hydrologic flow paths were significantly longer than straight-line paths for all three scales; BMP placement based on straight-line distances may not be the most effective. Although the overall difference was significantly positive, calculations on the 30m DEMs sometimes produced straight-line paths that were longer than the hydrologic flow paths, apparently due to inaccuracies in the data. Where fine-scale DEMs are available, BMPs might be more effectively situated by considering the corresponding drainage pathways. The very different results produced at the three scales demonstrate that using the finest-grained elevation data may substantially improve placement of BMPs intended to mitigate for heavy animal use areas. The use of 30m DEMs for this purpose should be avoided. Fine-grained data such as 1m-resolution LiDAR-derived DEMs are available for Pennsylvania through PAMAP, and can be incorporated in the planning stages of BMP placement ultimately resulting in reducing agricultural sediment and nutrient loadings into local watersheds and the Chesapeake Bay

Age and length composition of Columbia Basin chinook, sockeye, and coho salmon at Bonneville Dam in 2000

In 2000, representative samples of adult Columbia Basin chinook (Oncorhynchus tshawytscha), sockeye (O. nerka), and coho salmon (O. kisutch), populations were collected at Bonneville Dam. Fish were trapped, anesthetized, sampled for scales and biological data, allowed to revive, and then released. Scales were examined to estimate age composition and the results contribute to an ongoing database for age class structure of Columbia Basin salmon populations. Based on scale analysis, four-year-old fish (from brood year (BY) 1996) were estimated to comprise 83% of the spring chinook, 31% of the summer chinook, and 32% of the upriver bright fall chinook salmon population. Five-year-old fish (BY 1995) were estimated to comprise 2% of the spring chinook, 26% of the summer chinook, and 40% of the fall chinook salmon population. Three-year-old fish (BY 1997) were estimated to comprise 14% of the spring chinook, 42% of the summer chinook, and 17% of the fall chinook salmon population. Two-year-olds accounted for approximately 11% of the fall chinook population. The sockeye salmon population sampled at Bonneville was predominantly four-year-old fish (95%), and the coho salmon population was 99.9% three-year-old fish (Age 1.1). Length analysis of the 2000 returns indicated that chinook salmon with a stream-type life history are larger (mean length) than the chinook salmon with an ocean-type life history. Trends in mean length over the sampling period were also analysis for returning 2000 chinook salmon. Fish of age classes 0.2, 1.1, 1.2, and 1.3 have a significant increase in mean length over time. Age classes 0.3 and 0.4 have no significant change over time and age 0.1 chinook salmon had a significant decrease in mean length over time. A year class regression over the past 11 years of data was used to predict spring and summer chinook salmon population sizes for 2001. Based on three-year-old returns, the relationship predicts four-year-old returns of 325,000 (± 111,600, 90% Predictive Interval [PI]) spring chinook and 27,800 (± 29,750, 90% PI) summer chinook salmon. Based on four-year-old returns, the relationship predicts five-year-old returns of 54,300 (± 40,600, 90% PI) spring chinook and 11,000 (± 3,250, 90% PI) summer chinook salmon. The 2001 run size predictions used in this report should be used with caution, these predictions are well beyond the range of previously observed data

Planetary nebulae after common-envelope phases initiated by low-mass red giants

It is likely that at least some planetary nebulae are composed of matter which was ejected from a binary star system during common-envelope (CE) evolution. For these planetary nebulae the ionizing component is the hot and luminous remnant of a giant which had its envelope ejected by a companion in the process of spiralling-in to its current short-period orbit. A large fraction of CE phases which end with ejection of the envelope are thought to be initiated by low-mass red giants, giants with inert, degenerate helium cores. We discuss the possible end-of-CE structures of such stars and their subsequent evolution to investigate for which structures planetary nebulae are formed. We assume that a planetary nebula forms if the remnant reaches an effective temperature greater than 30 kK within 10^4 yr of ejecting its envelope. We assume that the composition profile is unchanged during the CE phase so that possible remnant structures are parametrized by the end-of-CE core mass, envelope mass and entropy profile. We find that planetary nebulae are expected in post-CE systems with core masses greater than about 0.3 solar masses if remnants end the CE phase in thermal equilibrium. We show that whether the remnant undergoes a pre-white dwarf plateau phase depends on the prescribed end-of-CE envelope mass. Thus, observing a young post-CE system would constrain the end-of CE envelope mass and post-CE evolution.Comment: Published in MNRAS. 12 pages, 12 figures. Minor changes to match published versio

An Interpretable Deep Hierarchical Semantic Convolutional Neural Network for Lung Nodule Malignancy Classification

While deep learning methods are increasingly being applied to tasks such as computer-aided diagnosis, these models are difficult to interpret, do not incorporate prior domain knowledge, and are often considered as a "black-box." The lack of model interpretability hinders them from being fully understood by target users such as radiologists. In this paper, we present a novel interpretable deep hierarchical semantic convolutional neural network (HSCNN) to predict whether a given pulmonary nodule observed on a computed tomography (CT) scan is malignant. Our network provides two levels of output: 1) low-level radiologist semantic features, and 2) a high-level malignancy prediction score. The low-level semantic outputs quantify the diagnostic features used by radiologists and serve to explain how the model interprets the images in an expert-driven manner. The information from these low-level tasks, along with the representations learned by the convolutional layers, are then combined and used to infer the high-level task of predicting nodule malignancy. This unified architecture is trained by optimizing a global loss function including both low- and high-level tasks, thereby learning all the parameters within a joint framework. Our experimental results using the Lung Image Database Consortium (LIDC) show that the proposed method not only produces interpretable lung cancer predictions but also achieves significantly better results compared to common 3D CNN approaches

ELISA detection of phenazepam, etizolam, pyrazolam, flubromazepam, diclazepam and delorazepam in blood using Immunalysis® benzodiazepine kit

Phenazepam and etizolam were the first uncontrolled benzodiazepines available for sale in the UK. Pyrazolam, flubromazepam and diclazepam are not used medicinally anywhere in the world; they are produced exclusively for the uncontrolled, recreational market. It is important to know whether potentially abused drugs like these can be detected in routine toxicological screening tests. The purpose of this study was to evaluate whether the Immunalysis® Benzodiazepines ELISA kit could detect phenazepam, etizolam, pyrazolam, flubromazepam, diclazepam and its metabolite delorazepam. Their cross-reactivity was assessed by comparing the absorbance of the drug with that of oxazepam, the reference standard. This study found that these uncontrolled benzodiazepines cross-react sufficiently to produce a positive result with the Immunalysis® Benzodiazepine ELISA kit. Cross-reactivity ranged from 79 to 107% for phenazepam, etizolam, pyrazolam, flubromazepam, diclazepam and delorazepam fortified into blood. The results show that it is possible to detect these newer benzodiazepines with traditional forensic toxicology laboratory tools and it is important to include these benzodiazepines in the confirmation tests