Effluent Treatment Facility tritium emissions monitoring

An Environmental Protection Agency (EPA) approved sampling and analysis protocol was developed and executed to verify atmospheric emissions compliance for the new Savannah River Site (SRS) F/H area Effluent Treatment Facility. Sampling equipment was fabricated, installed, and tested at stack monitoring points for filtrable particulate radionuclides, radioactive iodine, and tritium. The only detectable anthropogenic radionuclides released from Effluent Treatment Facility stacks during monitoring were iodine-129 and tritium oxide. This paper only examines the collection and analysis of tritium oxide

Distribution of radionuclides in L-Lake surface sediments phase 3

Gamma-emitting radionuclides in L Lake were examined in situ with an underwater High Purity Germanium (HPGe) detector and further studied by retrieving various sediment samples for analysis by HPGe gamma spectrometry. The predominant man-made radionuclide detected was cesium-137. These measurements constituted Phase 3 of a four phase strategy for characterizing L-Lake contaminants. The data provided by these studies will be utilized in the preparation of an Environmental Impact Statement that evaluates the consequences of discontinuing river water pumping to the man-made cooling water reservoirs on the Savannah River Site. A site evaluation report will also be prepared for the L-Lake basin

Dairy cattle in a temperate climate: the effects of weather on milk yield and composition depend on management

A better understanding of how livestock respond to weather is essential to enable farming to adapt to a changing climate. Climate change is mainly expected to impact dairy cattle through heat stress and an increase in the frequency of extreme weather events. We investigated the effects of weather on milk yield and composition (fat and protein content) in an experimental dairy herd in Scotland over 21 years. Holstein Friesian cows were either housed indoors in winter and grazed over the summer or were continuously housed. Milk yield was measured daily, resulting in 762 786 test day records from 1369 individuals, and fat and protein percentage were sampled once a week, giving 89 331 records from 1220 cows/trait. The relative influence of 11 weather elements, measured from local outdoor weather stations, and two indices of temperature and humidity (THI), indicators of heat stress, were compared using separate maximum likelihood models for each element or index. Models containing a direct measure of temperature (dry bulb, wet bulb, grass or soil temperature) or a THI provided the best fits to milk yield and fat data; wind speed and the number of hours of sunshine were most important in explaining protein content. Weather elements summarised across a week's timescale from the test day usually explained milk yield and fat content better than shorter-scale (3 day, test day, test day -1) metrics. Then, examining a subset of key weather variables using restricted maximum likelihood, we found that THI, wind speed and the number of hours of sunshine influenced milk yield and composition. The shape and magnitude of these effects depended on whether animals were inside or outside on the test day. The milk yield of cows outdoors was lower at the extremes of THI than at average values, and the highest yields were obtained when THI, recorded at 0900 h, was 55 units. Cows indoors decreased milk yield as THI increased. Fat content was lower at higher THIs than at intermediate THIs in both environments. Protein content decreased as THI increased in animals kept indoors and outdoors, and the rate of decrease was greater when animals were outside than when they were inside. Moderate wind speeds appeared to alleviate heat stress. These results show that milk yield and composition are impacted at the upper extreme of THI under conditions currently experienced in Scotland, where animals have so far experienced little pressure to adapt to heat stress

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

'Who Wrote 2 Thessalonians:A Fresh Look at an Old Problem'

In light of the New Perspective on Paul, recognition of apocalyptic as a central category in Pauline theology, and the crumbling consensus concerning seven authentic epistles of Paul, it is time to reconsider the arguments for the authenticity of his letters. Here the specific question of the authorship of 2 Thessalonians is re-examined. It is noted that many of the standard arguments for or against the authenticity of 2 Thessalonians are either irrelevant or inconclusive. This discussion seeks to reveal the slender evidential basis of certain ‘classic’ arguments against the authenticity of the letter, and also to present some fresh reasons why the epistle should be regarded as written by Paul. The implications of including 2 Thessalonians among the authentic Pauline writings are then examined. In particular, it is suggested that the development in Paul’s thinking as reflected in 2 Thessalonians reveals that his theological formulations developed in response to situations in his fledgling communities. In this regard, Paul’s theological positions emerged through a negotiated response to pressing pastoral situations

Psychological distress and quality of life in lung cancer: The role of health-related stigma, illness appraisals and social constraints

Objective: Health-related stigma is associated with negative psychological and quality of life outcomes in lung cancer patients. This study describes the impact of stigma on lung cancer patients\u27 psychological distress and quality of life and explores the role of social constraints and illness appraisal as mediators of effect. Methods: A self-administered cross-sectional survey examined psychological distress and quality of life in 151 people (59% response rate) diagnosed with lung cancer from Queensland and New South Wales. Health-related stigma, social constraints and illness appraisals were assessed as predictors of adjustment outcomes. Results: Forty-nine percent of patients reported elevated anxiety; 41% were depressed; and 51% had high global distress. Health-related stigma was significantly related to global psychological distress and quality of life with greater stigma and shame related to poorer outcomes. These effects were mediated by illness appraisals and social constraints. Conclusions: Health-related stigma appears to contribute to poorer adjustment by constraining interpersonal discussions about cancer and heightening feelings of threat. There is a need for the development and evaluation of interventions to ameliorate the negative effects of health-related stigma among lung cancer patients

Schools out : Adam Smith and pre-disciplinary international political economy

In this article, I argue that invocations of Adam Smith in international political economy (IPE) often reveal the influence therein of a disciplinary ontological disaggregation of economic and non-economic rationality, which I claim is obscured by the tendency to map its complex intellectual contours in terms of competing schools. I trace the origins of the disciplinary characterisation of Smith as the founder of IPE's liberal tradition to invocations of his thought by centrally important figures in the perceived Austrian, Chicago and German historical schools of economics, and reflect upon the significance to IPE of the reiteration of this portrayal by apparent members of its so-called American and British schools. I additionally contrast these interpretations to those put forward by scholars who seek to interpret IPE and Smith's contribution to it in pre-disciplinary terms, which I claim reflects a distinct ontology to that attributed to the British school of IPE with which their work is often associated. I therefore contend that reflection upon invocations of Smith's thought in IPE problematises the longstanding tendency to map its intellectual terrain in terms of competing schools, reveals that the disciplinary ontological consensus that informs this tendency impacts upon articulations of its core concerns and suggests that a pre-disciplinary approach offers an alternative lens through which such concerns might be more effectively framed

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

Scaling ozone responses of forest trees to the ecosystem level in a changing climate

Many uncertainties remain regarding how climate change will alter the structure and function of forest ecosystems. At the Aspen FACE experiment in northern Wisconsin, we are attempting to understand how an aspen/birch/maple forest ecosystem responds to long-term exposure to elevated carbon dioxide (CO 2 ) and ozone (O 3 ), alone and in combination, from establishment onward. We examine how O 3 affects the flow of carbon through the ecosystem from the leaf level through to the roots and into the soil micro-organisms in present and future atmospheric CO 2 conditions. We provide evidence of adverse effects of O 3 , with or without co-occurring elevated CO 2 , that cascade through the entire ecosystem impacting complex trophic interactions and food webs on all three species in the study: trembling aspen ( Populus tremuloides Michx . ), paper birch ( Betula papyrifera Marsh), and sugar maple ( Acer saccharum Marsh). Interestingly, the negative effect of O 3 on the growth of sugar maple did not become evident until 3 years into the study. The negative effect of O 3 effect was most noticeable on paper birch trees growing under elevated CO 2 . Our results demonstrate the importance of long-term studies to detect subtle effects of atmospheric change and of the need for studies of interacting stresses whose responses could not be predicted by studies of single factors. In biologically complex forest ecosystems, effects at one scale can be very different from those at another scale. For scaling purposes, then, linking process with canopy level models is essential if O 3 impacts are to be accurately predicted. Finally, we describe how outputs from our long-term multispecies Aspen FACE experiment are being used to develop simple, coupled models to estimate productivity gain/loss from changing O 3 .Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72464/1/j.1365-3040.2005.01362.x.pd

Patient-specific Alzheimer-like pathology in trisomy 21 cerebral organoids reveals BACE2 as a gene dose-sensitive AD suppressor in human brain

A population of >6 million people worldwide at high risk of Alzheimer’s disease (AD) are those with Down Syndrome (DS, caused by trisomy 21 (T21)), 70% of whom develop dementia during lifetime, caused by an extra copy of β-amyloid-(Aβ)-precursor-protein gene. We report AD-like pathology in cerebral organoids grown in vitro from non-invasively sampled strands of hair from 71% of DS donors. The pathology consisted of extracellular diffuse and fibrillar Aβ deposits, hyperphosphorylated/pathologically conformed Tau, and premature neuronal loss. Presence/absence of AD-like pathology was donor-specific (reproducible between individual organoids/iPSC lines/experiments). Pathology could be triggered in pathology-negative T21 organoids by CRISPR/Cas9-mediated elimination of the third copy of chromosome-21-gene BACE2, but prevented by combined chemical β and γ-secretase inhibition. We found that T21-organoids secrete increased proportions of Aβ-preventing (Aβ1-19) and Aβ-degradation products (Aβ1-20 and Aβ1-34). We show these profiles mirror in cerebrospinal fluid of people with DS. We demonstrate that this protective mechanism is mediated by BACE2-trisomy and cross-inhibited by clinically trialled BACE1-inhibitors. Combined, our data prove the physiological role of BACE2 as a dose-sensitive AD-suppressor gene, potentially explaining the dementia delay in ~30% of people with DS. We also show that DS cerebral organoids could be explored as pre-morbid AD-risk population detector and a system for hypothesis-free drug screens as well as identification of natural suppressor genes for neurodegenerative diseases