Dissolved gas and isotopic tracers of denitrification

We present results from field studies in California (USA) where tritium-helium age dating is used in conjunction with major gases (N{sub 2}, O{sub 2}, CH{sub 4}, CO{sub 2}), noble gases (He, Ne, Ar, Kr, Xe), and stable isotopes ({sup 15}N/{sup 14}N, {sup 18}O/{sup 16}O) in order to document nitrate loading and denitrification associated with confined animal agricultural operations and septic systems. Preliminary results show that in-field extraction of the full suite of dissolved gases will be possible using a new Gas Extraction System under development to augment the current Noble Gas Mass Spectrometry and Membrane Inlet Mass Spectrometry techniques. Ascribing observed groundwater nitrate levels to specific current and past land use practices is often complicated by uncertainty in groundwater age and the degree and locus of dentrification. Groundwater age dating at dairy field sites using the {sup 3}H-{sup 3}He method indicates that the highest nitrate concentrations (150-260 mg/L-NO3) occur in waters with apparent ages of <5 yrs, whereas older waters contain excess N{sub 2} from saturated zone denitrification [1]. At a residential septic system site in Livermore, CA, waters with young apparent ages (<1 yr) proximal to leach line drainage have lower nitrate concentrations and elevated nitrate {delta}{sup 15}N and {delta}{sup 18}O values consistent with denitrification, but little evidence for excess N{sub 2}, indicating that denitrification is occurring in the unsaturated zone. Degassing of groundwater can complicate efforts to calculate travel times [2] and to quantify denitrification. Degassed groundwater underlying dairy operations is formed by two distinct mechanisms: (1) recharge of manure lagoon water affected by biogenic gas ebullition [3] and (2) saturated zone denitrification producing N{sub 2} gas above solubility in groundwater. Gas loss due to both mechanisms is evident in the concentrations of noble gases and major gases in dairy groundwater samples

One-health simulation modelling : assessment of control strategies against the spread of influenza between swine and human populations using NAADSM

Simulation models implemented using a range of parameters offer a useful approach to identifying effective disease intervention strategies. The objective of this study was to investigate the effects of key control strategies to mitigate the simultaneous spread of influenza among and between swine and human populations. We used the pandemic H1N1 2009 virus as a case study. The study population included swine herds (488 herds) and households-of-people (29 707 households) within a county in Ontario, Canada. Households were categorized as: (i) rural households with swine workers, (ii) rural households without swine workers and (iii) urban households without swine workers. Seventy-two scenarios were investigated based on a combination of the parameters of speed of detection and control strategies, such as quarantine strategy, effectiveness of movement restriction and ring vaccination strategy, all assessed at three levels of transmissibility of the virus at the swine-human interface. Results showed that the speed of detection of the infected units combined with the quarantine strategy had the largest impact on the duration and size of outbreaks. A combination of fast to moderate speed of the detection (where infected units were detected within 5-10 days since first infection) and quarantine of the detected units alone contained the outbreak within the swine population in most of the simulated outbreaks. Ring vaccination had no added beneficial effect. In conclusion, our study suggests that the early detection (and therefore effective surveillance) and effective quarantine had the largest impact in the control of the influenza spread, consistent with earlier studies. To our knowledge, no study had previously assessed the impact of the combination of different intervention strategies involving the simultaneous spread of influenza between swine and human populations

A review of simulation modelling approaches used for the spread of zoonotic influenza viruses in animal and human populations

Increasing incidences of emerging and re-emerging diseases that are mostly zoonotic (e.g. severe acute respiratory syndrome, avian influenza H5N1, pandemic influenza) has led to the need for a multidisciplinary approach to tackling these threats to public and animal health. Accordingly, a global movement of 'One-Health/One-Medicine' has been launched to foster collaborative efforts amongst animal and human health officials and researchers to address these problems. Historical evidence points to the fact that pandemics caused by influenza A viruses remain a major zoonotic threat to mankind. Recently, a range of mathematical and computer simulation modelling methods and tools have increasingly been applied to improve our understanding of disease transmission dynamics, contingency planning and to support policy decisions on disease outbreak management. This review provides an overview of methods, approaches and software used for modelling the spread of zoonotic influenza viruses in animals and humans, particularly those related to the animal-human interface. Modelling parameters used in these studies are summarized to provide references for future work. This review highlights the limited application of modelling research to influenza in animals and at the animal-human interface, in marked contrast to the large volume of its research in human populations. Although swine are widely recognized as a potential host for generating novel influenza viruses, and that some of these viruses, including pandemic influenza A/H1N1 2009, have been shown to be readily transmissible between humans and swine, only one study was found related to the modelling of influenza spread at the swine-human interface. Significant gaps in the knowledge of frequency of novel viral strains evolution in pigs, farm-level natural history of influenza infection, incidences of influenza transmission between farms and between swine and humans are clearly evident. Therefore, there is a need to direct additional research to the study of influenza transmission dynamics in animals and at the animal-human interface

Dirty Bomb Fallout

At present, there is a significant need to develop decontamination agents that can be used effectively after detonation of a radiological dispersal device (RDD) in an urban environment. There is also a need for the development of reproducible test surfaces to be used to determine the efficacy of the agent being developed. Researchers at Lawrence Livermore National Laboratory (LLNL), under the auspices of the US Department of Energy (DoE), conducted a field study to evaluate the deposition of an explosively dispersed radionuclide surrogate (CsCl) on grime-bearing and non-grime-bearing urban surfaces. The goal was to investigate the preparation and contamination of urban surfaces that closely mimic what one would expect to encounter following the detonation of an RDD. Migration of Cs into concrete surfaces was investigated in detail. Many non-proliferation, security and response organizations that have modeled RDD scenarios use cesium-137, as well as cobalt-60, strontium-90, americium-241 as the most likely RDD agents. Cesium-137 is an isotope of concern for possible use in an RDD due to its potential availability resulting from its widespread legitimate use in construction, geotechnical and medical industrial devices. In some Cs-containing instruments the Cesium-137 is present as the highly dispersible and water soluble salt, cesium chloride (CsCl). In this form Cs is able to rapidly disperse in the environment, as witnessed in the 1987 Goiania accident in Brazil, when inadvertent dispersal of a radiotherapy source resulted in fatalities and injuries

Field Evaluation of the Explosive Deposition of Cesium on Concrete Surfaces Following the Detonation of a Mock Radiological Dispersal Device (RDD)

Researchers at Lawrence Livermore National Laboratory conducted a field study to evaluate the deposition of an explosively dispersed radionuclide surrogate (CsCl) on grime and non-grime containing urban surfaces. An additional objective of this study was to evaluate several laboratory surface contamination techniques for the preparation of mock urban surfaces in order to determine the method that most closely mimics surface contamination following an RDD event. The field study was conducted at the LLNL Site 300 Contained Firing Facility (CFF). For our study, we detonated a mock RDD made using C4 and non-radioactive CsCl. Lab prepared concrete samples (3.8 cm x 7.6 cm cylinders) were made using 4 different conditioning regimes to mimic a range of conditions that may be encountered during an RDD event. This sample set included dry, wet, carbonated and non-carbonated cores with and without the application of urban grime. In addition, concreted samples (13 cm x 13 cm x 5 cm) removed from an urban surface were placed inside the CFF chamber. The samples were placed inside the firing chamber at 3 different distances from the mock RDD device. Following the detonation of the mock RDD, the samples were removed from the firing chamber and selected cores were characterized by laser ablation and scanning electron microscopy. Preliminary results suggest that Cs migrates into the concrete samples and the presence of a grime layer does not appear to impede this migration

Dyadic Speech-based Affect Recognition using DAMI-P2C Parent-child Multimodal Interaction Dataset

Automatic speech-based affect recognition of individuals in dyadic conversation is a challenging task, in part because of its heavy reliance on manual pre-processing. Traditional approaches frequently require hand-crafted speech features and segmentation of speaker turns. In this work, we design end-to-end deep learning methods to recognize each person's affective expression in an audio stream with two speakers, automatically discovering features and time regions relevant to the target speaker's affect. We integrate a local attention mechanism into the end-to-end architecture and compare the performance of three attention implementations -- one mean pooling and two weighted pooling methods. Our results show that the proposed weighted-pooling attention solutions are able to learn to focus on the regions containing target speaker's affective information and successfully extract the individual's valence and arousal intensity. Here we introduce and use a "dyadic affect in multimodal interaction - parent to child" (DAMI-P2C) dataset collected in a study of 34 families, where a parent and a child (3-7 years old) engage in reading storybooks together. In contrast to existing public datasets for affect recognition, each instance for both speakers in the DAMI-P2C dataset is annotated for the perceived affect by three labelers. To encourage more research on the challenging task of multi-speaker affect sensing, we make the annotated DAMI-P2C dataset publicly available, including acoustic features of the dyads' raw audios, affect annotations, and a diverse set of developmental, social, and demographic profiles of each dyad.Comment: Accepted by the 2020 International Conference on Multimodal Interaction (ICMI'20

Nitrate Biogeochemistry and Reactive Transport in California Groundwater: LDRD Final Report

Nitrate is the number one drinking water contaminant in the United States. It is pervasive in surface and groundwater systems,and its principal anthropogenic sources have increased dramatically in the last 50 years. In California alone, one third of the public drinking-water wells has been lost since 1988 and nitrate contamination is the most common reason for abandonment. Effective nitrate management in groundwater is complicated by uncertainties related to multiple point and non-point sources, hydrogeologic complexity, geochemical reactivity, and quantification of denitrification processes. In this paper, we review an integrated experimental and simulation-based framework being developed to study the fate of nitrate in a 25 km-long groundwater subbasin south of San Jose, California, a historically agricultural area now undergoing rapid urbanization with increasing demands for groundwater. The modeling approach is driven by a need to integrate new and archival data that support the hypothesis that nitrate fate and transport at the basin scale is intricately related to hydrostratigraphic complexity, variability of flow paths and groundwater residence times, microbial activity, and multiple geochemical reaction mechanisms. This study synthesizes these disparate and multi-scale data into a three-dimensional and highly resolved reactive transport modeling framework

Observation of two new Ξb−\Xi_b^- baryon resonances

Two structures are observed close to the kinematic threshold in the $\Xi_b^0 \pi^-$ mass spectrum in a sample of proton-proton collision data, corresponding to an integrated luminosity of 3.0 fb$^{-1}$ recorded by the LHCb experiment. In the quark model, two baryonic resonances with quark content $bds$ are expected in this mass region: the spin-parity $J^P = \frac{1}{2}^+$ and $J^P=\frac{3}{2}^+$ states, denoted $\Xi_b^{\prime -}$ and $\Xi_b^{*-}$. Interpreting the structures as these resonances, we measure the mass differences and the width of the heavier state to be $m(\Xi_b^{\prime -}) - m(\Xi_b^0) - m(\pi^{-}) = 3.653 \pm 0.018 \pm 0.006$ MeV$/c^2$, $m(\Xi_b^{*-}) - m(\Xi_b^0) - m(\pi^{-}) = 23.96 \pm 0.12 \pm 0.06$ MeV$/c^2$, $\Gamma(\Xi_b^{*-}) = 1.65 \pm 0.31 \pm 0.10$ MeV, where the first and second uncertainties are statistical and systematic, respectively. The width of the lighter state is consistent with zero, and we place an upper limit of $\Gamma(\Xi_b^{\prime -}) < 0.08$ MeV at 95% confidence level. Relative production rates of these states are also reported.Comment: 17 pages, 2 figure