Collision quenching effects in nitrogen and helium excited by a 30-keV electron beam

The quenching cross section for the 0-0 first negative band of nitrogen is determined for temperatures between 78 K and 300 K. As the temperature increases above 78 K, the quenching reaches a maximum at approximately 140 K and then decreases as 300 K is approached. At temperatures on the order of 5000 K, quenching is reported to increase with temperature and must therefore reach a minimum at some intermediate temperature between 300 K and 5000 K. By comparison, quenching of the 5016 A helium line increases continuously over the temperature range 78 K to 300 K

Groundwater chemistry of the Weaber Plain: preliminary results

In 2008, the Ord Irrigation Expansion Project was approved by the Western Australian Government to develop irrigated agriculture on the Weaber Plain. Construction of the M2 supply channel connecting the ORIA and the Weaber Plain, and the final period of irrigation design, environmental management and related approval processes, commenced later in 2009. This process followed a protracted period of public and private industry planning and environmental assessment (Kinhill 2000). This report summarises an analysis of groundwater salinity trends on the Ivanhoe and Weaber plains and the preliminary results of an intensive water-quality sampling program carried out in 2010 as part of Phase 1 of the project. The purpose of this report is to provide interim results to inform groundwater management plans required as part of the approval process for the development of the Weaber Plain

Groundwater chemistry of the Weaber Plain (Goomig Farmlands): baseline results 2010–13

The Ord River Irrigation Area (ORIA) is located in the north-east of the Kimberley region of Western Australia, near the town of Kununurra. The irrigation area was established in 1963 and over time developed to the current extent of 14 000 hectares (ha). The Weaber Plain (Goomig Farmlands) area is located north-north-east of the existing irrigation area, 30km from Kununurra, and has been identified as being suitable for irrigated agriculture for many decades. However, it was not until 2009, with state government support, that the 7400ha project commenced, with construction starting in 2010. State and Australian government environmental approvals required the proponent to install a groundwater monitoring network and develop a groundwater management plan. The environmental approvals required seasonal monitoring of groundwater to establish baseline groundwater chemistry conditions. The monitoring bores were sampled for up to three years and showed a large variation in water type and water quality across the Weaber and Knox Creek plains

Progress in the molecular biology of inherited bleeding disorders

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73391/1/j.1365-2516.2008.01718.x.pd

vrAIn: a deep learning approach tailoring computing and radio resources in virtualized RANs

Proceeding of: 25th Annual International Conference on Mobile Computing and Networking (MobiCom'19), October 21-25, 2019, Los Cabos, Mexico.The virtualization of radio access networks (vRAN) is the last milestone in the NFV revolution. However, the complex dependencies between computing and radio resources make vRAN resource control particularly daunting. We present vrAIn, a dynamic resource controller for vRANs based on deep reinforcement learning. First, we use an autoencoder to project high-dimensional context data (traffic and signal quality patterns) into a latent representation. Then, we use a deep deterministic policy gradient (DDPG) algorithm based on an actor-critic neural network structure and a classifier to map (encoded) contexts into resource control decisions. We have implemented vrAIn using an open-source LTE stack over different platforms. Our results show that vrAIn successfully derives appropriate compute and radio control actions irrespective of the platform and context: (i) it provides savings in computational capacity of up to 30% over CPU-unaware methods; (ii) it improves the probability of meeting QoS targets by 25% over static allocation policies using similar CPU resources in average; (iii) upon CPU capacity shortage, it improves throughput performance by 25% over state-of-the-art schemes; and (iv) it performs close to optimal policies resulting from an offline oracle. To the best of our knowledge, this is the first work that thoroughly studies the computational behavior of vRANs, and the first approach to a model-free solution that does not need to assume any particular vRAN platform or system conditions.The work of University Carlos III of Madrid was supported by H2020 5GMoNArch project (grant agreement no. 761445) and H2020 5G-TOURS project (grant agreement no. 856950). The work of NEC Laboratories Europe was supported by H2020 5GTRANSFORMER project (grant agreement no. 761536) and 5GROWTH project (grant agreement no. 856709). The work of University of Cartagena was supported by Grant AEI/FEDER TEC2016-76465-C2-1-R (AIM) and Grant FPU14/03701.Publicad

Hemophilia gene therapy knowledge and perceptions: Results of an international survey

Background Hemophilia gene therapy is a rapidly evolving therapeutic approach in which a number of programs are approaching clinical development completion. Objective The aim of this study was to evaluate knowledge and perceptions of a variety of health care practitioners and scientists about gene therapy for hemophilia. Methods This survey study was conducted February 1 to 18, 2019. Survey participants were members of the ISTH, European Hemophilia Consortium, European Hematology Association, or European Association for Hemophilia and Allied Disorders with valid email contacts. The online survey consisted of 36 questions covering demographic information, perceptions and knowledge of gene therapy for hemophilia, and educational preferences. Survey results were summarized using descriptive statistics. Results Of the 5117 survey recipients, 201 responded from 55 countries (4% response rate). Most respondents (66%) were physicians, and 59% were physicians directly involved in the care of people with hemophilia. Among physician respondents directly involved in hemophilia care, 35% lacked the ability to explain the science of adeno-associated viral gene therapy for hemophilia, and 40% indicated limited ability or lack of comfort answering patient questions about gene therapy for hemophilia based on clinical trial results to date. Overall, 75% of survey respondents answered 10 single-answer knowledge questions correctly, 13% incorrectly, and 12% were unsure of the correct answers. Conclusions This survey highlighted knowledge gaps and educational needs related to gene therapy for hemophilia and, along with other inputs, has informed the development of "Gene Therapy in Hemophilia: An ISTH Education Initiative.

Minimal dataset for post-registration surveillance of new drugs in hemophilia: communication from the SSC of the ISTH

Clinical epidemiolog

Continuous-time spike-based reinforcement learning for working memory tasks

As the brain purportedly employs on-policy reinforcement learning compatible with SARSA learning, and most interesting cognitive tasks require some form of memory while taking place in continuous-time, recent work has developed plausible reinforcement learning schemes that are compatible with these requirements. Lacking is a formulation of both computation and learning in terms of spiking neurons. Such a formulation creates both a closer mapping to biology, and also expresses such learning in terms of asynchronous and sparse neural computation. We present a spiking neural network with memory that learns cognitive tasks in continuous time. Learning is biologically plausibly implemented using the AuGMeNT framework, and we show how separate spiking forward and feedback networks suffice for learning the tasks just as fast the analog CT-AuGMeNT counterpart, while computing efficiently using very few spikes: 1–20 Hz on average

Development of a hybrid Bayesian network model for predicting acute fish toxicity using multiple lines of evidence

A hybrid Bayesian network (BN) was developed for predicting the acute toxicity of chemicals to fish, using data from fish embryo toxicity (FET) testing in combination with other information. This model can support the use of FET data in a Weight-of-Evidence (WOE) approach for replacing the use of ju-venile fish. The BN predicted correct toxicity intervals for 69%–80% of the tested substances. The model was most sensitive to components quantified by toxicity data, and least sensitive to compo-nents quantified by expert knowledge. The model is publicly available through a web interface. Fur-ther development of this model should include additional lines of evidence, refinement of the discre-tisation, and training with a larger dataset for weighting of the lines of evidence. A refined version of this model can be a useful tool for predicting acute fish toxicity, and a contribution to more quantitative WOE approaches for ecotoxicology and environmental assessment more generally.publishedVersio