Asian Longhorned Tick

The Asian longhorned tick (Haemophysalis longicorns Neumann; alternative names include Asian longhorned tick, Asian tick, bush tick, New Zealand cattle tick) is a species of hard tick in the family Ixodidae. It is native to eastern China, Japan, the Russian Far East and Korea. It has also established in Australia, New Zealand and several Pacific islands, where it is considered a severe exotic pest of livestock. In late 2017, the United States Department of Agriculture’s National Veterinary Services Laboratories (NVSL) confirmed the presence of the Asian longhorned tick in the United States. These ticks were first identified in New Jersey, but have since been found in archival samples from West Virginia as far back as 2010. The origin of the tick in the US remains unknown. Some possible routes of entry include entering on domestic pets, horses, livestock or humans. The real impact of the introduction of this tick into the US is not clear at this time, but animal health officials are concerned about potential detrimental impacts on livestock and wildlife

Radiation damage in the LHCb vertex locator

The LHCb Vertex Locator (VELO) is a silicon strip detector designed to reconstruct charged particle trajectories and vertices produced at the LHCb interaction region. During the first two years of data collection, the 84 VELO sensors have been exposed to a range of fluences up to a maximum value of approximately 45 × 1012 1 MeV neutron equivalent (1 MeV neq). At the operational sensor temperature of approximately −7 °C, the average rate of sensor current increase is 18 μA per fb−1, in excellent agreement with predictions. The silicon effective bandgap has been determined using current versus temperature scan data after irradiation, with an average value of Eg = 1.16±0.03±0.04 eV obtained. The first observation of n+-on-n sensor type inversion at the LHC has been made, occurring at a fluence of around 15 × 1012 of 1 MeV neq. The only n+-on-p sensors in use at the LHC have also been studied. With an initial fluence of approximately 3 × 1012 1 MeV neq, a decrease in the Effective Depletion Voltage (EDV) of around 25 V is observed. Following this initial decrease, the EDV increases at a comparable rate to the type inverted n+-on-n type sensors, with rates of (1.43±0.16) × 10−12 V/ 1 MeV neq and (1.35±0.25) × 10−12 V/ 1 MeV neq measured for n+-on-p and n+-on-n type sensors, respectively. A reduction in the charge collection efficiency due to an unexpected effect involving the second metal layer readout lines is observed

A Markov-Chain Monte-Carlo Based Method for Flaw Detection in Beams

A Bayesian inference methodology using a Markov Chain Monte Carlo (MCMC) sampling procedure is presented for estimating the parameters of computational structural models. This methodology combines prior information, measured data, and forward models to produce a posterior distribution for the system parameters of structural models that is most consistent with all available data. The MCMC procedure is based upon a Metropolis-Hastings algorithm that is shown to function effectively with noisy data, incomplete data sets, and mismatched computational nodes/measurement points. A series of numerical test cases based upon a cantilever beam is presented. The results demonstrate that the algorithm is able to estimate model parameters utilizing experimental data for the nodal displacements resulting from specified forces

The impacts of environmental warming on Odonata: a review

Climate change brings with it unprecedented rates of increase in environmental temperature, which will have major consequences for the earth's flora and fauna. The Odonata represent a taxon that has many strong links to this abiotic factor due to its tropical evolutionary history and adaptations to temperate climates. Temperature is known to affect odonate physiology including life-history traits such as developmental rate, phenology and seasonal regulation as well as immune function and the production of pigment for thermoregulation. A range of behaviours are likely to be affected which will, in turn, influence other parts of the aquatic ecosystem, primarily through trophic interactions. Temperature may influence changes in geographical distributions, through a shifting of species' fundamental niches, changes in the distribution of suitable habitat and variation in the dispersal ability of species. Finally, such a rapid change in the environment results in a strong selective pressure towards adaptation to cope and the inevitable loss of some populations and, potentially, species. Where data are lacking for odonates, studies on other invertebrate groups will be considered. Finally, directions for research are suggested, particularly laboratory studies that investigate underlying causes of climate-driven macroecological patterns

Multi-Layer Perceptrons and Support Vector Machines for Detection Problems with Low False Alarm Requirements: an Eight-Month Progress Report

In this project, the basic problem is to automatically separate test samples into one of two categories: clean or corrupt. This type of classification problem is known as a two-class classification problem or detection problem. In what follows, we refer to clean examples as negative examples and corrupt examples as positive examples. In a detection problem, a classifier decision on any one sample can be grouped into one of four decision categories: true negative, true positive, false negative and false positive. These four categories are illustrated by Table 1. True negatives and true positives are cases where the classifier has made the correct decision. False positives are cases where the classifier decides positive when the true nature of the sample was negative, and false negatives are cases where the classifier decides negative when the sample was actually positive. To evaluate the performance of a classifier, we run the classifier on all the samples of a data set and then count all the instances of true negatives, true positives, false negatives, and false positives. All of the performance metrics in this report are then formed from a combination of these four basic decision categories

Developing institutional capacity for reproductive health in humanitarian settings: A descriptive study

© 2015 Tran et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction. Institutions play a central role in advancing the field of reproductive health in humanitarian settings (RHHS), yet little is known about organizational capacity to deliver RHHS and how this has developed over the past decade. This study aimed to document the current institutional experiences and capacities related to RHHS. Materials and Methods. Descriptive study using an online questionnaire tool. Results. Respondents represented 82 institutions from 48 countries, of which two-thirds originated from low-and middle-income countries. RHHS work was found not to be restricted to humanitarian agencies (25%), but was also embraced by development organizations (25%) and institutions with dual humanitarian and development mandates (50%). Agencies reported working with refugees (81%), internally-displaced (87%) and stateless persons (20%), in camp-based settings (78%), and in urban (83%) and rural settings (78%). Sixtyeight percent of represented institutions indicated having an RHHS-related policy, 79% an accountability mechanism including humanitarian work, and 90% formal partnerships with other institutions. Seventy-three percent reported routinely appointing RH focal points to ensure coordination of RHHS implementation. There was reported progress in RHHSrelated disaster risk reduction (DRR), emergency management and coordination, delivery of the Minimum Initial Services Package (MISP) for RH, comprehensive RH services in post-crisis/recovery situations, gender mainstreaming, and community-based programming. Other reported institutional areas of work included capacity development, program delivery, advocacy/policy work, followed by research and donor activities. Except for abortion-related services, respondents cited improved efforts in advocacy, capacity development and technical support in their institutions for RHHS to address clinical services, including maternal and newborn health, sexual violence prevention and response, HIV prevention, management of sexually-transmitted infections, adolescent RH, and family planning. Approximately half of participants reported that their institutions had experienced an increase in dedicated budget and staff for RHHS, a fifth no change, and 1 in 10 a decrease. The Interagency RH Kits were reportedly the most commonly used supplies to support RHHS implementation. Conclusion. The results suggest overall growth in institutional capacity in RHHS over the past decade, indicating that the field has matured and expanded from crisis response to include RHHS into DRR and other elements of the emergency management cycle. It is critical to consolidate the progress to date, address gaps, and sustain momentum

The potential of a mobile group blog to support cultural learning among overseas students

We explored the use of mobile social software, in the form of a mobile group blog, to assist cultural learning. The potential of using this technology for cultural adaptation among overseas students was examined as those students adapted to the everyday life of studying abroad. Two pilot studies and a successful field study of a mobile group blog as used by UK overseas students are reported. A further study with prospective overseas students witnessing this ‘moblogging’ in China revealed the advantages of communicating through this technology as a form of peer-supported preparation for cultural adaptation. Potential advantages for learning a second language via this system, were highlighted as communication was interweaved with cultural adaptation and exercised in the blog entries. Given mobile internet, the language experience together with cultural observation impressively supported these students' growing confidence with time, space and imagination

Regional Seismic Discrimination Optimization With and Without Nuclear Test Data: Western U.S. Examples

The western U.S. has abundant natural seismicity, historic nuclear explosion data, and widespread mine blasts, making it a good testing ground to study the performance of regional source-type discrimination techniques. We have assembled and measured a large set of these events to systematically explore how to best optimize discrimination performance. Nuclear explosions can be discriminated from a background of earthquakes using regional phase (Pn, Pg, Sn, Lg) amplitude measures such as high frequency P/S ratios. The discrimination performance is improved if the amplitudes can be corrected for source size and path length effects. We show good results are achieved using earthquakes alone to calibrate for these effects with the MDAC technique (Walter and Taylor, 2001). We show significant further improvement is then possible by combining multiple MDAC amplitude ratios using an optimized weighting technique such as Linear Discriminant Analysis (LDA). However this requires data or models for both earthquakes and explosions. In many areas of the world regional distance nuclear explosion data is lacking, but mine blast data is available. Mine explosions are often designed to fracture and/or move rock, giving them different frequency and amplitude behavior than contained chemical shots, which seismically look like nuclear tests. Here we explore discrimination performance differences between explosion types, the possible disparity in the optimization parameters that would be chosen if only chemical explosions were available and the corresponding effect of that disparity on nuclear explosion discrimination. There are a variety of additional techniques in the literature also having the potential to improve regional high frequency P/S discrimination. We explore two of these here: three-component averaging and maximum phase amplitude measures. Typical discrimination studies use only the vertical component measures and for some historic regional nuclear records these are all that are available. However S-waves are often better recorded on the horizontal components and some studies have shown that using a three-component average or a vertical-P/horizontal-S or other three-component measure can improve discrimination over using the vertical alone (e.g. Kim et al. 1997; Bowers et al 2001). Here we compare the performance of vertical and three-component measures on the western U. S. test set. A complication in regional discrimination is the variation in P and S-wave propagation with region. The dominantly observed regional high frequency S-wave can vary with path between Sn and Lg in a spatially complex way. Since the relative lack of high frequency S-waves is the signature of an explosion, failing to account for this could lead to misidentifying an earthquake as an explosion. The regional P phases Pn and Pg vary similarly with path and also with distance, with Pg sometimes being a strong phase at near regional distances but not far regional. One way to try and handle these issues is to correct for all four regional phases but choose the phase with the maximum amplitude. A variation on this strategy is to always use Pn but choose the maximum S phase (e.g. Bottone et al. 2002). Here we compare the discrimination performance of several different (max P)/(max S) measures to vertical, three-component and multivariate measures. Our preliminary results show that multivariate measures perform much better than single ratios, though transportability of the LDA weights between regions is an issue. Also in our preliminary results, we do not find large discrimination performance improvements with three-component averages and maximum phase amplitude measures compared to using the vertical component alone