Bibliometrics Seminar

On 22 May 2014, the University Library System, University of Pittsburgh, held a Bibliometrics Seminar, a program detailing several research library service models for support of research evaluation and assessment. Three of the featured speakers--from academic libraries in the USA (Mayo), the UK (Rowlands), and Australia (Thomas)--discuss the development and operation of such services in their organizations, noting the drivers for development, the process of setting up the service, and the impact of the service on both the library and the institution. A faculty colleague (Larsen) talks about his needs for research assessment as both a senior researcher and university manager. Presentation 1: "Providing a Library Metrics Service: a perspective from an academic library within an Australian University" by Dr. Amberyn Thomas, Manager, Scholarly Publications, University of Queensland, Australia. Presentation 2: "Library Research Services at the University of Leicester, UK" by Ian Rowlands, Research Services Manager and University Bibliometrician, University of Leicester. Presentation 3: "Research Connection: Expertise to Advance Your Success" by Alexa Mayo, MLS AHIP, Health Sciences and Human Services Library, University of Maryland, Baltimore. Presentation 4: "Bibliometric Research Services - an iSchool Dean's Perspective" by Ronald L. Larsen, Dean and Professor, School of Information Sciences, University of Pittsburgh. The program for the event and a recording of the presentations are also included

Seasonal variation and impact of waste-water lagoons as larval habitat on the population dynamics of Culicoides sonorensis (Diptera:Ceratpogonidae) at two dairy farms in northern California.

The Sacramento (northern Central) Valley of California (CA) has a hot Mediterranean climate and a diverse ecological landscape that is impacted extensively by human activities, which include the intensive farming of crops and livestock. Waste-water ponds, marshes, and irrigated fields associated with these agricultural activities provide abundant larval habitats for C. sonorensis midges, in addition to those sites that exist in the natural environment. Within this region, C. sonorensis is an important vector of bluetongue (BTV) and related viruses that adversely affect the international trade and movement of livestock, the economics of livestock production, and animal welfare. To characterize the seasonal dynamics of immature and adult C. sonorensis populations, abundance was monitored intensively on two dairy farms in the Sacramento Valley from August 2012- to July 2013. Adults were sampled every two weeks for 52 weeks by trapping (CDC style traps without light and baited with dry-ice) along N-S and E-W transects on each farm. One farm had large operational waste-water lagoons, whereas the lagoon on the other farm was drained and remained dry during the study. Spring emergence and seasonal abundance of adult C. sonorensis on both farms coincided with rising vernal temperature. Paradoxically, the abundance of midges on the farm without a functioning waste-water lagoon was increased as compared to abundance on the farm with a waste-water lagoon system, indicating that this infrastructure may not serve as the sole, or even the primary larval habitat. Adult midges disappeared from both farms from late November until May; however, low numbers of parous female midges were detected in traps set during daylight in the inter-seasonal winter period. This latter finding is especially critical as it provides a potential mechanism for the "overwintering" of BTV in temperate regions such as northern CA. Precise documentation of temporal changes in the annual abundance and dispersal of Culicoides midges is essential for the creation of models to predict BTV infection of livestock and to develop sound abatement strategies

Benefits of Automated Crystallization Plate Tracking, Imaging, and Analysis

SummaryWe describe the design of a database and software for managing and organizing protein crystallization data. We also outline the considerations behind the design of a fast web interface linking protein production data, crystallization images, and automated image analysis. The database and associated interfaces underpin the Oxford Protein Production Facility (OPPF) crystallization laboratory, collecting, in a routine and automatic manner, up to 100,000 images per day. Over 17 million separate images are currently held in this database. We discuss the substantial scientific benefits automated tracking, imaging, and analysis of crystallizations offers to the structural biologist: analysis of the time course of the trial and easy analysis of trials with related crystallization conditions. Features of this system address requirements common to many crystallographic laboratories that are currently setting up (semi-)automated crystallization imaging systems

Adaptive edge-cloud environments for Rural AI

Cloud computing provides on-demand access to computational resources while outsourcing infrastructure and service maintenance. Edge computing could extend cloud computing capability to areas with limited computing resources, such as rural areas, by utilizing low-cost hardware, such as singleboard computers. Cloud data centre hosted machine learning algorithms may violate user privacy and data confidentiality requirements. Federated learning (FL) trains models without sending data to a central server and ensures data privacy. Using FL, multiple actors can collaborate on a single machine learning model without sharing data. However, rural network outages can happen at any time, and the quality of a wireless network varies depending on location, which can affect the performance of the Federated Learning application. Therefore there is a need to have a platform that maintains service quality independent of infrastructure status. We propose a self-adaptive system for rural FL, which employs the Greedy Nominator Heuristic (GNH) based optimisation to orchestrate application workflows across multiple resources that make up a rural computing environment. GNH provides distributed optimization for workflow placement. GNH utilises resource status to reduce failure risks and costs while still completing tasks on time. Our approach is validated using a simulated rural environment – composed of multiple decentralized controllers sharing the same infrastructure and running a shared FL application. Results show that GNH outperforms three algorithms for deployment of FL tasks: random plac

Rural AI: Serverless-powered federated learning for remote applications

With increasing connectivity to support digital services in urban areas, there is a realization that demand for offering similar capability in rural communities is still limited. To unlock the potential of Artificial Intelligence (AI) within rural economies, we propose Rural AI—the mobilization of serverless computing to enable AI in austere environments. Inspired by problems observed in New Zealand, we analyze major challenges in agrarian communities and define their requirements. We demonstrate a proof-of-concept Rural AI system for cross-field pasture weed detection that illustrates the capabilities serverless computing offers to traditional federated learning

The combination of abundance and infection rates of Culicoides sonorensis estimates risk of subsequent bluetongue virus infection of sentinel cattle on California dairy farms

Bluetongue (BT) is an important viral disease of ruminants that is transmitted by hematophagous Culicoides midges. We examined the seasonal patterns of abundance and infection of Culicoides sonorensis at four dairy farms in the northern Central Valley of California to develop estimates of risk for bluetongue virus (BTV) transmission to cattle at each farm. These four farms were selected because of their similar meteorological conditions but varying levels of vector abundance and BTV infection of cattle. C. sonorensis midges were collected weekly at each farm during the seasonal transmission period, using three different trapping methods: traps baited with either carbon dioxide (CO2) alone or traps with CO2 and UV light, and by direct aspiration of midges from sentinel cattle. Analysis of BTV-infected midges using group and serotype-specific quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR) assays confirmed that BTV serotypes 10, 11, 13 and 17 are all present in the region, but that midge infection rates and the number of BTV serotypes circulating differed markedly among the individual farms. Furthermore, more serotypes of BTV were present in midges than in sentinel cattle at individual farms where BTV circulated, and the virus was detected at each farm in midges prior to detection in cattle. BTV infection rates were remarkably lower among female C. sonorensis midges collected by CO2 traps with UV light than among midges collected by either animal-baited aspirations or in CO2 traps without light. A subsample of female midges examined from each collection method showed no overall differences in the proportion of female midges that had previously fed on a host. Findings from this study confirm the importance of using sensitive surveillance methods for both midge collection and virus detection in epidemiological studies of BTV infection, which is especially critical if the data are to be used for development of mathematical models to predict the occurrence of BTV infection of livestock.The Center for Food Animal Health at the University of California-Davis, the U.S. Department of Agriculture and the Bernice Barbour Foundation.http://www.elsevier.com/locate/vetpa