Public library consumer health information pilot project: results of a National Library of Medicine evaluation

In October 1998, the National Library of Medicine (NLM) launched a pilot project to learn about the role of public libraries in providing health information to the public and to generate information that would assist NLM and the National Network of Libraries of Medicine (NN/LM) in learning how best to work with public libraries in the future. Three regional medical libraries (RMLs), eight resource libraries, and forty-one public libraries or library systems from nine states and the District of Columbia were selected for participation. The pilot project included an evaluation component that was carried out in parallel with project implementation. The evaluation ran through September 1999. The results of the evaluation indicated that participating public librarians were enthusiastic about the training and information materials provided as part of the project and that many public libraries used the materials and conducted their own outreach to local communities and groups. Most libraries applied the modest funds to purchase additional Internet-accessible computers and/or upgrade their health-reference materials. However, few of the participating public libraries had health information centers (although health information was perceived as a top-ten or top-five topic of interest to patrons). Also, the project generated only minimal usage of NLM's consumer health database, known as MEDLINEplus, from the premises of the monitored libraries (patron usage from home or office locations was not tracked). The evaluation results suggested a balanced follow-up by NLM and the NN/LM, with a few carefully selected national activities, complemented by a package of targeted activities that, as of January 2000, are being planned, developed, or implemented. The results also highlighted the importance of building an evaluation component into projects like this one from the outset, to assure that objectives were met and that evaluative information was available on a timely basis, as was the case here.

The evolution of rural outreach from Package Library to Grateful Med: introduction to the symposium

Outreach is now a prevailing activity in health sciences libraries. As an introduction to a series of papers on current library outreach to rural communities, this paper traces the evolution of such activities by proponents in health sciences libraries from 1924 to 1992. Definitions of rural and outreach are followed by a consideration of the expanding audience groups. The evolution in approaches covers the package library and enhancements in extension service, library development, circuit librarianship, and self-service arrangements made possible by such programs as the Georgia Interactive Network (GaIN) and Grateful Med.

AHEC library services: from circuit rider to virtual librarian

The North Carolina Area Health Education Centers Library and Information Services (NC AHEC LIS) Network provides library outreach services to rural health care providers in all nine AHEC regions of North Carolina. Over the last twenty-five years, the AHEC and university-based librarians have collaborated to create a model program for support of community-based clinical education and information access for rural health care providers. Through several collaborative projects, they have supported Internet access for rural health clinics. The NC AHEC Digital Library—under development by NC AHEC, University of North Carolina at Chapel Hill, Duke University, East Carolina University, and Wake Forest University—will further extend access to electronic biomedical information and resources to health professionals in a statewide digital library.

Library outreach: addressing Utah's “Digital Divide”

A “Digital Divide” in information and technological literacy exists in Utah between small hospitals and clinics in rural areas and the larger health care institutions in the major urban area of the state. The goals of the outreach program of the Spencer S. Eccles Health Sciences Library at the University of Utah address solutions to this disparity in partnership with the National Network of Libraries of Medicine—Midcontinental Region, the Utah Department of Health, and the Utah Area Health Education Centers. In a circuit-rider approach, an outreach librarian offers classes and demonstrations throughout the state that teach information-access skills to health professionals. Provision of traditional library services to unaffiliated health professionals is integrated into the library's daily workload as a component of the outreach program. The paper describes the history, methodology, administration, funding, impact, and results of the program.

Breaking down complex saproxylic communities: understanding sub-networks structure and implications to network robustness

Saproxylic insect communities inhabiting tree hollow microhabitats correspond with large food webs which simultaneously are constituted by multiple types of plant-animal and animal-animal interactions, according to the use of trophic resources (wood- and insect-dependent sub-networks), or to trophic habits or interaction types (xylophagous, saprophagous, xylomycetophagous, predators and commensals). We quantitatively assessed which properties of specialised networks were present in a complex networks involving different interacting types such as saproxylic community, and how they can be organised in trophic food webs. The architecture, interacting patterns and food web composition were evaluated along sub-networks, analysing their implications to network robustness from random and directed extinction simulations. A structure of large and cohesive modules with weakly connected nodes was observed throughout saproxylic sub-networks, composing the main food webs constituting this community. Insect-dependent sub-networks were more modular than wood-dependent sub-networks. Wood-dependent sub-networks presented higher species degree, connectance, links, linkage density, interaction strength, and were less specialised and more aggregated than insect-dependent sub-networks. These attributes defined high network robustness in wood-dependent sub-networks. Finally, our results emphasise the relevance of modularity, differences among interacting types and interrelations among them in modelling the structure of saproxylic communities and in determining their stability.

THE DESIGN OF A POWER SYSTEM FOR A WIRELESS SENSOR NETWORK FOR LONG-TERM OPERATION

Wireless sensor networks (WSNs) have shown wide applicability to many fields including monitoring of environmental, civil, and industrial settings. WSNs however are resource constrained by many competing factors that span their hardware, software, and networking. One of the central resource constrains is the charge consumption of WSN nodes. With finite energy supplies, low charge consumption is needed to ensure long lifetimes and success of WSNs. This thesis details the design of a power system to support long-term operation of WSNs. The power system’s development occurs in parallel with a custom WSN from the Queen’s MEMS Lab (QML-WSN), with the goal of supporting a 1+ year lifetime without sacrificing functionality. The final power system design utilizes a TPS62740 DC-DC converter with AA alkaline batteries to efficiently supply the nodes while providing battery monitoring functionality and an expansion slot for future development. Testing tools for measuring current draw and charge consumption were created along with analysis and processing software. Through their use charge consumption of the power system was drastically lowered and issues in QML-WSN were identified and resolved including the proper shutdown of accelerometers, and incorrect microcontroller unit (MCU) power pin connection. Controlled current profiling revealed unexpected behaviour of nodes and detailed current-voltage relationships. These relationships were utilized with a lifetime projection model to estimate a lifetime between 521-551 days, depending on the mode of operation. The power system and QML-WSN were tested over a long term trial lasting 272+ days in an industrial testbed to monitor an air compressor pump. Environmental factors were found to influence the behaviour of nodes leading to increased charge consumption, while a node in an office setting was still operating at the conclusion of the trail. This agrees with the lifetime projection and gives a strong indication that a 1+ year lifetime is achievable. Additionally, a light-weight charge consumption model was developed which allows charge consumption information of nodes in a distributed WSN to be monitored. This model was tested in a laboratory setting demonstrating +95% accuracy for high packet reception rate WSNs across varying data rates, battery supply capacities, and runtimes up to full battery depletion.

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

Use of a probabilistic neural network to reduce costs of selecting construction rock

Rocks used as construction aggregate in temperate climates deteriorate to differing degrees because of repeated freezing and thawing. The magnitude of the deterioration depends on the rock's properties. Aggregate, including crushed carbonate rock, is required to have minimum geotechnical qualities before it can be used in asphalt and concrete. In order to reduce chances of premature and expensive repairs, extensive freeze-thaw tests are conducted on potential construction rocks. These tests typically involve 300 freeze-thaw cycles and can take four to five months to complete. Less time consuming tests that (1) predict durability as well as the extended freeze-thaw test or that (2) reduce the number of rocks subject to the extended test, could save considerable amounts of money. Here we use a probabilistic neural network to try and predict durability as determined by the freeze-thaw test using four rock properties measured on 843 limestone samples from the Kansas Department of Transportation. Modified freeze-thaw tests and less time consuming specific gravity (dry), specific gravity (saturated), and modified absorption tests were conducted on each sample. Durability factors of 95 or more as determined from the extensive freeze-thaw tests are viewed as acceptable—rocks with values below 95 are rejected. If only the modified freeze-thaw test is used to predict which rocks are acceptable, about 45% are misclassified. When 421 randomly selected samples and all four standardized and scaled variables were used to train aprobabilistic neural network, the rate of misclassification of 422 independent validation samples dropped to 28%. The network was trained so that each class (group) and each variable had its own coefficient (sigma). In an attempt to reduce errors further, an additional class was added to the training data to predict durability values greater than 84 and less than 98, resulting in only 11% of the samples misclassified. About 43% of the test data was classed by the neural net into the middle group—these rocks should be subject to full freeze-thaw tests. Thus, use of the probabilistic neural network would meanthat the extended test would only need be applied to 43% of the samples, and 11% of the rocks classed as acceptable would fail early.

Bistability and switching in the lysis/lysogeny genetic regulatory network of bacteriophage lambda

Bistability and switching are two important aspects of the genetic regulatory network of phage. Positive and negative feedbacks are key regulatory mechanisms in this network. By the introduction of threshold values, the developmental pathway of A phage is divided into different stages. If the protein level reaches a threshold value, positive or negative feedback will be effective and regulate the process of development. Using this regulatory mechanism, we present a quantitative model to realize bistability and switching of phage based on experimental data. This model gives descriptions of decisive mechanisms for different pathways in induction. A stochastic model is also introduced for describing statistical properties of switching in induction. A stochastic degradation rate is used to represent intrinsic noise in induction for switching the system from the lysogenic pathway to the lysis pathway. The approach in this paper represents an attempt to describe the regulatory mechanism in genetic regulatory network under the influence of intrinsic noise in the framework of continuous models. (C) 2003 Elsevier Ltd. All rights reserved.

Rheological Properties of Organoclay Suspensions in Epoxy Network Precursors

This paper deals with the evolution of the state of dispersion of organically modified montmorillonites in epoxy or amine precursors. The epoxy prepolymer is a diglycidyl ether of bisphenol A (DGEBA) and the curing agent is an aliphatic diamine with a polyoxypropylene backbone (Jeffamine D2000). The clay dispersion is evaluated at the platelet scale (nanoscopic scale) from X-ray spectrometry [wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS)] and at the aggregates scale (microscopic scale) from rheological analysis. The organoclays used form gels in the monomers above the percolation threshold if no shear is applied and present a mechanical gel/sol transition when shear stress increases. Gel strength and viscosity at high shear rates are linked to the nanometric state of dispersion and reveal the existence of two different organizations depending on organoclay/monomer interactions: (i) When the clay shows good interactions with the monomer, a significant swelling of the clay galleries by the monomer is obtained. These swollen particles lead to formation of weak gels which after shearing give high relative viscosity fluids. (ii) When the clay develops poor interactions with the monomer, the clay tends to reduce its exchange surface with the monomer and leads to a strongly connected gel. Shear breaks down this physical network leading to a very low relative viscosity fluid composed of nonswollen particles keeping a high aspect ratio. (C) 2003 Elsevier B.V All rights reserved.

Vitamin D supplementation during the first year of life and risk of schizophrenia: a Finnish birth cohort study

Objective: Based on clues from epidemiology and animal experiments, low vitamin D during early life has been proposed as a risk factor for schizophrenia. The aim of this study was to explore the association between the use of vitamin D supplements during the first year of life and risk of developing schizophrenia. Method: Subjects were drawn from the Northern Finland 1966 Birth Cohort (n = 9 114). During the first year of life, data were collected about the frequency and dose of vitamin D supplementation. Our primary outcome measures were schizophrenia, psychotic disorders other than schizophrenia, and nonpsychotic disorders as diagnosed by age 31 years. Males and females were examined separately. Results: In males, the use of either irregular or regular vitamin D supplements was associated with a reduced risk of schizophrenia (Risk ratio (RR) = 0.08, 95% CI 0.01-0.95; RR = 0.12, 95% CI 0.02-0.90, respectively) compared with no supplementation. In males, the use of at least 2000 IU of vitamin D was associated with a reduced risk of schizophrenia (RR = 0.23, 95% CI 0.06-0.95) compared to those on lower doses. There were no significant associations between either the frequency or dose of vitamin D supplements and (a) schizophrenia in females, nor with (b) nonpsychotic disorder or psychotic disorders other than schizophrenia in either males or females. Conclusion: Vitamin D supplementation during the first year of life is associated with a reduced risk of schizophrenia in males. Preventing hypovitaminosis D during early life may reduce the incidence of schizophrenia. (C) 2003 Elsevier B.V. All rights reserved.