Anita K. Foster and Gene R. Springs
Academic libraries are struggling to support the growing demand for streaming video. The purpose of this paper is to detail the experience of running three long-term pilots with…
Abstract
Purpose
Academic libraries are struggling to support the growing demand for streaming video. The purpose of this paper is to detail the experience of running three long-term pilots with different streaming video platforms, including processes involved, lessons learned and next steps.
Design/methodology/approach
This paper uses a mixed methods approach, combining analysis of usage data with case study observations.
Findings
The length of the pilots allowed for deep understanding of the needs of this academic library’s community’s engagement with streaming video in the classroom, and confirmed anecdotal information that availability of multiple platforms supports diverse needs which led to continuing access to all platforms, operationalized to be managed within existing processes. Using usage data and feedback from a task force led to decisions to continue with all three platforms that were piloted.
Research limitations/implications
While this research describes the experience at one academic library, the information may be generalizable enough that other libraries may use it for their streaming video collection development decisions.
Originality/value
Long-term pilot studies for streaming video platforms can be challenging for many libraries to undertake. With a modest initial financial commitment, the library was able to explore how the community might use streaming video. Through analysis of usage data, the library was able to see when, where and what was being used and could make better informed decisions about where to concentrate future funds for streaming video support.
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Heritability studies attempt to estimate the contribution of genes (vs. environments) to variation in phenotypes (or outcomes of interest) in a given population at a given time…
Abstract
Purpose
Heritability studies attempt to estimate the contribution of genes (vs. environments) to variation in phenotypes (or outcomes of interest) in a given population at a given time. This chapter scrutinizes heritability studies of adverse health phenotypes, emphasizing flaws that have become more glaring in light of recent advances in the life sciences and manifest most visibly in epigenetics.
Methodology/approach
Drawing on a diverse body of research and critical scholarship, this chapter examines the veracity of methodological and conceptual assumptions of heritability studies.
Findings
The chapter argues that heritability studies are futile for two reasons: (1) heritability studies suffer from serious methodological flaws with the overall effect of making estimates inaccurate and likely biased toward inflated heritability, and, more importantly (2) the conceptual (biological) model on which heritability studies depend – that of identifiably separate effects of genes versus the environment on phenotype variance – is unsound. As discussed, contemporary bioscientific work indicates that genes and environments are enmeshed in a complex (bidirectional, interactional), dynamic relationship that defies any attempt to demarcate separate contributions to phenotype variance. Thus, heritability studies attempt the biologically impossible. The emerging research on the importance of microbiota is also discussed, including how the commensal relationship between microbial and human cells further stymies heritability studies.
Originality/value
Understandably, few sociologists have the time or interest to be informed about the methodological and theoretical underpinnings of heritability studies or to keep pace with the incredible advances in genetics and epigenetics over the last several years. The present chapter aims to provide interested scholars with information about heritability and heritability estimates of adverse health outcomes in light of recent advances in the biosciences.
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Damian Tago, Henrik Andersson and Nicolas Treich
This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.
Abstract
Purpose
This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.
Design/methodology/approach
This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.
Findings
This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.
Originality/value
This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.
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J. Anke M. van Eekelen, Justine A. Ellis, Craig E. Pennell, Richard Saffery, Eugen Mattes, Jeff Craig and Craig A. Olsson
Genetic risk for depressive disorders is poorly understood despite consistent suggestions of a high heritable component. Most genetic studies have focused on risk associated with…
Abstract
Genetic risk for depressive disorders is poorly understood despite consistent suggestions of a high heritable component. Most genetic studies have focused on risk associated with single variants, a strategy which has so far only yielded small (often non-replicable) risks for depressive disorders. In this paper we argue that more substantial risks are likely to emerge from genetic variants acting in synergy within and across larger neurobiological systems (polygenic risk factors). We show how knowledge of major integrated neurobiological systems provides a robust basis for defining and testing theoretically defensible polygenic risk factors. We do this by describing the architecture of the overall stress response. Maladaptation via impaired stress responsiveness is central to the aetiology of depression and anxiety and provides a framework for a systems biology approach to candidate gene selection. We propose principles for identifying genes and gene networks within the neurosystems involved in the stress response and for defining polygenic risk factors based on the neurobiology of stress-related behaviour. We conclude that knowledge of the neurobiology of the stress response system is likely to play a central role in future efforts to improve genetic prediction of depression and related disorders.
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In the spring of 1982, I published an article in Reference Services Review on marketing libraries and information services. The article covered available literature on that topic…
Abstract
In the spring of 1982, I published an article in Reference Services Review on marketing libraries and information services. The article covered available literature on that topic from 1970 through part of 1981, the time period immediately following Kotler and Levy's significant and frequently cited article in the January 1969 issue of the Journal of Marketing, which was first to suggest the idea of marketing nonprofit organizations. The article published here is intended to update the earlier work in RSR and will cover the literature of marketing public, academic, special, and school libraries from 1982 to the present.
This paper presents a VHDL‐AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains…
Abstract
Purpose
This paper presents a VHDL‐AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance.
Design/methodology/approach
The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL‐AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench.
Findings
Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular‐shape, triangular or trapezoidal membership functions.
Research limitations
The test of the FLC has only been done in the simulation stage, no physical prototype has been made.
Originality/value
This paper proposes a novel way of improving the FLC's performance and a new application area for VHDL‐AMS.
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– This paper aims to discuss the role of goal diversity for resource development organized in an inter-organizational project.
Abstract
Purpose
This paper aims to discuss the role of goal diversity for resource development organized in an inter-organizational project.
Design/Methodology/Approach
The paper builds on a case study of an inter-organizational research project in the field of plant biotechnology in Sweden. The project had four members with differing goals: two research departments, one firm and one co-operative.
Findings
This particular project shows a diversity of goals and seeks to explain how actors with very different goals and resources involve in inter-organizational collaboration. The case illustrates how the goals are nested in different ways and how the goals are and become related with the resources developed during the project. The explanation found is that the involved actors manage to match their goals and resources.
Research limitations/implications
The paper identifies goal-and-resource-matching processes as an explanation behind resource development in collaboration between actors with diverse goals.
Practical implications
Designing projects with actors who have diverse sets of resources have enormous potential, but such projects need to ensure that the goals are resources become matched, processes which can emerge during the course of the project.
Originality/value
Few studies have focused on the interplay between diverse goals and resources in inter-organizational projects.
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Nageswara Rao Eluri, Gangadhara Rao Kancharla, Suresh Dara and Venkatesulu Dondeti
Gene selection is considered as the fundamental process in the bioinformatics field. The existing methodologies pertain to cancer classification are mostly clinical basis, and its…
Abstract
Purpose
Gene selection is considered as the fundamental process in the bioinformatics field. The existing methodologies pertain to cancer classification are mostly clinical basis, and its diagnosis capability is limited. Nowadays, the significant problems of cancer diagnosis are solved by the utilization of gene expression data. The researchers have been introducing many possibilities to diagnose cancer appropriately and effectively. This paper aims to develop the cancer data classification using gene expression data.
Design/methodology/approach
The proposed classification model involves three main phases: “(1) Feature extraction, (2) Optimal Feature Selection and (3) Classification”. Initially, five benchmark gene expression datasets are collected. From the collected gene expression data, the feature extraction is performed. To diminish the length of the feature vectors, optimal feature selection is performed, for which a new meta-heuristic algorithm termed as quantum-inspired immune clone optimization algorithm (QICO) is used. Once the relevant features are selected, the classification is performed by a deep learning model called recurrent neural network (RNN). Finally, the experimental analysis reveals that the proposed QICO-based feature selection model outperforms the other heuristic-based feature selection and optimized RNN outperforms the other machine learning methods.
Findings
The proposed QICO-RNN is acquiring the best outcomes at any learning percentage. On considering the learning percentage 85, the accuracy of the proposed QICO-RNN was 3.2% excellent than RNN, 4.3% excellent than RF, 3.8% excellent than NB and 2.1% excellent than KNN for Dataset 1. For Dataset 2, at learning percentage 35, the accuracy of the proposed QICO-RNN was 13.3% exclusive than RNN, 8.9% exclusive than RF and 14.8% exclusive than NB and KNN. Hence, the developed QICO algorithm is performing well in classifying the cancer data using gene expression data accurately.
Originality/value
This paper introduces a new optimal feature selection model using QICO and QICO-based RNN for effective classification of cancer data using gene expression data. This is the first work that utilizes an optimal feature selection model using QICO and QICO-RNN for effective classification of cancer data using gene expression data.
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Niloufar Azhdari, Seyed Shaker Hashemi, Saber Ezzi, Kabir Sadeghi and Abdoreza Fazeli
Ongoing research indicates that structures with infill panels manifest distinct seismic responses, necessitating further investigation. This study aims to introduce a novel…
Abstract
Purpose
Ongoing research indicates that structures with infill panels manifest distinct seismic responses, necessitating further investigation. This study aims to introduce a novel methodology for determining the response modification factor (RMF) of reinforced concrete (RC) moment-resisting frames and investigate the impact of infill sandwich panels on these structures.
Design/methodology/approach
Using SAP2000 software, 84 RC frames were meticulously designed and analyzed, followed by the development of a predictive model using genetic programming and GeneXpro Tools software to calculate the RMF values. The results underscore the efficacy of gene expression programming (GEP) in determining the RMF of RC moment-resisting frames.
Findings
The study’s results reveal that the variations in the yield stress of longitudinal reinforcements within the range of 340 to 400 MPa and changes in the design base acceleration have a minimal impact on the RMF value. For RC moment-resisting frames with infill sandwich panels, the RMF value decreases as the span length to storey height ratio (L/H) increases, while it increases with a higher number of storeys. Conversely, for RC frames without infill sandwich panels, the RMF decreases with an increase in the number of storeys. However, no consistent pattern emerges for the RMF with changes in the L/H ratio, highlighting the nonuniform effect of altering this ratio on RMF.
Originality/value
The proposed formula in this study is very effective in predicting the RMF and can assist engineers in the seismic design of RC structures.