SELENOPROTEIN O is a chloroplast protein involved in ROS scavenging and its absence increases dehydration tolerance in Arabidopsis thaliana

The evolutionary conserved family of Selenoproteins performs redox-regulatory functions in bacteria, archaea and eukaryotes. Among them, members of the SELENOPROTEIN O (SELO) subfamily are located in mammalian and yeast mitochondria, but their functions are thus far enigmatic. Screening of T-DNA knockout mutants for resistance to the proline analogue thioproline (T4C), identified mutant alleles of the plant SELO homologue in Arabidopsis thaliana. Absence of SELO resulted in a stress-induced transcriptional activation instead of silencing of mitochondrial proline dehydrogenase, and also high elevation of Delta(1)-pyrroline-5-carboxylate dehydrogenase involved in degradation of proline, thereby alleviating T4C inhibition and lessening drought-induced proline accumulation. Unlike its animal homologues, SELO was localized to chloroplasts of plants ectopically expressing SELO-GFP. The protein was co-fractionated with thylakoid membrane complexes, and co-immunoprecipitated with FNR, PGRL1 and STN7, all involved in regulating PSI and downstream electron flow. The selo mutants displayed extended survival under dehydration, accompanied by longer photosynthetic activity, compared with wild-type plants. Enhanced expression of genes encoding ROS scavenging enzymes in the unstressed selo mutant correlated with higher oxidant scavenging capacity and reduced methyl viologen damage. The study elucidates SELO as a PSI-related component involved in regulating ROS levels and stress responses

Using Rheo-Small-Angle Neutron Scattering to Understand How Functionalised Dipeptides Form Gels

We explore the use of rheo-small-angle neutron scattering as a method to collect structural information from neutron scattering simultaneously with rheology to understand how low-molecular-weight hydrogels form and behave under shear. We examine three different gelling hydrogel systems to assess what structures are formed and how these influence the rheology. Furthermore, we probe what is happening to the network during syneresis and why the gels do not recover after an applied strain. All this information is vital when considering gels for applications such as 3D-printing and injection

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

Towards actionable knowledge: A systematic analysis of mobile patient portal use

As the aging population grows, chronic illness increases, and our healthcare costs sharply increase, patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. A patient’s engagement in their healthcare contributes to improving health outcomes, and information technologies can support health engagement. In this chapter, we extend the existing literature by discovering design gaps for patient portals from a systematic analysis of negative users’ feedback from the actual use of patient portals. Specifically, we adopt a topic modeling approach, latent Dirichlet allocation (LDA) algorithm, to discover design gaps from online low rating user reviews of a common mobile patient portal, EPIC’s mychart. To validate the extracted gaps, we compared the results of LDA analysis with that of human analysis. Overall, the results revealed opportunities to improve collaboration and to enhance the design of portals intended for patient-centered care. Incorporating these changes may enable the technologies to have stronger position to influence health improvement and wellness

On opportunistic software reuse

The availability of open source assets for almost all imaginable domains has led the software industry toopportunistic design-an approach in which people develop new software systems in an ad hoc fashion by reusing and combining components that were not designed to be used together. In this paper we investigate this emerging approach. We demonstrate the approach with an industrial example in whichNode.jsmodules and various subsystems are used in an opportunistic way. Furthermore, to study opportunistic reuse as a phenomenon, we present the results of three contextual interviews and a survey with reuse practitioners to understand to what extent opportunistic reuse offers improvements over traditional systematic reuse approaches.Peer reviewe

Overcoming network overload and redundancy in inter-organizational networks:the roles of potential and latent ties

This paper builds on Granovetter's distinction between strong and weak ties [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol. 78(6) 1360–1380] in order to respond to recent calls for a more dynamic and processual understanding of networks. The concepts of potential and latent tie are deductively identified, and their implications for understanding how and why networks emerge, evolve, and change are explored. A longitudinal empirical study conducted with companies operating in the European motorsport industry reveals that firms take strategic actions to search for potential ties and reactivate latent ties in order to solve problems of network redundancy and overload. Examples are given, and their characteristics are examined to provide theoretical elaboration of the relationship between the types of tie and network evolution. These conceptual and empirical insights move understanding of the managerial challenge of building effective networks beyond static structural contingency models of optimal network forms to highlight the processes and capabilities of dynamic relationship building and network development. In so doing, this paper highlights the interrelationship between search and redundancy and the scope for strategic action alongside path dependence and structural influences on network processes

Scenario-Based Design Theorizing:The Case of a Digital Idea Screening Cockpit

As ever more companies encourage employees to innovate, a surplus of ideas has become reality in many organizations – often exceeding the available resources to execute them. Building on insights from a literature review and a 3-year collaboration with a banking software provider, the paper suggests a Digital Idea Screening Cockpit (DISC) to address this challenge. Following a design science research approach, it suggests a prescriptive design theory that provides practitioner-oriented guidance for implementing a DISC. The study shows that, in order to facilitate the assessment, selection, and tracking of ideas for different stakeholders, such a system needs to play a dual role: It needs to structure decision criteria and at the same be flexible to allow for creative expression. Moreover, the paper makes a case for scenario-based design theorizing by developing design knowledge via scenarios

An exploration of the determinants for decision to migrate existing resources to cloud computing using an integrated TOE-DOI model

Migrating existing resources to cloud computing is a strategic organisational decision that can be difficult. It requires the consideration and evaluation of a wide range of technical and organisational aspects. Although a significant amount of attention has been paid by many industrialists and academics to aid migration decisions, the procedure remains difficult. This is mainly due to underestimation of the range of factors and characteristics affecting the decision for cloud migration. Further research is needed to investigate the level of effect these factors have on migration decisions and the overall complexity. This paper aims to explore the level of complexity of the decision to migrate the cloud. A research model based on the diffusion of innovation (DOI) theory and the technology-organization-environment (TOE) framework was developed. The model was tested using exploratory and confirmatory factor analysis. The quantitative analysis shows the level of impact of the identified variables on the decision to migrate. Seven determinants that contribute to the complexity of the decisions are identified. They need to be taken into account to ensure successful migration. This result has expanded the collective knowledge about the complexity of the issues that have to be considered when making decisions to migrate to the cloud. It contributes to the literature that addresses the complex and multidimensional nature of migrating to the cloud