Weighted Networks: Applications from Power grid construction to crowd control

Since their discovery in the 1950\u27s by Erdos and Renyi, network theory (the study of objects and their associations) has blossomed into a full-fledged branch of mathematics. Due to the network\u27s flexibility, diverse scientific problems can be reformulated as networks and studied using a common set of tools. I define a network G = (V,E) composed of two parts: (i) the set of objects V, called nodes, and (ii) set of relationships (associations) E, called links, that connect objects in V. We can extend the classic network of nodes and links by describing the intensity of these associations with weights. More formally, weighted networks augment the classic network with a function f(e) from links to the real line, uncovering powerful ways to model real-world applications. This thesis studies new ways to construct robust micro powergrids, mine people\u27s perceptions of causality on a social network, and proposes a new way to analyze crowdsourcing all in the context of the weighted network model. The current state of Earth\u27s ecosystem and intensifying climate calls on scientists to find new ways to harvest clean affordable energy. A microgrid, or neighborhood-scale powergrid built using renewable energy sources attached to personal homes, suggest one way to ameliorate this energy crisis. We can study the stability (robustness) of such a small-scale system with weighted networks. A novel use of weighted networks and percolation theory guides the safe and efficient construction of power lines (links, E) connecting a small set of houses (nodes, V) to one another and weights each power line by the distance between houses. This new look at the robustness of microgrid structures calls into question the efficacy of the traditional utility. The next study uses the twitter social network to compare and contrast causal language from everyday conversation. Collecting a set of 1 million tweets, we find a set of words (unigrams), parts of speech, named entities, and sentiment signal the use of informal causal language. Breaking a problem difficult for a computer to solve into many parts and distributing these tasks to a group of humans to solve is called Crowdsourcing. My final project asks volunteers to \u27reply\u27 to questions asked of them and \u27supply\u27 novel questions for others to answer. I model this \u27reply and supply\u27 framework as a dynamic weighted network, proposing new theories about this network\u27s behavior and how to steer it toward worthy goals. This thesis demonstrates novel uses of, enhances the current scientific literature on, and presents novel methodology for, weighted networks

Robustness of spatial micronetworks

Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure

The Therapeutic Engagement Questionnaire (TEQ): a service user-focused mental health nursing outcome metric

Therapeutic engagement (TE) has been described as the crux of mental health nursing but despite its perceived importance, to date, there is no measurement tool that captures it as a result,there is no way of determining the contribution of mental health nursing interaction to service user recovery, in mental health settings or the wider care quality agenda

The Therapeutic Engagement Questionnaire (TEQ): a service user-focused mental health nursing outcome metric

Background: Therapeutic engagement (TE) has been described as the crux of mental health nursing but despite its perceived importance, to date, there is no measurement tool that captures it. As a result, there is no way of determining the contribution of mental health nursing interaction to service user recovery, in acute inpatient mental health settings or the wider care quality agenda. / Methods: To develop and validate a TE measurement tool in partnership with Service Users (SUs) and Registered Mental Health Nurses (RMHNs). The TEQ was developed in 3 stages: 1) item generation (and pre-testing), 2) item reduction using Principal Component Analysis (PCA), and 3) validation across Mental Health Trusts in England. / Results: The final questionnaire has two versions, (SU and RMHN version), each scored within two contexts (1–1 SU-RMHN interactions and overall environment and atmosphere of the ward) and includes 20 items with two sub-scales (care interactions and care delivery). Psychometric evaluation of the TEQ shows high inter-scale correlations (0.66–0.95 SU; 0.57–0.90 RMHN), sound sub-scale internal consistency (> 0.95), concurrent validity (> 0.60) and adequate score variability for both versions of the TEQ. In summary, the TEQ behaves well as a measurement tool. / Conclusions: The TEQ can determine the collaborative and empathic nature of RMHN-SU interactions, capture if SUs are treated with dignity and respect and recognise that the principles of the recovery approach are being respected. The TEQ can also provide robust monitoring of nursing activity, offer opportunity for transparency of activity, feed into healthcare organizations’ key performance indicators and provide reassurance about the nature and quality of nurses’ work

Structural and functional characterisation of human RNA helicase DHX8 provides insights into the mechanism of RNA-stimulated ADP release.

DHX8 is a crucial DEAH-box RNA helicase involved in splicing and required for the release of mature mRNA from the spliceosome. Here, we report the biochemical characterisation of full-length human DHX8 and the catalytically active helicase core DHX8Δ547, alongside crystal structures of DHX8Δ547 bound to ADP and a structure of DHX8Δ547 bound to poly(A)6 single-strand RNA. Our results reveal that DHX8 has an in vitro binding preference for adenine-rich RNA and that RNA binding triggers the release of ADP through significant conformational flexibility in the conserved DEAH-, P-loop and hook-turn motifs. We demonstrate the importance of R620 and both the hook-turn and hook-loop regions for DHX8 helicase activity and propose that the hook-turn acts as a gatekeeper to regulate the directional movement of the 3' end of RNA through the RNA-binding channel. This study provides an in-depth understanding of the activity of DHX8 and contributes insights into the RNA-unwinding mechanisms of the DEAH-box helicase family