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At least 631 records · Page 35

Evaluation of a scientific data search infrastructure

The ability to search over large scientific datasets has become crucial to next-generation scientific discoveries as data generated from scientific facilities grow dramatically. In previous work, we developed and deployed ScienceSearch, a search infrastructure for scientific data which uses machine learning to automate metadata creation. Our current deployment is deployed atop a container based platform at a HPC center. In this article, we present an evaluation and discuss our experiences with the ScienceSearch infrastructure. Specifically, we present a performance evaluation of ScienceSearch's infrastructure focusing on scalability trends. The obtained results show that ScienceSearch is able to serve up to 130 queries/min with latency under 3 s. We discuss our infrastructure setup and evaluation results to provide our experiences and a perspective on opportunities and challenges of our search infrastructure.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Organizational System Resilience to Disinformation: A Viable Systems Model Exploration

This paper explores the utility of organizational system modeling frameworks to provide valuable insight into information flows within organizations and subsequently the opportunities for increasing resilience against disinformation campaigns targeting the system's ability to utilize information within its decision making. Disinformation is a growing challenge for many organizations and in recent years has created delay in decision making. Here the paper has utilized the viable systems model (VSM) to characterize organizational systems and used this approach to outline potential subsystem requirements to promote resilience of the system. The results of this paper can support the development of simulations and models considering the human elements within the system as well as support the development of quantitative measures of resilience.

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Multiple Pathways of Influence for Tightly and Loosely Structured Organizations: Implications for Systems Resilience

Organizations play a key role in supporting various societal functions, ranging from environmental governance to the manufacturing of goods. Here, the behaviors of organization are impacted by various influences, including information, technology, authority, economic leverage, historical experiences, and external factors, such as regulations. This paper introduces a generalized framework, focused on the relative structure of an organization (tight vs. loose), that can be used to understand how different influence pathways can impact decision-making within differently structured organizations. This generalized framework is then translated into a modeling and simulation platform to support and assess implications of these structural differences in resilience to disinformation (measured by organizational behaviors of timeliness and inclusion of quality information) using a systems dynamics approach Preliminary results indicate that a tightly structured organization may be less timely at processing information but could be more resilient against using poor quality information in organizational decisions compared to a loosely structured organization. Ongoing work is underway to understand the robustness of these findings and to validate current model design activities with empirical insights.

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Factors influencing radiation therapy student clinical placement satisfaction

Introduction: Radiation therapy students at Queensland University of Technology (QUT) attend clinical placements at five different clinical departments with varying resources and support strategies. This study aimed to determine the relative availability and perceived importance of different factors affecting student support while on clinical placement. The purpose of the research was to inform development of future support mechanisms to enhance radiation therapy students’ experience on clinical placement. Methods: This study used anonymous Likert-style surveys to gather data from years 1 and 2 radiation therapy students from QUT and clinical educators from Queensland relating to availability and importance of support mechanisms during clinical placements in a semester. Results: The study findings demonstrated student satisfaction with clinical support and suggested that level of support on placement influenced student employment choices. Staff support was perceived as more important than physical resources; particularly access to a named mentor, a clinical educator and weekly formative feedback. Both students and educators highlighted the impact of time pressures. Conclusions: The support offered to radiation therapy students by clinical staff is more highly valued than physical resources or models of placement support. Protected time and acknowledgement of the importance of clinical education roles are both invaluable. Joint investment in mentor support by both universities and clinical departments is crucial for facilitation of effective clinical learning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Mechanism of Lithium Ion Exchange Into Spinel Manganese Oxide

Lithium manganese oxide (LMO) is an effective absorbent for lithium recovery from brines, characterized by its high adsorption capacity, excellent regeneration performance, and selectivity. Here, this study investigates the mechanisms of material degradation during lithium loading and unloading in LMO, employing a combination of time‐resolved Raman spectroscopy, X‐ray diffraction, and X‐ray photoelectron spectroscopy. Key findings reveal that the A 1g vibrational mode wavenumber shifts from 635 cm −1 at the onset of lithium ion exchange to 656 cm −1 after 12 min, indicating local symmetry loss and manganese (Mn) loss during lithium intercalation. The proposed lithium exchange mechanism involves initial occupation of tetrahedral interstitial voids, followed by migration into interstitial sites between Mn octahedral sites. Computational modeling suggests that the loss of symmetry in MnO cubane‐like groups occurs as lithium migrates, significantly affecting the Raman spectra. Importantly, the study demonstrates that after 100 cycles of lithium/hydrogen loading, a 24% loss in Mn is observed, which correlates with decreased structural stability; however, the structural integrity of LMO is enhanced when subjected to multiple cycles without complete loading. Here, these insights contribute to the understanding of LMO's performance in lithium recovery applications and highlight potential strategies to optimize its use in future technologies.

15 GEOTHERMAL ENERGY↗

A successful start for mLife

mLife made its debut with the publication of the inaugurating issue on March 30, 2022. We are pleased to have published 42 high-quality articles, including reviews, research articles, and application notes, which cover microbial genetics, biochemistry and physiology, ecology and evolution, pathogenic and public health microbiology, and so forth. Nine of the articles concern technical innovations and applications in areas including genome editing, single-cell analysis, and database. To pay tribute to the great microbiologist Carl Woese on the 10th anniversary of his death, the Journal published a special section containing three thought-provoking articles in the last issue of the year. mLife and its collaborating publisher Wiley have made great efforts to increase the Journal's national and continental representation. As a result, the Journal received submissions from over 20 countries in five continents last year. The authors of the published articles are from China, United States, Great Britain, France, Canada, Ger many, Japan, Switzerland, and Austria.

59 BASIC BIOLOGICAL SCIENCES↗

Typical event horizons in AdS/CFT

We consider the construction of local bulk operators in a black hole background dual to a pure state in conformal field theory. The properties of these operators in a microcanonical ensemble are studied. It has been argued in the literature that typical states in such an ensemble contain firewalls, or otherwise singular horizons. Here, we argue this conclusion can be avoided with a proper definition of the interior operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Establishing a Platform for Interest and Education in Interventional Radiology Amongst Radiology Trainees

Purpose: Over recent times, procedural Radiologists have begun to establish themselves as the distinct subspecialty of Interventional Radiology (IR). The Interventional Radiology Society of Australasia (IRSA) was established in 1982 to share collaborative ideas, encourage research, and promote education. IRSA developed a weekend registrar workshop attended by Radiology Registrars from Australia and New Zealand. In the 2018 event, we surveyed the Registrars to identify their interest in IR training before and after the workshop. Materials and Methods: The event was held over a weekend and consisted of both lectures and hands-on workshops. A survey was handed to all 67 registrants of the workshop and there was a 55% response rate including 78% of females in attendance. Results: Before the workshop, trainees rated their interest in IR training at a mean of 3.7 out of 5. After the workshop, trainees rated their interest in IR training as an average of 4.4 out of 5 (p < 0.001). The difference in interest between males and females before the workshop (4.0 vs. 3.1) was significant (p = 0.003), however after the workshop (4.5 vs. 4.1) was not significant (p = 0.07). The change in interest from attending the workshop was significant between genders, p = 0.03 (male interest increased mean 0.5, female increased mean 1.0). Conclusion: We show that a program of lectures and workshops designed to generate interest in IR leads to a significant increase in training interest, particularly amongst females. Other subspecialty groups should consider this type of intervention and promote ongoing education and inspiration. Level of Evidence: Cross-sectional study, Level IV.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Topological Optimization with Big Steps

Using persistent homology to guide optimization has emerged as a novel application of topological data analysis. Existing methods treat persistence calculation as a black box and backpropagate gradients only onto the simplices involved in particular pairs. We show how the cycles and chains used in the persistence calculation can be used to prescribe gradients to larger subsets of the domain. In particular, we show that in a special case, which serves as a building block for general losses, the problem can be solved exactly in linear time. This relies on another contribution of this paper, which eliminates the need to examine a factorial number of permutations of simplices with the same value. Here, we present empirical experiments that show the practical benefits of our algorithm: the number of steps required for the optimization is reduced by an order of magnitude.

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Comparing published scientific journal articles to their pre-print versions

Academic publishers claim that they add value to scholarly communications by coordinating reviews and contributing and enhancing text during publication. These contributions come at a considerable cost: US academic libraries paid $1.7 billion for serial subscriptions in 2008 alone. Library budgets, in contrast, are flat and not able to keep pace with serial price inflation. Here, we have investigated the publishers’ value proposition by conducting a comparative study of pre-print papers from two distinct science, technology, and medicine corpora and their final published counterparts. This comparison had two working assumptions: (1) If the publishers’ argument is valid, the text of a pre-print paper should vary measurably from its corresponding final published version, and (2) by applying standard similarity measures, we should be able to detect and quantify such differences. Our analysis revealed that the text contents of the scientific papers generally changed very little from their pre-print to final published versions. These findings contribute empirical indicators to discussions of the added value of commercial publishers and therefore should influence libraries’ economic decisions regarding access to scholarly publications.

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Cutting planes for the multistage stochastic unit commitment problem

As renewable energy penetration rates continue to increase in power systems worldwide, new challenges arise for system operators in both regulated and deregulated electricity markets to solve the security-constrained coal-fired unit commitment problem with intermittent generation (due to renewables) and uncertain load, in order to ensure system reliability and maintain cost effectiveness. In this paper, we study a security-constrained coal-fired stochastic unit commitment model, which we use to enhance the reliability unit commitment process for day-ahead power system operations. In our approach, we first develop a deterministic equivalent formulation for the problem, which leads to a large-scale mixed-integer linear program. Then, we verify that the turn on/off inequalities provide a convex hull representation of the minimum-up/down time polytope under the stochastic setting. Next, we develop several families of strong valid inequalities mainly through lifting schemes. In particular, by exploring sequence independent lifting and subadditive approximation lifting properties for the lifting schemes, we obtain strong valid inequalities for the ramping and general load balance polytopes. Lastly, branch-and-cut algorithms are developed to employ these valid inequalities as cutting planes to solve the problem. Our computational results verify the effectiveness of the proposed approach.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The impact of socio-technical communication styles on the diversity and innovation potential of global science collaboratories

Emerging cyber-infrastructure tools are enabling scientists to transparently co-develop, share, and communicate about real-time diverse forms of knowledge artifacts. In these environments, communication preferences of scientists are posited as an important factor affecting innovation capacity and robustness of social and knowledge network structures. Scientific knowledge creation in such communities is called global participatory science (GPS). Recently, using agent-based modeling and collective action theory as a basis, a complex adaptive social communication network model (CollectiveInnoSim) is implemented. This work leverages CollectiveInnoSim implementing communication preferences of scientists. Social network metrics and knowledge production patterns are used as proxy metrics to infer innovation potential of emergent knowledge and collaboration networks. The objective is to present the underlying communication dynamics of GPS in a form of computational model and delineate the impacts of various communication preferences of scientists on innovation potential of the collaboration network. Ultimately, the insight gained can help policy-makers to design GPS environments and promote innovation.

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Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

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ColdRoute: effective routing of cold questions in stack exchange sites

Routing questions in Community Question Answer services such as Stack Exchange sites is a well-studied problem. Yet, cold-start—a phenomena observed when a new question is posted is not well addressed by existing approaches. Additionally, cold questions posted by new askers present significant challenges to state-of-the-art approaches. We propose ColdRoute to address these challenges. ColdRoute is able to handle the task of routing cold questions posted by new or existing askers to matching experts. Specifically, we use Factorization Machines on the one-hot encoding of critical features such as question tags and compare our approach to well-studied techniques such as CQARank and semantic matching (LDA, BoW, and Doc2Vec). Furthermore by using data from eight stack exchange sites, we are able to improve upon the routing metrics (Precision@1, Accuracy, MRR) over the state-of-the-art models such as semantic matching by 159.5, 31.84, and 40.36% for cold questions posted by existing askers, and 123.1, 27.03, and 34.81% for cold questions posted by new askers respectively.

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On the emerging potential of quantum annealing hardware for combinatorial optimization

Abstract Over the past decade, the usefulness of quantum annealing hardware for combinatorial optimization has been the subject of much debate. Thus far, experimental benchmarking studies have indicated that quantum annealing hardware does not provide an irrefutable performance gain over state-of-the-art optimization methods. However, as this hardware continues to evolve, each new iteration brings improved performance and warrants further benchmarking. To that end, this work conducts an optimization performance assessment of D-Wave Systems’ Advantage Performance Update computer, which can natively solve sparse unconstrained quadratic optimization problems with over 5,000 binary decision variables and 40,000 quadratic terms. We demonstrate that classes of contrived problems exist where this quantum annealer can provide run time benefits over a collection of established classical solution methods that represent the current state-of-the-art for benchmarking quantum annealing hardware. Although this work does not present strong evidence of an irrefutable performance benefit for this emerging optimization technology, it does exhibit encouraging progress, signaling the potential impacts on practical optimization tasks in the future.

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Relating Lexicographic Smoothness and Directed Subdifferentiability

Lexicographic derivatives developed by Nesterov and directed subdifferentials developed by Baier, Farkhi, and Roshchina are both essentially nonconvex generalized derivatives for nonsmooth nonconvex functions and satisfy strict calculus rules and mean-value theorems. This article aims to clarify the relationship between the two generalized derivatives. In particular, for scalar-valued functions that are locally Lipschitz continuous, lexicographic smoothness and directed subdifferentiability are shown to be equivalent, along with the necessary optimality conditions corresponding to each. For such functions, the visualization of the directed subdifferential-the Rubinov subdifferential-is shown to include the lexicographic subdifferential, and is also shown to be included in its closed convex hull. As a result, various implications of these results are discussed.

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Challenges and Advances in Information Extraction from Scientific Literature: a Review

Scientific articles have long been the primary means of disseminating scientific discoveries. Over the centuries, valuable data and potentially groundbreaking insights have been collected and buried deep in the mountain of publications. In materials engineering, such data are spread across technical handbooks specification sheets, journal articles, and laboratory notebooks in myriad formats. Extracting information from papers on a large scale has been a tedious and time-consuming job to which few researchers have wanted to devote their limited time and effort, yet is an activity that is essential for modern data-driven design practices. However, in recent years, significant progress has been made by the computer science community on techniques for automated information extraction from free text. Yet, transformative application of these techniques to scientific literature remains elusive-due not to a lack of interest or effort but to technical and logistical challenges. Using the challenges in the materials science literature as a driving motivation, we review the gaps between state-of-the-art information extraction methods and the practical application of such methods to scientific texts, and offer a comprehensive overview of work that can be undertaken to close these gaps.

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Storages Are Not Forever

Not unlike the concern over diminishing fossil fuel, information technology is bringing its own share of future worries. Here, we chose to look closely into one concern in this paper, namely the limited amount of data storage. By a simple extrapolatory analysis, it is shown that we are on the way to exhaust our storage capacity in less than two centuries with current technology and no recycling. This can be taken as a note of caution to expand research initiative in several directions: firstly, bringing forth innovative data analysis techniques to represent, learn, and aggregate useful knowledge while filtering out noise from data; secondly, tap onto the interplay between storage and computing to minimize storage allocation; thirdly, explore ingenious solutions to expand storage capacity. Throughout this paper, we delve deeper into the state-of-the-art research and also put forth novel propositions in all of the abovementioned directions, including space- and time-efficient data representation, intelligent data aggregation, in-memory computing, extra-terrestrial storage, and data curation. The main aim of this paper is to raise awareness on the storage limitation we are about to face if current technology is adopted and the storage utilization growth rate persists. In the manuscript, we propose some storage solutions and a better utilization of storage capacity through a global DIKW hierarchy.

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