Science Case Research Articles

MHealth to improve implementation of TB contact investigation: a case study from Uganda

BackgroundImplementation science offers a systematic approach to adapting innovations and delivery strategies to new contexts but has yet to be widely applied in low- and middle-income countries. The Fogarty Center for Global Health Studies is sponsoring a special series, “Global Implementation Science Case Studies,” to address this gap.MethodsWe developed a case study for this series describing our approach and lessons learned while conducting a prospective, multi-modal study to design, implement, and evaluate an implementation strategy for TB contact investigation in Kampala, Uganda. The study included formative, evaluative, and summative phases that allowed us to develop and test an adapted contact investigation intervention involving home-based sample collection for TB and HIV testing. We concurrently developed a multi-component mHealth implementation strategy involving fingerprint scanning, electronic decision support, and automated reporting of test results via text message. We then conducted a household-randomized, hybrid implementation-effectiveness trial comparing the adapted intervention and implementation strategy to usual care. Our assessment included nested quantitative and qualitative studies to understand the strategy’s acceptability, appropriateness, feasibility, fidelity, and costs. Reflecting on this process with a multi-disciplinary team of implementing researchers and local public health partners, we provide commentary on the previously published studies and how the results influenced the adaptation of international TB contact investigation guidelines to fit the local context.ResultsWhile the trial did not show improvements in contact investigation delivery or public health outcomes, our multi-modal evaluation strategy helped us identify which elements of home-based, mHealth-facilitated contact investigation were feasible, acceptable, and appropriate and which elements reduced its fidelity and sustainability, including high costs. We identified a need for better tools for measuring implementation that are simple, quantitative, and repeatable and for greater attention to ethical issues in implementation science.ConclusionsOverall, a theory-informed, community-engaged approach to implementation offered many learnings and actionable insights for delivering TB contact investigation and using implementation science in low-income countries. Future implementation trials, especially those incorporating mHealth strategies, should apply the learnings from this case study to enhance the rigor, equity, and impact of implementation research in global health settings.

Siyaset Bilimi ve Kamu Yönetimi Bölümü Lisans Düzeyi Öğrencilerine Göre Bölümdeki Öğrenimde Yaşanan Sorunlar ve Öneriler

The study aimed to determine the problems experienced in political science and public administration education and suggestions for its solution in line with the views of undergraduate students of the faculty of economics and administrative sciences' department of political science and public administration. The research was conducted descriptively according to qualitative research method, case science and single case pattern. From the non-probability sampling types, the purposeful sampling method was used. Thirteen students determined from the fourth-year students of the department of political science and public administration of the faculty of economics and administrative sciences formed the participant group. Observation and interview and document review were used as data collection tools. Data were collected with semi-structured interview questions. The data obtained in the research were coded in the Maxqda 2022 program, categories based on codes and themes based on categories were reached. According to the participants, there are problems arising from their own learning in the department; from the education plan and program; from the course content and presentation; from the course supervisor and exams, and from employment after graduation, and there are some suggestions for solving these.

Awesome SOSS: transmission spectroscopy of WASP-96b with NIRISS/SOSS

ABSTRACT The future is now – after its long-awaited launch in 2021 December, JWST began science operations in 2022 July and is already revolutionizing exoplanet astronomy. The Early Release Observations (ERO) programme was designed to provide the first images and spectra from JWST, covering a multitude of science cases and using multiple modes of each on-board instrument. Here, we present transmission spectroscopy observations of the hot-Saturn WASP-96 b with the Single Object Slitless Spectroscopy (SOSS) mode of the Near Infrared Imager and Slitless Spectrograph, observed as part of the ERO programme. As the SOSS mode presents some unique data reduction challenges, we provide an in-depth walk-through of the major steps necessary for the reduction of SOSS data: including background subtraction, correction of 1/f noise, and treatment of the trace order overlap. We furthermore offer potential routes to correct for field star contamination, which can occur due to the SOSS mode’s slitless nature. By comparing our extracted transmission spectrum with grids of atmosphere models, we find an atmosphere metallicity between 1× and 5× solar, and a solar carbon-to-oxygen ratio. Moreover, our models indicate that no grey cloud deck is required to fit WASP-96 b’s transmission spectrum, but find evidence for a slope shortward of 0.9 μm, which could either be caused by enhanced Rayleigh scattering or the red wing of a pressure-broadened Na feature. Our work demonstrates the unique capabilities of the SOSS mode for exoplanet transmission spectroscopy and presents a step-by-step reduction guide for this new and exciting instrument.

ANOMALY DETECTION - REVIEW OF METHODS, TOOLS AND ALGORITHMS

This paper contains review of algorithms, methods and tools nowadays used for anomaly detection.Anomaly detection is used in many domains of science and industry, some authors classify anomaly detection as data mining and data science tool, others state it is decision support tool under artificial intelligence domain and indeed the use cases of anomaly detection are very different.The article describes the main algorithms used for anomaly detection from perspective of theory of computer science and practical use cases of anomaly detection in different domains of industry. Several paragraphs are dedicated to the frameworks used by one of the most popular and powerful anomaly detection tools available in the market - Microsoft Anomaly detector.

On the Perceptions of Russia as an Educational Destination by the Students at German University

Purpose. The purpose of the article was to explore how Russia is perceived as an educational destination among undergraduate (B. A.) and postgraduate (M. A.) students at Rhine-Waal University of Applied Sciences (Kleve, Germany) during the summer semester 2022.Methods. The research was conceived as a reflective study based on the case-oriented research design and with a single case examined: the Rhine-Waal University of Applied Sciences (Kleve, Germany) and its undergraduate (B. A.) and postgraduate (M. A.) students. To address the research question: “How is Russia being perceived as an educational destination by undergraduate (B.A) and postgraduate (M.A) students at Rhine-Waal University of Applied Sciences in Germany?”, a mixed method was selected with archival and document-based research which was paired with a survey as a data collection technique; and a content analysis as a strategy for data analysis.results. Results of this survey have showed that 79% of respondents would like to visit Russia, but only 18% of respondents may consider Russia as a place to go studying (results are based on 33 replies out of 7390 students in total — the justification of small sampling is explained in the Methods part). Strikingly low interest to study in Russia was explained by 1) other educational destination preferences; 2) language barrier, and 3) lack of information on the Russian study programs and 4) insufficient financial support of studying in Russia. In addition, the survey results indicated that the negative perceptions of Russia as an educational destination could be related to the different values held by the students at the Rhine-Waal University of Applied Sciences, and those held by general population in Russia (as perceived by the students), but this would require further investigation.Conclusions. There are three major findings resulting from this study. Firstly, there is an inadequate attention in International Relations’ literature on the influence of international student mobility and change in students’ worldview and values. Secondly, higher education and international student mobility are considered as one of the instruments for value promotion and factors contributing to the soft power of the states. Thirdly, the results of Rhine-Waal University of Applied Sciences case seem to confirm Sylvie Lomer’s hypothesis that students are already positively predisposed to the country where they intend to go studying.

Big Science, Big Trouble? Understanding Conflict in and Around Big Science Projects and Networks

Many Big Science projects and networks experience conflict. A plethora of disciplines have examined conflict causes in science collaboration and Big Science, contributing to a more nuanced understanding of why conflicts emerge. Yet, so far, there is no theoretical model that explains which mechanisms connect conflict cause and outbreak in Big Science. Drawing on interdisciplinary literature on science collaboration and Big Science as well as on scholarship on strategic action fields (SAFs), I address this blind spot by proposing a model that outlines which mechanisms induce and fuel conflict in Big Science projects and networks. Five interlinked mechanisms – attribution of threat or opportunity, mobilization of resources, coalition-building, boundary deactivation and innovative action – are central to it. Tracing these mechanisms in conflictual episodes which emerged in three typical, yet most-different, Big Science cases – the International Experimental Thermonuclear Reactor (ITER), the Human Brain Project (HBP) and the Thirty Meter Telescope (TMT) – this study also provides a proof of concept for the model.

Concept for a critical-angle transmission grating spectrometer for the AXIS probe

The Advanced X-ray Imaging Satellite (AXIS) is a probe-class mission concept with a large collecting area with a point-spread-function of order 1 to 2 arcsec. We describe a possible X-ray grating spectrometer (XGS) that could be added to AXIS with minimal design changes to the telescope itself and costs a small fraction of the total mission budget. The XGS would be based on critical-angle transmission (CAT) gratings, a technology already matured for Arcus and Lynx. Using detailed ray-tracing, we investigate several options for subaperturing that provide a trade-off between effective area and spectral resolving power. Depending on how much of the full aperture is covered with gratings (e.g., 17% to 100%), we find a high spectral resolving power up to λ / Δλ = 4000 can be achieved with effective area of 1500 cm2 in the 1.2 to 2.8 nm range or λ / Δλ = 6000 with effective area 500 cm2. An important benefit of CAT gratings is that they are mostly transparent at high energies, and thus hard x-rays can still be used for simultaneous imaging spectroscopy. We study different grating sizes and other enhancements, but even in the basic configuration an XGS can be added to AXIS to provide high-resolution spectral capabilities, opening a range of new science investigations. Our ray-tracing shows that this concept is mature and can be added to AXIS with minimal impact on other instruments. We discuss one exemplary science case that would be enabled by the XGS.

Inferring, not just detecting: Metrics for high-redshift sources observed with third-generation gravitational-wave detectors

The detection of black-hole binaries at high redshifts is a cornerstone of the science case of third-generation gravitational-wave interferometers. The star-formation rate peaks at $z\ensuremath{\sim}2$ and decreases by orders of magnitude by $z\ensuremath{\sim}10$. Any confident detection of gravitational waves from such high redshifts would imply either the presence of stars formed from pristine material originating from cosmological nucleosynthesis (the so-called population III stars), or black holes that are the direct relics of quantum fluctuations in the early Universe (the so-called primordial black holes). Crucially, detecting sources at cosmological distances does not imply inferring that sources are located there, with the latter posing more stringent requirements. To this end, we present two figures of merit, which we refer to as ``$z\text{\ensuremath{-}}z$ plot'' and ``inference horizon,'' that quantify the largest redshift one can possibly claim a source to be beyond. We argue that such inference requirements, in addition to detection requirements, should be investigated when quantifying the scientific payoff of future gravitational-wave facilities.

Choose Compassion: Why It Matters and How It Works (2022) by James Kirby. University of Queensland Press. ISBN: 9780702265648

One of Australia’s leading compassion researchers, Dr. James Kirby employs science and real-world cases to argue that compassion is the most important human motivation to harness in today’s world. Citing the benefits of compassion training exercises for life struggles including self-criticism, shame, grief, parenting, depression, and anxiety, Kirby draws on findings from the University of Queensland’s Compassionate Mind Research Group, of which he is co-director. Debunking the myth that compassion is a soft or weak emotion, he examines fears, blocks, and resistances we and our clients may have to compassion, which he defines as the courageous and wise motivation to turn towards suffering and try to alleviate it. Reviewer Prof. Paul Gilbert, who developed compassion focused therapy, applauds how Choose Compassion: Why it matters and how it works (Kirby, 2022) takes on big themes, such as the inevitability of suffering and loss, and makes them understandable and accessible to readers. Despite climate change, mass extinctions, genocide, wars, and the capacity of humans to be callous and contradictory, Kirby’s message is ultimately one of hope.

Effective Network Analytics: Network Visualization and Graph Data Management

Network analytics provides a scientific solution to interact with networks through effective management of network data and corresponding visualization. Network analytics has been considered essential in many research areas as well as in commercial applications, including use cases in bioinformatics, biomedicine, security, social science, and knowledge graph exploration. We see that networks and the associated analysis process are expected to be initially supported by graph databases with advanced query engines, and later the filtered contents are rendered using corresponding visualization approaches for better communication and knowledge exchange. For this special issue (SI), we recruited papers describing research based on graph database utilization and network visualization that potentially could be integrated as a full pipeline, as well as their synergy for various applied problems. Through the formal IEEE Computer Graphics and Applications review process of the four submissions, we accepted three papers for this SI, focusing on the novelty and potential integration within the network analytics pipeline. These selected papers demonstrate the wide potentiality of techniques for complex network analytics.

The case for citizen science in public health policy and practice: a mixed methods study of policymaker and practitioner perspectives and experiences

BackgroundCitizen science (CS) is increasingly being utilised to involve the public in public health research, but little is known about whether and how CS can address the needs of policy and practice stakeholders in health promotion and chronic disease prevention.MethodsUsing a mixed methods approach we conducted an online survey (n = 83) and semi-structured interviews (n = 21) with policy and practice stakeholders across Australia to explore how CS approaches are perceived and applied in chronic disease prevention, how CS aligns with existing approaches to community engagement, and how the uptake of CS can be supported within policy and practice settings.ResultsMost participants had heard of CS, and while few had experience of using CS, there was widespread support for this approach, with many seeing it as complementary to other community engagement approaches. CS was seen as providing: (a) a robust framework for engagement; (b) access to rich data; (c) opportunities for more meaningful engagement; and (d) a mutually beneficial approach for stakeholders and community members. However, stakeholders identified a need to weigh benefits against potential risks and challenges including competing organisational priorities, resourcing and expertise, data quality and rigour, governance, and engagement.ConclusionsTo expand the use of CS, stakeholders identified the need for increased awareness, acceptance, and capacity for CS within public health organisations, greater access to supporting tools and technology, and evidence on processes, feasibility and impacts to enhance the visibility and legitimacy of CS approaches.

Sleepy Mice Case Study: Implementation and Assessment.

Case studies are a valuable teaching tool to engage students in course content using real-world scenarios. As part of the High-throughput Discovery Science & Inquiry-based Case Studies for Today's Students (HITS) Research Coordination Network (RCN), our team has created the Sleepy Mice Case Study for students to engage with RStudio and the Allen Institute for Brain Science's open access high-throughput sleep dataset on mice. Sleep is important for health, a familiar concern to college students, and was a basis for this case study. In this case, students completed an initial homework assignment, in-class work, and a final take-home application assignment. The case study was implemented in synchronous and asynchronous Introductory Neuroscience courses, a Biopsychology course, and a Human Anatomy and Physiology course, reflecting its versatility. The case can be used to teach course-specific learning objectives such as sleep-related content and/or science data processing skills. The case study was successful as shown by gains in student scores and confidence in achieving learning objectives. Most students reported enjoying learning about sleep deprivation course content using the case study. Best practices based on instructor experiences in implementation are also included to facilitate future use so that the Sleepy Mice Case Study can be used to teach content and/or research-related skills in various courses and modalities.

Implicit electric field conjugation: Data-driven focal plane control

Context.Direct imaging of Earth-like planets is one of the main science cases for the next generation of extremely large telescopes. This is very challenging due to the star-planet contrast that has to be overcome. Most current high-contrast imaging instruments are limited in sensitivity at small angular separations due to non-common path aberrations (NCPA). The NCPA leak through the corona-graph and create bright speckles that limit the on-sky contrast and therefore also the post-processed contrast.Aims.We aim to remove the NCPA by active focal plane wavefront control using a data-driven approach.Methods.We developed a new approach to dark hole creation and maintenance that does not require an instrument model. This new approach is called implicit Electric Field Conjugation (iEFC) and it can be empirically calibrated. This makes it robust for complex instruments where optical models might be difficult to realize. Numerical simulations have been used to explore the performance of iEFC for different coronagraphs. The method was validated on the internal source of the Magellan Adaptive Optics extreme (MagAO-X) instrument to demonstrate iEFC’s performance on a real instrument.Results.Numerical experiments demonstrate that iEFC can achieve deep contrast below 10−9with several coronagraphs. The method is easily extended to broadband measurements and the simulations show that a bandwidth up to 40% can be handled without problems. Lab experiments with MagAO-X showed a contrast gain of a factor 10 in a broadband light and a factor 20–200 in narrowband light. A contrast of 5 × 10−8was achieved with the Phase Apodized Pupil Lyot Coronagraph at 7.5λ/D.Conclusions.The new iEFC method has been demonstrated to work in numerical and lab experiments. It is a method that can be empirically calibrated and it can achieve deep contrast. This makes it a valuable approach for complex ground-based high-contrast imaging systems.

Tree-based solvers for adaptive mesh refinement code flash – IV. An X-ray radiation scheme to couple discrete and diffuse X-ray emission sources to the thermochemistry of the interstellar medium

ABSTRACT X-ray radiation, in particular radiation between 0.1 and 10 keV, is evident from both point-like sources, such as compact objects and T-Tauri young stellar objects, and extended emission from hot, cooling gas, such as in supernova remnants. The X-ray radiation is absorbed by nearby gas, providing a source of both heating and ionization. While protoplanetary chemistry models now often include X-ray emission from the central young stellar object, simulations of star-forming regions have yet to include X-ray emission coupled to the chemo-dynamical evolution of the gas. We present an extension of the treeray reverse ray trace algorithm implemented in the flash magnetohydrodynamic code which enables the inclusion of X-ray radiation from 0.1 keV < Eγ < 100 keV, dubbed xraythespot. xraythespot allows for the use of an arbitrary number of bins, minimum and maximum energies, and both temperature-independent and temperature-dependent user-defined cross-sections, along with the ability to include both point and extended diffuse emission and is coupled to the thermochemical evolution. We demonstrate the method with several multibin benchmarks testing the radiation transfer solution and coupling to the thermochemistry. Finally, we show two example star formation science cases for this module: X-ray emission from protostellar accretion irradiating an accretion disc and simulations of molecular clouds with active chemistry, radiation pressure, and protostellar radiation feedback from infrared to X-ray radiation.

Research on the Development and Construction of Modern Science and Technology Park

Summarize the theoretical research results and the most advanced planning and development concepts of science and technology parks by combing the historical context of the construction and development of science and technology parks in the world. Study the typical cases of science and technology parks at home and abroad, study and sort out the development path and construction and operation ideas of new science and technology parks in small and medium-sized cities in China in recent years, absorb the experience of the establishment and operation of excellent science and technology parks at home and abroad, and explore the planning and design theory, development and operation ideas of science and technology parks in the context of "mass entrepreneurship and innovation", as well as the exploration of the park profit model based on the overall planning and development status of Qinchuangyuan, Shaanxi Province. To provide theoretical support and future development ideas for the subsequent planning and operation of Qinchuangyuan Western (Xianyang) Science and Technology Venture Bay, and improve its later construction plan and operation plan.

Identifying modified theories of gravity using binary black-hole ringdowns

Black-hole spectroscopy, that is, measuring the characteristic frequencies and damping times of different modes in a black-hole ringdown, is a powerful probe for testing deviations from the general theory of relativity (GR). In this work, we present a comprehensive study on its ability to identify deviations from the spectrum of a Kerr black hole in GR. Specifically, we investigate the performance of black hole spectroscopy on a diverse set of theoretically motivated as well as phenomenologically modified spectra. We find that while the signal-to-noise ratio $\rho_{\rm RD}$ in the ringdown required to identify a modification to the GR Kerr black hole spectrum depends on the details of the modifications, a modification that introduces $\sim 1 \%$ shift in the fundamental mode frequencies can typically be distinguished with $\rho_{\rm RD} \in [150,500]$. This range of $\rho_{\rm RD}$ is feasible with the next-generation detectors, showing a promising science case for black hole spectroscopy.

Radio galaxy zoo EMU: towards a semantic radio galaxy morphology taxonomy

ABSTRACT We present a novel natural language processing (NLP) approach to deriving plain English descriptors for science cases otherwise restricted by obfuscating technical terminology. We address the limitations of common radio galaxy morphology classifications by applying this approach. We experimentally derive a set of semantic tags for the Radio Galaxy Zoo EMU (Evolutionary Map of the Universe) project and the wider astronomical community. We collect 8486 plain English annotations of radio galaxy morphology, from which we derive a taxonomy of tags. The tags are plain English. The result is an extensible framework, which is more flexible, more easily communicated, and more sensitive to rare feature combinations, which are indescribable using the current framework of radio astronomy classifications.

Studi Literatur Konsep dan Implementasi Sains Data untuk Memaksimalkan Kinerja Industri Manufaktur

The manufacturing industry is currently faced with increasingly complex and diverse challenges. To address this challenge, companies need an approach based on data science to improve production performance and efficiency. This paper proposes the concept and implementation of data science in the manufacturing industry. Several important concepts in data science, including predictive analysis, prescriptive analysis, and optimization, are introduced. It also highlights the algorithms and data analysis techniques used to maximize production performance and reduce costs. Implementing data science in the manufacturing industry involves steps such as data collection, data processing, data analysis, and decision-making. Several use cases of data science in the manufacturing industry, including predictive analytics to forecast machine failures, prescriptive analysis to increase productivity, and optimization to optimize production schedules, are discussed here. The results of this scientific paper show that implementing data science in the manufacturing industry can significantly improve production performance and efficiency. This scientific paper provides useful insights for practitioners, researchers, and policymakers in the manufacturing industry who are interested in applying data science to production processes

141 Translational Barriers, Facilitators, and Benefits of Impactful Research on Health Inequities in the Criminal Justice System

OBJECTIVES/GOALS: - Illuminate processes and findings of a translational science case study of impactful research with incarcerated pregnant women and mothers; - Improve our understanding of the translational mechanisms by sharing translational challenges, facilitators, an METHODS/STUDY POPULATION: Utilized the following evaluation methods and tools: - The Retrospective Translational Science Case Study protocol to examine translational path from innovation to policy and practice, barriers and facilitators for that translational movement. - Translational Science Benefits Model (TSBM) Checklist for translational/research impact analysis Triangulated diverse data sources: - Primary data: semi-structured interviews with research partners - Secondary data: researchers’ grant applications, reports, and publications; public stories/news related to their research; scientific publications; organizational/policy documents; and over 50 interviews with 30 stakeholders featured in published sources. RESULTS/ANTICIPATED RESULTS: The research contributed to community and public health, policy/legislative, clinical/medical, and economic benefits, social/institutional change, health equity advocacy, catalyzing research (consequent research studies) and public awareness. Translational research challenges: cultural differences between research and prison system; politics of translating research to policy change; issues of capacity, power, privilege, and opportunity when doing community-engaged research; and science vs. social justice criticism. Facilitators of translation: CTSA support; stakeholder engagement; authentic collaboration; researchers as translation catalysts; and engagement in legislative activities. DISCUSSION/SIGNIFICANCE: The evaluation case study provides useful knowledge about translational impact, challenges, and facilitators of community-based research that moved along the translational continuum and contributed to transformational, systemic changes on the legal, clinical, organizational, and interpersonal levels.

57 Utility of Digital Phenotyping in Big Data to Answer Clinical Questions: Puberty as a Transdisciplinary Science Case Example

OBJECTIVES/GOALS: A disease-agnostic translational science framework for data mining is proposed for use across disciplines to: Answer clinical questions, justify future clinical research recruitment, and explore under-represented populations. As a case example, male puberty demonstrates utility of the framework. METHODS/STUDY POPULATION: As a case example using the generalizable framework, the following interdisciplinary question was asked: Does early pubertal timing increase the risk of developing type II diabetes (T2d) in boys? A digital phenotype of males < 18 years old was created in the TriNetX Diamond Network utilizing Boolean operator data queries. TriNetX contains patient electronic health record information (ICD-10 diagnoses, anthropometric measures). A case control analysis leveraging patient counts from various digital phenotypes allowed for outcome (T2d) comparison of boys diagnosed with precocious puberty (E30.1, ICD code for early pubertal timing) to those without, while controlling for body mass index (BMI). RESULTS/ANTICIPATED RESULTS: Subjects (N=12,996,132) displayed the following digital phenotype: Male, < 18 years old, without ever having a BMI documented >85th percentile. Boys diagnosed with precocious puberty (E30.1) were 6.89 times more likely to develop T2d when aged 14-18 years old than those without (OR 6.89, 95%CI: 5.17-9.19, p. DISCUSSION/SIGNIFICANCE: Boys are under-represented in the early pubertal timing literature, justifying future human subjects research on male puberty. This case example demonstrates a broader disease-agnostic framework which can be adapted across disciplines. Opportunities may include public health digital phenotyping.