Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.
Accounting for Pedagogical Content Knowledge in a Theory of Change Analysis

Educators have long claimed that pedagogical content knowledge (PCK), ways of presenting a subject that make it comprehensible to others, is a critical element of student academic success. This paper presents an exploratory study finding that PCK significantly correlates with students' computer science (CS) content knowledge acquisition while teacher CS content knowledge does not. This study analyzes systemic factors comprising the theory of change for the EarSketch learning intervention including classroom- and student-level factors that contribute to shifts in students' attitudes toward computing and ultimately to students' intentions to persist in future computing endeavors and students' CS content knowledge. We present the results of a multi-level modeling analysis and offer an exploratory approach to measuring CS PCK along with recommendations to improve the sensitivity of the method.
Chemoattraction and Recruitment of Activated Immune Cells, Central Autonomic Control, and Blood Pressure Regulation

Inflammatory mediators play a critical role in the regulation of sympathetic outflow to cardiovascular organs in hypertension. Emerging evidence highlights the involvement of immune cells in the regulation of blood pressure. However, it is still unclear how these immune cells are activated and recruited to key autonomic brain regions to regulate sympathetic outflow to cardiovascular organs. Chemokines such as C-C motif chemokine ligand 2 (CCL2), and pro-inflammatory cytokines such as tumor necrosis factor alpha (TNF-α) and interleukin 1 beta (IL-1β), are upregulated both peripherally and centrally in hypertension. More specifically, they are upregulated in key autonomic brain regions that control sympathetic activity and blood pressure such as the paraventricular nucleus of the hypothalamus and the rostral ventrolateral medulla. Furthermore, this upregulation of inflammatory mediators is associated with the infiltration of immune cells to these brain areas. Thus, expression of pro-inflammatory chemokines and cytokines is a potential mechanism promoting invasion of immune cells into key autonomic brain regions. In pathophysiological conditions, this can result in abnormal activation of brain circuits that control sympathetic nerve activity to cardiovascular organs and ultimately in increases in blood pressure. In this review, we discuss emerging evidence that helps explain how immune cells are chemoattracted to autonomic nuclei and contribute to changes in sympathetic outflow and blood pressure.
Accountable Disciplinary Knowledge in Computing Education: A Case-Comparative Approach

This paper uses an approach that differs from conventional interview research to trace the individual trajectories of two computing graduates. In this approach, interviews are considered a dialogic process and analysis is a case-centred process that explores similarities and differences in participants' trajectories. This approach allows us to probe the experience and lasting value of computing education beyond graduation. In this extended analytic approach we expose participants' sense of professionalism and we connect this with the concept of accountable disciplinary knowledge (ADK). ADK has previously only been applied to students' experiences and identity formation at university. The approach taken in this work allows us to see the extension of ADK into the workplace.
The Effect of Cochlear Implants on Cognitive Function in Older Adults: Initial Baseline and 18-Month Follow Up Results for a Prospective International Longitudinal Study

In older adults, hearing loss is independently associated with an increased rate of cognitive decline, and has been identified to be a modifiable risk factor for dementia. The mechanism underlying the cognitive decline associated with hearing loss is not understood, but it is known that the greater the hearing loss, the faster the rate of decline. It is unknown whether remediation of hearing loss with hearing devices can delay cognitive decline. This 5-year international longitudinal study is investigating the impact of cochlear implants on cognitive function in older people with severe-profound hearing loss, and whether remediation of hearing loss could delay the onset of cognitive impairment. This is the first study to examine the major primary risk factors associated with dementia in the same cohort. Participants were assessed before cochlear implantation and 18 months later using an identical battery including a visually presented cognitive assessment tool (Cogstate battery) that is highly sensitive to small changes in cognition and suitable for use with people with hearing loss. Hearing and speech perception ability were assessed in sound-treated conditions by an audiologist, and a range of questionnaire tools was administered to assess self-perceived ease of listening, quality of life, physical activity, diet, social and emotional loneliness, isolation, anxiety, and depression. A detailed medical health history was taken. Pre-operatively, despite the small initial sample size (n = 59), increased hearing loss and age predicted significantly poorer executive function and visual attention, while tertiary education predicted better executive function. Better self-reported quality of life was correlated with better visual learning performance, and engaging in frequent vigorous physical activity was correlated with poorer visual learning performance. At 18 months, for the first 20 participants, significant benefits of cochlear implants were seen in terms of speech perception, communication ability, and quality of life. Multiple linear regression modeling showed executive function improved significantly for non-tertiary educated males, while cognitive function remained stable for other participants. Further follow-up at 18 month intervals with a larger sample will reveal the effects of cochlear implant intervention on all outcomes, and whether this can delay cognitive decline.
From Theory Bias to Theory Dialogue: Embracing Cognitive, Situated, and Critical Framings of Computational Thinking in K-12 CS Education

The increased interest in promoting CS education for all has been coalescing around the idea of "computational thinking. " Several framings for promoting computational thinking in K-12 education have been proposed by practitioners and researchers that each place different emphases on either (1) skill and competence building, (2) creative expression and participation, or (3) social justice and ethics. We review each framing and how the framings structure the theory space of computational thinking. We then discuss how CS education can leverage the explanatory potential that each framing offers to the implementation and evaluation of learning, teaching, and tools in computing education. Our goal is to help CS education researchers, teachers, and designers unpack and leverage the complexities of this theory space (rather than ignoring it) while also addressing broader educational concerns regarding diversity, providing new directions for how students and teachers can actively participate in designing their digital futures, and directing current computing education efforts towards a more humanistic orientation.
An MIP Approach to the U-line Balancing Problem With Proportional Worker Throughput

One of the major challenges faced by manufacturing companies is to remain competitive in dynamic environments, where fluctuations in customer demand and production rates require systems capable of adapting in a practical and economical way. A U-shaped production cell is considered one of the most flexible designs for adapting the workforce level to varying conditions. However, re-balancing efforts are time consuming and often require a new work allocation and line design. In this paper, a two-stage MIP model to determine the best cell design under varying workforce levels is proposed. The model seeks to maintain proportionality between throughput and the number of workers. Computational experiments considering various line configurations (up to 19 stations) and workloads (up to 79 tasks) are performed. The results show the proposed algorithm provides excellent results for all small and medium size problems addressed in this study, as well as for certain configurations of large problems. This approach can be used to generate lookup tables of line designs to help with quick reallocation of worker assignments on the shop floor and with minimal disruption.
Instructors Desire Student Activity, Literacy, and Video Quality Analytics to Improve Video-based Blended Courses

While video becomes increasingly prevalent in educational settings, current research has yet to investigate what feedback instructors need regarding their students' engagement and learning despite video technologies being equipped to provide viewing analytics and collect student feedback. In this paper we investigate instructors' requirements from video analytics. We used a Grounded Theory Approach and interviewed 16 instructors who teach using video to determine the advantages for using video in their teaching and the different requirements for analytics and feedback in their existing practice. Based on our analysis of the interviews, we found three categories of information that instructors want to inform their teaching. Instructors are looking to see if their students have watched their videos, how much they understood in those videos, and how useful the videos are to the students. These categories provide the foundations and design implications for instructor-centric educational video analytics interfaces.
Disturbance Size Can Be Compensated for by Spatial Fragmentation in Soil Microbial Ecosystems

One major interest in soil systems ecology is to maintain ecosystem functions. As soil is exposed to disturbances of different spatial configurations, identifying disturbance characteristics that still allow for maintaining functions is crucial. In macro-ecology, the influence of fragmentation on ecosystems is continuously debated, especially in terms of extinction thresholds on the landscape scale. Whether this influence is positive or negative depends on the considered type of fragmentation: habitat fragmentation often promotes population extinction, whereas spatially fragmented disturbances reduce extinction probability in many cases. In this study, we make use of these concepts to analyze how spatial disturbance characteristics determine functional resilience on the microscale. We used the numerical model eColony considering bacterial growth, substrate consumption and dispersal for analyzing the dynamic response of biodegradation as an exemplary important microbial ecosystem function to disturbance events. We systematically varied the frequency of the disturbance events, and the size and fragmentation of the disturbed area. We found that the influence of the disturbance size on functional recovery depends on the spatial fragmentation of the disturbance, indicating that to some extent disturbance size can be compensated for by the spatial configuration of the disturbed area. In general, biodegradation performance decreases as the disturbed area increases in size and becomes more contiguous. However, if a disturbance is highly fragmented, an increase in disturbance size has no influence on biodegradation performance unless the disturbance is critically large. In this case, the functional performance decreases dramatically. Under recurrent disturbances, this critical disturbance size is shifted towards lower values depending on the disturbance frequency. Our results indicate the importance of spatial disturbance characteristics for functional resilience of soil microbial ecosystems. Critical values for disturbance size and degree of fragmentation emerge from an interplay between both characteristics. Consequently, these characteristics which are widely discussed on the landscape scale need to be equally considered on smaller scales when assessing functional resilience of soil ecosystems.
Sex and Age Dependencies of Aqueductal Cerebrospinal Fluid Dynamics Parameters in Healthy Subjects

Objectives To assess the influence of age and sex on 10 cerebrospinal fluid (CSF) flow dynamics parameters measured with an MR phase contrast (PC) sequence within the cerebral aqueduct at the level of the intercollicular sulcus. Materials and Methods 128 healthy subjects (66 female subjects with a mean age of 52.9 years and 62 male subjects with a mean age of 51.8 years) with a normal Evans index, normal medial temporal atrophy (MTA) score, and without known disorders of the CSF circulation were included in the study. A PC MR sequence on a 3T MR scanner was used. Ten different flow parameters were analyzed using postprocessing software. Ordinal and linear regression models were calculated. Results The parameters stroke volume (sex: p < 0.001, age: p = 0.003), forward flow volume (sex: p < 0.001, age: p = 0.002), backward flow volume (sex: p < 0.001, age: p = 0.018), absolute stroke volume (sex: p < 0.001, age: p = 0.005), mean flux (sex: p < 0.001, age: p = 0.001), peak velocity (sex: p = 0.009, age: p = 0.0016), and peak pressure gradient (sex: p = 0.029, age: p = 0.028) are significantly influenced by sex and age. The parameters regurgitant fraction, stroke distance, and mean velocity are not significantly influenced by sex and age. Conclusion CSF flow dynamics parameters measured in the cerebral aqueduct are partly age and sex dependent. For establishment of reliable reference values for clinical use in future studies, the impact of sex and age should be considered and incorporated.
Effectiveness of Presenting Multiple Driving Support Information Using the Driver's Peripheral Vision

6. ま と め 交差点での出合頭の実態を把握するため,交通事故データ の分析により多発事故形態を明らかにし,多発事故形態の一 つである無信号交差点での車両対自転車の出合頭事故に着目 した. タクシー車両に搭載したドライブレコーダで収集した ヒヤリハットデータの分析を行い,下記項目を明らかにした. (1)交通事故データからは把握できなかった,交差点に進入 する自転車の発見行動や,急ブレーキ操作時の車両速度,急 ブレーキ前後の車両の走行状況,急ブレーキ直前の運転者の ペダル操作等を解明できた. また,車両の走行状況や急ブレ ーキ直前の運転者のペダル操作から,車両対自転車出合頭に おける代表的なヒヤリハットのパターンを一時停止規制有無 別に明確にした. (2)パターン毎にヒヤリハット事例の詳細解析を行なうこと により,車両対自転車の出合頭での道路交通環境と車両の走 行状況,自転車の交差点進入状況を明らかにし,分類すると 共に,車両対自転車の危険要因を明らかにするための再現実 験や,シミュレーションモデル作成に必要な交通環境や要因 に対する知見を得ることができた. また,交差点に進入する 自転車の発見を遅らせる道路交通環境要因を,具体例を用い て示した. 本稿より無信号交差点での車両対自転車の出合頭事故の要 因を明らかにできたと考えられる. 今後このような要因を減 らす手法を考えていきたい.
Enhancing Computer Science Education with Adaptive Serious Games

The use of games for education has shown effectiveness in engaging students to learn. Computer Science is one of the most heavily targeted fields of study for educational games. A major challenge for serious games is the need for them to be suitable for learners with different abilities and needs. To address this challenge, this thesis considers the use of automatically adaptive serious games (in the context of Computer Science). The goal of this research is to develop a methodology for modifying existing non-adaptive programming games and assess the benefits of applying an adaptive approach with respect to learner engagement and achievement of learning outcomes.
Age-Related DNA Methylation Changes: Potential Impact on Skeletal Muscle Aging in Humans

Human aging is accompanied by a decline in muscle mass and muscle function, which is commonly referred to as sarcopenia. Sarcopenia is associated with detrimental clinical outcomes, such as a reduced quality of life, frailty, an increased risk of falls, fractures, hospitalization, and mortality. The exact underlying mechanisms of sarcopenia are poorly delineated and the molecular mechanisms driving the development and progression of this disorder remain to be uncovered. Previous studies have described age-related differences in gene expression, with one study identifying an age-specific expression signature of sarcopenia, but little is known about the influence of epigenetics, and specially of DNA methylation, in its pathogenesis. In this review, we will focus on the available knowledge in literature on the characterization of DNA methylation profiles during skeletal muscle aging and the possible impact of physical activity and nutrition. We will consider the possible use of the recently developed DNA methylation-based biomarkers of aging called epigenetic clocks in the assessment of physical performance in older individuals. Finally, we will discuss limitations and future directions of this field.
Deprecating Misconceptions through Context-Dependent Accounts of Productive Knowledge

This paper aims to expand our sense of what's possible in modeling cognition within computing education research. We argue that research approaches that privilege canonical knowledge do so at the expense of other productive knowledge and ways of knowing that students have. We explore applicable cognitive theory by showing how manifold models of cognition can be powerful frameworks for analysis in Computing Education (CEd). Finally, we conclude with an exploration of epistemological concerns, arguing that a fundamental concern for our research community should be paying attention to what counts as knowledge and knowing in computing learning environments.
Infant Brain Structural MRI Analysis in the Context of Thoracic Non-cardiac Surgery and Critical Care

Objective: To determine brain magnetic resonance imaging (MRI) measures of cerebrospinal fluid (CSF) and whole brain volume of full-term and premature infants following surgical treatment for thoracic non-cardiac congenital anomalies requiring critical care. Methods: Full-term (n = 13) and pre-term (n = 13) patients with long-gap esophageal atresia, and full-term naïve controls (n = 19) < 1 year corrected age, underwent non-sedated brain MRI following completion of thoracic non-cardiac surgery and critical care treatment. Qualitative MRI findings were reviewed and reported by a pediatric neuroradiologist and neurologist. Several linear brain metrics were measured using structural T1-weighted images, while T2-weighted images were required for segmentation of total CSF and whole brain tissue using the Morphologically Adaptive Neonatal Tissue Segmentation (MANTiS) tool. Group differences in absolute (mm, cm3) and normalized (%) data were analyzed using a univariate general linear model with age at scan as a covariate. Mean normalized values were assessed using one-way ANOVA. Results: Qualitative brain findings suggest brain atrophy in both full-term and pre-term patients. Both linear and volumetric MRI analyses confirmed significantly greater total CSF and extra-axial space, and decreased whole brain size in both full-term and pre-term patients compared to naïve controls. Although linear analysis suggests greater ventricular volumes in all patients, volumetric analysis showed that normalized ventricular volumes were higher only in premature patients compared to controls. Discussion: Linear brain metrics paralleled volumetric MRI analysis of total CSF and extra-axial space, but not ventricular size. Full-term infants appear to demonstrate similar brain vulnerability in the context of life-saving thoracic non-cardiac surgery requiring critical care as premature infants.
Storytelling from Structured Data and Knowledge Graphs : An NLG Perspective

In this tutorial, we wish to cover the foundational, methodological, and system development aspects of translating structured data (such as data in tabular form) and knowledge bases (such as knowledge graphs) into natural language. The attendees of the tutorial will be able to take away from this tutorial, (1) the basic ideas around how modern NLP and NLG techniques could be applied to describe and summarize textual data in format that is non-linguistic in nature or has some structure, and (2) a few interesting open-ended questions, which could lead to significant research contributions in future. The tutorial aims to convey challenges and nuances in structured data translation, data representation techniques, and domain adaptable solutions for translation of the data into natural language form. Various solutions, starting from traditional rule based/heuristic driven and modern data-driven and ultra-modern deep-neural style architectures will be discussed, followed by a brief discussion on evaluation and quality estimation. A significant portion of the tutorial will be dedicated towards unsupervised, scalable, and adaptable solutions, given that systems for such an important task will never naturally enjoy sustainable large scale domain independent labeled (parallel) data.
A Case Study on Design Patterns and Software Defects in Open Source Software

Design patterns are object oriented software design practices for solving common design problems and they affect software quality. In this study, we investigate the relationship of design patterns and software defects in a number of open source software projects. Design pattern instances are extracted from the source code repository of these open source software projects. Software defect metrics are extracted from the bug tracking systems of these projects. Using correlation and regression analysis on extracted data, we examine the relationship between design patterns and software defects. Our findings indicate that there is little correlation between the total number of design pattern instances and the number of defects. However, our regression analysis reveals that individual design pattern instances as a group have strong influences on the number of defects. Furthermore, we find that the number of design pattern instances is positively correlated to defect priority. Individual design pattern instances may have positive or negative impacts on defect priority.