Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of physiotherapy interventions on headache intensity, frequency, duration and quality of life of patients with tension-type headache. A systematic review and network meta-analysis

Background This systematic review assesses the effectiveness of physiotherapy on headache parameters and quality of life of patients with tension-type headache using network meta-analysis. Methods A systematic search was conducted in the databases Web of Science, Medline, Cochrane Library and Physiotherapy Evidence Database up to August 2021. Randomised controlled trials investigating the effect of physiotherapy on tension-type headache were included. Risk of bias assessment was performed using the Risk of bias tool 2.0. Results were presented according to the Cochrane handbook and the PRISMA statement. Results Twenty reports were eligible and 15 were included in network meta-analysis for pain intensity and frequency. Transcutaneous electrical stimulation combined with physiotherapy was the most effective approach to reduce pain intensity compared to control (mean difference (MD): −4.18, moderate confidence) and usual care (MD: −3.8, moderate confidence) Manual therapy (joint mobilisation) plus exercise was the most effective intervention to reduce headache frequency compared to control (MD: −13.03, low confidence) and usual care (MD: −13.95, moderate confidence). Conclusion Results suggest a combination of passive physiotherapy techniques with exercise and/or transcutaneous electrical stimulation as the most effective physiotherapy intervention to reduce pain intensity and frequency in the short term. More research is needed to investigate mid-term and long-term effects. Trial registration: This review was prospectively registered in www.aspredicted. org under the registration number #46098 and an updated protocol was registered in the Open Science Framework (OSF) with the registration DOI: https://doi.org/10.17605/OSF.IO/RVUEY
The Evaluation Method for the Hazard Grading of the Rockfall at the Slope Segment of the Tunnel Entrance

To meet the need of the decision-making for the rockfall control at the slope segment of the tunnel entrance,and in connection with the features of the tunnel entrance as well as the traffic operation of both the railway and the highway,the hazard grading for the rockfall was comprehensively evaluated.The evaluation was conducted from two aspects,namely,the possibility of rockfall causing hazard(including the possibility of the dangerous rock collapsing and the possibility of the rockfall reaching the tunnel entrance) and the severity of the hazard.Accordingly,the grading indexes for the rockfall hazard at the slope segment of the tunnel entrance were defined.On the basis of quantitatively scoring each influencing factor,the evaluation method was established for rockfall hazard grading in the zone of the tunnel entrance.The method was applied to the rockfall hazard evaluation of eight tunnel entrances.The results show that the method can meet the needs of the decision-making for the rockfall control and can set the risk grade for the calculation of rockfall movement path,speed,kinetic energy and so on.
Superior Efficacy of Midostaurin Over Cladribine in Advanced Systemic Mastocytosis: A Registry-Based Analysis

PURPOSE On the basis of data from the German Registry on Disorders of Eosinophils and Mast Cells, we compared the efficacy of midostaurin and cladribine in patients with advanced systemic mastocytosis (AdvSM). PATIENTS AND METHODS Patients with AdvSM (n = 139) were treated with midostaurin only (n = 63, 45%), cladribine only (n = 23, 17%), or sequentially (midostaurin-cladribine, n = 30, 57%; cladribine-midostaurin, n = 23, 43%). Prognosis was assessed through the Mutation-Adjusted Risk Score (MARS). Besides the comparison of efficacy between midostaurin and cladribine on response (eg, organ dysfunction, bone marrow mast cell [MC] infiltration, and tryptase), overall survival (OS), and leukemia-free survival, we focused on the impact of treatment on involved non-MC lineages, for example, monocytes or eosinophils, and the KIT D816V expressed allele burden. RESULTS Midostaurin only was superior to cladribine only with effects from responses on MC and non-MC lineages conferring on a significantly improved OS (median 4.2 v 1.9 years, P = .033) and leukemia-free survival (2.7 v 1.3 years, P = .044) on the basis of a propensity score–weighted analysis of parameters included in MARS. Midostaurin compensated the inferior efficacy of cladribine in first- and second-line treatment. On midostaurin in any line, response of eosinophilia did not improve its baseline adverse prognostic impact, whereas response of monocytosis proved to be a positive on-treatment parameter. Multivariable analysis allowed to establish three risk categories (low/intermediate/high) through the combination of MARS and the reduction of the KIT D816V expressed allele burden of ≥ 25% at month 6 (median OS not reached v 3.0 years v 1.0 year; P < .001). CONCLUSION In this registry-based analysis, midostaurin revealed superior efficacy over cladribine in patients with AdvSM. In midostaurin-treated patients, the combination of baseline MARS and molecular response provided a compelling three-tier risk categorization (MARSv2.0) for OS. The multikinase inhibitor midostaurin is superior to cladribine in 1L- and 2L-treatment of AdvSM.
Clinical Relevance of the Constitutive Androstane Receptor

Constitutive androstane receptor (CAR) (NR1I3), a xenobiotic receptor, has long been considered a master mediator of drug disposition and detoxification. Accumulating evidence indicates that CAR also participates in various physiologic and pathophysiological pathways regulating the homeostasis of glucose, lipid, and bile acids, and contributing to cell proliferation, tissue regeneration and repair, as well as cancer development. The expression and activity of CAR can be regulated by various factors, including small molecular modulators, CAR interaction with other transcription factors, and naturally occurring genetic variants. Given that the influence of CAR has extended beyond the realm of drug metabolism and disposition and has expanded into a potential modulator of human diseases, growing efforts have centered on understanding its clinical relevance and impact on human pathophysiology. This review highlights the current information available regarding the contribution of CAR to various metabolic disorders and cancers and ponders the possible challenges that might arise from pursuing CAR as a potential therapeutic target for these diseases. SIGNIFICANCE STATEMENT The growing importance of the constitutive androstane receptor (CAR) in glucose and lipid metabolism as well as its potential implication in cell proliferation emphasizes a need to keenly understand the biological function and clinical impact of CAR. This minireview captures the clinical relevance of CAR by highlighting its role in metabolic disorders and cancer development.
A re-appraisal of Parvicursor remotus from the Late Cretaceous of Mongolia: implications for the phylogeny and taxonomy of alvarezsaurid theropod dinosaurs

Parvicursor remotus Karhu & Rautian, 1996, based on a fragmentary skeleton from the Campanian Barungoyot Formation at Khulsan, in the Gobi Desert of Mongolia, is re-described in detail. Contrary to the original description, we find no evidence that the last dorsal vertebra is opisthocoelous. A biconvex last dorsal vertebra could be present in Parvicursor as in other parvicursorines. The transversely compressed sacral centrum with a sharp ventral keel is the last sacral, not the first sacral as originally alleged. The pelvic bones are not fused at the acetabulum. The holotype of P. remotus, the smallest known alvarezsaurid specimen, is a juvenile individual far from skeletal maturity. New morphological details of Parvicursor that are revealed include a ventral ridge on the posterior dorsal vertebrae; a horizontal supraacetabular crest of the ilium whose anterior end is placed anterior to the most ventrally projecting part of the pubic peduncle; the possible presence of a pubic obturator foramen; an entocondylar tuber on the femur; internal flexor flanges on metatarsals II and IV; a lateral flexor ridge on metatarsal IV; and a proximoventral notch on pedal phalanx IV-1. The Tugriken Shireh alvarezsaurid is not referable to Parvicursor because of its much larger ungual phalanx on the second pedal digit. Kol ghuva is excluded from Alzarezsauridae. The two successive sister taxa for Parvicursor are Ceratonykus and Linhenykus. Ceratonykus differs little from Parvicursor and might be a synonym of the latter. Linhenykus is very similar to Parvicursor in all overlapping skeletal elements. The Parvicursorinae includes all Asian Late Cretaceous alvarezsaurids except Qiupanykus and Nemegtonykus.
A queuing model of airport congestion and policy implications at JFK and EWR

Since the phasing-out of the High Density Rule, access to major commercial airports in the United States has been unconstrained or, in the case of the airports of New York, weakly constrained. This largely unregulated demand combined with capacity constraints led to record delay levels in 2007, whose costs were estimated as in excess of $30 billion a year. Mitigating airport congestion may be achieved through demand management measures. Quantifying the benefits of such measures requires careful modeling of flight delays as a function of flight schedules. This thesis applies a stochastic and dynamic queuing model to analyze operations at JFK and Newark (EWR), two of the most congested airports in the United States. Two models are used to approximate the dynamics of the queuing system: a numerical model called DELAYS and a new Monte Carlo simulation model, which combines time-varying stochastic models of demand and capacity. These two models are then calibrated and validated using historical records of operations. In particular, they provide estimates of the average throughput rate at JFK and EWR under different weather conditions. The models are then shown to predict accurately both the magnitude of the delays and their evolution over the course of a day of operations. In addition, the Monte Carlo simulation model evaluates reasonably well the variability of the delays between successive days of operations. These two models are then applied to a study of recent trends in scheduling and ontime performance at JFK and EWR. The analysis indicates that the significant delay reductions observed between 2007 and 2010 can be largely attributed to the relatively small reduction of airport demand over this period. In particular, it demonstrates the strongly nonlinear relationship between demand and delays when airports operate close to capacity. It also shows that, for a given daily number of flights, the more evenly they are distributed in a day, the lower the resulting delays are likely to be. Thesis Supervisor: Amedeo R. Odoni Title: Professor of Aeronautics and Astronautics and of Civil and Environmental Engineering
Too Fast for Their Own Good: Analyzing a Decade of Student Exercise Responses to Explore the Impact of Math Solving Photo Apps

The introduction of math solving photo apps in late 2014 presented students with a tempting new way to solve math problems quickly and accurately. Despite widespread acknowledgement that students increasingly use these apps to complete their coursework, as well as growing concerns about cheating as more students learn online, the prevalence and impact of this technology remains largely unexplored. This study uses a large dataset consisting of 700 unique math exercises and over 82 million student submissions to investigate changes in exercise answering speeds during the last decade. Through a series of exploratory analyses, we identify dramatic shifts in exercise submission speed distributions in recent years, with increasing numbers of rapid responses suggesting growing student reliance on math solving photo technology to answer math problems on homework and exams. Our analyses also reveal that decreases in exercise answering speeds have occurred contemporaneously with the introduction and proliferation of math solving photo apps in education and we further substantiate the role of these tools by verifying that exercise susceptibility to math solving photo apps is associated with decreases in submission speeds. We discuss potential applications of our findings to improve math assessment design and support students in adopting better learning strategies.
Needs Analysis and Prototype Evaluation of Student-facing LA Dashboard for Virtual Reality Content Creation

Being a promising constructionist pedagogy in recent years, maker education empowers students to take agency of their learning process through constructing both knowledge and real-world physical or digital products and fosters peer interactions for collective innovation. Learning Analytics (LA) excels at generating personalized, fine-grained feedback in near real-time and holds much potential in supporting process-oriented and peer-supported learning activities, including maker activities. In the context of virtual reality (VR) content creation for cultural heritage education, this study qualitatively solicited 27 students’ needs on progress monitoring, reflection, and feedback during their making process. Findings have inspired the prototype design of a student-facing LA dashboard (LAVR). Leveraging multimodal learning analytics (MmLA) such as text and audio analytics to fulfill students’ needs, the prototype has various features and functions including automatic task reminders, content quality detection, and real-time feedback on quality of audio-visual elements. A preliminary evaluation of the prototype with 10 students confirms its potential in supporting students’ self-regulated learning during the making process and for improving the quality of VR content. Implications on LA design for supporting maker education are discussed. Future work is planned to include implementation and evaluation of the dashboard in classrooms.
A Review of Learning Analytics Dashboard Research in Higher Education: Implications for Justice, Equity, Diversity, and Inclusion

Learning analytics dashboards (LADs) are becoming more prevalent in higher education to help students, faculty, and staff make data-informed decisions. Despite extensive research on the design and implementation of LADs, few studies have investigated their relation to justice, equity, diversity, and inclusion (JEDI). Excluding these issues in LAD research limits the potential benefits of LADs generally and risks reinforcing long-standing inequities in education. We conducted a critical literature review, identifying 45 relevant papers to answer three research questions: how is LAD research improving JEDI, ii. how might it maintain or exacerbate inequitable outcomes, and iii. what opportunities exist in this space to improve JEDI in higher education. Using thematic analysis, we identified four common themes: (1) participant identities and researcher positionality, (2) surveillance concerns, (3) implicit pedagogies, and (4) software development resources. While we found very few studies directly addressing or mentioning JEDI concepts, we used these themes to explore ways researchers could consider JEDI in their studies. Our investigation highlights several opportunities to intentionally incorporate JEDI into LAD research by sharing software resources and conducting cross-border collaborations, better incorporating user needs, and centering considerations of justice in LAD efforts to improve historical inequities.
The Question-driven Dashboard: How Can We Design Analytics Interfaces Aligned to Teachers’ Inquiry?

One of the ultimate goals of several learning analytics (LA) initiatives is to close the loop and support students’ and teachers’ reflective practices. Although there has been a proliferation of end-user interfaces (often in the form of dashboards), various limitations have already been identified in the literature such as key stakeholders not being involved in their design, little or no account for sense-making needs, and unclear effects on teaching and learning. There has been a recent call for human-centred design practices to create LA interfaces in close collaboration with educational stakeholders to consider the learning design, and their authentic needs and pedagogical intentions. This paper addresses the call by proposing a question-driven LA design approach to ensure that end-user LA interfaces explicitly address teachers’ questions. We illustrate the approach in the context of synchronous online activities, orchestrated by pairs of teachers using audio-visual and text-based tools (namely Zoom and Google Docs). This study led to the design and deployment of an open-source monitoring tool to be used in real-time by teachers when students work collaboratively in breakout rooms, and across learning spaces.
Energy-efficient and Reliable Inference in Nonvolatile Memory under Extreme Operating Conditions

Beyond-edge devices can operate outside the reach of the power grid and without batteries. Such devices can be deployed in large numbers in regions that are difficult to access. Using machine learning, these devices can solve complex problems and relay valuable information back to a host. Many such devices deployed in low Earth orbit can even be used as nanosatellites. Due to the harsh and unpredictable nature of the environment, these devices must be highly energy-efficient, be capable of operating intermittently over a wide temperature range, and be tolerant of radiation. Here, we propose a non-volatile processing-in-memory architecture that is extremely energy-efficient, supports minimal overhead checkpointing for intermittent computing, can operate in a wide range of temperatures, and has a natural resilience to radiation.
Knowledge Construction and Uncertainty in Real World Argumentation: A Text Analysis Approach

Collaborative argumentation is key to promoting understanding of scientific issues. However, classroom structures may not always prepare students to engage in argumentation. To address this challenge, education researchers have examined the importance of social knowledge construction and managing uncertainty in group understanding. In this study, we explore these processes using data from /r/ChangeMyView, an online forum on Reddit where users present their opinions, engage others in critiquing ideas, and acknowledge when the discussion has modified their opinions. This unfacilitated environment can illuminate how argumentation evolves naturally towards refined opinions. We employ automated text analyses (LIWC) and discourse analyses to understand the features and discourse sequences of successful arguments. We find that argumentative threads are more likely to be successful if they focus on idea articulation, coherence, and semantic diversity. Findings highlight the role of uncertainty: threads with more certainty words are less likely to be successful. Furthermore, successful arguments are characterized by cycles of raising, managing, and reducing uncertainty, with more occurrences of evidence and idea incorporation. We discuss how learning environments can create norms for idea construction, coherence, and uncertainty, and the potential to provide adaptive prompts to maintain and reduce uncertainty when unproductive argumentative sequences are detected.
Charting Design Needs and Strategic Approaches for Academic Analytics Systems through Co-Design

Academic analytics focuses on collecting, analysing and visualising educational data to generate institutional insights and improve decision-making for academic purposes. However, challenges that arise from navigating a complex organisational structure when introducing analytics systems have called for the need to engage key stakeholders widely to cultivate a shared vision and ensure that implemented systems create desired value. This paper presents a study that takes co-design steps to identify design needs and strategic approaches for the adoption of academic analytics, which serves the purpose of enhancing the measurement of educational quality utilising institutional data. Through semi-structured interviews with 54 educational stakeholders at a large research university, we identified particular interest in measuring student engagement and the performance of courses and programmes. Based on the observed perceptions and concerns regarding data use to measure or evaluate these areas, implications for adoption strategy of academic analytics, such as leadership involvement, communication, and training, are discussed.
Entanglement entropy in (2 + 1)-dimensional interacting theory: A dimensional reduction approach

A formidable perspective in understanding collective quantum phenomena of a given many-body system is through its entanglement contents. Yet apart from well-established knowledge for free theories, so far much less is known about entanglement structure of interacting particles, especially for the cases beyond (1 + 1) dimension. Here, we develop an efficient scheme to study the entanglement entropy for (2+1)-dimensional quantum field theories, which is able to go beyond the non-interacting or conformal settings. Within this framework, we exactly derive the area-law entanglement entropy for (2 + 1)-dimensional free scalar field and Dirac field, which are consistent with the expectations from existing studies. As a concrete example of interacting theory, we investigate the entanglement entropy of (2 + 1)-dimensional Dirac fermion under a random magnetic field, which cannot be straightforwardly solved via previous approaches. We analytically prove the area-law entanglement entropy remains, with a minor modification of the area-law coefficient by disorder. Our analytical solution is further validated by the corresponding lattice simulation. Moreover, our scheme opens a window to derive the universal sub-leading terms in the entanglement entropy, which is connected to the dynamics of the renormalization group flows of the underlying theories. Therefore, this methodology advance not only offers a tool to exploring the correlations and quantum criticality, but also achieves a deepened understanding of the entanglement structure of quantum many-body systems.
Jupiter's inhomogeneous envelope

While Jupiter's massive gas envelope consists mainly of hydrogen and helium, the key to understanding Jupiter's formation and evolution lies in the distribution of the remaining (heavy) elements. Before the Juno mission, the lack of high-precision gravity harmonics precluded the use of statistical analyses in a robust determination of the heavy-elements distribution in Jupiter's envelope. In this paper, we assemble the most comprehensive and diverse collection of Jupiter interior models to date and use it to study the distribution of heavy elements in the planet's envelope. We apply a Bayesian statistical approach to our interior model calculations, reproducing the Juno gravitational and atmospheric measurements and constraints from the deep zonal flows. Our results show that the gravity constraints lead to a deep entropy of Jupiter corresponding to a 1 bar temperature 5-15 K higher than traditionally assumed. We also find that uncertainties in the equation of state are crucial when determining the amount of heavy elements in Jupiter's interior. Our models put an upper limit to the inner compact core of Jupiter of 7 Earth masses, independently on the structure model (with or without dilute core) and the equation of state considered. Furthermore, we robustly demonstrate that Jupiter's envelope is inhomogenous, with a heavy-element enrichment in the interior relative to the outer envelope. This implies that heavy element enrichment continued through the gas accretion phase, with important implications for the formation of giant planets in our solar system and beyond.