Miracle-dz/UniFAR-FTUs huggingface dataset:
Efimov effect for two particles on a semi-infinite line

The Efimov effect (in a broad sense) refers to the onset of a geometric sequence of many-body bound states as a consequence of the breakdown of continuous scale invariance to discrete scale invariance. While originally discovered in three-body problems in three dimensions, the Efimov effect has now been known to appear in a wide spectrum of many-body problems in various dimensions. Here, we introduce a simple, exactly solvable toy model of two identical bosons in one dimension that exhibits the Efimov effect. We consider the situation where the bosons reside on a semi-infinite line and interact with each other through a pairwise δ-function potential with a particular position-dependent coupling strength that makes the system scale invariant. We show that, for sufficiently attractive interaction, the bosons are bound together, and a new energy scale emerges. This energy scale breaks continuous scale invariance to discrete scale invariance and leads to the onset of a geometric sequence of two-body bound states. We also study the two-body scattering off the boundary and derive the exact reflection amplitude that exhibits discrete scale invariance.
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair Extraction

Emotion-cause pair extraction (ECPE) is an emerging task in emotion cause analysis, which extracts potential emotion-cause pairs from an emotional document. Most recent studies use end-to-end methods to tackle the ECPE task. However, these methods either suffer from a label sparsity problem or fail to model complicated relations between emotions and causes. Furthermore, they all do not consider explicit semantic information of clauses. To this end, we transform the ECPE task into a document-level machine reading comprehension (MRC) task and propose a Multi-turn MRC framework with Rethink mechanism (MM-R). Our framework can model complicated relations between emotions and causes while avoiding generating the pairing matrix (the leading cause of the label sparsity problem). Besides, the multi-turn structure can fuse explicit semantic information flow between emotions and causes. Extensive experiments on the benchmark emotion cause corpus demonstrate the effectiveness of our proposed framework, which outperforms existing state-of-the-art methods.
Multi-Pose Fusion for Sparse-View CT Reconstruction Using Consensus Equilibrium

CT imaging works by reconstructing an object of interest from a collection of projections. Traditional methods such as filtered-back projection (FBP) work on projection images acquired around a fixed rotation axis. However, for some CT problems, it is desirable to perform a joint reconstruction from projection data acquired from multiple rotation axes. In this paper, we present Multi-Pose Fusion, a novel algorithm that performs a joint tomographic reconstruction from CT scans acquired from multiple poses of a single object, where each pose has a distinct rotation axis. Our approach uses multi-agent consensus equilibrium (MACE), an extension of plug-and-play, as a framework for integrating projection data from different poses. We apply our method on simulated data and demonstrate that Multi-Pose Fusion can achieve a better reconstruction result than single pose reconstruction.
Hub-aware Random Walk Graph Embedding Methods for Classification

In the last two decades we are witnessing a huge increase of valuable big data structured in the form of graphs or networks. To apply traditional machine learning and data analytic techniques to such data it is necessary to transform graphs into vector-based representations that preserve the most essential structural properties of graphs. For this purpose, a large number of graph embedding methods have been proposed in the literature. Most of them produce general-purpose embeddings suitable for a variety of applications such as node clustering, node classification, graph visualisation and link prediction. In this paper, we propose two novel graph embedding algorithms based on random walks that are specifically designed for the node classification problem. Random walk sampling strategies of the proposed algorithms have been designed to pay special attention to hubs -- high-degree nodes that have the most critical role for the overall connectedness in large-scale graphs. The proposed methods are experimentally evaluated by analyzing the classification performance of three classification algorithms trained on embeddings of real-world networks. The obtained results indicate that our methods considerably improve the predictive power of examined classifiers compared to currently the most popular random walk method for generating general-purpose graph embeddings (node2vec).
Dissociative Recombination of H3O+, HD2O+, and D3O+

We present an experimental study of the dissociative recombination (DR) of H3O+ and its isotopomers D3O+ and HD2O+ performed at the ASTRID storage ring. DR cross sections have been measured as a function of energy, while complete branching ratios have been measured at E = 0. The H3O+ data yield an accurate determination of the branching ratio for water formation (0.25 ± 0.01). The three molecular ions—H3O+, D3O+, and HD2O+—show a marked resemblance concerning cross sections and branching ratios. The only observed isotope effect is in the fragmentation pattern of HD2O+, where the release of a light fragment is favored over release of a heavier fragment. As a consequence, an enhanced production of deuterated molecules takes place as a result of the DR process.
Evaluation of low-cost MEMS accelerometers for measurements of velocity of unmanned vehicles

Aim of the paper is to assess uncertainty associated with determination of velocity using MEMS accelerometer. Two MEMS accelerometers are evaluated from the point of view of measurement characterized by short duration and possibility of repetitions in unchanged environment. Mathematical model of measurement of velocity is presented with its accompanying uncertainty. The accelerometers were first subjected to calibration and testing of nonlinearity of their scale factors, then fixed to a wheeled robot which performed repeated manoeuvres of straight line movement on laboratory ground. Standard uncertainty of velocity measured using the examined accelerometers was at the level of 0.02–0.04 m/s for run duration of about 1.5 s and averaged data from 12 runs. MEMS accelerometers can be recommended for velocity measurements characterised by short duration and possibility of repetitions, if uncertainties of calibration and of measurement of vehicle tilt angle during motion are
Gauge theories, Simple Groups and Integrable Systems

In this review we discuss interrelations between classical Hitchin integrable systems, monodromy preserving equations and topological field theories coming from N=4 supersymmetric Yang-Mills theories developed by Gukov, Kapustin and Witten. In particular, we define systems related to bundles with nontrivial characteristic classes and discuss relations of the characteristic classes with monopole configurations in the Yang-Mills theory.
A finite element analysis for a thermal convection problem with the infinite Prandtl number

A finite element analysis for a thermal convection problem with the infinite Prandtl number is discussed. This problem is observed, for example, in the earth's mantle convection and in some industrial plants such as glass melting furnaces, where the Prandtl number is set to be infinite as a limit of high Prandtl numbers. A finite element scheme for the thermal convection problem with the infinite Prandtl number is presented. Error estimates of the finite element solution are established. Sample numerical simulation results are shown, which agree well with the theoretical ones.
Periodic paralysis due to cumulative effects of rare variants in SCN4A with small functional alterations

Mutations in the SCN4A gene encoding a voltage‐gated sodium channel (Nav1.4) cause hyperkalemic periodic paralysis (HyperPP) and hypokalemic periodic paralysis (HypoPP). Typically, both HyperPP and HypoPP are considered as monogenic disorders caused by a missense mutation with a large functional effect. However, a few cases with atypical periodic paralysis phenotype have been caused by multiple mutations in ion‐channel genes expressed in skeletal muscles. In this study we investigated the underlying pathogenic mechanisms in such cases.
An empirical Bayes approach to improving population‐specific genetic association estimation by leveraging cross‐population data

Populations of non‐European ancestry are substantially underrepresented in genome‐wide association studies (GWAS). As genetic effects can differ between ancestries due to possibly different causal variants or linkage disequilibrium patterns, a meta‐analysis that includes GWAS of all populations yields biased estimation in each of the populations and the bias disproportionately impacts non‐European ancestry populations. This is because meta‐analysis combines study‐specific estimates with inverse variance as the weights, which causes biases towards studies with the largest sample size, typical of the European ancestry population. In this paper, we propose two empirical Bayes (EB) estimators to borrow the strength of information across populations although accounting for between‐population heterogeneity. Extensive simulation studies show that the proposed EB estimators are largely unbiased and improve efficiency compared to the population‐specific estimator. In contrast, even though the meta‐analysis estimator has a much smaller variance, it yields significant bias when the genetic effect is heterogeneous across populations. We apply the proposed EB estimators to a large‐scale trans‐ancestry GWAS of stroke and demonstrate that the EB estimators reduce the variance of the population‐specific estimator substantially, with the effect estimates close to the population‐specific estimates.
Relationship quality and psychophysiological distress for underserved breast cancer patients and their caregiver before treatment

Breast cancer patients and caregivers experience biobehavioral reactivity (e.g., depression, anxiety, pain, fatigue) during breast cancer treatment which predicts cancer recurrence and mortality. High quality patient‐caregiver relationships can mitigate this distress during treatment, but this association is unclear pre‐treatment. Identifying early interventions that target high risk Appalachian patients could impact biobehavioral reactivity.
FORMULAS FOR COMPUTING ATMOSPHERIC REFRACTION FOR OBJECTS INSIDE OR OUTSIDE THE ATMOSPHERE

Abstract : This report presents the derivation of new equations for determining the changes in the direction of a ray of light as it passes through the atmosphere from an object to the observer. The equations are applicable to objects inside or outside the atmosphere. Equations are also de rived for obtaining the topocentric distance of the object as a function of the object's height and the observed zenith distance.
Response Surface Methodology and Related Topics

Two-Level Factorial and Fractional Factorial Designs in Blocks of Size Two. Part 2 (Y J Yang & N R Draper) Response Surface Experiments on Processes with High Variation (S G Gilmour & L A Trinca) Random Run Order, Randomization and Inadvertent Split-Plots in Response Surface Experiments (J Ganju & J M Lucas) Statistical Inference for Response Surface Optima (D K J Lin & J J Peterson) A Search Method for the Exploration of New Regions in Robust Parameter Design (G Mero-Quesada & E del Castillo) Response Surface Approaches to Robust Parameter Design (T J Robinson & S S Wulff) Response Surface Methods and Their Application in the Treatment of Cancer with Drug Combinations: Some Reflections (K S Dawson et al.) Generalized Linear Models and Response Transformation (A C Atkinson) GLM Designs: The Dependence on Unknown Parameters Dilemma (A I Khuri & S Mukhopadhyay) Design for a Trinomial Response to Dose (S K Fan & K Chaloner) Evaluating the Performance of Non-Standard Designs: The San Cristobal Design (L M Haines) 50 Years of Mixture Experiment Research: 1955-2004 (G F Piepel) Graphical Methods for Comparing Response Surface Designs for Experiments with Mixture Components (H B Goldfarb & D C Montgomery) Graphical Methods for Assessing the Prediction Capability of Response Surface Designs (J J Borkowski) Using Fraction of Design Space Plots for Informative Comparisons between Designs (C M Anderson-Cook & A Ozol-Godfrey) Concepts of Slope-Rotatability for Second Order Response Surface Designs (S H Park) Design of Experiments for Estimating Differences between Responses and Slopes of the Response (S Huda).
Let’s get virtual! Reinventing a science festival during a pandemic: limitations and insights

ABSTRACT Non-formal, yet educative, activities such as science festivals can positively influence the public regarding their attitude towards Science, Technology, Engineering and Math (STEM) subjects and students’ willingness to pursue STEM-related careers. We evaluate the changes made to adapt the Oxford Brookes Science Bazaar, a science festival that has been delivered face-to-face since 2008, to a virtual format in 2021 due to the COVID-19 pandemic. The online festival included 28 pre-recorded and 12 live activities of different types (hands-on, demonstration, games, lectures, podcasts, virtual tours). Hands-on activities and virtual tours had the highest number of unique viewers, while lectures and podcasts were the least watched. The videos were watched also after the advertised date of the festival and reached a broader audience than the physical events. The number of participants, the holding time, and the proportion of people who filled the feedback forms, however, were lower in the online than the physical events. STEM organisations should consider hybrid events, with both virtual and in-person contents, to reach a broader audience and to create more inclusive events. We provide recommendations on how to maximise the benefit of virtual formats, including expanding blended virtual activities to reach a wider variety of age groups.
Maximizing a Submodular Function with Bounded Curvature Under an Unknown Knapsack Constraint

This paper studies the problem of maximizing a monotone submodular function under an unknown knapsack constraint. A solution to this problem is a policy that decides which item to pack next based on the past packing history. The robustness factor of a policy is the worst case ratio of the solution obtained by following the policy and an optimal solution that knows the knapsack capacity. We develop an algorithm with a robustness factor that is decreasing in the curvature $B$ of the submodular function. For the extreme cases $c=0$ corresponding to a modular objective, it matches a previously known and best possible robustness factor of $1/2$. For the other extreme case of $c=1$ it yields a robustness factor of $\approx 0.35$ improving over the best previously known robustness factor of $\approx 0.06$.
Integrality Gap of Time-Indexed Linear Programming Relaxation for Coflow Scheduling

Coflow is a set of related parallel data flows in a network. The goal of the coflow scheduling is to process all the demands of the given coflows while minimizing the weighted completion time. It is known that the coflow scheduling problem admits several polynomial-time 5-approximation algorithms that compute solutions by rounding linear programming (LP) relaxations of the problem. In this paper, we investigate the time-indexed LP relaxation for coflow scheduling. We show that the integrality gap of the time-indexed LP relaxation is at most 4. We also show that yet another polynomial-time 5-approximation algorithm can be obtained by rounding the solutions to the time-indexed LP relaxation.
Electromyography-based fatigue assessment of an upper body exoskeleton during automotive assembly

Abstract The purpose of this study was to assess an upper body exoskeleton during automotive assembly processes that involve elevated arm postures. Sixteen team members at Toyota Motor Manufacturing Canada were fitted with a Levitate Airframe, and each team member performed between one and three processes with and without the exoskeleton. A total of 16 assembly processes were studied. Electromyography (EMG) data were collected on the anterior deltoid, biceps brachii, upper trapezius, and erector spinae. Team members also completed a usability survey. The exoskeleton significantly reduced anterior deltoid mean active EMG amplitude (p = .01, Δ = −3.2 %MVC, d = 0.56 medium effect) and fatigue risk value (p < .01, Δ = −5.1 %MVC, d = 0.62 medium effect) across the assembly processes, with no significant changes for the other muscles tested. A subset of nine assembly processes with a greater amount of time spent in arm elevations at or above 90° (30 vs. 24%) and at or above 135° (18 vs. 9%) appeared to benefit more from exoskeleton usage. For these processes, the exoskeleton significantly reduced anterior deltoid mean active EMG amplitude (p < .01, Δ = −5.1 %MVC, d = 0.95 large effect) and fatigue risk value (p < .01, Δ = −7.4 %MVC, d = 0.96 large effect). Team members responded positively about comfort and fatigue benefits, although there were concerns about the exoskeleton hindering certain job duties. The results support quantitative testing to match exoskeleton usage with specific job tasks and surveying team members for perceived benefits/drawbacks.
Does Diversity of Social Ties Really Matter More for Health and Leisure Activity than Number of Social Ties? Evidence from Later Adulthood

Objectives Claims that the diversity of social ties matters more for health than the sheer number of ties have largely gone untested. This study accordingly compared the unique associations of number versus diversity of social ties with key health-related outcomes: functional limitations and leisure activities. Additionally, positive and ambivalent ties were distinguished. Methods Social networks, health, and leisure activities were assessed in a national sample of older adults (N = 874; ages 65–91). Results Regression analyses revealed that number of ties related to each outcome at a magnitude comparable to, or exceeding, that of diversity in most models. For positive ties, number related more strongly than diversity to greater leisure activities. For ambivalent ties, number related more strongly than diversity to worse functional limitations. Discussion Contrary to prevailing views, diversity of ties is not necessarily more important than number of ties. Findings extend scientific understanding and approaches to interventions.
How an idiosyncratic (zero-beta) risk can greatly increase the firm’s cost of capital

The celebrated capital asset pricing model (‘CAPM’) brought numerous appealing insights and spawned a new theory of capital budgeting. One key intuition is that there is ‘no penalty for diversifiable risk’ – that is, any risky payoff that has zero-correlation with the wider economy, and hence zero-beta, is treated as ‘risk-free’. Does that mean that managers can bet the firm on a spin of the roulette wheel without attracting a higher CAPM discount rate? Our re-interpretation of CAPM reveals that potential financial losses which are conventionally regarded as firm-specific ‘unpriced’ risks can bring a large increase in the firm’s beta and CAPM cost of capital, despite having zero-beta and making only negligible difference at the aggregate market level. This mathematical result clashes with textbook expositions but is easily demonstrated and can be traced to authoritative but overlooked parts of the theoretical CAPM literature. JEL Classification: G11, G12
Damage detection of cables in cable-stayed bridges using vibration data measured from climbing robot

This paper presents a method for damage detection of bridge cables using the vibration signal coming from the sensor installed in the climbing robot. In this paper, the damage types are crack and local reduction in diameter. The climbing robot consisting of a body and three wheels connected to the body by three springs. The cable is considered as an axially loaded Euler beam. When there is no crack, the dynamic displacement of the robot is smooth and no distortion at the crack position can be inspected. However, when there is a damage in the cable, there is a distortion in the robot displacement at the damage location but this distortion is small and difficult to be observed visually. The distortion caused by the crack is presented as the significant peaks in the wavelet transform of the robot displacement. The proposed method is promising since it is efficient to detect cracks with depth as small as 1% of the cable diameter and to detect local changes in diameter with amplitude as small as 0.1%.
One of the active ingredients in Paeoniae Radix Alba functions as JAK1 inhibitor in rheumatoid arthritis

Objective: We aimed to explore and verify the mechanism underlying the action of the active ingredients of Paeoniae Radix Alba (PRA) in the treatment of rheumatoid arthritis (RA). Methods: The protein targets of PRA’s six active ingredients and RA were identified. Then, the intersection of the two groups was studied. The drug–target network was constructed, visualized, and analyzed by Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were performed to analyze these genes. Furthermore, we validated our predictions of the potential targets through a docking study. Finally, the anti-inflammatory effect of Palbinone (PB), one of the active ingredients of PRA, was tested by conducting in vitro and in vivo studies. Results: Six active ingredients of PRA were identified, and 103 overlapping genes were discovered. Functional enrichment analysis indicated that the genes are mostly enriched in IL-17 signaling pathway, Th17 cell differentiation, and the FoxO, ErbB, and TNF signaling pathways. 10 hub genes and two gene cluster modules were identified by Cytoscape. Molecular docking analysis proved that PB was able to bind to the ATP binding site of Janus kinase (JAK)1, thereby acting as a potential inhibitor of JAK1. In vitro and in vivo studies demonstrated that PB exerts its anti-inflammatory role via the inhibition of JAK1. Conclusion: We constructed a multitarget pharmacological network of PRA in RA treatment. PB, one of the active compounds of PRA, was demonstrated to be a promising inhibitor of JAK1.
Can the systemic inflammation score be used to predict prognosis in gastric cancer patients undergoing surgery? A systematic review and meta-analysis

Background Inflammatory markers are being increasingly used to predict the prognosis of cancer patients. We hereby conducted the first meta-analysis assessing the association between systemic inflammation score (SIS) and prognosis of gastric cancer patients undergoing surgical intervention. Methods A literature search was carried out on PubMed, CENTRAL, Scopus, and Embase up to 3rd June 2022 for relevant studies. Adjusted data reported as hazard ratios (HR) was combined in a random-effects model. Results A total of seven studies with 5,338 patients could be included. All studies were from either China or Japan and published in the last four years. Meta-analysis showed that higher SIS scores (1 or 2) were significant predictors of poor overall survival (OS) in gastric cancer patients (HR: 1.25 95% CI: 1.05, 1.49, I2 = 11%). Similarly, the meta-analysis demonstrated that an SIS score of 2 was associated with poor OS as compared to scores of 0/1 (HR: 2.53 95% CI: 1.30, 4.89, I2 = 45%). Data on disease-free survival (DFS) was scarce to draw conclusions. Conclusion The SIS score can be a simple and useful tool to predict OS in gastric cancer patients undergoing surgery. Data on DFS is scarce and conflicting. Future studies should report using standard reference groups and provide data on DFS to enhance current evidence. Systematic Review Registration: https://www.crd. york.ac. uk/prospero/#searchadvanced, identifier: CRD42022335548.