Miracle-dz/UniFAR-FTUs huggingface dataset:
Asymptotic and measured large frequency separations

Context. With the space-borne missions CoRoT and Kepler, a large amount of asteroseismic data is now available and has led to a variety of work. So-called global oscillation parameters are inferred to characterize the large sets of stars, perform ensemble asteroseismology, and derive scaling relations. The mean large separation is such a key parameter, easily deduced from the radial-frequency differences in the observed oscillation spectrum and closely related to the mean stellar density. It is therefore crucial to measure it with the highest accuracy in order to obtain the most precise asteroseismic indices. Aims. As the conditions of measurement of the large separation do not coincide with its theoretical definition, we revisit the asymptotic expressions used for analyzing the observed oscillation spectra. Then, we examine the consequence of the difference between the observed and asymptotic values of the mean large separation. Methods. The analysis is focused on radial modes. We use series of radial-mode frequencies in published analyses of stars with solarlike oscillations to compare the asymptotic and observational values of the large separation. This comparison relies on the proper use of the second-order asymptotic expansion. Results. We propose a simple formulation to correct the observed value of the large separation and then derive its asymptotic counterpart. The measurement of the curvature of the radial ridges in the echelle diagram provides the correcting factor. We prove that, apart from glitches due to stellar structure discontinuities, the asymptotic expansion is valid from main-sequence stars to red giants. Our model shows that the asymptotic offset is close to 1/4, as in the theoretical development, for low-mass, main-sequence stars, subgiants and red giants. Conclusions. High-quality solar-like oscillation spectra derived from precise photometric measurements are definitely better described with the second-order asymptotic expansion. The second-order term is responsible for the curvature observed in the echelle diagrams used for analyzing the oscillation spectra, and this curvature is responsible for the difference between the observed and asymptotic values of the large separation. Taking it into account yields a revision of the scaling relations, which provides more accurate asteroseismic estimates of the stellar mass and radius. After correction of the bias (6% for the stellar radius and 3% for the mass), the performance of the calibrated relation is about 4% and 8% for estimating, respectively, the stellar radius and the stellar mass for masses less than 1.3 M� ; the accuracy is twice as bad for higher mass stars and red giants.
A highly adaptive magnetorheological fluid robotic leg for efficient terrestrial locomotion

To survive in nature, animals adjust the characteristics of their legs or fins to adapt the motion to their environment. Inspired by the locomotion of animals, a study on the tunable stiffness and damping of a leg will help in the development of intelligent locomotion robots. In this paper we report on the development and experiment of a novel and simple robotic leg that can be adapted to the environment via a smart magnetorheological fluid (MRF). The robotic leg consists of a rotation MRF damper, a torsional spring, a ‘foot’ and a ‘leg’. The curved part of the ‘foot’ makes contact with the grounds while the other end is linked to an outer cylinder of the MRF damper with an inelastic cable. The variable force arm rising from the MRF damper and the torsional spring can help the leg adapt to a changing environment. The characteristics of the MRF damper have been investigated and a model is built to describe its mechanical features when different currents are applied to the MRF damper. A test on a linear dynamic test instrument has been conducted to verify the accuracy of the model. The robotic leg is installed in a locomotion platform to investigate the speed of its locomotion and the cost of the transport; the result demonstrated the feasibility and adaptability of the leg when walking on hard terrain. Its simple structure, high adaptability, and easy control of the MRF leg helped in the design and development of a high performance field robot that can adapt to various environments.
QCM DETECTION OF GPCR-LIGAND BINDING USING CELL-DERIVED LIPOSOMES

We developed a novel technique to produce cell-derived liposomes which have specific GPCRs (G protein-coupled receptors), and applied those liposomes to a QCM (quartz crystal microbalance) sensor for detecting interactions between GPCRs and their ligands. First, liposomes having bradykinin B2 receptors (BB2Rs, GPCRs for bradykinin) were derived directly from cell membranes by chemical stimulation of human lymphocyte cells which have BB2Rs expressed on their membranes by gene transfection. Next, the liposomes were immobilized on the surface of a QCM sensor chip using cell-anchoring molecules. Finally, the significant reduction of the resonance frequency of the sensor was obtained in response to a bradykinin solution of 1 mg/ml.
Current challenges of ageing and ageism with a focus on healthcare and long-term care

243) [4]. Several scholars entered the debate. Indeed, Iversen and colleagues [5] presented the core aspects of ageism namely: “Ageism is defined as negative or positive stereotypes, prejudice and/or discrimination against (or to the advantage of) elderly people on the basis of their chronological age or on the basis of a perception of them as being ‘old’ or ‘elderly’. Ageism can be implicit or explicit and can be expressed on a micro-, mesoor macro-level” (p. 4). The key dimensions defined by Iverson and colleagues are the three classical components (cognitive-stereotypes, affective-prejudice, behavioraldiscrimination); the positive/negative aspect (positive ageism, negative ageism), the conscious/unconscious aspect (explicit ageism, implicit ageism); and the levels at which ageism can manifest (microlevel ageism, meso-level ageism, macro-level ageism). More recently, Levy and Macdonald [6] urged for a deeper understanding of ageism by moving beyond the negative aspect and including the positive aspect that would lead to better understanding of how to improve the lives of older persons and improve cross-age relations.
Evolutionary history of Phakopsora pachyrhizi (the Asian soybean rust) in Brazil based on nucleotide sequences of the internal transcribed spacer region of the nuclear ribosomal DNA

Phakopsora pachyrhizi has dispersed globally and brought severe economic losses to soybean growers. The fungus has been established in Brazil since 2002 and is found nationwide. To gather information on the temporal and spatial patterns of genetic variation in P. pachyrhizi, we sequenced the nuclear internal transcribed spacer regions (ITS1 and ITS2). Total genomic DNA was extracted using either lyophilized urediniospores or lesions removed from infected leaves sampled from 26 soybean fields in Brazil and one field in South Africa. Cloning prior to sequencing was necessary because direct sequencing of PCR amplicons gave partially unreadable electrophoretograms with peak displacements suggestive of multiple sequences with length polymorphism. Sequences were determined from four clones per field. ITS sequences from African or Asian isolates available from the GenBank were included in the analyses. Independent sequence alignments of the ITS1 and ITS2 datasets identified 27 and 19 ribotypes, respectively. Molecular phylogeographic analyses revealed that ribotypes of widespread distribution in Brazil displayed characteristics of ancestrality and were shared with Africa and Asia, while ribotypes of rare occurrence in Brazil were indigenous. The results suggest P. pachyrhizi found in Brazil as originating from multiple, independent long-distance dispersal events.
A Network-Theoretic Analysis of Hospital Admission, Transfer, and Discharge Data

Comprehending complex behavior of flow within a graph is of interest to clinicians and mathematicians alike. In this study we examine admission, discharge, and transfer data of patients within a hospital system, and process the importance of nodes through several graph metrics. One common metric, which measures population densities through a continuous time Markov process, will be compared against centrality measures, a technique more often used in social media studies. Our findings show that centrality measures capture behavior related to the topology of the network that may be missed by Markov processes. This suggests that, for determining the allocation of resources between departments of a hospital, centrality measures in some cases may prove more suitable for interpreting patient flow data. Departmental rankings and suitable instances for the application for each graph metric are provided.
Scratching Beneath the Surface: A Model to Predict the Vertical Distribution of Prochlorococcus Using Remote Sensing

The unicellular cyanobacterium Prochlorococcus is the most dominant resident of the subtropical gyres, which are considered to be the largest biomes on earth. In this study, the spatial and temporal variability in the global distribution of Prochlorococcus was estimated in the Atlantic Ocean using an empirical model based on data from 13 Atlantic Meridional Transect cruises. Our model uses satellite-derived sea surface temperature (SST), remote-sensing reflectance at 443 and 488 nm, and the water temperature at a depth of 200 m from Argo data. The model divides the population of Prochlorococcus into two groups: ProI, which dominates under high-light conditions associated with the surface, and ProII, which favors low light found near the deep chlorophyll maximum. ProI and ProII are then summed to provide vertical profiles of the concentration of Prochlorococcus cells. This model predicts that Prochlorococcus cells contribute 32 Mt of carbon biomass (7.4 × 1026 cells) to the Atlantic Ocean, concentrated mainly within the subtropical gyres (35%) and areas near the Equatorial Convergence Zone (30%). When projected globally, 3.4 × 1027 Prochlorococcus cells represent 171 Mt of carbon biomass, with 43% of this global biomass allocated to the upper ocean (0–45 m depth). Annual cell standing stocks were relatively stable between the years 2003 and 2014, and the contribution of the gyres varies seasonally as gyres expand and contract, tracking changes in light and temperature, with lowest cell abundances during the boreal and austral winter (1.4 × 1013 cells m−2), when surface cell concentrations were highest (9.8 × 104 cells mL−1), whereas the opposite scenario was observed in spring–summer (2 × 1013 cells m−2). This model provides a three-dimensional view of the abundance of Prochlorococcus cells, revealing that Prochlorococcus contributes significantly to total phytoplankton biomass in the Atlantic Ocean, and can be applied using either in situ measurements at the sea surface (r2 = 0.83) or remote-sensing observables (r2 = 0.58).
Conducting cognitive interviews over the phone: Benefits and challenges

Cognitive interviews are commonly used in the survey research world as a question evaluation method to test survey questions before they go into the field. Typically, they are done in-person face-to-face; however, some target populations such as doctors or farmers are very difficult to reach in-person and other interview modes such as telephone interviewing may be more feasible and less costly. To date, little published research has examined the effectiveness of conducting cognitive interviews over the telephone. Many researchers face budget and staff time constraints at the same time that respondents are becoming harder to contact in-person and demand for larger samples has increased. All of these factors contribute to the appeal of conducting cognitive interviews by telephone. This study looked at the benefits and challenges of conducting cognitive interviews over the phone. Eight cognitive interviewers were interviewed about their experiences conducting telephone cognitive interviews. Based on their experience, benefits of phone cognitive interviewing included better access to busy or disadvantaged populations, ability to get more sample variation, and cost and time efficiencies related to less travel and easier scheduling. Challenges included lost nonverbal cues and the need for more probing, more complicated logistics such as incentives, multi-tasking respondents, and more difficulty testing graphics, building rapport, and tracking instrument navigation. Most interviewers felt that in-person interviews were preferable but that if for some reason they could not do them in-person then phone would be better than not doing the interview at all. At the same time, most interviewers felt that the quality of the phone interview data was good enough compared to in-person interview data because they got what they needed for the analysis; however, they acknowledged that it was difficult to compare without a direct comparison within the same project.
Cooking behaviors are related to household particulate matter exposure in children with asthma in the urban East Bay Area of Northern California

Background Asthma is a common childhood disease that leads to many missed days of school and parents’ work. There are multiple environmental contributors to asthma symptoms and understanding the potential factors inside children’s homes is crucial. Methods This is a dual cohort study measuring household particulate matter (PM2.5), behaviors, and factors that influence air quality and asthma symptoms in the urban homes of children (ages 6–10) with asthma; one cohort had cigarette smoke exposure in the home (n = 13) and the other did not (n = 22). Exposure data included measurements every 5 minutes for a month. Results In the entire study population, a large contributor to elevations in indoor PM2.5 above 35 μg/m3 was not using the stove hood when cooking (8.5% higher, CI 3.1–13.9%, p<0.005). Median PM values during cooking times were 0.88 μg/m3 higher than those during non-cooking times (95% CI 0.33–1.42). Mean monthly household PM2.5 level was significantly related to the presence of a cigarette smoker in the home (10.1 μg/m3 higher, 95% CI 5.2–15.1, p<0.001) when controlling for use of the stove hood and proximity to major roadway. There was a trend toward increased odds of persistent asthma with increases in average monthly PM2.5 (OR 1.1, 95% CI 0.97–1.3, p = 0.16). Conclusions Consideration of only outdoor PM2.5 may obscure potentially modifiable risks for asthma symptoms. Specifically, this preliminary study suggests that cooking behaviors may contribute to the burden of PM2.5 in the homes of children with asthma and thus to asthma symptoms.
Efficiently Sampling from Underlying Models

The capability and mobility of exploration robots is increasing rapidly, yet missions will always be constrained by one main resource: time. Time limits the number of samples a robot can collect, sites it can analyze, and the availability of human oversight, so it is imperative the robot is able to make intelligent actions when it comes to choosing when, where, and what to sample, a process known as adaptive sampling. This work advances the state of the art in adaptive sampling for exploration robotics. We take advantage of the fact that rover operations are typically not performed in a vacuum; extensive contextual data is often present, most often in the form of orbital imagery, rover navigation images, and prior instrument measurements. Using this context, we apply Bayesian and nonparametric models to decide where best to sample under a limited budget, using real X-ray lithochemistry data. We find that our methods improve both the diversity of samples collected as well as select samples that are representative of the dataset. We find that model-based approaches made scalable with Dirichlet processes improve sampling results when the underlying number classes and class distribution is unknown. Unlike previous works, our approaches reduce the impact of noise on sampling location, a common problem when selecting samples based on noisy or incomplete contextual data.
Protective effects of ethyl acetate extract of Eclipta prostrata against 6-hydroxydopamine-induced neurotoxicity in SH-SY5Y cells

Oxidative stress plays an important role in the pathogenesis of Parkinson’s disease. The neurotoxin 6-hydroxydopamine initiates cellular oxidative stress which has been implicated in neurodegenerative conditions related to Parkinson’s disease. Eclipta prostrata, also known as false daisy, is a plant belonging to the sunflower family. It is a rich source of phenolic compounds that confer the plant an antioxidant activity. In this study, we investigated the protective effects of ethyl acetate extract of E. prostrata against 6-hydroxydopamine-induced neurotoxicity in SHSY5Y cells. Pretreatment with the ethyl acetate extract of E. prostrata before exposing the cells to 6-hydroxydopamine significantly increased cell survival and reduced intracellular reactive oxygen species formation in a concentrationdependent manner. In addition, the ethyl acetate extract of E. prostrata suppressed the Bax/Bcl-2 ratio and reduced caspase-3 activity, a key modulator of cell apoptosis. Our finding clearly shows that the ethyl acetate extract of E. prostrata possesses a potential antioxidant capacity and attenuates SH-SY5Y cell death by blocking apoptotic signalling caused by 6-hydroxydopamine. E. prostrata could therefore be used as a potential herb to prevent oxidative stress-induced neurodegeneration in Parkinson’s disease.
Forewing pigmentation predicts migration distance in wild-caught migratory monarch butterflies

Surprisingly, little is known about how the environment influences the production of the iconic orange coloration of the monarch butterfly (Danaus plexippus). Previous research under controlled laboratory conditions has shown that the temperature during larval development influences the color of monarch wings, where females raised in warm conditions had a greater proportion of melanization, whereas males raised in warm conditions had a lower proportion of melanization. These melanin-based colors have been found to increase flying ability in Lepidoptera, and recent experiments have found that monarchs with redder forewings flew greater distances than monarchs with less intense coloration. We examined whether wild-caught monarchs captured in the Great Lakes region exhibited geographic polyphenism by using stable isotopes to estimate natal origin, and hence rearing temperature, spectrophotometry to measure forewing coloration, and image analysis to estimate shape. We found that monarchs from the Gulf Coast were more melanized than monarchs from the Great Lakes, and southern male monarchs were more saturated than northern male monarchs. This supports previous research suggesting that colors that absorb more solar energy allow for greater flying ability but contradicts the patterns we expected based on natal temperature. Interestingly, this effect of color on migration distance was independent of wing shape. We provide the first evidence that the coloration of wild monarchs influences their migration ability over a continental scale, and we suggest that these differences in color may benefit the cohort of monarchs destined for long-distance migration to their wintering ground.
CRVI: Convex Relaxation for Variational Inference

We present a new technique for solving nonconvex variational inference optimization problems. Variational inference is a widely used method for posterior approximation in which the inference problem is transformed into an optimization problem. For most models, this optimization is highly non-convex and so hard to solve. In this paper, we introduce a new approach to solving the variational inference optimization based on convex relaxation and semidefinite programming. Our theoretical results guarantee very tight relaxation bounds that get nearer to the global optimal solution than traditional coordinate ascent. We evaluate the performance of our approach on regression and sparse coding.
3D Multi-Sensor Data Fusion for Object Localization in Industrial Applications

This paper describes a data fusion approach for 3D sensors exploiting assets of the signed distance function. The objectoriented model is described as well as the algorithm design. We developed a framework respecting different modalities for multi-sensor fusion, 3D mapping and object localization. This approach is suitable for industrial applications having need for contact-less object localization like bin picking. In experiments we demonstrate 3D mapping as well as sensor fusion of a structured light sensor with a Time-of-Flight (ToF) camera.
A Mobile App for Assisting Users to Make Informed Selections in Security Settings for Protecting Personal Health Data: Development and Feasibility Study

Background On many websites and mobile apps for personal health data collection and management, there are security features and privacy policies available for users. Users sometimes are given an opportunity to make selections in a security setting page; however, it is challenging to make informed selections in these settings for users who do not have much education in information security as they may not precisely know the meaning of certain terms mentioned in the privacy policy or understand the consequences of their selections in the security and privacy settings. Objective The aim of this study was to demonstrate several commonly used security features such as encryption, user authentication, and access control in a mobile app and to determine whether this brief security education is effective in encouraging users to choose stronger security measures to protect their personal health data. Methods A mobile app named SecSim (Security Simulator) was created to demonstrate the consequences of choosing different options in security settings. A group of study participants was recruited to conduct the study. These participants were asked to make selections in the security settings before and after they viewed the consequences of security features. At the end of the study, a brief interview was conducted to determine the reason for their selections in the security settings. Their selections before and after the security education were compared in order to determine the effectiveness of the security education. The usability of the app was also evaluated. Results In total, 66 participants finished the study and provided their answers in the app and during a brief interview. The comparison between the pre- and postsecurity education selection in security settings indicated that 21% (14/66) to 32% (21/66) participants chose a stronger security measure in text encryption, access control, and image encryption; 0% (0/66) to 2% (1/66) participants chose a weaker measure in these 3 security features; and the remainder kept their original selections. Several demographic characteristics such as marital status, years of experience using mobile devices, income, employment, and health status showed an impact on the setting changes. The usability of the app was good. Conclusions The study results indicate that a significant percentage of users (21%-32%) need guidance to make informed selection in security settings. If websites and mobile apps can provide embedded security education for users to understand the consequences of their security feature selection and the meaning of commonly used security features, it may help users to make the best choices in terms of security settings. Our mobile app, SecSim, offers a unique approach for mobile app users to understand commonly used security features. This app may be incorporated into other apps or be used before users make selections in their security settings.