Miracle-dz/UniFAR-FTUs huggingface dataset:
The Tarantula Massive Binary Monitoring

Context. Accurate stellar parameters of individual objects in binary systems are essential to constrain the effects of binarity on stellar evolution. These parameters serve as a prerequisite to probing existing and future theoretical evolutionary models. Aims. We aim to derive the atmospheric parameters of the 31 double-lined spectroscopic binaries in the Tarantula Massive Binary Monitoring sample. This sample, composed of detached, semi-detached and contact systems with at least one of the components classified as an O-type star, is an excellent test-bed to study how binarity can impact our knowledge of the evolution of massive stars. Methods. In the present paper, 32 epochs of FLAMES/GIRAFFE spectra are analysed by using spectral disentangling to construct the individual spectra of 62 components. We then apply the CMFGEN atmosphere code to determine their stellar parameters and their helium, carbon, and nitrogen surface abundances. Results. Among the 31 systems that we study in the present paper, we identify between 48 and 77% of them as detached, likely pre-interacting systems, 16% as semi-detached systems, and between 5 and 35% as systems in or close to contact phase. Based on the properties of their components, we show that the effects of tides on chemical mixing are limited. Components on longer-period orbits show higher nitrogen enrichment at their surface than those on shorter-period orbits, in contrast to expectations of rotational or tidal mixing, implying that other mechanisms play a role in this process. For semi-detached systems, components that fill their Roche lobe are mass donors. They exhibit higher nitrogen content at their surface and rotate more slowly than their companions. By accreting new material, their companions spin faster and are likely rejuvenated. Their locations in the N − v sin i diagram tend to show that binary products are good candidates to populate the two groups of stars (slowly rotating, nitrogen-enriched objects and rapidly rotating non-enriched objects) that cannot be reproduced through single-star population synthesis. Finally, we find no peculiar surface abundances for the components in (over-)contact systems, as has been suggested by evolutionary models for tidal mixing. Conclusions. This sample, consisting of 31 massive binary systems, is the largest sample of binaries composed of at least one O-type star to be studied in such a homogeneous way by applying spectral disentangling and atmosphere modelling. The study of these objects gives us strong observational constraints to test theoretical binary evolutionary tracks.
Visual representations as ‘artefacts of knowing’

How does the manipulation of visual representations play a role in the practices of generating, evolving and exchanging knowledge? The role of visual representation in mediating knowledge work is explored in a study of design work of an architectural practice, Edward Cullinan Architects. The intensity of interactions with visual representations in the everyday activities on design projects is immediately striking. Through a discussion of observed design episodes, two ways are articulated in which visual representations act as ‘artefacts of knowing’. As communication media they are symbolic representations, rich in meaning, through which ideas are articulated, developed and exchanged. Furthermore, as tangible artefacts they constitute material entities with which to interact and thereby develop knowledge. The communicative and interactive properties of visual representations constitute them as central elements of knowledge work. The paper explores emblematic knowledge practices supported by visual representation and concludes by pinpointing avenues for further research. Comment la manipulation de représentations visuelles joue-t-elle un rôle dans les pratiques de production, d'évolution et d'échange du savoir ? Le rôle de la représentation visuelle en tant qu'interface avec le travail intellectuel est analysé dans le cadre d'une étude d'un travail de conception d'un cabinet d'architectes (Edward Cullinan Architects). L'intensité des interactions avec les représentations visuelles dans les activités quotidiennes concernant des projets de conception est frappante. Au travers d'une analyse d'épisodes observés lors du travail de conception, l'auteur analyse deux voies le long desquelles les représentations visuelles agissent comme ‘artéfacts du savoir’. En tant que moyens de communication, ce sont des représentations symboliques, riches de signification, à travers lesquelles des idées sont exprimées, développées et échangées. De plus, en tant qu'artéfacts tangibles, ils constituent des entités matérielles avec lesquelles interagir et, par conséquent, développer de la connaissance. Les propriétés communicatives et interactives des représentations visuelles leur donnent vocation à être des éléments centraux du travail intellectuel. Cet article explore les pratiques emblématiques de la connaissance soutenues par des représentations visuelles et conclut en ouvrant des voies pour d'autres recherches. Mots-clés: artéfacts et pratique, connaissance située dans la conception, représentations visuelles
A Numerical Study of the Solar Modulation of Galactic Protons and Helium from 2006 to 2017

With continuous measurements from space-borne cosmic-ray detectors such as AMS-02 and PAMELA, precise spectra of galactic cosmic rays over the 11 yr solar cycle have become available. For this study, we utilize proton and helium spectra below 10 GV from these missions from 2006 to 2017 to construct a cosmic-ray transport model for a quantitative study of the processes of solar modulation. This numerical model is based on Parker’s transport equation, which includes four major transport processes. The Markov Chain Monte Carlo method is utilized to search the relevant parameter space related to the drift and the diffusion coefficients by reproducing and fitting the mentioned observed spectra. The resulting best-fit normalized χ 2 is mainly less than 1. It is found that (1) when reproducing these observations the parameters required for the drift and diffusion coefficients exhibit a clear time dependence, with the magnitude of the diffusion coefficients anticorrelated with solar activity; (2) the rigidity dependence of the resulting mean free paths varies with time, and their rigidity dependence at lower rigidity can even have a larger slope than at higher rigidity; (3) using a single set of modulation parameters for each pair of observed proton and helium spectra, most spectra are reproduced within observational uncertainty; and (4) the simulated proton-to-helium flux ratio agrees with the observed values in terms of its long-term time dependence, although some discrepancy exists, and the difference is mostly coming from the underestimation of proton flux.
Material selection of natural fibre using a grey relational analysis (GRA) approach

Numerous situations in daily life necessitate a decision. Several of them entail selecting the best option from a number of available options. In many such cases, no single solution is optimal for all of the performance characteristics. This study proposes using grey relational analysis (GRA), a multiple criteria decision making (MCDM) method, to solve this problem. Material selection is vital in designing and developing products, especially for composites materials requiring special attention. The substitution of conventional materials with natural fibres as base material is commonly practised due to high material consumption in mass-producing plastic components that could harm the environment. Therefore, in this work, natural fibres were chosen as composite reinforcement in the design of cyclist helmets. This approach was used to evaluate the right natural fibre and is able to fulfill the needs of consumers and the environment. From the results, the GRA method was utilised and revealed that pineapple was the best top ranking natural fibre with a grade of 0.5687, followed closely by bamboo with a grade of 0.5678, and abaca with a grade of 0.4966. Error analysis was performed to increase the confidence level of the results obtained.
A CNN and LSTM Network for Eye-Blink Classification from MRI Scanner Monitoring Videos

Eye closure changes brain activity, so eye-blink tracking of subjects undergoing resting-state functional magnetic resonance imaging (fMRI) is relevant for identifying when a subject blinks, falls asleep, or keeps their eyes closed. Existing MRI eye-tracking solutions use commercially available MR-compatible video cameras with tracking software that can fail on low-quality videos. In this paper, we propose a two-stage convolutional recurrent neural network to classify open and closed eyes from frames of MRI eye-tracking videos under variable camera conditions. The model extracts visual features from each video frame using a convolutional neural network based on the Inception-v3 model, then uses a long short-term memory network to incorporate temporal information encoded in the sequence of visual features over time. Our model is implemented in Keras and demonstrated on a dataset of MRI eye-tracking videos from the Human Connectome Project. We manually labelled frames from the dataset for training and evaluation. The network was able to classify eye-blink states with a precision of 0.739 and recall of 0.835 on a previously unseen holdout dataset under varying camera conditions, eye position, and video quality.Clinical relevance— Functional mapping studies in psychiatry and neuro-development which rely on a resting state fMRI protocol may yield divergent results depending on whether the subject keeps their eyes closed or open or whether the subject falls asleep. The clinical relevance of this work is to introduce the eye state (closed or open) in brain imaging studies as a prospective covariate, and as a feature that can potentially control for sleep state as a confounding factor.
Three-dimensional analysis of asymmetrical maxillary molar distalization using the indirect Palatal Miniscrew Anchorage and Distalization Appliance (iPanda)

The purpose of this clinical study was to evaluate the dentoalveolar changes due to maxillary molar distalization and to determine side effects using a 3-dimensional intraoral scanning method. The study group comprised 41 patients (mean age, 25.2 ± 2.3 years) with a Class II molar relationship. All patients were treated with the iPanda for unilateral and bilateral maxillary molar distalization. Three-dimensional models were obtained before and การประชมุวิชาการระดับชาติ ครั้งท่ี 9 มหาวิทยาลัยกรุงเทพธนบุร ี 581 after distalizaion. Digital models were superimposed using surface-to-surface matching of the palatal area which is rugae as a reference area. Molar movement was measured on the superimposed maxillary arches before and after distalization. The results showed that Class I molar relationship was obtained, with a movement rate of 0.6 mm per month. In the sagittal plane, the first molars showed a mean linear movement of 3.12 mm ± 0.91 mm and the average molar inclination was 4.29° ± 2.87°. In the vertical plane, the first molars showed slight intrusion, with a mean value of 0.83 mm ± 0.81 mm. In the transverse plane, the rotation of the first molars was 2.33° ± 2.11°. Non-extraction treatment for Class II subdivision malocclusions was achieved by iPanda for unilateral or bilateral molar distalization. Controlled angulation movement of maxillary molars was observed with slight side effects in the vertical and transverse plane.
MSTAR 10-Class classification and confuser and clutter rejection using SVRDM

We compare the performance of our SVRDM (support vector representation and discrimination machine, a new SVM classifier) to that of other popular classifiers on the moving and stationary target acquisition and recognition (MSTAR) synthetic aperture radar (SAR) database. We present new results for the 10-class MSTAR problem with confuser and clutter rejection. Much prior work on the 10-class database did not address confuser rejection. In our prior work [1], we presented our results on a benchmark three-class experiment with confusers to be rejected. In this paper, we extend results to the ten-class classification case with confuser and clutter rejection. Our SVRDM achieved perfect clutter rejection scores, but the clutter was not demanding. Energy-normalization, which was used in many prior algorithms, makes clutter chips similar to target chips and thus produces worse results. We do not energy-normalize data.
Mode power partition events in nearly single-frequency lasers

Frequent power dropouts are observed in the single dominant line of a number of dc-biased 1.3-μm injection lasers, each of which exhibits a nearly single-longitudinal-mode CW spectrum. During the dropout events, some of which essentially extinguish the dominant line for 1 to 8 ns, total laser output power is observed to remain constant: the power lost from the dominant mode appears in a side mode of very low average power. These events are capable of causing bit errors in a communications system. It was found that the frequency of events greater than a given threshold value falls exponentially with an increasing ratio of main-to-side-mode powers and that this ratio must exceed 100:1 in order to avoid a significant contribution to system error rates when the laser is operated continuously and an external modulator is used. These observations are in agreement with recently published calculations. The requirements on mode power ratio for the case of directly modulated lasers are much more severe. We present a calculation of the optical power penalty resulting from these mode power fluctuations.
Genetic Biomarkers of Psychiatric Disease: Discriminating Bipolar Disorder From Major Depressive Disorder With Polygenic Risk Scores

Background. Although accurate differentiation between bipolar disorder (BD) and unipolar major depressive disorder (MDD) has important prognostic and therapeutic implications, the distinction is often challenging based on clinical grounds alone. In this study, we tested whether psychiatric polygenic risk scores (PRSs) improve clinically based classification models of BD v. MDD diagnosis. Methods. Our sample included 843 BD and 930 MDD subjects similarly genotyped and phenotyped using the same standardized interview. We performed multivariate modeling and receiver operating characteristic analysis, testing the incremental effect of PRSs on a baseline model with clinical symptoms and features known to associate with BD compared with MDD status. Results. We found a strong association between a BD diagnosis and PRSs drawn from BD (R = 3.5%, p = 4.94 × 10) and schizophrenia (R = 3.2%, p = 5.71 × 10) genome-wide association meta-analyses. Individuals with top decile BD PRS had a significantly increased risk for BD v. MDD compared with those in the lowest decile (odds ratio 3.39, confidence interval 2.19–5.25). PRSs discriminated BD v. MDD to a degree comparable with many individual symptoms and clinical features previously shown to associate with BD. When compared with the full composite model with all symptoms and clinical features PRSs provided modestly improved discriminatory ability (ΔC = 0.011, p = 6.48 × 10). Conclusions. Our study demonstrates that psychiatric PRSs provide modest independent discrimination between BD and MDD cases, suggesting that PRS could ultimately have utility in subjects at the extremes of the distribution and/or subjects for whom clinical symptoms are poorly measured or yet to manifest.
Students' Activities and Behaviors in Virtual Class Environment Lesson Learnt from Indonesian Private University

The purpose of this study is to explore students' activities and behaviors in virtual class environment, at one of private universities in Indonesia. The methodology used in this study was first determining the indicators used, i.e. visit frequency, visit duration, module view, and discussion activity, then observing the system log files to get the data and analyzing whether any difference in the activities based on student's profiles, i.e. gender and department, using Independent Samples T Test. The sample used in this study was 84 students taught by 2 different lecturers. The results showed that mastery in information technology or computer self-efficacy has no effect on students' activeness. Students from Information System department, which are considered to have more knowledge about information technology, are less active than Economics students. Female students are more active than male students. Student activeness is influenced by institutional policy and the role of lecturer as a facilitator and mediator.
“Entrepreneurship and Economic Growth: Case of Kuwait” By Alia Ali Abu-Aisheh Course “Applied Macroeconomic Theory” Taught by Professor

The main purpose of this research is to highlight on the importance of entrepreneurship as a mechanism for knowledge spillovers, thereby contributing to the economic growth and prosperity of Kuwait. Entrepreneurship is proposed to be one of the main sources for job creations that is expected to help meeting high demands for youth employment in Kuwait in the coming few years. Theoretical studies have shown that entrepreneurship reduces unemployment, increases wealth, and generates market competition through innovation and creativity. Using data extracted from Kuwait Central Statistical Bureau, Kuwait Ministry of Finance, World Bank, and United Nations from 2001 to 2014, an OLS regression was done to estimate the effect of entrepreneurship on GDP growth. Empirical results revealed that entrepreneurship had positive effective on GDP growth of Kuwait, though it was statistically insignificant and this can be attributed to many reasonable explanations. First, the limited number of observations. Second, the impact of all the variables on GDP is theoretically to be effective on the long run. Third, there are other variables contributing to the GDP of Kuwait, like oil prices and the size of the oil exports. In addition, the research summarized few recommendations for policy makers to foster entrepreneurship and to encourage young people to startup their own business instead of joining the public sector. First, making starting a business easier in Kuwait, through minimizing the government interfaces to startup a business, simplifying procedures, and foster healthy market competition free from monopolistic behavior. Second, enhancing the role of universities to foster not only creation of new knowledge but also to cultivate creativity and innovation. Third, create effective funding methods for startups through government subsidies.
JUST ONE POST? FORECASTS OF DAILY SALES OF BEAUTY AND COSMETICS RETAIL COMPANIES BASED ON THE INFLUENCE OF SOCIAL MEDIA

Methodology: Time series of daily sales between the years 2017 and 2019 of 10 retail companies in the beauty and cosmetics sector were considered. Methods based on machine learning were used and the forecasting models were increased with numerical variables from the official profile of the company, from the posting made by the contracted digital influencer and the characteristics of the images posted by the digital influencer were included in the models.
Three dimensional generalised analysis of inclined‐slot coupled T‐junctions with a locally conformed pulsed finite‐difference time‐domain method

The narrow‐wall inclined‐slot coupling between rectangular waveguides from an H‐plane T‐junction, is numerically analysed, for the first time, via a 3D generalised locally conformed FDTD technique. The structure is excited by a combined pulsed modulated TEmn mode scheme which enables the imposition of higher‐order ABCs or advanced PMLs very close to the slot, thus achieving significant reduction of the computational demands. Numerical results, which are shown to be in very good agreement with those obtained by independent scientific research, indicate that the proposed technique can sufficiently handle this class of problems.
Estimation of the higher order modes in transforming time dependent data to frequency dependent data in the time domain simulation

One of the advantages of a time domain numerical analysis method such as the FD-TD method is that the broad band characteristics are obtained by the Fourier transform of the pulse responses. However, the generation of higher order modes makes it difficult to estimate the frequency dependent characteristics by the above technique. This problem also occurs in analyzing guided structures. It seems to be important to predict the s-parameters accurately even if there are higher order modes. Chu and Chaudhuri (1990) have proposed a technique to extract the modal parameters from the FD-TD results in the analysis of dielectric waveguide problems. However, the technique seems to be able to be used in the steady state. Dehler et al. (1993) also has proposed the technique to obtain the scattering matrix considering multiple modes. However, concrete results have not been shown. In the present paper, a new technique for overcoming the above problem is described. The technique consists of common Fourier transforms and Prony's method. In this technique, first, the Fourier transforms are carried out to transform the time domain data to frequency domain data at each spatial observing point, and next, Prony's method is used to separate modes by using the previously obtained Fourier transformed values at the several observation points spatially distributed. In the technique, whole fields values over a waveguide cross section are not needed, but only values at one point have to be considered. The technique can be applied to systems including an arbitrary number of modes. <<ETX>>
Absorptive capacity at the individual level: an ambidexterity approach to external engagement

The ability of an individual to capture knowledge from outside the firm is a critical element in the development of an organization? s absorptive capacity. Despite the acknowledgement that individuals are central to absorptive capacity, researchers have tended to overlook the roles that individuals play in exploring, assimilating and exploiting external knowledge. By defining and measuring absorptive capacity at the individual level, we seek to enrich our understanding of how individuals learn from external knowledge and how such efforts shape the ability of an individual to contribute to their organization? s innovative efforts. We posit that knowledge assimilation plays a vital role in gaining from exploring and exploiting external knowledge. That is, we argue that individuals? performance to develop innovations not only