Miracle-dz/UniFAR-FTUs huggingface dataset:
Demonstration of multi-star wavefront control for WFIRST, Habex, and LUVOIR

Coronagraphic instruments will enable direct imaging of dim planetary companions around nearby stars. The majority of nearby FGK stars are located in multi-star systems, including the Alpha Centauri stars, which may represent the best quality targets available for spectroscopic characterization due to their proximity and brightness. However, a binary system exhibits additional leakage from the off-axis companion star that may be brighter than the target exoplanet. Multi-Star Wavefront Control (MSWC) is a wavefront-control technique that allows simultaneous suppression of starlight of both stars in a binary system. MSWC would thus enable direct imaging of circumstellar planets in binary star systems such as Alpha Centauri. MSWC is compatible with a wide suite of planned coronagraphic instruments for future space missions. As part of the technology demonstration efforts for MSWC, the first milestone results are presented here demonstrating (via computer simulations), high-contrast imaging capabilities of multi-star systems for several instruments including: [1] the upcoming WFIRST and its CGI demonstrator, [2] the HABitable Worlds EXplorer (Habex) mission concept, [3] the segmented Large UV/Optical/IR (LUVOIR) mission concept, and [4] a small-aperture Alpha Centauri direct-imager mission concept. For each of these missions, a baseline coronagraph option planned for the mission will be adopted and instrument baseline performance will be compared for single-star wavefront control.
A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic

Internet of Things (IoT) is expected to have a significant impact on city’s service provisioning and make a smart city more accessible and pragmatic since the deployment of heterogeneous smart devices in each infrastructure of cities is increasing. So far, the IPv6 routing protocol for low power and lossy networks (RPL) is considered to fit on IoT infrastructure for achieving the expected network requirements. While RPL meets the IoT network requirements quite well, there are some issues that need to be addressed, such as adaptability to network dynamics. This issue significantly limits the use of RPL in many smart city application scenarios, such as emergency alerts with high traffic flows. As part of a smart city vision, IoT applications are becoming more diverse, which requires context-awareness in routing protocols to support the behavior of the network. To address this issue, we design an objective function that performs the route selection based on fuzzy logic techniques while using contextual information from the application. For this, we present a new context-oriented objective function (COOF) that comprises both nodes as well as link metrics. Further, we suggest two new routing metrics, known as queue fluctuation index (QFI) and residual energy index (REI), which consider the status of queue utilization and remaining energy, respectively. The metrics used are designed to respond to the dynamic needs of the network. The proposed approach has been examined and evaluated in different scenarios when compared to other similar approach and default RPL objective functions. Simulation experiments are conducted in Cooja network simulator for Contiki OS. The evaluation results show that COOF can cope with network dynamics and IoT-based smart city application requirements.
Classification of Javanese Language Level on Articles Using Multinomial Naive Bayes and N-Gram Methods

Javanese language articles can now be found in electronic media. But for people who are just learning the Javanese language, they have difficulty in knowing the language level that is contained in the article because there is no explanation regarding the type of language level. For this reason, it is necessary to classify the language level in Javanese language based on the article, where the Javanese language is divided into 4 levels, namely ngoko, ngoko alus, krama madya, and krama alus. Before beginning the classification process, the data must be preprocessed. One of the steps in preprocessing method is stemming, which is used to convert the affixes in words into basic words. The Javanese stemming process in this research refers to the Indonesian stemming rules based on the adjusted Nazief-Adriani algorithm. The extraction feature process was carried out using N-Gram with n = 2, 3, 4 (bigram, trigram, and quadgram). After finishing the preprocessing method, the classification process then was executed using Multinomial Naïve Bayes method. In the classification process, there often exist problems related to imbalance data between categories. To overcome this problem, SMOTE resampling method is utilized to balance the data. The classification with N-Gram variations accompanied by SMOTE and using stemming results to maximum accuracy of 67.01% at n = 2, then for the highest precision was at N-Gram n = 4 with condition not using stemming but using SMOTE at value 72.67%. The highest recall value was obtained in two conditions, namely at N-Gram n = 2 either using or not using SMOTE and use stemming, which is 67.00%. From the results of this study, it can be concluded that stemming rules which are adapted from Nazief-Adriani algorithm with the addition of stemming steps and affix list from Javanese language expert can be implemented properly for Javanese language stemming process. And the classification of the Javanese Language level using Multinomial Naïve Bayes and N-Gram methods can result in good enough accuracy, precision, and recall.
Performance Attributes and Risk Taking of Players-Evidence from Lawn Tennis

Lawn tennis is one of the most popular and most viewed sports of the world. It is an Olympic sport and played at all levels of society and at all ages. It represents an ideal outdoor sport, promoting alertness, endurance, and selfcontrol, as well as mental and physical health. Professional players across the world take part in various tournaments and based on their performance in those tournaments ranking of tennis players is done by Association of Tennis Players (ATP). Ranking of a player represents achievement or success of the player in lawn tennis.
Flood Risk Assessment of the Wadi Nu’man Basin, Mecca, Saudi Arabia (During the Period, 1988–2019) Based on the Integration of Geomatics and Hydraulic Modeling: A Case Study

This study aims to assess the impact of flash floods in the Wadi Nu’man basin on urban areas, east of Mecca, which are subjected to frequent floods, during the period from 1988–2019. By producing and analyzing the maps of the regions, an integrated approach to geomatics and hydraulic modelling is employed. The following maps are used: Flood-prone urbanity from 1988–2019, a flood risk map of Wadi Nu’man based on a risk matrix map, and a map of the proposed protection measures and alternatives in the study area. In order to achieve these goals, changes in the land use in the Wadi Nu’man basin were monitored by analyzing successive satellite images, taken by the US satellite, Landsat, in 1988, 1998, 2013, and 2019. Using a supervised classification, with the maximum likelihood method of ERDAS IMAGINE 2016, GIS was used in the production and analysis of soil maps, and geological and hydrological groups of drainage basins, as well as the hydrological model (HEC-HMS), were applied in calculating the hydrograph curve of the Wadi Nu’man basin. The flood water volumes and flow rates were estimated based on the SCS unit hydrograph, and the rain depth was analyzed and estimated for different periods. The hydraulic modeling program (HEC-RAS) was employed, when developing a two-dimensional model to calculate the speed, depth, and spread of the flood, in order to apply the risk matrix method. The recommendations based on this study give priority to the implementation of a flood prevention plan and the protection of infrastructure by maintaining the existing flood drainage facilities and establishing new drainage facilities to protect lives, property, and infrastructure.
A Model for Generating Workplace Procedures Using a CNN-SVM Architecture

(1) Background: Improving the management and effectiveness of employees’ learning processes within manufacturing companies has attracted a high level of attention in recent years, especially within the context of Industry 4.0. Convolutional Neural Networks with a Support Vector Machine (CNN-SVM) can be applied in this business field, in order to generate workplace procedures. To overcome the problem of usefully acquiring and sharing specialist knowledge, we use CNN-SVM to examine features from video material concerning each work activity for further comparison with the instruction picture’s features. (2) Methods: This paper uses literature studies and a selected workplace procedure: repairing a solid and using a fuel boiler as the benchmark dataset, which contains 20 s of training and a test video, in order to provide a reference model of features for a workplace procedure. In this model, the method used is also known as Convolutional Neural Networks with Support Vector Machine. This method effectively determines features for the further comparison and detection of objects. (3) Results: The innovative model for generating a workplace procedure, using CNN-SVM architecture, once built, can then be used to provide a learning process to the employees of manufacturing companies. The novelty of the proposed methodology is its architecture, which combines the acquisition of specialist knowledge and formalising and recording it in a useful form for new employees in the company. Moreover, three new algorithms were created: an algorithm to match features, an algorithm to detect each activity in the workplace procedure, and an algorithm to generate an activity scenario. (4) Conclusions: The efficiency of the proposed methodology can be demonstrated on a dataset comprising a collection of workplace procedures, such as the repair of the solid fuel boiler. We also highlighted the impracticality for managers of manufacturing companies to support learning processes in a company, resulting from a lack of resources to teach new employees.
Comparison of Feature Vector Compositions to Enhance the Performance of NIRS-BCI-Triggered Robotic Hand Orthosis for Post-Stroke Motor Recovery

Recently, brain–computer interfaces, combined with feedback systems and goal-oriented training, have been investigated for their capacity to promote functional recovery after stroke. Accordingly, we developed a brain–computer interface-triggered robotic hand orthosis that assists hand-closing and hand-opening for post-stroke patients without sufficient motor output. In this system, near-infrared spectroscopy is used to monitor the affected motor cortex, and a linear discriminant analysis-based binary classifier estimates hand posture. The estimated posture then wirelessly triggers the robotic hand orthosis. For better performance of the brain–computer interface, we tested feature windows of different lengths and varying feature vector compositions with motor execution data from seven neurologically intact participants. The interaction between a feature window and a delay in the hemodynamic response significantly affected both classification accuracy (Matthew Correlation Coefficient) and detection latency. The ‘preserving channels’ feature vector was able to increase accuracy by 13.14% and decrease latency by 29.48%, relative to averaging. Oxyhemoglobin combined with deoxyhemoglobin improved accuracy by 3.71% and decreased latency by 6.01% relative to oxyhemoglobin alone. Thus, the best classification performance resulted in an accuracy of 0.7154 and a latency of 2.8515 s. The hand rehabilitation system was successfully implemented using this feature vector composition, which yielded better classification performance.
Pharmacokinetics, medicolegal aspects, and general interest

This three-volume text provides a comprehensive review and reference source for those with a teaching, research, or practical involvement in alcohol metabolism in humans. Written by 70 contributing authors from 12 countries, this publication covers a wide range of material, from medicolegal aspects of alcohol metabolism to the structure of enzymes involved in metabolizing alcohol. Although primarily concerned with human alcohol metabolism, information from animal experiments is included where it clarifies results of human studies, or where information for human subjects is not available.
Caractérisation des interactions électromagnétiques pour l'intégration de capteurs en électronique de puissance

Cet article presente une analyse du comportement electromagnetique d’un systeme de puissance en vue de l’integration de capteurs champ proche. La connaissance des phenomenes electromagnetiques conduits et rayonnes est essentielle pour le design et le placement des capteurs, ainsi que pour l’analyse des signaux mesures. Le travail realise consiste en l’elaboration d’un modele « circuit » permettant la simulation de ces phenomenes. Il englobe le module et les differents capteurs integres. Il se base a la fois sur des mesures en conduit et sur le calcul numerique des elements parasites et des couplages electromagnetiques. La methode est appliquee a un hacheur dont les capteurs integres sont des antennes magnetiques de type « boucle ».
Transição de fase quântica em um hamiltoniano efetivo de três modos para bósons interagentes

Neste trabalho, nos estudamos um hamiltoniano efetivo de tres modos de frequencia descrevendo bosons interagentes. Podemos considerar estes bosons como exciton-polaritons em uma microcavidade semicondutora, na configuracao do ângulo magico, ou como atomos frios armadilhados opticamente em um poco triplo, com a conservacao do desequilibrio das populacoes. Verificamos que as propriedades do espectro quântico, que caracterizam uma transicao de fase quântica, possuem uma analogia com as propriedades do espaco de fase classico de uma funcao hamiltoniana obtida no limite termodinâmico. O adensamento de niveis no espectro, em torno do estado fundamental e do mais energetico, corresponde ao surgimento de uma separatriz (uma trajetoria que separa libracoes e rotacoes) no espaco de fase classico. Esta analogia classica nos permite, ainda, a caracterizacao das fases e a determinacao da ordem da transicao, alem da construcao de um diagrama de fase.
Vers une meilleure caractérisation des sujets atteints d'asthme exacerbé

Background: Work related asthma (WRA) refers to asthma that is induced or exacerbated by the workplace. Occupational asthma (OA) and work-exacerbated asthma (WEA) are difficult to distinguish in clinical practice since in both conditions workers complain of deterioration of their asthma while at work. In addition, physicians are often faced with subjects with work related respiratory symptoms (WRS) without being asthmatics. These subjects are often excluded from studies whose aim is to better characterize WRA. Objectives: 1. To compare the diurnal variability of peak expiratory flow (PEF) during periods at and away from work between subjects with OA and WEA. 2. To assess the prevalence of subjects with work related respiratory symptoms but without asthma among subjects referred for possible WRA, and to compare their characteristics and work environment to subjects with WRA. Results: Work exposures induce a significant PEF variability in both OA and WEA. However, the magnitude of variability is higher in OA than in WEA during work exposures. Subjects with WRS without asthma represent a large proportion of the subjects referred for possible WRA. Conclusions: WRA should be considered in all individuals who present with new-onset or worsening asthma. The similarity of the symptoms between subjects with WRA and WRS emphasizes the need to perform an extensive investigation. This investigation should be based on a stepwise approach in which multiple objective testing improves the certainty of diagnosis and help to differentiate between OA and WEA.
Geração de nuvem de pontos para métodos sem malhas

Uma tecnica para gerar nuvens de pontos para metodos sem malha, que sao limitadas por uma funcao de densidade especificada e pela geometria de entrada e apresentada. Inicialmente, os pontos sao distribuidos ao longo das bordas da geometria identificando seus limites e as fronteiras entre diferentes materiais. Para gerar pontos dentro da geometria, duas abordagens diferentes sao usadas: (i) distribuicao aleatoria e (ii) uma subdivisao baseada em quadtree, onde o menor quadrado que circunda a geometria e recursivamente subdividido em quatro, com a criacao de um novo ponto no centro de cada quadrado. Em ambos os casos, o processo iterativo e interrompido quando a densidade de pontos se aproxima da funcao de densidade especificada. Os pontos iniciais sao redistribuidos usando o algoritmo iterativo de refinamento de Lloyd, ate a distribuicao esperada ser cumprida. Tanto distribuicoes uniformes de pontos quanto nao uniformes, onde a funcao de densidade nao e constante, podem ser atendidas. A qualidade final da nuvem resultante so depende do algoritmo de refinamento de Lloyd. No entanto, o algoritmo que gera pontos iniciais com base em quadtrees, embora mais complexa do que a geracao aleatoria, necessita menos iteracoes do algoritmo de Lloyd para atingir a qualidade esperada. Isto e devido ao fato de que seus pontos de distribuicao inicial ja levam em conta a funcao de densidade especificada.
Schooling, Physical Education and the primary-secondary transition

Preliminary evidence indicates that although there have been attempts to ensure continuity across the primary-secondary transition (Tobell, 2003), discontinuities remain and that there is a "hiatus in progression" (Galton et al., 2000). For pupils the transition to secondary school is a time of change leaving their small familiar primary school and entering a large unfamiliar secondary school. This thesis presents pupils' expectations and experiences of the primary-secondary transition, across the curriculum and specifically with regards to Physical Education (PE). The primary-secondary transition with regards to PE is marked by significant changes in resource provision, and a mode of delivery from (mainly) non-specialist teachers to subject specialists (Capel and Piotrowski, 2000). As an exploratory case study, an ethnographic approach was adopted with "pupil-voice" a distinctive and central feature. Two phases of fieldwork were conducted. The first phase examined Year 6 (aged 10-11) pupils' expectations of the primary-secondary transition at Urban Primary and tracked these pupils into City Comprehensive to explore their experiences (June-October 2011). The second phase of fieldwork examined the particularities of the transition concerned with PE. Once more, expectations of Year 6 pupils at Urban Primary were explored and tracked into City Comprehensive (June-October, 2012). Thematic inductive analysis was conducted and there were four super-ordinate findings which relate to: pupils' perceptions of the process of transition across the curriculum and with regards to PE; the notion of "being good enough"; social implications of transition; concept of "growing up"; teachers and teaching. Findings suggest that these factors contribute to a discontinuous experience for pupils during transition. Future research directions point towards a focus on academia across transition and a consideration of the development in physical competence within primary school settings. Throughout this thesis reflexivity and reflection were used to provide an insight into the research journey as part of the doctoral apprenticeship.Thesis completed in 2014.
A Case Study of Terrain Influences on Upscale Convective Growth of a Supercell

Satellite- and ground-based radar observations have shown that the northern half of Argentina, South America, is a region susceptible to rapid upscale growth of deep moist convection into larger organized mesoscale convective systems (MCSs). In particular, the complex terrain of the Sierras de Córdoba is hypothesized to be vital to this upscale-growth process. A canonical orographic supercell-to-MCS transition case study was analyzed to determine the influence that complex terrain had on processes governing upscale convective growth. High-resolution numerical modeling experiments were conducted in which the terrain height of the Sierras de Córdoba was systematically modified by raising or lowering the elevation of terrain above 1000 m. The alteration of the terrain lead to both direct and indirect effects on storm morphology. A direct effect included terrain blocking of cold pools, whereas indirect effects included terrain-induced variations in pertinent storm environmental parameters (e.g., vertical wind shear, convective available potential energy). When the terrain was raised, low-level and deep-layer vertical wind shear increased, mixed-layer convective available potential energy decreased, deep moist convection initiated earlier, and cold pools were blocked and generally became stronger and deeper. The reverse occurred when the terrain was lowered, resulting in a weaker supercell that did not grow upscale into an MCS. The control simulation supercell displayed the deepest cold pool and correspondingly fastest transition from supercell to MCS, potentially revealing that the unique terrain configuration of the Sierras de Córdoba was supportive of the observed rapid upscale convective growth of this orographic supercell.
Hämodynamische und immunmodulatorische Effekte von niedrig dosiertem Hydrocortison im septischen Schock

In a prospective, double-blind, randomised, placebo-controlled cross-over study, hemodynamic and immune effects of a three-day adjunctive treatment with low doses of hydrocortisone (HC) (100 mg bolus followed by 10 mg per hour) were investigated in forty patients with septic shock. HC-therapy induced a rise of mean arterial pressure and systemic vascular resistance and a decline of cardiac index and heart rate without altering pulmonary vascular resistance. Both, nitrite/nitrate levels (nitric oxide formation) and cathecholamine requirement were reduced. Immune responses were complex and included: reduction of proinflammatory (interleukin-(IL)-6, 8) and antiinflammatory (IL-10, soluble tumor necrosis factor receptors) mediators, an increase of proinflammatory cytokines (IL-12 and interferon-γ), a reduction of endothelial (E-selectin) and granulocyte activation (CD11b, CD64), and a decrease of T-helper and suppressor cells as well as eosinophil and basophil granulocytes; monocytes increased and total granulocyte and leukocyte counts remained unaltered. Parameters of innate (respiratory burst, phagocytosis) and adaptive immune responses (HLA-DR-expression on monocytes, antigen presentation) were not essentially affected, monocyte phagocytosis rather increased. HC-withdrawal induced marked hemodynamic and immunologic rebound effects. In conclusion, effects of low dose HC-therapy in septic shock is characterised by hemodynamic stabilisation and immunomodulation, without inducing severe immunosuppression.
Two-dimensional Underdetermined DOA Estimation of Quasi-stationary Signals via Sparse Bayesian Learning

In order to improve the direction-of-arrival (DOA) estimation performance of quasi-stationary signals (QSS) using a uniform circular array (UCA), this paper addresses novel method in the context of sparse representation framework. Based on the Khatri-Rao transform, UCA can achieve a higher number of degrees of freedom to resolve more signals than the number of sensors. Then, by exploiting the two-dimensional (2-D) joint grid of UCA, the estimations of elevation and azimuth angles can be obtained from the sparse representation perspective. Finally, an expectation-maximization iteration method is developed to estimate DOAs of QSS from a Bayesian perspective. Since SBL makes full use of the sparse structure of QSS, thus the proposed algorithm possesses higher angular resolution and better DOA estimation precision compared with existing methods. Numerical simulations demonstrate the validity of the proposed method.