Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of photospheric, chromospheric and coronal activities of V1147 Tau

We present analyses of optical photometric, spectroscopic, polarimetric and X-ray observations of the K5V binary star, V1147 Tau. Nearly 20 yr of optical observations show that V1147 Tau is a periodic variable with a photometric period of 1.4845 ± 0.0001 d. Light curves observed at 16 epochs show changes in minima, amplitude and shape indicating that the variability is due to the presence of surface inhomogeneities. The surface coverage of spots was found to be in the range of 9–22 per cent. Most of the time, the spots were resolved as two active longitudes. Switching of dominant active longitudes was also seen. The optical spectroscopy revealed that Hα is present in emission, indicating a high level of chromospheric activity. The polarimetric observations yield average values of polarization to be 0.40 ± 0.03, 0.22 ± 0.05, 0.17 ± 0.07 and 0.12 ± 0.04 per cent in B, V, R and I bands, respectively, which indicates the possibility of scattering by thin circumstellar material. The X-ray light curve was found to be rotationally modulated and was anticorrelated with optical light curves observed at quasi-simultaneous epochs. The corona of V1147 Tau consists of a two temperature plasma with kT1 = 0.07 keV and kT2 = 0.66 keV. The X-ray luminosity in the 0.2–2.4 keV energy band was found to be 4.4–6.8 × 10 29 erg s −1 . Flaring features were also seen in the X-ray light curve.
Avoidance Manipulability for Redundant Manipulators

This paper is concerned with avoidance manipulability of redundant manipulators for trajectory tracking and obstacle avoidance. Possibility of avoiding a collision with obstacles during tracking a desired hand trajectory is discussed with proposed avoidance matrix, avoidance manipulability ellipsoid and avoidance manipulability measure which are defined on each link constructing the manipulator except top link. A necessary and sufficient condition that the intermediate links can avoid obstacles in a work space is indicated that a dimension of range space of the avoidance matrix coincides with the one of the work space of the manipulator. That means the avoidance manipulability ellipsoid is expanded in the whole work space. Relations of the ellipsoids and factors which influence the shape, namely, a posture of the manipulator, redundant degree, a serial position of the intermediate link from base, and priorities of the avoiding tasks, are also analyzed. Finally we show analyzed results of avoidance possibility with the proposed avoidance manipulability by numerical examples.
Edge detection using deep learning pipelines for TEM and SEM metrology by proposing generic and specific approaches

Edge detection is the core of most metrology tools to identify boundaries between materials. With the shrinking in size of all devices for higher performances, this task becomes more and more challenging. In addition, the use of new composition of materials increases the challenge by reducing the contrast between different materials. The general quality of the images is critical to recover the right edges, in particular for High Resolution Electronic Microscopy, which remains the reference for high quality metrology during R&D phases. In these images, the low contrast of the edges and changes in the texture of the materials creating no sharped borders are impacting the performances of classical edge extraction methods. In order to improve capacities of algorithms, we propose a pipeline to generate edge maps. These edge maps can be further used in more classical algorithms to extract better measurements. Two versions of the pipeline can be used, a first one trained on generic images from the semiconductor industry and a second one that can be tuned on specific use cases. The first one provides a readyto- use solution and the second one is able to provide more accurate measurements at the cost of annotating images. To illustrate these results, we demonstrate the use of these features with various algorithms on use cases from the semiconductor industry such as gates and wires. We propose comparison between the two pipelines both in term of accuracy and time to recipe.
Prediction of subglacial lake melt source regions from site characteristics

Abstract Subglacial melt has important implications for ice-sheet dynamics. Locating and identifying subglacial lakes are expensive and time-consuming, requiring radar surveys or satellite methods. We explore three methods to identify source regions for lakes using seven continent-wide environmental characteristics that are sensitive to or influenced by ice-sheet temperature. A simple comparison of environmental properties at lake locations with their continent-wide distributions suggests a statistical relationship (high Kolmogorov-Smirnov statistic) between stable lake locations and ice thickness and surface temperatures, indicating melting under passive conditions. Active lakes, in contrast, show little correlation with direct thermally influenced parameters, instead exhibiting large statistical differences with horizontal velocity and bedrock elevation. More sophisticated techniques, including principal component analysis (PCA) and machine learning (ML) classification, provide better spatial identification of lake types. Positive PCA scores derived from the environmental characteristics correlate with stable lakes, whereas negative values correspond to active lakes. ML methods can also identify regions where subglacial lake melt sources are probable. While ML provides the most accurate classification maps, the combination of approaches adds deeper knowledge of the primary controls on lake formation and the environmental settings in which they are likely to be found.
Performance evaluation of an improved deep CNN-based concrete crack detection algorithm

This study uses a novel directional lighting approach to produce a computationally efficient five-channel Visual Geometry Group-16 (VGG-16) convolutional neural network (CNN) model for concrete crack detection and classification in low-light environments. The first convolutional layer of the proposed model copies the weights for the first three channels from the pre-trained model. In contrast, the additional two channels are set to the average of the existing weights along the channel. The model employs transfer learning and fine-tuning approaches to enhance accuracy and efficiency. It utilizes variations in patterned lighting to produce five channels. Each channel represents a grayscale version of the images captured using directed lighting in the right, below, left, above, and diffused directions, respectively. The model is evaluated on concrete crack samples with crack widths ranging from 0.07 mm to 0.3 mm. The modified five-channel VGG-16 model outperformed the traditional three-channel model, showing improvements ranging from 6.5 to 11.7 percent in true positive rate, false positive rate, precision, F1 score, accuracy, and Matthew’s correlation coefficient. These performance improvements are achieved with no significant change in evaluation time. This study provides useful information for constructing custom CNN models for civil engineering problems. Furthermore, it introduces a novel technique to identify cracks in concrete buildings using directed illumination in low-light conditions.
Methyl 8- and 5-Bromo-1,4-Benzodioxane-2-carboxylate: Unambiguous Identification of the Two Regioisomers

A variety of biological active compounds can be classified as 2-substituted 1,4-benzodioxanes bearing one or more substituents at the benzene. The synthesis of these important templates can be approached by different strategies. The most straightforward ones generally lead to mixtures of positional isomers, whose identification can be more problematic than separation. Here, we unambiguously elucidate, by HSQC and HMBC NMR analyses, the structure of methyl 8- and 5-bromo-1,4-benzodioxane-2-carboxylate, two versatile synthetic intermediates that are one-step-obtainable from commercial products and easily separable. As conceived, the identification procedure is, in principle, generalizable to any pair of 2-substituted 1,4-benzodioxanes bearing an X substituent at C(8) or C(5).
Cholesterol Crystals as the Main Trigger of Interleukin-6 Production through Innate Inflammatory Response in Human Spontaneously Ruptured Aortic Plaques

Aim: This study aimed to clarify whether cholesterol crystals (CCs) are the main trigger of innate inflammation in human spontaneously ruptured aortic plaques (SRAPs). Methods: This study included 260 SRAPs collected during nonobstructive general angioscopy (NOGA) from 126 patients with confirmed or suspected coronary artery disease. Interleukin (IL)-6 levels in SRAPs were measured. IL-6 levels in the Valsalva sinus and femoral or brachial arteries were measured. IL-6 ratios (the IL-6 level in SRAPs and arteries divided by the IL-6 level at the Valsalva sinus at the beginning of the aorta) were calculated. Quantitative analysis of CCs was performed from SRAPs. The correlation between the count of CCs and IL-6 levels in SRAPs and that between the counts of CCs and IL-6 ratios in SRAPs were analyzed. Results: The IL-6 levels in SRAPs were 3.4 [2.1, 7.2] pg/mL, and the IL-6 ratio (median [interquartile range]) in SRAPs was 1.10 [1.00, 1.26]. CCs were detected in 94 of 260 SRAPs (36%). The count of CCs was 11,590 (95% confidence interval, 2,386–30,113) per 10 mL in CC-positive samples. There was a moderate correlation between the counts of CCs and IL-6 ratios in SRAPs (r=0.49, r＜0.0001), whereas there was no correlation between the count of CCs and IL-6 levels in SRAPs. The IL-6 ratios of the brachial and femoral arteries were 1.06 (95% CI, 0.99–1.20) and 1.11 (95% CI, 1.04–1.20), respectively. Conclusions: CC is the main trigger of IL-6 production through innate inflammatory response in human SRAPsin situ.
Characterization of Potent ABCG2 Inhibitor Derived from Chromone: From the Mechanism of Inhibition to Human Extracellular Vesicles for Drug Delivery

Inhibition of ABC transporters is a promising approach to overcome multidrug resistance in cancer. Herein, we report the characterization of a potent ABCG2 inhibitor, namely, chromone 4a (C4a). Molecular docking and in vitro assays using ABCG2 and P-glycoprotein (P-gp) expressing membrane vesicles of insect cells revealed that C4a interacts with both transporters, while showing selectivity toward ABCG2 using cell-based transport assays. C4a inhibited the ABCG2-mediated efflux of different substrates and molecular dynamic simulations demonstrated that C4a binds in the Ko143-binding pocket. Liposomes and extracellular vesicles (EVs) of Giardia intestinalis and human blood were used to successfully bypass the poor water solubility and delivery of C4a as assessed by inhibition of the ABCG2 function. Human blood EVs also promoted delivery of the well-known P-gp inhibitor, elacridar. Here, for the first time, we demonstrated the potential use of plasma circulating EVs for drug delivery of hydrophobic drugs targeting membrane proteins.
A Comprehensive Prediction Model for VHF Radio Wave Propagation by Integrating Entropy Weight Theory and Machine Learning Methods

In order to improve the prediction accuracy and robustness of radio wave propagation in the very high-frequency (VHF) band, we proposed a combination prediction model (CPM) based on the entropy weight theory and the machine learning method. The improved entropy weight method is used to determine the initial weights of recommendation ITU-R P.1546 and ITU-R P.2001 in the CPM based on the systematic analysis of the prediction performance of the two ITU-R models. Instead, we modeled the weight mapping using the machine learning method. The statistical comparison shows that the prediction accuracy and robustness of the proposed model are better than ITU-R P.1546 and P.2001 models, in which the root-mean-square error (RMSE) of path loss is reduced by 3.56 and 7.35 dB, respectively. In addition, the relative error (RE) of path loss is reduced by 0.0157 and 0.0255 dB, respectively, corresponding to a 40.53% and 52.62% reduction in the RE of path loss. The above research can provide basic support for the regional assimilation of radio propagation prediction methods.
Solar radiative transfer in clouds with vertical internal inhomogeneity

Abstract To investigate the photon transport in inhomogeneous clouds, a Monte Carlo cloud model with internal variation of optical properties is developed. The data for cloud vertical internal inhomogeneity are chosen from published observations. Parameterization of the solar radiative properties of clouds is used in the form of the liquid water content and the effective radius of cloud droplet. The Monte Carlo simulations show that for overcast stratocumulus clouds, the differences in reflectance between the vertical inhomogeneous clouds and their planeparallel counterpart are very small (only about 1%). These differences can be enhanced up to 10% for large solar zenith angles, when the overcast clouds are separated into broken cloud fields. If the cloud coverage is large, the vertical inhomogeneity of clouds can cause about 7% increase in cloud absorption, which may help to explain the cloud absorption anomaly. Also, the parameterization of effective cloud amount for cloud absorption is discussed.
Electromagnetic Transmit Array With Optical Control for Beamforming

This proof-of-concept communication demonstrates the feasibility of using a slide projector to steer the beam of a transmit array by adding solar cells and varactor diodes to each unit cell. By irradiating each solar cell with the light of different intensities from a slide projector, the measured phase of the wave transmitted by the <inline-formula> <tex-math notation="LaTeX">$4\times4$ </tex-math></inline-formula> transmit array shifts within 92° at 4.26 GHz, while the variation in magnitude is measured within 4 dB. Different light configurations are identified via a searching algorithm to achieve peak/null beamforming in a particular direction. The beam of the prototypical <inline-formula> <tex-math notation="LaTeX">$4\times4$ </tex-math></inline-formula> transmit array can be shifted by ±24° in terms of the peaks and −30° to 36° in terms of nulls. The concept of adding light modulation to the transmit array with a slide projector can provide update rates of tens of milliseconds with control of brightness and color distributed over a large area of the array.
Quasi-Biennial Variations in Temperature, Total Ozone, and Tropopause Height

Abstract An analysis of mean-monthly temperature and total ozone data suggests that quasi-biennial oscillations extend to the temperate and polar latitudes of both hemispheres. Basically, there is symmetry with respect to the equator, although the oscillations show up most clearly in the Southern Hemisphere, and there is a tendency for the biennial maximum of temperature and total ozone to occur in the spring. Harmonic analysis implies a poleward drift of the biennial maximum of temperature and total ozone at a rate near 0.2 m sec−1, with the drift becoming indistinct poleward of 40°. The quasi-biennial variation in total ozone is very nearly in phase with the quasi-biennial variation in 50-mb temperature. There is also a quasi-biennial variation in tropopause height associated with the temperature oscillation in the lower stratosphere. There is weak evidence for a quasi-biennial variation in beryllium-7 in the lower stratosphere.
Preparation of Nanocellulose-Based Aerogel and Its Research Progress in Wastewater Treatment

Nowadays, the fast expansion of the economy and industry results in a considerable volume of wastewater being released, severely affecting water quality and the environment. It has a significant influence on the biological environment, both terrestrial and aquatic plant and animal life, and human health. Therefore, wastewater treatment is a global issue of great concern. Nanocellulose’s hydrophilicity, easy surface modification, rich functional groups, and biocompatibility make it a candidate material for the preparation of aerogels. The third generation of aerogel is a nanocellulose-based aerogel. It has unique advantages such as a high specific surface area, a three-dimensional structure, is biodegradable, has a low density, has high porosity, and is renewable. It has the opportunity to replace traditional adsorbents (activated carbon, activated zeolite, etc.). This paper reviews the fabrication of nanocellulose-based aerogels. The preparation process is divided into four main steps: the preparation of nanocellulose, gelation of nanocellulose, solvent replacement of nanocellulose wet gel, and drying of nanocellulose wet aerogel. Furthermore, the research progress of the application of nanocellulose-based aerogels in the adsorption of dyes, heavy metal ions, antibiotics, organic solvents, and oil-water separation is reviewed. Finally, the development prospects and future challenges of nanocellulose-based aerogels are discussed.
Data quality control and homogenization of daily precipitation and air temperature (mean, max and min) time series of Ukraine

In this paper we present the results of quality control and homogenization procedures applied to long time series of daily atmospheric precipitation sums (Rr) and daily mean (Tm), maximum (Tx) and minimum (Tn) air temperature collected in Ukraine. The daily data from 178 meteorological stations covering the period of 1946–2020 were analysed. In order to perform a thorough quality assurance check, we used the R package INQC, while the Climatol homogenization software was used to detect and remove breaks from the time series. The INQC quality assurance tests revealed a relatively small number of erroneous records (around 0.01% for each variable) and suspicious values (up to 0.09%). The application of Climatol resulted in 195, 296, 355 and 359 break points, detected for Rr, Tm, Tx and Tn, respectively. These quantities coincide roughly with the results of the HOMER homogenization procedure applied to monthly time series for the same stations and almost the same period (performed in the previous works of the authors). To verify the homogenization results, statistical comparison of the raw and homogenized time series was performed. The verification demonstrated that the quality control and homogenization procedures detected and removed errors and breaks very well, and air temperature and precipitation fields after the homogenization are more self‐consistent compared to the original raw data.
Low modulus Ti-rich biocompatible TiNbZrTaHf concentrated alloys with exceptional plasticity

This study investigates the evolutions of microstructure and performance of TiNbZrTaHf-based alloys from equiatomic high-entropy alloys to Ti-rich dilute alloys. A novel biocompatible alloy, Ti50Nb12.5Zr12. 5Ta12.5Hf12. 5, was developed with a high yield strength of 839 ± 12 MPa, low modulus of 61.5 GPa, low magnetic susceptibility of ∼1.99 × 10−6 cm3g−1, and unprecedented tensile plasticity of 28.7 ± 2.2%. The study discusses the underlying mechanisms responsible for these superior performances, attributing the exceptional plasticity to the activation of cross-slip dislocations, enhanced dynamic recovery and high resistance to crack propagation. The findings provide new insights into the development of biomedical titanium alloys. GRAPHICAL ABSTRACT IMPACT STATEMENT This study introduces a novel biocompatible concentrated alloy with high strength, low modulus and unprecedented ductility, providing new insights for developing high-performance biomedical titanium alloys.
A critical analysis of education policy in turbulent times: A comparative study

This study is a qualitative investigation of education policies and decision making during COVID-19 pandemic in five Middle East and North Africa Region (MENA) countries: Kuwait, Lebanon, Morocco, Palestine, and Qatar. It aims at scrutinizing how these countries responded to the education disruption caused by the pandemic between February 2020 and July 2021 and how they managed the resulting turbulence. We also investigate the extent to which these decisions were equitable and innovative. Data were collected from Ministerial notes, media content, and international organizations reports about the situation of education in the region. Walt and Gilson’s (1994) policy analysis triangle and the Cynefin framework (Kurtz & Snowden, 2003) guided the objectives and the analysis of the data. Findings revealed that these countries muddled through the education policy at the beginning of the pandemic, centralized decision making, and faced difficulties to implement online and distance learning. In the second phase, most of these countries tried to save education, but were halted by structural challenges. Some differences were witnessed among these countries in how they have dealt with the evolving crisis. However, some similarities have also been noticed at the levels of context, process and actors. The decisions taken often lacked innovation and led to less equitable outcomes. The discussion of the findings has some implications for education policy and education management in turbulent times in the MENA region.
An integrated failure mode and effect analysis approach for accurate risk assessment under uncertainty

ABSTRACT Failure Mode and Effect Analysis (FMEA) is a reliability analysis technique that plays a prominent role in improving the reliability and safety of systems, products, and/or services. Although commonly used in quality improvement efforts, the conventional Risk Priority Number (RPN) method has been heavily criticized in the literature for its various limitations, such as in failure mode evaluations, risk factor weights, and RPN computation. In this article, we describe the application of an ELECTRE (ELimination Et Choix Traduisant la REalité)-based outranking approach for FMEA within the interval two-tuple linguistic environment. Considering different types of FMEA team members' assessment information, we employ a hybrid averaging operator to construct the group assessment matrix and use a modified ELECTRE method to analyze the group interval two-tuple linguistic data. Furthermore, the new risk-ranking model deals with the subjective and objective weights of risk factors concurrently, considering the degree of importance that each concept has in the risk analysis. The practicality and applicability of the proposed methodology are demonstrated by applying it to a risk evaluation problem of proton beam radiotherapy, and a comparative study is conducted to validate the effectiveness of the new FMEA approach.