Miracle-dz/UniFAR-FTUs huggingface dataset:
High Spectral Resolution Time-resolved Optical Spectroscopy of V893 Scorpii

We present high-resolution time-resolved optical spectra of the high-inclination, short orbital period dwarf nova V893 Scorpii. We performed spectral analysis through radial velocity measurements, Doppler mapping, and ratioed Doppler maps. Our results indicate that V893 Sco's accretion disk is dissimilar to WZ Sge's accretion disk and does not fit any of the current accretion disk models. We derive the system parameters M1 and i and present evidence for V893 Sco as a very young cataclysmic variable and an ER UMa star. We advance the hypothesis that all ER UMa stars may be newly formed cataclysmic variables.
Cornucopia: Tool Support for Selecting Machine Learning Lifecycle Artifact Management Systems

: The explorative and iterative nature of developing and operating machine learning (ML) applications leads to a variety of ML artifacts, such as datasets, models, hyperparameters, metrics, software, and conﬁgurations. To enable comparability, traceability, and reproducibility of ML artifacts across the ML lifecycle steps and iterations, platforms, frameworks, and tools have been developed to support their collection, storage, and management. Selecting the best-suited ML artifact management systems (AMSs) for a particular use case is often challenging and time-consuming due to the plethora of AMSs, their different focus, and imprecise speciﬁcations of features and properties. Based on assessment criteria and their application to a representative selection of more than 60 AMSs, this paper introduces an interactive web tool that enables the convenient and time-efﬁcient exploration and comparison of ML AMSs.
Green Technology as a Way of Cleaning the Environment from Petroleum Substances in South-Eastern Poland.

BACKGROUND In phytoextraction methods, the problem is the obtained contaminated plant biomass, the selection of the appropriate species, resistant to the type and degree of contamination, as well as the long time needed to completely clean the soil. GOAL when selecting the appropriate method of remediation of soils contaminated with polycyclic aromatic hydrocarbons, not only the effectiveness of the method should be considered, but also the degree of contamination, the location of the site and its current and planned use. METHODS Descriptive, laboratory and comparative methods were used. RESULTS Soil contamination with polycyclic aromatic hydrocarbons (PAHs), which can cause mutations and cancer, is of particular concern as it affects not only human health but also vegetation growth and the biological environment. A fast, nature-friendly and cost-effective method is required to remove and minimize the hazardous effects of crude oil. CONCLUSIONS Green technology is particularly beneficial, especially the phytoextraction technique, in which plants clean the soil of excess petroleum products, prevent its further movement from the site of contamination and prevent erosion of reclaimed soil. Species such as: Trifolium repens, Trifolium pratense, Lotus corniculatus, Agrostis stolonifera, Festuca rubra subsp. trichophylla, Arrhenatherum elatius performed their tasks very well, therefore they can be recommended for use as a factor counteracting environmental degradation.
Phosphorene as a nanoelectromechanical material

Based on density functional simulations combined with the Landauer transport theory, the mechanical strain impacts on the chemical bonds of phosphorene and their effects on the electronic properties are studied. Moreover, the effect of the tensile strain along the zigzag direction on the charge transport properties of a two-terminal phosphorene device is evaluated. Enhancement of the intraplanar interactions, in particular between the next-nearest neighbors in strained phosphorene, is found to be essential in the band-structure evolution. The charge transport analyzing shows that phosphorene has a strong piezoconductance sensitivity, which makes this material highly desirable for high-pressure nanoelectromechanical applications. The piezoconductance gauge factor increases by strain from 46 in 5% tension to 220 in 12% tension, which is comparable to state-of-the-art silicon strain sensors. The transmission pathways monitor the current flowing in terms of the chemical bonds and hopping, however, the transport mostly arises from the charge transferring through the chemical bonds. The strong anisotropy in the transport properties along zigzag and armchair directions is observed.
Strategies to "Bitcoin-Gold" Trading Decoupling the Qualitative Decision and the Quantitative Investment

: As investment fever rises, investment strategy is a critical choice for investors. In this paper, based on the price data of gold and bitcoin from 9/11/2016 to 9/10/2021, the corresponding mathematical models are established by the LSTM, evaluation model, and single-objective optimization model in an attempt to obtain the optimal investment strategy. Firstly, the price is predicted by the LSTM model after data cleaning. The evaluation system is constructed from three perspectives: market trading intention, price stability and market environment trend. Based on the scores and thresholds of the evaluation system, the trading directions (buy, sell, hold) are obtained qualitatively. Then, based on the corrected predicted price, a single-objective optimization is established for maximizing total assets, obtaining the final investment strategy, where an initial $1,000 asset is able to reach a final total asset of $134,226 after five years. Secondly, we establish the evaluation system of investment strategies and establish three evaluation indexes of Sharpe Value, Max Drawdown, and Interest Rate in terms of both return and risk. We construct four new investment strategies with different types of investment product and model selection. Comparing the five investment strategies, we can find that our investment strategy has the highest Interest Rate, higher Sharpe Value, and smaller Max Drawdown compared with other investment strategies. Thirdly, we test the impact of transaction costs on the model and learn that the model is more sensitive to the change of bitcoin transaction costs and not sensitive to the change of gold transaction cost.
Redshift-space distortions as a probe of dark energy

Redshift-space distortions as a probe of dark energy by Liesbeth-Helena Gouws Master of Science Department of Physics University of the Western Cape We begin by finding a system of di↵erential equations for the background and linearly perturbed variables in the standard, ⇤CDM model, using the Einstein Field Equations, and then solving these numerically. Later, we extend this to dynamical dark energy models parameterised by an equation of state, w, and a rest frame speed of sound, cs. We pay special attention to the large-scale behaviour of m, the gauge invariant, comoving matter density, since the approximation m ' m, where m is the longitudinal gauge matter density, is more commonly used, but breaks down at large scales. We show how the background is a↵ected by w only, so measurements of perturbations are required to constrain cs. We examine how the accelerated expansion of the universe, caused by dark energy, slows down the growth rate of matter. We then show the the matter power spectrum is not in itself useful for constraining dark energy models, but how redshift-space distortions can be used to extract the growth rate from the galaxy power spectrum, and hence how redshift-space power spectra can be used to constrain di↵erent dark energy models. We find that on small scales, the growth rate is more dependent on w, while on large scales, it depends more on cs.
Research on the Knowledge Map in the Prediction of Bond Default

—When solving the problem of bond default, because there is a lot of relational and categorical data in the bond data, reasonable use of these data to predict bond defaults is of great significance. Based on the construction of bonding knowledge map, in this paper, knowledge representation learning is used to vectorize the knowledge of picture, and the extracted vector is input into the deepfm model as a feature to predict whether the bond will default. Compared with the general traditional bond default prediction method, in this paper, knowledge map is introduced as the feature embedding of bond default prediction model. The experimental results show that it has higher prediction accuracy.
The antibacterial activity and biochemical composition of Adansonia Digitata edible parts

PurposeWithin the framework of the valorization of natural resources, a characterization of the biochemical composition of the edible parts of Adansonia Digitata is applied. The antibacterial effect against bacteria is also realized and compared to some synthetic antibiotics.Design/methodology/approachThe biochemical characterization is carried out according to the norms of the French Association of Normalization, methods of Association of Official Analytical Chemists (AOAC International) and gas chromatography (GC). The antibacterial activity is tested by disk diffusion on a solid medium. Parametric tests are used to compare the differences between groups and heat maps to show the expression of the mean inhibitions according to the studied parameters. Multivariate logistic modeling is applied to study the effect of extracts and antibiotics on bacteria.FindingsBiochemical characterization showed a variable importance of proteins, fibers and total sugars, with the presence of highly desired fatty acids such as palmitic, oleic, stearic, linoleic and a-linolenic acids. This gives the tested parts important energy values, especially in the seeds very rich in fatty acids. Methanol proved to be a better extraction solvent than dichloromethane. Antibacterial activity showed that pulp and leaves extracted with methanol had quite similar inhibitory activities against Enterococcus faecalis ATCC29212 and that this effect was better than some antibiotics. Multivariate analysis showed that the leaves had a similar effect to antibiotics, and a significant effect against Staphylococcus aureus ATCC29213.Originality/valueThis important activity and the attractive nutritional value of this plant could justify its extensive use in the traditional pharmacopoeia.
How the Earned Income Tax Credit Sustains Informal Child-Care Arrangements with Family Members and Helps Maintain Intergenerational Relations

The earned income tax credit (EITC) is one of the largest antipoverty programs in the United States. Although extensive research suggests the EITC is linked to various positive parent and child outcomes, limited attention has been paid to how familial obligations shape ways in which the EITC is spent. Research indicates that social networks of extended family and friends can be vital to low-income families’ social and economic well-being, suggesting the importance of exploring their roles in shaping EITC spending decisions. Drawing from in-depth interviews with primarily women of color, this article reveals how some women maintain extended family caregiving arrangements through monetary gifts from their EITC. The women’s narratives illustrate how they identified the social and economic value of the caregiving and how caregiving and monetary reciprocity facilitated the maintenance of intergenerational social support; they also expose limitations of current policies designed to support care arrangements among low-income families.
Effect of nanostructure, porosity and extent of oxidation on soot reactivity

Abstract Oxidation evolutions of structure, porosity and reactivity properties of four model carbons (PU, S160, N330 and R250) with different initial reactivity were studied. Results showed that changes in the porosity and nanostructure properties instead of initial properties significantly affected the soot reactivity during the soot oxidation process. Two high-reactivity soot surrogate samples, i.e., PU and S160, initially presented turbostratic disordered crystallites, resulting in higher reactivity at the early oxidation stage. Oxidation mainly proceeded inwardly in a peeling fashion, and more disordered internal crystallites were exposed after oxidized, slightly increasing the reactivity of PU and S160. Two low reactivity soot surrogate samples, i.e., N330 and R250, initially exhibited the typical core–shell structure. The oxidation rates of N330 and R250 were lower than that of PU and S160 due to more ordered exterior crystallites and less surface oxygen content at the early oxidation stage. Once oxygen penetrated the particle core, many pores were generated. Next, the particle became hollow through internal burning of the more reactive internal carbon at the late oxidation stage. After 40% burnoff, these hollow structures promoted oxidation in both outward and inward directions. Therefore, oxidation rates of N330 and R250 significantly increased. Graphical Abstract Highlights Oxidation evolutions of structure, porosity and reactivity properties of soot were performed. Porosity and nanostructure properties dominated the soot reactivity during oxidation process. Partial oxidation led to the reactivity increase for the soot with low initial reactivity properties.
A Solid Oxide Fuel Cell Runs on Hydrocarbon Fuels with Exceptional Durability and Power Output

Solid oxide fuel cells (SOFCs) that can operate on hydrocarbon fuels offer an efficient and cost‐effective solution for electricity generation. However, broader commercialization of SOFCs is hindered by inadequate performance and limited durability due to the sluggish hydrocarbon reforming/oxidation kinetics and coking on the SOFC anode. Here it has been reported that these findings in design, synthesis, and characterization of a novel anode catalyst Ba(Zr0.8Y0.2)0.9(Ni0.5Ru0.5)0.1O3‐δ (BZYNR) that overcomes the problems, enabling direct utilization of nearly dry hydrocarbon fuels (e.g., methane, ethanol, and iso‐octane with only 3 vol% H2O) with exceptional power output for over 1000 h on both button cells and tubular cells. The outstanding performance of BZYNR is attributed to the high activity of hydrocarbon reforming and the accelerated water‐mediated carbon cleaning process on Ni‐based SOFC anode.
Technology integrated guided inquiry-based learning approach and pre-service mathematics teachers’ attitude towards learning geometry

The study investigated the effects of technology-integrated guided inquiry (TGIBL), guided inquiry (GIBL), and traditional (TRAD) strategies on pre-service mathematics teachers’ attitudes towards geometry in college of teacher educations. The study employed nonequivalent quasi-experimental design with two experimental groups and control group. A three-stage sampling method was used. The experimental groups were exposed to TGIBL (n=48) and GIBL (n=38), while comparison group (n=30) with TRAD approach. The geometry attitude scale (GAS) questionnaire was the instrument employed to collect data from 116 PSMT. A one-way analysis of covariance, multiple comparison test and paired sample t-test were used to analyze data. The results of the study revealed that pre-service mathematics teachers who were exposed to the TGIBL had gained positive attitudes towards learning geometry than their counterparts exposed to the GIBL and TRAD, respectively. Moreover, the group taught with GIBL also shown to have a statistically significant difference with TRAD on attitude. Similarly, paired sample t-test also favored post-test score. Based on the results, TGIBL and GIBL approach should be embraced in the college of teacher educations to reinforce favorable attitudes towards learning geometry among pre-service mathematics teachers.
Bounds on the neutrino flux from cosmic sources of relativistic particles

In order to facilitate the identification of possible new physics signatures in neutrino telescopes, such as neutrinos from the annihilation of neutralinos or decaying relics, it is essential to gain full control over the astrophysical inventory of neutrino sources in the Universe. The total available accretion power, the extragalactic gamma ray background and the cosmic ray proton intensity can be used to constrain astrophysical models of neutrino production in extragalactic sources. The resulting upper limit on the extragalactic muon neutrino intensity from cosmic particle accelerators Fνµ,ul≈10-6 GeV cm-2 s-1 sr-1 combined with a reasonable minimum intensity of neutrinos due to cosmic rays stored in clusters of galaxies Fνµ,min≈10-9 GeV cm-2 s-1 sr-1 demark a zone of opportunity for neutrino astronomy over a broad range of energies between 100 MeV and 1 EeV. Discovery of this neutrino background would open a new era for astronomy and provide the first unobscured view to the early Universe.
An Effective Two-stage Noise Training Methodology for Classification of Breast Ultrasound Images

: Breast cancer is one of the most common and deadly diseases. An early diagnosis is critical and in-time treat-ment can help prevent the further spread of cancer. Breast ultrasound images are widely used for diagnosis, but the diagnosis heavily depends on the radiologist’s expertise and experience. Therefore, computer-aided diagnosis (CAD) systems are developed to provide an effective, objective, and reliable understanding of medical images for radiologists and diagnosticians. With the help of modern convolutional neural networks (CNNs), the accuracy and efﬁciency of CAD systems are greatly improved. CNN-based methods rely on training with a large amount of high-quality data to extract the key features and achieve a good performance. However, such noise-free medical data in high volume are not easily accessible. To address the data limitation, we propose a novel two-stage noise training methodology that effectively improves the performance of breast ultrasound image classiﬁcation with speckle noise. The proposed mix-noise-trained model in Stage II trains on a mix of noisy images at multiple different intensity levels. Our experiments demonstrate that all tested CNN models obtain resilience to speckle noise and achieve excellent performance gain if the mix proportion is selected appropriately. We believe this study will beneﬁt more people with a faster and more reliable diagnosis.
RECOVERY RESPONSES OF SIMULATED HAIL-DAMAGED Pelargonium graveolens L’Hér. (cv. ‘Bourbon’) TO DIFFERENT MIXTURES OF BIOSTIMULANTS

The aim of this study was to determine the potential ability of biostimulant-mixtures to recover the herbage and essential oil yield, as well improve the essential oil quality, of simulated hail-damaged rose geranium ( Pelargonium graveolens L’Her.). The experiment was carried out in a 3 × 4 factorial treatment design and laid out in a randomised complete block design in a temperature-controlled greenhouse during 2019 season. Treatments consisted of three hail damage simulation levels and three biostimulant-mixtures and a control. Plants grew taller when biostimulant-mixtures were applied from levels 2 up to 3. Level 3 treatment increased the essential oil yield of plants which sustained up to 50% foliage loss, and intact plants. Citronellol and geraniol content, as well the citronellol to geraniol ratio improved with the level 2 treatment in plants that sustained 100% foliage loss. It can be concluded that the application of biostimulants-mixture should be applied from level 3 concentration to improve the herbage yield and the essential oil quality of rose geranium plants with more than 50% foliage loss. Plants with less than 50% foliage loss can be treated with a biostimulant-mixture from level 2 to improve essential oil yield and the densities of brevicollate trichomes.
ON THE ESTIMATION OF VEHICLE TRAJECTORIES WITH A MINI-UAS

Abstract. The development of effective solutions for automated vehicles ensuring high levels of safety in any scenario have to be tested in many real world conditions. Large datasets describing real user behaviors in many conditions should be collected to this aim. To this purpose, a quite attractive option is that of using Unmanned Aerial System (UAS) imagery, which can be effectively used to extract real world driver trajectories, and to extract information of interest concerning both their interactions and the context. This work aims at providing an assessment of the accuracy of the geometric information that can be extracted on users’ trajectories and to present a strategy for the estimation of the 3D shape of the involved vehicles. The obtained results show a quite remarkable performance in terms of ability of determining a proper description of the characteristics of the vehicle trajectories, i.e. speed and track.
Remanufacturing process improvement by image recognition methods. Application of the mechanical part

The paper describes the possibility of using, building, and implementing an image recognition system in a company performing remanufacturing processes. It is based on a thesis prepared with the help of Wabco Reman Solutions. The tests were conducted using one of the parts remanufactured by the company – a manifold. The research focuses on different variants of the obtained image recognition models in order to identify differences that may affect their effectiveness and possible application in real work conditions. The environment used to build the models is Jupyter Notebook, and convolutional neural networks were implemented.
Dynamically monitoring lymphatic and vascular systems in physiological and pathological conditions of a swine model via a portable NIR-II imaging system with ICG

Objective: NIR-II imaging with indocyanine green (ICG) has been clinically used in liver tumor resection. However, few data are available concerning the application of ICG-NIR-II in lymphatic and vascular systems in clinic. To expand the application and promote the clinical translation of this approach, we aimed to investigate the feasibility of ICG-NIR-II imaging for monitoring both lymphatic and vascular systems in physiological and pathological conditions using a swine model and compared it to ICG-NIR-I imaging. Methods: we constructed a portable NIR-II imaging system suitable for large animals. Different simulated clinical scenarios in lymphatic and vascular systems of pigs, including lymphatic drainage, lymphorrhea, lymphatic obstruction, lymphatic reconstruction in flaps, venous thrombus formation and vascular anastomosis were modeled to evaluate the reliability of our NIR-II imaging system and the imaging quality of ICG in the NIR-I/II window. Results: Under different simulated clinical scenarios, our portable NIR-II imaging system showed good reliability for pigs. With the help of the portable imaging system, dynamical visualization of lymph vessels, lymph nodes and blood vessels of pigs in different clinical scenarios could be achieved in NIR-II imaging by using the tail fluorescence of ICG. Moreover, ICG-NIR-II imaging has lower background fluorescence and higher resolution than ICG-NIR-I imaging. Conclusions: We demonstrated the first application of a portable NIR-II imaging system for dynamically monitoring both lymphatic and vascular systems in physiological and pathological conditions using a swine model. Our study indicates that ICG-NIR-II imaging be a promising approach for the diagnosis of malfunctions in lymphatic and vascular systems and the surgical navigation of microsurgery and reconstructive surgery.