Miracle-dz/UniFAR-FTUs huggingface dataset:
Iprodione content of wines: where do we draw the line?

Abstract In order to define a safer, yet realistically attainable, limit for iprodione in commercial wine‐making, its concentrations were measured in 546 finished commercial wines using a high‐performance liquid chromatography method with an ultra‐violet detector. They were also measured in bulk raw wines and juices totalling 1782 and 1875, respectively, over a 5 year period from 1992 to 1997 using a gas chromatograph linked to a nitrogen‐phosphorous detector. In only 2.5% of the commercial wines did the iprodione concentration exceed 300 μg l‐1, most frequently in wines from New York, New Zealand and Oregon. Of the raw wines and juices, the proportion of products with iprodione concentrations 300 μg l‐1. Such high values were found much more commonly in white raw wines and juices than in red, but there was no significant difference in the incidence of values > 300 μg l.
Dependence of F atom density on pressure and flow rate in CF4 glow discharges as determined by emission spectroscopy

The dependence of the density of atomic fluorine as a function of pressure and flow rate in CF4 glow discharges has been measured using emission spectroscopy. The emission intensity of the 7037 A line of atomic fluorine and of the 7504 A line of argon, which is added to the CF4 discharge in small quantities (1%–2%), is used to deduce the F atom density. It is found that the pressure dependence of the F atom emission intensity alone is a poor indicator of the relative F atom concentration because the excitation efficiency of the CF4 discharge decreases rapidly with increasing pressure. The F atom density decreases with increasing flow rate as is to be expected if the lifetime of the F atom is determined largely by the vacuum pump. However, at low flow rates the F atom density is determined primarily by contaminant gases, in this case CO and CO2, through several mechanisms which are discussed.
Electrostatically Assembled Fluorescent Thin Films of Rare-Earth-Doped Lanthanum Phosphate Nanoparticles

We report on the formation of nanostructured, ultrathin films of a new class of fluorescent nanoparticles (NPs) within the same size range as quantum dots, but with a different kind of fluorescence, by using the layer-by-layer (LbL) technique. The fluorescence of these rare-earth-doped lanthanum phosphate (LaPO4) NPs is due to the bulk properties of the material and is therefore independent of their size. Additionally, different colors are available due to variation of the dopants used in their synthesis (e.g., Ce, Tb, Eu, and Dy). These NPs were electrostatically assembled to form thin films on planar quartz supports as well as on polystyrene (PS) microspheres with the aid of oppositely charged polyelectrolyte interlayers. Regular growth of the multilayers was observed on both quartz and PS substrates, providing control over the composition and, in turn, the fluorescence intensity of the planar films and composite spheres. The resulting films exhibit the same UV and fluorescence characteristics as the co.
Style Transfer Using Whitening and Coloring to Realize Feature Transformation

This paper proposes a general image style transfer method based on VGG network. This method does not need to learn and pre-train any kind of style in advance. The algorithm mainly implements the style transfer task by reconstructing the automatic decoder. In the process of feature extraction, the algorithm matches the content features and style features through whitening and coloring. We conducted a series of experiments with different photographic images. The experimental results show that our method has a simple training process, low computational complexity and high computational speed and excellent generalization ability.
GeoGebra as learning tool for the search of the roots of functions in numerical methods

Physics is capable of describing, through equations, phenomena on a micro and macroscopic scale. However, most of these equations are non-linear and the identification of their roots requires the use of approximation methods, with numerical methods being a proposal based on a systematic and iterative process, that conclude only when a pre-established tolerance is satisfied. Traditional teaching of numerical methods involves the memorization of algorithms. However, this hinders student’s ability to understand the important aspects and then apply them for solving applied problems in subjects such as kinematics, dynamics, electromagnetism, etc. Therefore, this work proposes the use of GeoGebra, as a didactic tool to illustrate the functioning of single root searching algorithms. By using the dynamical graphic’s view of GeoGebra, a series of abstract and applied problems where solved by engineering students taking a numerical methods course. The scores of this test group was then compared to a test group, taught trough algorithm memorization. Results show can improve their understanding of how the bisection, false position, secant, and Newton-Raphson methods are able to find approximated solutions to polynomial and trigonometric equations. The results are compared against traditional learning, based on memorizing the steps of the algorithm for each method and the representation of the convergence of successive roots by numerical tables.
Learning Partial Differential Equations from Noisy Data using Neural Networks

The problem of learning partial differential equations (PDEs) from given data is investigated here. Several algorithms have been developed for PDE learning from accurate data sets. These include using sparse optimization for approximating the coefficients of candidate terms in a general PDE model. In this work, the study is extended to spatiotemporal data sets with various noise levels. We compare the performance of conventional and novel methods for denoising the data. Different architectures of neural networks are used to denoise data and approximate derivatives. These methods are numerically tested on the linear convection-diffusion equation and the nonlinear convection-diffusion equation (Burgers’ equation). Results suggest that modification in the hidden units/hidden layers in the network architecture have an effect on the accuracy of approximations with a significant rate. This is a further improvement on the previously known denoising methods of finite differences, polynomial regression splines and single layer neural network.
Nativized Texts: Cultural Clues' Role in Improving EFL Undergraduates' Reading Comprehension

Even though many studies were carried out regarding the role of cultural background knowledge in reading comprehension, still rare studies were carried in the surrounding area. Accordingly, this study aimed at exploring the potential effect of cultural clues on Al al- Bayt University undergraduates' reading comprehension at three levels: literal, inferential, and evaluative. To achieve this, seven passages, each with two versions: the original and nativized, were selected from the textbook taught at Al al- Bayt University, situated in Mafraq in the north of Jordan. The researcher used pre-experimental design (i.e., One-group pretest-posttest design). In this design, a single case is observed at two-time points (repeated measures), one before the treatment (O1), and one after the treatment (O2). Subjects were thirty-eight EFL undergraduates selected by the researcher from Al al- Bayt University in the second semester of the academic year 2019/2020.To carry out the study, all expressions and clues that carry cultural aspects in the original passages were replaced by other expressions reflecting the Jordanian culture in the nativized ones. The students then were asked to read the two versions and answer different types of questions to collect the data aimed at measuring literal, inferential, and evaluative comprehension over the two versions of each passage. The collected data were analyzed using quantitative analyses. The study's findings revealed that cultural familiarity through applying nativization positively affected students' reading comprehension. More interesting is that text nativization did affect the literal level of comprehension and the inferential and evaluative ones. The current study would be fruitful for instructors and teachers in Jordan to help them develop reading comprehension in a way that would improve students' comprehension.
Moisture Content Prediction in the Switchgrass (Panicum virgatum) Drying Process Using Artificial Neural Networks

This article proposes two artificial neural network (ANN)-based models to characterize the switchgrass drying process: The first one models processes with constant air temperature and relative humidity and the second one models processes with variable air conditions and rainfall. The two ANN-based models proposed estimated the moisture content (MC) as a function of temperature, relative humidity, previous MC, time, and precipitation information. The first ANN-based model describes MC evolution data more accurately than six mathematical empirical equations typically proposed in the literature. The second ANN-based model estimated the MC with a correlation coefficient greater than 98.8%.
Based on Adam Optimization Algorithm: Neural Network Model for Auto Steel Performance prediction

Neural network is optimized using the Adam algorithm, which introduces the first-order and second-order momentum of gradient. At the same time, learning rate is dynamically adjusted to different training stages to avoid the network from slow converging or oscillating. The three-layer neural network model is trained with a 5000 samples data set for HSLA steel performance prediction. The result shows that: compared with the traditional SGD algorithm, Adam shows efficient and stable training characteristics. After 742 epochs with initial learning rate of 0.001, the mean square error (MSE) of training set and validation set are below 90. On a data set consisting of 50 new samples, the prediction error of the yield strength and tensile strength on test set are less than 19MPa and 22MPa respectively, and the elongation prediction error is less than 3.1%.
Wavelengths, Transition Probabilities, and Energy Levels for the Spectra of Sodium (NaI–NaXI)

Energy levels, with classifications and uncertainties, have been compiled for the spectra of the neutral atom and all positive ions of sodium (Z=11). Wavelengths with classifications, intensities, and transition probabilities are also tabulated. In addition, ground states and ionization energies are listed. Where available, the hyperfine structure constants and the percentages of the leading components of the energy levels are included. For all ionization stages of sodium, at least some experimental data are available; however, for those for which only a few transitions have been measured, theoretical calculations or values obtained by isoelectronic fitting are reported. Similarly, theoretical or isoelectronically determined ionization energies are given when they are thought to be more accurate than the available experimental data would produce.
Phase space interpretation of semiclassical theory

A useful and intuitive phase space picture of common semiclassical approximations and procedures is proposed and developed. Underlying the intuitive pictures is the semiclassical, C→0 limit of the Wigner distribution, which is discussed in an Appendix. Simple classical analog phase space diagrams are suggested which represent quantum amplitudes, completeness relations, stationary phase points and integrations, caustic singularities, uniformizations, and the interesting short and long time behavior of the semiclassical propagator. Semiclassical wave packet amplitudes, now known to be on equal footing with the more usual amplitudes between delocalized eigenstates of Hermitian operators, are included in the phase space pictures. It becomes apparent why the primitive semiclassical wave packet amplitudes are to some extent uniformizing, and numerical results are presented to support this conclusion. The power of the phase space picture as an aid in formulating new approximations is illustrated.
Ecopath modelling approach for the impact assessment of a small-scale coastal aquaculture system in Goa, India

In this study, the ecological impacts of introduction of cage aquaculture employing small cages integrating shellfish and finfish in coastal water bodies of Goa, situated in the west coast of India were analysed using Ecopath with Ecosim model. A multispecies cage aquaculture system incorporating Lutjanus argentimaculatus, Etroplus suratensis and Perna viridis was established in an estuarine ecosystem. The Ecopath model identified 12 functional groups starting from detritus (trophic level=1) to large benthic carnivores (trophic level=3.72). The ecosystem statistics such as total system throughput (8672 g m-2 year-1), gross efficiency (0.001), primary production/respiration (1.4), net system production (1028.2 g m-2 year-1) and system omnivory index (0.26) indicated that the ecosystem was highly productive and in a developing stage. With a medium rate of recycling (Finn’s Cycling Index=11.7%), high system throughput, high system overhead (79%) and moderate omnivory index (0.26), the food web was found to be immature having an organised trophic network with high production. Simulations of the various expanding scenarios for the cage culture within the ecosystem were explored using Ecosim. A scenario in which two cages each for pearlspot and red snapper and 20 mussel ropes was identified as a sustainable solution without sacrificing the threshold biomass for the functional groups of fish species. The study provided useful insights and methodology towards assessing aquaculture in coastal ecosystems in terms of ecosystem structure and function.
Model Identification and Equivalence Method for Grid Optimal Operation

In this paper, on the basis of simplification idea of external transfer consistence of internal power flow in power grid, the network identification method was used to find the local power grid with equivalent value, and WARD equivalent value was used to equalize the local power grid to the boundary node, because the power transfer relationship between internal nodes and boundary nodes of equivalent power grid is basically consistent, equivalent unit could reflect the overall output characteristics of equivalent power grid, there was no need to concern the power distribution of internal node of equivalent power grid, furthermore, the schedulable capacity and cost curve of schedulable resources of equivalent power grid could be calculated, on this basis, the dispatching optimization of power generation of large power grid were conducted. The example analysis showed that the equivalent method in this paper could maintain higher model equivalent accuracy, and the overall optimal solution of power generation dispatching of large-scale power grid was realized.
Research on the Application of College Physical Education Teaching Mode in the Cloud Computing Environment

With the development of educational informationization in Colleges and universities, cloud computing technology has become the main means of educational informationization in Colleges and universities. The application of educational information technology in college physical education promotes the integration with physical education. It realizes the transformation of physical education teaching mode and physical learning mode in Colleges and universities, gives full play to the greatest advantage of information technology, and provides students with a good education environment and a scientific and effective learning tool. This paper studies the application of physical education in the cloud computing environment. This paper investigates the current situation of College Physical Education in the cloud computing environment, analyzes and summarizes the problems in the process of college physical education teaching, and gives the corresponding countermeasures and suggestions. It can provide theoretical basis and reference for the future application of cloud computing in college physical education. From the point of view of physical education, this paper studies the relationship between education informatization and physical education, explores new physical education teaching mode, improves the use of school physical education informatization, creates a good teaching atmosphere, and promotes the improvement of teaching quality.
OSSOS. XXI. Collision Probabilities in the Edgeworth–Kuiper Belt

Here, we present results on the intrinsic collision probabilities, P I , and range of collision speeds, V I , as a function of the heliocentric distance, r, in the trans-Neptunian region. The collision speed is one of the parameters that serves as a proxy for a collisional outcome (e.g., disruption and scattering of fragments, or formation of a crater, as both processes are related to the impact energy). We utilize an improved and debiased model of the trans-Neptunian object (TNO) region from the “Outer Solar System Origins Survey” (OSSOS). It provides a well-defined model of TNO orbital distribution, based on multiple opposition observations of more than 1000 bodies. We compute collisional probabilities for the OSSOS models of the main classical, resonant, detached+outer, and scattering TNO populations. The intrinsic collision probabilities and collision speeds are computed using Öpik’s approach, as revised and modified by Wetherill for noncircular and inclined orbits. The calculations are carried out for each of the dynamical TNO groups, allowing for inter-population collisions as well as collisions within each TNO population, resulting in 28 combinations in total. Our results indicate that collisions in the trans-Neptunian region are possible over a wide range in (r, V I ) phase space. Although collisions are calculated to happen within r ∼ 20–200 au and V I ∼ 0.1 km s−1 to as high as V I ∼ 9 km s−1, most of the collisions are likely to happen at low relative velocities V I < 1 km s−1 and are dominated by the main classical belt.
Improving Performance of Python Code Using Rewriting Rules Technique

Python is a popular programming language used in many areas, but its performance is significantly lower than many compiled languages. We propose an approach to increasing performance of Python code by transforming fragments of code to more efficient languages such as Cython and C++. We use high-level algebraic models and rewriting rules technique for semi-automated code transformation. Performance-critical fragments of code are transformed into a low-level syntax model using Python parser. Then this low-level model is further transformed into a high-level algebraic model that is language-independent and easier to work with. The transformation is automated using rewriting rules implemented in Termware system. We also improve the constructed high-level model by deducing additional information such as data types and constraints. From this enhanced high-level model of code we generate equivalent fragments of code using code generators for Cython and C++ languages. Cython code is seamlessly integrated with Python code, and for C++ code we generate a small utility file in Cython that also integrates this code with Python. This way, the bulk of program code can stay in Python and benefit from its facilities, but performance-critical fragments of code are transformed into more efficient equivalents, improving the performance of resulting program. Comparison of execution times between initial version of Python code, different versions of transformed code and using automatic tools such as Cython compiler and PyPy demonstrates the benefits of our approach – we have achieved performance gains of over 50x compared to the initial version written in Python, and over 2x compared to the best automatic tool we have tested.
Organic chemistry of fullerenes: the major reactions, types of fullerene derivatives and prospects for practical use

Data on the methods of functionalisation of C60 and C70 fullerenes published over the last 15 years are summarised. The general analysis of fullerene reactivity is performed. Nucleophilic and radical addition and cycloaddition reactions are considered in detail. The prospects of using fullerene derivatives as medical drug and photoactive materials for light converting devices are demonstrated.
Patient Satisfaction in Medicine and Dentistry: A Need to Advance to a Patient-Reported Outcome Measures (PROMs) Culture in Surgical Sciences

There is little understanding of patients' experiences and perceptions with satisfaction by health professionals such as medical and dental clinicians. Furthermore, patient satisfaction is not well understood. The objective of this article is to better understand patients' satisfaction with their medical and dental care. The methods of the current article are based on a narrative review of the literature strategy. Patient satisfaction's multidimensional nature has been established since the perceived reasons for satisfaction varied widely among patients. Many aspects of the treatment influence participant satisfaction at different stages of the intervention's process. An improved understanding of the basis for managing patients' expectations with information reiteratively and efficiently may ultimately reduce patients' potential for negative feelings toward the medical and dental treatment experience. The consumerist method may misrepresent the concept of satisfaction in health service.
IN VITRO EVALUATION OF LECTINIZED CISPLATIN BEARING LIPOSOMES SYSTEM

Objective: The purpose of this study was to evaluate the extent and mechanism anti-cancer drug-loaded liposomes using wheat germ agglutinin as a guiding molecule. Methods: For the drug-loaded liposome synthesis, the thin film hydration method was used and the drug cisplatin was loaded during the synthesis and followed by the surface modification using wheat germ agglutinin (WGA) lectin. The developed system was confirmed based on transmission electron microscopy (TEM), atomic force microscopy (AFM), particle size (PS) analyzer, polydispersity index and Zeta Potential analyzer. Results: The results showed the surface modified by liposomes had the particle size 200±5 nm. The wheat germ agglutinin coated on the surface to liposome led to a reduction in zeta potential and drug entrapment efficiency while particle size increased. Plain liposomes containing cisplatin had less effect than WGA modified liposome on MCF-7 cell lines. Conclusion: The MTT studies indicated that the drug molecules were initially get delivered to the inside the cell. This formulation offered new simple approach and effectively kill the cells via targeting the nucleus.
UPLC-DAD determination of taxodione content in hairy roots of Salvia austriaca Jacq.

Taxodione is the abietane diterpenoid, which has been earlier reported to show cytotoxic, antitumor, antibacterial, and antioxidant properties. This compound has been isolated from a genetically transformed root culture of Salvia austriaca. However, no method for taxodione quantification is yet available. A validated ultra-performance liquid chromatography-diode array detector (UPLC-DAD) method was developed for the quantification of taxodione in a hexane extract taken from genetically transformed roots of S. austriaca. The developed UPLC-DAD method demonstrated good linearity in the range 10–500 μg mL−1 (r2 = 0.99988), high precision (relative standard deviation (RSD) <1.42%), and good repeatability (RSD <1.84%). The limits of detection and quantification of taxodione were found to be 0.48 ng and 1.60 ng, respectively. The recovery of taxodione ranged between 90.4 and 113.1%, and the RSD was less than 2.5%. The developed UPLC-DAD method was then used to determine the content of taxodione in various hairy .