Miracle-dz/UniFAR-FTUs huggingface dataset:
Curricular Concept Maps as Structured Learning Diaries: Collecting Data on Self-Regulated Learning and Conceptual Thinking for Learning Analytics Applications

The collection and selection of the data used in learning analytics applications deserve more attention. Optimally, selection of data should be guided by pedagogical purposes instead of data availability. Using design science research methodology, we designed an artifact to collect time-series data on students’ self-regulated learning and conceptual thinking. Our artifact combines curriculum data, concept mapping, and structured learning diaries. We evaluated the artifact in a case study, verifying that it provides relevant data, requires a limited amount of effort from students, and works in different educational contexts. Combined with learning analytics applications and interventions, our artifact provides possibilities to add value for students, teachers, and academic leaders.
Correlation between iron metabolism and development of breast cancer in pre- and postmenopausal women

reduces the loss of iron. This can lead to the body overload with this element and strengthen the process of carcinogenesis by accelerating the production of reactive oxygen species (ROS). Improper turnover of iron in the body does not have to be associated with dietary habits. Iron metabolism is strictly controlled by several proteins so as to pre-vent the excessive accumulation of free form of this element in the body. Ferritin, ferroportin, transferrin and its receptor play a role in tumor growth, because rapidly proliferating cells have a high demand for iron. Changes in the metabolism of this element can thus be an early symptom of the cancer in women both prior to and after menopause.
ENERGETIC EFFICIENCY OF AGRICULTURAL PLANTATIONS DEDICATED FOR BIOFUEL PRODUCTION

A deterministic model of “energetic” plantation aimed towards biofuel production is formulated in order to evaluate fluxes of energy occurring during subsequent agro-technical operations. The agro-technical production system, in general, is considered as a part of larger system that includes also industrial part dedicated to processing of crops to biofuel, at present stage of research it is, however, considered separately. The scale of production, resulting of the demand of industrial part of the system, is implicitly considered. The derived efficiency indicator, that principally corresponds to EROEI, indicates that one of the most important factors decreasing energetic efficiency of plantation is transportation of goods and machinery outside of cultivated fields. Contribution of transport term depends upon the distances driven outside of the fields, and therefore depends upon the size of production – controlled by the demand from the industrial part. (Because it seems impossible to find continuous field of required size). The other factors are the yield of plantation and technical characteristics of machinery being used.
Study of anisotropic strength properties of shale

Shale has been known to be the source of wellbore instability during the drilling process. Organic rich shales are anisotropic due to their laminated structure and chemical properties. The goal of this study is to evaluate anisotropic mechanical properties of shale by triaxial tests, and predict shale anisotropic properties by well logging data interpretation. Shale samples were prepared with bedding plane inclination angles equal to 0 degrees, 45 degrees, and 90 degrees. Young's modulus, shear modulus, and Poisson’s ratio in different directions were measured for a sample with 0 degrees bedding plane inclination angle. Parameters of the stiffness tensor were calculated by mechanical properties. Compressive strength was measured under different confining pressures of 0 psi, 500 psi, 1000 psi, and 1500 psi. The strength properties of shale samples were evaluated by both compressive strength and tensile strength. Simple Plane of Weakness and Modified Cam Clay failure criteria were applied to describe shear failure mechanisms. A scanning electron microscope method was used for the comparison of micro structures between the intact shale sample and failed sample with different bedding plane inclination angles. Well logging data was used to connect experimental lab data and field data. Compressional wave velocity was predicted with different inclination angles by stiffness parameters. The predicted compressional wave velocity for a 45-degree inclination angle showed a perfect fit with the field logging data. Steps of inverse sonic log data to stiffness parameters were shown by a flow chart. The UCS strength for 0 degrees and 45 degrees was predicted by several empirical relations using sonic logging data. The safe mud window for this special shale formation is predicted by experimental data. As shown in experimental results, our shale sample has a weak direction for both failure criteria. Well logging data and experimental data can be connected, especially by sonic log data. However, to predict shale anisotropic strength through well logging still requires more effort. The novelty of the process which connects experimental results and well logging data will be helpful for solving instability problems occurring in shale formation.
Wafer Map Defect Classification with Depthwise Separable Convolutions

In the IC design process, the test process is the main factor of production cost. Existing tests rely on additional analysis of testing result data by the engineer to determine the status of the process. Thus it could take an additional amount of time and cannot make adjustments of the process immediately. Wafer map defect recognition is an import part of semiconductor. There is lots of information in wafer maps which can quickly help engineers to identify what failure type it is. The location of the error point is graphical represented and the relationship of these points contains the feature of this map. In this paper, we proposed a classifier with reduced-weight architecture based on depthwise separable convolutions. The entire work is verified by using the real-world wafer map dataset (WM-811K). The accuracy is 96.63% in test set.
Polyphenol based adhesives for the production of agglomerate cork stoppers Synthesis and applications

In synthetic organic adhesives the emission of harmful substances is a serious problem, which is usually caused by the use of volatile organic solvents and evaporation of unreacted monomers. In the case of polyurethane based binders, they are formed by reaction of polyols with isocyanates, which derivate from non-renewable sources. The volatility in the price of these raw-materials, and the fact that they come from non-renewable sources, has made many companies seek for bio-based alternatives. In this particular case, since the objective is the production of agglomerate cork stoppers, which are used in contact with many different alcoholic beverages (wine, champagne, whisky, etc), there are a pressure in the consumer market to come up with bio-based adhesives which could be safe and without free monomers. With this objective in mind, the main goal of this study has been to develop one-component, thermo-curable adhesives based on natural sources, with solid contents between 50 to 60%, of which over 75% at 80% are adhesive components, and a viscosity between 500 and 4000 cP. Tests carried out have shown good behavior of gelatin and polyethylenimine as crosslinking agents, as an alternative to formaldehyde in the polymerization process of polyphenolic tannins. Torsion tests were showed that we can observe torsion momentums similar to a polyurethane based resin, but has a maximum angle below expectations. Yet the development of this adhesive is not finished, and some of its characteristics may still be improved.
Examining Hyper-Reactivity to Defecation-Related Sensations in Children With Functional Defecation Disorders (FDD)

Background: Adequate sensory perception and reactivity to sensory stimuli associated with defecation is key to successful stool toileting. Preliminary reports suggests that some of the difficulties that many children with FDD experience with toileting could be related to sensory hyper-reactivity. Objective: This study investigated the relationship between sensory hyper-reactivity and functional defecation disorders (FDD). Methods: Parents of three to six-year-old children with and without FDD completed two questionnaires; the Toileting Habit Profile Questionnaire-Revised (THPQ-R; tool that measures sensory hyper-reactivity to defecation related sensations) and the Short Sensory Profile (SSP). On both questionnaires, low scores indicate more concerns. Between group comparisons and the relationship between scores on the THPQ-R and on the sensory hyper-reactivity items of the SSP were examined. Results: The sensory hyper-reactivity mean score of the SSP was lower for children with FDD. The difference was statistically significant (p < .0005). There was a positive correlation between THPQ-R and SSP hyper-reactivity scores (r274 = .485, p < .0005). Further, higher levels of sensory hyperreactivity (low SSP score) were associated with a higher frequency of the challenging defecation behaviors described in the THPQ-R (low THPQ-R score). Conclusion: Health practitioners do not usually consider sensory hyper-reactivity as a possible factor contributing to the difficulties of the child with FDD. Our results indicate that routine screening for sensory hyper-reactivity may be an important practice element when working with children with FDD. In addition, the present study adds support to the validity of the THPQ-R in identifying behaviors potentially linked to sensory hyper-reactivity.
Photocontrolled DNA minor groove interactions of imidazole/pyrrole polyamides

Azobenzenes are photoswitchable molecules capable of generating significant structural changes upon E-to-Z photoisomerization in peptides or small molecules, thereby controlling geometry and functionality. E-to-Z photoisomerization usually is achieved upon irradiation at 350 nm (π–π* transition), while the Z-to-E isomerization proceeds photochemically upon irradiation at >400 nm (n–π* transition) or thermally. Photoswitchable compounds have frequently been employed as modules, e.g., to control protein–DNA interactions. However, their use in conjunction with minor groove-binding imidazole/pyrrole (Im/Py) polyamides is yet unprecedented. Dervan-type Im/Py polyamides were equipped with an azobenzene unit, i.e., 3-(3-(aminomethyl)phenyl)azophenylacetic acid, as the linker between two Im/Py polyamide strands. Only the (Z)-azobenzene-containing polyamides bound to the minor groove of double-stranded DNA hairpins. Photoisomerization was exemplarily evaluated by 1H NMR experiments, while minor groove binding of the (Z)-azobenzene derivatives was proven by CD titration experiments. The resulting induced circular dichroism (ICD) bands of the bound ligands, together with the photometric determination of the dsDNA melting temperature, revealed a significant stabilization of the DNA upon association with the ligand. The (Z)-azobenzene acted as a building block inducing a reverse turn, which favored hydrogen bonds between the pyrrole/imidazole amide and the DNA bases. In contrast, the E-configured polyamides did not induce any ICD characteristic for minor groove binding. The incorporation of the photoswitchable azobenzene unit is a promising strategy to obtain photoswitchable Im/Py hairpin polyamides capable of interacting with the dsDNA minor groove only in the Z-configuration.
Use of machine learning to improve simulations of climate

Global climate models represent small-scale processes such as clouds and convection using quasi-empirical models known as parameterizations, and these parameterizations are a leading cause of uncertainty in climate projections. A promising alternative approach is to use machine learning to build new parameterizations directly from high-resolution model output. However, parameterizations learned from three-dimensional model output have not yet been successfully used for simulations of climate. Here we use a random forest to learn a parameterization of subgrid processes from output of a three-dimensional high-resolution atmospheric model. Integrating this parameterization into the atmospheric model leads to stable simulations at coarse resolution that replicate the climate of the high-resolution simulation. The parameterization obeys physical constraints and captures important statistics such as precipitation extremes. The ability to learn from a fully three-dimensional simulation presents an opportunity for learning parameterizations from the wide range of global high-resolution simulations that are now emerging.
Coupled Tensor Completion via Low-rank Tensor Ring

The coupled tensor decomposition aims to reveal the latent data structure which may share common factors. Using the recently proposed tensor ring decomposition, in this paper we propose a non-convex method by alternately optimizing the latent factors. We provide an excess risk bound for the proposed alternating minimization model, which shows the improvement in completion performance. The proposed algorithm is validated on synthetic data.
Improved bound on vertex degree version of Erdős matching conjecture

For a k $k$ ‐uniform hypergraph H $H$ , let δ 1 ( H ) ${\delta }_{1}(H)$ denote the minimum vertex degree of H $H$ , and ν ( H ) $\nu (H)$ denote the size of the largest matching in H $H$ . In this paper, we show that for any k ≥ 3 $k\ge 3$ and β > 0 $\beta \gt 0$ , there exists an integer n 0 ( β , k ) ${n}_{0}(\beta ,k)$ such that for positive integers n ≥ n 0 $n\ge {n}_{0}$ and m ≤ ( k 2 ( k − 1 ) − β ) n k $m\le (\frac{k}{2(k-1)}-\beta )\frac{n}{k}$ , if H $H$ is an n $n$ ‐vertex k $k$ ‐graph with δ 1 ( H ) > n − 1 k − 1 − n − m k − 1 ${\delta }_{1}(H)\gt \left(\genfrac{}{}{0ex}{}{n-1}{k-1}\right)-\left(\genfrac{}{}{0ex}{}{n-m}{k-1}\right)$ , then ν ( H ) ≥ m $\nu (H)\ge m$ . This improves upon earlier results of Bollobás, Daykin, and Erdős for the range n > 2 k 3 ( m + 1 ) $n\gt 2{k}^{3}(m+1)$ and Huang and Zhao for the range n ≥ 3 k 2 m $n\ge 3{k}^{2}m$ .
A Serological Survey of Bisphenol A in Shenzhen City

Objective To understand the population serum level of bisphenol A to provide scientific basis for relationship between bisphenol A and reproductive health among the exposures. Methods Bisphenol A serum levels were determined by HPLC (high-performance liquid chromatography) in 100 workers with occupational bisphenol A exposure and compared with 100 controls without exposure. Results Serum bisphenol A was positive among the exposed group, their serum levels were 27.16 μg/L, and the maximum was 41.61 μg/L. While the positive rate of the control group was 51%, and the serum levels ranged between 0.58 μg/L to 13.54 μg/L. Conclusions The serum positive rate of bisphenol A shows significant difference between the exposure group vs. the control group.
Fastest Frozen Temperature for a Degree of Freedom

The equipartition theorem states that the mean thermal energy for each degree of freedom at a temperature $T$ is given by $k_{B}T/2$ where $k_{B}$ is Boltzmann's constant. However, this theorem for the degree of freedom breaks down at lower enough temperature when the relevant degree of freedom is not thermally excited. The frozen condition can be \textit{qualitatively} expressed as $T\ll T_{C}$ which is the characteristic temperature defined via $k_{B}T_{C}\equiv\varepsilon_{1}-\varepsilon_{0}$ in which $\varepsilon_{0}$ and $\varepsilon_{1}$ are, respectively, the ground state and first excited energy of the degree of freedom. This characteristic temperature $T_{C}$ so defined is the temperature at which the degree of freedom is almost activated. We report that there is a well-defined temperature at which the specific heat coming from the given degree of freedom \textit{changes most dramatically} with temperature, i.e., the derivative of the specific heat with respect to temperature reaches its maximum. For some system such as a mixture of ortho- and para- hydrogen molecules, the characteristic temperature is hard to define, the fastest frozen temperature is also straightforward and well-defined. In general, the fastest frozen temperature is a \emph{quantitative}\textit{\ }criterion of the frozen temperature.
Type Ia supernova sub-classes and progenitor origin

Abstract This paper presents a short review on the current state of SN Ia progenitor origin. Type Ia supernova explosions (meaning thermonuclear disruption of a white dwarf) are observed to be widely diverse in peak luminosity, lightcurve width and shape, spectral features, and host stellar population environment. In the last decade alone, theoretical simulations and observational data have come together to seriously challenge the long-standing paradigm that all SNe Ia arise from explosions of Chandrasekhar mass white dwarfs. In this review I highlight some of the major developments (and changing views) of our understanding of the nature of SN Ia progenitor systems. I give a brief overview of binary star configurations and their plausible explosion mechanisms, and infer links between some of the various (observationally-categorized) SN Ia sub-classes and their progenitor origins from a theoretical standpoint.
Two Faced Janus of Quantum Nonlocality

This paper is a new step towards understanding why “quantum nonlocality” is a misleading concept. Metaphorically speaking, “quantum nonlocality” is Janus faced. One face is an apparent nonlocality of the Lüders projection and another face is Bell nonlocality (a wrong conclusion that the violation of Bell type inequalities implies the existence of mysterious instantaneous influences between distant physical systems). According to the Lüders projection postulate, a quantum measurement performed on one of the two distant entangled physical systems modifies their compound quantum state instantaneously. Therefore, if the quantum state is considered to be an attribute of the individual physical system and if one assumes that experimental outcomes are produced in a perfectly random way, one quickly arrives at the contradiction. It is a primary source of speculations about a spooky action at a distance. Bell nonlocality as defined above was explained and rejected by several authors; thus, we concentrate in this paper on the apparent nonlocality of the Lüders projection. As already pointed out by Einstein, the quantum paradoxes disappear if one adopts the purely statistical interpretation of quantum mechanics (QM). In the statistical interpretation of QM, if probabilities are considered to be objective properties of random experiments we show that the Lüders projection corresponds to the passage from joint probabilities describing all set of data to some marginal conditional probabilities describing some particular subsets of data. If one adopts a subjective interpretation of probabilities, such as QBism, then the Lüders projection corresponds to standard Bayesian updating of the probabilities. The latter represents degrees of beliefs of local agents about outcomes of individual measurements which are placed or which will be placed at distant locations. In both approaches, probability-transformation does not happen in the physical space, but only in the information space. Thus, all speculations about spooky interactions or spooky predictions at a distance are simply misleading. Coming back to Bell nonlocality, we recall that in a recent paper we demonstrated, using exclusively the quantum formalism, that CHSH inequalities may be violated for some quantum states only because of the incompatibility of quantum observables and Bohr’s complementarity. Finally, we explain that our criticism of quantum nonlocality is in the spirit of Hertz-Boltzmann methodology of scientific theories.
Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution

Click-through rate (CTR) prediction is an essential task in industrial applications such as video recommendation. Recently, deep learning models have been proposed to learn the representation of users' overall interests, while ignoring the fact that interests may dynamically change over time. We argue that it is necessary to consider the continuous-time information in CTR models to track user interest trend from rich historical behaviors. In this paper, we propose a novel Deep Time-Stream framework (DTS) which introduces the time information by an ordinary differential equations (ODE). DTS continuously models the evolution of interests using a neural network, and thus is able to tackle the challenge of dynamically representing users' interests based on their historical behaviors. In addition, our framework can be seamlessly applied to any existing deep CTR models by leveraging the additional Time-Stream Module, while no changes are made to the original CTR models. Experiments on public dataset as well as real industry dataset with billions of samples demonstrate the effectiveness of proposed approaches, which achieve superior performance compared with existing methods.
The X-shooter Spectral Library (XSL): Data release 2

We present the second data release (DR2) of the X-shooter Spectral Library (XSL), which contains all the spectra obtained over the six semesters of that program. This release supersedes our first data release from Chen et al. (2014, A&A, 565, A117), with a larger number of spectra (813 observations of 666 stars) and with a more extended wavelength coverage as the data from the near-infrared arm of the X-shooter spectrograph are now included. The DR2 spectra then consist of three segments that were observed simultaneously and, if combined, cover the range between ∼300 nm and ∼2.45 μm at a spectral resolving power close to R = 10 000. The spectra were corrected for instrument transmission and telluric absorption, and they were also corrected for wavelength-dependent flux-losses in 85% of the cases. On average, synthesized broad-band colors agree with those of the MILES library and of the combined IRTF and Extended IRTF libraries to within ∼1%. The scatter in these comparisons indicates typical errors on individual colors in the XSL of 2−4%. The comparison with 2MASS point source photometry shows systematics of up to 5% in some colors, which we attribute mostly to zero-point or transmission curve errors and a scatter that is consistent with the above uncertainty estimates. The final spectra were corrected for radial velocity and are provided in the rest-frame (with wavelengths in air). The spectra cover a large range of spectral types and chemical compositions (with an emphasis on the red giant branch), which makes this library an asset when creating stellar population synthesis models or for the validation of near-ultraviolet to near-infrared theoretical stellar spectra across the Hertzsprung-Russell diagram.
Confinement Dynamics on a Digital Quantum Computer

Confinement is a phenomenon that occurs when the attraction between two particles grows with their distance, most prominently found in quantum chromodynamics (QCD) between quarks. In condensed matter physics, similar phenomena appear in quantum spin chains, for example, in the one dimensional transverse field Ising model (TFIM) with an additional longitudinal field, famously observed via neutron scattering in the quantum material cobalt niobate or in optical lattice experiments. Confinement also drastically alters the non-equilibrium dynamics starting from selected initial states. Here, the physics of confinement in the TFIM is explored in relation to quantum simulation capabilities of state-of-the-art quantum computers. We report quantitative confinement signatures on an IBM quantum computer observed via two distinct velocities for information propagation from domain walls and their mesonic bound states. Our results are a crucial step for exploring non-perturbative interacting quantum phenomena beyond the capabilities of classical computers.