Miracle-dz/UniFAR-FTUs huggingface dataset:
HOW TO DECIDE? STUDENTS' WAYS OF DETERMINING THE VALIDITY OF MATHEMATICAL STATEMENTS

patterns of high school students. The initial findings came out of a study that examined learning processes and student understandings related to the concept of counterexample. More specifically, it examined the ways in which students understand and use counterexamples in mathematics, in the course of studying a special unit designed to foster opportunities for determining the validity of numerous mathematical statements. During the study a number of strategies, which students employed in the process of evaluating the validity of mathematical statements, were identified. These strategies involved a range of underlying cognitive processes that became the main focus of the current research. BACKGROUND
Analysis of ranging biases of BOC signal threat based on non-ideal channel group delay characteristics

Satellite signal threat is an important kind of satellite signal anomaly, which will lead to ranging biases of user receiver. BOC modulation is used more and more widely in the field of satellite navigation system. In the existing literature, there is a shortage that the non-ideal characteristics of the channel are not taken into account in the ranging biases analysis of BOC signal threat. The non-ideal characteristic of the receiving channel is one of the main bias sources of navigation signal reception. In the process of receiving navigation signal, due to the jitter caused by channel noise and the non-ideal phase of the channel, ranging biases will be introduced. To solve this problem, this paper proposes the analysis model of ranging biases of BOC signal threat based on non-ideal channel characteristics, and analyzes the non-ideal group delay characteristics of BOC (1,1) signal incoherent ranging mode. From the analysis results of ranging biases under multiple threated signals, it can be seen that the non-ideal group delay characteristics will worsen the ranging biases of BOC signal threat in most cases. In the sense of minimum ranging biases caused by BOC signal threat, 0.3chip∼0.35chip is the recommended parameter for non-coherent reception of BOC (1,1) early late code.
Relationships Between $l^1 $ Metrics on Linear Ranking Spaces

In this paper we examine various $l^1 $ distance measures on linear ranking spaces. Beginning with the absolute position measure of Blin, we construct two offspring measures—one based on relative rank positioning, the other on relative object positioning. The first is shown to be equivalent to the permutation vector method of Cook and Seiford. The other is equivalent to the preference matrix method of Kemeny and Snell. We also prove that the Kemeny and Snell method can be formulated as a quadratic assignment problem.
Co-infection of TYLCV and ToCV increases cathepsin B and promotes ToCV transmission by Bemisia tabaci MED

Tomato disease is an important disease affecting agricultural production, and the combined infection of tomato chlorosis virus (ToCV) and tomato yellow leaf curl virus (TYLCV) has gradually expanded in recent years, but no effective control method has been developed to date. Both viruses are transmitted by Bemisia tabaci Mediteranean (MED). Previously, we found that after B. tabaci MED was fed on ToCV-and TYLCV-infected plants, the transmission efficiency of ToCV was significantly higher than that on plants infected only with ToCV. Therefore, we hypothesize that co-infection could enhance the transmission rates of the virus. In this study, transcriptome sequencing was performed to compare the changes of related transcription factors in B. tabaci MED co-infected with ToCV and TYLCV and infected only with ToCV. Hence, transmission experiments were carried out using B. tabaci MED to clarify the role of cathepsin in virus transmission. The gene expression level and enzyme activity of cathepsin B (Cath B) in B. tabaci MED co-infected with ToCV and TYLCV increased compared with those under ToCV infection alone. After the decrease in cathepsin activity in B. tabaci MED or cathepsin B was silenced, its ability to acquire and transmit ToCV was significantly reduced. We verified the hypothesis that the relative expression of cathepsin B was reduced, which helped reduce ToCV transmission by B. tabaci MED. Therefore, it was speculated that cathepsin has profound research significance in the control of B. tabaci MED and the spread of viral diseases.
On sufficient conditions for Bayesian consistency

This paper contributes to the theory of Bayesian consistency for a sequence of posterior and predictive distributions arising from an independent and identically distributed sample. A new sufficient condition for posterior Hellinger consistency is presented which provides motivation for recent results appearing in the literature. Such motivation is important since current sufficient conditions are not known to be necessary. It also provides new insights into Bayesian consistency. A new consistency theorem for the sequence of predictive densities is given. Copyright Biometrika Trust 2003, Oxford University Press.
The properties of Lyman limit absorbing clouds at Z = 3 - Physical conditions in the extended gaseous halos of high-redshift galaxies

Les observations spectroscopiques de 7 quasars, dont le systeme limite Lyman (SLL) a un redshift compris entre 2.9 et 3.2, sont presentees. Les raie d'absorption sont identifiees. Les densites de colonne des elements lourds et HI, associes aux SLLs, sont determinees
Curie's Principle

physical sciences. Reasoning based on notions of symmetry has been evident in science since antiquity1 but the arguments employed are usually vague or implicit.2 Even if the sole function of the principle is to render such reasoning more precise and explicit an exposition of it is desirable in so far as it clarifies the status of and the assumptions involved in the arguments. One explanation of the lack of reference to the principle would be that it is implied by some other principle in common use. We are led to ask, then, if Curie's principle can be derived from some more general assertions. We shall show that the principle can be derived from the invariance properties of physical laws but that this fact by no means renders the principle redundant. Our remarks so far have been based on the assumptions that the principle is valid and can be formulated with sufficient precision for it to be of use in the physical sciences. If either of these assumptions were to prove false then we would, of course, have a very definite answer to our puzzle over the lack of attention paid to the principle. Freudenthal (I968, p. 420) has suggested that the principle acquires its generality by being necessarily vague. In this respect he attributes to Curie's principle a status similar to that of Leibniz's principle of sufficient reason.3 That such a claim is
Estimation of Thickness and Radius of Hollow Metallic Spheres With a Simplified Forward Model

The measurement of metallic spherical objects in various industrial applications has a significant role in guaranteeing safety and product quality, which can be realized by the eddy-current testing (ECT) technique without contact. In this study, for the measurement of thickness and radius of nonmagnetic spherical shells, the original analytical model is simplified according to the asymptotic forms of the modified spherical Bessel functions. The simplified model contains only elementary functions, and can therefore accelerates the sphere property estimation by employing the optimization approach based on the Newton–Raphson method. In numerical simulation and experimental study, the proposed method can provide accurate spherical shell radii with less computational time compared with the original analytical model.
Efficient construction of constrained suffix trees

Suffix tree, proposed by Weiner in 1973, is a well-known full-text index structure that stores all the substrings in a given text. For a text T of length n, the suffix tree for T can be constructed in O(n log |Σ|) time and O(n) space, where T is a string over an alphabet Σ and |Σ| is the size of Σ. However, due to the rise of the large-scale and semi-structured text data, several applications need more powerful and flexible index structures. For this reason, we consider a constraint for the text and then extend the suffix tree to store all the substrings in the text that satisfy the constraint. Applying a constraint is not only effective for reducing the space consumption of the constrained index structure, but also for improving the computation time for searching queries, because the number of the results for queries will get fewer than the number of the results by the normal suffix tree. In this thesis, we propose a family of the constrained suffix trees, which are suffix trees that store the set of all substrings in an input text that satisfy a given constraint. In Chapter 3, we propose the word-based truncated suffix tree and its efficient construction algorithm. We here assume that the input text is written in a natural language such as English and each word is splitted by some special character like the white space. Given an integer k > 0 and a text T , the k-word-based suffix tree for T is an index structure that stores any substring which consists of at most k words. Then, we show an online construction algorithm that runs in O(n log |Σ|) time.
Dynamic nonlinear σ-model of electron localization

We review the nonlinear σ-model approach to the localization problem. However, different from usual, we do not make use of replicas or superfields in order to perform the averaging over the realizations of the disorder. Instead, we pursue the derivation of the nonlinear σ-model as an effective theory for the disordered electron system within the framework of the so-called time-path formalism, which is a real-time finite-temperature quantum field theory. This formalism is especially suitable for the description of the disordered electron system due to the automatic normalization of real-time quantities, thereby avoiding the denominator problem. We shall compare this dynamic method with the replica- and superfield-methods as the perturbative level of the calculation of physical quantities.
Quantified multidimensional public sentiment characteristics on social media for public opinion management: Evidence from the COVID-19 pandemic

Background Public sentiments arising from public opinion communication pose a serious psychological risk to public and interfere the communication of nonpharmacological intervention information during the COVID-19 pandemic. Problems caused by public sentiments need to be timely addressed and resolved to support public opinion management. Objective This study aims to investigate the quantified multidimensional public sentiments characteristics for helping solve the public sentiments issues and strengthen public opinion management. Methods This study collected the user interaction data from the Weibo platform, including 73,604 Weibo posts and 1,811,703 Weibo comments. Deep learning based on pretraining model, topics clustering and correlation analysis were used to conduct quantitative analysis on time series characteristics, content-based characteristics and audience response characteristics of public sentiments in public opinion during the pandemic. Results The research findings were as follows: first, public sentiments erupted after priming, and the time series of public sentiments had window periods. Second, public sentiments were related to public discussion topics. The more negative the audience sentiments were, the more deeply the public participated in public discussions. Third, audience sentiments were independent of Weibo posts and user attributes, the steering role of opinion leaders was invalid in changing audience sentiments. Discussion Since the COVID-19 pandemic, there has been an increasing demand for public opinion management on social media. Our study on the quantified multidimensional public sentiments characteristics is one of the methodological contributions to reinforce public opinion management from a practical perspective.
Diffraction in high numerical aperture systems: polarization effects

In high numerical aperture systems polarization effects should be taken into account; hence it is necessary to use a vectorial diffraction theory to describe them. We develop a computational model to study image formation in a high numerical aperture microscope objective by simulating images of self-luminous, non-polarized point objects. We compare the predictions made by scalar and vectorial theories of diffraction. In the last case we also consider an analyzer placed behind the objective to study the polarization effects. We find that vectorial theory predicts a larger diffraction pattern and, when an analyzer is used, an enlargement along the transmission axis of the analyzer. We also study the resolution of the system, finding that the true resolution predicted for vectorial theory is approximately 10% lower than that usually expected for scalar theory.
Store-Wide Shelf-Space Allocation with Ripple Effects Driving Traffic

How Product Locations Drive Traffic Throughout a Retail Store In “Store-Wide Shelf-Space Allocation with Ripple Effects Driving Traffic,” Flamand, Ghoniem, and Maddah develop a framework for deciding where to place products in a store, in addition to apportioning the shelf space among products, in a way that maximizes impulse profit, a phenomenon that may account for 50% of transactions. By analyzing a large data set of customer receipts from a grocery store in Beirut, the authors develop a regression model that estimates traffic at a shelf based on its location and the “attraction” from products allocated nearby. The traffic model is embedded within a mixed-integer nonlinear program, which they solve via specialized linear approximations. For the store in Beirut, a 65% improvement in impulse profit is anticipated, and the location of products is found to be significantly more important in driving store-wide traffic than the relative shelf-space allocation.
Use of recirculation theory and reduced dimensionality for efficient calculation of jet flow in cylindrical combustors

Abstract This work evaluates use of a dimensionally adaptive (DA) meshing technique to speed CFD modeling of non-reacting pressurized flow in a cylindrical geometry with a center jet and non-axisymmetric secondary jets. The DA-capable approach incorporates an a priori dimensional boundary location and extension of 3-D RANS flow solvers. Recirculation zone length, not flow asymmetry, was the limiting factor in placement of the dimensional boundary between 3-D and axisymmetric meshes. Boundary placement was based on confined turbulent jet theory, which suggests jet attachment is a linear function of cylinder radius, L, expressed as 5.85L. CFD results for a turbulent axial pipe flow showed that as the dimensional boundary was moved upstream, computational time dropped quadratically with the reduction in mesh cells. Further simulations of a 0.2032-m diameter, 1.5-m long reactor with turbulent center primary jet and outer radius secondary jets placed the dimensional boundary at 0.7 m. Results for pressures of 20, 10, and 5 bar and mass flow rates of 75% and 50% of baseline demonstrated two key results. First, flow similarity was preserved across all cases and the predicted jet attachment location was approximately 0.61 m, compared with the theoretical value of 0.594 m. Second, runtime reductions of 79% (pressure) and 82% (flow rate) were seen for the DA meshes compared with fully 3-D meshes. Differences in average exit axial velocities between DA and fully 3-D meshes were 2–4% for the pressure cases and 0.7–1.5% for the flow rate cases. Lastly, comparison with 3-D quarter-geometry calculations showed the DA approach to be ∼10% faster with exit axial velocities within 3–5% of 3-D velocities.
Large stroke MOEMS actuators for optical path length modulation in miniaturized FTIR spectrometers

In this paper we present a novel translatory MOEMS device with extraordinary large stroke especially designed for fast optical path modulation in an improved miniaturized Fourier-transform infrared (FTIR) spectrometer capable to perform time resolved measurements from NIR to MIR. Recently, we presented a first MOEMS based FTIR system using a different translatory MOEMS actuator with bending suspensions of the mirror plate and ±100μm oscillation amplitude resulting in a limited spectral resolution of 30 cm-1. For the novel MOEMS actuator an advanced pantograph suspension of the mirror plate was used to guarantee an extraordinary large stroke of up to 500 μm required for an improved spectral resolution. To optimize the optical throughput of the spectrometer the mirror aperture was increased to 7 mm2. The MOEMS actuators are driven electro statically resonant using out-of-plane comb drives and operate at a resonant frequency of 500 (1000) Hz, respectively. Hence, this enables to realize an improved MOEMS based FTIR-spectrometer with a spectral resolution of up to 10 cm-1, a SNR of > 1000:1 and an acquisition time of 1 ms per spectrum of the miniaturized FTIR-system. In this article we discuss in detail the design and the experimental characteristics of the novel large stroke translatory MOEMS device. The application and system integration, especially the optical vacuum packaging, of this MOEMS device in an improved miniaturized MOEMS based FTIR spectrometer enabling ultra rapid measurements in the NIRMIR spectral region with 12cm-1 spectral resolution is discussed in a separate paper submitted to this conference.
Processing and microstructure of single grain, uranium-doped Y-Ba-Cu-O superconductor

Large grain Y–Ba–Cu–O (YBCO) superconductor doped with various amounts of depleted UO2 and containing excess Y2BaCuO5 (Y-211) and Y2O3 have been fabricated by top seeded melt growth (TSMG). The effect of depleted UO2 on the large grain microstructure has been studied systematically in samples with and without added Pt. It is found that UO2 refines the size of the second phase particles in the superconducting YBa2Cu3O7−δ (Y-123) matrix to dimensions of a few hundred nanometres with an approximately spherical morphology. Addition of Y2O3 to the uranium-doped precursor powder, rather than Y-211, yields a significantly finer distribution of second phase particles and an associated higher critical current density Jc at increased magnetic field.
Evidence factors in observational studies

Some experiments involve more than one random assignment of treatments to units. An analogous situation arises in certain observational studies, although randomization is not used, so each assignment may be biased. If each assignment is suspect, it is natural to ask whether there are separate pieces of information, dependent upon different assumptions, and perhaps whether conclusions about treatment effects are not critically dependent upon one or another suspect assumption. The design of an observational study contains evidence factors if it permits several statistically independent tests of the same null hypothesis about treatment effects, where these tests rely on different assumptions about treatment assignments at several levels of assignment. Two designs and two empirical examples are considered, one example of each design. In the dose-control design, there are matched pairs of a treated subject and an untreated control, and doses of treatment vary between pairs for treated subjects; this yields two evidence factors. In the varied intensity design, there are matched sets with two treated subjects and one or more untreated controls, where the two treated subjects within the same matched set receive different doses of treatment, and in a technically different way, the design yields two evidence factors. Copyright 2010, Oxford University Press.
A method of estimating parameters and assessing reliability for models of steady state groundwater flow: 1. Theory and numerical properties

A new nonlinear least squares solution for the Hydrogeologic parameters, sources and sinks, and boundary fluxes contained in the equations approximately governing two-dimensional or radial steady state groundwater motion was developed through use of a linearization and iteration procedure applied to the finite element discretization of the problem. Techniques involving (1) use of an iteration parameter to interpolate or extrapolate the changes in computed parameters and head distribution at each iteration and (2) conditioning of the least squares coefficient matrix through use of ridge regression techniques were proven to induce convergence of the procedure for virtually all problems. Because of the regression nature of the solution for the parameter estimation problem, classical methods of regression analysis are promising as an aid to establishing approximate reliability of computed parameters and predicted values of hydraulic head. Care must be taken not to compute so many parameters that the stability of the estimates is destroyed. Reduction of the error variance by adding parameters is desirable provided that the number of degrees of freedom for error remains large.
UV-FPM for the label-free analysis of biological samples

Currently, biological samples that are analyzed microscopically such as blood smears or tissue sections need to be stained to visualize important information such cell nuclei. This represents a major hurdle on the path to further automation, increases costs and can lead to significant lab-to-lab variation in terms of diagnostic results. Here, the authors will present a novel microscopy approach, based on UV Fourier Ptychography Microscopy, that is able to directly image blood smears and digital pathology samples without the need for staining.
Blue monolithic AlInN-based vertical cavity surface emitting laser diode on free-standing GaN substrate

We report on III-nitride based blue vertical cavity surface emitting lasers using defect-free highly reflective AlInN/GaN distributed Bragg reflectors grown on c-plane free-standing GaN substrates. Lasing is demonstrated at room temperature under pulsed electrical injection. The high lasing threshold current density still prevents devices from continuous wave lasing because of large self-heating. The reasons for such a high threshold are discussed and we show that it mainly comes from large light absorption in the indium tin oxide current spreading layer. Properly tuning both its thickness and its position with respect to the electrical field could remarkably decrease the threshold.
The Synergy between Deep Learning and Organs-on-Chips for High-Throughput Drug Screening: A Review

Organs-on-chips (OoCs) are miniature microfluidic systems that have arguably become a class of advanced in vitro models. Deep learning, as an emerging topic in machine learning, has the ability to extract a hidden statistical relationship from the input data. Recently, these two areas have become integrated to achieve synergy for accelerating drug screening. This review provides a brief description of the basic concepts of deep learning used in OoCs and exemplifies the successful use cases for different types of OoCs. These microfluidic chips are of potential to be assembled as highly potent human-on-chips with complex physiological or pathological functions. Finally, we discuss the future supply with perspectives and potential challenges in terms of combining OoCs and deep learning for image processing and automation designs.