Miracle-dz/UniFAR-FTUs huggingface dataset:
A Cost-Effective Interpolation for Multi-Magnification Super-Resolution

Super-Resolution (SR) was an important research topic, and SR methods based on Convolutional Neural Network (CNN) confirmed its groundbreaking performance. However, notably implementing the CNN model into resource-limited hardware devices is a great challenge. Therefore, we present a hardware-friendly and low-cost interpolation for Multi-Magnification SR image reconstruction. We follow our previous work, which is a learning-based interpolation (LCDI) with a self-defined classifier of image texture, and extend its original <inline-formula> <tex-math notation="LaTeX">$\times 2$ </tex-math></inline-formula> architecture to <inline-formula> <tex-math notation="LaTeX">$\times 3$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\times 4$ </tex-math></inline-formula> architecture. Besides, the required pre-trained weights are reduced by the fusion scheme. Experimentally, the proposed method has only 75% lower pre-trained weights than LCDI. Compared to the related work OLM-SI (One linear learning mapping-SI), the run-time and quantity of pre-trained weights of the <inline-formula> <tex-math notation="LaTeX">$\times 2$ </tex-math></inline-formula> proposed method are at least 90% lower. Compared to CNN-based SR methods, the proposed method loses a little lower performance, but the evaluation of computational cost is much lower. In conclusion, the proposed method is cost-effective and a practical solution for resource-limited hardware and device.
The Enrichment History of the Intergalactic Medium—Measuring the C IV/H I Ratio in the Lyα Forest

We have obtained an exceptionally high signal-to-noise, high-resolution spectrum of the gravitationally lensed quasar Q1422+231. A total of 34 C IV systems are identified, several of which had not been seen in previous spectra. Voigt profiles are fitted to these C IV systems and to the entire Lyα forest in order to determine column densities, b-values, and redshifts for each absorption component. The column density distribution for C IV is found to be a power law with index α = 1.44 ± 0.05, down to at least log N(C IV) = 12.3. We use simulations to estimate the incompleteness correction and find that there is in fact no evidence for flattening of the power law down to log N(C IV) = 11.7—a factor of 10 lower than previous measurements. In order to determine whether the C IV enrichment extends to even lower column density H I clouds, we utilize two analysis techniques to probe the low column density regime in the Lyα forest. First, a composite stacked spectrum is produced by combining the data for Q1422+231 and another bright QSO, APM 08279+5255. The signal-to-noise ratio of the stacked spectrum is 1250, and yet no resultant C IV absorption is detected. We discuss the various problems that affect the stacking technique and focus in particular on a random velocity offset between H I and its associated C IV which we measure to have a dispersion of σv = 17 km s-1. It is concluded that, in our data, this offset results in an underestimate of the amount of C IV present by a factor of about 2, and this technique is therefore not sufficiently sensitive to probe the low column density Lyα clouds to meaningful metallicities. Second, we use measurements of individual pixel optical depths of Lyα and corresponding C IV lines. We compare the results obtained from this optical depth method with analyses of simulated spectra enriched with varying C IV enrichment recipes. From these simulations, we conclude that more C IV than is currently directly detected in Q1422+231 is required to reproduce the optical depths determined from the data, consistent with the conclusions drawn from consideration of the power-law distribution.
A new nucleotide variant in the ELAC2 gene in a young child with a ventricular hypertrophy

The few foreign papers of the last decade have shown the relationship of various pathogenic variants of the ELAC2 gene to heterogeneous phenotypic manifestations, for which the unfavorable prognosis is common, caused by severe cardiomyopathy in the first year of life. The article presents the first clinical observation of a rare variant of the hypertrophic phenotype cardiomyopathy with a fatal outcome in the first year of life, and variants c.887T>C, p.L296P and c.1979A>T, p.K660I of the ELAC2 gene in Russia.The purpose of the work is to present clinical observation of a child with an early manifestation of a hypertrophic phenotype of cardiomyopathy caused by pathogenic variants of the ELAC2 gene.
Complex Dynamics of a Cournot Quantum Duopoly Game with Memory and Heterogeneous Players

Previous authors tend to consider a certain range of values of the parameters involved in a game, not taking into account other possible values. In this article, a quantum dynamical Cournot duopoly game with memory and heterogeneous players (one of them is boundedly rational and the other one, a naive player) is studied, where the quantum entanglement can be greater than one and the speed of adjustment can be negative. In this context, we analyzed the behavior of the local stability and the profit in those values. Considering the local stability, it is observed that the stability region increases in the model with memory regardless of whether the quantum entanglement is greater than one or whether the speed of adjustment is negative. However, it is also shown that the stability is greater in the negative than in the positive zone of the speed of adjustment and, therefore, it improves the results obtained in previous experiments. This increase of stability enables higher values of speed of adjustment and, as a result of that, the system reaches the stability faster, resulting in a remarkable economic advantage. Regarding the behavior of the profit with these parameters, the principal effect shown is that the application of memory causes a certain delay in the dynamics. Through this article, all these statements are analytically proved and widely supported with several numerical simulations, using different values of the memory factor, the quantum entanglement, and the speed of adjustment of the boundedly rational player.
An Activity Based on Figurative Patterns: Moroccan Students’ Reasoning

The aim of this paper is to analyse the reasoning and symbolisations used by sixth grade Moroccan students in solving a task based on figurative patterns. Our analysis aims at identifying the systems of actions elaborated by the students to give the general expression of the sequence, according to their perceptions of the sequence of its patterns. The results of this study show that the students can produce a wide variety of generalisations, without using the letter, by resorting to verbal expressions, the majority of which remain in the class of a factual or contextual generalisation. However, several students were not able to determine the general term of the sequence in the question, through an expression that is detached from the context of the situation. This study also contributes to raising the consciousness of Moroccan teachers and researchers of mathematics didactics about the important role played by algebraic thinking, in particular the generalisation coming from an activity based on the figurative patterns, which generates several equivalent and meaningful numerical or algebraic expressions. This article also sheds light on ways for programme designers to enrich primary school curricula, by proposing arithmetic activities with algebraic potential, like the one proposed in our study.
Application of continuous measurement theory to the current through quantum dots

A simple theory of the detected current $I(t)$ flowing through charge qubits---quantum dots---is proposed in terms of standard continuous measurement theory. Applied to a double dot, our formalism easily confirms previous results on quantum Zeno effect, driven by growing ammeter performance $\ensuremath{\gamma}$. Due to the transparent formalism, we can calculate the exact fluctuation spectrum $S(\ensuremath{\omega})$ of the detected current, containing a significant Lorentzian peak near the Rabi frequency of the double dot.
Dynamical systems and categories

We study questions motivated by results in the classical theory of dynamical systems in the context of triangulated and A-infinity categories. First, entropy is defined for exact endofunctors and computed in a variety of examples. In particular, the classical entropy of a pseudo-Anosov map is recovered from the induced functor on the Fukaya category. Second, the density of the set of phases of a Bridgeland stability condition is studied and a complete answer is given in the case of bounded derived categories of quivers. Certain exceptional pairs in triangulated categories, which we call Kronecker pairs, are used to construct stability conditions with density of phases. Some open questions and further directions are outlined as well.
Effects of Branched-Chain Amino Acids on Skeletal Muscle, Glycemic Control, and Neuropsychological Performance in Elderly Persons with Type 2 Diabetes Mellitus: An Exploratory Randomized Controlled Trial

Although branched-chain amino acids (BCAA) are known to stimulate myofibrillar protein synthesis and affect insulin signaling and kynurenine metabolism (the latter being a metabolite of tryptophan associated with depression and dementia), the effects of BCAA supplementation on type 2 diabetes (T2D) are not clear. Therefore, a 24-week, prospective randomized open blinded-endpoint trial was conducted to evaluate the effects of supplementation of 8 g of BCAA or 7.5 g of soy protein on skeletal muscle and glycemic control as well as adverse events in elderly individuals with T2D. Thirty-six participants were randomly assigned to the BCAA group (n = 21) and the soy protein group (n = 15). Skeletal muscle mass and HbA1c, which were primary endpoints, did not change over time or differ between groups. However, knee extension muscle strength was significantly increased in the soy protein group and showed a tendency to increase in the BCAA group. Homeostasis model assessment for insulin resistance did not significantly change during the trial. Depressive symptoms were significantly improved in the BCAA group but the difference between groups was not significant. Results suggested that BCAA supplementation may not affect skeletal muscle mass and glycemic control and may improve depressive symptoms in elderly individuals with T2D.
Current State of Molecular and Serological Methods for Detection of Porcine Epidemic Diarrhea Virus

Porcine epidemic diarrhea virus (PEDV), a member of the Coronaviridae family, is the etiological agent of an acute and devastating enteric disease that causes moderate-to-high mortality in suckling piglets. The accurate and early detection of PEDV infection is essential for the prevention and control of the spread of the disease. Many molecular assays have been developed for the detection of PEDV, including reverse-transcription polymerase chain reaction (RT-PCR), real-time RT-PCR (qRT-PCR) and loop-mediated isothermal amplification assays. Additionally, several serological methods have been developed and are widely used for the detection of antibodies against PEDV. Some of them, such as the immunochromatography assay, can generate results very quickly and in field conditions. Molecular assays detect viral RNA in clinical samples rapidly, and with high sensitivity and specificity. Serological assays can determine prior immune exposure to PEDV, can be used to monitor the efficacy of vaccination strategies and may help to predict the duration of immunity in piglets. However, they are less sensitive than nucleic acid-based detection methods. Sanger and next-generation sequencing (NGS) allow the analysis of PEDV cDNA or RNA sequences, and thus, provide highly specific results. Furthermore, NGS based on nonspecific DNA cleavage in clustered regularly interspaced short palindromic repeats (CRISPR)–Cas systems promise major advances in the diagnosis of PEDV infection. The objective of this paper was to summarize the current serological and molecular PEDV assays, highlight their diagnostic performance and emphasize the advantages and drawbacks of the application of individual tests.
Toward Computerized Tomography With Microwaves

Microwave imaging holds the potential to bring an alternative to ionizing and expensive imaging modalities, such as mammography, magnetic resonance imaging (MRI), and computerized tomography (CT) scan. The absence of a high-resolution and non-model-based image reconstruction technique is one of the reasons that limited microwaves-based imaging. We introduce a microwaves-based imaging modality relying on the Radon transform technique adopted to create an imaging system identical in concept to CT-scanning methods that employ X-rays. This system uses low-frequency microwaves and highly localized radiators and receivers. While low-frequency microwaves are not perceived to have the ray-like behavior of X-rays, our system hinges on the principle that if the object under test (OUT) is electrically small (smaller than the wavelength), then the impression/projection due to an electrically very small localized source will be highly similar to a projection generated by a ray-like source. This phenomenon is due to the fact that a receiver closest to the highly localized transmitter will capture the highest energy. Several simulation studies and measurements demonstrate the ability of this technique to provide cross-sectional images of a 3-D object with high resolution.
Modular categories and 3-manifold invariants

The aim of this paper is to give a concise introduction to the theory of knot invariants and 3-manifold invariants which generalize the Jones polynomial and which may be considered as a mathematical version of the Witten invariants. Such a theory was introduced by N. Reshetikhin and the author on the ground of the theory of quantum groups. Here we use more general algebraic objects, specifically, ribbon and modular categories. Such categories in particular arise as the categories of representations of quantum groups. The notion of modular category, interesting in itself, is closely related to the notion of modular tensor category in the sense of G. Moore and N. Seiberg. For simplicity we restrict ourselves in this paper to the case of closed 3-manifolds.
Using the dark to see: dark matter and neutrinos enlighten the Universe

We discuss two important research avenues in astroparticle physics: dark matter and neutrinos. We discuss both direct and indirect detection of dark matter. We calculate the signatures of dark matter annihilation from galaxy clusters in neutrinos. We show the constraints on dark matter annihilation from radio measurements near the Galactic Center. We consider the dark matter annihilation contribution to the isotropic diffuse gamma-ray background and show how to determine the minimum dark matter halo mass for a given dark matter mass and annihilation channel. Motivated by recent hints on dark matter self-interactions, we calculate the nuclear recoil spectrum from a bound state dark matter scattering with a nuclei at rest in a dark matter direct detection experiment. We discuss non-standard interactions of neutrinos and astrophysical neutrino detection in the second part of the thesis. We derive strong constraints on a light Abelian gauge boson coupling to Standard Model leptons. In light of the recent detection of high energy neutrinos in IceCube, we discuss the cascade detection of high energy astrophysical neutrinos in IceCube and point out the benefits of this detection channel. We propose a new method to detect supernova νe in gadolinium loaded Super-Kamiokande detector and show that it can be used to measure the supernova νe spectrum to ∼ 20% accuracy.
Nightmare Distress as a Risk Factor for Suicide Among Adolescents with Major Depressive Disorder

Purpose Nightmare is common and is also independently implicated in suicide risk among the adolescent population. Adolescents with major depressive disorder (MDD) are at an increased risk of suicide. Therefore, comorbid nightmares may amplify suicide risk among this clinical population. This study aimed to explore the effects of nightmares on suicide risk among adolescents with MDD. Patients and Methods Subjects were 499 outpatients aged 12–18 in four large psychiatric hospitals clinic of China, from January 1 to October 31, 2021. Simultaneously, we matched 499 healthy controls according to gender and age. All participants underwent affective state (depressive and anxiety symptoms) and sleep variable (nightmare frequency/distress, insomnia symptoms, and daytime sleepiness) evaluation as well as MDD diagnoses and determination of suicide risk by a fully structured diagnostic clinical interview. Results Adolescents with MDD reported a higher incidence of frequent nightmares (at least one night per week) and level of nightmare distress than healthy controls (22.0% vs 6.1%; 28.85 ± 11.92 vs 17.30 ± 5.61). Over half of the patients with suicide risk (51.6%) experienced frequent nightmares compared with approximately one-third of those at a risk for suicide (30.7%). Patients with suicide risk scored scientifically higher on sleep variables, depressive and anxiety symptoms than those without the risk. Further logistic regression analysis indicated that female gender, junior grade, recurrent depressive episode, severe nightmare distress and severe depressive symptoms were independently and significantly associated with suicide risk. Conclusion Our study provided evidence that adolescents with MDD experienced a higher prevalence of frequent nightmares and suffered more nightmare distress. Nightmare distress is an independent risk factor for suicide risk.
Comparative Study of M(Ⅱ)Al (M=Co, Ni) Layered Double Hydroxides for Silicone Foam: Characterization, Flame Retardancy, and Smoke Suppression

To compare the different actions of the two representative transition metal cations of Co2+ and Ni2+ in layered double hydroxides (LDHs), CoAl-LDH and NiAl-LDH intercalated with CO32− were synthesized, and the chemical structures, microstructures, and surface areas thereof were successfully characterized. Then, the two LDHs were utilized as flame retardants and smoke suppressants for silicone foam (SiF). The densities, flame retardancy, smoke suppression, thermal stabilities, and compressive strengths of the two SiF/LDHs nanocomposites were investigated. The introduction of LDHs slightly decreased the density of SiF due to the catalytic actions of Co and Ni during the foaming process of SiF. With respect to the flame retardancy, the addition of only 1 phr of either CoAl-LDH or NiAl-LDH could effectively improve the limiting oxygen index of SiF from 28.7 to 29.6%. Based on the results of vertical flame testing and a cone calorimeter test, the flame retardancy and fire safety of the SiF were effectively enhanced by the incorporation of LDHs. In addition, owing to the good catalytic action and large specific surface area (NiAl-LDH: 174.57 m2 g−1; CoAl-LDH: 51.47 m2 g−1), NiAl-LDH revealed higher efficiencies of flame retardancy and smoke suppression than those of CoAl-LDH. According to the results of energy-dispersive X-ray spectroscopy, Co and Ni participated in the formation of protective char layers, which inhibited the release of SiO2 into the gas phase. Finally, the influences on the thermal decomposition and compressive strength for SiF resulting from the addition of LDHs are discussed.
Computationally Efficient Overmodulation Methods for Synchronous Motor Drive Systems

This article presents two computationally efficient methods for selecting the optimal modulated voltage that can achieve superior dynamic performance for surface-mounted permanent magnet synchronous motors (SPMSMs). Specifically, when an SPMSM suffers a large reference or sudden load change, the controller might command a voltage reference, which is beyond the range of voltages that a modulator can synthesize. In such cases, the transient behavior of the motor can deteriorate when the demanded voltage is not properly limited to the voltage boundary. To address this issue, a simple overmodulation method based on common-mode-saturation injection (CMSI) is proposed. This strategy comes with very low computational cost and can easily find the voltage vector on the boundary, which is nearest to the reference voltage vector. Moreover, an alternative control method, referred to as quadratic program (QP) based deadbeat (DB) control, is proposed that also ensures optimal system performance during overmodualtion. According to this strategy, the control problem is formulated as a constrained QP, which is solved with an efficient solver based on an active-set method. Finally, extensive simulative and experimental investigations for an SPMSM are presented to demonstrate the effectiveness of the proposed overmodulation methods.
A miniaturized CRLH based SIW leaky‐wave antenna for continuous backward‐to‐forward fast beam scanning with low side lobe levels

In this study, a substrate‐integrated waveguide (SIW)‐based miniaturized leaky‐wave antenna (LWA) with fast beam scanning is proposed. The proposed LWA exhibits composite right/left‐handed (CRLH) property and its unit cell consist of an inverted Z‐shaped slot etched on the top layer of SIW. By sweeping frequency from 9.4 to 11.4 GHz, the proposed CRLH LWA can steer the frequency beam continuously from −40° to 51°, which shows fast beam scanning within the impedance bandwidth (2 GHz) of LWA. The good leakage constant contributes to the miniaturization of the LWA with electrical dimensions of 3. 38λ0 × 0. 34λ0 mm2. The antenna attains a peak gain of 12.5 dBi with maximum radiation efficiency of 92%. The antenna attains low sidelobe levels below 12 dB; the low sidelobe levels in the LWA are obtained by creating symmetricity in the unit cell around the centerline. The designed LWA is a viable contender for X‐band beam scanning applications.
Investigating the Efficiency of Deep Learning Methods in Estimating GPS Geodetic Velocity

Geodetic velocity (GV) has many applications in tectonic motion determination and geodynamic studies. Due to the high cost of global navigation satellite system stations, deep learning methods have been investigated to estimate GV. In this research, four methods of convolutional neural networks (CNNs), deep Boltzmann machines, deep belief net and recurrent neural networks have been applied. The GV of 42 global positioning system stations is entered the deep learning methods. The outputs of the four methods have successfully passed the normality test. The results show that the CNN method has a lower goodness of fit and root mean square error (RMSE). CNN can learn different dependencies and extract features.
Psychometric Analysis Instruments of Self-efficacy in Work

The purpose of this study was to determine the Self-efficacy of students in their ability to achieve a certain level in the context of work. Respondents in this study were 234 students of class XII Vocational High School in Tangerang City. The sampling technique used in this research is non-probability sampling with the snowball sampling method. Researchers distributed online questionnaires through Google Forms to student representatives from several class XII Vocational High School in various schools. The instrument used in this study was the Work Self-efficacy Scale (WSES). This scale consists of a total of 10 items with 2 dimensions, namely Relational Willingness and Commitment. The results of the study, this Work Self-efficacy instrument can be declared reliable and valid. It is said to be reliable or consistent because in the third test, the calculation results obtained a Cronbach alpha reliability coefficient value of 0.874. The coefficient value is greater than the standard parameter, namely 0.7. This means that this instrument can be used repeatedly and can produce a consistent picture of Work Self-efficacy.