Miracle-dz/UniFAR-FTUs huggingface dataset:
D2UNet: Dual Decoder U-Net for Seismic Image Super-Resolution Reconstruction

Super-resolution reconstruction is an essential task of seismic inversion due to the low resolution and strong noise of field data. Popular deep networks derived from U-Net lack the ability to recover detailed edge features and weak signals. In this article, we propose a dual decoder U-Net (D2UNet) to explore both the detail and edge information of the data. The encoder inputs the low-resolution image and the edge image obtained through the Canny algorithm. Edge images can provide rich shape and boundary information, which is helpful to generate more accurate and high-quality data. The dual decoder consists of a main decoder for high-resolution recovery and an edge decoder for edge contour detection. These two decoders interact with a texture-warping module (TWM) with deformable convolution. TWM aims to distort realistic edge details to match the fidelity of low-resolution inputs, especially the location of edges and weak signals. The loss function is a combination of $L_{1}$ loss and multiscale structural similarity loss (MS-SSIM) to ensure perception quality. Results on synthetic and field seismic images show that D2UNet not only improves the resolution of noisy seismic images, but also maintains the image fidelity.
MLFAN: Multilevel Feature Attention Network With Texture Prior for Image Denoising

Machine learning techniques, especially deep learning, have made great achievements in computer vision including image denoising recently. However, in most convolutional neural network (CNN) based methods presented for image denoising, convolutional kernels are considered for only one scale and more scales are neglected mostly. Studies on multilevel feature extraction treat these features as if they have the same importance and do not use a mechanism such as feature attention for their weighting. Also, for effective noise removal, edge information is used as prior knowledge, but texture information is generally disregarded. This study has focused on these shortcomings and introduced a new attention-based CNN for image denoising. The main contributions of this study are as follows: First, we propose a CNN-based network to extract Local Binary Pattern (LBP) from the noisy image for texture information. So, we use texture information as prior knowledge for the preservation of details in the evolved image during the denoising process. Besides we propose a new multilevel feature extraction block to get different level features. After extracting multilevel features using feature attention, we weight these different levels of features. In addition to this, we introduce a multilevel feature attention network (MLFAN) for noise removal by combining them. The comprehensive experimental results show that our MLFAN noise reduction network can effectively remove Gaussian noise from images and compared with some state-of-the-art denoising methods, it outperforms in terms of both quantitative and qualitative evaluations. For Set12 grey image set, and McMaster color image set, MLFAN gives PSNR = <inline-formula> <tex-math notation="LaTeX">$\{33.08,30.75,27.56\}$ </tex-math></inline-formula>, SSIM = <inline-formula> <tex-math notation="LaTeX">$\{0.9087,0.8702,0.7939\}$ </tex-math></inline-formula> and PSNR = <inline-formula> <tex-math notation="LaTeX">$\{35.08,32.68,29.47\}$ </tex-math></inline-formula>, SSIM = <inline-formula> <tex-math notation="LaTeX">$\{0.9288,0.8956,0.8263\}$ </tex-math></inline-formula> respectively for noise level <inline-formula> <tex-math notation="LaTeX">$\sigma =\{15,25,50\}$ </tex-math></inline-formula>.
Photon Antibunching from Few Quantum Dots in a Cavity

Single quantum dots (QDs) are frequently used as single-photon sources, taking advantage of the final exciton decay in a cascade that produces energetically detuned photons. We propose and analyze a new concept of single-photon source, namely, a few-QD microcavity system driven close to, but below the lasing threshold under strong excitation. Surprisingly, even for two or three QDs inside a cavity, antibunching is observed. To quantify the results, we find that a classification of single-photon emission in terms of antibunching in the autocorrelation function g(2)(0) is insufficient and more details of the photon statistics are required. Our investigations are based on a quantum-optical theory that we solve to obtain the density operator for the quantum-mechanical active medium and radiation field.
Current Methods for Identifying Plasma Membrane Proteins as Cancer Biomarkers

Plasma membrane proteins are a special class of biomolecules present on the cellular membrane. They provide the transport of ions, small molecules, and water in response to internal and external signals, define a cell’s immunological identity, and facilitate intra- and intercellular communication. Since they are vital to almost all cellular functions, their mutants, or aberrant expression is linked to many diseases, including cancer, where they are a part of cancer cell-specific molecular signatures and phenotypes. In addition, their surface-exposed domains make them exciting biomarkers for targeting by imaging agents and drugs. This review looks at the challenges in identifying cancer-related cell membrane proteins and the current methodologies that solve most of the challenges. We classified the methodologies as biased, i.e., search cells for the presence of already known membrane proteins. Second, we discuss the unbiased methods that can identify proteins without prior knowledge of what they are. Finally, we discuss the potential impact of membrane proteins on the early detection and treatment of cancer.
Online Trajectory Planning Control for a Class of Underactuated Mechanical Systems

Efficient control of underactuated systems has always been a great challenge, since one has to stabilize both actuated and unactuated states with fewer control inputs. During the past decades, great efforts have been devoted to improving the transient performance and robustness of the system, which are very crucial in plenty of application scenarios. To motivate corresponding research, an online trajectory planning method is proposed for a class of underactuated mechanical systems in this article. Specifically, reference trajectories are first generated for actuated states. Based on that, appropriate online adjustments are made to these reference trajectories, so as to realize efficient stabilization of the unactuated states. Different from traditional offline planning methods, the proposed one utilizes real-time feedback to counteract various unfavorable conditions, which endows it stronger robustness and better transient performance. Rigorous Lyapunov-based analysis is performed to show that the closed-loop system is asymptotically stable around the desired equilibrium point. Finally, the proposed method is applied to two underactuated mechanical systems, with simulation/experiment results provided to demonstrate its superior performance.
The role of demographic factors on religious beliefs: Evidence from five countries

Background: Individuals' values, attitudes, and behaviours are significantly influenced by their religious beliefs. The present study examines the demographic factors (gender, age groups, religion, employment status, household income, marital status, self-perceived adulthood, and country of origin) that may influence religious beliefs. Methods: The data was collected from September to December 2022 using an online survey. A cross-sectional design was used to collect data from 885 respondents from five countries: Malaysia, the Philippines, China, Kenya, and Indonesia. The survey included questions on five variables related to religious belief: religious certainty, religious culture, religious importance, religious practice, and belief in God. Respondents were asked to rate their level of agreement or disagreement with statements related to each variable on a Likert scale. T-tests and one-way ANOVA were used to analyze the data and determine any significant differences in religious beliefs between the five countries. Results: The results revealed that female respondents held stronger religious beliefs than male respondents. Furthermore, respondents aged 30-45 rated themselves as having a higher religious culture and practice than respondents aged 18-29. Islam groups ranked highest in religious beliefs, followed by Christian, Roman Catholic, and Hindu groups. Full-time students rated themselves as less religious than full-time employed and other groups, while lower-income groups rated themselves as more religious than middle- and upper-income groups. Single groups rated themselves higher on belief in God than cohabiting and in-relationship groups. Conclusions: In conclusion, this study provides evidence that demographic factors influence religious beliefs among respondents from five different countries. These findings can contribute to a better understanding of how religiosity is shaped by various socio-demographic factors and can inform policies and interventions designed to promote religious tolerance and diversity. More research is required to investigate the complex relationships between demographic factors and religiosity, particularly in different cultural and religious contexts.
Enhancement of the Seismic Data Resolution Through Q-Compensated Denoising Based on Dictionary Learning

Seismic wave acquisition is usually disturbed by natural noise and instrument noise. As the seismic wave propagates, the filtering effect of the Earth and its various layers will result in energy attenuation and velocity dispersion; these phenomena weaken the seismic time series amplitudes and distort the seismic phase data. In traditional processing methods, noise removal precedes the data compensation process, which attempts to retrieve information that was originally lost due to signal attenuation. If denoising is performed, weak seismic signals are often removed, resulting in the loss of useful signal data that cannot be recovered. Here, we propose a sparse regularization strategy based on dictionary learning. This inversion method performs the denoising and data compensation tasks in parallel. By applying this method to both synthetic and real datasets, we demonstrate that this technique effectively compensates and denoises the seismic data and improves both the data resolution and the signal-to-noise ratio of the seismic records of interest.
Exploration of the DNA Photocleavage Activity of O-Halo-phenyl Carbamoyl Amidoximes: Studies of the UVA-Induced Effects on a Major Crop Pest, the Whitefly Bemisia tabaci

The DNA photocleavage effect of halogenated O-carbamoyl derivatives of 4-MeO-benzamidoxime under UVB and UVA irradiation was studied in order to identify the nature, position, and number of halogens on the carbamoyl moiety that ensure photoactivity. F, Cl, and Br-phenyl carbamate esters (PCME) exhibited activity with the p-Cl-phenyl derivative to show excellent photocleavage against pBR322 plasmid DNA. m-Cl-PCME has diminished activity, whereas the presence of two halogen atoms reduced DNA photocleavage. The substitution on the benzamidoxime scaffold was irrelevant to the activity. The mechanism of action indicated function in the absence of oxygen, probably via radicals derived from the N-O bond homolysis of the carbamates and in air via hydroxyl radicals and partially singlet oxygen. The UVA-vis area of absorption of the nitro-benzamidoxime p-Cl-PCMEs allowed for the investigation of their potential efficacy as photopesticides under UVA irradiation against the whitefly Bemisia tabaci, a major pest of numerous crops. The m-nitro derivative exhibited a moderate specificity against the adult population. Nymphs were not affected. The compound was inactive in the dark. This result may allow for the development of lead compounds for the control of agricultural insect pests that can cause significant economic damage in crop production.
The need and opportunities for developing emotional intelligence in education

Emotional intelligence directly influences teacher performance as one of the indicators of successful teaching evaluation. In a comprehensive meta-analysis, Martins, Ramalho, and Morin (2010) showed that emotional intelligence is clearly, strongly, and unequivocally related to mental and physical health. They examined emotional intelligence in relation to school performance. It was shown that emotional intelligence has organisational, clinical, health, educational and social implications. Another question of great interest and importance is whether emotional intelligence can be developed. Recent evidence from Di Fabio and Kenny (2011) suggests that specific training may have significant benefits. We need to know more about what type of training is needed and why (Di Fabio & Kenny, 2011). In this publication we seek answers to the following questions: - Can emotional intelligence be developed in education? - If it can be developed, how? - Is there a link between emotional intelligence and empathy? - What are the links between emotional intelligence and coping strategies? It is assumed that emotional intelligence can be learned. From birth, children are able to decode the feelings of others, express their own emotional state, delay or even control their emotions, i.e. they learn to "manage their emotions" (Kádár, A., 2012). Therefore, it is important that teacher education institutions and teacher training should place more emphasis on the development of emotional intelligence. This development is necessary for two reasons. Firstly, as our research has shown, the number of teachers who become emotionally weak, putting their own and their students' mental health at risk, increases in proportion to the length of time in the profession. On the other hand, their relational skills suggest that the majority of these teachers are capable of effective interpersonal relationships, as they are well-intentioned, willing to care about others, and even their strong desire to conform is underpinned by a desire to maintain good social relationships (Baracsi, 2011).
Propagation of VLF Waves Below Anisotropic Ionosphere Models With a Dipping Static Magnetic Field

A semi-infinite homogeneous ionosphere with a dipping static magnetic field is used as an approximation to the upper region of a cylindrically stratified ionosphere model. The presence of a vertical static magnetic field component is neglected in the lower stratified regions. The presence of TM modes in the space between the earth and the ionosphere excites coupled TE and TM modes in the upper half space, and these TE fields also propagate in the cylindrically stratified region and in the space between the earth and ionosphere. The TE waves modify the effective surface impedance for the TM modes and the propagation parameters are determined by an iterative solution of the modal equation. Propagation parameters are calculated numerically for a homogeneous sharply-bounded ionosphere and also for stratified ionosphere models. The interference distance D of the two lowest waveguide modes is increased for propagation in the east-to-west (EW) direction relative to the west-to-east (WE) direction for frequencies less than 25 kHz and for the angles between the vertical and the direction of the static magnetic field in the range of 20° to 60°. These results are consistent with the recently reported measurements by Crombie (1966). The attenuation rates computed for the sharply bounded ionosphere model are in excess of 5 dB/1000 km for EW direction of propagation, but are lower in the stratified ionosphere models.
Effects of dietary interventions focused on adding base in the management of metabolic acidosis in adults with chronic kidney disease: A protocol for systematic review and meta-analysis of randomized clinical trials

Background: Metabolic acidosis is a common complication of chronic kidney disease (CKD) which can impair the function of multiple organs and accelerate CKD progression to kidney failure. The condition is usually treated with sodium bicarbonate (NaHCO3), which is an alkali salt. Although effective, alkali therapy has numerous side effects including gastric discomfort and bloating, with many people having difficulty tolerating higher doses. Research has shown that base producing fruit and vegetables may have the ability to increase serum bicarbonate concentrations similar to what is achieved with alkali therapy, but also provides added benefits. This systematic review aims to identify, critically-appraise and meta-analyze findings from randomized clinical trials (RCTs) comparing the effects of dietary interventions, including base producing fruit and vegetables, on serum bicarbonate concentrations as well as other factors related to kidney function in adult patients with CKD. Methods: RCTs (in adult participants (18 years of age or older), with CKD will be included in the study. Studies will be excluded if participants are undergoing dialysis or have chronic obstructive pulmonary disease (COPD) requiring oxygen therapy. The interventions of interest are any dietary intervention aimed at manipulating dietary acid load, compared with usual care, no treatment or placebo. Our primary outcome measure will be changes in serum bicarbonate concentration, while other parameters related to kidney function will be considered as secondary outcomes. A knowledge synthesis librarian developed a literature search strategy for MEDLINE (Ovid). The search strategy was then adjusted for use in Cochrane Central (Ovid), Embase (Ovid), Web of Science Core Collection (Clarivate) and CINAHL (EBSCO). Two independent reviewers will select studies for eligibility in Covidence and data extraction will be conducted using a custom MS Excel worksheet. We are planning to perform meta-analysis wherever possible using random effects model. Standardized mean difference (95% confidence interval) and risk ratio will be used to present continuous and dichotomous data, respectively. The assessment of publication bias will be performed using funnel plots and Eggers regression test while I2 statistics will be used to assess heterogeneity. We are planning to perform subgroup analysis to deal with potential heterogeneity.
Aesthetics in the Eugenics Movement: A Critical Examination

Abstract:Although multiple scholars have pushed music education to embrace the aesthetic as a curricular and pedagogical touchstone, research surrounding this aesthetic turn has largely framed aesthetics as a sensory experience rather than a social technology (one that can both liberate and oppress). In response, I address the following question: how do uncritical aesthetic philosophies and the experiences they engender act as a means of oppression within music education? By way of example, I approach this question through a text analysis of writings on aesthetics from The Eugenics Review, a long-running publication that disseminated eugenics news and research. In doing so, I construct a eugenical theory of aesthetics that illuminates how eugenicists used aesthetics to enact what Foucault defines as pastoral power and assert control of bodies and populations through education. I then frame the writings of Carl Seashore (a pioneering music education researcher and avowed eugenicist) within this eugenical theory of aesthetics, revealing the ways that Seashore used aesthetic theory to forward eugenical arguments. I conclude with implications for contemporary educators and researchers, sounding a call for a deep and critical examination of all aesthetic formations within music education.
Text Localization and Character Extraction in Natural Scene Images using Contourlet Transform and SVM Classifier

The objective of this study is to propose a new method for text region localization and character extraction in natural scene images with complex background. In this paper, a hybrid methodology is suggested which extracts multilingual text from natural scene image with cluttered backgrounds. The proposed approach involves four steps. First, potential text regions in an image are extracted based on edge features using Contourlet transform. In the second step, potential text regions are tested for text content or non-text using GLCM features and SVM classifier. In the third step, detection of multiple lines in localized text regions is done and line segmentation is performed using horizontal profiles. In the last step, each character of the segmented line is extracted using vertical profiles. The experimentation has been done using images drawn from own dataset and ICDAR dataset. The performance is measured in terms of the precision and recall. The results demonstrate the effectiveness of the proposed method, which can be used as an efficient method for text recognition in natural scene images.
On the gauge for the Neumann problem in the half space

SUMMARY. We consider the gauge function G for the Neumann problem for J4-f g in the half space D ? {(a, x) 6 Rd : a > 0}, where q is independent of a and is periodic in X. It is shown that if G j? oo, then G is a bounded continuous function on Cl(D). If H(x) = 00 J G(<x, x)d<z # oo, it is shown that the corresponding Feynman-Kac semi-group decays 0 exponentially. The gauge function plays a central role in studying the Neumann problem for the Schr? dinger operator, \ &+q, in a bounded domain. The gauge func tion for th3 Neumann problem is defined in terms of the reflected Brownian motion. If the gauge function is not identically infinite, then the so called gauge theorem states that it is a bounded continuous function and that the corresponding Feynman-Kac semigroup exponentially decays ; (and in such a case the existence of a unique solution to the Neumann problem is guaran teed). A crucial ingredient of the proof of the gauge theorem is that the transition probability density function of the reflected Brownian motion in a bounded region is bounded away from zero ; see Chung and Hsu [2], Chung
2 Boundary conditions in Chern – Simons

We consider the most general asymptotically anti-de Sitter boundary conditions in three-dimensional Einstein gravity with negative cosmological constant. The metric contains in total twelve independent functions, six of which are interpreted as chemical potentials (or non-normalizable fluctuations) and the other half as canonical boundary charges (or normalizable fluctuations). Their presence modifies the usual Fefferman–Graham expansion. The asymptotic symmetry algebra consists of two sl(2)k current algebras, the levels of which are given by k = `/(4GN ), where ` is the AdS radius and GN the three-dimensional Newton constant.
Analytic methods in combinatorial number theory

Analytic methods in combinatorial number theory (“Analitiese metode in kombinatorise getalleteorie”) L. Baker Mathematics Division, Department of Mathematical Sciences, University of Stellenbosch, Private Bag X1, 7602 Matieland, South Africa Thesis: MSc (Math) October 2015 Two applications of analytic techniques to combinatorial problems with number-theoretic flavours are shown. The first is an application of the real saddle point method to derive second-order asymptotic expansions for the number of solutions to the signum equation of a general class of sequences. The second is an application of more elementary methods to yield asymptotic expansions for the number of partitions of a large integer into powers of an integer b where each part has bounded multiplicity. ii Stellenbosch University https://scholar.sun.ac.za