Miracle-dz/UniFAR-FTUs huggingface dataset:
Electronic structure of epitaxial graphene nanoribbons on SiC(0001)

We present electronic structure calculations of few-layer epitaxial graphene nanoribbons on SiC(0001). Trough an atomistic description of the graphene layers and the substrate within the extended H\"{u}ckel Theory and real/momentum space projections we argue that the role of the heterostructure's interface becomes crucial for the conducting capacity of the studied systems. The key issue arising from this interaction is a Fermi level pinning effect introduced by dangling interface bonds. Such phenomenon is independent from the width of the considered nanostructures, compromising the importance of confinement in these systems.
Keyphrase extraction from Slovak court decisions

Keyphrase extraction is a vital subtask of text summarization and comparison, through which we can obtain the most relevant set of words and phrases that describe the content of a given document. In this paper we test multiple approaches of unsupervised keyword extraction on a set of court decisions. These approaches are TF - IDF , YAKE ! and a graph-based weighted PageRank algorithm. We combine these algorithms with a dictionary-based word embedding method in order to capture the semantic relationships between the potential keyphrases. Extracted keyphrases can be used for semantic indexing of court decisions, which can help with finding decisions with similar content. Abstract Manually extracted keyphrases 1 The complainant (lector) demanded via judicial proceedings that the defendant pays the fullpriceofthein-voicefortheservicesprovided(realizationofprofessionaltraining). The defendant, who was the complainant’s customer, paid the invoice only in part (liability for delay) due to considering the services provided by the complainant to be of poor quality (liability for defects). The defendant has also demanded a refund. The complainant the court cancel duty support and maintain against two from high school, legal who are able to earn a living wage. The defendants agreed with the cancellation of the duty to support and maintain.
Modelling the Rhizosphere Priming Effect in Combination with Soil Food Webs to Quantify Interaction between Living Plant, Soil Biota and Soil Organic Matter

A model of rhizosphere priming effect under impact of root exudate input into rhizosphere soil was developed as an important process of the plant-soil interaction. The model was based on the concept of nitrogen (N) mining, compensating for the N scarcity in exudates for microbial growth by accelerating SOM mineralisation. In the model, N deficiency for microbial growth is covered (“mined”) by the increased SOM mineralisation depending on the C:N ratio of the soil and exudates. The new aspect in the model is a food web procedure, which calculates soil fauna feeding on microorganisms, the return of faunal by-products to SOM and mineral N production for root uptake. The model verification demonstrated similar magnitude of the priming effect in simulations as in the published experimental data. Model testing revealed high sensitivity of the simulation results to N content in exudates. Simulated CO2 emission from the priming can reach 10–40% of CO2 emission from the whole Ah horizon of boreal forest soil depending on root exudation rates. This modeling approach with including food web activity allows quantifying wider aspects of the priming effect functioning including ecologically important available N production.
Determining the Willingness of Organic Agricultural Enterprises to Accept Product Price

Received : 19/07/2022 Accepted : 15/09/2022 The study’s main purpose is to to determine the price levels in the market and their willingness to accept higher prices of organic farming enterprises. For this purpose, enterprises engaged in organic farming activities in Konya were interviewed. A total of 883 organic farming enterprises in Konya grow 123 kinds of organic products, and as the products change, the organic structures of agricultural products change and their marketing channels, strategies and price formations also differ. In this context, 219 surveys were conducted in 13 product groups classified by TURKSTAT. In line with the data obtained as a result of the survey, the social, economic, production and marketing characteristics of the organic farming enterprises and the effects of the marketing structures of organic products on their willingness to accept prices were investigated using the Willingness to Accept (WTA) method, which is one of the conditional valuation methods. Furthermore, the marginal effects of each factor were determined by constructing the equation of the ordinal probit regression to be used to estimate the function of the WTA curve. As a result, suggestions have been developed for optimal price formation in the organic agriculture sector, where the marginal benefit is at the forefront, due to the high level of healthy life and environmental awareness, as well as marginal income, unlike traditional agricultural enterprises.
Review Article Effects of Lycopene Attenuating Injuries in Ischemia and Reperfusion

Tissue and organ ischemia can lead to cell trauma, tissue necrosis, irreversible damage, and death. While intended to reverse ischemia, reperfusion can further aggravate an ischemic injury (ischemia-reperfusion injury, I/R injury) through a range of pathologic processes. An I/R injury to one organ can also harm other organs, leading to systemic multiorgan failure. A type of carotenoid, lycopene, has been shown to treat and prevent many diseases (e.g., rheumatoid arthritis, cancer, diabetes, osteoporosis, male infertility, neurodegenerative diseases, and cardiovascular disease), making it a hot research topic in health care. Some recent researches have suggested that lycopene can evidently ameliorate ischemic and I/R injuries to many organs, but few clinical studies are available. Therefore, it is essential to review the e ﬀ ects of lycopene on ischemic and I/R injuries to di ﬀ erent organs, which may help further research into its potential clinical applications.
A Systematic Analysis for Cardiovascular Disease Classification Using Deep Learning

The processing of medical data has profited from automation and contemporary computing breakthroughs, which have given rise to several novel instructional approaches. In both traditional and cutting-edge disciplines, deep learning has emerged as a cutting-edge machine learning paradigm. Deep learning algorithms have developed into supervised, semi-supervised, and unsupervised modes for a variety of real-time applications. The technology has shown to be broadly applicable in image processing, computer vision, medical diagnostics, robotics, and control operation. Deep learning is essential in the field of medical science for recognizing various diseases and solving health issues. The deep learning revolution will significantly alter cardiovascular imaging within the next decade. To ensure that deep learning may meaningfully impact clinical practice, it is crucial for medical practitioners to stay up with these breakthroughs. This evaluation is intended to be a preliminary step in that process. In this study cardiovascular disease diagnosis and classification have been examined using different state-of-the-art deep learning approaches. Deep Neural Networks can be used to improve the classification of heart disease as a whole in a crucial field called heart illness. The classification process can be carried out using a variety of methods, such as DL, KNN, SVM, ANN Nave Bayes, Random Forest, SSD, DNN, and TDNN where DL exhibited maximum accuracy. Although deep learning-based automated cardiovascular classification algorithms have shown highly accurate results, they have not yet been widely used by healthcare professionals.
A model for polarized microwave foreground emission from interstellar dust

The upcoming generation of cosmic microwave background experiments face a major challenge in detecting the weak cosmic B-mode signature predicted as a product of primordial gravitational waves. To achieve the required sensitivity these experiments must have impressive control of systematic effects and detailed understanding of the foreground emission that will influence the signal. In this paper, we present templates of the intensity and polarization of emission from one of the main Galactic foregrounds, interstellar dust. These are produced using a model which includes a three-dimensional description of the Galactic magnetic field, examining both large and small scales. We also include in the model the details of the dust density, grain alignment and the intrinsic polarization of the emission from an individual grain. We present here Stokes parameter template maps at 150 GHz and provide an online repository (http://www.imperial.ac.uk/people/c.contaldi/fgpol) for these and additional maps at frequencies that will be targeted by upcoming experiments such as EBEX, Spider and SPTpol.
The nature of the cataclysmic variable PT Per

We present a study of the cataclysmic variable star PT Per based on archival XMMNewton X-ray data and new optical spectroscopy from the WHT with ISIS. The X-ray data show deep minima which recur at a period of 82 minutes and a hard, unabsorbed X-ray spectrum. The optical spectra of PT Per show a relatively featureless blue continuum. From an analysis of the X-ray and optical data we conclude that PT Per is likely to be a magnetic cataclysmic variable of the polar class in which the minima correspond to those phase intervals when the accretion column rotates out of the eld of view of the observer. We suggest that the optical spectrum, obtained around 4 years after the X-ray coverage, is dominated by the white dwarf in the system, implying that PT Per was in a low accretion state at the time of the observations. An analysis of the likely system parameters for PT Per suggests a distance of 90 pc and a very low-mass secondary, consistent with the idea that PT Per is a \period-bounce" binary. Matching the observed absorption features in the optical spectrum with the expected Zeeman components constrains the white dwarf polar eld to be Bp 25 27 MGauss.
Instance segmentation of 3D woven fabric from tomography images by Mathematical Morphology and Deep Learning methods

In the ﬁeld of composite materials, mesoscale modeling based on X-ray computed tomography are very widespread nowadays. This descriptive method requires image processing to identify the diﬀerent objects within the material. In the present study, two diﬀerent instance segmentation approaches are proposed: 1) a method based on Mathematical Morphology and 2) a Deep Learning one. Both methods are applied to determine the yarns paths and their envelopes. We succeed in both tasks on a dry 3D ply-to-ply angle-interlock fabric at low compaction level. In absence of manual labelling of the yarns envelopes, we manage to train a Deep Convolutional Neural Network (DCNN) on the pseudo-labeling provided by the morphological method, improving the latter and showing the potential of deep learning for image segmentation in this context, when yarns cross-sections are labelled by distance functions. At a higher level of compaction, we also manage to recover the yarn paths thanks to deep learning.
RADIATION TECHNOLOGY FOR THE MANUFACTURE OF MEDICAL PRODUCTS WITH NANOSILVER: FROM DEVELOPMENT TO COMMERCIALIZATION

Material Methods. High molecular weight polymers, silver salts, and water have been used. The electron irradiation method, optical spectroscopy, electron microscopy, microbiological analysis, and the method for curing thermal injuries and purulent wounds. Results. The regularities of the effect of radiation on the microstructure and properties of hydrogels based on the polyvinyl alcohol — polyethylene glycol system and on the formation and stability of silver nanoparticles in the composition of 3D polymer networkshave been established. A technology for manufacturing a metal-water-polymer nanocomposite with nanosilver has been developed;the bactericidal properties of the nanocomposite have been experimentally demonstrated. The technology formanufacturingmedical products from this nanocomposite under the HYDROBINT trademark has been developed and put into production. The organizational and technical procedures for the state certification of HYDROBINT medical products, asestablished by the legislation of Ukraine, have been described. The medical results of their use have been illustrated. A road map of developer’sactions for commercialization of innovation product has been proposed. Conclusions. Electronic irradiation of polymer hydrogels makes it possible to create new composite materials with properties relevant for the treatment of wounds and inflammations. The products made of such composites are effective in medical practice and commercially attractive in the market.Practical recommendations for the commercialization of an R & D innovation in the form of a roadmap for the developer’s actions have been offered.
Polarization signatures of unresolved radio sources

We investigate how the imprint of Faraday rotation on radio spectra can be used to determine the geometry of radio sources and the strength and structure of the surrounding magnetic fields. We model spectra of Stokes Q and U for frequencies between 200 MHz and 10 GHz for Faraday screens with large-scale or small-scale magnetic fields external to the source. These sources can be uniform or 2D Gaussians on the sky with transverse linear gradients in rotation measure (RM), or cylinders or spheroids with an azimuthal magnetic field. At high frequencies the spectra of all these models can be approximated by the spectrum of a Gaussian source; this is independent of whether the magnetic field is large-scale or small-scale. A sinc spectrum in polarized flux density is not a unique signature of a volume where synchrotron emission and Faraday rotation are mixed. A turbulent Faraday screen with a large field coherence length produces a spectrum which is similar to the spectrum of a partial coverage model. At low and intermediate frequencies, such a Faraday screen produces a significantly higher polarized signal than the depolarization model by Burn, as shown by a random walk model of the polarization vectors. We calculate RM spectra for four frequency windows. Sources are strongly depolarized at low frequencies, but RMs can be determined accurately if the sensitivity of the observations is sufficient. Finally, we show that RM spectra can be used to differentiate between turbulent foreground models and partial coverage models.
Research on cone-beam CT image reconstruction algorithm based on compressed sensing

With the development of computed tomography (CT) technology, how to reconstruct high-quality pathological images under low-dose X-ray radiation has become the focus of attention. Compressed sensing theory has become a research hotspot because of its good reconstruction quality under incomplete data. In compressed sensing theory, the design of projection matrix and total variational model is the key factor to determine the quality of reconstruction. In this paper, after the cone beam projection is rearranged into fan beam, a fan beam projection matrix model is designed. Based on the traditional distance driven model, the forward and back projection distance driven model is used to roughly estimate the image, and the multilevel scheme (MLS) is introduced to further improve the reconstruction quality of the image. The experimental results show that under the condition of incomplete projection data, the reconstructed image has less artifacts, complete edge details and clear image.
The 'Minimal' viscosity and elliptic flow at RHIC

We show from covariant transport theory that, for a massless ideal gas equation of state, even a small shear viscosity to entropy density ratio $\eta \approx s/(4 \pi)$ generates significant 15-30% dissipative corrections to elliptic flow for conditions expected in mid-peripheral (b = 8 fm) Au+Au collisions at $\sqrt{s_{NN}} \sim 200$ GeV at RHIC.
A Family of Hybrid Stochastic Conjugate Gradient Algorithms for Local and Global Minimization Problems

This paper contains two main parts, Part I and Part II, which discuss the local and global minimization problems, respectively. In Part I, a fresh conjugate gradient (CG) technique is suggested and then combined with a line-search technique to obtain a globally convergent algorithm. The finite difference approximations approach is used to compute the approximate values of the first derivative of the function f. The convergence analysis of the suggested method is established. The comparisons between the performance of the new CG method and the performance of four other CG methods demonstrate that the proposed CG method is promising and competitive for finding a local optimum point. In Part II, three formulas are designed by which a group of solutions are generated. This set of random formulas is hybridized with the globally convergent CG algorithm to obtain a hybrid stochastic conjugate gradient algorithm denoted by HSSZH. The HSSZH algorithm finds the approximate value of the global solution of a global optimization problem. Five combined stochastic conjugate gradient algorithms are constructed. The performance profiles are used to assess and compare the rendition of the family of hybrid stochastic conjugate gradient algorithms. The comparison results between our proposed HSSZH algorithm and four other hybrid stochastic conjugate gradient techniques demonstrate that the suggested HSSZH method is competitive with, and in all cases superior to, the four algorithms in terms of the efficiency, reliability and effectiveness to find the approximate solution of the global optimization problem that contains a non-convex function.
An Efficient Optical Mura Compensation System for Large Liquid-Crystal Display Panels

Increased mura defect rates as liquid-crystal display (LCD) sizes and resolutions increase have become an issue of the utmost concern for large LCD panel makers. To address this issue, an efficient optical mura compensation (referred to as a de-mura) system for large LCD panels is proposed in this work. More specifically, the following measures were implemented to ensure the operation of the system with high reliability and efficiency: 1) an elliptic paraboloid (EP) model was proposed to deal with the measurement error caused by the viewing-angle vignetting in the LCD panel during imaging; 2) a time-domain filter and other preprocessing algorithms were built into the firmware of a high-resolution monochrome camera; 3) to accurately compensate for luminance mura, a fourth-order polynomial was applied to generate luminance de-mura data and on this basis, a local linear interpolation model was established to generate the chromaticity de-mura data; and 4) the parallel acceleration of the algorithm was achieved by using a combined central processing unit (CPU) multithreading—graphic processing unit (GPU) computing architecture. The experimental results show that the developed system and algorithm perform quite well, in terms of reliability and operational efficiency. The tact time (TT) for 4K and 8K LCD panels was less than 20 and 25 s, respectively, which fully meets manufacturers’ mass production requirements.
Linear-FM fuze signal enhancement based on WGAN

In order to solve the problem that the effect of jamming Linear-FM(LFM) fuze decreases in strong noise environment, this paper proposes a WGAN-based LFM fuze signal enhancement technology. Taking advantage of the obvious feature of the LFM signal in the time-frequency domain, we connect two WGANs in series for signal enhancement. The first WGAN learns to reduce the noise in the signal while converting a time-series signal into a spectrogram. The second WGAN learns to enhance the main frequency components of the signal while converting the spectrogram back to a time-series signal. The experimental results show that the algorithm proposed in this paper reduces the noise component and enhances the main frequency component in the signal, which improves the interference effect to the LFM fuze in strong noise environment.
Beyond land rights registration: understanding the mundane elements of land conflict in Ethiopia

ABSTRACT While land registration may increase the sense of security amongst landholders and provide a mechanism for resolving boundary disputes, its interaction with social, political-economic and ecological dynamics can actually generate conflicts by creating new opportunities by which some actors can assert claims or expand their landholdings, often at the expense of others. Conflicts over land cannot be understood without understanding the local dynamics with which they are intertwined. Drawing from case studies in the Amhara region of Ethiopia, this paper shows that, despite land registration and certification, there are widespread conflicts within and between households and state authorities regarding the usufruct of individual and communal lands. The paper argues that conflicts over land are complex and political and are linked to and embedded in the processes of commercialization, as well as in local social processes and power relations. These, in turn, influence and are shaped by the political economy of local governance and land administration processes, particularly in relation to the implementation of land registration. The paper highlights that land conflicts are attributed to a range of issues, including not only the challenges of governance in land registration but also population growth, commercialization, urbanization, inheritance and gender inequality, all of which intersect with corrupt land administration systems .
Why Tic Severity Changes from Then to Now and from Here to There

Much of the research regarding Tourette’s syndrome (TS) has focused on why certain individuals develop tics while others do not. However, a separate line of research focuses on the momentary influences that cause tics to increase or decrease in patients who are already known to have TS or another chronic tic disorder (CTD). Environmental and internal variables such as fatigue, anxiety, and certain types of thoughts all have been shown to worsen tic severity and may even overcome the positive effects of treatment. Other influences such as stress, distraction, and being observed have had mixed effects in the various studies that have examined them. Still, other variables such as social media exposure and dietary habits have received only minimal research attention and would benefit from additional study. Understanding the impact of these environmental and internal influences provides an opportunity to improve behavioral treatments for TS/CTD and to improve the lives of those living with these conditions. This review will examine the current literature on how these moment-to-moment influences impact tic expression in those with TS/CTD.