Miracle-dz/UniFAR-FTUs huggingface dataset:
Does TLS Exist in Canine Mammary Gland Tumours? Preliminary Results in Simple Carcinomas

Simple Summary Studies on the tumour microenvironment show that part of the body’s defence against neoplastic cells is carried out directly in the tumour through the organization of immune cellular aggregates, called tertiary lymphoid structures (TLSs). This study demonstrates the existence of TLS in canine mammary simple carcinomas, where some inflammatory infiltrates assume a follicle-like organization, especially in high-grade carcinomas and simulate the follicle of secondary lymphoid organs (SLOs). The role of TLS is controversial and it has been suggested that they contribute to an immunosuppressive environment or, on the contrary, have positive effects on neoplasm growth. Although canine mammary tumours have long been proposed as a model for studying breast cancer, there is still little research on the tumour stromal microenvironment in veterinary medicine and TLS evidence could allow for advances in understanding the process of tumour immunoediting. Abstract Neoplastic progression is influenced by the expression of tumour antigens that activate an anti-tumour immune response. Human medical studies show that this body defence is carried out in secondary lymphoid organs (SLOs) but also directly in the tumour through organized cellular aggregates that are called tertiary lymphoid structures (TLSs). However, their occurrence has different meanings in different tumour types. For example, the presence of TLSs in breast cancer is associated with the most aggressive subtypes. This paper aimed to study TLSs in canine mammary simple carcinomas. A morphological assessment of the inflammatory infiltrate was performed on H&E sections of fifty cases. Immunohistochemistry was then carried out to typify the inflammatory cells in the tumour microenvironment. Results showed that, sometimes, inflammatory infiltrates were organized in follicles close to high-grade carcinomas, simulating a lymphoid organization, as in breast cancer. Therefore, we can assume that even in canine mammary tumours, TLSs exist and they are entities to consider due to their presence in the most aggressive histotypes or tumours with a high degree of malignancy.
Multiplicative groups of division rings

Exactly 170 years ago, the construction of the real quaternion algebra by William Hamilton was announced in the Proceedings of the Royal Irish Academy. It became the first example of non-commutative division rings and a major turning point of algebra. To this day, the multiplicative group structure of quaternion algebras have not completely been understood. This article is a long survey of the recent developments on the multiplicative group structure of division rings.
Assessing the potential correlation of polymorphisms in the TMPRSS2 gene with severity of COVID 19 patients

Introduction and Aim: Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Once infected this virus induces several clinical disorders in humans. SARSCoV-2 enters cells via TMPRSS2. Genetic variation in TMPRSS2 could affect the severity of infection. The purpose of this study was to investigate how the (TMPRSS2) gene polymorphism affected COVID-19 severity in patients as well as the effect of age and comorbidities on infection. Materials and Methods: This cross-sectional analytical study comprised of 400 (185 male, 215 female) Covid-19-infected patients between ages 18-65 receiving treatment in hospitals at Baghdad, Iraq. The patients were divided into three groups: mild, moderate, and severe based on the severity of Covid-19 infection. Baseline data was collected for each patient through interview and questionnaire. Blood collected from patients was subjected to DNA extraction and detecting polymorphisms within SNPs of the TMPRSS2 gene. Results: The present investigation indicated higher age to be significantly associated with severe COVID-19 infection when compared to moderate and mild infection (36.14 ± 12.716 vs. 48.52 ± 17.513 vs. 59.26 ± 16.035) (F= 3.697, df: 64, P= 0.000). Patients with comorbidities was associated with a greater rate of severe Covid-19 infection (74.2% vs. 25.8%). However, individuals without comorbidities had a considerably lower rate of mild and moderate Covid-19 infection (13.9% vs. 86.1%) and (36% vs. 64%), respectively (x^2: 97.930, df: 2, P = 0.000). SNPs; (rs383510, rs12329760) within the transmembrane TMPRSS2–7113 was studied and we found no significant (P> 0.05) association for these SNPs to severity of Covid-19 infection. Conclusion: The results show that the allelic variation within the TMPRSS2 (SNP rs2070788) gene to be linked to increasing illness severity in COVID-19 patients.
Stable type II blowup for the 7 dimensional 1-corotational energy supercritical harmonic map heat flow

We consider the energy-supercritical harmonic map heat flow from $\mathbb{R}^d$ into $\mathbb{S}^d$, under an additional assumption of 1-corotational symmetry. We are interested by the 7 dimensional case which is the borderline between the Type I blowup regime. We construct for this problem a stable finite time blowup solution under the condition of corotational symmetry that blows up via concentration of the universal profile $$u(r,t) \sim Q\left(\frac{r}{\lambda(t)}\right),$$ where $Q$ is the stationary solution of the equation and the speed is given by the rate $$\lambda(t) \sim \frac{\sqrt{(T-t)}}{|\log(T-t)|},$$ which corresponds to the speed predicted by Biernat.
Application of Two-Dimensional Entropy Measures to Detect the Radiographic Signs of Tooth Resorption and Hypercementosis in an Equine Model

Dental disorders are a serious health problem in equine medicine, their early recognition benefits the long-term general health of the horse. Most of the initial signs of Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) syndrome concern the alveolar aspect of the teeth, thus, the need for early recognition radiographic imaging. This study is aimed to evaluate the applicability of entropy measures to quantify the radiological signs of tooth resorption and hypercementosis as well as to enhance radiographic image quality in order to facilitate the identification of the signs of EOTRH syndrome. A detailed examination of the oral cavity was performed in eighty horses. Each evaluated incisor tooth was assigned to one of four grade–related EOTRH groups (0–3). Radiographs of the incisor teeth were taken and digitally processed. For each radiograph, two–dimensional sample (SampEn2D), fuzzy (FuzzEn2D), permutation (PermEn2D), dispersion (DispEn2D), and distribution (DistEn2D) entropies were measured after image filtering was performed using Normalize, Median, and LaplacianSharpening filters. Moreover, the similarities between entropy measures and selected Gray–Level Co–occurrence Matrix (GLCM) texture features were investigated. Among the 15 returned measures, DistEn2D was EOTRH grade–related. Moreover, DistEn2D extracted after Normalize filtering was the most informative. The EOTRH grade–related similarity between DistEn2D and Difference Entropy (GLCM) confirms the higher irregularity and complexity of incisor teeth radiographs in advanced EOTRH syndrome, demonstrating the greatest sensitivity (0.50) and specificity (0.95) of EOTRH 3 group detection. An application of DistEn2D to Normalize filtered incisor teeth radiographs enables the identification of the radiological signs of advanced EOTRH with higher accuracy than the previously used entropy–related GLCM texture features.
Dark Photons from Captured Inelastic Dark Matter Annihilation: Charged Particle Signatures

The dark sector may contain a dark photon that kinetically mixes with the Standard Model photon, allowing dark matter to interact weakly with normal matter. In previous work we analyzed the implications of this scenario for dark matter capture by the Sun. Dark matter will gather in the core of the Sun and annihilate to dark photons. These dark photons travel outwards from the center of the Sun and may decay to produce positrons that can be detected by the Alpha Magnetic Spectrometer (AMS-02) on the ISS. We found that the dark photon parameter space accessible to this analysis is largely constrained by strong limits on the spin-independent WIMP-nucleon cross section from direct detection experiments. In this paper we build upon previous work by considering the case where the dark sector contains two species of Dirac fermion that are nearly degenerate in mass and couple inelastically to the dark photon. We find that for small values of the mass splitting $\Delta \sim 100 ~\kev$, the predicted positron signal at AMS-02 remains largely unchanged from the previously considered elastic case while constraints from direct detection are relaxed, leaving a region of parameter space with dark matter mass $100 ~\gev \lesssim m_X \lesssim 10 ~\tev$, dark photon mass $1 ~\mev \lesssim m_{A'} \lesssim 100 ~\mev$, and kinetic mixing parameter $10^{-9} \lesssim \varepsilon \lesssim 10^{-8}$ that is untouched by supernova observations and fixed target experiments but where an inelastic dark sector may still be discovered using existing AMS-02 data.
The FABLE simulations: a feedback model for galaxies, groups, and clusters

NAH is supported by the Science and Technology Facilities Council (STFC). EP acknowledges support by the Kavli Foundation. DS and SS acknowledge support by the STFC and the European Research Council Starting Grant 638707 ‘Black holes and their host galaxies: co-evolution across cosmic time’. This work made use of the following DiRAC facilities (www.dirac.ac.uk): the Data Analytic system at the University of Cambridge [ funded by a BIS National E-infrastructure capital grant (ST/K001590/1), STFC capital grants ST/H008861/1 and ST/H00887X/1, and STFC DiRAC Operations grant ST/K00333X/1] and the COSMA Data Centric system at Durham University (funded by a BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grant ST/K00087X/1, DiRAC Operations grant ST/K003267/1 and Durham University). DiRAC is part of the National E-Infrastructure.
Two-side a posteriori error estimates for the DWR method

In this work, we derive two-sided a posteriori error estimates for the dual-weighted residual (DWR) method. We consider both single and multiple goal functionals. Using a saturation assumption, we derive lower bounds yielding the efficiency of the error estimator. These results hold true for both nonlinear partial differential equations and nonlinear functionals of interest. Furthermore, the DWR method employed in this work accounts for balancing the discretization error with the nonlinear iteration error. We also perform careful studies of the remainder term that is usually neglected. Based on these theoretical investigations, several algorithms are designed. Our theoretical findings and algorithmic developments are substantiated with some numerical tests.
Numerical simulation of compressible flows using two-phase observable Euler equations

Most fluid flow problems that are vital in engineering applications involve at least one of the following features: turbulence, shocks, and/or material interfaces. While seemingly different phenomena, these flows all share continuous generation of high wavenumber modes, which we term the '$k_\infty$ irregularity. ' In this work, an inviscid regularization technique called 'observable regularization' is proposed for the simulation of two-phase compressible flows. The proposed approach regularizes the equations at the level of the partial differential equation and as a result, any numerical method can be used to solve the system of equations. The regularization is accomplished by introducing an 'observability limit' that represents the length scale below which one cannot properly model or continue to resolve flow structures. An observable volume fraction equation is derived for capturing the material interface, which satisfies the pressure equilibrium at the interface. The efficacy of the observable regularization method is demonstrated using several test cases, including a one-dimensional material interface tracking, one-dimensional shock-tube and shock-bubble problems, and two-dimensional simulations of a shock interacting with a cylindrical bubble. The results show favorable agreement, both qualitatively and quantitatively, with available exact solutions or numerical and experimental data from the literature. The computational saving by using the current method is estimated to be about one order of magnitude in two-dimensional computations and significantly higher in three-dimensional computations. Lastly, the effect of the observability limit and best practices to choose its value are discussed.
Students’ Mobile Phone Practices for Academic Purposes: Strengthening Post-Pandemic University Digitalization

The COVID-19 pandemic is considered as a turning point that has impacted the digital transformation of higher education. However, the link between students′ mobile phone practices and university digitalization is not sufficiently or explicitly discussed. The purpose of this study is to provide evidence about university students′ mobile phone practices for academic purposes, and to contribute to the debate regarding post-pandemic university digitalization. The participants were 60 students studying in a Greek university, data were collected via an open-ended questionnaire, and descriptive content analysis was used to examine the qualitative data. Students mainly use their mobile phones for information searches (e.g., for assignments, videos, photos, graphs, simulations, online dictionaries, and scientific papers), easy and quick access to e-classes (e.g., course material/slides) and the faculty′s site, and for communication with peers (e.g., queries, sharing educational resources) and tutors. During mobile practices, students experience advantages (easy-quick searches, flexibility, familiarization with digital technology) and disadvantages (internet connectivity, unreliable information sources, distractions). Implications for students, educators, and university policy-organization (policymakers have a role in reshaping digitalization) are discussed. It is argued that mobile learning has the potential to strengthen university digitalization, thus affecting the sustainability of education in the post-pandemic era.
The space density of post-period minimum Cataclysmic Variables

Binary evolution theory predicts that accreting white dwarfs with sub-stellar companions dominate the Galactic population of cataclysmic variables (CVs). In order to test these predictions, it is necessary to identify these systems, which may be difficult if the signatures of accretion become too weak to be detected. The only chance to identify such "dead" CVs is by exploiting their close binary nature. We have therefore searched the Sloan Digital Sky Survey (SDSS) Stripe 82 area for apparently isolated white dwarfs that undergo eclipses by a dark companion. We found no such eclipses in either the SDSS or Palomar Transient Factory data sets among our sample of 2264 photometrically selected white dwarf candidates within Stripe 82. This null result allows us to set a firm upper limit on the space density, $\rho_0$, of dead CVs. In order to determine this limit, we have used Monte-Carlo simulations to fold our selection criteria through a simple model of the Galactic CV distribution. Assuming a $T_{WD}=7,500$ K, the resulting 2$\sigma$ limit on the space density of dead CVs is $\rho_0 \lesssim 2 \times 10^{-5}$ pc$^{-3}$, where $T_{WD}$ is the typical effective temperature of the white dwarf in such systems.
The asymmetries of the $B \to K^* \mu^+ \mu^-$ decay and the search of new physics beyond the Standard Model

In this paper, we compute the forward-backward asymmetry and the isospin asymmetry of the $B \to K^* \mu^+ \mu^-$ decay. The $B \to K^*$ transition form factors (TFFs) are key components of the decay. To achieve a more accurate QCD prediction, we adopt a chiral correlator for calculating the QCD light-cone sum rules for those TFFs with the purpose of suppressing the uncertain high-twist distribution amplitudes. Our predictions show that the asymmetries under the Standard Model and the Minimal Supersymmetric Standard Model with minimal flavor violation are close in shape for $q^2 \ge 6~{\rm GeV}^2$ and are consistent with the Belle, LHCb and CDF data within errors. When $q^2 < 2~{\rm GeV}^2$, their predictions behave quite differently. Thus a careful study on the $B \to K^* \mu^+ \mu^-$ decay within small $q^2$-region could be helpful for searching new physics beyond the Standard Model. As a further application, we also apply the $B \to K^*$ TFFs to the branching ratio and longitudinal polarization fraction of the $B\to K^*\nu\bar\nu$ decay within different models.
Classification of Brain Tumors using MRI images based on Convolutional Neural Network and Supervised Machine Learning Algorithms

Brain tumor is abnormal cells that originate from cranial tissue and is considered one of the most destructive diseases, and lead to the cause of death, where the early diagnosis is crucial for accelerating the therapy of brain tumors. Examining the patient's MRI scans is one traditional way of distinguishing brain cancers. The conventional approaches take a long time and are prone to human error, especially when dealing with huge amounts of data and diverse brain tumor classes. Artificial Intelligence (AI) is extremely useful for the strict detection and classification of several diseases in the brain. Convolutional Neural Network (CNN) is one of the modes techniques which act as a tumor classifier due to it shows high effectiveness for diagnosing brain tumors. That's why, in this research, we presented a hybrid method that merged a group of pre-trained deep learning CNN patterns with a group of supervised classifiers in machine learning called, k- Nearest Neighbor (KNN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA). We used an MRI image that consist of images of four brain tumor classes, namely glioma, meningioma, pituitary, and no tumor. We deduced the features extracted from the images by hiring three types of CNN called (GoogleNet, Shuffle-Net, and NasNet-Mobile). Depending upon the experimental consequences, ShuffleN et with SVM achieved the highest results according to the four categories of metrics evaluation that are Accuracy of 98.40%, Precision of 97%, Recall of 96.75%, and Fl-Score of 96.75%. Finally, we compared our results with different state-of-the-art papers recently published and our proposed method show outperforms compared them.
Dynamic Analysis of Closed Die Electromagnetic Sheet Metal Forming to Predict Deformation and Failure of AA6061-T6 Alloy Using a Fully Coupled Finite Element Model

This research presents a fully coupled 3D numerical model to analyse the dynamics of high-speed electromagnetic forming process for aluminium alloy AA6061-T6. The effect of Lorentz force distribution, velocity and kinetic energy on deformation, the bounce back effect and failure of the sheet has been investigated. Experiments were performed for AA6061-T6 alloy using an 18.750 KJ electromagnetic forming machine for varying the sheet thickness (0.5 mm, 1.02 mm and 1.63 mm) compared with the simulation results. The results showed that increasing the sheet thickness increases the Lorentz force due to a higher induced current. The inertial forces were more pronounced in thicker sheets (1.63 mm) as compared to the thinner sheets (0.5 mm and 1.02 mm), resulting in a higher bounce back effect for the thicker sheet. The numerical model accurately predicted the sheet failure for the 0.5-mm sheet, as also observed from the experimentation. The sheet deformation from simulations was found to be in good agreement with the experimental results.
Simulation of McKean–Vlasov SDEs with super-linear growth

We present two fully probabilistic Euler schemes, one explicit and one implicit, for the simulation of McKean–Vlasov Stochastic Differential Equations (MV-SDEs) with drifts of super-linear growth and random initial condition. We provide a pathwise propagation of chaos result and show strong convergence for both schemes on the consequent particle system. The explicit scheme attains the standard $1/2$ rate in stepsize. From a technical point of view, we successfully use stopping times to prove the convergence of the implicit method; although we avoid them altogether for the explicit one. The combination of particle interactions and random initial condition makes the proofs technically more involved. Numerical tests recover the theoretical convergence rates and illustrate a computational complexity advantage of the explicit over the implicit scheme. Comparative analysis is carried out on a stylized non-Lipschitz MV-SDE and a mean-field model for FitzHugh–Nagumo neurons. We provide numerical tests illustrating particle corruption effect where one single particle diverging can ‘corrupt’ the whole particle system. Moreover, the more particles in the system the more likely this divergence is to occur.
On the almost sure running maxima of solutions of affine neutral stochastic functional differential equations

This paper studies the large fluctuations of solutions of finite--dimensional affine stochastic neutral functional differential equations with finite memory, as well as related nonlinear equations. We find conditions under which the exact almost sure growth rate of the running maximum of each component of the system can be determined, both for affine and nonlinear equations. The proofs exploit the fact that an exponentially decaying fundamental solution of the underlying deterministic equation is sufficient to ensure that the solution of the affine equation converges to a stationary Gaussian process.
Dynamical Friction and the Evolution of Supermassive Black Hole Binaries: The Final Hundred-parsec Problem

The supermassive black holes originally in the nuclei of two merging galaxies will form a binary in the remnant core. The early evolution of the massive binary is driven by dynamical friction before the binary becomes “hard” and eventually reaches coalescence through gravitational-wave emission. We consider the dynamical friction evolution of massive binaries consisting of a secondary hole orbiting inside a stellar cusp dominated by a more massive central black hole. In our treatment, we include the frictional force from stars moving faster than the inspiralling object, which is neglected in the standard Chandrasekhar treatment. We show that the binary eccentricity increases if the stellar cusp density profile rises less steeply than . In cusps shallower than , the frictional timescale can become very long due to the deficit of stars moving slower than the massive body. Although including fast stars increases the decay rate, low mass-ratio binaries ( ) in sufficiently massive galaxies have decay timescales longer than one Hubble time. During such minor mergers, the secondary hole stalls on an eccentric orbit at a distance of order one-tenth the influence radius of the primary hole (i.e., for massive ellipticals). We calculate the expected number of stalled satellites as a function of the host galaxy mass and show that the brightest cluster galaxies should have of such satellites orbiting within their cores. Our results could provide an explanation for a number of observations, which include multiple nuclei in core ellipticals, off-center AGNs, and eccentric nuclear disks.
A necessary and sufficient condition for Ricci shrinkers to have positive AVR

In this short note we observe that a recent result of C. -W. Chen meshes well with earlier work of H. -D. Cao and D. -T. Zhou, O. Munteanu, J. Carrillo and L. Ni, and S. -J. Zhang to give a necessary and sufficient condition for complete noncompact shrinking gradient Ricci solitons to have positive asymptotic volume ratio.