Miracle-dz/UniFAR-FTUs huggingface dataset:
New Target for Prevention and Treatment of Neuroinflammation: Microglia Iron Accumulation and Ferroptosis

Microglia play an important role in maintaining central nervous system homeostasis and are the major immune cells in the brain. In response to internal or external inflammatory stimuli, microglia are activated and release numerous inflammatory factors, thus leading to neuroinflammation. Inflammation and microglia iron accumulation promote each other and jointly promote the progression of neuroinflammation. Inhibiting microglia iron accumulation prevents neuroinflammation. Ferroptosis is an iron-dependent phospholipid peroxidation-driven type of cell death regulation. Cell iron accumulation causes the peroxidation of cell membrane phospholipids and damages the cell membrane. Ultimately, this process leads to cell ferroptosis. Iron accumulation or phospholipid peroxidation in microglia releases a large number of inflammatory factors. Thus, inhibiting microglia ferroptosis may be a new target for the prevention and treatment of neuroinflammation.
The Efficacy of Vaccination in the Prevention of Renal and Genital Leptospirosis in Experimentally Infected Sheep

(1) Background: Leptospirosis, mainly determined by strains belonging to serogroup Sejroe, has a direct impact on the reproductive efficiency of ruminants, such as sheep. In Brazil, Leptospira santarosai serovar Guaricura, known to be able to chronically colonize the uterine environment, is of special note. Although vaccination minimizes the effects of acute disease, whether or not it can protect from renal colonization remains controversial, and its effects on the genital tract are unknown. In this context, the present study aims to investigate the efficacy of vaccination in the prevention of experimental genital leptospirosis. (2) Methods: Eighteen sheep were divided into three groups: one vaccinated with a polyvalent commercial bacterin, one vaccinated with an autologous bacterin, and one unvaccinated. After 14 days, the sheep were experimentally challenged with 108 leptospires (L. santarosai, serogroup Sejroe, serovar Guaricura, strain FV52) intraperitoneally. Serology and colonization of the urinary and genital tracts were carried out monthly by PCR for 210 days in all animals. (3) Results: Vaccination significantly elicited antibody titers with a predominance of agglutinins against serogroup Sejroe. Both urinary and genital infections were confirmed by PCR. Positivity in urine PCR was absent after D120, while genital infection persisted until the end of the study. Serological results and the finding that vaccination did not avoid renal colonization align with previous studies. Despite vaccination, Leptospira established chronic and asymptomatic colonization of the genital tract until D210, an outstanding finding that remains to be fully understood in its mechanisms. (4) Conclusions: This is the first study conducted to analyze the effects of vaccination in the prevention of genital leptospirosis.
Geodesic bulk diagrams on the Bruhat-Tits tree

Geodesic bulk diagrams were recently shown to be the geometric objects which compute global conformal blocks. We show that this duality continues to hold in $p$-adic AdS/CFT, where the bulk is replaced by the Bruhat-Tits tree, an infinite regular graph with no cycles, and the boundary is described by $p$-adic numbers, rather than reals. We apply the duality to evaluate the four-point function of scalar operators of generic dimensions using tree-level bulk diagrams. Relative to standard results from the literature, we find intriguing similarities as well as significant simplifications. Notably, all derivatives disappear in the conformal block decomposition of the four-point function. On the other hand, numerical coefficients in the four-point function as well as the structure constants take surprisingly universal forms, applicable to both the reals and the $p$-adics when expressed in terms of local zeta functions. Finally, we present a minimal bulk action with nearest neighbor interactions on the Bruhat-Tits tree, which reproduces the two-, three-, and four-point functions of a free boundary theory.
The Infrared Luminosity Function of Galaxies in the Coma Cluster

An infrared survey of the central 650 arcmin2 of the Coma Cluster is used to determine the H-band luminosity function for the cluster. Redshifts are available for all galaxies in the survey with H<14.5, and for this sample we obtain a good fit to a Schechter function with H*=11.13 and α=-0.78. These luminosity function parameters are similar to those measured for field galaxies in the infrared, which is surprising considering the very different environmental densities and, presumably, merger histories for field galaxies. For fainter galaxies, we use two independent techniques to correct for field galaxy contamination in the cluster population: the B-R color-magnitude relation and an estimate for the level of background and foreground contamination from the literature. Using either method, we find a steep upturn for galaxies with 14
350 μm Dust Emission from High-Redshift Quasars

We report detections of six high-redshift (1.8 ≤ z ≤ 6.4), optically luminous, radio-quiet quasars at 350 μm, using the SHARC II bolometer camera at the Caltech Submillimeter Observatory. Our observations double the number of high-redshift quasars for which 350 μm photometry is available. By combining the 350 μm measurements with observations at other submillimeter/millimeter wavelengths, for each source we have determined the temperature of the emitting dust (ranging from 40 to 60 K) and the far-infrared luminosity [ × 1013 L☉]. The combined mean spectral energy distribution of all high-redshift quasars with two or more rest-frame far-infrared photometric measurements is best fit with a graybody with temperature of 47 ± 3 K and a dust emissivity power-law spectral index of β = 1.6 ± 0.1. This warm dust component is a good tracer of the starburst activity of the quasar host galaxy. The ratio of the far-infrared to radio luminosities of infrared-luminous, radio-quiet high-redshift quasars is consistent with that found for local star-forming galaxies.
Volumetric evolution of elastic turbulence in porous media

Abstract Viscoelastic flow instability, which is compelled by elastic effects rather than inertia, can be driven to a chaotic state termed elastic turbulence (ET) manifested as strong velocity fluctuations with an algebraic decay in the frequency spectrum and increased mixing. We report the first spatiotemporally complete description of ET by considering a broad volume within a novel three-dimensional ordered porous medium, reconstructing flow at a micrometre characteristic length scale ($\text {Reynolds numbers} \ll 1$) via time-resolved microtomographic particle image velocimetry. Beyond a critical Weissenberg number of 2, we observe an elastic flow instability accompanied by an enhanced pressure drop with spectral characteristics typical of ET. Polymer chains in the ET flow state are advected along increasingly curved streamlines between pores such that they accumulate strain and generate a local flow instability evaluated per an established instability criterion based on local evaluation of elastic tensile stress and streamline curvature. The onset of ET leads to increased pore-scale resistance and positive feedback on upstream streamline curvature. ET is thus characterized by a continuous evolution between states of laminar and unstable flow: pores with unstable flow flood their adjacent peers and thus encourage straightened streamlines and flow stability across the array, while positive feedback from flow resistance on streamline curvature results in the instability propagating upstream along the array. By employing a geometrically ordered medium, we permit flow state communication between pores, yielding generalized insights highlighting the significance of spatial correlation and flow history, and thus provide new avenues for explaining the mechanisms of ET.
Performance Evaluation of UWB Active-Passive Two-Way Ranging Distance Estimation Matrix Weighting Methods

This paper explores least squares (LS), median (MED), inverse distance weighting (IDW), distance weighted estimator (DWE) and three different weighted least squares (WLS) methods for Ultra-Wideband (UWB) active-passive two-way ranging (AP-TWR) measurement matrix estimation. The proposed methods were tested with practical experiments in line-of-sight (LOS) and two different non-line-of-sight (NLOS) conditions, and were benchmarked against an active-only single-sided two-way ranging (SS-TWR) method. The results show that the proposed methods MED, IDW and DWE achieve comparable standard deviation values, while outperforming the root-mean-squared-error (RMSE) of SS-TWR ranging by up to 14.3% in LOS and 19.08% in NLOS conditions. The experiments validate that the MED, IDW and DWE methods for AP-TWR are NLOS-robust and achieve better RMSE performance than active-only SS-TWR ranging.
Syntax-based machine translation using dependency grammars and discriminative machine learning

Machine translation underwent huge improvements since the groundbreaking introduction of statistical methods in the early 2000s, going from very domain-specific systems that still performed relatively poorly despite the painstakingly crafting of thousands of ad-hoc rules, to general-purpose systems automatically trained on large collections of bilingual texts which manage to deliver understandable translations that convey the general meaning of the original input. These approaches however still perform quite below the level of human translators, typically failing to convey detailed meaning and register, and producing translations that, while readable, are often ungrammatical and unidiomatic. This quality gap, which is considerably large compared to most other natural language processing tasks, has been the focus of the research in recent years, with the development of increasingly sophisticated models that attempt to exploit the syntactical structure of human languages, leveraging the technology of statistical parsers, as well as advanced machine learning methods such as marging-based structured prediction algorithms and neural networks. The translation software itself became more complex in order to accommodate for the sophistication of these advanced models: the main translation engine (the decoder) is now often combined with a pre-processor which reorders the words of the source sentences to a target language word order, or with a post-processor that ranks and selects a translation according according to fine model from a list of candidate translations generated by a coarse model. In this thesis we investigate the statistical machine translation problem from various angles, focusing on translation from non-analytic languages whose syntax is best described by fluid non-projective dependency grammars rather than the relatively strict phrase-structure grammars or projectivedependency grammars which are most commonly used in the literature. We propose a framework for modeling word reordering phenomena between language pairs as transitions on non-projective source dependency parse graphs. We quantitatively characterize reordering phenomena for the German-to-English language pair as captured by this framework, specifically investigating the incidence and effects of the non-projectivity of source syntax and the non-locality of word movement w.r. t. the graph structure. We evaluated several variants of hand-coded pre-ordering rules in order to assess the impact of these phenomena on translation quality. We propose a class of dependency-based source pre-ordering approaches that reorder sentences based on a flexible models trained by SVMs and and several recurrent neural network architectures. We also propose a class of translation reranking models, both syntax-free and source dependency-based, which make use of a type of neural networks known as graph echo state networks which is highly flexible and requires extremely little training resources, overcoming one of the main limitations of neural network models for natural language processing tasks.
Quantum electromagnetic field in a three-dimensional oscillating cavity

We compute the photon creation inside a perfectly conducting, three dimensional oscillating cavity, taking the polarization of the electromagnetic field into account. As the boundary conditions for this field are both of Dirichlet and (generalized) Neumann type, we analyze as a preliminary step the dynamical Casimir effect for a scalar field satisfying generalized Neumann boundary conditions. We show that particle production is enhanced with respect to the case of Dirichlet boundary conditions. Then we consider the transverse electric and transverse magnetic polarizations of the electromagnetic field. For resonant frequencies, the total number of photons grows exponentially in time for both polarizations, the rate being greater for transverse magnetic modes.
Batman and Robin in Healthcare Knowledge Work: Human-AI Collaboration by Clinical Documentation Integrity Specialists

This article describes the successful collaboration “in the wild” between Clinical Documentation Integrity Specialists (CDIS) and an Artificial Intelligence (AI)-embedded software to conduct knowledge work. CDIS review patient charts in near real-time to improve clinicians’ documentation, with the goal to make medical documentation more accurate, consistent and complete. CDIS collaborate with an AI-embedded “Computer Assisted Coding” (CAC) system that scans records from the Electronic Healthcare Record and auto-suggests codes based on natural language processing. CDIS find the CAC's suggestions are often inaccurate—often humorously so. Still, they find the CAC to be a useful helper, like Robin is to Batman. This human-AI collaboration is contingent on several factors: the flexible integration of the AI into the workflow similar to the notion of unremarkable AI; supporting the CDIS’ sensemaking; the CDIS’ knowledge about the CAC being predictably unreliable, an experience by the CDIS of the AI's value; humans remaining in control; and ability to experiment with the AI, which spurs reflection and learning for these knowledge workers.
High Expression of CD58 and ALDH1A3 Predicts a Poor Prognosis in Basal-like Breast Cancer

Abstract Background/Aim: CD58 is an immune adhesion molecule on the cellular surface. It was previously found that a high expression of CD58 predicted a poor prognosis of patients with lower-grade gliomas. Therefore, the aim of this paper was to investigate the association between CD58 and breast cancer. Materials and Methods: CD58 gene expression data downloaded from cBioPortal was compared between the different subtypes of breast cancer. Clinical prognosis was examined using Kaplan-Meier analysis and multivariable Cox regression analysis. The association between CD58 expression and immune cell infiltration was estimated using the TIMER 2.0 web platform. Finally, the tumour sphere formation of aldehyde dehydrogenase 1 (ALDH1)high basal-like breast cancer stem cells in which CD58 was knocked down using siRNA was measured. Results: CD58 mRNA was mainly enriched in claudin-low and basal-like subtypes. The high expression of CD58 predicted a good prognosis in patients with luminal A and luminal B breast cancer. This prediction may be due to the association of immune cell infiltration with CD58. Notably, patients with luminal A breast cancer with a high expression of CD58 in association with ALDH1A3 exhibited a good prognosis; however, this did not apply to patients with basal-like breast cancer. The in vitro experiments revealed that knockdown of CD58 inhibited the tumour sphere formation ability of ALDH1high basal-like cancer cells. Conclusion: CD58 may function as a potential prognostic biomarker and therapeutic target in ALDH-positive basal-like cancer stem cells.
The asteroseismic surface effect from a grid of 3D convection simulations - I. Frequency shifts from convective expansion of stellar atmospheres

We analyse the effect on adiabatic stellar oscillation frequencies of replacing the near-surface layers in 1D stellar structure models with averaged 3D stellar surface convection simulations. The main difference is an expansion of the atmosphere by 3D convection, expected to explain a major part of the asteroseismic surface effect; a systematic overestimation of p-mode frequencies due to inadequate surface physics. We employ pairs of 1D stellar envelope models and 3D simulations from a previous calibration of the mixing-length parameter, alpha. That calibration constitutes the hitherto most consistent matching of 1D models to 3D simulations, ensuring that their differences are not spurious, but entirely due to the 3D nature of convection. The resulting frequency shift is identified as the structural part of the surface effect. The important, typically non-adiabatic, modal components of the surface effect are not included in the present analysis, but relegated to future papers. Evaluating the structural surface effect at the frequency of maximum mode amplitude, $\nu_{\rm max}$, we find shifts from $\delta\nu$=-0.8 microHz for giants at $\log g$=2.2 to -35 microHz for a ($T_{\rm eff}=6901$ K, $\log g$=4.29) dwarf. The fractional effect $\delta\nu(\nu_{\rm max})/\nu_{\rm max}$, ranges from -0.1% for a cool dwarf (4185 K, 4.74) to -6% for a warm giant (4962 K, 2.20).
Query Log Mining to Enhance User Experience in Search Engines

The Web is the biggest repository of documents humans have ever built. Even more, it is increasingly growing in size every day. Users rely on Web search engines (WSEs) for finding information on the Web. By submitting a textual query expressing their information need, WSE users obtain a list of documents that are highly relevant to the query. Moreover, WSEs tend to store such huge amount of users activities in query logs. Query log mining is the set of techniques aiming at extracting valuable knowledge from query logs. This knowledge represents one of the most used ways of enhancing the users search experience. According to this vision, in this thesis we firstly prove that the knowledge extracted from query logs suffer aging effects and we thus propose a solution to this phenomenon. Secondly, we propose new algorithms for query recommendation that overcome the aging problem. Moreover, we study new query recommendation techniques for efficiently producing recommendations for rare queries. Finally, we study the problem of diversifying Web search engine results. We define a methodology based on the knowledge derived from query logs for detecting when and how query results need to be diversified and we develop an efficient algorithm for diversifying search results.
The TACS Model: Understanding Primary School Teachers’ Adoption of Computer Science Pedagogical Content

Context. With the introduction of Computer Science (CS) into curricula worldwide, teachers’ adoption of CS pedagogical content is essential to ensure the long-term success of reform initiatives. Continuing Professional Development (CPD) programs play a key role in this process. Unfortunately, adoption is seldom evaluated in CS-CPDs or CPDs in general. The result is a dearth of studies (i) modelling teachers’ adoption of CS pedagogical content or (ii) investigating factors influencing the uptake of this new discipline. Both aspects are crucial to design and characterize successful CPD programs. Objectives. We thus propose the Teachers’ Adoption of CS (TACS) model to investigate factors influencing the adoption of CS pedagogical content by teachers who are following a mandatory CS-CPD program. More specifically, the model proposes that contextual factors (e.g., age, gender, and general teaching experience), prior factors (e.g., experience, and CS perception), and acceptance factors (e.g., interest, and self-efficacy) may impact teachers’ adoption of CS pedagogical content. Methods. The study included 180 grades 5 and 6 teachers (students aged 9–11) that were following a mandatory CS-CPD program. The CS-CPD program involved participation in three-day-long sessions distributed over the 2019–2020 academic year. In between sessions, with the support of instructional coaches in the schools, teachers were encouraged, but not required, to adopt the CS pedagogical content. Therefore, during the CPD, and employing surveys based on the TACS model, we evaluated teachers’ adoption of the proposed content and investigated how the different factors influenced it. Results. At the PD-level, the results indicate that self-efficacy and interest queried during the CS-CPD are indicative of CS pedagogical content adoption. To shed more light on the relationship between these metrics, a more in-depth analysis was conducted with n = 92 teachers whose responses could be matched between sessions. While interest relates to how teachers adopt CS pedagogical content overall, both interest and self-efficacy are necessary to ensure the likelihood of a specific activity being adopted. Finally, individual teacher characteristics appear to impact adoption, with teachers with low experience with Information and Communication Technologies (ICT) requiring onboarding, while middle-aged teachers require convincing to adopt CS pedagogical content. Conclusion. Three takeaways emerge from the study. First, the analyses confirm the foundation of the TACS model. Second, the findings establish the key role that interest plays in said model. Finally, the results support the relationship between the contextual, prior and acceptance factors on the adoption of primary school CS pedagogical content.
Sumsets in primes containing almost all even positive integers

Let $A$ be a subset of primes up to $x$. If we assume $A$ is well-distributed (in the Siegel-Walfisz sense) in any arithmetic progressions to moduli $q\leqslant(\log x)^c$ for any $c>0$, then the sumset $A+A$ has density 1/2 in the natural numbers as $x$ tends to infinity, which also yields almost all even positive integers could be represented as the sums of two primes in $A$ as $x$ tends to infinity. This result, improving the previous results in such special case, could be compared with the classical estimation for the exceptional set of binary Goldbach problem.
Supplementary Material to “ColorFormer: Image Colorization via Color Memory assisted Hybrid-attention Transformer”

We list the detailed architecture of our ColorFormer in Table 1, where an input image size of 256 × 256 is assumed. For Stage1 to Stage4, “Concat n × n” indicates a concatenation of n × n neighboring features in a patch. This operation results in a downsampling of the feature map by a rate of n. “96-d” denotes a linear layer with an output dimension of 96. “win. sz. 7 × 7” indicates a multi-head self-attention module with window size of 7 × 7. “[ ]×2” means a GLH-Transformer block consisting of a GL-MSA and a SW-MSA. For Stage5 to Stage7, we merge features from corresponding encoder stage and upscale feature map with PixelShuffle operations. Stage8 is our proposed Color Memory module, which stores color priors to enhance features. Stage9 is used to refine features and generate ab maps.
Search for chargino and neutralino at Run II of the Tevatron Collider

In this dissertation we present a search for the associated production of charginos and neutralinos, the supersymmetric partners of the Standard Model bosons. We analyze a data sample representing 745 pb{sup -1} of integrated luminosity collected by the CDF experiment at the p{bar p} Tevatron collider. We compare the Standard Model predictions with the observed data selecting events with three leptons and missing transverse energy. Finding no excess, we combine the results of our search with similar analyses carried out at CDF and set an upper limit on the chargino mass in SUSY scenarios.