Miracle-dz/UniFAR-FTUs huggingface dataset:
IL-13 deficiency exacerbates lung damage and impairs epithelial-derived type 2 molecules during nematode infection

IL-13 is tissue protective during acute lung injury caused by nematode migration and specifically regulates type 2 epithelial cell effector functions. IL-13 is implicated in effective repair after acute lung injury and the pathogenesis of chronic diseases such as allergic asthma. Both these processes involve matrix remodelling, but understanding the specific contribution of IL-13 has been challenging because IL-13 shares receptors and signalling pathways with IL-4. Here, we used Nippostrongylus brasiliensis infection as a model of acute lung damage comparing responses between WT and IL-13-deficient mice, in which IL-4 signalling is intact. We found that IL-13 played a critical role in limiting tissue injury and haemorrhaging in the lung, and through proteomic and transcriptomic profiling, identified IL-13-dependent changes in matrix and associated regulators. We further showed a requirement for IL-13 in the induction of epithelial-derived type 2 effector molecules such as RELM-α and surfactant protein D. Pathway analyses predicted that IL-13 induced cellular stress responses and regulated lung epithelial cell differentiation by suppression of Foxa2 pathways. Thus, in the context of acute lung damage, IL-13 has tissue-protective functions and regulates epithelial cell responses during type 2 immunity.
Extremal problems for pairs of triangles in a convex polygon

A convex geometric hypergraph or cgh consists of a family of subsets of a strictly convex set of points in the plane. The study of cghs is motivated by problems in combinatorial geometry, and was studied at length by Bras and by Aronov, Dujmovic, Morin, Ooms and da Silveira. In this paper, we determine the extremal functions for five of the eight configurations of two triangles exactly and another one asymptotically. We give conjectures for two of the three remaining configurations. Our main results solve problems posed by Frankl, Holmsen and Kupavskii on intersecting triangles in a cgh. In particular, we determine the exact maximum size of an intersecting family of triangles whose vertices come from a set of $n$ points in the plane.
Physiological Ca2+ Transients Versus Pathological Steady-State Ca2+ Elevation, Who Flips the ROS Coin in Skeletal Muscle Mitochondria

Mitochondria are both the primary provider of ATP and the pivotal regulator of cell death, which are essential for physiological muscle activities. Ca2+ plays a multifaceted role in mitochondrial function. During muscle contraction, Ca2+ influx into mitochondria activates multiple enzymes related to tricarboxylic acid (TCA) cycle and oxidative phosphorylation, resulting in increased ATP synthesis to meet the energy demand. Pathophysiological conditions such as skeletal muscle denervation or unloading also lead to elevated Ca2+ levels inside mitochondria. However, the outcomes of this steady-state elevation of mitochondrial Ca2+ level include exacerbated reactive oxygen species (ROS) generation, sensitized opening of mitochondrial permeability transition pore (mPTP), induction of programmed cell death, and ultimately muscle atrophy. Previously, both acute and long-term endurance exercises have been reported to activate certain signaling pathways to counteract ROS production. Meanwhile, electrical stimulation is known to help prevent apoptosis and alleviate muscle atrophy in denervated animal models and patients with motor impairment. There are various mechanistic studies that focus on the excitation-transcription coupling framework to understand the beneficial role of exercise and electrical stimulation. Interestingly, a recent study has revealed an unexpected role of rapid mitochondrial Ca2+ transients in keeping mPTP at a closed state with reduced mitochondrial ROS production. This discovery motivated us to contribute this review article to inspire further discussion about the potential mechanisms underlying differential outcomes of physiological mitochondrial Ca2+ transients and pathological mitochondrial Ca2+ elevation in skeletal muscle ROS production.
Target identification of a novel unsymmetrical 1,3,4‐oxadiazole derivative with antiproliferative properties

1,3,4‐Oxadiazole derivatives are widely used in research on antineoplastic drugs. Recently, we discovered a novel unsymmetrical 1,3,4‐oxadiazole compound with antiproliferative properties called 2j. To further investigate its possible targets and molecular mechanisms, RNA‐seq was performed and the differentially expressed genes (DEGs) were obtained after treatment. Data were analyzed using functional (Gene Ontology term) and pathway (Kyoto Encyclopedia of Genes and Genomes) enrichment of the DEGs. The hub genes were determined by the analysis of protein‐protein interaction networks. The connectivity map (CMap) information provided insight into the model action of antitumor small molecule drugs. Hub genes have been identified through function gene networks using STRING analysis. The small molecular targets obtained by CMap comparison showed that 2j is a tubulin inhibitor and it acts mainly affecting tumor cells through the cell cycle, FoxO signaling pathway, apoptotic, and p53 signaling pathways. The possible targets of 2j could be TUBA1A and TUBA4A. Molecular docking results indicated that 2j interacts at the colchicine‐binding site on tubulin.
On the Impact of Soft Photons on $B\rightarrow K \ell^+ \ell^-$

We give detailed results of $\mathcal{O}(\alpha)$ QED corrections (both real emission and virtual corrections) to $B\to K\ell^+\ell^-$ modes. Requiring the real emission to be gauge invariant, the structure of the contact term(s) is fixed. The calculation is done with a fictitious photon mass as the IR regulator and results are shown to be independent of it, establishing cancellation of the soft divergences. Results are presented for a choice of photon energy, $k_{max}$, and photon angle $\theta_{cut}$. The QED effects are negative, thereby reducing the rate compared to that without QED effects. Electron channels are shown to receive large corrections ($\mathcal{O}(20\%)$). Impact on lepton flavour universality ratio, $R^{\mu e}_K$ are also discussed.
Learning Curves for Analysis of Deep Networks

A learning curve models a classifier's test error as a function of the number of training samples. Prior works show that learning curves can be used to select model parameters and extrapolate performance. We investigate how to use learning curves to analyze the impact of design choices, such as pre-training, architecture, and data augmentation. We propose a method to robustly estimate learning curves, abstract their parameters into error and data-reliance, and evaluate the effectiveness of different parameterizations. We also provide several interesting observations based on learning curves for a variety of image classification models.
Data Privacy in Journalistic Knowledge Platforms

Journalistic knowledge platforms (JKPs) leverage data from the news, social media and other sources. They collect large amounts of data and attempt to extract potentially news-relevant information for news production. At the same time, by harvesting and recombining big data, they can challenge data privacy ethically and legally. Knowledge graphs offer new possibilities for representing information in JKPs, but their power also amplifies long-standing privacy concerns. This paper studies the implications of data privacy policies for JKPs. To do so, we have reviewed the GDPR and identified different areas where it potentially conflicts with JKPs.
Fine‐grained management of cloud‐native applications, based on TOSCA

Containers and container‐based orchestrators allow deploying and managing multi‐service applications over cloud platforms, by coupling the lifecycle of each application service to that of its hosting container. In this use case letter, we demonstrate how the OASIS standard TOSCA and Toskose allow overcoming such a coupling by enabling to exploit Docker containers as system containers where to independently deploy and manage application services. More precisely, we show how TOSCA and Toskose enable a fine‐grained, service‐aware management of a third‐party multi‐service application on top of existing Docker‐based container orchestrators (such as Docker Compose and Kubernetes) and independently of whether the application is deployed on premises or on a public cloud (such as MS Azure).
Symbolic Vs Sub-symbolic AI Methods: Friends or Enemies?

There is a long and unresolved debate between the symbolic and sub-symbolic methods. However, in recent years, there is a push towards in-between methods. In this work, we provide a comprehensive overview of the symbolic, sub-symbolic and in-between approaches focused in the domain of knowledge graphs, namely, schema representation , schema matching , knowledgegraphcompletion , linkprediction , entityresolution , entityclassification and tripleclassification . Wecriticallypresent key characteristics, advantages and disadvantages of the main algorithms in each domain, and review the use of these methods in knowledge graph related applications.
Gold nanoparticles for diagnostic development

Nanotechnology has become a topic of interest in various fields including biomedicine. The term refers to materials that are less than 100 nm in at least one dimension. Nanotechnology has gained considerable interest in biomedicine because the materials involved have large surface areas, which affect their physical and chemical properties. Nanoparticles of various materials such as gold, iron oxide, silver, carbon nanotubes, graphene, zinc oxide, alumina, silica, and titania have been studied and used extensively in biomedicine. The most common applications are diagnostics, theranostics, drug delivery, and imaging.
Studies on some determinants of virulence in Alcelaphine herpesvirus-1

Malignant catarrhal fever (MCF) is a fatal lymphoproliferative disease of Artiodactyla. The disease is caused by infection of susceptible hosts with one of two gammaherpesviruses, Alcelaphine herpesvirus-1 (AHV-1) or Ovine herpesvirus-2 (OHV-2). On primary isolation, AHV-1 infectivity is cell-associated and the virus can induce MCF following inoculation into susceptible hosts. Cell free virus which is pathogenic for cattle is observed following low serial passage of the virus in cell cultures. After further serial passage cell free virus is observed, but this virus cannot produce disease experimentally. AHV-1 genomic rearrangements occur during the transition from virulence to attenuation. Two genes, encoding putative protein 5 (P-5) and protein 1 (P1), are truncated during this rearrangement. The aim of this study was determine the importance of these putative proteins in the pathogenesis ofAHV-1. Sequence encoding each of these proteins was cloned and the proteins expressed in vitro. Rabbits, a laboratory model for AHV-1, were successfully immunised with these proteins. Neither of these proteins however induced a protective immune response. Although both proteins are expressed in vitro, transcripts for these proteins could not be detected in vivo in animals reacting with MCF. During the course of this study, the complete sequence of the AHV-1 genome was published. P-l and P-5 were shown to form part of open reading frames (ORF) 50 and A7 respectively. These ORFs were therefore re-assessed to determine their positions in the attenuated and virulent virus. New isolates were obtained from cattle showing clinical MCF and also from wildebeest. Analysis of viral DNA derived from the new
Progress in Chlamydia psittaci vaccine development in poultry

Chlamydia psittaci, depending on its serovar, can infect humans, birds, and other animals and livestock. Its economic impact on poultry production, especially on turkeys and chickens, and potential zoonotic risk have driven the search for an effective vaccination protocol to prevent and control the infection and shedding of the organism. Currently, no vaccine is approved for use against avian chlamydiosis despite efforts in the past decades. The present genomic era presents an opportunity to establish an effective vaccination scheme, taking advantage of the major outer membrane protein (MOMP) as the major protective antigen of C. psittaci. The plasmid DNA expressing MOMP can be coupled with optimisation of controllable factors during vaccination such as codon optimisation (through formation of polyplexes and lipoplexes), route of administration, vaccination schedule, addition of adjuvants/co-stimulatory factors such as cytokines and CpG motifs, and recombination with other poultry pathogens such as viruses. The development of an effective vaccine against C. psittaci will protect susceptible poultry from infection and production performance losses and reduce the zoonotic risk and minimise the emergence of antibiotic-resistant C. psittaci strains.
Data augmentation as stochastic optimization

We present a theoretical framework recasting data augmentation as stochastic optimization for a sequence of time-varying proxy losses. This provides a unified approach to understanding techniques commonly thought of as data augmentation, including synthetic noise and label-preserving transformations, as well as more traditional ideas in stochastic optimization such as learning rate and batch size scheduling. We prove a time-varying Monro-Robbins theorem with rates of convergence which gives conditions on the learning rate and augmentation schedule under which augmented gradient descent converges. Special cases give provably good joint schedules for augmentation with additive noise, minibatch SGD, and minibatch SGD with noise.
A Study on the Korean-Version of the Youth Attitudes toward Noise Scale

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2020 Korean Academy of Speech-Language Pathology and Audiology A Study on the Korean-Version of the Youth Attitudes toward Noise Scale
Finding the K-best paths in evacuation network

The problem of K-shortest paths between two nodes in network has been extensively studied, offering several efﬁcient algorithms for different applications. These algorithms, so-called ranking methods, aim to compute the ﬁrst shortest path then the second one etc. It’s well known that the computation in these methods is based only on one criterion which is generally the distance or the time. Often a single criterion is not sufﬁcient in some real-world problems (road network, internet, etc.) where one or several supplementarycriteria(suchascost, capacity, security, etc.) mustalsobetakenintoconsideration. Thismulti-criteriaoptimization, so-called labeling algorithm, aims to compute a Pareto front that represents a set of non-dominated pathways. However it is very difﬁcult to make a decision on which K − best paths to choose among this set, and especially when this sub-set of paths serves as a data input for a sensitive problem such as the evacuation. In the event of this, buildings located in dangerous area must leave to a safety zone via an established evacuation network. We present in this paper a ranking methods enabling the computation of a set of K-best paths between an origin-destination pair. The free-ﬂow travel time, the capacity and the number of lanes of roads are the criteria which are considered when computing the K-best paths among buildings and shelters associated. The strategy applied here and the optimization criteria used in these methods aim both to convert the mono-criteria aspect to a multi-criteria one combining between time and trafﬁc.
Author Profiling in Social Media with Multimodal Information

This paper summarizes the thesis: ”Author Profiling in Social Media with Multimodal Information. ” Our solution uses a multimodal approach to extracting information from written messages and images shared by users. Previous work has shown the existence of useful information for this task in these modalities; however, our proposal goes further, demonstrating the complementarity of the modalities when merging these two sources of information. To do this, we propose to transform images to texts, and with them, to have the same framework of representation for both kinds of information, which allow to achieve their fusion. Our work explores different methods for extracting information either from the text and the images. To represent the extracted information, different distributional term representations approaches were explored in order to identify the topics addressed by the user. For this purpose, an evaluation framework was proposed in order to identify the most appropriate method for this task. The results show that the textual descriptions of the images contain useful information for the author profiling task, and that the fusion of textual information with information extracted from the images increases the accuracy of this task.
PubMed 2.0

Abstract After years of strategic planning, the National Library of Medicine has introduced an updated and redesigned version of its PubMed health sciences research website. The new website features a more modern and responsive interface, especially on mobile devices. Tools and features have been relocated to make them more intuitive for new users. While not without some turbulence and slight discomfort for long-time users adjusting to the modernized interface and search engine, the new version of the PubMed website introduced in 2020 succeeds in the website’s time-honored task of collecting and making freely accessible high-quality health sciences information and resources.
Surface-Codes-Based Quantum Communication Networks

In this paper, we propose the surface codes (SCs)-based multipartite quantum communication networks (QCNs). We describe an approach that enables us to simultaneously entangle multiple nodes in an arbitrary network topology based on the SCs. We also describe how to extend the transmission distance between arbitrary two nodes by using the SCs. The numerical results indicate that transmission distance between nodes can be extended to beyond 1000 km by employing simple syndrome decoding. Finally, we describe how to operate the proposed QCN by employing the software-defined networking (SDN) concept.
Phloem transport of assimilates in relation to flowering time and senescence in barley grown with different availabilities of nitrogen and phosphorus

ABSTRACT Understanding the way in which N and P availability affects the transport of sugar and amino acids is crucial to improve grain quality and yield. Thus, in the present study, two greenhouse and field experiments were conducted with barley plants grown with different N and P availabilities to assess the dynamics of the phloem transport of assimilates in relation to the beginning of flowering and senescence. The phloem transport of assimilates decreased before the beginning of protein degradation in all treatments, but the onset of flowering and senescence varied according to the N and P availability, as evidenced by the concentrations of proteins, amino acids, and sugar and the gene expression of senescence-related proteases and all glutamine synthetase isoforms. In N-deficient plants, the phloem transport decreased before flowering, but only when P was not limiting; in N- and P-sufficient plants it decreased at flowering; and in P-deficient plants it decreased after flowering. Therefore, only N-deficient but P-sufficient plants have a post-anthesis period with high export rate of assimilates. This alteration of phenology in relation to phloem leads to important consequences in assimilate utilization, as shown by the higher yield and N content of the former compared to P-deficient plants.
Automatic System for COVID-19 Diagnosis

During the last months, the virus COVID 19 spread globally, quickly and affected many people. This last, is an infection caused by severe acute respiratory. Unfortunately, the number of cases increases significantly and early diagnosis of this disease can help to save the health of patient and his entourage by stopping contamination. In this paper, we propose a process of COVID 19 diagnosis in Chest X-rays. This process is composed of three main steps. The first one is the feature extraction using four approaches. The second one is the feature selection phase using a new feature selection approach. The last phase is the classification. The classifier used in this approach is composed of four supervised classification approaches. The proposed work has been tested COVID-19 in X-ray images obtained by PyImageSearch.
A novel hybrid approach towards movie recommender systems

Abstract Collaborative and content-based filtering are the majorly used approaches towards implementing recommender systems which can successfully predict the item(s) to be recommended to users based upon their preferences. Each of the methods has its own advantages and disadvantages that are specific to the situation they are used in. The hybrid approach aims to combine both techniques in multiple ways to optimize results and overcome shortcomings. In this paper, we propose a hybrid approach based recommendation engine to improve accuracy. While content based recommendations are made on the similarity of items’ attributes, collaborative recommendations are based on similarity of users. Collaborative filtering is achieved by matrix factorization technique. One of the most effective algorithms for matrix factorization: Singular Value Decomposition (SVD) has been used to perform collaborative filtering and combined with content based model to predict the item ratings per user. The paper aims to achieve the final result with minimum possible errors as per user preferences and recommended items.
An Ultrametric Random Walk Model for Disease Spread Taking into Account Social Clustering of the Population

We present a mathematical model of disease (say a virus) spread that takes into account the hierarchic structure of social clusters in a population. It describes the dependence of epidemic’s dynamics on the strength of barriers between clusters. These barriers are established by authorities as preventative measures; partially they are based on existing socio-economic conditions. We applied the theory of random walk on the energy landscapes represented by ultrametric spaces (having tree-like geometry). This is a part of statistical physics with applications to spin glasses and protein dynamics. To move from one social cluster (valley) to another, a virus (its carrier) should cross a social barrier between them. The magnitude of a barrier depends on the number of social hierarchy levels composing this barrier. Infection spreads rather easily inside a social cluster (say a working collective), but jumps to other clusters are constrained by social barriers. The model implies the power law, 1−t−a, for approaching herd immunity, where the parameter a is proportional to inverse of one-step barrier Δ. We consider linearly increasing barriers (with respect to hierarchy), i.e., the m-step barrier Δm=mΔ. We also introduce a quantity characterizing the process of infection distribution from one level of social hierarchy to the nearest lower levels, spreading entropy E. The parameter a is proportional to E.