Miracle-dz/UniFAR-FTUs huggingface dataset:
Phosphoproteomic Analyses Reveal Signaling Pathways That Facilitate Lytic Gammaherpesvirus Replication

Lytic gammaherpesvirus (GHV) replication facilitates the establishment of lifelong latent infection, which places the infected host at risk for numerous cancers. As obligate intracellular parasites, GHVs must control and usurp cellular signaling pathways in order to successfully replicate, disseminate to stable latency reservoirs in the host, and prevent immune-mediated clearance. To facilitate a systems-level understanding of phosphorylation-dependent signaling events directed by GHVs during lytic replication, we utilized label-free quantitative mass spectrometry to interrogate the lytic replication cycle of murine gammaherpesvirus-68 (MHV68). Compared to controls, MHV68 infection regulated by 2-fold or greater ca. 86% of identified phosphopeptides – a regulatory scale not previously observed in phosphoproteomic evaluations of discrete signal-inducing stimuli. Network analyses demonstrated that the infection-associated induction or repression of specific cellular proteins globally altered the flow of information through the host phosphoprotein network, yielding major changes to functional protein clusters and ontologically associated proteins. A series of orthogonal bioinformatics analyses revealed that MAPK and CDK-related signaling events were overrepresented in the infection-associated phosphoproteome and identified 155 host proteins, such as the transcription factor c-Jun, as putative downstream targets. Importantly, functional tests of bioinformatics-based predictions confirmed ERK1/2 and CDK1/2 as kinases that facilitate MHV68 replication and also demonstrated the importance of c-Jun. Finally, a transposon-mutant virus screen identified the MHV68 cyclin D ortholog as a viral protein that contributes to the prominent MAPK/CDK signature of the infection-associated phosphoproteome. Together, these analyses enhance an understanding of how GHVs reorganize and usurp intracellular signaling networks to facilitate infection and replication.
Consistent Kaluza-Klein reductions for general supersymmetric AdS solutions

For the most general supersymmetric solutions of type IIB supergravity consisting of a warped product of $Ad{S}_{5}$ with a five-dimensional manifold ${M}_{5}$, we construct an explicit consistent Kaluza-Klein reduction on ${M}_{5}$ to minimal $D=5$ gauged supergravity. Thus, any solution of the gauged supergravity can be uplifted on ${M}_{5}$ to obtain an exact solution of type IIB supergravity. We also show that for general $Ad{S}_{4}\ifmmode\times\else\texttimes\fi{}S{E}_{7}$ solutions, where $S{E}_{7}$ is a seven-dimensional Sasaki-Einstein manifold, and for a general class of supersymmetric solutions that are a warped product of $Ad{S}_{4}$ with a seven-dimensional manifold ${N}_{7}$, there is an analogous consistent reduction to minimal $D=4$ gauged supergravity.
Fast and accurate object detection by means of recursive monomial feature elimination and cascade of SVM

Support Vector Machines (SVMs) are an established tool for pattern recognition. However, their application to real-time object detection (such as detection of objects in each frame of a video stream) is limited due to the relatively high computational cost. Speed is indeed crucial in such applications. Motivated by a practical problem (hand detection), we show how second-degree polynomial SVMs in their primal formulation, along with a recursive elimination of monomial features and a cascade architecture can lead to a fast and accurate classifier. For the considered hand detection problem we obtain a speed-up factor of 1600 with comparable classification performance with respect to a single, unreduced SVM.
Development of Hybrid Models and a System for Forecasting the Indicators of the Russian Economy

Scenario forecasting of social and economic indicators is highly important for strategic planning of the country's economic development. In this regard, it is very important to build a forecasting system for a model of the main economic indicators of the country and/or region for experts. At present time there is lack of such systems on the market. The article describes a hybrid system of models and a prototype of an analytical forecasting system Horizon that is based on using a hybrid forecasting approach, has learning capabilities and adaptability. Over the past 3 years, many works have been published on the development of time series forecasting models by means of artificial networks and deep learning. Unfortunately, the models developed are not implemented in an information system, but rather as separate mathematical calculations using various analysis packages or Python libraries. The authors’ system of econometric models of the Russian economy indicators and the process of development of the Horizon system are described. Hybrid forecasting models were developed within the framework of the Horizon system for 70 indicators of Russian economy. The forecasts calculated in the RESUMEN: El pronóstico de escenarios de indicadores sociales y económicos es muy importante para la planificación estratégica del desarrollo económico del país. En este sentido, es muy importante construir un sistema de pronóstico para un modelo de los principales indicadores económicos del país y / o la región para expertos. En la actualidad hay falta de tales sistemas en el mercado. El artículo describe un sistema híbrido de modelos y un prototipo de un sistema de pronóstico analítico Horizon que se basa en el uso de un enfoque de pronóstico híbrido y tiene capacidades de aprendizaje y adaptabilidad. En los últimos 3 años, se han publicado muchos trabajos sobre el desarrollo de modelos de pronóstico de series de tiempo por medio de redes artificiales y aprendizaje profundo. Desafortunadamente, los modelos desarrollados no se implementan en un sistema de información, sino más bien como cálculos matemáticos separados que utilizan varios paquetes de análisis o bibliotecas Python. Se describe el sistema de autores de modelos econométricos de los indicadores de la economía rusa y el proceso de desarrollo del sistema Horizon. Los modelos de pronóstico híbridos se desarrollaron en el marco del sistema Horizon para 70 indicadores de la system showed high accuracy for 80% of indicators.
Subcutaneous apomorphine increases regional cerebral blood flow in parkinsonian patients via peripheral mechanisms.

1. We have measured regional cerebral blood flow (rCBF) and motor function before and after the subcutaneous (s.c.) injection of apomorphine in parkinsonian patients deprived of their usual treatment for at least 48 h. 2. Nineteen patients, pretreated with domperidone (20 mg three times daily for 48 h), received a mean dose of 5.8 mg s.c. apomorphine. All patients switched 'on'. The mean motor score was significantly improved (-65%, P less than 0.01) but no significant change in rCBF was observed. 3. Seven other patients, not pretreated with domperidone, received a lower dose (0.3 mg) of s.c. apomorphine. No change in motor score was observed while the mean rCBF significantly increased (+12%, P less than 0.05). 4. We conclude that s.c. apomorphine increases rCBF in parkinsonian patients. This effect is independent of the central therapeutic effects of the drug. It is mediated by the stimulation of dopaminergic receptors of the cerebral vessels. These receptors are located outside the cerebral blood brain barrier and can be considered as 'peripheral' ones.
Speech Perception in Infants

Discriminiationi of synthetic speech sounds was studied in 1- and 4-month-old infants. The speech sounds varied along an acoustic dimension previously shown to cue phonemic distinctions among the voiced and voiceless stop consonants in adults. Discriminability was measured by an increase in conditioned response rate to a second speech sound after habituation to the first speech sound. Recovery from habituation was greater for a given acoustic difference when the two stimuli were from different adult phonemic categories than when they were from the same category. The discontinuity in discrimination at the region of the adult phonemic boundary was taken as evidence for categorical perception.
Rigorous numerical models for the dynamics of complex Henon mappings on their chain recurrent sets

We describe a rigorous and efficient computer algorithm for building a model of the dynamics of a polynomial diffeomorphism of C2 on its chain recurrent set, $R$, and for sorting points into approximate chain transitive components. Further, we give explicit estimates which quantify how well this algorithm approximates the chain recurrent set and distinguishes the chain transitive components. We also discuss our implementation for the family of Henon mappings, $f_{a,c}(x,y) = (x^2 + c - ay, x)$, into a computer program called Hypatia, and give several examples of running Hypatia on Henon mappings.
SNP discovery in candidate adaptive genes using exon capture in a free‐ranging alpine ungulate

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein‐coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR‐based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease‐regulating functions (e.g. Ovar‐DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene‐targeted SNP discovery and subsequent SNP chip genotyping using low‐quality samples in a nonmodel species.
A Krylov Subspace Method for Option Pricing

We consider the pricing of financial contracts that are based on two or three underlyings and are modelled using time dependent linear parabolic partial differential equations (PDEs). To provide accurate and efficient numerical approximations to the financial contract's value, we decompose the numerical solution into two parts. The first part involves the spatial discretization, using finite difference methods of the governing PDE. From this a large system of ordinary differential equations (ODEs) with a special affine structure is obtained. On the second part, we develop highly efficient numerical methods to approximate the exact solution of the system of ODEs with a high level of accuracy. We compare our approach, which is based of Krylov subspace methods, with the Crank-Nicolson and Alternating Direct Implicit (ADI) methods on Rainbow and Basket options, European call options using Heston stochastic volatility, and power reverse dual currency (PRDC) swaps with Bermudan and knockout features.
Approximation Theory for Connectivity of Ad Hoc Wireless Networks With Node Faults

In this letter, we propose an approximation theory for connectivity of general random geometric graphs (RGGs) with stochastic node faults, which is regarded as an abstract model of ad hoc wireless sensor networks (WSNs) with unreliable nodes. In the model, each node in an RGG is independently at fault and the disconnection probability of a resulting survival network is evaluated. The proposed approximation formula for the probability is asymptotically correct and reveals the phase transition phenomena of connectivity in the model. In addition, we obtain phase transition thresholds of a practical Rayleigh single-input single-output (SISO) model and Rayleigh multiple-input multiple-output (MIMO) model, which shows the effectiveness of the MIMO system against attenuation and random node faults. The numerical results in Rayleigh MIMO model show that the approximation formula well estimates the connection probability even for finite graphs and that it provides useful information for design of WSN immune to node faults.
Variational estimation of experimental fluid flows with physics-based spatio-temporal regularization

We present a variational approach to motion estimation of instationary experimental fluid flows from image sequences. Our approach extends prior work along two directions: (i) the full incompressible Navier–Stokes equation is employed in order to obtain a physically consistent regularization which does not suppress turbulent variations of flow estimates; (ii) regularization along the time axis is employed as well, but formulated in a receding horizon manner in contrast to previous approaches to spatio-temporal regularization. This allows for a recursive on-line (non-batch) implementation of our variational estimation framework. Ground-truth evaluations for simulated turbulent flows demonstrate that due to imposing both physical consistency and temporal coherency, the accuracy of flow estimation compares favourably even with advanced cross-correlation approaches and optical flow approaches based on higher order div–curl regularization.
Role for sagA and siaA in Quorum Sensing and Iron Regulation in Streptococcus pyogenes

ABSTRACT Streptococcus pyogenes is a ubiquitous and versatile pathogen that causes a variety of infections with a wide range of severity. The versatility of this organism is due in part to its capacity to regulate virulence gene expression in response to the many environments that it encounters during an infection. We analyzed the expression of two potential virulence factors, sagA and siaA (also referred to as pel and htsA, respectively), in response to conditions of varying cell densities and iron concentrations. The sagA gene was up-regulated in conditioned medium from a wild-type strain but not from sagA-deficient mutants, and the gene was also up-regulated in the presence of streptolysin S (SLS), the gene product of sagA, thus indicating that this gene or its product is involved in density-dependent regulation of S. pyogenes. By comparison, siaA responded in a manner consistent with a role in iron acquisition since it was up-regulated under iron-restricted conditions. Although siaA expression was also up-regulated in the presence of SLS and in conditioned media from both wild-type and sagA-deficient mutants, this up-regulation was not growth phase dependent. We conclude that sagA encodes a quorum-sensing signaling molecule, likely SLS, and further support the notion that siaA is likely involved in iron acquisition.
Multicarrier SPWM Control Techniques for Three Phase Eleven Level Diode Clamped Multilevel Inverter and Hybrid Inverter with Reduced Number of Components

A comparative analysis of three phase eleven level diode clamped multilevel inverter (DCMLI) and hybrid inverter is performed in this paper in which the later requires fewer carrier signals, less number of devices and gate drive circuits. The performance is evaluated using phase disposition (PD), alternate phase opposition disposition (APOD) and carrier overlapping (CO) sinusoidal pulse width modulation (SPWM) methods. The hybrid multilevel inverter has superior features over diode clamped multilevel inverters and is more efficient since the positive levels of the inverter that are generated by high frequency switches (level generation part), are reversed by low frequency switches (polarity generation part) when the voltage polarity is required to be changed for negative polarity. Therefore, the overall cost and complexity of the hybrid inverter are greatly reduced particularly for higher inverter output voltage levels. Simulation is performed for three phase eleven level diode clamped multilevel inverter and hybrid multilevel inverter using MATLAB/Simulink for induction motor load and the total harmonic distortion is evaluated at different load torques.
Switzerland's rise to a wealthy nation: Competition and contestability as key success factors

This paper argues that economic competition and political contestability are two key determinants of the successful development of the Swiss economy in the nineteenth and twentieth century. We describe how Switzerland evolved from a relatively poor country with no natural resources and net emigration in 1800 to one of the richest countries of the world two hundred years later. Based on quantitative and qualitative evidence, we argue that early internationalization, open and flexible markets as well as a high degree of competition were crucial for the development of the Swiss economy. In addition, the Swiss political system with its direct democratic elements and the implemented principle of subsidiarity created political contestability that maintained government efficiency and led to political stability throughout history. The combination of these elements seems to explain the Swiss success, but also to make it difficult for other
Modèles de Markov Cachés et Modèle de Longueur pour la Reconnaissance de l’Ecriture Arabe à Basse Résolution

Résumé Nous présentons dans ce papier un système de reconnaissance automatique de l’écriture arabe à vocabulaire ouvert, basse résolution, basé sur les Modèles de Markov Cachés. De tels modèles sont très performants lorsqu’il s’agit de résoudre le double problème de segmentation et de reconnaissance pour des signaux correspondant à des séquences d’états différents, par exemple en reconnaissance de la parole ou de l’écriture cursive. La spécificité de notre ap-proche est dans l’introduction des modèles de longueurs pour la reconnaissance de l’Arabe imprimé. Ces derniers sont inférés automatiquement pendant la phase d’entraînement et leur implémentation est réalisée par une simple altération des modèles de chaque caractère compo-sant les mots. Dans notre approche, chaque mot est représenté par une séquence des sous mo-dèles, ces derniers étant représentés par des états dont le nombre est proportionnel à la lon-gueur de chaque caractère
Impact of aerosols on convective clouds and precipitation

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular, the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancies between results simulated by models, as well as those between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large‐scale analyses, (4) results from cloud‐resolving model simulations, and (5) results from large‐scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol‐cloud‐precipitation interactions are suggested.
Cardiac dysfunctions following spinal cord injury

The aim of this article is to analyze cardiac dysfunctions occurring after spinal cord injury (SCI). Cardiac dysfunctions are common complications following SCI. Cardiovascular disturbances are the leading causes of morbidity and mortality in both acute and chronic stages of SCI. We reviewed epidemiology of cardiac disturbances after SCI, and neuroanatomy and pathophysiology of autonomic nervous system, sympathetic and parasympathetic. SCI causes disruption of descendent pathways from central control centers to spinal sympathetic neurons, originating into intermediolateral nuclei of T1–L2 spinal cord segments. Loss of supraspinal control over sympathetic nervous system results in reduced overall sympathetic activity below the level of injury and unopposed parasympathetic outflow through intact vagal nerve. SCI associates significant cardiac dysfunction. Impairment of autonomic nervous control system, mostly in patients with cervical or high thoracic SCI, causes cardiac dysrrhythmias, especially bradycardia and, rarely, cardiac arrest, or tachyarrhytmias and hypotension. Specific complication dependent on the period of time after trauma like spinal shock and autonomic dysreflexia are also reviewed. Spinal shock occurs during the acute phase following SCI and is a transitory suspension of function and reflexes below the level of the injury. Neurogenic shock, part of spinal shock, consists of severe bradycardia and hypotension. Autonomic dysreflexia appears during the chronic phase, after spinal shock resolution, and it is a life–threatening syndrome of massive imbalanced reflex sympathetic discharge occurring in patients with SCI above the splanchnic sympathetic outflow (T5–T6). Besides all this, additional cardiac complications, such as cardiac deconditioning and coronary heart disease may also occur. Proper prophylaxis, including nonpharmacologic and pharmacological strategies and cardiac rehabilitation diminish occurrence of the cardiac dysfunction following SCI. Each type of cardiac disturbance requires specific treatment.
Leakage flux modelling of multi-winding transformer using permeance magnetic circuit

The size and position difference of the windings determine the leakage flux path and give rise to unbalance of the short-circuit impedances, which strongly affects the transient behaviour of the transformer. This work proposes a new approach of modelling with magnetic equivalent circuit, making use of the transformer geometry and permeance magnetic equivalent circuit, which is suitable for system-level simulation in terms of complexity. Equivalent model requires limited number of parameters and for verification purposes, FEM simulations as well as measurement on the experimental prototype have been performed.