Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of the PB2 627 Domain in Influenza A Virus Polymerase Function

ABSTRACT The RNA genome of influenza A viruses is transcribed and replicated by the viral RNA-dependent RNA polymerase, composed of the subunits PA, PB1, and PB2. High-resolution structural data revealed that the polymerase assembles into a central polymerase core and several auxiliary highly flexible, protruding domains. The auxiliary PB2 cap-binding and the PA endonuclease domains are both involved in cap snatching, but the role of the auxiliary PB2 627 domain, implicated in host range restriction of influenza A viruses, is still poorly understood. In this study, we used structure-guided truncations of the PB2 subunit to show that a PB2 subunit lacking the 627 domain accumulates in the cell nucleus and assembles into a heterotrimeric polymerase with PB1 and PA. Furthermore, we showed that a recombinant viral polymerase lacking the PB2 627 domain is able to carry out cap snatching, cap-dependent transcription initiation, and cap-independent ApG dinucleotide extension in vitro, indicating that the PB2 627 domain of the influenza virus RNA polymerase is not involved in core catalytic functions of the polymerase. However, in a cellular context, the 627 domain is essential for both transcription and replication. In particular, we showed that the PB2 627 domain is essential for the accumulation of the cRNA replicative intermediate in infected cells. Together, these results further our understanding of the role of the PB2 627 domain in transcription and replication of the influenza virus RNA genome. IMPORTANCE Influenza A viruses are a major global health threat, not only causing disease in both humans and birds but also placing significant strains on economies worldwide. Avian influenza A virus polymerases typically do not function efficiently in mammalian hosts and require adaptive mutations to restore polymerase activity. These adaptations include mutations in the 627 domain of the PB2 subunit of the viral polymerase, but it still remains to be established how these mutations enable host adaptation on a molecular level. In this report, we characterize the role of the 627 domain in polymerase function and offer insights into the replication mechanism of influenza A viruses.
Reduction of Impulsive Noise in OFDM System using Adaptive Algorithm

— The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.
Perfect electromagnetic conductor as metamaterial: corollaries regarding the existence of Tellegen media

Perfect electromagnetic conductor (PEMC) is a recently introduced fundamental concept in electromagnetics and the study of metamaterials, which generalizes the well-understood PEC and PMC media. In this paper the character and properties of PEMC media are discussed in bulk and particulate form. A special emphasis is given to the conclusions that the advent of PEMC raises regarding the controversial question about the existence of non-reciprocal bi-isotropic media (so-called Tellegen media)
The Effects of World War II on Economic and Health Outcomes across Europe

Abstract We investigate long-run effects of World War II on socioeconomic status and health of older individuals in Europe. We analyze data from SHARELIFE, a retrospective survey conducted as part of SHARE in Europe in 2009. SHARELIFE provides detailed data on events in childhood during and after the war for over 20,000 individuals in thirteen European countries. We construct several measures of war exposure: experience of dispossession, persecution, combat in local areas, and hunger periods. Exposure to war and, more important, to individual-level shocks caused by the war significantly predicts economic and health outcomes at older ages.
Black hole masses in narrow-line Seyfert 1 galaxies

The masses of central supermassive black holes in a soft X-ray-selected sample of the narrow-line Seyfert 1 galaxies (NLS I s) are estimated by various methods to test the theoretical models. Apart from the methods using the Hβ linewidth and the [O III] linewidth, soft X-ray excess as a prominent character of NLS 1 s is used to estimate the black hole masses. The virial mass derived from the Hβ linewidth assuming random orbits of broad-line regions (BLRs) is consistent with that from the soft X-ray bump luminosity for NLS 1s, but with a larger scatter. The virial black hole masses showed that most of NLS1s are in the super-Eddington accretion state, while most of broad-line Seyfert 1 galaxies are not. We found that the black hole mass estimated from the [O III] linewidth is not in agreement with above two methods. Using the Eddington limit relation for the super-Eddington accretion suggested by Wang, we found that there are 16 NLSIs satisfied by this Eddington limit relation. The masses of these 16 NLS1s derived from X-ray luminosity are systematically larger than that from Hβ linewidth assuming random BLRs orbits. If the mass derived from X-ray luminosity is true, the mean disc inclination to the line of sight in these 16 NLS s is approximately 17°, which provided new support for the pole-on orientation effect in NLS 1 s.
Using Decision Trees for Coreference Resolution

This paper describes RESOLVE, a system that uses decision trees to learn how to classify coreferent phrases in the domain of business joint ventures. An experiment is presented in which the performance of RESOLVE is compared to the performance of a manually engineered set of rules for the same task. The results show that decision trees achieve higher performance than the rules in two of three evaluation metrics developed for the coreference task. In addition to achieving better performance than the rules, RESOLVE provides a framework that facilitates the exploration of the types of knowledge that are useful for solving the coreference problem.
A Pipeline-Based Genetic Algorithm Accelerator for Time-Critical Processes in Real-Time Systems

The meta-heuristic methods, genetic algorithms (GAs), are frequently used to obtain optimal solutions for some complicated problems. However, due to the characteristic of natural evolution, the methods slowly converge the derived solutions to an optimal solution and are usually used to solve complicated and offline problems. While, in a real-world scenario, there are some complicated but real-time problems that require being solved within a short response time and have to obtain an optimal or near optimal solution due to performance considerations. Thus, the convergence speed of GAs becomes an important issue when it is applied to solve time-critical optimization problems. To address this, this paper presents a novel method, named hyper-generation GA (HG-GA), to improve the convergence speed of GAs. The proposed HG-GA breaks the general rule of generation-based evolution and uses a pipeline operation to accelerate the convergence speed of obtaining an optimal solution. Based on an example of a time-critical scheduling process in an optical network, both analysis and simulation results show that the HG-GA can generate more and better chromosomes than general GAs within the same evolutionary period. The rapid convergence property of the HG-GA increases its potential to solve many complicated problems in real-time systems
Empty Promises and Arbitrage

Analysis of absence of arbitrage normally ignores payoffs in states to which the agent assigns zero probability. We extend the fundamental theorem of asset pricing to the case of 'no empty promises' in which the agent cannot promise arbitrarily large payments in some states. There is a superpositive pricing rule that can assign positive price to claims in zero probability states important to the market as well as assigning positive prices to claims in the states of positive probability. With continuous information arrival, no empty promises can be enforced by shutting down the agent's subsequent investments once wealth hits zero. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
Towards A Formal Framework for Business Process Compliance

: The advent of regulatory compliance requirements such as Sarbanes Oxley Act has forced enterprises to set up a process for managing an effective internal controls system on business processes. In this paper a formal framework consisting of a formal definition of business process compliance and a set of properties is proposed. A system implementing the formalization must satisfy the given properties. The advantage is that enterprises can verify whether their system responsible for achieving business process compliance itself is complaint in terms of checking whether its current state fulfills the given properties. The proposed model and its properties are motivated and exemplified using a scenario, showing the current challenges in achieving business process compliance at a use case company.
Dynamic lifting by whole body motion of humanoid robots

A motion control method of lifting a heavy object up to a higher position with humanoid robots is developed. The key issue of lifting motion is how to reduce the load on humanoid arms in which low-power actuators are implemented. The use of singular postures of arms is well-known to avoid actuator saturation of the arms. By combining two different kinds of humanoid motions such as accelerating an object upward and sliding the body into under the object, we propose a method that enables to transit one singular posture of arms to another while lifting the object. Simulation results show the effectiveness of the proposed method for reducing the load on the arms. We realize a motion of lifting a heavy object dynamically with the humanoid robot HRP-2 through experiment.
Domain Specific Feature Transfer for Hybrid Domain Adaptation

Heterogeneous domain adaptation needs supplementary information to link up domains. However, this supplementary information is unavailable in many real cases. In this paper, a new problem setting called hybrid domain adaptation is investigated. It is a special case of heterogeneous domain adaptation in which different domains share some common features, but also have their own domain specific features. In this case, it can be efficiently solved without any supplementary information by using the common features to link up the domains in adaptation. We propose a domain specific feature transfer (DSFT) method, which can link up different domains using the common features and simultaneously reduce domain divergences. Specifically, we first learn the translations between the common features and the domain specific features. Then we cross-use the learned translations to transfer the domain specific features of one domain to another domain. Finally, we compose a homogeneous space in which the domain divergences are minimized. Extensive experiments verify the effectiveness of our proposed method.
Synthesis of high-performance packet processing pipelines

Packet editing is a fundamental building block of data communication systems such as switches and routers. Circuits that implement this function are critical and define the features of the system. We propose a high-level synthesis technique for a new model for representing packet editing functions. Experiments show our circuits achieve a throughput of up to 40Gb/s on a commercially available FPGA device, equal to state-of-the-art implementations
MayBMS: Managing Incomplete Information with Probabilistic World-Set Decompositions

Managing incomplete information is important in many real world applications. In this demonstration we present MayBMS - a system for representing and managing finite sets of possible worlds - that successfully combines expressiveness and efficiency. Some features of MayBMS are: completeness of the representation system for finite world-sets; space-efficient representation of large world-sets; scalable evaluation and support for full relational algebra queries; and probabilistic extension of the representation system and the query language. MayBMS is implemented on top of PostgreSQL. It models incomplete data using the so-called world-set decompositions (WSDs) (Ruggles et al., 2004). For this demonstration, we introduce a probabilistic extension of world-sets and WSDs, where worlds or correlations between worlds have probabilities. The main idea underlying probabilistic WSDs is to use relational factorization combined with probabilistic independence in order to efficiently decompose large world-sets into a set of independent smaller relations. Queries in MayBMS can be expressed in an SQL-like language with special constructs that deal with incompleteness and probabilities. MayBMS rewrites and optimizes user queries into a sequence of relational queries on world-set decompositions.
Dominance, Politics, and Physiology: Voters' Testosterone Changes on the Night of the 2008 United States Presidential Election

Background Political elections are dominance competitions. When men win a dominance competition, their testosterone levels rise or remain stable to resist a circadian decline; and when they lose, their testosterone levels fall. However, it is unknown whether this pattern of testosterone change extends beyond interpersonal competitions to the vicarious experience of winning or losing in the context of political elections. Women's testosterone responses to dominance competition outcomes are understudied, and to date, a clear pattern of testosterone changes in response to winning and losing dominance competitions has not emerged. Methodology/Principal Findings The present study investigated voters' testosterone responses to the outcome of the 2008 United States Presidential election. 183 participants provided multiple saliva samples before and after the winner was announced on Election Night. The results show that male Barack Obama voters (winners) had stable post-outcome testosterone levels, whereas testosterone levels dropped in male John McCain and Robert Barr voters (losers). There were no significant effects in female voters. Conclusions/Significance The findings indicate that male voters exhibit biological responses to the realignment of a country's dominance hierarchy as if they participated in an interpersonal dominance contest.
Polymer Nanocomposites with Thermoplastic Matrices—Processing and Tribology

An analysis has been made of the literature on tribology of polymer nanocomposites prepared by compounding nanofillers with molten thermoplastics. A process is described for preparing nanocomposites with various polymer binders by reactive extrusion. The introduction of nanofillers (carbon nanomaterials, layered clays, metals, and metal-containing compounds) into thermoplastics influences the kinetics and mechanism of tribochemical transformations in a friction contact with metals or other materials. Nanofillers affect significantly the physicochemical behavior of macromolecules, as well as the macromolecular transformations, under the conditions of frictional interaction. This can be explained by adsorption (chemisorption) of functional groups found on the particle surface, variations in polymer crystallinity and morphology, constrained molecular (segmental) mobility in macrochains, and catalytic (inhibiting) effects of the additives on the course of contact reactions. As a consequence, alterations occur in the formation of transfer layers and wear debris, along with the parameters of friction. Depending on the polymer and the nature and concentration of the fillers, the latter can either improve or impair the performance parameters of friction pairs.
Use of a Nonvisual Display for Improving the Manual Control of an Unstable System

An approach to aiding the operator of an unstable system by use of a nonvisual display which supplements normal visual information and guides the operator in his control actions is described. The procedure is based on the feedback of significant plant variables and the combination of these variables to continuously define the desired operator action. The nonvisual display is used to present the operator with the error between this desired control action and his current control effort. By striving to duplicate the desired action, the operator's ability to control and stabilize the system is enhanced. A specific example involving an automotive vehicle is considered, and a simulation study is described which uses an audio display and indicates the feasibility of this approach.
Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks

Given an undirected network where some of the nodes are labeled, how can we classify the unlabeled nodes with high accuracy? Loopy Belief Propagation (LBP) is an inference algorithm widely used for this purpose with various applications including fraud detection, malware detection, web classification, and recommendation. However, previous methods based on LBP have problems in modeling complex structures of attributed networks because they manually and heuristically select the most important parameter, the propagation strength. In this paper, we propose Supervised Belief Propagation (SBP), a scalable and novel inference algorithm which automatically learns the optimal propagation strength by supervised learning. SBP is generally applicable to attributed networks including weighted and signed networks. Through extensive experiments, we demonstrate that SBP generalizes previous LBP-based methods and outperforms previous LBP and RWR based methods in real-world networks.
State Estimation for Legged Robots - Consistent Fusion of Leg Kinematics and IMU

—This paper introduces a state estimation framework for legged robots that allows estimating the full pose of the robot without making any assumptions about the geometrical structure of its environment. This is achieved by means of an Observability Constrained Extended Kalman Filter that fuses kinematic encoder data with on-board IMU measurements. By including the absolute position of all footholds into the ﬁlter state, simple model equations can be formulated which accurately capture the uncertainties associated with the intermittent ground contacts. The resulting ﬁlter simultaneously estimates the position of all footholds and the pose of the main body. In the algorithmic formulation, special attention is paid to the consistency of the linearized ﬁlter: it maintains the same observability properties as the nonlinear system, which is a prerequisite for accurate state estimation. The presented approach is implemented in simulation and validated experimentally on an actual quadrupedal robot.
Analysis and applications of lateral-spread volume holographic lens for optical beams conversion

A new type of volume holographic grating lenses for converting a plane wave to a lateral-spread spherical wave and vice versa, has been designed. The lenses have the advantages of small volume, light weight, high wavelength selectivity and simplicity of fabrication. Grating pitch and grating vector of the grating lenses which derived from intensity distribution of wavefront interfering field of a plane wave and a spherical wave are discussed. And basis is provided to design and fabricate volume holographic grating lenses devices. On the basis of two beams coupled-wave theory, coupled wave differential equations and diffraction efficiency are derived. The practical applications of the lenses are demonstrated.
A Building Block Approach for Designing Multilevel Coding Schemes

A novel building block (BB) design approach is presented for systematically constructing multilevel codes (MLCs) under the balanced distances rule (BDR). In contrast to the traditional method of starting from an overall signal constellation and then using a mapping policy, the BB approach starts by designing a BB constellation for the first level of the MLC and then uses two copies of this BB to construct a second level constellation. This process is continued to the highest level by constructing the next level constellation using multiple copies of the current level constellation as a BB. Compared to the traditional method of construction of MLCs according to the BDR, the BB approach provides additional flexibility in selecting component codes and is able to exactly balance the distances of all levels. Compared with MLCs constructed using the traditional BDR approach, MLCs constructed using the BB approach have the same decoding complexity and perform better in the error floor region, which is typically the operating region for MLCs constructed with convolutional component codes.
The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages

We study the computational complexity of finding maximum a posteriori configurations in Bayesian networks whose probabilities are specified by logical formulas. This approach leads to a fine grained study in which local information such as contextsensitive independence and determinism can be considered. It also allows us to characterize more precisely the jump from tractability to NP-hardness and beyond, and to consider the complexity introduced by evidence alone.
DeepDive: An End-to-End Dehazing Method Using Deep Learning

Image dehazing can be described as the problem of mapping from a hazy image to a haze-free image. Most approaches to this problem use physical models based on simplifications and priors. In this work we demonstrate that a convolutional neural network with a deep architecture and a large image database is able to learn the entire process of dehazing, without the need to adjust parameters, resulting in a much more generic method. We evaluate our approach applying it to real scenes corrupted by haze. The results show that even though our network is trained with simulated indoor images, it is capable of dehazing real outdoor scenes, learning to treat the degradation effect itself, not to reconstruct the scene behind it.
A constructive denotational semantics for Kahn networks in Coq

Semantics of programming languages and interactive environments for the development of proofs and programs are two important aspects of Gilles Kahn's scientific contributions. In his paper ``The semantics of a simple language for parallel programming'', he proposed an interpretation of (deterministic) parallel programs (now called Kahn networks) as stream transformers based on the theory of complete partial orders (cpos). A restriction of this language to synchronous programs is the basis of the data-flow Lustre language which is used for the development of critical embedded systems. We present a formalization of this seminal paper in the Coq proof assistant. For that purpose, we developed a general library for cpos. Our cpos are defined with an explicit function computing the least upper bound (lub) of an increasing sequence of elements. This is different from what Kahn developed for the standard Coq library where only the existence of lubs (for arbitrary directed sets) is required, giving no way to explicitly compute a fixpoint. We define a cpo structure for the type of possibly infinite streams. It is then possible to define formally what is a Kahn network and what is its semantics, achieving the goal of having the concept closed under composition and recursion. The library is illustrated with an example taken from the original paper as well as the Sieve of Eratosthenes, an example of a dynamic network.