Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multiplex RT-PCR Test for the Differential Identification of Turkey Astrovirus Type 1, Turkey Astrovirus Type 2, Chicken Astrovirus, Avian Nephritis Virus, and Avian Rotavirus

Abstract Recent studies have revealed the presence of astroviruses and rotavirus in numerous poorly performing and healthy chicken and turkey flocks in the United States. The phylogenetic analysis of the sequence data produced during these studies has identified four groups of avian astroviruses circulating in the United States: turkey astrovirus types 1 and 2 (TAstV-1 and TAstV-2), avian nephritis virus (ANV), and a chicken-origin astrovirus (CAstV). As the molecular epidemiology of poultry enteric disease is poorly understood, the development of updated diagnostic assays is crucial to the continued surveillance and management of enteric disease in affected as well as healthy flocks. This report details the development of a multiplex reverse transcriptase–polymerase chain reaction (RT-PCR) assay specific for astroviruses and avian rotavirus in turkey-origin and chicken-origin samples. The assay consists of two multiplex tests, one for turkey-origin samples and one for chicken-origin samples. The turkey sample test differentially identifies TAstV-1, TAstV-2, ANV, and avian rotavirus. The test for chicken-origin samples differentially identifies CAstV, ANV, and avian rotavirus. Assay sensitivity varied by target sequence between approximately 10 copies for avian rotavirus alone and approximately 2 × 106 copies for TAstV-2 in the presence of a heterologous competitor RNA sequence. Each test was shown to be specific for the intended target by testing for cross-reaction with other common avian enteric viruses. The specificity was further shown by testing 109 chicken specimens and 32 turkey specimens from commercial flocks with the appropriate test and sequencing the RT-PCR amplicons to confirm amplification of the correct target.
EVALUATION OF THE CARBON MARKET IMPACT ON THE POLISH POWER EXCHANGE

Significant reduction of CO2 emissions, the increase of energy production from renewable sources and the increase of energy efficiency are the key priorities of EU's energy and climate policy. All these factors have significant impact on the development of the Polish Power Exchange (PPE), what is reflected among others in the electricity prices volatility. Therefore, in this article the behavior of the CO2 emission allowance prices from ECX and ICE Future Europe is examined and compared to the behavior of electricity prices quoted on the PPE. Empirical analysis is connected with the construction of Markov switching models in order to make a comparison between average duration of each variables in highand lowvolatility regimes. These findings allow toevaluate the synchronization of occurrence of higher price risk periods on the carbon market and on the Polish Power Exchange.
Quasi-Newton multimodulus blind equalization algorithm

In this work, a new stochastic Newton-like algorithm for blind equalization is developed. This is obtained by applying a complex Taylor series on a recently proposed soft constraint satisfaction multi-modulus blind equalization algorithm of order p (SCSMMA-p). The proposed algorithm is a generalized version of the SCS-MMA-p and is named as stochastic Newton-like soft constraint satisfaction multi-modulus algorithm of order p (SNL-SCS-MMA-p). Great improvement in performance of the proposed algorithm is obtained against that of the SCS-MMA for different values of p.
A multilanguage environment for interactive simulation and development controls for power electronics

Virtual prototyping of complex systems presents interesting challenges, especially with regard to systems in which different languages are used to represent different parts. We describe here one approach to solving such a problem. In particular, we describe how to integrate the virtual test bed (VTB) solver engine with the Simulink solver. This produces a rich environment for virtual prototyping of power electronic applications due to the inherent mixture of circuital and control problems. The integration is conducted within the context of the resistive companion approach. We present here the theoretical foundation of the approach, and also suggest the generality and extensibility to other solver engines such as SPICE. The theory is then enriched with some examples that illustrate the approach including the use of the VTB high-level graphic user interface.
Analysis of Evasion Techniques in Web-based Malware

Web-based mechanisms, often mediated by malicious JavaScript code, play an important role in malware delivery today, making defenses against web-based malware crucial for system security. To make it even more challenging, malware authors often take advantage of various evasion techniques to to evade detection. As a result, a constant arms race of evasion and detection techniques between malware authors and security analysts has led to advancement in code obfuscation and anti-analysis techniques. This dissertation focuses on the defenses against web-based malware protected by advanced evasion techniques from both defensive and offensive perspectives. From a defensive perspective, we examine existing evasion techniques and propose deobfuscation and detection approaches to defeating some popular techniques used by web-based malware today. In the case of code-unfolding based obfuscation, we use a semantics-based approach to simplify away obfuscations by identifying code that is relevant to the behavior of the original program. In the case of environment-dependent malware, we propose environmental predicate, which detects behavior discrepancy of JavaScript program between targeted browser and detector sandbox, therefore protecting users from possible detection false negatives caused by environmental triggers. From an offensive perspective, we analyze existing detection techniques to examining their assumptions and study how these assumptions can be broken. We also propose a combination of obfuscation and anti-analysis techniques, targeting these limitations, which can hide existing web-based malware from state-of-the-art detectors.
ISLAMIC AND NEO-CONFUCIAN PERSPECTIVES ON THE NEW TRADITIONAL ECONOMY

This paper argues that the new traditional economy is an emerging form important both ideologically and in practice in the world economy today. It is characterized by an effort to embed economic practices within a traditional socio-religious structure while simultaneously seeking modern technology and high incomes. The examples of the Islamic economic system and the neo-Confucian economic system are considered in more detail, with the former seen as more significant ideologically and the latter as more important practically.
Bayesian Inference in the Gravity Model

This paper seeks to empirically extend the gravity model, which has been widely used to analyze volumes of trade between pairs of countries. We generalize the basic threshold tobit model by allowing for the inclusion of country-specific effects into the analysis and also show how one can explore the relationship between trade volumes and a given covariate via a non-parametric approach. We use our derived methodology to investigate the impact of a particular aspect of institutions-the enforcement of contracts-on bilateral trade. We find that contract enforcement matters in predicting trade volumes for all types of goods, that it matters most for the trade of differentiated goods, and that the relationship between contract enforcement and trade in our threshold tobit exhibits some nonlinearities. Copyright © 2007 John Wiley & Sons, Ltd.
Can You Believe an Anonymous Contributor? On Truthfulness in Yahoo! Answers

Internet users notoriously take an assumed identity or masquerade as someone else, for reasons such as financial profit or social benefit. But often the converse is also observed, where people choose to reveal true features of their identity, including deeply intimate details. This work attempts to explore several of the conditions that allow this to happen by analyzing the content generated by these users. We examine multiple social media on the Web, specifically focusing on Yahoo! Answers, encompassing more than a billion answers posted since 2006. Our analysis covers discussions of personal topics such as body measurements and income, and of socially sensitive subjects such as sexual behaviors. We offer quantitative proof that people are aware of the fact that they are posting sensitive information, and yet provide accurate information to fulfill specific information needs. Our analysis further reveals that on community question answering sites, when users are truthful, their expectation of an accurate answer is met.
An Equivalent Noise Investigation of Saccadic Suppression

Visual stimuli presented just before or during an eye movement are more difficult to detect than those same visual stimuli presented during fixation. This laboratory phenomenon—behavioral saccadic suppression—is thought to underlie the everyday experience of not perceiving the motion created by our own eye movements—saccadic omission. At the neural level, many cortical and subcortical areas respond differently to perisaccadic visual stimuli than to stimuli presented during fixation. Those neural response changes, however, are complex and the link to the behavioral phenomena of reduced detectability remains tentative. We used a well established model of human visual detection performance to provide a quantitative description of behavioral saccadic suppression and thereby allow a more focused search for its neural mechanisms. We used an equivalent noise method to distinguish between three mechanisms that could underlie saccadic suppression. The first hypothesized mechanism reduces the gain of the visual system, the second increases internal noise levels in a stimulus-dependent manner, and the third increases stimulus uncertainty. All three mechanisms predict that perisaccadic stimuli should be more difficult to detect, but each mechanism predicts a unique pattern of detectability as a function of the amount of external noise. Our experimental finding was that saccades increased detection thresholds at low external noise, but had little influence on thresholds at high levels of external noise. A formal analysis of these data in the equivalent noise analysis framework showed that the most parsimonious mechanism underlying saccadic suppression is a stimulus-independent reduction in response gain.
A DSP Implementation of Source LocationUsing Microphone

The design, implementation, and performance of a low-cost, real-time DSP system for source location is discussed. The system consists of an 8-element electret microphone array connected to a Signalogic DSP daughterboard hosted by a PC. The system determines the location of a speaker in the audience in an irregularly shaped auditorium. The auditorium presents a non-ideal acoustical environment; some of the walls are acoustically treated, but there still exists signiicant reverberation and a large amount of low frequency noise from fans in the ceiling. The source location algorithm is implemented in a two step process: The rst step determines time delay of arrival (TDOA) for select microphone pairs. A modiied version of the Cross-Power Spectrum Phase Method is used to compute TDOAs and is implemented on the DSP daughterboard. The second step uses the computed TDOAs in a least mean squares gradient descent search algorithm implemented on the PC to compute a location estimate.
Opportunistic spectrum sharing in Poisson femtocell networks

In this paper, we propose a cognitive-based opportunistic spectrum sharing strategy for performance enhancement of a femtocell networks. This cognitive-based opportunistic spectrum access strategy aims to achieve better spectrum utilization with quality of service (QoS) protection for macrocell user equipments (MUEs) since the macrocell tier can be over-allocated spectrum resources. We analyze the performance of the two-tier network where the success probability with respect to the received signal to interference ratio (SIR) at each user and the total network throughput are derived under both closed and open access policies. In addition, we describe how to optimally choose the SIR threshold Q to maximize the total network throughput subject to QoS constraints for macrocell and femtocell users in terms of success probability. Via numerical studies, we show that our proposed opportunistic spectrum access scheme can achieve significant throughput gain compared to the conventional spectrum partitioning strategy.
Interest points detection and matching by exploiting 3 D mesh saliency in a Hidden Markov Model framework

This paper proposes an unsupervised methodology for the det ection and matching of salient points over several views of an object, which are modelled as 3D meshes. The proce ss is three-fold. In the first step, detection is carried out by adopting a new perceptually-inspired 3D sali ency measure. Such measure is computed for each vertex of the mesh triangles by combining opportunely multi scale 3D features as multidimensional representations. In the second step, a model-based matching of salient points across different views is carried out, employing continuous Hidden Markov Models (HMMs). Each salient point is modelled by a HMM, which is trained in an unsupervised way by using contextual 3D neighborhood inf ormation, thus providing a robust and invariant point signature. Finally, matching among points of differe nt views is performed by evaluating a pairwise similarity measure among HMMs. An extensive and comparative experimen tal s ssion has been carried out, considering real objects acquired by a 3D scanner from different points of vie w, where objects come from standard 3D databases. Results are promising as the detection of salient points is i n agreement to the human perceptual expectation, and the matching is robust and precise.
A Refined Electrical Model for Particle Strikes and its Impact on SEU Prediction

Decreasing feature sizes have led to an increased vulnerability of random logic to soft errors. A particle strike may cause a glitch or single event transient (SET) at the output of a gate, which in turn can propagate to a register and cause a single event upset (SEU) there. Circuit level modeling and analysis of SETs provides an attractive compromise between computationally expensive simulations at device level and less accurate techniques at higher levels. At the circuit level particle strikes crossing a pn-junction are traditionally modeled with the help of a transient current source. However, the common models assume a constant voltage across the pn-junction, which may lead to inaccurate predictions concerning the shape of expected glitches. To overcome this problem, a refined circuit level model for strikes through pn-junctions is investigated and validated in this paper. The refined model yields significantly different results than common models. This has a considerable impact on SEU prediction, which is confirmed by extensive simulations at gate level. In most cases, the refined, more realistic, model reveals an almost doubled risk of a system failure after an SET.
GRAVITATIONAL WAVE SCINTILLATION BY A STELLAR CLUSTER

The diffraction effects on gravitational waves propagating through a stellar cluster are analyzed in the relevant approximation of Fresnel diffraction limit. We find that a gravitational wave scintillation effect — similar to the radio source scintillation effect — comes out naturally, implying that the gravitational wave intensity changes in a characteristic way as the observer moves.
Structure and interactions of the Bacillus subtilis sporulation inhibitor of DNA replication, SirA, with domain I of DnaA

Chromosome copy number in cells is controlled so that the frequency of initiation of DNA replication matches that of cell division. In bacteria, this is achieved through regulation of the interaction between the initiator protein DnaA and specific DNA elements arrayed at the origin of replication. DnaA assembles at the origin and promotes DNA unwinding and the assembly of a replication initiation complex. SirA is a DnaA‐interacting protein that inhibits initiation of replication in diploid Bacillus subtilis cells committed to the developmental pathway leading to formation of a dormant spore. Here we present the crystal structure of SirA in complex with the N‐terminal domain of DnaA revealing a heterodimeric complex. The interacting surfaces of both proteins are α‐helical with predominantly apolar side‐chains packing in a hydrophobic interface. Site‐directed mutagenesis experiments confirm the importance of this interface for the interaction of the two proteins in vitro and in vivo. Localization of GFP–SirA indicates that the protein accumulates at the replisome in sporulating cells, likely through a direct interaction with DnaA. The SirA interacting surface of DnaA corresponds closely to the HobA‐interacting surface of DnaA from Helicobacter pylori even though HobA is an activator of DnaA and SirA is an inhibitor.
Social sub-group identification using social graph and semantic analysis

Social networks proliferate daily life, many are part of big groups within social networks, many of these groups contain people unknown to you, but with whom you share interests. Some of these shared interest are based on context which has real-time properties (e.g. Who would like to go to a jazz concert during an AI conference). This paper presents a possible method for identifying such subgroups. We aim to do this by creating a social graph based on one or more “comparators”; Frequency (how often two members interact) and content (how often the two talk about the same thing). After the graph is created we apply standard graph segmentation (clique estimation) techniques to identify the subgroups. We propose a system which continuously polls social network for updates, to keep the social graph up-to-date and based on that suggest new subgroups. As a result the system will suggest new subgroups in a timely and near real-time manner. This paper will focus on the methods behind the creation of the weighted social graph and the subsequent pruning of the social graph.
The Effect of an Altitude Training Camp on Swimming Start Time and Loaded Squat Jump Performance

This study evaluated the influence of an altitude training (AT) camp on swimming start time and loaded squat jump performance. To accomplish this goal, 13 international swimmers (8 women, 5 men) were allocated to both the control (Sea Level Training, SLT) and experimental conditions (AT, 2320 m above sea level) that were separated by a one year period. All tests (15 m freestyle swimming start and loaded squat jumps with additional loads of 25%, 50%, 75%, and 100% of swimmers’ body weight) were performed before and after a concurrent 3-week strength and endurance training program prescribed by the national coach. Following the SLT camp, significant impairments in swimming start times to 10 (+3.1%) and 15 m (+4.0%) were observed (P < 0.05), whereas no significant changes for the same distances were detected following the AT camp (-0.89%; P > 0.05). Trivial changes in peak velocity were obtained during the loaded squat jump after both training periods (effect sizes: < 0.20). Based on these results we can conclude that a traditional training high—living high strategy concurrent training of 3 weeks does not adversely affect swimming start time and loaded squat jump performance in high level swimmers, but further studies are necessary to assess the effectiveness of power-oriented resistance training in the development of explosive actions.
Compression of Model-based Group Delay Function for Robust Speech Recognition

In this paper, we improve the performance of the ARGDMF feature by adding a nonlinear filtering block. ARGDMF is a group delay-based feature consists of four main parts, namely autoregressive (AR) model extraction, group delay function (GDF) calculation, compression, and scale information augmentation. The main problem with the GDF is its spiky nature which is solved by coupling the GDF with an all-pole model. The compression step includes two stages similar to MFCC without taking a logarithm of the output energies. The fourth part augments the phase-based feature vector with scale information. The novelty of this paper is in adding a filtering block to compression process to make it more efficient. This filter aims at elevating the performance of the ARGDMF via a more optimum dynamic range and formants sharpness adjustment. The feature was evaluated on Aurora 2 database. In the presence of both additive and convolutional noises, the proposed method noticeably outperforms the MFCCs and other phase-based features, without remarkable increase in computational load.
Timed traces and their applications in specification and verification of distributed real-time systems

This paper proposes a method for specification and verification of distributed real-time systems using timed traces. The key idea of the proposed method is to extend distributed transition systems and linear temporal logic over Foata configurations with time. We show that systems are easily specified and verified with this method. The system behaviors are specified by a distributed duration transition system and the system properties are specified by a formula of our proposed timed logic over timed traces. We give an algorithm for solving the verification problem automatically. We also give an example to illustrate how our algorithm work.
Rooting in Km selective media as efficient in vitro selection method for sunflower genetic transformation

Despite of numerous publications in sunflower genetic transformation, there is no efficient or reproducible protocol with low number of escapes. The latter would indicate that the selection method is not effective. In this work we used Km as selective agent, Agrobacterium tumefaciens EHA105 strain and a vector with the nptII gene under the nos promoter and uidA gene under 35S promoter. The response of agroinfected ( A) and control ( C) explants during the in vitro culture was studied and in both cases in presence or absence of Km in order to assign a differential morphologic response between transformed and non-transformed plants. The characteristics analyzed were: height, colour/aspect of the plantlets, in vitro rooting and in vitro bud-flower development. Selection was applied from the third regeneration media. Among the A plantlets two were capable of rooting, being positive by PCR, whereas the C were unable to root in presence of Km. One of them gave 6 seeds and in these plants, it was determined the presence of the transgene by PCR and GUS staining. This work shows that in Km selection, colour/aspect of shoots is not useful as selection criteria whereas rooting is an effective selection method in which no escapes were obtained.
Design Rule Hierarchy and Analytical Decision Model Transformation

We present two contributions to help make design rule theory operable in software engineering practice. First, we develop an approach to automatically transform a design, expressed in the prevailing unified modeling language, into an augmented constraint network (ACN), from which a design structure matrix (DSM) can be generated. Using ACNs formalizes design rule theory and using DSMS enables option-based reasoning. Second, we design an algorithm to derive a design rule hierarchy from an ACN, revealing the impact scope of each design rule and identifying the independent modules. This hierarchy defines an order in which decisions can be made to maximize task parallelism, constrained by the dependency structure of the architecture. We evaluate the accuracy and scalability of our approaches using both small, but canonical, systems and the open-source Apache Ant system.