Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Viral Interference between Lentogenic Newcastle Disease Virus (Lasota) and Avian Influenza Virus (H9N2) using Real-Time Reverse Transcription Polymerase Chain Reaction in SPF Chicken

Lentogenic Newcastle disease virus (lNDV) such as Lasota strain and low pathogenicity avian influenza such as H9N2 virus are two of the most economically important viruses affecting poultry worldwide, and little attention in recent years has been paid to simultaneous infections in chickens with these two viruses for the reason that co-infection do occur but are not easily detected. In the present study, chickens were inoculated with lNDV (Lasota) and LPAIV (A/chicken/Tehran/ZMT-173/99(H9N2)) simultaneously or sequentially three days apart. Oropharyngeal and cloacal swabs were collected from chickens from 1 to 14 days after inoculation. RRT-PCR for AIV and NDV detection was performed. The rate of viral shedding was measured within 14 days. No clinical symptoms were observed during the experiment however the pattern of virus shed was different with co-infection, thus comparing the results obtained from viral shedding showed that AIV is a much stronger agent than NDV in the occurrence of viral interference. This is due to the fact that in simultaneous inoculation, AIV replication delayed and reduced NDV replication, while replication of Lasota in simultaneous or pre-inoculated inoculation could not significantly disrupt H9N2 virus replication. These findings indicate that the infection with one virus can interfere with the replication of another, modifying the pathogenesis of the viruses. So, infection of the host with both viral agents simultaneously causes higher shedding of LPAIV than lNDV in OP and CL areas. In conclusion, coinfection with LPAVI in chickens did not impact clinical signs but affected the replication dynamics of these viruses.
Integrating Intrusion Detection Model Using Ensemble of Classifiers and Extreme Learning Machine

------------------------------------------------------------------- ABSTRACT --------------------------------------------------------------- The Intrusion detection from the last some decades are very important for current as well as for present networks. In the recent times many new methods have been used for IDS with machine learning technique and analysis for huge data is very much suitable. But the techniques like WMV (weighted majority voting) which have large dataset will take much more amount of time with this there is degradation of results whenever increasing the dataset. For this problem this paper focuses on the Extreme learning machine would be the best suitable for IDS with the analysis of big data and improving the accuracy. The proposed technique will integrate Mutual information ranking filter and attribute ranking feature selection with ELM technique. The Mutual information technique will implement attribute selection and will analyse proposed technique performance MI-ELM technique with algorithms like Modified Naïve Bayes, Support vector machine, LP Boosting and also hybrid of these three algorithms with respect to Precision, Recall. F-measure, accuracy, the (KS) Kappa statistic, Incorrectly and Correctly (CI) classified instances, RMSE (Root of Mean square erratum or error) and RRE (Root relative of error). There will be analysis of the dataset on according to basis of traffic is it normal or abnormal and the experimental results has shown that there will be increased accuracy in comparison with the classifiers.
Pricing VIX Futures on Affine Stochastic Volatility Models with Simultaneous Sate-Dependent Jumps both in the S&P 00 Price and Variance Processes: Evidence from Integrated Physical and Risk-Neutral Probability Measures

The paper presents alternate stochastic variance models and develops closed-form solutions to the fair price of VIX futures. The derivation for theoretical futures prices is based upon the conditional moments of VIX squared on affine stochastic volatility models with simultaneous jumps both in the asset price and variance processes. An integrated analysis of spot and option prices, or equivalently integrated volatility and VIX time series, is proposed to estimate monthly-updated model parameters and the market prices of risks. Existing literature, however, has not provided the moment conditions of the total quadratic variation (except for the stochastic-volatility model), which are given in this study. The daily VIX futures prices in the subsequent month, since 19 May 2004, are adopted to test the futures price formulas. Our results show that state-dependent jumps in volatilities and prices simultaneously fare better in fitting short-dated VIX futures prices whereas stochastic volatility and random jumps in returns outperforms for mediumand long-lived futures. In addition, while both price and volatility jump-risk premia appear to be positive, the diffusive volatility-risk premium is found to be negative that is consistent with the negative correlation between volatility and index returns. Gauging by the magnitude of risk premia, the volatility jump-risk premium is found to be far more important than the one for price jumps in terms of the VIX futures valuation.
Shaping Women: National Identity Through the Use of Language in Franco's Spain

In my article I show how a very particular identity was created for women during the period of Franco's Spain. I will draw upon a varied range of materials from official discourses, particularly the Seccion Femenina (the women's branch of Falange); the Alvarez Enciclopedia and other texts such as songs, poems and the popular press. Following Foucault (1980: 30) I analyse an identity based on oppressive discourses whose power 'reaches into the very grain of individuals, touches their bodies and inserts itself into their actions and attitudes, their discourses, learning process and everyday life'. The nationalistic stress of this discourse is one that encourages women to create a new image of Spanish femininity that should be 'different' from the liberated portrayal of women coming from Europe, mainly through the path of growing tourism. The language of these discourses is somehow baroque, elaborated, energetic and highly dramatic. It tries to seek attention through an unnecessary and badly misorientated dramatism. It is cryptic and manipulative and claims to be poetical, but its main intention is to confine women indoors and to make them look at the world through the curtains or from a closed window. On the other hand it made women feel they were the representation of a unique matriarchal nationalism making them appear as the heroines of an essentialist national metaphor: women mothers of the nation. Inherent in Franco's equation of women = femininity = nation is a contradiction that defines women as 'indoor heroines' and bases nationalism in a naturalised representation of gender where women are a gendered representation of this nationalism.
NATIONAL REMOTE SENSING CENTRE REPORT / DOCUMENT CONTROL SHEET

Planetary Boundary Layer Height (PBLH) over the Indian land mass is estimated using vertical profiles of temperature and relative humidity from Cross track Infrared Sounder (CrIS) onboard Suomi-NPP, through integration of five different methods. The integrated approach is performed by comparing PBLH values estimated from vertical gradients of potential temperature (PT), virtual potential temperature (VPT), relative humidity (RH), refractivity (N) and specific humidity (q). If at least three of them are consistent with the same value, it is considered as the PBLH. PBLH values estimated through the integrated approach show reasonable comparison with the estimates using radiosonde profiles and COSMIC GPS Radio Occultation measurements. Following the integrated approach, day time PBLH over Indian land mass is retrieved on daily basis and are further averaged for seven days and monthly mean values.
A Graph Based Approach for Efficient Document Similarity Detection

Commonsense knowledge representation and thinking bolster a wide assortment of potential applications in fields, for example, record auto-order, Web seek improvement, theme gisting, social process demonstrating, and idea level conclusion and assessment examination. Answers for these issues, notwithstanding, request vigorous information bases fit for supporting adaptable, nuanced thinking. Populating such information bases is profoundly tedious, making it important to create procedures for deconstructing regular dialect writings into conventional ideas. In this work, we propose an approach for viable multi-word realistic articulation extraction from unlimited English content, notwithstanding a semantic likeness discovery strategy permitting extra matches to be found for particular ideas not officially show in knowledge bases.
A Granular Approach to the Effects of Bilateral Investment Treaties and Regional Trade Investment Agreements on Foreign Direct Investment

We adopt a granular approach to investigate the impact of bil ateral investment treaties (BITs) and regional trade investment agreements (RTIAs) on foreig n d rect investment (FDI). Using detailed and under-exploited databases, our empirical analy sis explicitly takes into account the heterogeneity of both treaties and FDI projects. We find that BIT s specifically granting access to an investor-state dispute mechanism and RTIAs specifically protecting foreign investors from discrimination have a large, positive, and statistically sign ificant effect on FDI. These results hold when we distinguish FDI flows according to the partners invol ved, the entry mode, or the destination sector. The focus on narrowly identified investment pro visi ns and various robustness checks suggest that our findings are not driven by reverse causality or an omitted variable bias. Overall a ‘pro-FDI’ BIT or RTIA can be expected to increase the number o f FDI projects by 35% and 58% respectively.
Use of Different Animal Models in Prediction of Genetic Parameters of First Lactation and Herd Life Traits of Murrah Buffaloes

In order to compare different animal models, the methodology of mixed models under animal models was used to predict (Co) variance components of 8 traits related to production, reproduction and life time traits of 1312 Murrah buffaloes descendent from 122 Sires and 341 dams raised at four military dairy farm viz. Ambala, Agra, Lucknow and Bareilly. The phenotypic mean (LSD) of body weight at first calving, age at first calving, first lactation milk yield, herd life milk yield, first lactation period, first dry period, first calving interval and first service period were 497.86 ± 57.95 kg, 1267.04 ± 232.94 days, 1761.57 ± 506.91 kg, 5630.00 ± 1383.88 kg, 306.76 ± 65.39 days, 177.08 ± 96.19 days, 481.86 ± 126.21 days and 179.54 ± 125.61 days respectively. Additive variance (direct) component estimated for all the traits from univariate, model 2 and model 8 were not similar. Univariate RMEL analysis had higher values of additive variance for WFC, AFC, FLMY, HLMY, FLP, FDP, FCI and FSP than the estimate of model 2 and model 8. However, model 2 had lower values of additive vanances only for WFC than univeriate and model 8, but higher values for all other traits than univariate and model 8. Model 8 and univariate REML had similar values of environmental variances for all the traits but values estimated by model 2 were much lower than the other two models. The phenotypic variances estimated by model 2 and 8 univariate animal model were agreed for all the traits under study. The heritability estimates obtained under model 2 and univariate REML were found almost similar for all the traits while the heritability estimated under model 8 was low. The values for coefficient of variation estimated under different models were found to be almost similar. Genetic correlations among different traits ranged from very low to very high under model 2. Phenotypic and environmental correlations also showed same trend.
Travelling waves in delayed reaction–diffusion equations on higher dimensional lattices

This paper is concerned with travelling wave solutions for a class of monostable delayed reaction–diffusion equations on higher dimensional lattices. We first show that, for any fixed unit vector , there is a minimal wave speed such that a travelling front exists if and only if its speed is above this minimal speed. The exact asymptotic behaviour of the wave profiles at infinity is then established. Finally, we show that any travelling wave solution is strictly monotone and unique (up to a translation), including even the minimal wave. Of particular interest is the effects of the delay, spatial dimension and direction of wave on the minimal wave speed and we obtain some interesting phenomena for the delayed lattice dynamical system which are different from the case when the spatial variable is continuous.
Engineering Students ’ Acceptance of mLearning in Formal English Language Learning : Application of UTAUT Model

The paper describes the investigation into the undergraduate Engineering students’ acceptance level towards the incorporation of mLearning in their formal English Language course. The researchers posit that before mLearning could be implemented, students’ acceptance and intention to use mLearning need to be determined to justify the cause of the implementation. The study adopts a needs analysis survey technique to probe into the undergraduate students’ acceptance. The survey questionnaires was designed based on UTAUT model to seek elaborative findings specifically on students’ acceptance and intention to use mLearning in their formal language learning. This study was conducted on 220 undergraduate engineering students of a Malaysian private university who were undergoing an English Language communication course. The findings indicated that the overall result on all the key constructs (based on UTAUT model) concluded that the students highly accepted mLearning as intervention in facilitating their learning needs and they intended to use it. These findings justified the incorporation of mLearning as learning support to the students’ language learning needs to improve their language competence as well as fulfilling the learning course outcomes as the literature dictated that a language course or program should accommodate not only the target needs but also the students’ learning needs. This is vital for the success implementation of a learning solution such as mLearning because learners should accept and intend to use a proposed solution before the solution could be implemented. Keywords— Engineering education, English Language learning, mLearning, UTAUT model.
SPITZER MID-IR SPECTROSCOPY OF POWERFUL 2 JY AND 3CRR RADIO GALAXIES. I. EVIDENCE AGAINST A STRONG STARBURST–AGN CONNECTION IN RADIO-LOUD AGN

We present deep Spitzer/Infrared Spectrograph (IRS) spectra for complete samples of 46 2 Jy radio galaxies (0.05 < z < 0.7) and 19 3CRR FRII radio galaxies (z < 0.1), and use the detection of polycyclic aromatic hydrocarbon (PAH) features to examine the incidence of contemporaneous star formation and radio-loud active galactic nucleus (AGN) activity. Our analysis reveals PAH features in only a minority (30%) of the objects with good IRS spectra. Using the wealth of complementary data available for the 2 Jy and 3CRR samples we make detailed comparisons between a range of star formation diagnostics: optical continuum spectroscopy, mid- to far-IR (MFIR) color, far-IR excess and PAH detection. There is good agreement between the various diagnostic techniques: most candidates identified to have star formation activity on the basis of PAH detection are also identified using at least two of the other techniques. We find that only 35% of the combined 2 Jy and 3CRR sample show evidence for recent star formation activity (RSFA) at optical and/or MFIR wavelengths. This result argues strongly against the idea of a close link between starburst and powerful radio-loud AGN activity, reinforcing the view that, although a large fraction of powerful radio galaxies may be triggered in galaxy interactions, only a minority are triggered at the peaks of star formation activity in major, gas-rich mergers. However, we find that compact radio sources (D < 15 kpc) show a significantly higher incidence of RSFA (>75%) than their more extended counterparts (≈15%–25%). We discuss this result in the context of a possible bias toward the selection of compact radio sources triggered in gas-rich environments.
CIA_A_214367 1615..1630

Lauren Yates* Emese Csipke* Esme Moniz-Cook Phuong Leung Holly Walton Georgina Charlesworth Aimee Spector Eef Hogervorst Gail Mountain Martin Orrell 1Institute of Mental Health, University of Nottingham, Nottingham, UK; 2Division of Psychiatry, University College London, London, UK; 3Department of Psychological Health and Well-Being, Faculty of Health Sciences, School of Health and Social Work, University of Hull, Hull, UK; 4Department of Applied Health Research, University College London, London, UK; 5Department of Clinical, Educational and Health Psychology, University College London, London, UK; 6National Centre for Sports and Exercise Medicine, Loughborough University, Loughborough, UK; 7Centre for Applied Dementia Studies, University of Bradford, Bradford, UK
Multi-Objective Stochastic Simulation-Based Optimisation Applied to Supply Chain Planning

Abstract The paper discusses the optimisation of complex management processes, which allows the reduction of investment costs by setting the optimal balance between product demand and supply. The systematisation of existing methods and algorithms that are used to optimise complex processes by linking stochastic discrete-event simulation and multi-objective optimisation is given. The two-phase optimisation method is developed based on hybrid combination of compromise programming, evolutionary computation and response surface-based methods. Approbation of the proposed method is performed on the multi-echelon supply chain planning problem that is widely distributed in industry and its solution plays a vital role in increasing the competitiveness of a company. Three scenarios are implemented to optimise supply chain tactical planning processes at the chemical manufacturing company based on using different optimisation methods and software. The numerical results prove the competitive advantages of the develope.
An Improved K-means Algorithm for Brain MRI Image Segmentation

For the problem of low accuracy by the traditional K-means clustering algorithm to segment noised brain magnetic resonance imaging (MRI) images. This paper proposed an improved K-means algorithm. The traditional K-means algorithm only considers the brain image gray value itself, ignoring the relationship between pixels. Due to the characteristics of brain MRI image adjacent pixels most likely belonging to the same class, this paper adopts average value of small neighborhood of each image pixel and image gray value to compose a new sample point, in order to reduce the impact of noise on the clustering accuracy. Experimental results show that the improved K-means algorithm can effectively improve the segmentation accuracy of the noised brain MRI image.
Carbon Nanotubes: A Review on Structure and Their Interaction with Proteins

Carbon nanotubes (CNTs) are allotropes of carbon with a nanostructure that can have a length-to-diameter ratio greater than 1,000,000. Techniques have been developed to produce nanotubes in sizeable quantities, including arc discharge, laser ablation, and chemical vapor deposition. Developments in the past few years have illustrated the potentially revolutionizing impact of nanomaterials, especially in biomedical imaging, drug delivery, biosensing, and the design of functional nanocomposites. Methods to effectively interface proteins with nanomaterials for realizing these applications continue to evolve. The high surface-to-volume ratio offered by nanoparticles resulted in the concentration of the immobilized entity being considerably higher than that afforded by other materials. There has also been an increasing interest in understanding the influence of nanomaterials on the structure and function of proteins. Various immobilization methods have been developed, and in particular, specific attachment of enzymes on carbon nanotubes has been an important focus of attention. With the growing attention paid to cascade enzymatic reaction, it is possible that multienzyme coimmobilization would be one of the next goals in the future. In this paper, we focus on advances in methodology for enzyme immobilization on carbon nanotubes.
Motivational Interviewing Skills: A tool for Healthy Behavioral Changes

Applying the principles and essence of motivational interviewing in everyday primary care practice has been proven effective in promoting “behavioral change” which presents and improves positive health outcomes and enhances the patient-counsellor relationship. Review ARticle encompasses mentoring and non-direct coaching and is patient-centered [3]. MI is supported by many scientific researches, with successful favorable results in different high-risk populations. MI can be useful in brief sessions. It can also be used and learned by non-specialists [3,5].
Seabirds and marine mammals redistribute bioavailable iron in the Southern Ocean

Biological vectors are important for redistribution of nutrients in many ecological systems. While availability of iron (Fe) to phytoplankton limits pelagic productivity in the Southern Ocean, biomagnification within marine food webs can lead to high concentrations of Fe in the diet of seabirds and marine mammals. We investigated patterns in concentrations of the micronutrients Fe, Co, Zn and Mn, and the toxins Cd and As, in the guano of oceanic, coastal and predatory seabirds and in faeces of 2 species of marine mammals that congregate to breed in the sub-Antarctic Auckland Islands. We found that much of the variability in concentrations of Fe, Co, Zn and Mn among species could be explained by foraging behaviour and by trophic position. We observed concentrations of Fe to be 8 orders of magnitude higher in the guano of predators and coastal foragers than in the sub-Antarctic mixed layer. High concentrations of As and Cd were associated with organic matter sources from macroalgae. Analyses of the molar ratio Fe:Al indicated that Fe within food webs supporting seabirds has likely been extensively recycled from its lithogenic source. Patterns in Fe:N among species indicated that Fe is concentrated 2 to 4 orders of magnitude in the guano of seabirds compared to limiting conditions for phytoplankton growth in sub-Antarctic waters. These data highlight the potential role of seabirds and marine mammals in the redistribution of micronutrients in the Southern Ocean and their likely role as key nutrient vectors in the ecosystem, particularly around the sub-Antarctic islands during the breeding season.