Miracle-dz/UniFAR-FTUs huggingface dataset:
Acknowledgment : The Research work is done under the guidance of my guide

Computer Technology has Revolutionized Science. Scientists have developed accurate mathematical model of Physical universe and computer programmed with these models can approximate reality at many levels of scale: an atomic nucleus, weather forecasting, the earth’s biosphere or the entire Universe . We can predict the future validate or disapprove theories using these programs. If The computer power is greater the greater will be the accuracy in approximation i.e close will be the approximation to the reality. The speed of the computer should be fast enough to do TeraFLOPS, PetsFLOPS of the calculations in the small amount of time. The way to speed up the computation is to “parallize” it i.e. divide the work into pieces that can be worked on by separate processors at the same time. Thus we can solve the problems that are Non-Polynomial form in polynomial time. If the Scientist has an idea for a computation, but finds that it will take a million years of computer time, normal reaction is to toss the idea in a Waste bucket. One of the approach is to use multimillion dollar Supercomputer e.g. Jaguar by Cray Research Inc and Installed at Oak Ridge Nation and Eka (fourth fast Super Computer) by Tata or Computational Grid that are geographically distributed resources e.g. SETI@home(Used to detect radio waves emited by intelligent civilizations outside earth) has 4.6 million participants computers. So instead of investing so much of money on Super Computer, we can built Computational grid having the power same that of the desktop computer. Computational Grid is used in number of applications like Weather Forecasting, Climate Change Prediction, Detection of Radio Signals emitted by intelligent Civilizations outside earth etc. In this paper the Alchemi.NET framework is used for calculating the 100 digit places value after decimal of Pi (π) value.
Phylogenetics GEIGER : investigating evolutionary radiations

Summary: GEIGER is a new software package, written in the R language, to describe evolutionary radiations. GEIGER can carry out simulations, parameter estimation and statistical hypothesis testing. Additionally, GEIGER’s simulation algorithms can be used to analyze the statistical power of comparative approaches. Availability: This open source software is written entirely in the R language and is freely available through the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/. Contact: lukeh@uidaho.edu
Chapter 6 Prognostic Biomarkers for Breast Cancer Metastasis

Breast cancer treatment has improved rapidly through the years, starting from surgery, to hormonal therapy, to targeted therapy. Despite this, tumor metastasis remains the highest cause of breast cancer–related death. The current regime to deter metastasis is through adjuvant therapy, but such therapy frequently yields undesirable side effects. As such, prognostic markers for metastasis are important to stratify patients for adjuvant therapy so as to ameliorate the standard of living of patients with low metastatic potential. So far, only a few well-characterized prognostic biomarkers for metastasis are used in clinics. This chapter will cover both established and novel prognostic biomarkers for breast cancer metastasis and metastatic breast cancer prognosis. The potential of using these biomarkers as predictive biomarkers or new targeted therapy will also be discussed.
Effects of Usage of Sepiolite in Layer Diet on Pellet Quality and Pellet Production Parameters

The purpose of this experiment was to determine the effects of sepiolite usage on pellet quality and pellet production parameters for layer diet under industrial conditions. In this study; 14 t pellet diets for control and treatment groups with 7 batch were produced in a commercial feed factory. Each batch was 2 t. Control group diet manufactured in this study, contained 14.12% crude protein, 4.47% crude fibre and 3.20% ether extract. For the treatment group diet 1% sepiolite was used as top dressed in the mixer. Pelleting disc having 6 mm hole diameter was used in the factory. Sepiolite usage reduced energy consumption at the level of 16.14% and increased pellet durability index significantly (p<0.001). Pellet durability index was found to be 49.08% in the control group and 87.39% in the treatment group. Therefore, it is concluded that sepiolite usage in layer diets would be beneficial for improvement in pellet quality.
Yarn pulling out test and numerical solution of penetration into woven fabric target impregnated with shear thickening fluid using SiO2 /Polyethylene Glycol

In this paper, finite element model of woven fabric target has been investigated which is impacted by a cylindrical projectile. Fabrics are impregnated with Shear Thickening Fluid (STF). The effects of the (STF) have been considered as frictional effect. The STF has been made (Nano Silica and Polyethylene Glycol (PEG)) and then diluted by ethanol proportion of 3:1. Yarn pulling out test from inside of fabric is performed to estimate the pulling out force and the friction coefficient. The speed of pulling out was 500 mm/min and the samples were placed vertically in tensile device. The results of yarn pulled out indicated that the fabric impregnated in STF needs more force in order to gets out of fabric. Friction coefficient of a regular fabric is 0.26 and in a fabric impregnated by STF is 1.5. Friction coefficients of tow fabric types of raw fabric and fabric with STF are entered in ANSYS software along with mechanical characteristic of a yarn. Ballistic range velocity was extracted for samples in software and was compared with experience results.
An Intrinsic Difference Between Vanilla RNNs and GRU Models

In order to perform well in practice, Recurrent Neural Networks (RNN) require computationally heavy architectures, such as Gated Recurrent Unit (GRU) or Long Short Term Memory (LSTM). Indeed, the original Vanilla model fails to encapsulate middle and long term sequential dependencies. The aim of this paper is to show that gradient training issues, which have motivated the introduction of LSTM and GRU models, are not sufficient to explain the failure of the simplest RNN. Using the example of Reber's grammar, we propose an experimental measure of both Vanilla and GRU models, which suggest an intrinsic difference in their dynamics. A better mathematical understanding of this difference could lead to more efficient models without compromising performance.
A ROBUST PATHFINDING ALGORITHM USING CHEMICAL COMPOSITION BY PRATIK LAHIRI

Metabolic pathfinding is the task of finding preferred metabolic pathways from metabolic large reaction databases. Representing metabolism via networks enables quick enumeration of paths between two compounds. Automated pathfinding helps in working with ever increasing databases if reactions and in finding novel pathways for metabolic engineering. However, the number of pathways between two compounds can be as large as 500,000 in some metabolic models and even more as the size of the input database grows, which makes it imperative that the most relevant ones are ranked highly. While graph theoretic representations of metabolic networks bring speed and ease in enumeration of pathways, they also create the challenge of biochemically insensible shortcuts through pool or currency metabolites. In the past, strategies to circumvent such irrelevant pathways have included weighing networks using the degree of nodes or the manual curation of edges in the metabolic network. The former method wrongfully penalizes some primary metabolites central to metabolism, while the latter requires someone to complete manual curation. KEGG RPAIR database is an annotation to describe reactions in terms of reactant pairs and has been used for metabolic pathfinding. Here, I first study a few different centrality measures to identify currency metabolites and identify one better than the degree centrality. I then describe a method to augment the KEGG RPAIR based pathfinding method using a chemical composition score and evaluate its ability to augment and replace the role of RPAIRs in pathfinding. The new algorithm is validated against a set of 30 biochemical pathways in E.coli. Since this method uses chemical composition as a fallback measure, it can be used in the absence of explicit RPAIR information, thus allowing the identification of putative paths not possible via methods using the RPAIR database alone.
CONTRACEPTIVE FOR USE BY A MALE

2,384,085 4/1941 Gerhart . 522/168 2,955,994 10/1960 Guthrie et al. . 522/168 3,398,226 8/1968 Yamamoto et al. . 424/78.21 3,616,229 9/1968 Wildli et al. . 424/78.21 4,432,967 2/1984 Szymanski . 424/78 4,439,441 3/1984 Hailesy et al. 424/DIG. 14 4,760,097 7/1988 Wiebe . 514/841 4,917,901 4/1990 Bourbon et al. . 514/84
An acoustic analysis of short front vowel realizations in the conversational style of young English speakers from Western Australia

This study presents the findings of an analysis of short front vowel (SFV) realisations in a corpus of unscripted conversational speech generated by 40 young speakers from Perth. As well as providing the first comparative account of SFV realisations in that location, we consider the extent to which the realisational variability observed is associated with properties of the continuous unscripted speech style that are known to influence spectral and temporal properties of vowels.
PERSISTENT PULMONARY HYPERTENSION IN NEWBORN RECENT PROGRESS

Persistent pulmonary hypertension in newborn (PPHN) is a collection of symptoms showing failed circulatory adaptation at birth. This is characterized by increased pulmonary vascular pressure resistance which leads to extra-pulmonary shunting from right to left flow of blood across the ductus and/or foramen ovale. PPHN occurs mostly in term and near term infants but it is not uncommon in preterm infants who have respiratory distress syndrome. The treatment of PPHN include oxygen supplementation, mechanical ventilation, nitric oxide, phosphodiesterase inhibitors, prostaglandins analogs, endothelin receptor antagonists to maintain ideal vital signs and internal environment homeostasis required and also decrease pulmonary pressure, to decrease the need of ECMO, progression of disease and duration of hospital stay.
Effects of Different Supplementation Levels on Intake and Ruminal Parameters of Post Weaning Steers Grazing Brachiaria brizantha , in the Amazonian Area

The objective of this trial was to evaluate the effects of different levels of supplementation on dry matter intake and of ruminal pH and ammonia content of growing steers grazing Brachiaria brizantha, during the dry to rainy transition season, from April to June 2003. Five ruminally fistulated steers averaging 15 months old and initial weight of 271 kg were assigned to a 5x5 Latin square design. The treatments were as follows: control (mineral salt) and supplements fed at different levels (0.125, 0.25, 0.50, and 1.0% body weight/animal/day) and contained corn and soybean meal formulated to yield 24% crude protein. The voluntary intake was calculated by the relation between the amount of fecal dry matter excreted by using both external (chromium oxide) and internal (indigestible acid detergent fiber) markers. It was observed difference on dry matter forage intake by increasing the levels of supplementation. The control group showed higher dry matter intake (9.27 kg/day), with no difference among the supplementation levels. The most evident decrease of forage intake was observed at 1.0% BW (1.95% BW), with no change on average daily gain. Observed replacement and additive effects increased stocking rate by 16, 25, 27 and 32%, respectively, at 0.125, 0.25, 0.5% and 1.0% BW. The pH values for all treatments averaged 6.2, below which inhibit fiber digestion. The ruminal ammonia contents of the supplemented animals were always higher than the threshold value of 10 mg/dL that maximize microbial growth and ruminal digestibility in tropical conditions.
Chapter 7 Impacts of Wind Farms on Power System Stability

Power systems are complex systems that evolve over years in response to economic growth and continuously increasing power demand. With growing populations and the industriali‐ zation of the developing world, more energy is required to satisfy the basic needs and to attain improved standards of human welfare. In order to make energy economically available with reduced carbon emission using renewable energy sources, the structure of the modern power system has become highly complex [1].
Title Parameter identification of wireless power transfer systemsusing input voltage and current

Wireless power transfer (WPT) systems based on the use of resonators with high quality factors are highly sensitive to the parameters of the resonant tanks. While the inductance terms can be theoretically calculated, the mutual inductance terms require very accurate measurements of the coil dimensions, locations and orientations. Slight deviations of these measurements could therefore lead to significant errors. In addition, capacitors have fairly large tolerance in terms of their capacitance, making it difficult to assume their rated values in the determination of the optimal operating frequency of the WPT systems. In this paper, a parameter identification method for WPT systems based on the measurements of the input voltage and current is presented. Using an evolutionary algorithm, accurate parameter values required for modeling the WPT system can be determined. This method has been successfully illustrated in a 3-coil WPT system. Good agreements between calculated and measured parameters have been achieved.
Towards formal testing of jet engine

The Rolls-Royce BR725 is a newly designed jet engine for ultra-longrange and high-speed business jets. In this paper we apply our theory of formal testing [5,6] to the starting system of the Rolls-Royce BR725 control software. To this end we model the system in CSP, evaluate test suites against the formal model, and finally execute test suites in an in-the-loop setting of the SUT. This case study demonstrates the applicability of our testing approach to industrial systems: it scales up to real world applications and it potentially fits into current verification and quality assurance processes, as e.g., in place at Rolls-Royce.
Control Region Approximation III : Scattered Data Interpolation

In the predecessors to the present paper [14, 15], the Control Region Approximation [9, 13] was developed for numerical differentiation and integration on arbitrary lattices [11]. Herein, this approximate technique is extended to apply to the complementary problem of scattered data interpolation on arbitrary two-dimensional domains [10]. This is achieved by utilizing the Dirichlet tessellation of a general discrete point set [18, 20] in concert with the reduced quintic triangular finite element of Bell [1]. The resulting piecewise-quintic C1 interpolant is third-order accurate for sufficiently smooth data on an arbitrary lattice. This leads naturally to a correspondingly third-order accurate quadrature formula based upon the Delaunay triangulation [2, 6] that is complementary to that based upon the dual Dirichlet tessellation [15]. The path of extension of this technique to three-dimensional scattered data is traced.
Título : An Application of Quah and Vahey ' s SVAR Methodology for Estimating Core Inflation in Brazil

The issue of core inflation measurement and its relevance for policy making has been thoroughly discussed both in the international, and on the Brazilian applied literature. Despite this relevance, there is no consensus on how best to measure core inflation. Several different methodologies have been employed for Brazilian data, with different results. Here we apply Quah and Vahey's (1995) methodology to Brazilian data. This methodology is attractive in computational and data requirement aspects, and is the only one based on economic theory. We also discuss how the results from the estimated model can be used to provide a measure of potential product, which is also a very relevant issue for policy making. Key-Words: Core Inflation, Structural VAR estimation, Potential Product estimation Área de Classificação da ANPEC: 02 (Macroeconomia) Código JEL: C22, E31
CIRJE-F-693 Realized Volatility Risk

In this paper we document that realized variation measures constructed from highfrequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Carefully modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility (DARV) model, which incorporates the important fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks.
Global Development of Farmer Water User Associations ( WUA ) : Lessons from South-East Asia

The author, Dr. Mei Xie, is a World Bank (WB) expert on Water Resources Development. She has been in Vietnam many times since 1996 in order to collaborate with agencies of the Vietnamese Ministry of Agriculture & Rural Development (MARD) to prepare the Agreement of the ODA Project of Water Resources Development in the Mekong Delta. The Agreement was signed in 2000 between WB & Vietnam State Bank (authorized by the Vietnam Goverment) and WB had appointed her as the Project Leader since then. Her outstanding efforts together with the Vietnamese side cooperation had overcome objective difficulties to implement the Project successfully. In 2006 she was promoted to a new function in the WB Institute.
Harnessing Forests for Climate Change Mitigation through REDD + Convening lead

Deforestation, forest degradation, and land-use change are a major source of carbon emissions. The Copenhagen Accord recognised the crucial role of reducing emissions from deforestation, emphasized the role of forests in climate change mitigation, and called for the immediate establishment of a REDD+ mechanism. Most likely, it will form an integral part of the future climate change regime. For many developed countries, REDD+ seems to be an attractive option to achieve part of their reduction targets through investments in developing countries. For some developing countries, this offers an additional source of financing to support sustainable forest management and to boost their development plans and poverty-reduction strategies. This paper analyses the challenges and major gaps that developing countries are facing when planning their national strategies for the implementation of REDD+ schemes. We conclude that REDD+ as a climate change mitigation instrument will only be able to proceed at a pace that allows the meaningful participation of all relevant stakeholders in consensus-building. When the REDD+ enters the markets, the rights of local communities to forest land and carbon will need to be clarified and secured. Successful implementation of REDD+ will, in most cases, require strengthening the stake of local communities for managing their forest carbon assets and allowing them to benefit fully from emerging carbon markets and other funding schemes. Governments will need to renew their institutions and adopt new approaches to handle these challenges by including the role of forests in climate change mitigation as an integral part of their development plans and policies.
Evidence Aggregation Based Spam Detection in e-Commerce Social Network

Ranking spam in the Social Media and Social Network market refers to fake or deceptive activities which have a purpose of striking up the products and the services for different interests in the popularity list. Indeed, it becomes more and more repeated for Social Networks to use sheltered means, such as inflating their products sales or posting services of the product ratings, to commit ranking spam. While the importance of preventing ranking spamming has been recognized, we provide a holistic inspection of ranking spam and propose a spamming detection system for social network. We propose to exactly locate the ranking spam by mining the active periods, namely leading sessions, of social network. Such sessions can be influenced for detecting the actual rating instead of spammed rating of product rankings. by modeling social networks ranking, rating and review behaviors in the course of statistical proposition tests.
D ec 2 01 7 Gravity and Unification : A review

We review various classical unified theories of gravity and other interactions that have appeared in the literature, paying special attention to scenarios in which spacetime remains four-dimensional, while an “internal” space is enlarged. The starting point for each such unification scenario is a particular formalism for General Relativity. We thus start by reviewing, besides the usual EinsteinHilbert and Palatini formulations, the Einstein-Cartan, MacDowell-Mansouri and BF (both nonchiral and chiral) formulations. Each of these introduces some version of “internal” bundle and a dynamical variable that ties the internal and tangent bundles. In each of these formulations there is also an independent connection in the “internal” bundle. One can then study the effects of “enlarging the internal space”, which typically leads to a theory of gravity and Yang-Mills fields. We review what has been done in the literature on each of these unification schemes, and compare and contrast their achievements to those of the better developed Kaluza-Klein scenario. Electronic address: kirill.krasnov@nottingham.ac. uk Electronic address: percacci@sissa.it
Applicable Analysis and Discrete Mathematics

We give a survey of graph spectral techniques used in computer sciences. The survey consists of a description of particular topics from the theory of graph spectra independently of the areas of Computer science in which they are used. We have described the applications of some important graph eigenvalues (spectral radius, algebraic connectivity, the least eigenvalue etc.), eigenvectors (principal eigenvector, Fiedler eigenvector and other), spectral reconstruction problems, spectra of random graphs, Hoffman polynomial, integral graphs etc. However, for each described spectral technique we indicate the fields in which it is used (e.g. in modelling and searching Internet, in computer vision, pattern recognition, data mining, multiprocessor systems, statistical databases, and in several other areas). We present some novel mathematical results (related to clustering and the Hoffman polynomial) as well.