Miracle-dz/UniFAR-FTUs huggingface dataset:
ANALYTICAL SOLUTION OF THE EULER EQUATIONS FOR AIRFOIL FLOW AT SUBSONIC AND TRANSONIC CONDITIONS

A compact formulation for obtaining analytical solutions of the 2D steady-state Euler equations is presented. The equations are formulated in the physical plane with flow angle and logarithm of isentropic momentum magnitude as dependent variables. Higher-order effects (e.g., compressibility and entropy) appear as nonhomogeneous forcing terms. The solution procedure does not require a Green’s function for the forcing terms and has general applicability to many other disciplines (e.g., heat transfer) besides fluid dynamics. The zero-order approximation is obtained from solution of the linear, homogeneous system (a boundary-value problem on a simple domain), and is remarkably accurate into the transonic range. Higher-order corrections are generated by iterating on the non-homogeneous terms. Application of the solution approach combined with specialized shock mappings allows analytical transonic flow solutions with a shock wave. The Rankine-Hugoniot shock relations are enforced across the discontinuity along with the correct entropy change. Generation of the analytical solutions is facilitated by the Mathematica symbolic manipulation software. Results are presented that demonstrate the potential accuracy and simplicity of the new procedure.
Investigation of a Numerical Approach for Assessing Liquefaction and its Effects on Telecom Systems

Soil liquefaction has caused substantial infrastructure damage in recent earthquakes. During the 2010-2011 Canterbury Earthquake Sequence (CES), in New Zealand, liquefaction-induced damage to buried cables resulted in service interruption of the telecommunication network. This paper is part of a broader study on the seismic risk of buried infrastructure. It aims to compare numerical and empirical prediction methodologies with the observation maps produced in the aftermath of the Christchurch event. Starting from a description of the New Zealand telecommunication infrastructure and pipelines, the research first explores the vast amount of data and in-situ geotechnical inspections collected after the CES. These data are employed to test several liquefaction-triggering models available in the literature and results are provided through an exploratory spatial analysis. Then, a numerical simulation of a soil profile with and without pipelines from the suburb of Avondale, which was one of the locations most impacted by liquefaction damages, is carried out adopting the Byrne’s formulation for the classic Martin and Finn’s constitutive model in a full dynamic analysis in FLAC-2D. The obtained results from the numerical model are finally cross-checked with the empirical analyses, the existing liquefaction investigation maps, and field observations collected in the aftermath of the event.
COMPARATIVE MOLECULAR ANALYSIS OF ISSR MARKERS IN ARABIAN HORSE BREEDS

Microsatellites are abundantly present in nuclear genome. They are renowned for their utility in polymorphism analyses. The informativeness of multilocus ISSR (Inter-simple sequence repeats) markers was compared to analyze the Arabian horse breeds (Equus caballus) including Middle Eastern Arabian (28) and mixed (hybrid) Arabians (10). They are helpful in the assessment of genetic diversity among horse populations. The marker (GA)9C gave 18 alleles in electrophoretic agarose gel. The low number of loci were detected with the (CA)9G ISSR marker. We calculated the Polymorphism Information Content (PIC) for each of the 12 ISSR markers. In total, 136 alleles were obtained with 12 ISSR markers. The allelic frequencies were also calculated which were ranging from 0.2 to 1.The PIC values were ranging 0.07 to 0.48 from lowest to highest respectively. Trinucleotide-based ISSR markers were found to be more conclusive than the dinucleotide ones. The overall average PIC was 0.2994. The polymorphic bands and their proportion were directly proportional to the PIC value. The highest PIC value detected with the trinucleotide marker (GTG)7C i.e.(0.48).
Retrieving Non Rigid Configuration for Image Matching

Now a day we are finding vast and fast development in every field. Specifically in computer field where every day you can find new technology and its various applications. These technologies provide us the easy and secure way to live a better life. We provide here the approach to identify human being. As the image recognized by the software gives the freedom and security for daily life. The poor quality image will be smoothen and then used by the software. Accessing image capture at different angles should be used as our need. The image not having the frontal view of face still it will be used to detect the human being and identify him. It gives the liability to tag a parson, identify him/her. It decreases the limitation for the controlled setting image capture. Keywords— recognition, face angle, security, trained image, feature extraction, face localization and image pattern matching.
Influence of Method of Teaching on Secondary School Students Academic Achievements in Chemistry

This study investigated the influence of method of teaching on secondary school students academic achievements in chemistry. A total of seventy (70) students form the sample of the study. Two instruments, namely Chemistry Achievement Test (CAT) and Chemistry Attitude Questionnaire (CAQ) were use for data collection. The CAT was develop by the researcher and validated by experts in chemistry education and psychology. The reliability coefficient of CAT and CAQ were found to be r=0.785 and r=0.82 respectively. Analysis of data using t-test statistic and weight average revealed that the experimental group which was taught chemistry using inquiry teaching methods performed significantly better than the control group which was taught using the traditional lecture method. The study recommends, among others, that chemistry teachers should be encouraged to use inquiry method in the teaching of chemistry.
From Sparse Bayesian Learning to Deep Recurrent Nets

where y ∈ R is an observed vector, Φ ∈ Rn×m is some known dictionary of basis vectors with m > n, ‖·‖0 denotes the `0 sparsitypromoting norm, and λ is a trade-off parameter. Although crucial to many applications [1], [2], [3], [4], [5], [6], solving (1) is NP-hard. Popular approximations include convex relaxations such as `1-norm regularization [7], [8], [9] and iterative hard-thresholding (IHT) [10], [11]. However, a core weakness underlies them all: If the columns of Φ are highly correlated, then estimation of x∗ may be poor. Interestingly, many existing sparse estimation implementations involve an update rule comprised of a fixed, linear filter followed by a non-linear activation function that promotes sparsity, both features of typical deep neural network layers. Consequently, algorithm execution can be interpreted as passing an input through a deep network with constant filters (dependent on Φ) at every layer [12], [13], which is also tantamount to a simple form of recurrent network. This association immediately suggests that we consider substituting discriminatively learned filters in place of those inspired by the original sparse recovery algorithm. For example, it has been argued that, given access to a sufficient number of {x∗,y} pairs, a trained network may be capable of producing quality sparse estimates with a few number of layers [12], [14], [15], [16]. In each of these cases however, the initial archetype is a sparse estimation algorithm known to be highly sensitive to data correlations, e.g., convex relaxations, IHT, etc. But if our ultimate goal is to learn a new ‘algorithm’ that efficiently compensates for structure in Φ, it seems reasonable to invoke iterative approaches known a priori to handle such correlations directly as our template for learned network layers. One important example is sparse Bayesian learning (SBL) [17], which has been shown to solve (1) even in cases where Φ displays strong correlations [18]. Herein we demonstrate that, when judiciously unfolded, SBL iterations can be formed into variants of long short-term memory (LSTM) cells, one of the more popular recurrent deep neural network architectures [19], [20]. The resulting network dramatically outperforms existing methods in solving (1) with a minimal computational budget.
Automated key setup and recovery from key exposure for power networks

Power networks are built with inherent redundancy, including in the communication channels. In this work, we show that this redundancy can increase the cyber security resiliency to key exposure. Specifically, we present CrypTop, a novel protocol for the key setup and refresh problem in power networks. CrypTop uses multipath communication and already-keyed devices, to setup keys in other devices, and to recover from key exposures. We evaluate CrypTop in realistic power network topologies. Our results show a significant to dramatic improvement compared to previous works, in both recovery from key exposure and ability to setup keys automatically. For example, in IEEE 300 network, and for a single corruption, CrypTop can recover security in 100% of the devices compared to 1% for previous works.
GUIDELINES FOR THE SUBMISSION OF THE FINAL PAPER

INTRODUCTION An increasing number of wind turbines are being incorporated into electrical networks. In some countries they are becoming a key part of the distribution network & as such affect the overall system performance & reliability [1]. The configuration, technology & size of wind turbines have been changing rapidly over the last few years & larger turbines, >=2MW, incorporating this new technology are being installed onshore throughout Europe. The potential for more wind turbines to be erected in remote locations & offshore, to achieve a greater wind energy harvest, is heightening the need for accurate reliability prediction so that network reliability calculations can be done & wind turbine life predicted. This paper concerns a reliability modelling problem that has arisen when analysing the Failure Rates of wind turbines in Denmark & Germany, using data collected from Windstats [2] over the past 7 years. One of the authors has also shown [3] that such data can be used to predict the reliability of future equipment.
SHRIMP AND FISH CATCH LANDING TRENDS IN SONGKHLA LAGOON , THAILAND DURING 2003-2016

Time series analysis techniques and Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to analyze monthly fish and shrimp catch landing trends recorded for Songkhla shallow lagoon in Thailand (2003-2016). Autocorrelation (AC) and Partial Autocorrelation (PAC) functions were calculated to build seasonal ARIMA models. These models were well-chosen for explaining the time series and forecasting future catch landings. It is found that both fish and shrimp catch landings tend to fluctuate steadily. The fish catch from 2017 to 2020 is steadily increasing on the average catch for the period 2003-2016 by up to 36.06%, while the shrimp catch is decreasing by around 15.47% for the same period. This study demonstrates the importance of undertaking detailed studies of ecological and economic sustainable development to support the comprehensive fisheries management policy for Songkhla Lagoon. The present study shows an effective tool for making accurate forecasts; it also helps in decision making about, and fisheries management of the Songkhla Lagoon.
A TWO-PHASE FLOW SIMULATION USING A FULL-EXPLICIT SCHEME WITH INTERFACE-ADAPTED AMR METHOD

A weakly compressible scheme for gas-liquid two-phase flows with low Mach number is proposed for a fully explicit time integration. To capture the gas-liquid interface, the conservative phase-field equation is solved by using the multi-moment method. The AMR(Adaptive Mesh Refinement) method greatly reduces the computational cost by assigning high-resolution mesh to the region around the moving interface. Several benchmark problems are examined and the results of the explicit scheme are in good agreement with the experimental and computational references and we successfully carried out some violent two-phase flow simulations by using the method which is combined weakly compressible scheme with AMR method.
LBLOCA UNCERTAINTY ANALYSIS USING META MODELS

Safety analysis and the form how this methodology meets safety objectives, is important in the aim to demonstrate that nuclear power plants can operate safely. In this line, the safety guidelines of the International Atomic Energy Agency (IAEA) stablish that safety analysis of the plant design should apply deterministic and probabilistic methods. These studies are complementary, while the two approaches are focused on compliance with the acceptance criteria, the deterministic analysis focuses on verification of limits of damage (usually through safety margins), while the probabilistic focuses on verification of limits of frequency. In this context, it is essential to include in the safety analysis the study of uncertainties. For this reason must be shown that the results are stable to a realistic variation of input parameters into such models. This aspect is more important when realistic codes are used to carry out the analysis of security. In this context, this paper presents an application of the uncertainty and sensitivity analysis to a LargeBreak Loss of Coolant Accident, LBLOCA, in the cold leg of a Pressurized Water Reactor (PWR) using the thermal-hydraulic code TRACE. The aim is to characterize the behavior of the Peaking Clad Temperature (PCT), using an order statistic method, as Wilk’s method, comparing it with a parametric regression model, a metamodel. The metamodel is trained with different sample sizes in order to determine the minimum size required to improve the results obtained by the Wilks method.
THE MEMRISTOR CROSSBAR-BASED WTA NEURAL NETWORK

The problems of programming memristor arrays (memristor crossbars) are considered. An estimate for the pulse width to set the desired memristor resistance (memristance) value is obtained. The implementation of the Winner-Take-All (WTA) neural network on the memristor crossbar and the NMOS transistors for binary images recognition is proposed. The proposed WTA network implementation by simulation on the LTspice IV software was approved.
ORGANIC FARMING IN ROMANIA AND BULGARIA

These days, agriculture and also food business confront new tendencies of developing environmentally friendly options. This kind of agriculture sector surfaced due to folk’s worries regarding health and ecosystem because of the new technologies. These issues appeared and recognized by the developed nations and the like, are usually firmly associated with ecological pollution along with escalating troubles of health degradation. This research compares Romania with Bulgaria, and indicates the possibilities of developing de organic farming sector. The results of this study indicate that this sector has a great potential of developing over the years, in both of the countries that are analysed. In this exploratory research, statistics data were collected from both official governments in Romania and Bulgaria, and this paper indicates the resources on witch both nations can count for developing this sector.
Removing Overflow Tests via Run-Time Partial Evaluation

Trace compilation is a new technique used by just-in-time (JIT) compilers such as TraceMonkey, the JavaScript engine in the Mozilla Firefox browser. Contrary to traditional JIT machines, a trace compiler use only part of source program, normally a linear path inside a heavily executed loop. Because the trace is compiled during the interpretation of the source program the JIT compiler has access to the values manipulated at run-time, a fact that opens the doors to very aggressive optimizations. This fact gives the compiler writer the possibility of improving code via partial evaluation techniques at run-time. In this paper we rely on this observation to present an analysis that removes unnecessary overflow tests from JavaScript programs. Our optimization uses a variation of range analysis to estimate the lower and upper limits of the values assumed by variables during the execution of the program. Such information allows us to prove that some operations cannot produce overflows. Our analysis runs in linear time, in terms of both time and space, and is much more effective than traditional range analyses, given that we have access to values known only at execution time. We have implemented our analysis on top of TraceMonkey, and our experiments show that our non-optimized implementation removes 56% of all the overflow tests that we found, reducing the code size by 2.6%, while increasing the overall time in 6.3%.
Construction and Expression of Two Cytoplasmic hnRNPK Mutants

Heterogeneous nuclear ribonucleoprotein K (hnRNPK) is a member of the hnRNP family which is a DNA/RNA binding protein shuttling between nucleus and cytoplasm but mainly located in the nuleus in most physiological conditions. Previous studies from our lab and the others have shown that hnRNPK is upregulated and displays abnormal cytoplasmic localization in the lung adrenocarcinoma tissue. The functional significance and its related mechanisms of cytoplasmic hnRNPK in the physiopathology of cancer remains still elusive. In order to address this question, we have constructed two hnRNPK mutated forms lacking respectively the nuclear localization signal (NLS) and amino acids 323-337, and examined their subcellular distribution in lung adenocarcinoma H1299 cells in comparison with wild type hnRNPK. This provides appropriate tools for further studies aiming to assess the functions of the cytoplasmic hnRNPK in the physiopathology of cancer and elucidate the related mechanisms.
3 J an 2 01 9 Attitude and Angular Velocity Tracking for a Rigid Body using Geometric Methods on the Two-Sphere Michalis Ramp

The control task of tracking a reference pointing direction (the attitude about the pointing direction is irrelevant) while obtaining a desired angular velocity (PDAV) around the pointing direction using geometric techniques is addressed here. Existing geometric controllers developed on the two-sphere only address the tracking of a reference pointing direction while driving the angular velocity about the pointing direction to zero. In this paper a tracking controller on the two-sphere, able to address the PDAV control task, is developed globally in a geometric frame work, to avoid problems related to other attitude representations such as unwinding (quaternions) or singularities (Euler angles). An attitude error function is constructed resulting in a control system with desired tracking performance for rotational maneuvers with large initial attitude/angular velocity errors and the ability to negotiate bounded modeling inaccuracies. The tracking ability of the developed control system is evaluated by comparing its performance with an existing geometric controller on the two-sphere and by numerical simulations, showing improved performance for large initial attitude errors, smooth transitions between desired angular velocities and the ability to negotiate bounded modeling inaccuracies.
OF DENTIN SURFACES AT IN VITRO EXCAVATION WITH DIFFERENT METHODS FOR MINIMAL INTERVENTION BY ATOMIC FORCE MICROSCOPY ( AFM ) AND SCANNING ELECTRON MICROSCOPY ( SEM )

The micro-invasive method applied to dentine, requires selective controlled excavation. New and various alternative methods for selective excavation and high-tech equipment for excavation control are being created. Modern science is concerned with researching these methods in regards to the control during excavation as well as the choice of method for the excavation itself. The aim of this study was characterization of dentinal surfaces during in vitro excavation with different methods for minimal intervention by atomic force microscopy (AFM) and scanning electron microscopy (SEM). The presented SEM micrographs showed that the obtained dentinal surfaces after excavation by different methods next to healthy dentin differed among themselves. Relatively preserved tubular structure was observed only in the laser processing, while in mechanical treatment the structure was masked by coating “smear layer”. In the resulting dentinal surfaces after excavation to healthy dentin with Carisolv, no visible structure of dentin was observed. The surface was very rough with clearly distinguishable particles of dentine that were flaking and remained bound to it.
Collusive Price Rigidity under Price-Matching Punishments Luke Garrod

By analysing an infinitely repeated game where unit costs alternate stochastically between low and high states and where firms follow a price – matching punishment strategy, we demonstrate that the best collusive prices are rigid over time when the two cost levels are sufficiently close. This provides game theoretic support for the results of the kinked demand curve. In contrast to the kinked demand curve it also generates predictions regarding the level and the determinants of the best collusive price, which in turn has implications for the corresponding collusive profits. The relationships between such price rigidity and the expected duration of a high-cost phase, the degree of product differentiation, and the number of firms in the market are also investigated.
Influence of Interpersonal Barrier and Fear of Crime on Walking Behavior

Walking is a popular form of leisure activity and a convenient option to prevent diseases through a personal control of physical activities. However, little is discussed on walking pattern and its association with social, personal, and physical factors in less developed nations as compared to the developed ones. Previous studies have identified that the most basic factor that influences the individual behavior has been found to occur at the intrapersonal level. In practice the intrapersonal factors influence the people’s behaviors and attributes of their surroundings; while the fear of crime was found to have the most association with walking behavior. On the other hand, the findings for decision and frequency of walking are still ambiguous. This paper elaborates on the influence of the fear of crime and interpersonal factor on the residents’ decisions and regularity of walking leisurely around the neighborhood. A questionnaire survey was used to collect the data. The questionnaire survey was conducted by recruiting 424 representative samples of adults (18-65 years of age). The respondents were the residents of Bandar Baru Bangi, a residential area in Malaysia, as the sample area of the study. Leisure walking was measured for both intention and regularity of walking. The fear of crime was measured by four items and the interpersonal factor was measured by 7 items in terms of the personal barrier. Leisure-time walking was measured for both walking categories-recreational and exercise. A Smart-PLS model was run to analyze the data. The results indicate significant correlation between the interpersonal barrier and the fear of crime with recreational and exercise walking. The fear of crime was found to be more associated with recreational and exercise walking rather than the interpersonal factors.