Miracle-dz/UniFAR-FTUs huggingface dataset:
THE INFLUENCE OF ASCORBIC ACID AND HONEY ADDITION ON THE ANTI‐OXIDANT PROPERTIES OF FRUIT TEA INFUSIONS: ANTIOXIDANTS IN FRUIT TEA INFUSIONS

The influence of ascorbic acid and honey addition on the total phenol (TP) content and anti-oxidant capacity of ten commercial fruit tea infusions was studied. The Folin-Ciocalteu assay was used to determine the TP content, ferric reducing anti-oxidant power assay for reducing capacity and 1,1-diphenyl-2-picryl-hydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt assays for radical scavenging capacity. High pressure liquid chromatography was employed to quantify polyphenolic compounds in infusions. The addition of ascorbic acid (22.5 mg) increases the TP content as well as anti-oxidant capacity of all fruit tea infusions. The addition of honey (1.5 g) to infusions containing ascorbic acid resulted in an average 28% decrease in the TP value, and a significant average (22%) decrease in the DPPH radical scavenging capacity. Chlorogenic acid is the predominant phenolic acid in tested infusions (range: 12.86–91.55 mg/L), while epigallocatechin-gallate is the most concentrated among analyzed catechins (range: 19.26–161.41 mg/L). PRACTICAL APPLICATIONS There are no published scientific papers characterizing polyphenolic compounds and anti-oxidant activity of infusions prepared from bagged fruit teas, although these beverages are very popular in Europe and United States where they are often taken with lemon and honey. The results reported in this study indicate that fruit tea infusions are, just like herbal teas, valuable sources of polyphenolic anti-oxidants and that beverages prepared from teas containing a substantial portion of fruit parts exhibit the best anti-oxidant properties. Also, we have demonstrated that the addition of ascorbic acid enhances the anti-oxidant capacity of fruit teas while the addition of honey causes a decrease in the total phenol content and may adversely affect the radical scavenging potential of analyzed fruit teas.
Learning Simon's quantum algorithm

We consider whether trainable quantum unitaries can be used to discover quantum speed-ups for classical problems. Using methods recently developed for training quantum neural nets, we consider Simon's problem, for which there is a known quantum algorithm which performs exponentially faster in the number of bits, relative to the best known classical algorithm. We give the problem to a randomly chosen but trainable unitary circuit, and find that the training recovers Simon's algorithm as hoped.
DEVELOPMENT: A DIALOG BETWEEN THEORY AND RESTROSPECTION

This paper presents two independently developed design methodologies: Environment-Based Design (EBD) and X-Development. These two methodologies share exactly the same foundation: design is based on environment. The environment is where the designed product is to work. The environment was there, is there, and will still be there. Any design action changes only the environment. This paper thus conducted a preliminary comparison of these two methodologies. This coincidental convergence of two design methodologies provides one kind of support to the each other. Future work will be focused on the formalization and refinement of X-Development through the mathematical operations included in the EBD.
Integration of Audit Data Analysis and Mining Techniques into Aide

Abstract : In recent years, intrusion detection systems have gained wide acceptance within both government and commercial organizations. A number of intrusion detection tools are commercially available and are being routinely used as part of the protection of network and computer systems. There are several limitations to the present generation of the intrusion detection systems: these tools detect only those attacks that are already known, generate too many false positives, and operation of these tools is too labor intensive. To overcome these problems, we developed methods and tools that can be used by the system security officer to understand the massive amount of data that is being collected by the intrusion detection systems, analyze the data, and determine the importance of an alarm. Report divided into three parts. Part I describes a network intrusion detection system, called Audit Data Analysis and Mining (ADAM), which employs a series of data mining techniques including association rules, classification techniques, and pseudo-Bayes estimators to detect attacks using the network audit trail data. Part II shows how to build attack scenarios by explicitly including network vulnerability/exploit relationships in the model. Part III provides a complete list of publications resulting from this effort and successfully licensed the resulting technology to a company called Secure Decisions and filed for four patents.
Trajectories of social vision: Eye contact increases saccadic curvature

ABSTRACT Saccades are known to deviate away from distractors, and the amplitude of this deviation seems to reflect the salience of these stimuli, as in the case of human faces. Here, we investigated whether eye contact can modulate attention allocation by examining saccadic curvature when faces with closed vs. open eyes act as distractors. In two experiments, participants were asked to perform a vertical saccade towards a symbolic target. At the same time, task-irrelevant faces with open or closed eyes (Experiments 1 and 2) and scrambled faces (Experiment 2) could appear leftwards or rightwards with respect to the ideal trajectory towards the target. Overall, a greater saccadic curvature was observed in response to faces with open eyes, as compared to the other two conditions. These results confirm that eye contact plays an important role in shaping attentional mechanisms and provide further evidence concerning the link between social vision and eye movements.
REAL-TIME INTRUSION DETECTION SYSTEM FOR BIG DATA

The objective of the proposed system is to integrate the high volume of data along with the important considerations like monitoring a wide array of heterogeneous security. When a real time cyber attack occurred, the Intrusion Detection System automatically store the log in distributed environment and monitor the log with existing intrusion dictionary. At the same time the system will check and categorize the severity of the log to high, medium, and low respectively. After the categorization, the system will automatically take necessary action against the user-unit with respect to the severity of the log. The advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or reports based on abnormal behaviour.
EXPERIMENTAL INVESTIGATION OF EVAPORATION ENHANCEMENT FOR WATER DROPLET CONTAINING SOLID PARTICLES IN FLAMING COMBUSTION AREA

The experimental study of integral characteristics of extinguishing liquid (water) droplet evaporation in flaming combustion area has been held. Optical methods of two-phase and heterogeneous mixtures diagnostics (“Particle Image Velocimetry” and “Interferometric Particle Imaging”) have been used for heat and mass transfer process investigation. It was established that small-size solid particles (for example, carbon particles) in droplet structure can enhance water evaporation in flame area. It was shown that the rate of evaporation process depends on concentration and sizes of solid particles in a water droplet. The correlations have been determined between the sizes of solid particles and water droplets for maximum efficiency of fire extinguishing. The physical aspects of the problem have been discussed.
IMAGE SEGMENTATION BY MODIFIED MAP -ML ESTIMATIONS

Though numerous algorithms exist to perform image segmentation there are several issues related to execution time of these algorithm. Image Segmentation is nothing but label relabeling problem under probability framework. To estimate the label configuration, an iterative optimization scheme is implemented to alternately carry out the maximum a posteriori (MAP) estimation and the maximum likelihood (ML) estimations. In this paper this technique is modified in such a way so that it performs segmentation within stipulated time period. The extensive experiments shows that the results obtained are comparable with existing algorithms. This algorithm performs faster execution than the existing algorithm to give automatic segmentation without any human intervention. Its result match image edges very closer to human perception.
Improved resolution in far-field integral imaging

In multi-view three-dimensional imaging, to capture the elemental images of distant objects, the use of a field-like lens that projects the reference plane onto the microlens array is necessary. In this case, the spatial resolution of reconstructed images is determined by the spatial density of microlenses in the array. In this paper we report a simple method, based on the realization of double snapshots, to double the 2D pixel density of reconstructed scenes. Experiments are reported to support the proposed approach.
Analysis of generalized processor sharing systems using matrix analytic methods

| Generalized Processor Sharing (GPS) is an important scheduling discipline because it enables bandwidth sharing with work conservation and traÆc isolation properties. Although Markov Modulated Fluid Processes (MMFP) captures the ne dynamics of the sources and is expected to give tight performance bounds, the analysis of MMFP sources with a GPS server is usually diÆcult because of the large state space and the coupled services of the classes. Matrix analytic methods [8], which yield great numerical accuracy and stability, are e ective alternatives to the spectral analysis approach (e.g. [12]). In this paper, we apply Matrix Analytic methods for uid ows as introduced by Ramaswami [11] to the analysis of GPS systems fed by MMFP sources. We propose a new technique to calculate the tail distributions of the classes where matrices processed are of smaller sizes, which greatly reduces the computation complexity. Numerical results illustrate the eÆciency and accuracy of the technique. We also investigate the Caudal Characteristics of GPS queues which further illustrate the e ectiveness of the GPS scheduling discipline.
Effects of Particle Size and Surface Chemistry on the Dispersion of Graphite Nanoplates in Polypropylene Composites

Carbon nanoparticles tend to form agglomerates with considerable cohesive strength, depending on particle morphology and chemistry, thus presenting different dispersion challenges. The present work studies the dispersion of three types of graphite nanoplates (GnP) with different flake sizes and bulk densities in a polypropylene melt, using a prototype extensional mixer under comparable hydrodynamic stresses. The nanoparticles were also chemically functionalized by covalent bonding polymer molecules to their surface, and the dispersion of the functionalized GnP was studied. The effects of stress relaxation on dispersion were also analyzed. Samples were removed along the mixer length, and characterized by microscopy and dielectric spectroscopy. A lower dispersion rate was observed for GnP with larger surface area and higher bulk density. Significant re-agglomeration was observed for all materials when the deformation rate was reduced. The polypropylene-functionalized GnP, characterized by increased compatibility with the polymer matrix, showed similar dispersion effects, albeit presenting slightly higher dispersion levels. All the composites exhibit dielectric behavior, however, the alternate current (AC) conductivity is systematically higher for the composites with larger flake GnP.
Adapting Data Adaptive Methods for Small, but High Dimensional Omic Data: Applications to GWAS/EWAS and More

Exploratory analysis of high dimensional “omics” data has received much attention since the explosion of high-throughput technology allows simultaneous screening of tens of thousands of characteristics (genomics, metabolomics, proteomics, adducts, etc., etc.). Part of this trend has been an increase in the dimension of exposure data in studies of environmental exposure and associated biomarkers. Though some of the general approaches, such as GWAS, are transferable, what has received less focus is 1) how to derive estimation of independent associations in the context of many competing causes, without resorting to a misspecified model, and 2) how to derive accurate small-sample inference when data adaptive techniques are used in this context. This paper focuses on semiparametric variable importance analysis of high dimensional data sets of modest sample size (e.g., gene expression, mRNA, etc). Though the methodology we propose is generally applicable to similar situations, we present the method in the context of a study of miRNA expression for an environmental exposure. Specifically, the analysis is faced with not just a large number of comparisons, but also trying to tease out of association of the expression of miRNA with an exposure apart from confounds such as age, race, smoking conditions, BMI, etc. Our goal is to propose a method that is reasonably robust in small samples, but does not rely on misspecified (arbitrary) parametric assumptions, and thus will be based on data-adaptive methods. The methodology proposed is we believe a powerful combination of existing semi-parametric statistical methods and theory, as well as a simple framework for use of commonly used empirical Bayes approaches to aid in small sample inference. Specifically, We propose using targeted maximum likelihood estimation (TMLE) for estimating variable importance measures along with a general adaptation of the commonly used Limma approach, which relies on specification of the so-called influence curve of the proposed estimator. The result is a machine-based approach that can estimate independent associations in high dimensional data, but protects against the unreliability of small-sample inference that can result when using data adaptive estimation in relatively small samples.
AN EFFICIENT FRAMEWORK FOR IMAGE DATA RECOGNITION & RETRIEVAL

Valuable information can be hidden in images, however, few research discuss data mining on them. Image retrieval means searching, browsing and retrieving images from image databases. There are two different methodologies for image retrieval i.e. text based image retrieval and content based image retrieval. Former one is obsolete. In latter one many visual features like texture, size, intensities, and frequency of pixels and color of image are extracted. In query-by-example search extracted featured are compared with stored ones. In this work an efficient for extracting image features is considered using intensity histogram of gray color image. Here in this general framework based on the decision tree for mining and processing image data. Pixel wised image features were extracted and transformed into a database-like table which allows various data mining algorithms to make explorations on it. Finally results of average gradient vectors are to be compared with previously stored one dimensional array of intensities to find similarities in image data
On the Use of Photothermal Techniques as a Tool to Characterize Ceramic-Metal Materials

Since the discovery of the photoacoustic effect by Bell in 1881 (Bell, 1880), the so-called photoacoustic techniques have experienced great expansion. Since 1980, approximately, they have been used in a wide range of scientific areas. The photoacoustic and related photothermal techniques have proved to be a valuable tool to thermal characterization of solids, liquids and gases (Vargas & Miranda, 2003). This is one of the non-destructive laserinduced photothermal techniques that are based on the detection of periodic thermal waves generated due to a non-radiative de-excitation in the sample, which is illuminated by a chopped or pulsed optical excitation. In this chapter, thermal and structural characteristics of hardmetal (WC-10%wt Co) alloys were examined. Hardmetal is a composite material (ceramic-metal) comprised by hard tungsten carbide – WC grains or particles, embedded into a tough binder – normally cobalt Co (Allibert, 2001). Co percolates the WC particles, forming the WC-Co structure – the most common hardmetal alloy. The hardmetal’s formation occurs through the liquid phase sintering of the as compacted WC and Co powders, at temperatures roughly about 1400oC, in which Co spreads around WC grains and particles, enabling homogeneity, density, hardness and other desired properties. Both phases can be modified, aiming at achieving the final desired properties (Upadhyaya, 2001). As an example, the binder phase amount is linked to the hardmetal properties, that is, as large is the Co amount, as lower is the hardness, but the fracture toughness is substantially improved. Hardmetals present high hardness, good wear resistance, and considerable fracture toughness, allied with interesting thermal properties. These materials have been widely used in industry, due to the excellent combination among wear, impact, compressive resistance, high elastic modulus, corrosion and thermal shock resistance (Allibert, 2001; Fang et al., 2009). Therefore, due to the high stability and excellent mechanical properties, their main applications includes the cutting tools in general, oil and gas well drills, forming parts – such as wire drawings tools, high energy milling components, among others (Gille et al ., 2002). Thermal characterization plays an important role to qualify hardmetals, rare are the literatures with the purpose of analyzing these properties (Faria Jr. et al., 2005, Kny & Neumann, 1985). This study intends to discuss the thermal behavior in six diversified WC-
Portfolio Optimisation Problems

Portfolio optimization problems or asset allocation problems look at the “best” way for an investor or fund manager to allocate funds between a number of different asset classes. One criterion is to maximize the utility of the portfolio of assets at the end of the investment period. The classical mean variance model, which involves maximizing the portfolio return and minimizing the risk, was proposed by Markowitz [21] in 1952. There has been continual interest in the problem since (see [22, 28, 19, 23, 8, 12] for example), with increasingly sophisticated mathematical models being proposed (see [26, 7, 20, 25] for recent examples). In the most basic setting the planning horizon is just a single period, and transaction costs are ignored. This allows some of the basic ideas to be discussed but limits the applicability of the models. Let the asset classes be indexed {1, . , n} and let xi be the fraction of the portfolio allocated to asset class i. The vector of weights x = (x1, . . . , xn) T ∈ R then satisfies e x = 1 x ≥ 0.
The All-Wavelength Extended Groth Strip International Survey (AEGIS) Data Sets

In this the first of a series of Letters, we present a panchromatic data set in the Extended Groth Strip region of the sky. Our survey, the All-Wavelength Extended Groth Strip International Survey (AEGIS), aims to study the physical properties and evolutionary processes of galaxies at z ~ 1. It includes the following deep, wide-field imaging data sets: Chandra/ACIS X-ray, GALEX ultraviolet, CFHT/MegaCam Legacy Survey optical, CFHT/CFH12K optical, Hubble Space Telescope/ACS optical and NICMOS near-infrared, Palomar/WIRC near-infrared, Spitzer/IRAC mid-infrared, Spitzer/MIPS far-infrared, and VLA radio continuum. In addition, this region of the sky has been targeted for extensive spectroscopy using the Deep Imaging Multi-Object Spectrograph (DEIMOS) on the Keck II 10 m telescope. Our survey is compared to other large multiwavelength surveys in terms of depth and sky coverage.
LOW VOLTAGE OPERATIONAL TRANSCONDUCTANCE AMPLIFIER

Operational amplifier is one of the essential component of signal processing task ranging from simple amplification of weak signal to complex audio or video processing applications in mixed signal domain. In this paper the detailed analysis of The Three Stage Operational Trans-conductance Amplifier (OTA) using active single Miller capacitor along with Inner half feed-forward technique for driving high load capacitor and comprehensive performance analysis between the active capacitive feedback compensation technique and the three stage operational trans-conductance amplifier is made. The proposed technique is implemented to work on power supply of 1.8 V while attaining amplification of more than 280 dB with increased slew rate.
Assessment of Morbidity Profile in a Slum Community in Kolkata

Background: In cities of India, almost one fifth people live in slums. Still these are the neglected portions of the community. Morbidity survey may give an overall picture of the condition of the population under study Objective: To assess the morbidity profile of the study population and to find out the association between sociodemographic characteristics and morbidity profile of the study population Methodology: It was a community based, observational, descriptive study; cross-sectional in design; conducted in Arpuli Lane, a slum area in ward no.40 of Kolkata Municipal Corporation during February to April of 2016. Slum dwellers of all age groups in the study area constituted the study population. Participants were selected applying inclusion and exclusion criteria. Data was collected by house to house visit and face to face interview of the subjects using a pre-designed, pre-tested, semi-structured interview schedule. Analysis was done in Statistical Packages for Social Sciences (SPSS) version 19. Chi-square test was done to examine the statistical significance. Result: Overall 51.7% study subjects were either suffering from or had a history of one or more illness in previous one month. Pallor (16.1%), hypertension (14.4%) and arthritis (12.7%) were the three most common morbidities encountered in the study subjects. Age, education and per-capita monthly income had statistically significant influence on the morbidity profile of the study population. Conclusion: Considering the high morbidity of the slum dwellers, special clinics should be arranged for treatment of common morbidities and health promotional activities should be undertaken to improve their health status
Role of Vaccination in the Control of Turkey Coccidiosis: Vaccine Associated Oocyst Shedding, Lesions, and Mucosal Gene Expression

Role of Vaccination in the Control of Turkey Coccidiosis: Vaccine Associated Oocyst Shedding, Lesions, and Mucosal Gene Expression. (May 2011) Michelle A. Behl, B.S., University of Wisconsin-Madison Chair of Advisory Committee: Dr. Morgan Farnell Coccidiosis vaccine associated side effects, oocyst shedding patterns, intestinal lesions, and mucosal gene expression in the turkey were studied. The first study examined vaccine associated side effects and oocyst shedding patterns under experimental conditions. Peak oocyst shedding occurred on days 5-6, 13-17, and 19-20 days post vaccination. Throughout the course of the study, several poults exhibited clinical coccidiosis. Based on body weights, growth was correlated with vaccine cycling. The second study examined coccidiosis vaccine induced lesions and changes in mucosal gene expression on day 5, 10, 13, 17, and 20 days post vaccination. Poults were gavaged the equivalent of 0x, 1/2x, 1x, and 2x the available vaccine dose. Intestinal sections adjacent to the Meckel‟s diverticulum, ileocecal junction, and middle of the ceca were collected for histological analysis and gene expression. Measurements from the tip of the villus to the base of the lamina propria, villus width, and the muscularis mucosae thickness were acquired from the histological sections. Interleukin-10, IL-1β,