Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentiment Analysis Approach based N-gram and KNN Classifier

The sentiment analysis is the approach which is design to analysis positive, negative and neural aspects towards any approach. In the past years, many techniques are designed for the sentiment analysis of twitter data. Based on the previous study about sentiment analysis, novel approach is presented in this research paper for the sentiment analysis of twitter data. The proposed approach is the combination of feature extraction and classification techniques. The N-gram algorithm is applied for the feature extraction and KNN classifier is applied to classify input data into positive, negative and neural classes. To validate the proposed system, performance is analyzed in terms of precision, recall and accuracy. The experiments results of proposed system show that it performs well as compared to existing system which is based on SVM classifier.
Online and offline integration in marketing communication. Delving into the business perspective

Literature about Integrated Marketing Communication (IMC) is still evolving, but lacks a systematic focus on online and offline integration approaches. This research aims to identify the key managerial issues related to online and offline integration within IMC and explore the existence of clusters of firms with consistent conducts and results. We carried out a survey with 124 large firms operating in Italy, running first exploratory factor analyses and then a non-hierarchical cluster analysis. The former highlight the nature of the implementation modalities of online and offline integration in IMC, the main types of advantages, and the different categories of barriers to such implementation. The latter results in two clusters of firms. Academic and managerial implications are presented along with future research directions.
Proof of Principle for Electronic Collimation of a Gamma Ray Detector

Abstract : This note describes the initial development of an electronic collimation technique that uses the characteristics of the detector waveforms to infer the directionality of gamma rays. This note documents some of the key points in achieving the proof of principle of the technique, which is intended to be further developed. A gamma ray detector system utilizing electronic collimation should be far more portable and/or deployable than previous systems using conventional collimation with heavy shielding materials.
Tax Policy and Human Capital Formation with Public Investment in Education

This paper studies the effects of distortionary taxes and public investment in an endogenous growth OLG model with knowledge transmission. Fiscal policy affects growth in two respects: first, work time reacts to variations of prospective tax rates and modifies knowledge formation; second, public spending enhances labour efficiency but also stimulates physical capital through increased savings. It is shown that Ramsey-optimal policies reduce savings due to high tax rates on young generations, and are not necessarily growth-improving with respect to a pure private system. Non-Ramsey policies that shift the burden on adults are always growth-improving due to crowding-in effects: the welfare of all generations is unambiguously higher with respect to a private system, and there generally exists a continuum of non-optimal tax rates under which long-run growth and welfare are higher than with the Ramsey-optimal policy.
PYRROLOQUINOLINE QUINONE HAS THE POTENTIAL TO AMELIORATE PTU INDUCED LIPID PEROXIDATION AND OXIDATIVE DAMAGES IN MICE

Objective: This investigation was aimed to examine the hitherto unknown potential of pyrroloquinoline quinone (PQQ) in ameliorating propylthiouracil (PTU) induced lipid peroxidation and in oxidative damages of the different tissues including muscle, testis and brain of adult mice. Methods: Out of 5 groups of animals 4 groups received PTU (0.05% in drinking water) for 35 days and were rendered hypothyroidic. While group one, receiving normal drinking water served as control, group III, IV and V were treated with 1, 5 and 10 mg/ Kg of PQQ respectively for last 6 days along with PTU, after which alterations in tissue lipid peroxidation (LPO) and in enzymatic activities of superoxide dismutase (SOD) and catalase (CAT) and in glutathione (GSH) content were evaluated in different organs such as muscle, testis and brain. Simultaneously, concentrations of serum glucose, total cholesterol, serum glutamate oxaloacetate transaminase (SGOT), creatinine and urea were measured. Results: PTU administration enhanced the tissue LPO, serum SGOT, total cholesterol, creatinine and urea with a parallel decrease in serum glucose and tissue antioxidants. When PTU treated animals also received different amounts of PQQ, these adverse effects were ameliorated. However, PQQ at 10 mg/kg was found to be the most effective concentration, as it reduced the tissue LPO, with a parallel increase in cellular antioxidants in a better way.
Delegating Powers in the European Community

The theory of delegation developed by Epstein and O'Halloran for the US federal system is used here to generate original hypotheses on the politics of delegation in the European Community (EC). It is argued that two institutional features of the Community, namely the decision rules of the Council of Ministers and the possibility of relying on both the Commission and the member states for policy implementation are at the core of the choices of delegation of EC legislators. Using an original dataset of 158 major EC legislative acts, it is demonstrated that the Council delegates greater policy authority to national institutions if legislation is adopted unanimously or in issue areas that require specialized and technical knowledge, while it relies to a greater extent on the Commission when acts are adopted by qualified majority voting or require general managerial skills at the supranational level. Results also show that national administrators are the main providers of policy expertise, while the informational role of the Commission appears to be secondary, though not negligible. Finally, these findings qualify propositions on the relation between veto players and bureaucratic autonomy and on that between conflict within the legislature and delegation outcomes.
Career Needs of R & D Personnel during the ‘ Maintenance ’ Stage : A Exploration Study and a New Scale

This is a study comprising of two parts with the major feature of this part being the exploration of career needs and describe the development of a 9-item instrument (called Career Need Scale, CNS) for assessing R&D personnel perceptions of career needs. After a discussion of the conceptualization of career needs, the operationalization of the career needs construct and a multiple-item scale to measure the construct are described. We outlines the development of a new scale for maintenance stage R&D personnel career needs, and a total of 960 Taiwan high-tech R&D personnel were used for development and evaluation of the scale. Reliability, factor structure, and construct validity, discriminant validity, and convergent validity were all evaluated. The potential applications of the scale are also discussed.
Latitudinal decrease in folivory within Nothofagus pumilio forests: dual effect of climate on insect density and leaf traits?

Aim The strength of consumer–plant interactions may decrease with latitude. Our objectives were to assess the spatial variation in folivory on Nothofagus pumilio and understand the influence of climate on folivory patterns as mediated by changes in folivore density and leaf traits. Location Nothofagus pumilio forests, between 38 and 55°S (Argentina). Methods We studied the correlation of leaf damage with latitude on data from 47 sampling sites, and evaluated spatial patterns of autocorrelation on latitudinally detrended data with a principal coordinates of neighbour matrices method. Path analysis was used to test the association of temperature and precipitation with leaf damage, mediated by folivore density and leaf traits. We evaluated the adequacy of this ecological model by examining the spatial pattern of autocorrelation in the residuals, and combined spatial and environmental predictors of leaf damage into partial regression. Results Leaf damage decreased with latitude, which was the only significant spatial predictor. The latitudinal decrease in temperature and precipitation was correlated with a decrease in the density of folivores and leaf size, and diminished leaf damage. Our ecological model adequately explained the spatial autocorrelation in the data: 44% of the variation in leaf damage was explained by the latitudinally structured component of the environment, whereas local environmental effects accounted for another 22%. Main conclusions We conclude that N. pumilio forests show consistent latitudinal patterns of variation in folivory, folivore density and leaf traits. Our study suggests that the latitudinal variation in folivory rates is partly driven by the influence of climate on both plants and herbivores. This warns us about the potential susceptibility of folivory rates to climate warming. We emphasize the value of large-scale analyses as complementary to local experimental approaches to understanding the regulation of herbivory.
Multi-User Searchable Symmetric Encryption with Dynamic Updates for Cloud Computing

With the advent of cloud computing, more and more users begin to outsource encrypted files to cloud servers to provide convenient access and obtain security guarantees. Searchable encryption (SE) allows a user to search the encrypted files without leaking information related to the contents of the files. Searchable symmetric encryption (SSE) is an important branch of SE. Most of the existing SSE schemes considered single-user settings, which cannot meet the requirements for data sharing. In this work, we propose a multi-user searchable symmetric encryption scheme with dynamic updates. This scheme is applicable to the usage scenario where one data owner encrypts sensitive files and shares them among multiple users, and it allows secure and efficient searches/updates. We use key distribution and re-encryption to achieve multi-user access while avoiding a series of issues caused by key sharing. Our scheme is constructed based on the index structure where a bit matrix is combined with two static hash tables, pseudorandom functions and hash functions. Our scheme is proven secure in the random oracle model.
Visualization of meiotic events in intact living anthers by means of two-photon microscopy

In this paper we describe the application of two-photon microscopy (2PM) to the study of meiosis in plants. Fresh, un®xed anthers of Agapanthus umbelatus were brie ̄y incubated on a minimal medium containing the DNA ̄uorophore DAPI. DAPI incorporation took place in about 30 min and nuclei and other DNA-containing organelles kept their ̄uorescence for more than 24 h. Using 2PM it was possible to optically section the whole, un®xed anthers to a depth of approximately 200 mm. This was up to the mid sagital section and into the sporogenic tissue. Several meiotic ®gures were observed with unparalleled resolution. Sequences of nuclear dynamics and division were occasionally observed in the surrounding tissues and epidermal layer of cells. However we could not optimize the procedures up to the level of observing the dynamics of division on the meiotic nuclei as well. We hypothesize that either (1) meiotic cells are sensitive to the reasonably high excitation levels of infrared light needed to attain such penetration in the tissue, or (2) that our incubation procedures are not suf®ciently non-invasive for meiosis to remain unperturbed. To the best of our knowledge this is the ®rst report on direct observation of living meiotic cells in plants and establishes the potential of 2PM for intact organ research. q 2001 Elsevier Science Ltd. All rights reserved.
Entanglement Evolution of Noisy Teleportation

We generalize the teleportation protocol of Bennet et al. to a noisy quantum teleportation protocol (NTP) in which noise factors are corresponded to noisy channels, imperfect measurement and non-maximally entangled channel (isotropic channel). Evolution of entanglement between every two parts of three-partite density matrix changing through five steps of NTP is considered employing concurrence and negativity measures. Then results of concurrence and negativity are evaluated and compared by mutual information as a criterion of correlation. We illustrate the necessity of entanglement in the middle steps of NTP.
The Role of University Students’ General Self-Efficacy, Depression and Psychological Well-being in Predicting Their Exercise Behavior

The aim of this research is to examine the relationship between exercise and general self-efficacy, depression, and psychological well-being of college students. Five hundred and twenty-two university students ( n male= 273; X age = 23.33±4.36 and n female = 279; X age =25.91±7.11 ) have participated in this research. The General Self-Efficacy Scale (GSES), Beck Depression Inventory (BDI), Physical Activity Stages of Change Questionnaire (PASCQ), and “Psychological Well-Being Scale (PWBS) have been applied to the sample group in this study. While differences in participants’ self-efficacy, depression, and psychological well-being levels with regard to the stage of changes in exercise are calculated with one way analysis of variance (ANOVA), the relationship between these ideas discussed in the research have been determined with Pearson Moments Product Correlation Analysis. According to the stages of exercise behavior, significant disparities have been found between participants’ level of self-efficacy, depression, and psychological well-being, and the relationship between those notions has been observed. According to the results, the participants’ general self-efficacy and psychological well-being levels were high and the depression levels were low when on advanced levels of exercise. In light of the findings obtained from this research, it has been concluded that continuity in exercise has a positive effect on psychological effects like general self-efficacy, depression and psychological well-being.
Volatility Models and their Performance in Indian Capital Markets

Estimation and forecasting of volatility of asset returns is important in various applications related to financial markets such as valuation of derivatives, risk management, etc. Till early eighties, it was commonly assumed that the volatility of an asset is constant and estimation procedures were based on this assumption even though some of the pioneering studies on property of stock market returns did not support this assumption. Following the pioneering work of Engle and Bollerslev in eighties on developing models (ARCH/GARCH type models) to capture time-varying characteristics of volatility and other stock return properties, extensive research has been done world over in modeling volatility for estimation and forecasting. There are broadly four possible approaches for estimating and forecasting volatility. These are: Traditional Volatility Estimators — These estimators assume that ‘true’ volatility is unconditional and constant. The estimation is based on either squared returns or standard deviation of returns over a period. Extreme Value Volatility Estimators — These estimators are similar to traditional estimators except that these also incorporate high and low prices observed unlike traditional estimators which are based on closing prices of the asset. Conditional Volatility Models — These models (ARCH/GARCH type models) take into account the time-varying nature of volatility. There have been quite a few extensions of the basic conditional volatility models to incorporate ‘observed’ characteristics of asset/stock returns. Implied Volatility — In case of options, most of the parameters relevant for their valuation can be directly observed or estimated, except volatility. Volatility is, therefore, backed out from the observed option values and is used as volatility forecast. The empirical research across countries and markets has not been equivocal about the effectiveness of using these approaches. This study compares the result of the first three approaches in estimating and forecasting Nifty returns. Based on four different criteria related to bias and efficiency of the various estimators and models, this study analysed the estimation and forecasting ability of three different traditional estimators, four extreme value estimators, and two conditional volatility models. As a benchmark, it used ‘realized’ volatility estimates. The findings of this study are as follows: For estimating the volatility, the extreme value estimators perform better on efficiency criteria that the conditional volatility models. In terms of bias, conditional volatility models perform better than the extreme value estimators. As far as predictive power is concerned, extreme value estimators estimated from sample of length equal to forecast period perform better than the conditional volatility estimators in providing five-day and month ahead volatility forecasts.
Time-lapse wave-equation migration velocity analysis

Summary Time-lapse analysis of seismic data acquired at different stages of hydrocarbon production or fluid/gas injection has been very successful at capturing detailed reservoir changes (e.g., pressure, saturation, fluid flow). Conventional 4D analysis is performed in the time domain assuming a constant baseline model; however, this procedure becomes difficult when the subsurface is significantly altered by production/injection and large time anomalies and complex 4D coda are recorded. We argue that a more robust 4D analysis procedure in these situations requires iterative wave-equation depth imaging and time-lapse velocity analysis. Wave-equation depth migration requires accurate knowledge of the velocity field usually obtained by one of two ways. First, data-space methods are where recorded data are matched to those calculated through a background velocity model. Differences between the two datasets are used in tomographic backprojections to generate velocity model updates. Alternatively, imagespace methods are where discrepancies between migrated images (non-flat gathers) are backprojected to estimate velocity model updates. These types of approaches are termed migration velocity analysis (MVA). This abstract focuses on extending 3D wave-equation MVA (WEMVA) approaches to time-lapse velocity analysis. We discuss the differences between 3D and 4D WEMVA inversion goals, and how we leverage the locality of 4D image perturbations to provide highresolution velocity model updates. We demonstrate the utility of 4D WEMVA analysis in a synthetic CO2 geosequestration experiment by successfully inverting for a velocity perturbation corresponding to a thin layer (<20m) of injected CO2 in a typical North Sea reservoir.
Using Sieving and Unknown Sand Samples for a Sedimentation-Stratigraphy Class Project With Linkage to Introductory Courses

ABSTRACT Using sieving and sample “unknowns” for instructional grain-size analysis and interpretation of sands in undergraduate sedimentology courses has advantages over other techniques. Students (1) learn to calculate and use statistics; (2) visually observe differences in the grain-size fractions, thereby developing a sense of specific size ranges, weight percentages being plotted, and how grain composition and properties are a function of size; (3) are enthusiastic and observant as they search for clues of the origin of their sample, but discover that determining depositional environments using grain-size analysis is not the hoped for “fingerprinting” technique; and (4) enjoy learning the geographic origin and depositional environment of their sample. Plus, sieving equipment generally is less costly to acquire and maintain than “black box” techniques, and sieving is a commonly used procedure in industry. Using unknown sand samples results in some students making “incorrect” interpretations, which allows for illustrating that a scientist may have an excellent data set and a valid interpretation based on that data but, although the data are sound, the interpretation may be erroneous. Moreover, using a suite of unknowns allows students in a class to collectively be exposed to sands from a range of environments and geographic locales without the need for local sediment-rich environments. Building a set of unknowns is aided by recruiting students in introductory geology courses to collect and document samples during their school-break travels for future “unknowns,” thereby linking courses and creating interest among nonmajors. When these students venture into the field to collect a sample and characterize the environment, they are enticed into thinking about sedimentary processes and possible anthropogenic effects, such as beach nourishment, while on break.
Systematic study of the α-optical potential via elastic scattering near the Z=50 region for p-process nuclei

Production of proton-rich nuclei beyond iron in stars proceeds via the p process, i.e., a sequence of photodisintegration reactions, (γ ,n), (γ ,p), and (γ ,α) on heavy nuclei at temperatures of 2–3 × 109 K. The involved reaction rates are typically calculated with the statistical Hauser-Feshbach (HF) model. However, the HF model performs poorly in calculating the critical (γ ,α) rates due to the uncertainty of the alpha optical potentials applied. To test the reliability of the HF calculations and provide a systematic understanding of the α optical potential at energies of astrophysical interest, a series of precision α scattering measurements were carried out at the Notre Dame FN Tandem Accelerator. Specifically, 106Cd, 118Sn, and 120,124,126,128,130Te were studied at energies both below and above the Coulomb barrier. A new parametrization of the α optical potential was derived of the elastic scattering cross section data. The derived potential was applied for calculating the α-induced reaction cross sections on these nuclei using the HF approach. The results were compared to the corresponding experimental values obtained from previous activation measurements on Cd, Sn, and Te isotopes.
Machine Learning Enhanced Real-Time Intrusion Detection Using Timing Information

Past work has investigated intrusion detection mechanisms for real-time control devices. This work contributes a novel framework of separating security monitoring and detection from real-time control, where the former is performed on Cloud edge devices while the latter is run on embedded devices attached to the system that is controlled. We contribute a security monitoring system that validates worst-case timing bounds of the target controller and also validates its control outputs by comparing it against model-based predictions, which are derived from machine learning.