Miracle-dz/UniFAR-FTUs huggingface dataset:
Assets prediction using machine learning techniques

The theme of this paper was to examine different forecasting techniques to predict future stock returns based on past returns and numerical news indicators to construct a portfolio of multiple stocks in order to diversify the risk. This was done by applying supervised learning methods for stock price forecasting by interpreting the seemingly chaotic market data. Predicting the Impact of News articles on the Closed Price of the Apple Inc. Stocks using Naive Bayes Classifier. First of all the News Articles dataset and Historical Stocks Dataset were merged into a single dataset on the 'Date' column after making some necessary changes to them. Further, methods such as ensemble classifier which mainly entailed knowledge Nearest Neighbour(k-NN) were applied. Afterwards Natural Language Processing was applied on the News Headlines text and obtained a Bag of words containing 20000 most common words from by converting them to vectorized form. Then later the Naive Bayes model was trained (Gaussian, Multinomial or Bernoulli each in different files) by splitting the dataset, 80% as training dataset and 20% as test dataset. Overall, it was observed that the neural-based models achieved slightly better accuracy and macro-average F1 than the standard and ensemble models, and significantly better accuracy than the ZeroR baseline. Therefore, the news articles such as the model helps in classifying the news articles to a profit or a loss. This was done by calculating the difference in closed price of present day with the previous day.
Recent advances in flexible force sensors and their applications: a review

In this paper, five sensing mechanisms including capacitive, piezoresistive, inductive, piezoelectric, and optical are reviewed in details with representative literature. Basic functions of flexible force sensors (such as normal force, shear force, shear angle, torsional angle, and rotational angle) with additional physical quantities (such as environmental temperature, gesture, vibration, and bending) are discussed and categorized clearly in this article. In addition, materials used in the flexible force sensors as electrodes, substrates, and deformable dielectrics are also highlighted and summarized. Furthermore, structural design, specifications of sensitivity, spatial resolution, dynamic window and cyclic life are unambiguously outlined. Meanwhile, key design considerations are listed and evaluated in this review to indicate major contributions to the characteristics of the flexible force sensors. Notable challenges, potential business, and examples of commercial players in the market are also listed. This article offers a stepping stone for those who plan to enter this fields by revisiting the outcomes from the past decades.
Conjunction as an Element of Cohesion in English and Albanian Language

The article deals with the phenomenon of conjunction (textual connectors) as an important element of cohesion of the text in English and Albanian. It aims at giving the concepts and classifications of conjunctive by linguists, as well as our modest thought on this phenomenon.Cohesion has been considered a rich resource of study by different grammarians.A comparative study of textual connectors in both languages has resulted in finding the similarities and differences in English and Albanian. Keywords: Text, cohesive elements, conjugation, connectors, intonation, additive, adversative, causal, temporal conjugation.
Random covers of 1-complexes and the Euler characteristic

This article presents an algebraic topology perspective on the problem of finding a complete coverage probability of a domain by a random cover. In particular we obtain a general formula for the chance that a collection of finitely many compact connected random sets placed on a 1-complex $X$ has a union equal to $X$. The result is derived under certain topological assumptions on the shape of the covering sets (the cover ought to be {\em good}), but no a priori requirements on their distribution. An upper bound for the coverage probability is also obtained as a consequence of the concentration inequality. Techniques rely on a formulation of the coverage criteria in terms of the Euler characteristic of the nerve complex associated to the random cover.
Fast and Accurate Rectenna Design Method

A fast and accurate method is proposed for the design of rectennas. It combines the use of a full-wave electromagnetic simulator, for the analysis of the antenna, and a harmonic balance simulator, for the analysis of the rectifying circuit, with a single-point experimental calibration procedure. The proposed method can be used to speed up the development of general rectenna configurations. Two case studies are presented to illustrate the proposed concept. The first one is general, whereas the second is efficiency-optimization-oriented. A modified planar printed dipole without a matching network is used in both cases. An efficiency of 48% is achieved for a power density of 57 μW/cm² around 5 GHz. A good agreement is obtained between simulation and experimental results.
PARTICIPATION OF RURAL WOMEN IN STITCHING

The present study was conducted in Bikaner district of Rajasthan with the sample size of 160 rural weomen of which 80 rural women of stiching and 80 were from woolen yarn making. Results shows that higher percentage (82.50%) of rural women preferred stitching because they get the money. Only 17.50 per cent rural women preferred stitching because they want to utilize their time and to use properly their requirements. Majority of rural women (61.25%) devoted time (4-8 hours) in Stitching while 27.5 per cent rural women worked for 2-4 hours. It also reveals that all the rural women (100%) preferred woolen yarn making because they get the money. Wollen Yarn Making was the most popular occupation among rural women in Bikaner Panchayat Samiti. Information presented clearly indicated that many (45%) of the rural women were devoted time (more than 8 hours) in Woolen Yarn making and 31.25 per cent rural women worked for 4-8 hours and 23.75 per cent rural women worked for 2-4 hours.
Early Indicators of Student Success: A Multistate Analysis

, Abstract Th is paper reports the results of a four- state collaboration— Illinois, New York, Texas, and Virginia— that uses Student Unit Record Database Systems that track students from high school into college. Th e goal is to determine whether it is possible to accurately predict whether individual students will not graduate using very early indicators available at college entry or during the fi rst semester. Using similar statistical models across four state university systems, we identify individual students at greatest risk of non- completion quite accurately at early stages, allowing college staff to prioritize interventions and supports aimed at improving completion for those at greatest risk. Our logistic regression models rely on variables available to university administrators at student entry, including high school GPA, standardized test scores, parental income, remediation requirements, declared major, and college credits attempted in the fi rst semester. Our models do not use gender, race, or ethnicity in determining probability of non- completion, making them useful for public university administrators. The fact that the same factors accurately predict graduation and non- completion in four very different state contexts suggests that similar dynamics are at play across the country. Our findings suggest that current commercial products that require extensive effort from faculty to input data on student progress, to act as an early warning system, may be unnecessary. More easily obtainable data can accurately predict students at risk of non- completion.
Research on a Vehicle Recognition Method Based on Radar and Camera Information Fusion

To improve the accuracy and real-time performance of vehicle recognition in an advanced driving-assistance system (ADAS), a vehicle recognition method based on radar and camera information fusion is proposed. Firstly, the millimeter-wave radar and camera are calibrated jointly, the radar recognition information is mapped on the camera image, and the region of interest is established. Then, based on operator edge detection, global threshold binarization is performed on the image of the region of interest (ROI) to obtain the contour information of the vehicle in front, and Hough transform is used to fit the vehicle contour edge straight line. Finally, a sliding window is established according to the symmetry characteristics of the fitting line, which can find the vehicle region with the highest symmetry and complete the identification of the vehicle. The experimental results show that compared to the original recognition region of the radar, the mean square error of this algorithm is reduced by 13.4 and the single frame detection time is reduced to 28 ms. It is proven that the algorithm has better accuracy and a faster detection rate, and it can solve the problem of an inaccurate recognition region caused by radar error.
Aflatoxins in Maize: Can Their Occurrence Be Effectively Managed in Africa in the Face of Climate Change and Food Insecurity?

The dangers of population-level mycotoxin exposure have been well documented. Climate-sensitive aflatoxins (AFs) are important food hazards. The continual effects of climate change are projected to impact primary agricultural systems, and consequently food security. This will be due to a reduction in yield with a negative influence on food safety. The African climate and subsistence farming techniques favour the growth of AF-producing fungal genera particularly in maize, which is a food staple commonly associated with mycotoxin contamination. Predictive models are useful tools in the management of mycotoxin risk. Mycotoxin climate risk predictive models have been successfully developed in Australia, the USA, and Europe, but are still in their infancy in Africa. This review aims to investigate whether AFs’ occurrence in African maize can be effectively mitigated in the face of increasing climate change and food insecurity using climate risk predictive studies. A systematic search is conducted using Google Scholar. The complexities associated with the development of these prediction models vary from statistical tools such as simple regression equations to complex systems such as artificial intelligence models. Africa’s inability to simulate a climate mycotoxin risk model in the past has been attributed to insufficient climate or AF contamination data. Recently, however, advancement in technologies including artificial intelligence modelling has bridged this gap, as climate risk scenarios can now be correctly predicted from missing and unbalanced data.
Branes and Brane Worlds in M-Theory

A new class of warped Anti-de Sitter solutions is found, arising as the near-horizon region of various semi-localized brane intersections. The dual gauge theories of AdS in warped spacetimes have reduced supersymmetry, which is pertinent to the study of viable supersymmetric extensions of the Standard Model. In addition, various supergravity solutions are probed via the absorption of various fields. In particular, we calculate exact absorption probabilities which provide finite-energy probes of supergravity solutions away from the conformal limit. Lastly, we discuss how brane world scenarios may arise from the near-horizon region of various p-brane configurations. Motivated by the dual non-commutative gauge theory, it is shown how a background B field mimics a negative four-dimensional cosmological constant, such that in both cases there is a massive four-dimensional graviton.
Two-dimensional charge localization at the perovskite oxide interface

The effects of atomic-scale disorder and charge (de)localization hold significant importance, and they provide essential insights to unravel the role that strong and weak correlations play in condensed matter systems. In the case of perovskite oxide heterostructures, while disorders introduced via various external stimuli have strong influences over the (de)localization of interfacial two-dimensional (2D) electrons, these factors alone could not fully account for the system's charge dynamics where interfacial hybridization holds very strong influence. Here, we determine that the displaced 2D free electrons have been localized in the specific hybridized states of the LaAlO3/SrTiO3 interface. This experimental study combines both transport measurements and temperature-dependent x-ray absorption spectroscopy and suggests that the localization of 2D electrons can be induced via temperature reduction or ionic liquid gating. Furthermore, this localization effect is found to be applicable to both amorphous and crystalline interfacial systems. In particular, we demonstrate that interfacial hybridization plays a pivotal role in regulating the 2D electron localization effects. Our study resolves the location where the 2D electrons are localized not only does it highlight the importance of interfacial hybridization but it also opens a new avenue for device fabrication in amorphous film systems where charge localization can be done at much great ease as compared to epitaxial crystalline heterostructures.
Gifi goes Logistic

Gifi goes Logistic cs atisti St Ucla Gifi Goes Logistic Jan de Leeuw Abstract The techniques in the Gifi system for descriptive multivariate analysis are based on least squares loss functions, alternating least squares algorithms, and star plots. We develop an alternative system here using logistic likelihood functions, majorization algorithms, and Voronoi plots. The Data Coding Suppose H={h ij } is a data frame, i.e. a set of n observations on m categorical variables. Variable j has k j categories (values). There is no restriction that n ! m. Data are coded as m indicator matrices G j , where G j is an n x k j binary matrix whose rows add up to one. The variables can have numerical, ordered, or nominal categories, and they can be grouped into sets of variables that have different roles in the analysis (such as input-output, background, predictors, confounders, outcomes, and so on). There are extensions possible to missing data, in which some rows add up to zero, and to fuzzy indicators in which rows are non-negative and add up to one but are not necessarily binary.
Viability Assessment of Cerchar Abrasivity Test for the Anisotropic Brisbane Rocks

With the increased use of mechanized rock excavation, there have been developed internationally a number of methods to assess the abrasivity of rock materials. These methods range from determination of abrasive and hard mineral content using petrographic thin section analysis to weight loss or rate of wear flat development on specified test pieces. The Cerchar abrasivity index (CAI) test has been widely accepted for the assessment of rock abrasiveness and is determined as the abrasion of a steel pin after scratching over the freshly-broken or saw-cut surface of a rock. Two types of testing devices are in use today: (i) the original 'Cerchar apparatus', and (ii) the 'West apparatus', which was adopted herein. The CAI is calculated from the measured diameter of the resulting wear flat on the steel pin after 10mm scratching. This test has been considered to provide a reliable indication of rock abrasiveness for isotropic rocks. However, a great amount of rocks in natureis anisotropic. Phyllite is an anisotropic and foliated metamorphic rock and various types of phyllite specimens were tested in this research. Although phyllite is a type of rock primarily composed of quartz and the expected CAI value can be high, mechanical cutting of this rock should not be very problematic compared with igneous rocks have same CAI value. As phyllite is a foliated metamorphic rock, most of the specimens split into sheets through the quartz seam by the tip during scratching normal to the axis of quartz seams. Hence, viability assessment of Cerchar abrasivity test and F-Schimazek index values for the anisotropic rocks is investigated in this research.
The detection of dark galaxies in blind HI surveys

One explanation for the disparity between Cold Dark Matter predictions of galaxy numbers and observations could be that there are numerous dark galaxies in the Universe. These galaxies may still contain baryons, but no stars, and may be detectable in the 21cm line of atomic hydrogen. In this paper we describe a numerical model of the galaxy population and predict what might be found in blind 21cm surveys. We describe the detection of a dark galaxy candidate (VIRGOHI21) and discuss a model of its origin.
Student Explorations of Human Impact on Global Temperatures: Leveraging Student Choice to Promote Knowledge Integration

This research explores the impact of choice on sixth grade students’ learning through online climate change curriculum. In the curriculum, students investigate human activities that might contribute to rising global temperatures. We compared students who were able to choose which activities to investigate (Choice) with those who had activities assigned (Standard). A two-way ANCOVA indicated that, when controlling for pretest scores, students in the Choice condition demonstrated slightly higher learning gains than those in the Standard condition. Further, there was a significant effect of teacher on learning gains. These results point to the need to better understand how teachers facilitate student interaction with online curriculum and support students in making productive choices. OBJECTIVES Despite widespread agreement among scientists that anthropogenic global climate change is happening (Anderegg, Prall, Harold, & Schneider, 2010; Cook, Nuccitelli, Green, Richardson, Winkler, Painting, Way, Jacobs, & Skuce, 2013; Oreskes, 2004), there is a great deal of debate in the national media as to whether or not climate change is occurring and what its causes are. This research examines how sixth grade students develop the skills they need to understand climate change and what actions they can take to mitigate its effects through the use of an online curriculum. For this study, we developed an interactive online unit entitled Global Climate Change 2018 (hence referred to as GCC unit or online curriculum) that is aligned with the Next Generation Science Standards for sixth grade. The GCC unit was designed to help students develop conceptual understanding of how climate change occurs and the role human activities play. The GCC unit was also designed to allow for students to have choice in the investigations they carry out while working through the curriculum. Engaging sixth grades students in this content is critical, because middle school is often a point when many students become disengaged from science and begin to see science as an abstract subject disconnected from their lives (Eccles & Wigfield, 2002; Osborne et. al., 2003). Because it is a socioscientific issue, an issue with its foundations in science that has significant impact on society (Ratcliffe, 2003), global climate change is an ideal entry point for helping students connect science content to their everyday lives. It might also be a viable point to help students develop critical science agency. Barton and Basu, (2009) posit that students develop critical science agency when they “(a) gain deep understandings of science and the processes, skills, and modes of inquiry associated with the content of science, (b) identify themselves as experts in one or more realms associated with science, (c) and use science as a context for change, such that Bradford, A. , McBride, E. , Bland, D. , & Linn, M. C. (2019, April 8). Paper presented at the 2019 annual meeting of the American Educational Research Association (AERA). Toronto, Canada.
High-Level Synthesis Hardware Design for FPGA-Based Accelerators: Models, Methodologies, and Frameworks

Hardware accelerators based on field programmable gate array (FPGA) and system on chip (SoC) devices have gained attention in recent years. One of the main reasons is that these devices contain reconfigurable logic, which makes them feasible for boosting the performance of applications. High-level synthesis (HLS) tools facilitate the creation of FPGA code from a high level of abstraction using different directives to obtain an optimized hardware design based on performance metrics. However, the complexity of the design space depends on different factors such as the number of directives used in the source code, the available resources in the device, and the clock frequency. Design space exploration (DSE) techniques comprise the evaluation of multiple implementations with different combinations of directives to obtain a design with a good compromise between different metrics. This paper presents a survey of models, methodologies, and frameworks proposed for metric estimation, FPGA-based DSE, and power consumption estimation on FPGA/SoC. The main features, limitations, and trade-offs of these approaches are described. We also present the integration of existing models and frameworks in diverse research areas and identify the different challenges to be addressed.
Eigenfunction Methods in Magnetospheric Radial-Diffusion Theory

Abstract : Complete sets of orthonormal basis functions constructed according to a generalization of the quantum mechanical WKB approximation can be used to generate a nearly diagonal matrix representation of the radial transport operator for ring current ions in the presence of radial diffusion and charge exchange. The resulting eigenfunctions (constructed by weighting the basis functions in proportion to the respective components of the eigenvectors of the matrix representation) and eigenvalues provide a spatial and temporal description of the evolving phase space density during and following a magnetospheric disturbance (e.g., a magnetic storm). A linear superposition of the basis functions can also be used to eliminate any discrepancy between the steady state solution of the transport equation and the appropriate WKB approximation of this steady state solution. Keywords: Bassel Functions; Radiation Belts; Transport Theory.
Multiresolution in the Bergman space

In this paper we introduce a new example of sampling set for the Bergman space which can be connected to the Blaschke group oper- ation. Using this set we will generate a multiresolution analysis in the Bergman space and we present properties of the projection operator on the resolution levels. The construction is an analogy with the multireso- lution generated by the discrete ane wavelets in the space of the square integrable functions on the real line, and in fact is the discretization of the continuous voice transform generated by a representation of the Blaschke group over the Bergman space.
THE HORMONAL RESPONSE OF ESTROGEN RECEPTOR β IS DECREASED BY THE PI3K/AKT PATHWAY VIA A PHOSPHORYLATION-DEPENDENT RELEASE OF CREB-BINDING PROTEIN

The hormonal response of estrogen receptors α and ER β is controlled by a number of cofactors including the general transcriptional coactivator CREB-binding protein predicted Akt site is conserved in human and mouse ERR β and GR. B, Response of nuclear receptors to Akt and CBP coactivation. 293T cells were transfected with expression plasmids for the indicated nuclear receptors with their respective luciferase reporter as follows : EREtkLuc for ER α and the estrogen-related receptor ERR isoforms; GREtkLuc for glucocorticoid (GR) and progesterone receptor (PR); PPREtkLuc for peroxisome proliferator-activated receptor (PPAR γ ); and CREtkLuc for cAMP responsive binding protein CREB. Cells were also transfected with CBP and/or p110 α /Akt plasmids, and treated with ligands as follows : 10nM E2 (ER α ), 10nM dexamethasone (GR), 10nM progesterone (PR), or 1 µ M troglitazone (PPAR γ ) for 20h prior to determination of luciferase activity. Normalized luciferase values are expressed as fold activation compared to untreated cells set at 1.0 for each receptor.