Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting academic performance and attrition in undergraduate students

El proposito de este estudio es analizar si las aptitudes educativas pueden predecir el rendimiento academico y la desercion. Para medir las aptitudes educativas se aplico el Test de Aptitudes Diferenciales (Differential Aptitude Test – DAT) a una muestra no probabilistica de 1530 estudiantes de primer ano de grado de una universidad privada de la Argentina. Para el analisis se utilizaron modelos de regresion multiple y logistica. Los resultados muestran que el DAT puede predecir el rendimiento academico, mientras que la relacion entre el DAT y la desercion es de moderada a baja. Este estudio es un primer paso para predecir el exito academico de los estudiantes, con el objetivo de ahorrar recursos y evitar la frustracion
Correlation Between Intraocular Pressure (IOP) and Intracranial Pressure (ICP) in Dog

Abstract Mehdizadeh, M. , Mosallaei, M. , Alibai, E.A. , Razeghinejad, M.R. , Sheikhi, A.R. , Alirezaee, M. , Tanideh, N. and Mehrabani, D. 2010. Correlation between intraocular pressure (IOP) and intracranial pressure (ICP) in Dog. J. Appl. Anim. Res., 38: 61–64. To evaluate correlation between intraocular pressure (IOP) and intracranial pressure (ICP) 15 mature dogs were divided into three equal groups. Under general anesthesia, the IOP and ICP were determined. Group 1 received timolol, group 2 latanoprost and group 3 underwent trabeculotomy in a single eye. After 2 and 4 weeks, the IOP and ICP were measured again. Before any drug administrations or surgery, the correlation between primary IOP and primary ICP was not significant (P>0.05) but after 2 and 4 weeks, there was a considerable negative linear correlation between these two measures (r=—0.595; P=0.01) and (r=- 0.570; P=0.02), respectively. There was a negative linear correlation between IOP and ICP (r=-0.67; P=0.001) when the multiple regression formula was applied to make a model.
Contention-Aware Scheduling of Parallel Code for Heterogeneous Systems

A typical consumer desktop computer has a multi-core CPU with at least two and up to eight processing elements over two processors, and a multi-core GPU with up to 512 processing elements. Both the CPU and the GPU are capable of running parallel code, yet it is not obvious when to utilize one processor or the other because of workload considerations and, as importantly, contention on each device. This paper demonstrates a method for dynamically deciding whether to run a given parallel workload on the CPU or the GPU depending on the state of the system when the code is launched. To achieve this, we tested a selection of parallel OpenCL code on a multi-core CPU and a multi-core GPU, as part of a larger program that runs on the CPU. When the parallel code is launched, the runtime makes a dynamic decision about which processor to run the code on, given system state and historical data. We demonstrate a method for using meta-data available to the runtime and historical data from code profiling to make the dynamic decision. We outline the runtime information necessary for making effective dynamic decisions, and suggest hardware, operating system, and driver support.
MDR 1 Gene Polymorphisms : Possible Association with its Expression and Clinicopathology Characteristics in Colorectal Cancer Patients

Although chemotherapy is one of the most effective ways of cancer treatment resistance to chemotherapy drugs evolved in many cancers is a major obstacle in cancer therapy (Gregory et al., 2003; Martin, 2004; Luqmani, 2005; Isabel et al., 2007). Multi drug resistance (MDR) is a phenomenon in which cancerous cells become resistant to wide range of structurally and functionally different drugs (Darinka et al., 2008). Colorectal cancer (CRC) is the fourth cause of the overall cancer mortality by 655,000 deaths yearly in the world. A chemo-resistant form of tumor and MDR-based mechanisms has been suspected to participate in the general unresponsiveness of colorectal tumors to drugs (Linn and Giaccone, 1995). ATP Binding Cassette (ABC) transporters super-family is a class of trans-membrane proteins that increase the ability of tumor cells to transport drugs out of the cells by using ATP molecule (Longley and Johnston, 2005). These transporters are one of the best known mechanisms responsible for MDR phenotype (Childs and Ling, 1994). The multi drug resistance (MDR1) gene belongs to the ABC gene family and encodes a 170Kd glycoprotein (van der Deen et al., 2005). This protein has been reported to correlate with the degree of drug resistance in several cell lines (Yukihiko, 2001). In some studies the over-
You ’ re Gonna Die : Diet Edition

What you consume can kill you, or at least have an effect on how long and well you live. In this paper we put aside other attributes that have an effect on your lifespan and focus on diet. We created and will describe a form-based graphical visualization that allows a user to enter his traits and dietary habits to have an estimate generated for the time left to live and the quantity of time each diet attribute has on lessening this number.
Overview of Recent Progress in Lightning Research and Lightning Protection

This review paper, prepared for this second special issue on lightning of the IEEE Transactions on Electromagnetic Compatibility, summarizes major publications on lightning and lightning protection since the first special issue published in November 1998, i.e., during the last decade. The review is organized in the following five sections: lightning discharge-observations, lightning discharge-modeling, lightning occurrence characteristics/lightning locating systems, lightning electromagnetic pulse and lightning-induced effects, and protection against lightning-induced effects.
Links Between Adolescents’ Relationships With Peers, Parents, and Their Values in Three Cultural Contexts

The study examined associations among adolescents’ perceived mother-child and father-child relationship quality (intimacy, conflict, and admiration), perceived peer acceptance, and their values (individualism and collectivism) in a sample of 795 Estonian, German, and Russian 15-year-olds. Adolescents from the three cultural contexts differed in terms of their relationships with parents and peers but were similar in valuing both individualism and collectivism highly. Individualistic values were positively linked to adolescents’ peer acceptance in individualistic cultures, whereas collectivistic values of adolescents were positively associated with the quality of their relationships with parents in all cultures. Across cultures, maternal and paternal admiration showed the strongest positive association with peer acceptance of adolescents. Among Estonian adolescents, further associations emerged: higher levels of intimacy with fathers and conflict levels in both mother-child and father-child relationship were related to adolescents’ lower peer acceptance. The results are discussed from a social-cultural perspective.
A Random Walk–Based Model for Identifying Semantic Orientation

Automatically identifying the sentiment polarity of words is a very important task that has been used as the essential building block of many natural language processing systems such as text classification, text filtering, product review analysis, survey response analysis, and on-line discussion mining. We propose a method for identifying the sentiment polarity of words that applies a Markov random walk model to a large word relatedness graph, and produces a polarity estimate for any given word. The model can accurately and quickly assign a polarity sign and magnitude to any word. It can be used both in a semi-supervised setting where a training set of labeled words is used, and in a weakly supervised setting where only a handful of seed words is used to define the two polarity classes. The method is experimentally tested using a gold standard set of positive and negative words from the General Inquirer lexicon. We also show how our method can be used for three-way classification which identifies neutral words in addition to positive and negative words. Our experiments show that the proposed method outperforms the state-of-the-art methods in the semi-supervised setting and is comparable to the best reported values in the weakly supervised setting. In addition, the proposed method is faster and does not need a large corpus. We also present extensions of our methods for identifying the polarity of foreign words and out-of-vocabulary words.
Channel Coding Diversity with Mismatched Decoding Metrics

We analyze the performance of channel coding diversity with general decoding metrics in terms of the generalized mutual information (GMI). We show that the GMI of the diversity channel is less than or equal to the baud-rate weighted sum of the component GMIs; and equality is achieved only in special cases. We then focus on bit-interleaved coded modulation (BICM) schemes and demonstrate the applicability of our findings by an example of hybrid free-space optical and radio-frequency (FSO-RF) communication.
Class Imbalance and Active Learning

The rich history of predictive modeling has culminated in a diverse set of techniques capable of making accurate predictions on many real-world problems. Many of these techniques demand training, whereby a set of instances with ground-truth labels (values of a dependent variable) are observed by a model-building process that attempts to capture, at least in part, the relationship between the features of the instances and their labels. The resultant model can be applied to instances for which the label is not known, to estimate or predict the labels. These predictions depend not only on the functional structure of the model itself, but on the particular data with which the model was trained. The accuracy of the predicted labels depends highly on the model’s ability to capture an unbiased and sufficient understanding of the characteristics of different classes; in problems where the prevalence of classes is imbalanced, it is necessary to prevent the resultant model from being skewed towards the majority class and to ensure that the model is capable of reflecting the true nature of the minority class. Another consequence of class imbalance is observed in domains where the ground truth labels in the dataset are not available beforehand and need to be gathered ondemand at some cost. The costs associated with collecting labels may be due to human labor or as a result of costly incentives, interventions or experiments. In these settings, simply labeling all available instances may not be practicable, due to budgetary constraints or simply a strong desire to be cost efficient. In a similar fashion to predictive modeling with imbalanced classes, the goal here is to ensure that the budget is not predominantly expended on getting the labels of the majority class instances, and to make sure that the set of instances to be labeled have comparable number of minority class instances as well. In the context of learning from imbalanced datasets, the role of active learning can be viewed from two different perspectives. The first perspective considers the case where the labels for all the examples in a reasonably large, imbalanced dataset are readily available. The role of active learning in this case is to reduce, and potentially eliminate, any adverse effects that the class imbalance can have on the model’s generalization performance. The other perspective addresses the setting where we have prior knowledge that the dataset is imbalanced, and we would like to employ active
Investigating the X-ray counterparts to unidentified sources in the 1000-orbit INTEGRAL/IBIS catalogue

The latest INTEGRAL/IBIS all-sky survey lists 219 hard X-ray sources whose nature is still unknown. We report on our ongoing campaign aimed at identifying these high-energy emitters by exploiting the focusing capabilities of the X-ray Telescope (XRT, 0.2-10 keV) on board Swift, which allow an enhancement of the source localisation to arcsec level, thus facilitating the identification of the likely counterpart. By cross-correlating the list of the unidentified IBIS sources included in the latest IBIS catalogue with Swift/XRT archival data, we found a set of 14 objects, not yet reported in the literature, for which XRT data were available. We found no detection in only one case, a single X-ray association in 9 sources, and 2/3 associations in the remaining objects. We then made use of multi-waveband archives to search for counterparts at other wavelengths of these XRT detections and exploited X-ray spectral information in an attempt to determine their nature and association with the IBIS object. As a result of our analysis, we identified a single counterpart for 13 sources, although in some cases its nature/class could not be assessed on the basis of the information collected. More specifically, we found that SWIFT J0924.2-3141 and SWIFT J1839.1-5717 are absorbed AGN, while SWIFT J0800.7-4309 and 1SWXRT J230642.8+550817 are Cataclysmic Variable binary systems. Finally, we found that IGR J14059-6116 is likely associated with the Fermi source 3FGL J1405.4-6119. In the case of XMMSL1 J030715.5-545536 no XRT counterpart was detected. In all the other cases, optical/infrared spectroscopy is necessary to classify properly each X-ray counterpart and confirm their association with the INTEGRAL/IBIS detection.
Robust passivity analysis and design for chemical processes

In this paper, a new approach is developed for robust control of nonlinear chemical processes. The methodology proposed is based on passivity theory. Uncertainty and perturbations are taken into account in the stability analysis and controller synthesis such that the resulting closed-loop system can achieve better robustness and performance. The suggested passivity framework can deal with a large class of uncertainties and perturbations in chemical processes.
Effects of gonadotropin-releasing hormone agonist on brain development and aging : results from two animal models

∗ Corresponding author. Tel. : +47 92011533; fax: +47 23074920. E-mail address: i.h. haraldsen@medisin.uio. no (I.R.H. Haraldsen). 166-4328/$ – see front matter © 2012 Elsevier B.V. All rights reserved. ttp://dx.doi. org/10.1016/j.bbr. 2012.12. 027 © 2012 Elsevier B.V. All rights reserved.
High Speed Reconfigurable FFT Design by Vedic Mathematics

The Fast Fourier Transform (FFT) is a computationally intensive digital signal processing (DSP) function widely used in applications such as imaging, software-defined radio, wireless communication, instrumentation. In this paper, a reconfigurable FFT design using Vedic multiplier with high speed and small area is presented. Urdhava Triyakbhyam algorithm of ancient Indian Vedic Mathematics is utilized to improve its efficiency. In the proposed architecture, the 4x4 bit multiplication operation is fragmented reconfigurable FFT modules. The 4x4 multiplication modules are implemented using small 2x2bit multipliers. Reconfigurability at run time is provided for attaining power saving. The reconfigurable FFT has been designed, optimized and implemented on an FPGA based system. This reconfigurable FFT is having the high speed and small area as compared to the conventional FFT.
Query-Based Evolutionary Graph Cuboid Outlier Detection

Graph-OLAP is an online analytical framework which allows us to obtain various projections of a graph, each of which helps us view the graph along multiple dimensions and multiple levels. Given a series of snapshots of a temporal heterogeneous graph, we aim to find interesting projections of the graph which have anomalous evolutionary behavior. Detecting anomalous projections in a series of such snapshots can be helpful for an analyst to understand the regions of interest from the temporal graph. Identifying such semantically related regions in the graph allows the analyst to derive insights from temporal graphs which enables her in making decisions. While most of the work on temporal outlier detection is performed on nodes, subgraphs and communities, we are the first to propose detection of evolutionary graph cuboid outliers. Further, we perform this detection in a query sensitive manner. Thus, an evolutionary graph cuboid outlier is a projection (or cuboid) of a snapshot of the temporal graph such that it contains an unexpected number of matches for the query with respect to other cuboids both in the same snapshot as well as in the other snapshots. Identifying such outliers is challenging because (1) the number of cuboids per snapshot could be large, and (2) number of snapshots could itself be large. We model the problem by predicting the outlier score for each cuboid in each snapshot. We propose to build subspace ensemble regression models to learn (a) the behavior of a cuboid across different snapshots, and (b) the behavior of all the cuboids in a given snapshot. Experimental results on both synthetic and real datasets show the effectiveness of the proposed algorithm in discovering evolutionary graph cuboid outliers.
The Aspirations of Youth in Arkansas: A Comparison of Rural Locales

Rural youth are leaving their home communities in search of economic opportunity. Students’ residential, occupational, and educational aspirations are effective predictors of life choices, such as future residence. This study’s purpose was to determine the aspirations of rural students in Arkansas overall, and by locale. This study used descriptive survey methodology and a stratified random sample of 15 rural schools to determine the respondents’ (n = 133) aspirations, expectations for the future, and perception(s) of their home community. Overall, a majority of respondents indicated they want to leave their home communities and obtain at least a bachelor’s degree. Nearly half aspired to work in health sciences or education. Moderate associations were found between the respondents’ residential and educational aspirations. Weak associations were also found for respondents’ expectations and locale code. Students indicated that occupational and educational barriers were similar. Lack of money for school, poor job markets, and family responsibilities were the most frequent barriers for a majority of respondents overall. Good paying jobs, many chances to get ahead, and indoor entertainment were the community characteristics for which respondents indicated high importance, but low satisfaction. As for students’ perceptions of their home communities, responses provided were fairly low to neutral. Negligible to small effect sizes were found when describing differences by rural code for perceptions of community, perceived importance of community characteristics, and satisfaction with community characteristics. The residential aspirations of these respondents resemble individuals involved in the brain drain. Responses provided from respondents concerning their aspirations supports previous research regarding the aspirations of rural students. These students’ responses also reflect concepts associated with achievement motivation, social comparison, and human capital theory. Based on these findings, this study recommends conducting future research regarding more in-depth information concerning rural Arkansas youth’s aspirations. Additionally, for school districts whose students are similar to those in this study, counselors and administrators should provide opportunities college prep, such as, applying for financial aid, and hosting ACT and college entrance requirement workshops. Finally, based on respondents’ low perceptions of their communities, similar communities should consider providing opportunities such as job fairs, job shadowing, and mentorship programs.
Autofocusing region selection for computer vision

Focusing region selection is an important part in autofocusing algorithm, which directly influences the accuracy, unimodality and stability of the sharpness function curve. Two criteria for focusing region selection are presented. Then, a novel region selection method based on edge mask is proposed. The edge mask is obtained by Canny detector, morphological image processing and central region selecting. This edge mask takes into account the pixels which represent the edge information of the main target. Experiments show that the proposed strategy can significantly exclude the influence of background and noises in the image. It has good adaptivity and anti-noise capability, and therefore improves the performance of the autofocusing system.
Prosody in speech production: A fMRI study

Clinical observations of distortions of production (and perception) of prosody implicate that distinct, non-overlapping neural circuits are responsible for distinct prosodic cues and functions [1]. These observations motivate a question whether similar evidence can be found in the neurologically intact brain. In our experiments we use new technology designed to reveal the function of active, healthy brain. The experiments are constructed to check the neuroanatomical basis of thePROSODY GENERATOR, a functional unit in the phonological system which integrates and controls the variation of prosodic parameters [2]. The results show that relatively small, non-overlapping, distinct perisilvian areas of both the right and the left hemisphere are involved in the generation of prosody. We found specific activity correlated with the FOCUS accent, the MODUS marker and theAFFECT characterization. The localization appears to correlate best with the address frame of the prosodic cues. These results can not be fully accommodated by any of the existing theories of prosodic representation of speech in the human brain.
Transient Eexpression of β-glucuronidase Reporter Gene in Sainfoin ( Onobrychis viciifolia Scop . ) Cotyledons Via Microprojectile Bombardment

Transient β-glucuronidase reporter gene (GUS) expression was visualised in whole cotyledons of sainfoin (Onobrychis viciifolia Scop.) after microprojectile bombardment with pBI221.23 DNA. Optimum rupture disk pressure and sample plate distance were determined to be 1350 psi and 6 cm, respectively. Mean gold particle diameter of 1.0 μm and 48 h post-bombardment histochemical GUS assay was found to be superior to 1.6 μm gold particles and 120 h postbombardment GUS assay. Microscopic analysis revealed the localisation of the gold particles predominantly in the epidermal cell layer, whereas less than 1% of the particles were localised in subepidermal cells, as deep as three cell layers. Availability of a regeneration protocol from sainfoin cotyledons and the potential of the microprojectile bombardment recommend future applications for obtaining transgenic sainfoin plants.
Network-dependent kernels for image ranking

The exponential growth of social networks (SN) currently makes them the standard way to share and explore data where users put informations (images, text, audio,…) and refer to other contents. This creates connected networks whose links provide valuable informations in order to enhance the performance of many tasks in information retrieval including ranking and annotation. We introduce in this paper a novel image retrieval framework based on a new class of kernels referred to as “network-dependent”. The main contribution of our method includes (i) a variational framework which helps designing a kernel using both the intrinsic image features and the underlying contextual informations resulting from different (e.g. social) links and (ii) the proof of convergence of the kernel to a fixed-point, that is positive definite and thus associated with a reproducing kernel Hilbert space (RKHS). Experiments conducted on different ground truths, including the ImageClef/Flickr set, show the outperformance and the substantial gain of our ranking kernel with respect to the use of classic “network-free” kernels.