nils-herrmann/clean_scirepeval huggingface dataset:
Validity and Reliability Evidence of the Engineering Professional Responsibility Assessment Tool

The development of social responsibility is important for educating holistic engineers, able to work across social and cultural boundaries to solve complex social issues. A way is needed to measure effective interventions for increasing social responsibility.  This article describes the Engineering Professional Responsibility Assessment (EPRA) instrument and provides evidence of its usability, validity, and reliability. The EPRA measures students' social responsibility attitudes and operationalizes the professional social responsibility development model, which describes the development of personal and professional social responsibility in engineers. The EPRA is intended to be used by educators to assess curricular interventions aimed at changing students' views of social responsibility.  The EPRA was developed in an iterative manner, using five different survey administrations with adjustments made to the instrument between each. Data from the final survey with 1,000 student responses were used to develop evidence of validity through expert feedback, structural equation modeling, multidimensional item response theory, and convergent evidence of validity and evidence of reliability using ordinal alpha.  Evidence of validity and reliability indicates the appropriateness of the EPRA to measure social responsibility attitudes in engineering students.  The evidence of reliability and validity shows that the EPRA may be a useful tool to assess engineering student views of social responsibility, changes in those views over time, and the effectiveness of educational interventions intended to affect these attitudes.
Customizing the EPSA rubric to cover local curriculum content for assessment of engineering professional skills

The Accreditation Board for Engineering and Technology Engineering Criteria 2000 (ABET EC 2000) identifies two areas of expertise, commonly distinguished as "hard engineering skills" and "soft engineering skills" with the latter also known as Engineering Professional Skills (EPS) EPS includes skills such as communication, teamwork, and ethical responsibility, and professionalism, awareness of the impact of engineering solutions on society, life long learning and understanding of contemporary issues. The criteria of ABET EC 2000 have been widely adopted by many engineering programs as program outcome criteria. Recently a rubric has been developed to facilitate engineering professional skill assessment (EPSA) in the context of ABET EC 2000 criteria. However, any engineering program is likely to be strongly influenced by both the global and local situations faced by the country in which the engineering program is located. For instance, in a developing country like Indonesia, in addition to ABET EC 2000, the curriculum must simultaneously cover both the national (core) curriculum and the local (institutional) curriculum. (This requirement is stipulated by a Decree of the Minister of National Education of the Republic of Indonesia No. 232/U/2000 about Guidelines for Proposing of Higher Education Curriculum and Assessment of Student Learning) This necessitates a requirement for assessment that evaluates students' understanding of both ABET EC 2000 and the national and local curricula.
Profit maximization for viral marketing in Online Social Networks
Venue: 2016 IEEE 24th International Conference on Network Protocols (ICNP)

Information can be disseminated widely and rapidly through Online Social Networks (OSNs) with "word of mouth" effects. Viral marketing is such a typical application in which new products or commercial activities are advertised by some seed users in OSNs to other users in a cascading manner. The budget allocation for seed selection reflects a tradeoff between the expense and reward of viral marketing. In this paper, we define a general profit metric that naturally combines the benefit of influence spread with the cost of seed selection in viral marketing to eliminate the need for presetting the budget for seed selection. We carry out a comprehensive study on finding a set of seed nodes to maximize the profit of viral marketing. We show that the profit metric is significantly different from the influence metric in that it is no longer monotone. As a result, from the computability perspective, the problem of profit maximization is much more challenging than that of influence maximization. We develop new seed selection algorithms for profit maximization with strong approximation guarantees. Experimental evaluations with real OSN datasets demonstrate the effectiveness of our algorithms.
EMPOWERMENT OF WOMEN IN INDIA

Despite the best efforts of the exponents of social movement theory, the dynamics of empowerment of women in India has not been (re)visited to lend specificity to the Indian gender mainstreaming strategies. So the Indian post feminist efforts to engender a gender just society by empowering women, critical symbols of continued subalternship, need to be put under post feminist scanners. Against this backdrop, it is mooted that the principal aim of this paper is to (re)defme empowerment of women in India as an open ended process aiming at the felicitating (i) abolition of gender based discrimination in all institutions and structures of the India society and (ii) participation of women in policy and decisionmaking processes at private and public levels of assorted activities, qualified by all dyadic relations among mind, matter, politics of knowledge, gender politics, and poetics of lack and desire. 1. Statement of the Problem With reference to the commonplace paradox of very social interpretation of the Indian women, it can be submitted that the activities of most of the Indian women, by and large inferiorized and devalorized, have been mostly circumscribed because of the invidious distinctions which the Indian MCPs (Male Chauvinist Prigs) very often allude to with a view to re specifying the non essentialist nuances of the womanliness of the Indian women. Though the nation's identify does lay in the culture and more specifically in its womanhood, the Indian male supremacists have, very smugly, denigrated 'female exclusiveness' So most of the Indian women have been suffering from the lack of self and space, disempowerment, disprivilege, disadvantage, sexist discrimination, gender inequity, invisibility, asymmetries, marginal ization, devalorizaiton and reification. Concomitantly, over the years, their development/empowerment has been neglected inspite of the populist gimmicks of the 'welfarists' and advocates of feminisms and postfeminisms. Despite the best efforts of the exponents of social movement theory, the dynamics of empowerment of women in India has not been (re)visited to lend specificity to the Indian gender mainstreaming strategies. So the Indian post feminist efforts to engender 'a gender just society' by empowering women, critical symbols of continued subalternship, need to be put under post feminist scanners.
Red light generation through the lead boro telluro phosphate glasses activated by Eu3+ ions

Lead boro telluro phosphate glasses containing 0.05 to 2.0 wt% of Eu 3+ ions were prepared through melt quenching technique. Structural characteristics of title glasses were identified through XRD, FTIR and Raman studies. The optical properties of the prepared glasses were studied using UV Vis NIR absorption and photoluminescence spectra. From the resultant spectra, we have obtained the bonding parameters (d) nephelauxetic ratio (b) direct and indirect band gaps and Urbach energy (DE) values. A deep red luminescence due to 5 D 0 7 F 2 transition of Eu 3+ ions could be observed for the title glasses. The local site symmetry around the Eu 3+ ions and the degree of Eu 3+ O 2 covalence were assessed from the luminescence intensity ratio of 5 D 0 7 F 2 5 D 0 7 F 1 transitions. Judd Ofelt intensity parameters, calculated from the luminescence spectra, were used to estimate the radiative parameters like transition probability (A) branching ratio (b exp b cal and stimulated emission cross section s P E concerning the 5 D 0 7 F J (J 0, 1, 2, 3 and 4) transitions. The important laser parameters, gain bandwidth and optical gain are also estimated. The decay curves associated with the transition from 5 D 0 state was found to be single exponential at all Eu 3+ ion concentrations. CIE colour coordinates and colour purity of the prepared glasses were estimated from the CIE chromaticity diagram.
Electrolytic exfoliation synthesis of boron doped graphene quantum dots: a new luminescent material for electrochemiluminescence detection of oncogene microRNA 20a

In this work, boron doped graphene quantum dots (BGQDs) with the atomic percentage of boron (B) of 0.67 2.26% were synthesized by electrolytic exfoliation of B doped graphene rods. X ray photoelectron spectroscopy of BGQDs confirmed that the B atoms have been successfully incorporated into the GQDs. Characterizations by transmission electron microscopy, photoluminescence (PL) spectra and UV visible spectra demonstrated that BGQDs had a consistent lattice spacing with the plane of graphene and possessed good luminous performance. The PL stability, the electrochemical impedance and Zeta potential test indicated that the 60 days PL stability of BGQDs was improved by 51% and the resistance of BGQDs was decreased by 11% compared with that of the pure GQDs when 1.29% (atomic percentage) of B was doped. Electrochemiluminescence (ECL) sensing results showed that the ECL sensor with BGQDs as luminescent material exhibited an excellent analytical property for the detection of miRNA 20a in a linear range of 0.1 1x104 pM with a quantification limit of 0.1 pM. Specificity tests showed that this ECL sensor could distinguish the target miRNAs 20a with several similar bases strand. The obtained results in this study prove that the proposed ECL sensor provides a high sensitively, specifically and simply platform for detection of miRNAs 20a.
A Red Emitting Luminescent Material Capable of Detecting Low Water Content in Organic Solvents.
Venue: Chemistry

A new red emitting luminescent material was prepared from a gel formed by simply mixing EuCl3 6 H2 O and 4' para phenylcarboxyl 2,2':6',2' terpyridine (Hcptpy) in a molar ratio of 1:2 in anhydrous ethanol at room temperature. It shows bright red luminescence dominated by the (5) D0 (7) F2 transition of Eu(3+ a long lifetime (1.16 ms) a high absolute quantum yield (48.2 and good thermostability (stable up to 500 degC) In addition, the luminescence of the material can be easily quenched by contact with water, which makes it suitable for detecting low contents of water (0.1 1.5 vol in common organic solvents such as diethyl ether and THF.
The Contextual Turn: from Context Aware to Context Driven Recommender Systems
Venue: RecSys

A critical change has occurred in the status of context in recommender systems. In the past, context has been considered 'additional evidence' This past picture is at odds with many present application domains, where user and item information is scarce. Such domains face continuous cold start conditions and must exploit session rather than user information. In this paper, we describe the `Contextual Turn? the move towards context driven recommendation algorithms for which context is critical, rather than additional. We cover application domains, algorithms that promise to address the challenges of context driven recommendation, and the steps that the community has taken to tackle context driven problems. Our goal is to point out the commonalities of context driven problems, and urge the community to address the overarching challenges that context driven recommendation poses.
Secure Linear Regression on Vertically Partitioned Datasets
Venue: IACR Cryptol. ePrint Arch.

We propose multi party computation protocols for securely computing a linear regression model from a training dataset whose columns are distributed among several parties. Our solution enables organizations to collaborate in the construction of a predictive model while keeping their training data private. Our approach is based on a hybrid MPC protocol combining garbled circuits with an offline phase enabled by a semi trusted external party. As part of our contribution, we evaluate several algorithms and implementations for solving systems of linear equations using garbled circuts. Experiments conducted with an implementation of our protocols show that our approach leads to highly scalable solutions that can solve data analysis problems with one million records and one hundred features in less than one hour.
Recommending learning material in Intelligent Tutoring Systems
Venue: Ann. UMCS Informatica

Nowadays, intelligent e learning systems which can adapt to learner's needs and preferences, became very popular. Many studies have demonstrated that such systems can increase the eects of learning. However, providing adaptability requires consideration of many factors. The main problems concern user modeling and personalization, collaborative learning, determining and modifying learning senarios, analyzing learner's learning styles. Determining the optimal learning scenario adapted to students' needs is very important part of an e learning system. According to psychological research, learning path should follow the students' needs, such as (i.a. content, level of diculty or presentation version. Optimal learning path can allow for easier and faster gaining of knowledge. In this paper an overview of methods for recommending learning material is presented. Moreover, a method for determining a learning scenario in Intelligent Tutoring Systems is proposed. For this purpose, an Analytic Hierarchy Process (AHP) method is used.
The effects of learner generated videos for YouTube on learning outcomes and satisfaction
Venue: Comput. Educ.

This paper presents the results of an educational innovation project based on learner generated videos. The videos were created for a YouTube channel specifically developed for a marketing course. Despite the potential of YouTube as a learning tool in education, its use as a learning instrument for learner generated content is scarce. In this project, students could voluntarily participate in the creation of videos, which were then uploaded to the channel by the professors. At the end of the course, students completed a questionnaire assessing learning outcomes and satisfaction. The findings showed that active participation had a direct influence on the perceived acquisition of cross curricular competencies and on academic performance. While participation did not directly increase subjective learning or satisfaction with the course, it had an indirect influence through cross curricular competencies. This research contributes to previous literature by showing how learner generated content and the use of YouTube as a teaching vehicle has a positive impact on students' learning outcomes and satisfaction. Learner generated content (videos for YouTube) is promoted in higher education.Video creation improves cross curricular competencies and academic performance.Effects on satisfaction are null and effects on subjective learning are negative.These two variables are positively affected via cross curricular competencies.Active and experiential learning help improve students' learning and satisfaction.
A facile method for processing lignin reinforced chitosan biopolymer microfibres: optimising the fibre mechanical properties through lignin type and concentration

A chitosan biopolymer microfibre reinforced by lignin has been processed by a wet spinning method. To optimise the fibre mechanical and structural properties two types of lignin, with molecular weights 28 000 g mol 1 and 60 000 g mol 1, were examined and the chitosan fibre was blended with the respective lignin type at 1, 3, 5, 7 and 8 wt% lignin concentrations. The main effects of lignin type and concentration, as well as the interaction between the two parameters, on the fibre tensile stiffness, extensibility, strength and toughness were evaluated using the two factor analysis of variance. Significant variations in the respective mechanical properties were observed with varying lignin concentrations (P 0.05) The magnitude of the respective mechanical properties is low at 1 wt% but peaks at 3 wt% before decreasing steadily with increasing lignin concentration. Except for extensibility, significant variations in the strength and toughness were observed with respect to lignin type (P 0.05) variations in the stiffness were masked by interactions between lignin type and concentration. These results were related to the dispersion of lignin in the fibre and the nature of the bonds between lignin and chitosan, based on findings from scanning electron microscopy and Fourier transform infrared spectroscopy. This new method for the fabrication of chitosan biopolymer microfibre is inexpensive and versatile and could lend itself to the production of high performance biocomposite structures.
Two Step Forward Genetic Screen in Mice Identifies the Ral Pathway as a Central Drug Target in Hepatocellular Carcinoma.
Venue: Gastroenterology

76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 Aof hepatocellular carcinoma (HCC) will be crucial to developing new therapies aimed at selected targets. Given the sparse treatment options of advanced HCC, such progress is needed urgently for this highly prevalent cancer. However, even though the full genomes of roughly 500 HCC samples are now fully available from diverse sequencing efforts and public databases, the genetics of HCC remains challenging. This is mostly owing to the significant heterogeneity of these tumors and the experimental/diagnostic problem of a lack of disease free control liver tissue. Thus, novel approaches investigating HCC genetics from a different perspective are needed. In this issue of Gastroenterology, Kodama et al present a forward genetics approach to identify novel aspects in HCC biology. In contrast with conventional reverse genetic approaches investigating the effects of altering particular genes, the forward genetic approach begins with a particular biological phenomenon and aims to identify the genetic changes responsible for the development of this specific phenotype. A forward genetic approach has the advantage of providing an unbiased selection of genes associated with the phenotype of interest, such as HCC development. The authors used the sleeping beauty transposon system (SB) Generally, transposable elements are capable of moving from 1 location on the genome to another. Among the diverse known and developed transposon systems the SB system functions through a DNA cut and paste mechanism. This process is catalyzed by the active enzyme transposase. The enzyme binds to the transposable DNA element (transposon) at its bindings sites within terminal inverted repeats at both ends. After formation of a synaptic complex, the transposable element is excised from its original location and reintegrated at a novel target site, exclusively TA dinucleotide sites. Since the Noble Prize winning discovery of transposable elements in maize plants by Barbara McClintock in 1983, these genetic elements have been identified in multiple organisms among them mouse and man. Their identification changed the perception of genes and chromosomes as an all time stable composite, toward a flexible organization of genetic information in our cells. To apply transposon technology to vertebrate model organisms or even gene therapy, the Tc1/mariner type, an active vertebrate element
b 3 js A Library for Interactive Web Data Visualizations in Virtual Reality

As virtual reality (VR) devices become more ubiquitous, data scientists increasingly recognize the power of viewing and manipulating complex, multivariate data in immersive virtual worlds. In their quest to extract knowledge from the data, data scientists may benefit from visualizations that are easily controlled by hand motion. We here present b3.js, a library for creating interactive VR data visualizations on a web browser. The 3D visualizations, for example, 3D scatter, bar, and surface plots, may be viewed through the Oculus Rift and manipulated gesturally with the Leap Motion controller. Oculus Rift provides immersive point of view perspective within the VR environment. Leap Motion enables gestural interaction by allowing users to control the parameters of the virtual camera, for example, modify the point of view. Users can also modify points of a rendered plot. We show that combining the Oculus Rift and Leap Motion with b3.js enables users to engage with a complex data set consisting of coherently organized 3D flight paths of thousands of bats. A novel data exploration experience was created that is difficult to achieve on a flat screen with the traditional mouse keyboard paradigm.
Femtosecond Laser Micromachining Photonic And Microfluidic Devices In Transparent Materials

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A Review of Artificial Neural Networks Application to Stock Market Predictions

The purpose of this paper is to review artificial neural network applications used in the field of stock price forecasting. The field of stock price forecasting has increasingly grown to be an important subject matter for researchers, everyday investors and practitioners in the finance domain as it aids financial decision making. This study brings to attention some of the neural network applications used in stock price forecasting focusing on application comparisons on different stock market data and the gaps that can be worked on in the foreseeable future. This work makes an introduction of neural network applications to those novels in the field of artificial intelligence.  Neural Networks, Forecasting Stock Price. Financial Markets, Complexity, Error Measures, Decision Making
A new architecture for modeling and prediction of dynamic systems using neural networks: Application in Tehran stock exchange
Venue: 2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA)

Modeling and forecasting Stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. This nonlinearity affects the efficiency of the price characteristics. Using an Artificial Neural Network is a proper way to model this nonlinearity and it has been used successfully in one step ahead and multi step ahead prediction of different stock prices. Several factors, such as input variables, preparing data, network architecture and training procedure, have huge impact on the accuracy of the neural network prediction. The purpose of this paper is to derive a method for multi step ahead prediction based on Recurrent Neural Networks (RNN) Real Time Recurrent Learning (RTRL) networks and Nonlinear AutoRegressive model process with eXogenous input (NARX) The model is trained and tested by Tehran Securities Exchange data.