nils-herrmann/clean_scirepeval huggingface dataset:
Predictive modelling for 3D inkjet printing processes
Venue: 2016 39th International Spring Seminar on Electronics Technology (ISSE)

The importance of predictive modelling in addressing quality and reliability issues of 3D printing technology is quite significant. The aim of this paper is to develop and demonstrate a data driven approach for monitoring and forecasting the quality of electronics structures manufactured by a 3D inkjet printing process. In order to realise this predictive capability, data driven prognostics techniques that use information for process parameters are employed. The proposed quality assessment of 3D printed electronics products is based on the predictive capabilities of computational intelligence algorithms. The ability of neural network models to assess the quality characteristics of printed electronic products caused by dimensional deviations is evaluated and discussed. Performance capabilities of selected training algorithms for the adopted neural network models is also studied and reported.
Teachers' Perceptions of Culturally Responsive Pedagogy and the Impact on Leadership Preparation: Lessons for Future Reform Efforts.

The purpose of this study was to investigate the impact of one school's teacher driven professional development effort to address culturally responsive teaching practices in a large district in a Midwestern state. During the 2011 2012 school year, a team of teachers and principals began a three year long effort to provide job embedded professional development intended to focus on delivering high impact strategies to transform the educational practices of teachers through improving cultural competence. A survey was given to 120 fulltime certified teachers, and findings suggest that while teachers agreed most that the professional development helped examine views on poverty, they agreed least that the professional development helped close the achievement gap. Additionally, elective and special education teachers were significantly more positive than core subject classroom teachers in terms of how the research they read improved instruction and how the professional development provided impacted building wide faculty instruction. Analysis of open ended items highlight several themes, namely the professional development helped teachers by acknowledging cultural differences of the students they taught, but that ultimately the challenges of lack of time and implementation apathy impeded the success of the professional development effort. These findings provide important insight for leadership preparation, particularly about supporting teacher driven efforts, facilitating culturally responsive practices, and the reflecting on the pressures teachers face due to high stakes accountability and reform efforts.
Visual analytics for supply network management: System design and evaluation
Venue: Decis. Support Syst.

We propose a visual analytic system to augment and enhance decision making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on demand and update the visual representation via user initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision making processes in a supply network setting. We conduct multi stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities. Supply network scale, scope, and complexity strain managers' cognitive capacity.Visual analytics augments and amplifies managers' supply network intelligence.We propose a visual analytic framework for supply network management.System incorporates multiple interactive visualizations and predictive analytics.Multi phase evaluations reveal significant utility and usefulness of our system.
Website Fingerprinting at Internet Scale
Venue: NDSS

The website fingerprinting attack aims to identify the content (i.e. a webpage accessed by a client) of encrypted and anonymized connections by observing patterns of data flows such as packet size and direction. This attack can be performed by a local passive eavesdropper one of the weakest adversaries in the attacker model of anonymization networks such as Tor. In this paper, we present a novel website fingerprinting attack. Based on a simple and comprehensible idea, our approach outperforms all state of the art methods in terms of classification accuracy while being computationally dramatically more efficient. In order to evaluate the severity of the website fingerprinting attack in reality, we collected the most representative dataset that has ever been built, where we avoid simplified assumptions made in the related work regarding selection and type of webpages and the size of the universe. Using this data, we explore the practical limits of website fingerprinting at Internet scale. Although our novel approach is by orders of magnitude computationally more efficient and superior in terms of detection accuracy, for the first time we show that no existing method including our own scales when applied in realistic settings. With our analysis, we explore neglected aspects of the attack and investigate the realistic probability of success for different strategies a real world adversary may follow.
Technology and Production Fragmentation: Domestic Versus Foreign Sourcing

This paper provides direct empirical evidence on the relationship between technology and firms' global sourcing strategies. Using new data on U.S. firms' decisions to contract for manufacturing services from domestic or foreign suppliers, I show that a firm's adoption of communication technology between 2002 to 2007 is associated with a 3.1 point increase in its probability of fragmentation. The effect of firm technology also differs significantly across industries; in 2007, it is 20 percent higher, relative to the mean, in industries with production specifications that are easier to codify in an electronic format. These patterns suggest that technology lowers coordination costs, though its effect is disproportionately higher for domestic rather than foreign sourcing. The larger impact on domestic fragmentation highlights its importance as an alternative to offshoring, and can be explained by complementarities between technology and worker skill. High technology firms and industries are more likely to source from high human capital countries, and the differential impact of technology across industries is strongly increasing in country human capital.
MISSING FOURTH ELEMENT MEMRISTOR MODELING WITH NEW WINDOW FUNCTION DERIVED FROM SIGMOID LOGISTIC EQUATION

As a potential competition for the next generation memory technology, the newly found missing forth fundamental circuit element called memristor by HP labs in 2008 has drawn a great deal of interest. Among the emerging nanotechnologies possibilities, Memristor based technology provides much better scalability and higher packing density when used as a memory that enables the improvement of performance, power and cost of integrated circuits. Memristor behaves as a nonvolatile resistive memory and retains the information even though a power source is switched off. In this research paper, we propose a memristor model with new window function derived from sigmoid logistic equation that resolves the terminal state problem and the parameters in the proposed window function can be easily adjusted to model the different kind of memristors. The main advantages of the new window function contains less fitting parameter that should satisfy all of the memristor properties such as frequency dependent hysteresis behaviors, Hard switching effects and boundary assurance.
Nineteen Step Total Synthesis of Phorbol
Venue: Nature

Phorbol, the flagship member of the tigliane diterpene family, has been known for over 80 years and has attracted attention from many chemists and biologists owing to its intriguing chemical structure and the medicinal potential of phorbol esters. Access to useful quantities of phorbol and related analogues has relied on isolation from natural sources and semisynthesis. Despite efforts spanning 40 years, chemical synthesis has been unable to compete with these strategies, owing to its complexity and unusual placement of oxygen atoms. Purely synthetic enantiopure phorbol has remained elusive, and biological synthesis has not led to even the simplest members of this terpene family. Recently, the chemical syntheses of eudesmanes, germacrenes, taxanes and ingenanes have all benefited from a strategy inspired by the logic of two phase terpene biosynthesis in which powerful C C bond constructions and C H bond oxidations go hand in hand. Here we implement a two phase terpene synthesis strategy to achieve enantiospecific total synthesis of phorbol in only 19 steps from the abundant monoterpene 3 carene. The purpose of this synthesis route is not to displace isolation or semisynthesis as a means of generating the natural product per se, but rather to enable access to analogues containing unique placements of oxygen atoms that are otherwise inaccessible.
Determining Process Model Using Time Based Process Mining and Control Flow Pattern

Determining right model of business process from event log is the purpose of process discovery. However some problems i.e the inability to discover OR, noise and event log incompleteness are emmerged while determining right model of business process. First, OR relation is often discovered as AND relation. Second, noise problem is occured when there are truncated and low frequency traces in event log. Thus control flow pattern is used to solve issues of same noise relation frequency hence it discovers relation based on transaction function of activity. Consequently, it can refine non noise relation in business process model. Third, incompleteness leads to incorrect discovery of parallel process model; therefore we used Timed based Process Mining which utilized non linear dependence to solve the incompleteness. Finally this paper proposed combination of Timed based Process Mining and control flow pattern to discover OR and handle same frequency noise and incompleteness. From the experiment in section 3, this proposed method manages to get right process model from event log.
Determinants of structural unemployment in Colombia: a search approach

We provide evidence of the structural unemployment rate determinants in Colombia between 1984 and 2015. In the first stage, we estimate different measures of this variable including the ones that emerge from the search theoretic, the Phillips curve and a structural vector autoregressive model. Next, by using a fully modified ordinary least squares cointegration approach, we test the determinants in the Colombian case following the search model guidelines. Accordingly, the main explanations of the structural unemployment rate are the real minimum wage, the real interest rate, a hiring cost indicator, sectoral shifts, non wage labour costs and some demographic factors such as the proportion of workers with no college education. Finally, we use these variables to estimate a new measure of the structural unemployment rate called the true structural unemployment rate.
The effect of instructional method on teaching assistants' classroom discourse

There has been increased interest in the transformation of post secondary level instructional practices in STEM from more traditional to evidence based practices that are more aligned with how learning occurs. Research has shown that instructional practices are linked to student learning outcomes even when content is unchanged; therefore, incorporating evidence based practices into the classroom represents an area worthy of focus and resources. Problem based learning (PBL) is an inquiry oriented instructional strategy wherein students answer ill structured real world problems through collaboration, research, experimentation, and trial and error. The success or failure of an inquiry oriented laboratory session depends in large part on the practices of the instructor. The work presented here focuses on the instructional practices of chemistry graduate teaching assistants (GTAs) who over the course of a semester, taught both expository/demonstration and inquiry laboratory sessions. Upon comparing GTA discourse across inquiry and expository/demonstration settings, three assertions were generated: (a) there was an apparent relationship between the instructional mode (expository/demonstration versus inquiry) and the structure of the classroom discourse employed by GTAs, (b) patterns in classroom discourse repeated within given instructional modes, even when the nature of content being covered varied widely, and (c) patterns in classroom discourse observed in inquiry labs exemplified a constructivist learning environment and were achieved with minimal intervention.
Abstract 2205: Exosomal encapsulation of doxorubicin reduces the cardiac toxicity of mice

Exosomes are nanovesicles produced by cells embedded of cellular information and represent a formidable natural cargo for communication. The name "FedExosomes" denotes the general idea that exosomes could deliver cargo that conveniently manipulated could be of help for patient therapy. Up to now, a few papers demonstrated that modified exosomes could deliver drugs specifically to cancer cells and many laboratories are now studying their properties and compositions. Differently from previously published papers that focused on the efficacy of the doxorubicin encapsulated in exosomes (exoDOX) for the first time, we demonstrated that unmodified exosomes loaded with DOX are less toxic than free DOX by altering the biodistribution of the drug. The heart tissue of mice treated with a toxic dosage of DOX exhibited scattered cytoplasmic paranuclear vacuoles and focal intense eosinophilic cytoplasm, devoid of their transversal striations with moderate disarrangement of cardiomyocytes. The heart tissue of exoDOX treated mice at the same dosage appeared normal. Mass spectrometry studies confirmed that although the quantity of exoDOX in the blood was the same compared to DOX, accumulation in the heart was reduced of about forty percent. Maximum tolerated dose of exoDOX treated mice is double than free DOX. Mice treated at double concentration of exoDOX vs DOX have reduced tumor burden compared to free DOX without observable toxicity. We demonstrated that exoDOX increased the therapeutic index of DOX by reducing toxic side effects and envisage a similar mechanism for others chemotherapeutic drugs. Since the exosomes could be prepared directly from the patients, our preclinical approach could have a possible immediately application in the clinic.  Flavio Rizzolio, Mohamad Hadla, Giuseppe Corona, Isabella Caligiuri, Stefano Palazzolo, Sabrina Semeraro, Amelia Gamini, Vincenzo Canzonieri, Giuseppe Toffoli. Exosomal encapsulation of doxorubicin reduces the cardiac toxicity of mice.
EQUIPPING MINDS: APPLYING A BIBLICALLY BASED CURRICULUM FOR IMPROVING WORKING MEMORY

APPLYING A BIBLICALLY BASED CURRICULUM FOR IMPROVING WORKING MEMORY Carol Thompson Brown Ed.D. The Southern Baptist Theological Seminary, 2016 Supervisor: Dr. Danny R. Bowen Recent findings in neuroscience confirm the neuroplasticity of the brain. There has been strong interest in applying these discoveries to learners with learning disorders focusing on increasing working memory capacity. The aim of the present study was to explore the effectiveness of cognitive intervention with the Equipping Minds Cognitive Development Curriculum (EMCDC) based on Feuerstein's theory of structural cognitive modifiability. Feuerstein's theory states that a learner's cognitive functioning can be modified through mediated learning. EMCDC is aimed at enhancing processing, working memory, comprehension, and reasoning abilities. Participants were learners with Specific Learning Disorders (SLD) Learners were randomly assigned into one of two groups. The active control group received small group intervention in academic subjects an hour a day five times a week for 7 weeks. The training group received small group intervention in the Equipping Minds Cognitive Development Curriculum an hour a day five times a week for 7 weeks. Both groups were tested on measures of working memory, verbal and nonverbal ability, and academic attainment before training and re tested on the same measures after training. Analysis of the pre to post test scores demonstrated significant (p<0.05) advantage of the training over the
A survey of photon mapping state of the art research and future challenges
Venue: Frontiers of Information Technology Electronic Engineering

Global illumination is the core part of photo realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.
Phonon Photon Mapping in a Color Center in Hexagonal Boron Nitride.
Venue: Physical review letters

We report on the ultraviolet optical response of a color center in hexagonal boron nitride. We demonstrate a mapping between the vibronic spectrum of the color center and the phonon dispersion in hexagonal boron nitride, with a striking suppression of the phonon assisted emission signal at the energy of the phonon gap. By means of nonperturbative calculations of the electron phonon interaction in a strongly anisotropic phonon dispersion, we reach a quantitative interpretation of the acoustic phonon sidebands from cryogenic temperatures up to room temperature. Our analysis provides an original method for estimating the spatial extension of the electronic wave function in a point defect.
Adaptive Photon Mapping Based on Gradient
Venue: Journal of Computer Science and Technology

Photon mapping can simulate some special effects efficiently such as shadows and caustics. Photon mapping runs in two phases: the photon map generating phase and the radiance estimation phase. In this paper, we focus on the bandwidth selection process in the second phase, as it can affect the final quality significantly. Poor results with noise arise if few photons are collected, while bias appears if a large number of photons are collected. In order to solve this issue, we propose an adaptive radiance estimation solution to obtain trade offs between noise and bias by changing the number of neighboring photons and the shape of the collected area according to the radiance gradient. Our approach can be applied in both the direct and the indirect illumination computation. Finally, experimental results show that our approach can produce smoother quality while keeping the high frequency features perfectly compared with the original photon mapping algorithm.
Locating battery exchange stations for electric taxis: A case study of Seoul, South Korea

As climate change and severe air pollution become life threatening, numerous attempts have been made to encourage the use of electric vehicles as alternative fuel vehicles. One such proposal is the introduction of electric taxis supported by the battery exchange station (BES) system. This article presents the framework on how the BESs should be located in a city considering the demand and practical constraints using Seoul, South Korea, as the case study. As a solution approach, p median models are applied for 25 candidate locations and modeling results are presented and interpreted.
Indoor localization of vehicles using Deep Learning
Venue: 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM)

Modern vehicles are equipped with numerous driver assistance and telematics functions, such as Turn by Turn navigation. Most of these systems rely on precise positioning of the vehicle. While Global Navigation Satellite Systems (GNSS) are available outdoors, these systems fail in indoor environments such as a car park or a tunnel. Alternatively, the vehicle can localize itself with landmark based positioning and internal car sensors, yet this is not only costly but also requires precise knowledge of the enclosed area. Instead, our approach is to use infrastructure based positioning. Here, we utilize off the shelf cameras mounted in the car park and Vehicle to Infrastructure Communication to allow all vehicles to obtain an indoor position given from an infrastructure based localization service. Our approach uses a Convolutional Neural Network (CNN) with Deep Learning to identify and localize vehicles in a car park. We thus enable position based Driver Assistance Systems (DAS) and telematics in an underground facility. We compare the novel Deep Learning classifier to a conventional classifier using Haar like features.
An improved optimized clustering technique for crime detection
Venue: 2016 Symposium on Colossal Data Analysis and Networking (CDAN)

Data mining automates the finding predictive records procedure in big databases. Clustering is a most famous method in data mining and is an important methodology that is performed based on the similarity principle. The segregation of a big database is a stimulating and task of time consuming. It concludes two different stages: first, feature extraction maps all documents or record to a point in the space of high dimensional, then algorithms for clustering automatically grouping the points into a cluster hierarchy. Clustering has various applications in different fields. Few of the fields include criminology, text mining, image resolution, machine learning. Crime detection has become one of the most attractive field as the crime rate in India and whole world is increasing at a greater pace. We as citizens of a country have to contribute towards its detection and removal. Thus, a comprehensive survey carried about the basics of clustering has given in this paper. Moreover, proposed work was given that gives the idea of the work going to be done in the upcoming time.