nils-herrmann/clean_scirepeval huggingface dataset:
The use of scaffolding in the teaching of creative dance by kindergarten teachers
Year: 2013

In 2006, the Taiwanese Ministry of Education launched a kindergarten supervision project with the aim of advancing curriculum and instruction quality, and reinforcing teachers' professional development. As a supervisor, I visited 12 kindergartens between 2007 and 2011, spending 60 hours per year at each, spread across 10 visits. My particular roles were to facilitate the arts curriculum and promote teachers' knowledge of, and skills in, teaching creative dance. This paper explores how kindergarten teachers are using the concept of scaffolding, as described in Vygotsky's social construction theory, in their creative dance teaching strategies, referencing data collected through classroom observation, photographs, supervision reports, interviews with teachers, young children's dance and drawing, and my own and other researchers' reflective diaries. Findings show that teachers' use of language, appropriately structured activities, teaching materials, reference to peers, demonstration, and review all help scaffold young children's learning. By always being interactive with children, and encouraging interaction among them, teachers facilitate their discovery of creativity through their bodies.
All Ambient Processed Binary CsPbBr3 CsPb2Br5 Perovskites with Synergistic Enhancement for High Efficiency Cs Pb Br Based Solar Cells.
Venue: ACS applied materials interfaces
Year: 2018

All inorganic CsPbBr3 perovskite solar cells display outstanding stability toward moisture, light soaking, and thermal stressing, demonstrating great potential in tandem solar cells and toward commercialization. Unfortunately, it is still challenging to prepare high performance CsPbBr3 films at moderate temperatures. Herein, a uniform, compact CsPbBr3 film was fabricated using its quantum dot (QD) based ink precursor. The film was then treated using thiocyanate ethyl acetate (EA) solution in all ambient conditions to produce a superior CsPbBr3 CsPb2Br5 composite film with a larger grain size and minimal defects. The achievement was attributed to the surface dissolution and recrystallization of the existing SCN and EA. More specifically, the SCN ions were first absorbed on the Pb atoms, leading to the dissolution and stripping of Cs+ and Br ions from the CsPbBr3 QDs. On the other hand, the EA solution enhances the diffusion dynamics of surface atoms and the surfactant species. It is found that a small amount of CsPb2Br5 in the composite film gives the best surface passivation, while the Br rich surface decreases Br vacancies (VBr) for a prolonged carrier lifetime. As a result, the fabricated device gives a higher solar cell efficiency of 6.81% with an outstanding long term stability.
Novel butyrylcholinesterase inhibitors through pharmacophore modeling, virtual screening and DFT based approaches along with design of bioisosterism based analogues.
Venue: Biomedicine pharmacotherapy Biomedecine pharmacotherapie
Year: 2017

Ligand and structure based pharmacophore models were used to identify the important chemical features of butyrylcholinesterase (BChE) inhibitors. A training set of 16 known structurally diverse compounds with a wide range of inhibitory activity against BChE was used to develop a quantitative ligand based pharmacophore (Hypo1) model to identify novel BChE inhibitors in virtual screening databases. A structure based pharmacophore hypothesis (Phar1) was also developed with the ligand binding site of BChE in consideration. Further, the models were validated using test set, Fisher's Randomization and Leave one out validation methods. Well validated pharmacophore hypotheses were further used as 3D queries in virtual screening and 430 compounds were finally selected for molecular docking analysis. Subsequently, ADMET, DFT and chemical similarity search were employed to narrow down on seven compounds as potential drug candidates. Analogues of the best hit were further developed through a bioisosterism guided approach to further generate a library of potential BChE inhibitors.
J Tree: An Efficient Index using User Searching Patterns for Large Scale Data
Year: 2009

In recent years, with the development of portable terminals, various searching services on large data have been provided in portable terminals. In order to search large data, most applications for information retrieval use indexes such as B trees or R trees. However, only a small portion of the data set is accessed by users, and the access frequencies of each data are not uniform. The existing indexes such as B trees or R trees do not consider the properties of the skewed access patterns. And a cache stores the frequently accessed data for fast access in memory. But the size of memory used in the cache is restricted. In this paper, we propose a new index based on disk, called J tree, which considers user's search patterns. The proposed index is a balanced tree which guarantees uniform searching time on all data. It also supports fast searching time on the frequently accessed data. Our experiments show the effectiveness of our proposed index under various settings.
Simulacion dinamica de un sistema de produccion retroalimentado
Year: 2019

This paper shows a model of a feedback system of a connector assembly line. The feedback is established as a control system, where the result of certain variables such as pending orders to be delivered, are introduced again to the model in order to improve its performance. The dynamic model was developed in the simulation platform of the VensimPle software, student version, with the system dynamics methodology. The main results are that the feedback loops established in the model allow the productive system, inventory levels and production flows of the stations to remain stable; this considering two scenarios: production capacity greater and less than demand. It was demonstrated, when the client's requirement exceeds the productive capacity, pending orders are generated, but the levels of inventories and productive flows remain stable.
Deep convolutional neural networks for multi modality isointense infant brain image segmentation
Venue: NeuroImage
Year: 2015

The segmentation of infant brain tissue images into white matter (WM) gray matter (GM) and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6 8 months of age) WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multi modality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi modality images led to significant performance improvement.
Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non Negative Matrix Factorization
Venue: IEEE/ACM Transactions on Audio, Speech, and Language Processing
Year: 2016

Community question answering (CQA) has become an increasingly popular research topic. In this paper, we focus on the problem of question retrieval. Question retrieval in CQA can automatically find the most relevant and recent questions that have been solved by other users. However, the word ambiguity and word mismatch problems bring about new challenges for question retrieval in CQA. State of the art approaches address these issues by implicitly expanding the queried questions with additional words or phrases using monolingual translation models. While useful, the effectiveness of these models is highly dependent on the availability of quality parallel monolingual corpora (e.g. question answer pairs) in the absence of which they are troubled by noise issues. In this work, we propose an alternative way to address the word ambiguity and word mismatch problems by taking advantage of potentially rich semantic information drawn from other languages. Our proposed method employs statistical machine translation to improve question retrieval and enriches the question representation with the translated words from other languages via non negative matrix factorization. Experiments conducted on real CQA data sets show that our proposed approach is promising.
Factors affecting students' engagement with online content in blended learning
Venue: Kybernetes
Year: 2019

PurposeIncreasing use of information and communication technology (ICT) in education has, along with other consequences, shifted the context from teacher centric to student centric. These changes pose fresh challenges to the prevalent education systems all over the world, which already have fallen short of the expectations. The purpose of this study is to show that e learning is not only about ICT following a holistic approach to learning which embeds systemic approach and learning loops but also about students and teacher's actions in ICT enabled learning environment. This study investigates the importance of engagement of students and teachers in blended learning with a focus on factors which affect this engagement. on systems theory and socio technological approach to e learning, the paper documents an experiment which was carried out in a higher education institution. Postgraduate students of one course were divided into two groups. Instructor of the first group was not required to engage with the online content and had to deliver his course in a traditional face to face format. Instructor of the second group continuously spent time on the learning management system (LMS) developing more content, participating in online discussions and responding to students. LMS tracked the online activity of both the instructors, and semi structured interviews of students were conducted.FindingsBased on behaviour of 152 students of a postgraduate programme, students' time spent online is directly proportional to the instructor's online time, promptness of instructor's response to online activities queries of students increased student engagement, the students' engagement increases if the online content is related to the syllabus but engagement is not the same as the face to face lectures in the class.implicationsThe research was conducted in India and is based on the behaviour of instructors and students in India. It was focussed on engagement issues of blended learning, while other issues of blended learning have not been in the focus of the research.Practical implicationsThe research is important for the practice of higher education, and the result of the study can be taken into consideration while developing online courses for students enrolled in higher education.Social implicationsIf higher education institutions take a strategic decision to use ICT in e learning, engagements of participants and factors affecting engagement are crucial for the better quality of education. In such a way, blended learning fulfils requirements of a holistic approach to learning. the fact that e learning as a way to deliver academic content has been extensively researched, there are not many studies focussed on engagement issues in blended learning, and even fewer studies have been conducted in an experimental way which allow in depth research.
CNN Feature Based Image Copy Detection with Contextual Hash Embedding
Year: 2020

As one of the important techniques for protecting the copyrights of digital images, content based image copy detection has attracted a lot of attention in the past few decades. The traditional content based copy detection methods usually extract local hand crafted features and then quantize these features to visual words by the bag of visual words (BOW) model to build an inverted index file for rapid image matching. Recently, deep learning features, such as the features derived from convolutional neural networks (CNN) have been proven to outperform the hand crafted features in many applications of computer vision. However, it is not feasible to directly apply the existing global CNN features for copy detection, since they are usually sensitive to partial content discarded attacks, such as copping and occlusion. Thus, we propose a local CNN feature based image copy detection method with contextual hash embedding. We first extract the local CNN features from images and then quantize them to visual words to construct an index file. Then, as the BOW quantization process decreases the discriminability of these features to some extent, a contextual hash sequence is captured from a relatively large region surrounding each CNN feature and then is embedded into the index file to improve the feature's discriminability. Extensive experimental results demonstrate that the proposed method achieves a superior performance compared to the related works in the copy detection task.
Gnosticism And Christianity In Roman And Coptic Egypt
Year: 2016

gnosticism and christianity in roman and coptic egypt is available in our book collection an online access to it is set as public so you can get it instantly. Our books collection spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the gnosticism and christianity in roman and coptic egypt is universally compatible with any devices to read.
Pemikiran Islamisasi ilmu pengetahuan menurut Ismail Raji Al Faruqi
Year: 2016

Skripsi dengan judul "Pemikiran Islamisasi Ilmu Pengetahuan Menurut Ismail Raji Al Faruqi" ini adalah hasil penelitian kepustakaan yang dilakukan oleh peneliti guna untuk mengetahui latar belakang dari Islamisasi ilmu pengetahuan yang ditujukan untuk orang orang Muslim pada khususnya. Apalagi dengan adanya berbagai kemunduran yang dialami oleh umat Muslim ketika kebangkitan Barat. Dalam penelitian ini, peneliti menggunakan metode penelitian library research dengan pendekatan hermeneutik yaitu panafsiran, suatu upaya untuk memahami suatu makna atau maksud dalam suatu pemikiran agar tidak terjadinya kesalah pahaman. Adapun teknik pengumpulan data yang digunakan selama peneliti lakukan adalah dengan cara mengumpulkan data data dari buku buku, jurnal, maupun artikel. Dari penelitian yang dilakukan dapat dikatakan bahwa pengaruh Barat yang begitu signifikan telah membuat masyarakat Muslim tercengang, mulai hal pendidikannya, budaya, serta teknologi yang sangat cepat berkembang ke seluruh dunia. Masyarakat Muslim banyak yang taqlid dengan hal itu semua tanpa memikirkan apa dampak kedepannya. Apalagi dengan sikap yang seperti di jaman modern yang kapitalis seperti sekarang semakin merajalela sekulerisme, westernisasi di kalangan masyarakat Muslim pada khususnya. Sikap yang membuat masyarakat Muslim jauh dengan dunia spiritual. Pemikiran ummat diubahnya menjadi pemikiran sekuler yang hanya memikirkan kesenangan dunia tanpa memikirkan hal hal yang ukhrawi. Maka dari itu dapat disimpulkan bahwa munculnya ide Islamisasi ilmu pengetahuan yang dikemukakan oleh Ismail Raji Al Faruqi adalah untuk membangkitkan semangat orang orang Islam dalam mengembangkan ilmu pengetahuan yang berlandaskan tauhid. Ilmu apa saja yang ada di hadapan kita, yang kita pelajari baik itu ilmu ilmu agama maupun ilmu ilmu eksakta tetap tidak melakukan suatu hal yang melanggar aturan agama.
Financial Development and Inclusive Growth: Impact of Government Intervention in Prioritised Credit
Year: 2010

Equitable growth is indeed vital for inclusive growth which in turn can lead to sustainable growth. Access to finance by the poor is a prerequisite for poverty reduction and sustainable economic development. This study has established that there is a strong need to strengthen policy approach for financing the priority sector in India as it has had a positive impact on inclusive growth. In view of the strong relationship between priority sector lending and inclusive growth, it is imperative on the policy makers in general and the governments in particular to make efforts to induce the banks and financial institutions in increasing priority sector lending beyond the stipulations laid down
Image encryption algorithm for synchronously updating Boolean networks based on matrix semi tensor product theory
Venue: Inf. Sci.
Year: 2020

This paper studies chaotic image encryption technology and an application of matrix semi tensor product theory, and a Boolean network encryption algorithm for a synchronous update process is proposed. A 2D LASM chaotic system is used to generate a random key stream. First, a Boolean network is coded, and a Boolean matrix is generated. If necessary, the Boolean network matrix is diffused in one round so that the Boolean matrix can be saved in the form of an image. Then, three random position scramblings are used to scramble the plaintext image. Finally, using a matrix semi tensor product technique to generate an encrypted image in a second round of diffusion, a new Boolean network can be generated by encoding the encrypted image. In secure communications, users can choose to implement an image encryption transmission or a Boolean network encryption transmission according to their own needs. Compared with other algorithms, this algorithm exhibits good security characteristics.
Syddansk Universitet Effectiveness of a comprehensive interactive eHealth intervention on patient reported and clinical outcomes in patients with an implantable cardioverter defibrillator ACQUIRE ICD trial study protocol of a national Danish randomised controlled trial
Year: 2018

In Denmark and other countries, there has been a shift in the management of patients with an implantable cardioverter defibrillator (ICD) with remote device monitoring largely replacing in hospital visits. Less patient nurse and patient physician interaction may lead to gaps in patients' quality of care and impede patients' adaptation to living successfully with the ICD. A comprehensive eHealth intervention that include goal setting, monitoring of symptoms of depression, anxiety, and quality of life, psychological treatment, information provision, supportive tools, online dialogues with nursing staff and access to an online community network, may help fill these gaps and be particularly beneficial to patients who suffer from anxiety and depression. This study will evaluate the effectiveness of the ACQUIRE ICD care innovation, a comprehensive and interactive eHealth intervention, on patient reported and clinical outcomes.  The ACQUIRE ICD study is a multicenter, prospective, two arm, unblinded randomised controlled superiority trial that will enroll 478 patients implanted with a first time ICD or ICD with cardiac synchronisation therapy (CRT D) from the six implanting centers in Denmark. The trial will evaluate the clinical effectiveness and cost effectiveness of the ACQUIRE ICD care innovation, as add on to usual care compared with usual care alone. The primary endpoint, device acceptance, assessed with the Florida Patient Acceptance Survey, is evaluated at 12 months' post implant. Secondary endpoints, evaluated at 12 and 24 months' post implant, include patient reported outcomes, return to work, time to first ICD therapy and first hospitalisation, mortality and cost effectiveness. (Continued on next page) Correspondence: sspedersen@health.sdu.dk Department of Psychology, University of Southern Denmark, Campusvej 55, DK 5230 Odense M, Denmark Department of Cardiology, Odense University Hospital, Odense, Denmark Full list of author information is available at the end of the article (c) The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http:/creativecommons.org/licenses/by/4.0/ which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http:/creativecommons.org/publicdomain/zero/1.0/ applies to the data made available in this article, unless otherwise stated. Pedersen et al. BMC Cardiovascular Disorders (2018) 18:136 https:/doi.org/10.1186/s12872 018 0872 7
Using tabular notation to support model based testing: A practical experience using STTSpec and Spec Explorer
Venue: 2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
Year: 2020

Finite state machines are a widely used concept for specifying the behavior of reactive systems for development as well as for testing purpose. Numerous graphical notations based on finite state machines have been developed and are commonly used today, such as state transition diagrams, state charts, and Unified Modeling Language (UML) state machine diagrams. While not as widely used, tabular notations for state machine based specifications offer complementary advantages to diagrammatic notations. In this article, we describe an approach using tabular notations for state machine based specifications in Model Based Testing and we evaluate these approaches using Spec Explorer from Microsoft. We developed a tool, called STTSpec, to convert tabular notation from an Excel sheet to the C# input models of Spec Explorer, allowing us to do functional testing with the benefit of simplicity of tabular notation. We demonstrate this by applying our approach to an industrial size case study.
#PuffBar: how do top videos on TikTok portray Puff Bars?
Venue: Tobacco control
Year: 2020

Since 2 January 2020, the US Food and Drug Administration banned sales of all flavoured (other than menthol or tobacco) pod mod e cigarettes, like JUUL, that appeal to youth.1 However, the finalised policy exempted disposable e cigarettes such as Puff Bar, Posh, Eon Stik, Mr. Vapor and other brands that are illegally introduced into the market and gaining popularity among youth.2 The objective of this Industry Watch article is to describe how Puff Bar e cigarettes, a leading disposable e cigarette brand among youth,3 are portrayed on the popular Beijing based video sharing social media platform TikTok.4 Unlike other major e cigarette companies, information on the ownership of the Puff Bar company is unclear.5 We focused on TikTok specifically because 60% of the platform's 26.5 million active users in the USA in 2019 were between the ages of 16 and 24.6 TikTok's user guidelines prohibit the posting of 'content that depicts minors consuming, possessing, or suspected of consuming alcoholic beverages, drugs, or tobacco'.7 However, on other social media such as Facebook, enforcement of such policies to restrict promotion of tobacco products is lacking.8 Information on the