nils-herrmann/clean_scirepeval huggingface dataset:
Expressive Graph Informer Networks.
Year: 2019

Applying machine learning to molecules is challenging because of their natural representation as graphs rather than vectors.Several architectures have been recently proposed for deep learning from molecular graphs, but they suffer from informationbottlenecks because they only pass information from a graph node to its direct neighbors. Here, we introduce a more expressiveroute based multi attention mechanism that incorporates features from routes between node pairs. We call the resulting methodGraph Informer. A single network layer can therefore attend to nodes several steps away. We show empirically that the proposedmethod compares favorably against existing approaches in two prediction tasks: (1) 13C Nuclear Magnetic Resonance (NMR)spectra, improving the state of the art with an MAE of 1.35 ppm and (2) predicting drug bioactivity and toxicity. Additionally, wedevelop a variant called injective Graph Informer that isprovablyas powerful as the Weisfeiler Lehman test for graph isomorphism.Furthermore, we demonstrate that the route information allows the method to be informed about thenonlocal topologyof the graphand, thus, even go beyond the capabilities of the Weisfeiler Lehman test.
EFL Literacy Teaching in Relation to Teachers' Self Efficacy, Experience and Native Language
Year: 2021

English as a foreign language (EFL) literacy is necessary for the career success of non English speaking students. Many students lack adequate EFL literacy skills which may indicate a gap between EFL literacy instruction theory and practice. Teachers' self efficacy regarding their ability to teach reading and writing, years of teaching experience, and/or native language may influence their selection of components for EFL literacy instruction. This study examines these components as they are perceived by teachers. One hundred and sixty seven Israeli EFL elementary school teachers completed online questionnaires. Findings showed a weak correlation between teachers' self efficacy and their instructional approach. Teaching experience and teachers' native language did not influence their selection of EFL literacy instructional components or their sense of selfefficacy regarding their ability to teach reading and writing. Providing theoretical knowledge in teacher education to all types of EFL teachers may lead to more effective literacy instruction.
A consistency regularization based semi supervised learning approach for intelligent fault diagnosis of rolling bearing
Year: 2020

Deep learning has been widely used nowadays to achieve an automated fault diagnosis of rolling bearings. However, most of deep learning based bearing fault diagnosis methods are based on the assumption that the recorded samples are labeled data, though most of field data are recorded without label information. To address this issue, an effective semi supervised learning method based on the principle of consistency regularization is proposed in this study. The principle of consistency regularization underlines that the model predictions should be less sensitive to the extra perturbation imposed on the input samples. In the proposed method, a data augmentation method is proposed to serve as the extra perturbation, which is imposed on both the labeled and unlabeled samples to enrich the data library. Meanwhile, a label predicting process is formulated to estimate the appreciable label distribution for the unlabeled sample. Correspondingly, two consistency loss terms are introduced to regularize the model predictions for both the labeled and unlabeled samples to be invariant to the extra perturbation, among which a supervised loss term is adopted to enforce the model predictions for augmented labeled samples to be consistent with its true label information and an unsupervised loss is proposed to minimize the discrepancy between label distributions for the original unlabeled samples and its appreciable label distributions. The analysis result on an experimental bearing fault dataset demonstrates that the proposed method can provide an excellent identification performance under limited labeled samples situation.
Applying questioning or reading strategy to review technology enhanced coedited notes of elementary school students
Year: 2016

The authors examined whether applying questioning review better enhances elementary level students' learning from technology enhanced coediting based note taking than does traditional reading review. A nonequivalent comparison group quasi experimental design was implemented and replicated on four independent units. Two sixth grade elementary classes (66 students) participated in this study and were arranged into coediting notes with questioning review and coediting notes with reading review conditions respectively. The comparisons of student notes and achievement tests do not reveal that the questioning review group achieves better performance than does the reading review group. Considerations associated with technology enhanced coediting notes and questions are discussed based on the results.
Pengaruh Internet Terhadap Industri Ecommerce Dan Regulasi Perlindungan Data Pribadi Pelanggan Di Indonesia
Year: 2020

Penetrasi internet telah banyak menjangkau masyarakat umum di Indonesia. Jumlah pengguna internet yang ada saat ini mampu dimanfaatkan oleh para pelaku usaha khususnya dalam peningkatan ekonomi melalui industri ecommerce. Kehadiran teknologi baru seperti IoT dan Big Data, turut memberikan dorongan yang amat pesat terhadap kemajuan industri e commerce. E commerce lahir dari perkembangan teknologi yang semakin bergerak dengan cepat dan dipadukan dengan perkembangan ekonomi yang menuju ke arah digitalisasi. Tujuan dari penelitian ini adalah memberikan analisis deskriptif perkembangan industri e commerce di Indonesia, peran big data serta regulasi perundang undangan khususnya menyangkut perlindungan data pribadi. Metoda penelitian yang digunakan yaitu deskriptif kualitatif dengan pendekatan studi literatur untuk melacak data catatan peristiwa, yang selanjutnya digunakan oleh penulis untuk mengumpulkan data termasuk sumber dari penelitian sebelumnya. Hasil dan kesimpulan dari penelitian ini adalah peningkatan kesadaran pemerintah, pelaku usaha dan pelanggan serta warga negara Indonesia terhadap pentingnya perlindungan data pribadi dalam bentuk undang undang yang selanjutnya dapat memberikan rasa aman dan nyaman dalam melakukan proses jual beli maupun transaksi online di semua platform media e commerce.
Image based visual servoing using algebraic curves applied to shape alignment
Venue: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Year: 2009

Visual servoing schemes generally employ various image features (points, lines, moments etc. in their control formulation. This paper presents a novel method for using boundary information in visual servoing. Object boundaries are modeled by algebraic equations and decomposed as a unique sum of product of lines. We propose that these lines can be used to extract useful features for visual servoing purposes. In this paper, intersection of these lines are used as point features in visual servoing. Simulations are performed with a 6 DOF Puma 560 robot using Matlab Robotics Toolbox for the alignment of a free form object. Also, experiments are realized with a 2 DOF SCARA direct drive robot. Both simulation and experimental results are quite promising and show potential of our new method.
Pick Yourself Up: Dorothy Fields and the American Musical By Charlotte Greenspan. Oxford: Oxford University Press, 2010; pp. xx 288, 22 illustrations. $27.95 cloth.
Venue: Theatre Survey
Year: 2012

In his foreword to Pick Yourself Up: Dorothy Fields and the American Musical, Geoffrey Block, editor of Oxford University Press's Broadway Legacies series, notes the anonymity of lyricists who are not part of famous musical theatre partnerships such as Rodgers and Hammerstein (xi) Dorothy Fields's lyrics are memorable enough that President Obama quoted "Pick Yourself Up" from Swing Time during his inaugural address, but Fields herself is so anonymous that neither Obama nor those reporting on the address recognized or cited her as its lyricist (xii) More than a biography, musicologist Charlotte Greenspan's monograph seeks to rescue Fields from anonymity and offer readers a history of American stage and film musicals through the career of a lyricist whose collaborators are a "who's who" of Broadway and Hollywood. Fields's lyrics and libretti form a rich body of work through which to study the musical, and her versatility demonstrates the form's dynamism from the 1920s through the 1970s. Fields was the daughter of vaudevillian Lew Fields, and the sister of writers Joseph and Herbert Fields, making show business a family business for the "Fabulous Fieldses." In her book's first three chapters, Greenspan offers a thorough discussion of Lew Fields's Lower East Side childhood and his later success as a performer and impresario. Subsequent chapters chart Dorothy Fields's development as a lyricist and librettist contributing songs to Broadway revues, Harlem's Cotton Club, and Hollywood musicals before she reestablished herself in New York as a lyricist and librettist of book musicals. Chapters 5 through 8 chronicle Fields's lengthy collaboration with composer Jimmy McHugh, with whom she wrote hits such as "I Can't Give You Anything But Love," "I'm in the Mood for Love," and "I Feel a Song Coming On." The songwriting team's work on both coasts illustrates Broadway and Hollywood's close relationship in the 1920s and 1930s, and Greenspan effectively contrasts Fields's Broadway career with the security of Hollywood's contract system. Greenspan also provides much insight into the highs and lows of Fields's brother Herbert's Broadway career as a librettist, including his collaborations with Rodgers and Hart. Dorothy's own early failures highlight a radically different climate on Broadway than the one that exists there today. Both brother and sister continued to be employed despite their contributions to flop musicals, and as is
Man Xing Zu Sai Xing Fei Ji Bing Huan Zhe Xie Qing PCT, CRP, IL 6, TNF aDe Biao Da Shui Ping Ji Lin Chuang Yi Yi
Year: 2016

Mu De Guan Cha Man Xing Zu Sai Xing Fei Ji Bing (COPD)Huan Zhe Xie Qing Jiang Gai Su Yuan (PCT) CFan Ying Dan Bai (CRP) Bai Xi Bao Jie Su (IL 6) Zhong Liu Pi Si Yin Zi a(TNF a)De Biao Da Shui Ping Ji Lin Chuang Yi Yi Fang Fa 51Li Man Xing Zu Sai Xing Fei Ji Bing Ji Xing Jia Zhong Qi (AECOPD)Huan Zhe She Wei AECOPDZu ,50Li COPDWen Ding Qi Huan Zhe She Wei COPDZu ,Tong Qi Jian Kang Ti Jian Zhe 50Li She Wei Dui Zhao Zu ,Jian Ce 3Zu Xie Qing PCT, CRP, IL 6Ji TNF aShui Ping ,Fen Xi Qi Yu Fei Gong Neng He Sheng Huo Zhi Liang De Xiang Guan Xing Jie Guo PCT, CRP, IL 6Ji TNF aZai AECOPDZu COPDZu Ji Dui Zhao Zu Zhong Jun Cheng Zhu Jian Xia Jiang Qu Shi ,Liang Liang Bi Jiao ,Chai Yi You Tong Ji Xue Yi Yi (P<0.01) AECOPDZu FEV1%Ji FEV1/FVCJun Di Yu COPDZu ,Sheng Qiao Zhi Hu Xi Wen Juan (SGRQ)Ping Fen Gao Yu COPDZu (P<0.01) PearsonXiang Guan Xing Fen Xi Biao Ming ,Xie Qing Yan Zheng Yin Zi Yu Fei Gong Neng Zhi Biao Cheng Fu Xiang Guan ,Yu SGRQPing Fen Cheng Zheng Xiang Guan ( Zhu Yu Pan Ding Bing Qing Zhi Dao Zhi Liao Ji Ping Gu Yu Hou
Digital Supply Chain Management New Competitiveness Imperative for Economic Development
Year: 2020

The study introduced the concept of countries' digital development in the field of supply chain management (SCM) from the perspective of participation in global supply chains (GSC) A SWOT analysis of the proposed concept was performed, according to which, strengths, weaknesses, opportunities, and threats of the nation's involvement in GSCs were denoted. This research outlined the necessity for creating approaches and programs to ensure the logistics sector's digital growth for developed and developing nations and reduce modern unlevelled threats. The present study statistically verified the hypothesis that the improvement in the country's digital development contributes to the increase in its participation in GSCs. Within the research, indicators that determine the country's digital development in the context of SCM were selected. On their basis, digital profiles of the Russian Federation, Switzerland, Azerbaijan, and Cambodia were created and compared. As a result, the study disclosed competitive strategies in international trade for the countries under consideration. This research presented ways to strengthen the nations' competitive position in the world market and increase their digital competitiveness.
Emotion Recognition Based on Multi View Body Gestures
Venue: 2019 IEEE International Conference on Image Processing (ICIP)
Year: 2019

Body gesture, a crucial component of "body language" remains less explored to recognize emotion while face expression based and speech based approaches are widely investigated. In this paper, we introduce an exploratory experiment to recognize emotion using deep learning only from body gestures. 43,200 multi view RGB videos of simplified body gestures and their neutral control groups are captured from 80 humans using Hikvision network cameras to support the experiment. A novel approach is proposed to use deep neural network fuse skeleton and RGB features only using single modality RGB video data. Experimental results show our approach achieves substantial improvements both in individual categories and overall and is provided with stronger generalization capability as well.
SGDR: A simple GPS based disrupt tolerant routing for vehicular networks
Venue: 2017 International Conference on Information and Communication Technology Convergence (ICTC)
Year: 2017

The provision of Internet connectivity for a vehicle anywhere anytime is an essential element to realize the vision of Connected Car. However, we observe that the current vehicular network technologies mainly focus on single hop communications having limited coverage for the Internet connectivity. Accordingly, in order to support the always Internet connectivity, multi hop routing that can cover wider area should be considered in vehicular networks. This paper proposes a novel multi hop routing protocol for vehicular networks, called SGDR (Simple GPS based Disrupt tolerant Routing) that can provide efficient Internet connectivity even in infrastructure less environment. SGDR facilitates simple, efficient and practical multi hop networking for vehicular networks by adopting GPS based geographic and disrupt tolerant routing and by introducing VDTN bundle concept.
Small UAV Target Detection Model Based on Deep Neural Network
Year: 2018

Unmanned aerial vehicle (UAV) has relatively small size and weak visual characteristics. The recognition accuracy of traditional object detection methods can decrease sharply when complex background and distraction objects exist. In this paper, we proposed a novel deep neural network (DNN) model for small UAV target recognition task. Based on the visual characteristics of surveillance image and UAV target, a multi channel DNN is designed. Training and optimization of the DNN are completed with self constructed UAV image database. Simulation results show that the proposed DNN model can achieve good results in recognizing the variable scale UAV target and have compatible performance in distinguishing the interference and that the proposed model is robust and has a great potential prospect for engineering application.
Adolescent Sense of Belonging in Outdoor Adventure Education: The Influence of Conflict and Instructors
Year: 2019

Outdoor adventure education programs are strategically positioned to provide a multitude of positive social outcomes for youth. The social connections adolescents develop with their peers are critically important for positive youth development. This study sought to understand how sense of belonging develops within a wildernessbased outdoor adventure education program while using a dynamical systems theory (DST) framework and analysis. The findings showed that groupbased components, such as process conflict influenced the rate of change while instructor support increased the level of sense of belonging students felt. Implications for research and practice are discussed.
Professional Survival in a Neoliberal Age: A Case Study of an EFL Teacher in China
Year: 2017

This study explored the negotiation of a Chinese EFL teacher's teaching identity in light of recent critique of neoliberalism. Ms. Q, our focal participant, worked in a private English school that commodified English, and her main teaching responsibility was to prepare students for the IELTS test. We adopted an agency centered approach to explore how Ms. Q's professional identity was negotiated in relation to the exercise and investment of her professional agency. In particular, Haneda and Sherman's (2016) job crafting perspective on teacher agency was adopted to illustrate how Ms. Q was able to go beyond the prescribed teaching role assigned by the school. This move, in turn, contributed to her teacher identity development because she was able to exercise agency within the affordances and constraints of the given work context. Our data include classroom observation, interviews with Ms. Q and her students, Ms. Q's teaching materials and her posts in a Chinese social network (Wechat) Our findings revealed that Ms. Q's investment in constructing the desired teacher identity, that is, to be a good educator, supported her to transcend the prescribed space for teaching practice and make agentic decisions in the classroom that were in accordance with her teaching beliefs.
MECHANICAL PROPERTIES CHARACTERIZATIONS OF GREEN COMPOSITES MADE FROM POLY (LACTIC ACID) AND VARIOUS MILLED FIBERS WITH A MELT MIXING EXTRUDER FOR ADDITIVE MANUFACTURING APPLICATIONS
Year: 2017

In the present study, as a preliminary report of the present authors on "On Additive Manufacturing of Green Composites" poly(lactic acid) PLA, composites, which is reinforced with two different kinds of reinforcing fibers in the form of milled filler, i.e. kenaf and carbon fibers, were molded by melt mixing and then filament extruding processes to make green composite filaments for 3D printing additive manufacturing purposes. From tensile test results of single monofilaments extruded from a FDM (Fused Deposition Modeling) 3D printer with a nozzle of 1mm diameter, it was found that the milled carbon fibers were able to reinforce PLA, while milled kenaf fibers and, for comparison purpose, cellulose base nano fillers were found to make little contribution for improvement in terms of strength and modulus of the present additive manufactured green composites. From the scanning electron microscope (SEM) fractography of the fracture surfaces in the present green composites, interface imperfections between PLA matrix and reinforcing fibers except carbon fibers, unevenness of reinforcing fiber distribution as well as existence of resin rich portions in the composites may have affected the present poor results obtained in this preliminary study.
Effect of galvanneal coating evolution during press hardening on laser welding of 22MnB5 steel
Venue: Science and Technology of Welding and Joining
Year: 2019

Understanding phase evolution and growth kinetics of Zn coating during press hardening is essential in predicting welding behaviour of press hardened 22MnB5 steel. The results showed that during press hardening, the initial d and G G1 phases in the coating transform into a Fe(Zn) G, and ZnO phases. As heat treating continued at a constant temperature, the a Fe(Zn) thickness grew and the overall Zn content decreased. This resulted in the full penetration weld window shifting towards higher heat inputs. However, when heat treating at higher temperatures, severe oxidation and Fe Zn inter diffusion led to the reduction of Zn content in the evolved coating. It was found that higher heat treatment times resulted in wider weld beads, thereby increasing joint strength.
ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades
Venue: ArXiv
Year: 2020

Word embeddings learn implicit biases from linguistic regularities captured by word co occurrence information. As a result, statistical methods can detect and quantify social biases as well as widely shared associations imbibed by the corpus the word embeddings are trained on. By extending methods that quantify human like biases in word embeddings, we introduce ValNorm, a new word embedding intrinsic evaluation task, and the first unsupervised method that estimates the affective meaning of valence in words with high accuracy. The correlation between human scores of valence for 399 words collected to establish pleasantness norms in English and ValNorm scores is r=0.88. These 399 words, obtained from social psychology literature, are used to measure biases that are non discriminatory among social groups. We hypothesize that the valence associations for these words are widely shared across languages and consistent over time. We estimate valence associations of these words using word embeddings from six languages representing various language structures and from historical text covering 200 years. Our method achieves consistently high accuracy, suggesting that the valence associations for these words are widely shared. In contrast, we measure gender stereotypes using the same set of word embeddings and find that social biases vary across languages. Our results signal that valence associations of this word set represent widely shared associations and consequently an intrinsic quality of words.
Evaluation of Kocarli Adnan Menderes urban forest in terms of the ecotourism
Year: 2011

The aim of this research is to evaluate the natural and ecological features of Kocarli Adnan Menderes Urban Forest with regard to the suitability for ecotourism. Design suggestions will be presented to develop the Urban Forest. Continuity in public transportation will eliminate the problems of access. Kocarli Adnan Menderes Urban Forest is not only a very considerable ecotourism area for people who live in Kocarli and near villages but also for people living in Aydin and other districts. Activities in Kocarli Adnan Menderes Urban Forest ensure social and cultural improvement of the people and economic development of the region.
A review of therapeutic agents and Chinese herbal medicines against SARS COV 2 (COVID 19)
Venue: Pharmacological Research
Year: 2020

The epidemic of pneumonia (COVID 19) caused by novel coronavirus (SARS CoV 2) infection has been listed as a public health emergency of international concern by the World Health Organization (WHO) and its harm degree is defined as a global "pandemic" At present, the efforts of various countries focus on the rapid diagnosis and isolation of patients, as well as to find a treatment that can combat the most serious impact of the disease. The number of reported COVID 19 virus infections is still increasing. Unfortunately, no drugs or vaccines have been approved for the treatment of human coronaviruses, but there is an urgent need for in depth research on emerging human infectious coronaviruses. Clarification transmission routes and pathogenic mechanisms, and identification of potential drug treatment targets will promote the development of effective prevention and treatment measures. In the absence of confirmed effective treatments, due to public health emergencies, it is essential to study the possible effects of existing approved antivirals drugs or Chinese herbal medicines for SARS CoV 2. This review summarizes the epidemiological characteristics, pathogenesis, virus structure and targeting strategies of COVID 19. Meanwhile, this review also focus on the re purposing of clinically approved drugs and Chinese herbal medicines that may be used to treat COVID 19 and provide new ideas for the discovery of small molecular compounds with potential therapeutic effects on novel COVID 19.