nils-herrmann/clean_scirepeval huggingface dataset:
Ownership, Privacy, and Control in the Wake of Cambridge Analytica: The Relationship between Attitudes and Awareness
Venue: CHI
Year: 2020

Has widespread news of abuse changed the public's perceptions of how user contributed content from social networking sites like Facebook and LinkedIn can be used? We collected two datasets that reflect participants' attitudes about content ownership, privacy, and control, one in April 2018, while Cambridge Analytica was still in the news, and another in February 2019, after the event had faded from the headlines, and aggregated the data according to participants' awareness of the story, contrasting the attitudes of those who reported the greatest awareness with those who reported the least. Participants with the greatest awareness of the news story's details have more polarized attitudes about reuse, especially the reuse of content as data. They express a heightened desire for data mobility, greater concern about networked privacy rights, increased skepticism of algorithmically targeted advertising and news, and more willingness for social media platforms to demand corrections of inaccurate or deceptive content.
Comparative Analysis of Clinical Parameters and Sputum Biomarkers in Establishing the Relevance of Filamentous Fungi in Cystic Fibrosis
Venue: Frontiers in Cellular and Infection Microbiology
Year: 2020

The relationship between fungal culture (FC) positivity and airway inflammation in CF is largely unknown. Identifying the clinical significance of filamentous fungi in CF using both clinical parameters and biomarkers may change our antimicrobial therapeutic strategies.  To investigate the clinical characteristics and airway biomarker profile in relation to the detection of filamentous fungi in respiratory samples obtained from CF patients.  A prospective cohort study over 24 months, including children and adults with CF. Participants provided sputum and/or bronchoalveolar lavage samples, which underwent processing for bacterial and fungal culture, leukocyte differential cell count and biomarker analysis for neutrophil elastase (NE) interleukin 8 (IL 8) galactomannan and tumor necrosis factor receptor type 2 (TNF R2) We performed FC using neat sputum plugs, an approach shown to be more sensitive compared to routine laboratory testing.  Sixty one patients provided 76 respiratory samples (72 sputum and 4 BAL) Median age was 17 years (range 6 months 59 years) FC positivity was noted in 49% of the cohort. FC positivity was greater during pulmonary exacerbation compared to the stable state (67 versus 50% Participants aged 5 30 years had a lower FEV1 within the FC positive group. A significant association between FC positivity and non tuberculosis mycobacterial (NTM) culture was observed on non parametric testing (p 0.022) and regression analysis (p 0.007) Exposure to indoor mold was a predictor for FC positivity (p 0.047) There was a trend towards increased lung clearance index (LCI) bronchiectasis and intravenous antibiotic use in the FC positive group. There was no significant difference in biomarkers between FC positive and negative patients. . fumigatus is the commonest filamentous fungi cultured from CF airways. We found no difference in the airway biomarker profile between FC positive and negative patients. The role of galactomannan and TNFR2 as fungal specific biomarkers in CF remains uncertain. FC positivity is associated with a lower FEV1 in younger patients, a lower LCI, NTM positivity, bronchiectasis, and intravenous antibiotic exposure. Larger trials are needed to determine the role of galactomannan and TNF R2 as potential fungal biomarkers in CF.
Silicon nanodot based aptasensor for fluorescence turn on detection of mucin 1 and targeted cancer cell imaging.
Venue: Analytica chimica acta
Year: 2018

We report herein a new dual color fluorescent aptasensor for detection of tumor marker mucin 1 (MUC1) and targeted imaging of MCF 7 cancer cells based on the specific interaction between MUC1 and its aptamer S2.2. The aptasensor was prepared by covalent attachment of the cyanine (Cy5) tagged aptamer S2.2 to fluorescent silicon nanodot (SiND) The fluorescence of S2.2 Cy5 could be quenched by the SiND carrier in the absence of MUC1, and its fluorescence was restored in the presence of MUC1 due to structure switching of S2.2. This aptasensor exhibits specificity for MUC1 possitive MCF 7 cells rather than MUC1 negative MCF 10A cells and Vero cells. The SiND plays multiple roles in this fluorescence assay, making the method easier compared with other approaches. The limit of detection and precision of this method for MUC1 was 1.52 nM and 3.6% (10 nM, n 7) respectively. The linear range was 3.33 250 nM, and the recoveries in spiked human serum were in the range of 87 108% This is a simple, selective, sensitive and reliable method, which can well achieve not only quantitative analysis of tumor marker but also dual color visualization of single cancer cells.
Faktor Faktor Internal Individual Dalam Pembuatan Keputusan Etis: Studi Pada Konsultan Pajak Di Kota Surabaya
Year: 2016

This study aims to examine the influence of individual factors (perception of the importance of ethical and social responsibility; machiavellianism; ethical reasoning) toward ethical decision making of tax consultants. This study used 50 tax consultants as the study samples in Tax Consultant Office in Surabaya. The method of data analysis using regression analysis. This study reveals perception of the importance of ethical and social responsibility have positive influence toward ethical decision making by tax consultant, machiavellianism have negative influence toward ethical decision making by tax consultant and ethical reasoning have positive imfluence toward ethical decision making. The implication of this study is a person who has a high perception of the importance of ethical and responsibility supporting that person to conduct ethical decision making. The General Director of Taxation or the official which is delegated in issuing tax practical license needed to conduct a machiavellianism trait test from tax consultant itself. Besides, it also takes to be ensured that the tax consultant who have had the licence is an individual who has a high moral maturity (post conventional stage) so that the possibilities will be less to approve the non ethical act and more independent in decision making which is related to ethical dilemma.
A Mixed Neural Network and Support Vector Machine Model for Tender Creation in the European Union TED Database
Year: 2019

This research article proposes a new method of automatized text generation and subsequent classification of the European Union (EU) Tender Electronic Daily (TED) text documents into predefined technological categories of the dataset. The TED dataset provides information about the respective tenders includes features like Name of project, Title, Description, Types of contract, Common procurement vocabulary (CPV) code, and Additional CPV codes. The dataset is obtained from the SIMAP Information system for the European public procurement website, which is comprised of tenders described in XML files. The dataset was preprocessed using tokenization, removal of stop words, removal of punctuation marks etc. We implemented a neural machine learning model based on Long Short Term Memory (LSTM) nodes for text generation and subsequent code classification. Text generation means that given a single line or just two or three words of the title, the model generates the sequence of a whole sentence. After generating the title, the model predicts the main applicable CPV code for that title. The LSTM model reaches an accuracy of 97% for the text generation and 95% for code classification using Support Vector Machine(SVM) This experiment is a first step towards developing a system that based on TED data is able to auto generate and code classify tender documents, easing the process of creating and disseminating tender information to TED and ultimately relevant vendors. The development and automation of this system will future vision and understand current undergoing projects and the deliveries by a SIMAP Information system for European public procurement tenders organisation based on the tenders published by it.
Seamless Compiler Integration of Variable Precision Floating Point Arithmetic
Venue: 2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)
Year: 2021

Floating Point (FP) units in processors are generally limited to supporting a subset of formats defined by the IEEE 754 standard. As a result, high efficiency languages and optimizing compilers for high performance computing only support IEEE standard types and applications needing higher precision involve cumbersome memory management and calls to external libraries, resulting in code bloat and making the intent of the program unclear. We present an extension of the C type system that can represent generic FP operations and formats, supporting both static precision and dynamically variable precision. We design and implement a compilation flow bridging the abstraction gap between this type system and low level FP instructions or software libraries. The effectiveness of our solution is demonstrated through an LLVM based implementation, leveraging aggressive optimizations in LLVM including the Polly loop nest optimizer, which targets two backend code generators: one for the ISA of a variable precision FP arithmetic coprocessor, and one for the MPFR multi precision floating point library. Our optimizing compilation flow targeting MPFR outperforms the Boost programming interface for the MPFR library by a factor of 1.80 x and 1.67 x in sequential execution of the Poly Bench and RAJAPerf suites, respectively, and by a factor of 7.62 x on an 8 core (and 16 thread) machine for RAJAPerf in OpenMP.
Fictional Characters in the Eighteenth Century Literary Commons
Venue: Characters Before Copyright
Year: 2019

The final chapter shows that fan fiction was treated as raising legal issues separate from piracy. This chapter argues that, because authors were newly vested with the legal capacity to hold rights in their literary creations, literary characters were not free to be appropriated however readers wished. Rather, literary characters constituted a distinctive form of communal property, the use of which was subject to conditions. Chapter 6 thus redefines the "literary commons" of eighteenth century Germany, providing a new perspective on the rise of intellectual property rights. This chapter proposes a reevaluation of the concept of literary property, the history of moral rights, and the tradition of free culture.
RESTful Web Services: Principles, Patterns, Emerging Technologies
Venue: Web Services Foundations
Year: 2014

Recent technology trends in Web services indicate that a solution eliminating the perceived complexity of the WS standard technology stack may be in sight: advocates of Representational State Transfer (REST) have come to believe that their ideas explaining why the World Wide Web works are just as applicable to solve enterprise application integration problems and to radically simplify the plumbing required to implement a Service Oriented Architecture (SOA) In this tutorial we give an introduction to the REST architectural style as the foundation for RESTful Web services. The tutorial starts from the basic design principles of REST and how they are applied to service oriented computing. Service orientation concentrates on identifying selfcontained units of functionality, which should then be exposed as easily reusable and repurposable services. This tutorial focuses not on the identification of those units, but on how to design the services representing them. We explain how decisions on the SOA level already shape the architectural style that will be used for the eventual IT architecture, and how the SOA process itself has to be controlled to yield services which can then be implemented RESTfully. We do not claim that REST is the only architectural style that can be used for SOA design, but we do argue that it does have distinct advantages for loosely coupled services and massive scale, and that any SOA approach already has to be specifically RESTful on the business level to yield meaningful input for IT architecture design.
PENDAMPINGAN IMPLEMENTASI PEMBELAJARAN MATEMATIKA BERBASIS PENDIDIKAN MATEMATIKA REALISTIK DAN HIGH ORDER THINKING SKILLS
Year: 2020

Guru matematika di Kabupaten Bantul, Yogyakarta, banyak yang mengalami kesulitan dalam menerapkan pembelajaran matematika berbasis Pendidikan Matematika Realistik (PMR) dan High Order Thinking Skills (HOTS) Banyak kendala yang dirasakan oleh guru sehingga perlu adanya pendampingan bagi guru dalam melaksanakan pembelajaran matematika berbasis PMR dan HOTS. Artikel ini mengulas tentang implementasi PMR dan HOTS pada kegiatan pembelajaran di kelas. Peserta pelatihan terdiri dari 54 guru dari 54 sekolah Muhammadiyah di Kabupaten Bantul. Implementasi dibagi menjadi 3 kelompok yaitu kelompok Timur, Barat, dan Selatan. Metode yang digunakan yaitu Lesson Study dalam kelompok beranggotakan 15 19 guru. Implementasi dilakukan sebanyak 3 kali di waktu yang berbeda dan sekolah yang berbeda pula. Hasil dari kegiatan ini yaitu para guru berhasil menyusun desain PMR dan HOTS yang diimplementasikan pada kegiatan pembelajaran matematika di kelas.
Design Patterns for Smart Contracts in the Ethereum Ecosystem
Venue: 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Year: 2018

The idea to digitally facilitate contract law and business practices through computer programs has led to the notion of smart contracts. Today's most prominent smart contract ecosystem is Ethereum, a blockchain based distributed computing platform. Due to the inherent nature of blockchain based contract execution, missing low level programming abstractions, and the constant evolution of platform features and security considerations, writing correct and secure smart contracts for Ethereum is a difficult task. Based on a Multivocal Literature Research and an analysis of the gathered data based on qualitative research methods, we mined a number of design patterns providing design guidelines. We describe those patterns in detail and provide exemplary code for better illustration. Our research shows that the patterns are widely used to address application requirements and common problems. We expect generalizability of some or all of the patterns for other smart contract ecosystems, but this is outside of the scope of this study, which studied only smart contract patterns in Ethereum.
Visual detection and recognition for medical infusion automatic production lines
Year: 2014

The detection of filling quality for pharmaceutical is an important element in pharmaceutical process,which guarantees the medication security.According to the detection demand of visible foreign substances for glass bottle medical infusion,a high speed automated foreign substance detection system based on the machine vision consisting of multi types image acquisition devices is developed.Firstly,a high speed high reliability preprocessing method for medical infusion images is proposed to eliminate the disturbance caused by mechanical vibration and tracking.Then,an improved fuzzy cellular neural network(IFCNN) is developed for image segmentation to effectively solve the problem of edge detection,which reveals the mechanism of foreign substances,particles as well as liquid bubbles,comprehensively analyzes the morphological boundary of the target operating characteristics,and obtains various characteristics and the dynamic change information in image sequences.Finally,the classification approaches of support vector machine(SVM) and AdaBoosting,based on image sequences target characteristics,is employed to recognize multiple tiny insoluble foreign substances.Experimental results indicate that the developed approach is efficient and increases the recognition rate,which is of great significance to the development of engineering equipment.
ImageCLEF 2019: Deep Learning for Tuberculosis CT Image Analysis
Venue: CLEF
Year: 2019

In this article, we present the methodologies used in our participation in the two subtasks of the ImageCLEF 2019 Tuberculosis Task (SVR and CTR) Our contributions are essentially based on deep learning and other machine learning techniques. In addition to the use of deep learners, semantic descriptors are tested to represent patients CT scans. These features are extracted after a first learning step. Our submissions on the test corpus reached AUC value of about 65% in the SVR task and an average AUC value of about 63% in CTR. These results offered us the seventh and the eighth places in SVR and CTR, respectively. We believe that our contributions could be further improved and might give better results if they applied properly and in an optimized way.
Surfing the Deeper Levels of Consciousness: Emotions Mental Health
Year: 2020

If we want to understand some of the requisites for mental health, we first have to know what we mean by mental, which is related to the term mind. For this, we need to explore the topographical nature of consciousness from the 'inside out' position. Only by doing this, can we begin to understand the nature of consciousness and the different levels of mind. The exploration of our inherent nature is a natural art where we use our will to direct the cursor awareness of our surface mind into the inner, deeper realms of their being. For people who have forgotten how to do this, certain somatic focusing heart based methods of meditation may assist them. As the deeper levels of consciousness below our thinking mind, are linked with sensations, feelings, and emotions, it is important to learn more about them, especially as many mental health disorders are linked with emotions, including those related to violence. When an emotion such as anger has become part of our repressed shadow personality, it may erupt with very little provocation causing us to act in a violent way that is inappropriate to the situation. Shadow emotions can also be projected onto others, which may result in aggressive and violent acts against another or even a collective body of people. As such, learning about the different levels of consciousness, and how to bring our repressed emotions to the light by learning how to 'surf' the different bodily sensations that arise during meditation, warrant more scientific attention and investigation.
Does Corporate Social Responsibility Lead to Superior Financial Performance? A Regression Discontinuity Approach
Venue: Manag. Sci.
Year: 2015

This study examines the effect of shareholder proposals related to corporate social responsibility CSR on financial performance. Specifically, I focus on CSR proposals that pass or fail by a small margin of votes. The passage of such "close call" proposals is akin to a random assignment of CSR to companies and hence provides a quasi experiment to study the effect of CSR on performance. I find that the adoption of close call CSR proposals leads to positive announcement returns and superior accounting performance, implying that these proposals are value enhancing. When I examine the channels through which companies benefit from CSR, I find that labor productivity and sales growth increase after the vote. Finally, I document that close call CSR proposals differ from non close proposals along several dimensions. Accordingly, although my results imply that adopting close call CSR proposals is beneficial to companies, they do not necessarily imply that CSR proposals are beneficial in general. Data, as supplemental material, are available at http:/dx.doi.org/10.1287/mnsc.2014.2038 This paper was accepted by Wei Jiang, finance.
Customer churn prediction in telecom using machine learning in big data platform
Venue: Journal of Big Data
Year: 2019

Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customer to churn. Therefore, finding factors that increase customer churn is important to take necessary actions to reduce this churn. The main contribution of our work is to develop a churn prediction model which assists telecom operators to predict customers who are most likely subject to churn. The model developed in this work uses machine learning techniques on big data platform and builds a new way of features' engineering and selection. In order to measure the performance of the model, the Area Under Curve (AUC) standard measure is adopted, and the AUC value obtained is 93.3% Another main contribution is to use customer social network in the prediction model by extracting Social Network Analysis (SNA) features. The use of SNA enhanced the performance of the model from 84 to 93.3% against AUC standard. The model was prepared and tested through Spark environment by working on a large dataset created by transforming big raw data provided by SyriaTel telecom company. The dataset contained all customers' information over 9 months, and was used to train, test, and evaluate the system at SyriaTel. The model experimented four algorithms: Decision Tree, Random Forest, Gradient Boosted Machine Tree "GBM" and Extreme Gradient Boosting "XGBOOST" However, the best results were obtained by applying XGBOOST algorithm. This algorithm was used for classification in this churn predictive model.
Analisis Kualitas Butir Soal UTS Mata Pelajaran IPA Tahun Pelajaran 2019/2020 Kelas VII di SMPN 6 Kota Langsa
Year: 2020

The purpose of this study is to determine the quality of the results of the vii class science class in 2019/2020, a class of validity, reliability, depth of adversity and contrasting power. And this study USES a descriptive method. The subject in this study is a student class vii middle school n 6 langsa. Data collection techniques are done using methods of documentation and observation. Data obtained use manual calculations by helping excel programs.  based on reclassification power, from exam problems are low, only article no. 4 has enough categories. (4) for her level of suffering from no. 1 to no. 5, she was categorized as a simple group. Tests are good as a gauge when they meet the following requirement: good validity, good reliability, good objectivity, normal practicality and good economic value. Well, according to research conducted, the fact that entire grains of matter were rated as inferior. Because of validity, reliability, contrition power and severity it does not meet well defined standard scores.