Miracle-dz/UniFAR-FTUs huggingface dataset:
Overview of the effects of chemical mixtures with endocrine disrupting activity in the context of real-life risk simulation: An integrative approach (Review)

Research over the past years has indicated that chronic human exposure to very low doses of various chemical species in mixtures and administered via different routes (percutaneous, orally, etc.) should be the main focus of new biochemical and toxicological studies. Humans have daily contact with various chemicals, such as food additives, pesticides from fruits/vegetables, antibiotics (and other veterinary drugs) from meat, different types of preservatives from cosmetics, to name a few. Simultaneous exposure to this wide array of chemicals does not produce immediate effects, but summative effect/s over time that may be clinically manifested several years thereafter. Classical animal studies designed to test the toxic outcome of a single chemical are not suitable to assess, and then extrapolate to humans, the effects of a whole mixture of chemicals. Testing the aftermath of a combination of chemicals, at low doses, around or below the no observed adverse effect is stressed by many toxicologists. Thus, there is a need to reformulate the design of biochemical and toxicological studies in order to perform real-life risk simulation. This review discuss the potential use of computational methods as a complementary tool for in vitro and in vivo toxicity tests with a high predictive potential that could contribute to reduce animal testing, cost and time, when assessing the effects of chemical combinations. This review focused on the use of these methods to predict the potential endocrine disrupting activity of a mixture of chemicals.
Método para sistemas de recomendaciones sensibles al contexto en entornos turísticos/Method of Context Aware Recommender System in Tourist Environment

Este trabajo se centra en el desarrollo de un metodo de sistemas de recomendaciones hibrido sensible al contexto basado en ontologias en el entorno de las Infraestructuras de Datos Espaciales, que impacte positivamente en la efectividad de la toma de decisiones en las aplicaciones para usuarios de sistemas moviles en el sector turistico. El metodo elaborado cuenta de tres fases: marco semantico y de datos, otra que implementa el sistema de recomendaciones y una encargada de la visualizacion de las recomendaciones. La fase de sistema de recomendaciones implementa un filtro espacial, un filtro semantico y otro colaborativo. Las recomendaciones generadas muestran los elementos de posible interes, estas pueden ser visualizadas en forma tabular o combinadas con informacion espacial. Se comprobo por medio de un experimento y diferentes metricas aplicadas, el incremento en la efectividad del mismo para usuarios moviles segun sus preferencias en cuanto a las recomendaciones dadas en un entorno espacial. ABSTRACT This paper focuses on developing a method of hybrid context-aware recommender systems, based on ontologies in the environment of the Spatial Data Infrastructure, which will positively impact the effectiveness of decision-making in the tourist applications for mobile users. The method developed has three components: data and semantic framework, other that implements the recommender system and another responsible for displaying the recommendations. The recommender system component implements a spatial, a semantic and collaborative filters. The recommendations generated show the elements of potential interest, these can be displayed in tabular or combined with spatial information. It was found through an experiment and different applied metrics the increase in its effectiveness for mobile users according to their preferences as to the recommendations given in a spatial environment.
Delay Learning in a Biologically Plausible Reservoir Computing Model

In this thesis, a reservoir model created by Paugam-Moisy et al. (2008) was replicated, and subsequently modiﬁed to be more biologically plausible. The use of a diﬀerent neuron model and STDP function had no negative impact on performance. For the delay learning mechanism, replacing delay adaptation with delay selection proved viable, but did result in somewhat lower performance. It was discovered here that the reservoir in this model served no purpose. Therefore, the use of a small-world Watts-Strogatz reservoir instead of a randomly connected reservoir, could not aﬀect performance.
X-Ray Near-Field Holography: Beyond Idealized Assumptions of the Probe

All images are flawed, no matter how good your lenses, mirrors etc. are. Especially in the hard X-ray regime it is challenging to manufacture high quality optics due to the weak interaction of multi-keV photons with matter. This is a tremendous challenge for obtaining high resolution quantitative X-ray microscopy images. In recent years lensless phase contrast imaging has become an alternative to classical absorption-based imaging methods. Without any optics, the image is formed only by the free space propagation of the wave field. The actual image has to be formed posteriori by numerical reconstruction methods. Advanced phasing methods enable the experimentalist to recover a complex valued specimen from a single or a set of intensity measurement. This would be the ideal case - reality teaches us that there are no ideal imaging conditions. Describing, understanding and circumventing these non ideal imaging conditions and their effects on X-ray near-field holographic (NFH) imaging are the leitmotifs for this thesis. In NFH the non ideal conditions manifest themselves in the illuminating wave field or probe. The probe generally does not satisfy the canonical assumptions of fully coherent and monochromatic radiation emitted by a point source. The main results of this thesis are compiled as a collection of publications. An approach is shown to reconstruct the probe of a X-ray nano-focus setup by a series of measurements of the probe at varied Fresnel number. The following chapter presents a study concerning the reconstruction efficiency in terms of resolution for near- and far-field based lensless imaging. In the following, the reconstruction scheme for the probe is extended to incorporate the effects of partial coherence in the near field. This enables the recovery of the modal structure of the probe which yields a full description of its coherence properties. Giving up the assumption of temporal stability due to the stochastic pulses, delivered by X-ray free electron lasers, the reconstruction of probe and specimen must be achieved from a single shot. A suitable scheme for this purpose is proposed in this work.
Improved Ant Colony Scheduling Algorithm for High-score Data Storage Model Based on Cloud Platform

In order to find the optimal scheduling, to ensure the global optimization, and to adapt to the dynamic environment, the adaptive capacity remote sensing data cloud platform scheduling strategy is proposed based on the cloud platform high score data storage model. The main contents are as follows. The characteristics of the task of high score data in cloud environment are analyzed, and the applicability of ant colony algorithm in task scheduling of cloud computing platform is pointed out. The initial set of ant colony algorithm is optimized by combining the two parts. The quality of service (QoS) is used as the ant colony algorithm pheromone, and the ant colony algorithm scheduling strategy with QoS and double pheromone updating model are designed. It can be observed that in the process of dealing with large-scale data tasks, the traditional ACO algorithm needs to be further considered node load balancing problem. And the scheduling algorithm to node QoS is as a pheromone, the resource node reliability, response time and load rate are taken into account as it is in task scheduling, which makes the node with better performance easy to be selected. It can be concluded that this strategy can improve the traditional ant colony algorithm and get the local optimal solution. At the same time, the load balance of the resource node is improved to a certain extent.
Analisis dan Implentasi Content Based Image Retrieval Menggunakan Metode ORB

Pada citra retrieval terdapat dua metodologi untuk memanggil data yang ada pada basis data, yang pertama dengan text-based yaitu dengan menggunakan text sebagai suatu kunci pada pencariannya dan yang kedua adalah content-based yang menggunakan suatu content tertentu sebagai kuncinya. Salah satu kekurangan dari text-based adalah sulitnya mencari kata kunci pada data yang ingin dicari terutama pada data multimedia seperti video, gambar, dan suara. Kata kunci yang tidak tepat memungkinkan user akan mendapatkan data yang tidak tepat ketika menginputkan suatu text untuk mencari data multimedia karena terlalu banyaknya data multimedia pada basis data. Berbeda dengan text-based, content-based menggunakan sebuah fitur seperti bentuk, warna, tekstur, dan titik untuk mencari data sehingga akurasi pada data yang diinginkan akan lebih baik dibandingkan dengan menggunakan suatu kata untuk mencari data multimedia. Dengan mencocokkan fitur pada gambar yang diinput dengan pada fitur gambar yang ada pada basis data, sistem akan menampilkan data sesuai dengan kecocokkannya. Teknik tersebut biasa disebut dengan Content-Based Image Retrieval (CBIR). Dibutuhkan akurasi yang baik agar pengembalian data yang dicari akan tepat pada data yang diinputkan, metode ORB akan diimplementasikan pada sistem CBIR karena memiliki akurasi yang baik pada image retrieval. Metode ORB menggunakan fitur keypoint pada data sebagai kunci pencariannya. Akurasi sistem CBIR dengan menggunakan metode ORB dapat mencapai 90.12%. Kata kunci: Content Based Image Retrieval, ORB, Image Matching, Image Retrieval
Comparison of Physical Activity Questions in the Korea National Health and Nutrition Examination Surveys

Objectives: This study aims to compare the contents of physical activity questions of Korean National Health and Nutrition Examination Survey(KNHANES), and to propose suggestions for improvement. Methods: Questions measuring physical activity prevalence of adults in the KNHANES from KNHANES I(1998) to the first year of KNHANES V(2010) were compared. Results: The questions used in each survey showed some problems in consistency and appropriateness. Major issues identified are as follows. First, the questions in each survey were not consistent, and would be inappropriate to make time series comparisons. Second, the purpose of physical activity was not clear. Third, the examples of physical activities suggested in the questions were not appropriate. Fourth, the intensity of physical activity were not adequately described. Fifth, by excluding walking from the moderate-intensity physical activity category, the prevalence of moderate-intensity physical activity could be underestimated. Sixth, it is difficult to measure the total amount of physical activity performed in one day because answers from the other domains cannot be clearly differentiated. Conclusions: The physical activity questions in the KNHANES questionnaire should be improved so that they are consistent with the purpose of survey, the respondents can easily understand the contents of the questions, and the questions can measure all physical activity performed in the different domains.
Working Through the Unconscious Assumption of Neglect

ABSTRACT Most often, neglect is viewed through the lens of immediate consequences such as nutritional or physical deficits. The science of neglect is now revealing that the effects of neglect are both long-lasting and cumulative. This article explores 3 long-term consequences of neglect through a case study of a child who experienced severe neglect the first 24 months of his life and the clinical interventions that are providing remediation for those consequences.
Business Ethics : Ethical Decision Making and Cases

Part I: AN OVERVIEW OF BUSINESS ETHICS. 1. The Importance of Business Ethics. 2. Stakeholder Relationships, Social Responsibility, and Corporate Governance. Part II: ETHICAL ISSUES AND THE INSTITUTIONALIZATION OF BUSINESS ETHICS. 3. Emerging Business Ethics Issues. 4. The Institutionalization of Business Ethics. Part III: THE DECISION-MAKING PROCESS. 5. Ethical Decision Making. 6. Individual Factors: Moral Philosophies and Values. 7. Organizational Factors: The Role of Ethical Culture and Relationships. Part IV: IMPLEMENTING BUSINESS ETHICS IN A GLOBAL ECONOMY. 8. Developing an Effective Ethics Program. 9. Managing and Controlling Ethics Programs. 10. Globalization of Ethical Decision-Making. 11. Ethical Leadership. 12. Sustainability: Ethical and Social Responsibility Dimensions. Part V: CASES. CASE 1. Monsanto Attempts to Balance Stakeholder Interests. CASE 2. Starbucks' Mission: Social Responsibility and Brand Strength. CASE 3. Walmart Manages Ethical and Compliance Challenges. CASE 4. Sustainability Challenges in the Gas and Oil Industry. CASE 5. New Belgium Brewing: Ethical and Environmental Responsibility. CASE 6. National Collegiate Athletic Association Ethics and Compliance Program. CASE 7. Google: The Quest to Balance Privacy with Profits. CASE 8. Zappos: Delivering Customer Satisfaction. CASE 9. Enron: Questionable Accounting Leads to Collapse. CASE 10. Home Depot Implements Stakeholder Orientation. CASE 11. Frauds of the Century. CASE 12. Insider Trading at the Galleon Group. CASE 13. Whole Foods Strives to Be an Ethical Corporate Citizen. CASE 14. Apple Inc.'s Ethical Successes and Challenges. CASE 15. PepsiCo's Journey Toward an Ethical and Socially Responsible Culture. CASE 16. Ethical Leadership at Cardinal IG: The Foundation of a Culture of Diversity. CASE 17. Better Business Bureau: Protecting Consumers and Dealing with Organizational Ethics Challenges. CASE 18. Managing the Risks of Global Bribery in Business. CASE 19. Mattel Responds to Ethical Challenges. CASE 20. Best Buy Fights Against Electronic Waste.
MULTILEVEL ASSOCIATION RULE MINING FOR LARGE DATASETS: A REVIEW

- Association rule mining is an imperative research issue in domain of data mining,but association rules mining at single concept level lead to uninteresting rules. For large data applications, it is hard to discover solid association rules among data elements at single abstraction level, because of the lack of data in multidimensional space. So finding association rules at multiple abstraction levels leads to knowledge discovery. The discovery of association rules at multiple levels is helpful in numerous applications. Priorwork in field of data mining has yielded proficient techniques for finding multilevel rules. This study aims to review the multilevel association rule mining and different techniques used for mining multilevel association rules from large datasets.
Empire State College: The Development of Online Learning

Empire State College was founded in 1971 to meet the needs of adult and other nontraditional student populations in the state of New York. Its initial delivery model was individualized instruction with a student working with a full-time faculty member to develop a unique plan of study and learning contracts to support that plan. By 1979, the College established the Center for Distance Learning, which developed and still offers structured, print-based courses to students with no requirement for on-site meetings. It began to experiment with computer-supported learning activities in the late 1980s, employing professional staff to support the exploration of technology and to provide assistance to faculty in instructional design. However, it was not until 1994, with the formal creation of the Center for Learning and Technology, that the development of online courses and programs was systematically pursued. This article outlines the development of online programs since that time, emphasizing the issues and challenges faced by the institution in seeking to provide quality, cost-effective distance education.
WHAT CAN L2 WRITERS’ PAUSING BEHAVIOR TELL US ABOUT THEIR L2 WRITING PROCESSES?

Abstract When responding to a writing task, writers spend a significant amount of their time not writing. These periods of physical inactivity, or pauses, during writing provide observable and measurable cues as to when, where, and how long writers halt to plan and/or revise their texts. Consequently, examining writers’ pausing patterns can provide important insights into the cognitive processes that writers employ when composing and the impact of various individual, task, and contextual factors on those processes. This article discusses theory and research on writers’ pausing behavior; how pause analysis can be used to investigate second language (L2) learners’ writing processes; challenges in researching writers’ pausing behavior (e.g., defining pauses); and some strategies to address these challenges. Next, the article illustrates how L2 writers’ pause data can be collected, analyzed, and interpreted, using keystroke logging data from a research project that aimed to examine the effects of task type, L2 proficiency, and keyboarding skills on L2 learners’ writing processes when writing on the computer. The article concludes with a call for more research on L2 writers’ pausing behavior, particularly how L2 writers’ pausing behavior relates to L2 writing outcomes and development across learners, contexts, and time.
Faculty Interactions with Black Male Students at HBCUS and Community Colleges as Predictors of Academic Achievement in STEM

ii ACKNOWLEDGMENTS . iv DEDICATION . v LIST OF TABLES . x LIST OF ILLUSTRATIONS . xi LIST OF ABBREVIATIONS . xii CHAPTER I – INTRODUCTION . 1 Background . 1 Statement of the Problem . 5 Purpose Statement . 6 Hypotheses . 6 Overview of Theoretical Framework . 6 Delimitations . 7 Justification . 8 Assumptions . 10 Definition of Terms. 10 CHAPTER II – REVIEW OF RELATED LITERATURE . 12 Introduction . 12 Diversity in STEM . 13 viii Faculty Characteristics and Interactions on Student Desired Outcomes . 15 Black Males at Four-Year Institutions . 18 Black Males at Two-Year Institutions . 20 Males in STEM . 21 Black Males in STEM at HBCUs . 22 Black Males in STEM at Community Colleges . 23 Conceptual Framework . 24 CHAPTER III – METHODOLOGY . 28 Introduction . 28 Research Design. 28 Participants . 28 Instrumentation . 29 Procedure . 32 Data analysis . 32 CHAPTER IV – RESULTS . 35 Introduction . 35 Logistic Regression Analysis . 35 Multiple Regression Analyses . 37 CHAPTER V – DISCUSSION . 43 Introduction . 43 ix Major Findings . 44 Implications. 49 Recommendations for Future Research . 50 Limitations . 52 APPENDIX A – Survey Instrument . 54 APPENDIX B – Permission to Use Instrument . 64 APPENDIX C – IRB Approval Letter . 66 REFERENCES . 67
HyperFlex: Towards Reliable and Dynamic SDN Virtualization for Next Generation Mobile Networks

Limitations of Current SDN Network Hypervisors [1] • Inflexible architecture as current implementations are either in software hosted on servers or as hardware extensions to SDN switches • Virtual SDN abstraction focuses on data plane abstraction, less attention to slicing of the control plane, which can be a performance bottleneck • No dynamic and flexible mechanisms for adaptation available • Not adapting to hardware platforms • No SDN-based management available
THE STUDY OF RELATIONSHIP BETWEEN PRE-SERVICE TEACHERS' SELF-EFFICACY BELIEFS AND ATTITUDES TOWARDS THE TEACHING PROFESSION

The purpose of this study was to examine the relationship between preservice teachers' attitudes towards the teaching profession (ATP) and teachers' self-efficacy beliefs (TSEB). In particular, the study aimed to understand the effect of preservice teachers' self-efficacy beliefs (TSEB), age, gender and discipline on their attitudes towards the teaching profession (ATP). The study was conducted with a correlational research design. Sample for the study comprised 157 preservice teachers attending a public university. Attitude Scale towards the Profession of Teaching (ASPT) and the Teachers' Sense of Efficacy Scale (TSES) were used as tools for data collection. The data were analyzed using correlation and multiple regression analysis techniques. The results showed that there were positive and significant relations between the variables selected for the study. Regression analysis revealed that preservice teachers' self- efficacy beliefs (TSEB) have a positive and significant effect on their attitudes towards teaching profession (ATP).
Teaching content and thematic analysis using PostSecret submissions

Courses: Communication Research Methods Survey; Qualitative Communication Research Methods. Objectives: It is appropriate to conduct this activity throughout a unit focused on methods of analyzing qualitative data. Implemented during two separate class periods, this activity will help students to differentiate, practice, and reflect on two types of qualitative data analysis: content analysis (i.e. in which qualitative data are quantified into results) and thematic analysis (i.e. wherein texts are organized and retain qualitative features to produce findings). The in-class activity uses PostSecret submissions to assist students in conducting steps of analysis, and encourages students to compare and contrast the analytic processes and their paradigmatic underpinnings.
Preparing students for STEM college and careers: The influence of redesigned high schools in North Carolina

Abstract:Given concerns that students are not prepared for STEM (science, technology, engineering and mathematics) college and careers, some states have created schools to enhance STEM proficiency. Inclusive STEM schools are designed to develop STEM interest and talent in groups of students underrepresented in STEM careers. We examined inclusive STEM schools to see whether those students were better prepared for postsecondary work than their matched peers in traditional schools. Then, we determined whether STEM schools provided a greater benefit to students underrepresented in STEM: girls, members of underrepresented minority groups, and economically disadvantaged students. Students in STEM high schools were more likely to pass advanced math and science classes, earn potential college credits, and graduate than those in traditional high schools. The effect of attending a STEM school was stronger for girls, economically disadvantaged, and underrepresented minority group students.
Yenilikçi İnsan Kaynakları Uygulamalarının Z Kuşağının Mutluluğuna ve İşten Ayrılma Niyetine Etkisi: Bankacılık Sektöründe Karma Yöntem Araştırması

Bu arastirmanin temel amaci yenilikci insan kaynaklari uygulamalarinin Z kusagi calisanlarinin mutluluguna ve isten ayrilma niyetine etkisini ortaya cikarmaktir. Arastirmanin orneklemini bankacilik sektorunde bulunan 198 Z kusagi calisan olusturmaktadir. Arastirmamizda karma yontem (nitel-nicel) benimsenmistir. Teorik model olusturulurken oncelikle nitel arastirma deseninden destek alinmistir. Bu dogrultuda Z kusagi calisanlar ve yoneticileriyle nitel mulakatlar gerceklestirilmistir. Yuz yuze mulakatlar 25 kisiyi kapsayan bir orneklem uzerinden gerceklestirilmistir. Yuz yuze gorusme yapilmasinin nedeni, katilimcilarin kendilerini sinirlama olmaksizin ozgurce ifade edebilmeleridir, boylelikle daha derinlemesine veri toplanabilmesi mumkun olmustur. Verilerin Nvivo 11 nitel veri analizi ile kategorize edilmesi saglanmistir. Karma yontem arastirma stratejisinin ikinci bolumunde teorik modelimizde yer alan degiskenler arasi etkilesimi olcmek amacli nicel arastirma yonteminden destek alinmistir. Veriler 198 calisandan anket yontemiyle toplanmistir ve SPSS 20 paket programiyla analiz edilmistir. Arastirmanin bulgulari mutlulugun, yenilikci insan kaynaklari uygulamalari ve isten ayrilma niyeti uzerinde araci etkiye sahip oldugunu ortaya koymustur.