Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Chattooga River Rafters and Kayakers and Their Effects on Each Other's Experience

Massarelli, Erin Adelle. A Comparison of Chattooga River Rafters and Kayakers and Their Effects on Each Other’s Experience. (Under the direction of Dr. Roger L. Moore) The purpose of this study was to compare rafters and kayakers on the Chattooga River and their effects on each other’s experience. Data was collected via a mail survey of individuals who used the Chattooga River and its corridor in 2002, including commercially guided boaters, self-guided boaters, and annual pass holders to fee-based parking areas. Based on their primary activity for their most recent visit, rafters and kayakers were isolated from the remainder of the sample for analysis. Participants’ general characteristics and their Chattooga River trip histories were gleaned from the survey responses. Motivations for visiting were measured by asking participants to rate the importance of different motives provided in the survey. Rafter and kayaker effects on each other’s experiences were assessed by asking participants to rate their increased or decreased enjoyment due to encounters with each other. Results revealed that the rafters and kayakers were distinctly different groups based on general characteristics, most recent trip characteristics, and trip history. Overall, the rafters appeared to be families on vacation trips down the river, whereas the kayakers were generally small groups of friends participating in a frequently engaged in activity. Differences between the rafters and kayakers were also revealed in the importance that they placed on the motivation statements. Finally, when assessing the effects that they had on each other’s experiences, the majority of encounters produced neutral effects. However, there was evidence of asymmetrical conflict felt by kayakers towards rafters. These findings suggest that differences in activity style, mode of experience, resource specificity, and perceived status could have affected the amount of conflict experienced by the kayakers. One way to reduce the occurrence of conflict among river users on the Chattooga River may be to familiarize members of each group with each other. One way to familiarize river users with one another is though education efforts that emphasize group similarities and promote tolerance for their differences. A COMPARISON OF CHATTOOGA RIVER RAFTERS AND KAYAKERS AND THEIR EFFECTS ON EACH OTHER’S EXPERIENCE by ERIN ADELLE MASSARELLI A thesis submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Master of Science PARKS, RECREATION, AND TOURISM MANAGEMENT
Does sociality aﬀect evolutionary speed?

An overlooked source of variation in evolvability resides in the social lives of animals. In trying to foster research in this direction, we oﬀer a critical review of previous work on the link between evolutionary speed and sociality. A ﬁrst set of studies emerged that we grouped under the “selectionist perspective”. These studies conceive social interactions as knitting forces of an environment with speciﬁc selection pressures. Social pressures, in turn, promote evolutionary change in the characters they depend on. Studies in this perspective have investigated cladogenetic eﬀects of sexual selection, while non-sexual contexts have been relatively ignored. We grouped a second set of studies grounded on population genetics under the “populationist perspective”. Such studies regard social interactions and the social units arising from them as a dividing force that splits a population into smaller parts, tweaking the number of reproducing individuals and unbalancing the contribution of both sexes. The consequences of these eﬀects on the eﬀective breeding population size are made responsible for changes in the speed of neutral evolution. Despite the manifold approaches used to measure sociality and evolutionary
Animatable Facial Reflectance Fields

We present a technique for creating an animatable image-based appearance model of a human face, able to capture appearance variation over changing facial expression, head pose, view direction, and lighting condition. Our capture process makes use of a specialized lighting apparatus designed to rapidly illuminate the subject sequentially from many different directions in just a few seconds. For each pose, the subject remains still while six video cameras capture their appearance under each of the directions of lighting. We repeat this process for approximately 60 different poses, capturing different expressions, visemes, head poses, and eye positions. The images for each of the poses and camera views are registered to each other semi-automatically with the help of fiducial markers. The result is a model which can be rendered realistically under any linear blend of the captured poses and under any desired lighting condition by warping, scaling, and blending data from the original images. Finally, we show how to drive the model with performance capture data, where the pose is not necessarily a linear combination of the original captured poses.
Safety Precaution Practices and Associated Factors Among Public Hospital Cleaners: Case In Addis Ababa, Ethiopia.

Cleaners working in hospitals are exposed to different health problems than other health personnel due to low knowledge and skill, poor biomedical waste management, hospital acquired infections, and poor safety precaution practices. However, little attention has been given to this flaming issue. This study was therefore designed to assess safety precaution practices and associated factors among public hospital cleaners in Addis Ababa city. An institutional based cross-sectional study was deployed among 320 cleaners in six public hospitals selected through cluster random sampling methods, from July to August 2019. Data collected through pre-tested structured interviewer-administered questionnaires, and the collected data was entered into Epi -Info version 7software and then exported to SPSS version 20 for further analysis. Variables with p-value of < 0.2 at bi-variable logistic regression earmarked for the multi-variable logistic regression analysis, and in this model, variables of p-value < 0.05 were considered as the important predictors of the safety precaution practices. We found that safety precaution practice was very low among study participants and was highly associated with inadequate knowledge, employment condition, employee organization, work experience, health and safety training, supportive supervision, work rotation in different units of the hospital, and also knowing the availability of soap or hand rub alcohol. Therefore, strengthening regular training and awareness, conducting program based supportive supervision, strengthening work rotation, adequate and continues supply of safety commodities for cleaners are essential to improve safety precaution practices that lessen the work related health challenges among hospital cleaners.
UvA-DARE ( Digital Academic Repository ) Regional and seasonal flight speeds of soaring migrants and the role of weather at hourly and daily

Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva. nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
Factor-augmented Model for Functional Data

We propose modeling raw functional data as a mixture of a smooth function and a high-dimensional factor component. The conventional approach to retrieving the smooth function from the raw data is through various smoothing techniques. However, the smoothing model is inadequate to recover the smooth curve or capture the data variation in some situations. These include cases where there is a large amount of measurement error, the smoothing basis functions are incorrectly identified, or the step jumps in the functional mean levels are neglected. A factor-augmented smoothing model is proposed to address these challenges, and an iterative numerical estimation approach is implemented in practice. Including the factor model component in the proposed method solves the aforementioned problems since a few common factors often drive the variation that cannot be captured by the smoothing model. Asymptotic theorems are also established to demonstrate the effects of including factor structures on the smoothing results. Specifically, we show that the smoothing coefficients projected on the complement space of the factor loading matrix are asymptotically normal. As a byproduct of independent interest, an estimator for the population covariance matrix of the raw data is presented based on the proposed model. Extensive simulation studies illustrate that these factor adjustments are essential in improving estimation accuracy and avoiding the curse of dimensionality. The superiority of our model is also shown in modeling Australian temperature data.
Journal of Fibers and Polymer Composites

This study aims to synthesis and characterize PES/PEG/PVA/SiO 2 composite membranes. The composite membranes were synthesized by phase inversion method with composition (% w/w) Polyethersulfone/ PES (17.25), Polyvinylalcohol/ PVA (3.58; 0.85; 1.43; 2.57; 3.57, Polyethylene glycol/ PEG (3.72), Silica/SiO 2 (0.35; 0.85; 1.43; 2.57; 3.57), and Dimethyl acetamide/DMAc solvent. Composite membranes were characterized using FTIR spectroscopy, X-ray diffraction, Scanning Electron Microscopy (SEM)
High-Resolution DOA Estimation via a Novel Tree Model-based Deep Neural Network

—To satisfy the high-resolution requirements of direction-of-arrival (DOA) estimation, conventional deep neural network (DNN)-based methods using grid idea need to significantly increase the number of output classifications and also produce a huge high model complexity. To address this problem, a multi-level tree-based DNN model (TDNN) is proposed as an alternative, where each level takes small-scale multi-layer neural networks (MLNNs) as nodes to divide the target angular interval into multiple sub-intervals, and each output class is associated to a MLNN at the next level. Then the number of MLNNs is gradually increasing from the first level to the last level, and so increasing the depth of tree will dramatically raise the number of output classes to improve the estimation accuracy. More importantly, this network is extended to make a multi-emitter DOA estimation. Simulation results show that the proposed TDNN performs much better than conventional DNN and root-MUSIC at extremely low signal-to-noise ratio (SNR), and can achieve Cramer-Rao lower bound (CRLB). Additionally, in the multi-emitter scenario, the proposed Q -TDNN has also made a substantial performance enhancement over DNN and Root-MUSIC, and this gain grows as the number of emitters increases.
Journal Pre-proof Sex hormones drive changes in lipoprotein metabolism

Women have a reduced cardiovascular disease (CVD) risk compared to men which could be partially driven by sex hormones influencing lipid levels post-puberty. The interrelationship between sex hormones and lipids was explored in pre-pubertal children, young post-pubertal cis-men/women, and transgender individuals on cross-sex-hormone treatment (trans-men/women) using serum metabolomics assessing 149 lipids. High-density lipoproteins (HDL, typically atheroprotective) were significantly increased and very-low-and low-density lipoproteins (typically atherogenic) were significantly decreased in post-pubertal cis-women compared to cis-men. These differences were not observed pre-puberty and were induced appropriately by cross-sex-hormone treatment in transgender individuals, supporting that sex hormones regulate lipid metabolism in vivo . Only atheroprotective apolipoprotein (Apo)A1 expressing lipoproteins (HDL) were differentially expressed between all hormonally unique comparisons. Thus, oestradiol drives a typically atheroprotective lipid profile through upregulation of HDL/ApoA1 which could contribute to the sexual dimorphism observed in CVD risk post-puberty. Together, this could inform sex-specific therapeutic strategies for CVD management.
Pisang Menggunakan Metode Convolutional Neural Network

– Bananas are plants from the Southeast Asian region and belong to the genus Musa and the family Musaceae. Grown in tropical and subtropical regions, bananas are one of the agricultural commodities with the largest production compared to other fruits. Indonesia is one of the countries that produce the largest bananas in the world. The yields are then sorted based on the level of ripeness by looking at the color change of the banana skin. However, the process of sorting bananas requires a lot of time and effort due to the large production of bananas. In addition, differences in the assessment of each individual on changes in the color of banana peels result in an unstable or consistent sorting of bananas. Therefore, this study intends to create a ripeness classification system for bananas based on changes in skin color with the aim that the sorting process can be carried out efficiently and accurately. The color variants used range from dominant green for unripe bananas, dominant yellow for ripe bananas and blackish brown spots for overripe bananas. The method used is a Convolutional Neural Network with a self-designed architecture. The results showed that the accuracy reached 88% with a learning rate setting of 0.001 and a maximum epoch limit of 15.
International Review of Research in Open and Distributed Learning Exploring the Roles of Social Participation in Mobile Social Media Learning: A Social Network Analysis

Social media is increasingly becoming an essential platform for social connectivity in our daily lives. The availability of mobile technology has further fueled its importance – making it a ubiquitous tool for social interaction. However, limited studies have been conducted to investigate roles of social participation in this field. Thus, the study investigates roles of social participation in mobile social media learning using the “ladder of participation and mastering. ” Participants were students taking an educational technology course in a local university. The study was conducted in a four-month period. Data was collected from discussions while learning among the students a social media platform, Facebook groups, on mobile devices. The data was analyzed using a social network analysis tool, NodeXL. Data was analyzed based on egocentric networks, betweeness centrality, and closeness centrality. The findings revealed that there are four roles of social participation in mobile social media, which are: (i) lurkers; (ii) gradually mastering members/passive members; (iii) recognized members; and (iv) coaches. The findings also indicated that over the course of four months, learners can inter-change roles of social participation – becoming more central or less central in learning discussions. As a result, a roles of social participation continuum for mobile social media learning is proposed. Future research could be conducted in other fields to investigate whether the continuum produced could be used to understand the relationship between mobile social media learning and social participation roles.
International Review of Research in Open and Distributed Learning Decision, Implementation, and Confirmation: Experiences of Instructors behind Tourism and Hospitality MOOCs

As the popularity of Massive Open Online Courses (MOOCs) continues to grow, studies are emerging to investigate various topics in this area. Most have focused on the learners’ perspective, leaving a gap in the literature about MOOC instructors. The current research—conducted in the field of tourism and hospitality—explored early experiences of MOOC instructors as they progressed through three stages of the innovation-decision process: decision, implementation, and confirmation. The tourism and hospitality field was chosen because its related industries contribute significantly to global employment, and training is one of their critical success factors. MOOCs possess a good potential to benefit tourism and hospitality education, yet tourism and hospitality MOOCs are under-researched. Semi-structured interviews were conducted with six instructors who offered tourism and hospitality MOOCs between 2008 and 2015. Findings revealed that: (1) the instructors’ decisions to offer MOOCs were mostly influenced by their institutes’ interests in MOOCs; (2) when the instructors implemented MOOCs, a pattern of action emerged, which included six phases and one cross-phase element— prepare, design, develop, launch, deliver, and evaluate—and across phases—support and train; (3) most instructors chose to avoid risk in their adoption and implementation of the MOOCs, staying away from innovative teaching or learning activities such as peer-review assessments and collaborative activities; and (4) half of the instructors intended to repeat the experience of teaching in the MOOCs format in the future.
International Review of Research in Open and Distributed Learning Towards an Integration of Text and Graph Clustering Methods as a Lens for Studying Social Interaction in MOOCs

In this paper, we describe a novel methodology, grounded in techniques from the field of machine learning, for modeling emerging social structure as it develops in threaded discussion forums, with an eye towards application in the threaded discussions of massive open online courses (MOOCs). This modeling approach integrates two simpler, well established prior techniques, namely one related to social network structure and another related to thematic structure of text. As an illustrative application of the integrated technique’s use and utility, we use it as a lens for exploring student dropout behavior in three different MOOCs. In particular, we use the model to identify twenty emerging subcommunities within the threaded discussions of each of the three MOOCs. We then use a survival model to measure the impact of participation in identified subcommunities on attrition along the way for students who have participated in the course discussion forums of the three courses. In each of three MOOCs we find evidence that participation in two to four subcommunities out of the twenty is associated with significantly higher or lower dropout rates than average. A qualitative post-hoc analysis illustrates how the learned models can be used as a lens for understanding the values and focus of discussions within the subcommunities, and in the illustrative example to think about the association between those and detected higher or lower dropout rates than average in the three courses. Our qualitative analysis demonstrates that the patterns that emerge make sense: It associates evidence of stronger expressed motivation to actively participate in the course as well as evidence of stronger cognitive engagement with the material in subcommunities associated with lower attrition, and the opposite in subcommunities associated with higher attrition.
International Review of Research in Open and Distributed Learning Qualifying with Different Types of Quizzes in an Online EFL Course: Influences on Perceived Learning and Academic Achievement

This quasi-experimental study explored how different online exam types differentiate learners’ academic achievement and perceived learning. The participants comprised 95 undergraduate students enrolled in an English course at a Turkish university in three groups, each taking a different type of quiz: with multiple-choice, open-ended, and mixed type questions. The results indicated that the academic achievement of the students in multiple-choice and open-ended groups increased and that quiz results improved the most for the multiple-choice group relative to the other groups. The study found a moderate level of significant relationship between cognitive and affective perceived learning and multiple-choice quiz scores. In addition, the study found a weak level of significant relationship between cognitive and affective perceived learning and mixed-design quiz scores, and between cognitive learning and the academic achievement scores of the mixed-design group. Semi-structured online interviews undertaken to further explain the quantitative data displayed positive influences of the different types of quizzes in terms of study behaviors and satisfaction. The findings of this study are expected to shed light for practitioners aiming to use different online assessment types.
International Review of Research in Open and Distributed Learning Rethinking Dropout in Online Higher Education: The Case of the Universitat Oberta de Catalunya

In recent years, several studies have been carried out into the reasons why students drop out of online higher education, following the rise in the relative weight of this form of education. However, more effort has gone into analyzing the causes of this phenomenon than into trying to characterize students who drop out, that is defining what a dropout student is. But obtaining a proper definition of dropout is just as important as describing its causes. It also appears that the definition of dropout is very sensitive to context. As one of the main findings of this article, we reach a pure empirical definition, at a programme level, of students who drop out of an online higher education context with non-mandatory enrollment. This definition is based on the probability of students not continuing a specific academic programme following several consecutive semesters of “theoretical break”, and is highly adaptable to institutions offering distance education with no permanence requirements, that is ones offering the possibility of taking breaks. Our findings show that there are differences regarding the number of consecutive semesters that define dropout depending on whether the programme requires previous experience or not. Additionally, we observe significant differences in the dropout rate between specific programmes, as well as a higher level of dropout in the first semesters. Analyzing the reasons behind these facts should help higher education institutions to make more sound and efficient decisions.
International Review of Research in Open and Distributed Learning A Top Down Strategy to Enhance Information Technologies into Israeli Higher Education

This article examines the integration of the new information technologies (IT) into Israeli higher education, and most particularly its research universities through a top-down strategy, initiated by the Israeli Council for Higher Education since the end of 1999. This top-down strategy has created a systemic change that will affect the many layers of university activities rather than in a random, sporadic manner undertaken by enthusiastic individuals. This article discusses the built-in contradictions and dilemmas in the process of adapting distance teaching methods by conventional universities in Israel (as well as in other higher education systems). It examines the merits of a top-down strategy aimed to implement the IT through a macro-level, systemic approach, and analyses the differential uses of the IT in Israeli higher education institutions, relating to variables of: access-outreach; teaching-learning processes; study materials production; data and information retrieval; administrative functions; the creation of "researcher" communities; inter-institutional collaboration; and associated costs. The article concludes with some suggestions for effective implementation of the IT in different types of higher education institutions in a comprehensive and systematic manner, that will take into account their academic ethos and organizational infrastructure, and cater to the unique needs and characteristics of their relevant constituencies.