nils-herrmann/clean_scirepeval huggingface dataset:
Community Restructuring and Depressive Symptoms of Rural Mature and Elderly Adults: A Multilevel Analysis Based on a National Dataset in China
Venue: Community Mental Health Journal

Community restructuring is an important predictor for residents' mental health. However, few studies have investigated how it affects the depressive symptoms of rural ageing population. Using cross sectional data from China Health and Retirement Longitudinal Study (CHARLS) this study examined how community restructuring was associated with depressive symptoms of Chinese rural mature and older adults and what community level factors mediated the association. We found that people in restructuring communities reported .75 unit lower depression score (p .01) community restructuring is associated with more infrastructure, recreational amenities, and grassroots organization (p .001) in the community; and the availability of infrastructure (p .01) and grassroots organization (p .05) had significant indirect effect on the association between community restructuring and depressive symptoms. World countries' urbanization policy shall not only focus on community physical environment, but also on the development of grassroots organizations that involve and connect local people.
Game based learning and children with ADHD

Game Based Learning and Children with ADHD Margaret Sullivan Carr, M.B.A. Mary Jean Tecce DeCarlo, Ph.D. Children with ADHD (Attention Deficit Hyperactivity Disorder) Attention Deficit Hyperactivity Disorder (ADHD) may exhibit behavioral and executive function issues that affect classroom learning. Documented behaviors include inattention, disruptive behavior, and poor social relationships (Gureasko Moore, DuPaul, White, 2006) Support for children with ADHD has primarily focused on behavioral modifications and organizational skill enhancement. Computerassisted or game based learning has shown promise with this population in small scale studies (Mautone, 2005; Ota, 2002) This case study research sought to investigate the use of gamebased learning and children with ADHD. The subjects were high school aged children with the primary diagnosis of ADHD who received a game based intervention. This study shows gamebased learning has a positive effect on students with ADHDs' engagement and interest in Math. The analysis of the data from the qualitative portion of this study lends itself to a grounded theory approach indicating game based learning is an important consideration in curriculum development for students with ADHD.
Analysis Of The Finite Element Method

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Systems Theory as a Foundation for Discovery of Pathologies for Complex System Problem Formulation

This chapter articulates a set of systems theory based pathologies that act to limit performance of complex systems. In response to the common mantra that problem formulation is the most important activity in successfully dealing with complex system problems, this research elaborates on the utility of systems theory as the basis for problem formulation through the discovery of system pathologies. Pathologies are taken as circumstances that act to limit system performance or lessen system viability (continued existence) and as such they reduce the likelihood of a system meeting performance expectations. As an extension of contemporary developments in systems theory, this chapter is focused on three primary objectives. First, systems theory is examined to generate a comprehensive set of 45 principles, laws and concepts that explain system behavior and performance. Second, a set of systems theory based pathologies that can be explained as deviation in application of systems theory (i.e. lack of use or violation) are articulated. Third, the chapter discusses implications of the developed pathologies for practitioners faced with the task of formulating complex system problems. The chapter concludes with proposed future research.
Understanding sustainable innovation as a complex adaptive system: a systemic approach to the firm

The aim of this paper is to understand how firms engage in new processes, strategies and behaviors for sustainable innovation. It results on a non linear, recursive and self organized process that can be studied as a complex adaptive system. Based on an integrative literature review, we find five ontological sustainable innovation components: operational, collaborative, organizational, instrumental, and holistic. Our analysis also yields three complex adaptive system phenomena, which explain three main patterns of how components interact and interconnect: non linearity, self organization and emergence. The three phenomena are mutually dependent and specific to each company. Non linearity explains the connection between the components, including positive and negative feedback loops and the rates of change, disorder, chaos and stability between them. Self organization increases the order or regularity between the components interaction and even generates a new order and configuration with the different components behaving autonomously. Emergence involves radically new processes and component interactions due to new and radical experimentation, rule breaking and disruptive sustainable technologies. Each phenomenon is explained in three extended examples, including three interaction mechanisms describing the dynamics of the five components. The outcomes of this research provide a new approach to theory building in the sustainable innovation field and serve as the basis for further research on the complexity of engaging sustainable innovation in firms. This suggests new research questions regarding the role of firms in sustainable innovation and sustainable system transitions. It also calls for more interdisciplinary work on the issue due to the systemic nature of sustainable innovation at the firm level.
Latino/a professionals as entrepreneurs: how race, class, and gender shape entrepreneurial incorporation

This paper examines how race, class, and gender intersect to shape professional Latinos' entrepreneurial incorporation, as observed by the conditions that prompt professional Latinos to start a business, including access to capital and experiences with discrimination. In depth interviews with professional Latino business owners in Los Angeles reveal that individual human capital via resources and wealth accrued through corporate careers facilitates entrepreneurial activity. Race, ethnicity, and gender, as intersectional social group identities, combine with class to shape variegated impacts on access to capital and business experiences by gender and target market. Ethnicity is a resource for those serving the coethnic community and is more significant in shaping business ownership experiences for men who target a racially/ethnically diverse clientele, whereas gender and race are more salient for women outside the coethnic community. This study contributes to the ethnic enterprise literature by going beyond ethnicity to demonstrate that multiple dimensions of identity shape professional Latino/as' entrepreneurial incorporation.
Chinese Immigrant Wealth: Heterogeneity in Adaptation
Venue: PloS one

Chinese immigrants are a diverse and growing group whose members provide a unique opportunity to examine within immigrant group differences in adaptation. In this paper, we move beyond thinking of national origin groups as homogenous and study variation among Chinese immigrants in wealth ownership, a critical indicator of adaptation that attracts relatively little attention in the immigration literature. We develop an analytical approach that considers national origin, tenure in the U.S. and age to examine heterogeneity in economic adaptation among the immigrant generation. Our results show that variations among Chinese immigrants explain within group differences in net worth, asset ownership, and debt. These differences also account for important variation between Chinese immigrants, natives, and other immigrant groups and provide important, new insight into the processes that lead to immigrant adaptation and long term class stability.
Simultaneous Sentence Boundary Detection and Alignment with Pivot based Machine Translation Generated Lexicons
Venue: LREC

Sentence alignment is a task that consists in aligning the parallel sentences in a translated article pair. This paper describes a method to perform sentence boundary detection and alignment simultaneously, which significantly improves the alignment accuracy on languages like Chinese with uncertain sentence boundaries. It relies on the definition of hard (certain) and soft (uncertain) punctuation delimiters, the latter being possibly ignored to optimize the alignment result. The alignment method is used in combination with lexicons automatically generated from the input article pairs using pivot based MT, achieving better coverage of the input words with fewer entries than pre existing dictionaries. Pivot based MT makes it possible to build dictionaries for language pairs that have scarce parallel data. The alignment method is implemented in a tool that will be freely available in the near future.
Artificial neural network based modeling and optimization of refined palm oil process
Venue: Neurocomputing

The content and concentration of beta carotene, tocopherol and free fatty acid is one of the important parameters that affect the quality of edible oil. In simulation based studies for refined palm oil process, three variables are usually used as input parameters which are feed flow rate (F) column temperature (T) and pressure (P) These parameters influence the output concentration of beta carotene, tocopherol and free fatty acid. In this work, we develop 2 different ANN models; the first ANN model based on 3 inputs (F, T, P) and the second model based on 2 inputs (T and P) Artificial neural network (ANN) models are set up to describe the simulation. Feed forward back propagation neural networks are designed using different architecture in MATLAB toolbox. The effects of numbers for neurons and layers are examined. The correlation coefficient for this study is greater than 0.99; it is in good agreement during training and testing the models. Moreover, it is found that ANN can model the process accurately, and is able to predict the model outputs very close to those predicted by ASPEN HYSYS simulator for refined palm oil process. Optimization of the refined palm oil process is performed using ANN based model to maximize the concentration of beta carotene and tocopherol at residue and free fatty acid at distillate.
Process enhancement of hydrogen and methane production from palm oil mill effluent using two stage thermophilic and mesophilic fermentation

The present study investigates the technical possibilities of hydrogen and methane production from palm oil mill effluent (POME) The production was carried out in two stage (thermophilic and mesophilic) continuous phase with recirculation of the digestate sludge. The reactors used for the present study, up flow anaerobic sludge blanket reactor (UASB) and continuous stirred tank reactor (CSTR) were operated under thermophilic and mesophilic conditions, respectively. The UASB reactor was operated at 2 days hydraulic retention time (HRT) and 75 kgCOD m3 d 1 organic loading rate (OLR) for hydrogen production. The effluents from UASB reactor containing mainly with acetate and butyrate were directly fed into CSTR for methane production and 5 days HRT was maintained. Both UASB and CSTR reactors were operated for 120 days continuously, and a stable production of the hydrogen and methane was obtained in the separate reactors. The maximum hydrogen and methane production rate achieved was 1.92 L H2 L d 1 and 3.2 L CH4 L 1 d 1, respectively. The cumulative hydrogen and methane yields were 215 L H2/kgCOD 1 and 320 L CH4/kgCOD 1, respectively with the total COD removal efficiency of 94% Thermoanaerobacterium species was dominant in hydrogen reactor, while methane reactor was dominated with Methanobrevibacter sp.
Characteristics of and Quality of Life in a Transit Oriented Development (TOD) of Bandar Sri Permaisuri, Kuala Lumpur

is a relatively new strategy to arrest the phenomenon of urban sprawl. It entails development centers around a transit station with mixed use and high density development. This paper evaluates the TOD in Bandar Sri Permaisuri, Kuala Lumpur through descriptive and comparative analyses and survey of residents. It found that Sri Permasuri TOD has met main physical characteristics of TODs especially related to land use mix and density. The survey found that most respondents are comfortable with the mixed use and high density of Sri Permaisuri TOD but unhappy with pollution, congestions and lack of covered walkway in the township.
The integrated applications of WIFI and APP used in the shopping mall environment for menber card E marketing
Venue: 2016 International Conference on Machine Learning and Cybernetics (ICMLC)

In the Information Age, the problem of information overload as a form of explicitly good news or pollution has become more popular, the consumer's attention also becomes the scarce resource to be allocated. Member card can provide personal identification, authentication, data storage, and relevant application. It may provide strong marketing media for customer relationship within business organizations. However, many customers have received annoyed messages in the inappropriate time and place on their mobile devices when they were not expecting it. In this paper, the integrated applications of mall's Wi Fi and App are proposed. The mobile devices of member card holder's media access control address (MAC address) collected by way of the mall's App via local Wi Fi APs(access point) which connected the central administration server and received or interchanged information and configuration settings with the card account. By the integrated system, the mall and card members always keep in communication upon the system infrastructure; meanwhile, they are in visiting mall domain area. This is an important opportunity moment for the mall managers to grasp the categorized customers in real time. As the above mentioned moment, the mall manager could create extensive value and precisely aim to their products or services to their targeted customers by delivering marketing information. The typical deployment zone for the proposed approach is multiple computing applications. Our expected goal is to build a smart mall applications and location based services (LBS)
Video summarization for remote invigilation of online exams
Venue: 2016 IEEE Winter Conference on Applications of Computer Vision (WACV)

This paper focuses on video summarization of abnormal behavior for remote invigilation of online exams. While the last decade has seen a massive increase in e learning and online courses offered at postsecondary institutions, preserving the integrity of online examinations still heavily relies on web video conference invigilation performed by a remote proctor. Live remote invigilation is limited in the number of students that can be handled at once, and manual post exam review is labor intensive. We propose a novel computer vision based video content analysis system for the automatic creation of video summaries of online exams to assist remote proctors in post exam reviews. The proposed method models normal and abnormal student behavior patterns using head pose estimations and a semantically meaningful two state hidden Markov model. Video summaries are created from detected sequences of abnormal behavior. Experimental results are promising and demonstrate the viability of the proposed approach, which could readily be expanded to generate real time alerts for live remote invigilation.
A Teacher Professional Development Model for Teaching Socioscientific Issues.

This paper describes the development and implementation of a three pillared model for teaching socioscientific issues: teacher professional development; curriculum resources; and classroom support. A professional development program and curriculum resource based on the socioscientific issue of climate change was trialled with 75 Western Australian secondary science teachers. Teachers responded positively to the workshops and curriculum resource and indicated a willingness to use some or all of the activities in their classes. Two of these teachers have subsequently trialled the curriculum resource. These classes have been observed and feedback provided. This support aims to develop and maintain teachers' confidence in teaching socioscientific issues such as climate change.
Animating eco education: To see, feel, and discover in an augmented reality based experiential learning environment
Venue: Comput. Educ.

An antagonistic relationship is traditionally seen as existing between eco education and technology, with conventional instructional approaches usually characterized by a commentator guiding students in field learning. Unfortunately, in this passive learning approach, the discovery of rich ecological resources in eco environments to stimulate positive emotions and experiences is often condensed into a "sightseeing" Therefore, precise and systematic guidance focused on providing a rich learning experience is needed in field learning and eco education. Based on Kolb's experiential learning theory, the current study develops an eco discovery AR based learning model (EDALM) which is implemented in an eco discovery AR based learning system (EDALS) In a field experiment at a botanical garden, 21 middle school students constitute three groups participated in a learning activity using different learning types and media. Quantitative results indicate that, compared to the human guidance only model, EDALS successfully stimulates positive emotions and improved learning outcomes among learners. In post activity interviews, students indicated they found the exploration mode provided by the proposed system to be more interesting and helpful to their learning in school. The use of attractive technologies increase students' willingness not only to learn more about the environment, but also to develop a more positive emotional attachment to it. Design of an eco discovery AR based learning model and system (EDALS) for eco education.Students used EDALS to connect virtual and real world to enrich exploring experience.Students performed best when they are learning with EDALS integrated in commentator approach.EDALS integrated with eco environment stimulates students' positive emotions and engagement.
Encyclopedia Of Research Design

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Encyclopedia Of Common Natural Ingredients Used In Food Drugs And Cosmetics

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Encyclopedia Of Insects

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The Wiley Blackwell Encyclopedia of Gender and Sexuality Studies

This entry examines 'cyber intimacies' by outlining the nature of computer mediated communication between newly met strangers and individuals with pre existing relationships. It covers the use of CMC in already established relationships, in meeting new people (in particular online dating) and for cybersex and outlines the positives as well as the potential risks of such practices. The Wiley Blackwell Encyclopedia of Gender and Sexuality Studies
Encyclopedia Of Social Psychology

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Knowledge Extraction in Web Media: At The Frontier of NLP, Machine Learning and Semantics
Venue: WWW

We identify two main factors that can cause numerous difficulties when developing a generic entity linking system: i) the amount of data currently available on the Web that do not stop to increase and where a large part comes in the form of natural language texts; ii) the velocity at which data is published that may impose to process streams of text in near real time. Social media platforms such as Twitter, Facebook or LinkedIn become a reliable source of news and play a key role for being aware of events around the world. Encyclopedia and newspaper articles contain general knowledge of our world and they can be used to explain concepts and known entities. Videos can be associated with subtitles and images may have captions. Depending on where a text comes from, it can have different properties such as a specific language, style of writing or topic. In this research, we present a preliminary framework based on a novel hybrid architecture for an entity linking system, that combines methods from the Natural Language Processing (NLP) information retrieval and semantic fields. In particular, we propose a modular approach in order to be as independent as possible of the text to be processed. Our evaluation suggests that this framework can outperform the state of the art systems or show encouraging results on three datasets: OKE2015, #Micropost 2014 and #Micropost 2015. We identify the current limitations and we provide promising future research directions.