A meta-study of qualitative research examining stressor appraisals and coping among adolescents in sport

The main aim of this study was to create an integrated theoretical perspective of the qualitative adolescent sport stressor appraisal and coping literature. A secondary aim was to critique theoretical and methodological issues in the extant literature. Following database searches, 20 studies were retained for analysis. Meta-data, meta-theory, and meta-method analyses were conducted followed by a final meta-synthesis of findings. Analyses produced four themes: contextual and dynamic stressor appraisals, contextual and dynamic coping, coping resources and processes of acquisition, and social networks as assets and liabilities. Findings highlight the need for precise use of theory in the study of coping. Finally, while several data collection methods have been used, there is scope for greater methodological diversity to advance our understanding of coping among adolescent athletes.     

Connecting and Creating for Learning: Integrating Subject Matter Across the Curriculum and the School

In this article, the authors explore a growing awareness of problems and current developments in classroom and schoolwide research on subject matter integration. Schwab's four common places—including the learner, the teacher, the content, and the context—provide a framework for examining subject matter integration from a language arts perspective. Two lines of classroom-based research are examined that were conducted in response to the lack of integration within the curriculum: Explanation and Responsive Elaboration in Reading and Cognitive Strategies in Writing. As a result of these two lines of research, researchers became more aware of the importance of understanding the complexity of integrating process into content within the context of the classroom and the school. A major shift toward schoolwide integration in two Professional Development School settings is described that was created in response to these research findings. Teachers and researchers within specific contexts generated and implemented integrated instruction and curriculum content collaboratively. The authors conclude with emerging questions and principles for stimulating thinking among teachers and researchers who work toward furthering understanding of language and subject matter integration within specific contexts.     

Searching the Web: New Tools-New Dilemmas

Drawing on their experiences as researchers and teacher educators, the authors discuss issues concerning student research that uses web-based references. This article describes ways the authors: 1) structure the inquiry process for student research, 2) help students manage the quantity of information, and 3) provide a model for analyzing the quality of information that students find on web sites. The web-site analysis form provided to students requires them to evaluate information provided about the “who, what, when, how, and where” of a web site. The authors conclude with a discussion of the ways this model helps students engage, organize, and publish information in ways that share the knowledge that the students have constructed and the process of their inquiry.     

Updating and expanding systematic reviews and meta-analyses on the effects of school-wide positive behavior interventions and supports

School-wide positive behavior interventions and supports (SWPBIS) is a multitiered support framework for preventing problem behaviors and increasing prosocial behaviors. There has been an increasing number of experimental group design research studies focused on the impacts of SWPBIS. Therefore, we conducted a systematic review to update and extend prior reviews by including both published and unpublished studies and conducting a robust variance estimation meta-analysis to examine the magnitude of the effect of SWPBIS on all available school-level outcomes. A total of 29 studies were identified across the United States and Europe, including seven randomized controlled trials and 22 quasi-experimental group design studies. Overall, statistically significant reductions in school discipline and increased academic achievement were found. Effect sizes were small to medium. Limitations and implications are discussed.     

Muscle-fiber array inspired,multiple-mode,pneumatic artificial muscles through planar design and one-step rolling fabrication

Advances in development of artificial muscles have enabled creation of soft robots with biological dexterity and self-adaption in unstructured environments; however, production of scalable artificial muscles with multiple-mode actuations remains elusive. Inspired by muscle-fiber arrays in muscular hydrostats, we present a class of versatile artificial muscles called MAIPAMs (muscle-fiber array inspired pneumatic artificial muscles), capable of multiple-mode actuations (such as parallel elongation-bending-spiraling actuations, 10 parallel bending actuations and cascaded elongation-bending-spiraling actuations). Our MAIPAMs consist of active 3D elastomer-balloon arrays reinforced by a passive elastomer membrane, achieved through a planar design and one-step rolling fabrication approach. We introduce prototypical designs for the MAIPAMs and demonstrate their muscle-mimic structures and versatility, as well as their scalable ability to integrate flexible but non-stretchable layers for contraction and twisting actuation modes and compliant electrodes for self-sensing. We further demonstrate that this class of artificial muscles shows potential for versatile robotic applications, such as carrying a camera for recording videos, gripping or manipulating objects, and climbing a pipe-line.     

Real-time processing of social media with SENTINEL: A syndromic surveillance system incorporating deep learning for health classification

Interest in real-time syndromic surveillance based on social media data has greatly increased in recent years. The ability to detect disease outbreaks earlier than traditional methods would be highly useful for public health officials. This paper describes a software system which is built upon recent developments in machine learning and data processing to achieve this goal. The system is built from reusable modules integrated into data processing pipelines that are easily deployable and configurable. It applies deep learning to the problem of classifying health-related tweets and is able to do so with high accuracy. It has the capability to detect illness outbreaks from Twitter data and then to build up and display information about these outbreaks, including relevant news articles, to provide situational awareness. It also provides nowcasting functionality of current disease levels from previous clinical data combined with Twitter data.The preliminary results are promising, with the system being able to detect outbreaks of influenza-like illness symptoms which could then be confirmed by existing official sources. The Nowcasting module shows that using social media data can improve prediction for multiple diseases over simply using traditional data sources.