scholarly journals GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

2021 ◽  
Author(s):  
Shuai Zhou ◽  
Yanling Li ◽  
Guangqing Chi ◽  
Junjun Yin ◽  
Zita Oravecz ◽  
...  
Keyword(s):  
Open Source ◽  
Contextual Information ◽  
Activity Patterns ◽  
Routine Data ◽  
Activity Space ◽  
Gps Data ◽  
Age Related ◽  
Shared Space ◽  
Social Media Platforms ◽  
Using Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals’ activity space and twin siblings’ shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

scholarly journals Novel approach to modeling high-frequency activity data to assess therapeutic effects of analgesics in chronic pain conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zekun Xu ◽  
Eric Laber ◽  
Ana-Maria Staicu ◽  
B. Duncan X. Lascelles
Keyword(s):  
High Frequency ◽  
Activity Patterns ◽  
Treatment Strategies ◽  
Therapeutic Effects ◽  
Activity Levels ◽  
Activity Data ◽  
Novel Approach ◽  
High Frequency Activity ◽  
Using Data ◽  
Chronic Pain Conditions

AbstractOsteoarthritis (OA) is a chronic condition often associated with pain, affecting approximately fourteen percent of the population, and increasing in prevalence. A globally aging population have made treating OA-associated pain as well as maintaining mobility and activity a public health priority. OA affects all mammals, and the use of spontaneous animal models is one promising approach for improving translational pain research and the development of effective treatment strategies. Accelerometers are a common tool for collecting high-frequency activity data on animals to study the effects of treatment on pain related activity patterns. There has recently been increasing interest in their use to understand treatment effects in human pain conditions. However, activity patterns vary widely across subjects; furthermore, the effects of treatment may manifest in higher or lower activity counts or in subtler ways like changes in the frequency of certain types of activities. We use a zero inflated Poisson hidden semi-Markov model to characterize activity patterns and subsequently derive estimators of the treatment effect in terms of changes in activity levels or frequency of activity type. We demonstrate the application of our model, and its advance over traditional analysis methods, using data from a naturally occurring feline OA-associated pain model.

Bidirectional Association Between Depression and Hearing Loss: Evidence From the China Health and Retirement Longitudinal Study

2021 ◽  
pp. 073346482110423
Author(s):  
Chao Wu
Keyword(s):  
Hearing Loss ◽  
Longitudinal Study ◽  
Cognitive Decline ◽  
Age Related ◽  
Bidirectional Association ◽  
Health Related ◽  
Clinically Significant ◽  
Using Data ◽  
Bidirectional Associations ◽  
Age Related Hearing Loss

The relationship between depression and age-related hearing loss (ARHL) is not fully understood. This study tested the bidirectional associations between clinically significant depressive symptoms (CSDSs) and ARHL in middle-aged and older adults using data from the China Health and Retirement Longitudinal Study. Among 3,418 participants free of baseline ARHL, baseline CSDS was associated with an increased odds of incident ARHL (odds ratio [OR]: 1.51). Cognitive decline, BMI, and arthritis partially mediated the longitudinal CSDS–ARHL association and explained 24% of the variance in the total effect. Among 4,921 participants without baseline CSDS, baseline ARHL was associated with an increased odds of incident CSDS (OR: 1.37). The bidirectional associations remained significant after adjustments for baseline demographic factors, comorbidities, and other health-related covariates. Depression may contribute to the development of ARHL, and vice versa. Interventions in depression, cognitive decline, and arthritis may delay the onset of ARHL and break the vicious circle between them.

scholarly journals Multi-Platform Social Media Use: Little Evidence of Impacts on Adult Well-Being

2020 ◽  
Author(s):  
Sophie Lohmann ◽  
Emilio Zagheni
Keyword(s):  
Social Media ◽  
Media Use ◽  
Scientific Evidence ◽  
General Social Survey ◽  
Well Being ◽  
Young Female ◽  
Social Media Use ◽  
Social Media Platforms ◽  
Data Source ◽  
Using Data

Social media have become a near-ubiquitous part of our lives. The growing concern that their use may alter our well-being has been met with elusive scientific evidence. Existing literature often simplifies social media use as a homogeneous process. In reality, social media use and functions vary widely depending on platform and demographic characteristics of users, and there may be qualitative differences between using few versus many different social media platforms. Using data from the General Social Survey, an underanalyzed data source for this purpose, we characterize intensive social media users and examine how differential platform use impacts well-being. We document substantial heterogeneity in the demography of users and show that intensive users tend to be young, female, more likely to be Black than Hispanic, from high SES backgrounds, from more religious backgrounds, and from families with migration background, compared to both non-users and moderate users. The intensity of social media use seemed largely unrelated to well-being in both unadjusted models and in propensity-score models that adjusted for selection bias and demographic factors. Among middle-aged and older adults, however, intensive social media use may be slightly associated with depressive symptoms. Our findings indicate that although mediums of communication have changed with the advent of social media, these new mediums are not necessarily detrimental to well-being.

scholarly journals Associations among Physical Activity, Diet, and Obesity Measures Change during Adolescence

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Janne H. Maier ◽  
Ronald Barry
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Health Behaviors ◽  
Diet Quality ◽  
Activity Patterns ◽  
Health Study ◽  
Blood Institute ◽  
Age Related ◽  
Juvenile Obesity ◽  
Positive Correlations

Background. Obesity in youth is highly prevalent. Physical activity and diet are influential in obesity development. However, there is a knowledge gap regarding links between activity and diet quality and their combined influence on obesity during adolescence.Objectives. We used five years of data from 2379 adolescent girls in the National Heart Lung and Blood Institute Growth and Health Study to evaluate the association between physical activity and diet quality during adolescence and to assess both as correlates of obesity.Design. Diet, activity, and body composition measures were evaluated pairwise for correlation. A canonical correlation analysis was used to evaluate relationships within and between variable groups. All statistics were examined for trends over time.Results. We found positive correlations between physical activity and diet quality that became stronger with age. Additionally we discovered an age-related decrease in association between obesity correlates and body composition.Conclusion. These results suggest that while health behaviors, like diet and activity, become more closely linked during growth, obesity becomes less influenced by health behaviors and other factors. This should motivate focus on juvenile obesity prevention capitalizing on the pliable framework for establishing healthy diet and physical activity patterns while impact on body composition is greatest.

scholarly journals Age-related differences in muscle activity patterns during walking in healthy individuals

2018 ◽  
Vol 41 ◽  
pp. 124-131 ◽  
Author(s):  
Tamaya Van Criekinge ◽  
Wim Saeys ◽  
Ann Hallemans ◽  
Patricia Van de Walle ◽  
Luc Vereeck ◽  
...  
Keyword(s):  
Muscle Activity ◽  
Activity Patterns ◽  
Healthy Individuals ◽  
Age Related

Deep Learning and Machine Learning Techniques for Analyzing Travelers' Online Reviews

2022 ◽  
pp. 20-39
Author(s):  
Elliot Mbunge ◽  
Benhildah Muchemwa
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Deep Learning ◽  
Hospitality Industry ◽  
Learning Models ◽  
Online Data ◽  
Social Media Platforms ◽  
Using Data ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Social media platforms play a tremendous role in the tourism and hospitality industry. Social media platforms are increasingly becoming a source of information. The complexity and increasing size of tourists' online data make it difficult to extract meaningful insights using traditional models. Therefore, this scoping and comprehensive review aimed to analyze machine learning and deep learning models applied to model tourism data. The study revealed that deep learning and machine learning models are used for forecasting and predicting tourism demand using data from search query data, Google trends, and social media platforms. Also, the study revealed that data-driven models can assist managers and policymakers in mapping and segmenting tourism hotspots and attractions and predicting revenue that is likely to be generated, exploring targeting marketing, segmenting tourists based on their spending patterns, lifestyle, and age group. However, hybrid deep learning models such as inceptionV3, MobilenetsV3, and YOLOv4 are not yet explored in the tourism and hospitality industry.

Shared Space: How North American Olympic Broadcasters Framed Gender on Instagram

2020 ◽  
pp. 216747952093289
Author(s):  
Rich G. Johnson ◽  
Miles Romney ◽  
Kevin Hull ◽  
Ann Pegoraro
Keyword(s):  
Gender Stereotypes ◽  
News Media ◽  
North American ◽  
Female Athletes ◽  
Olympic Games ◽  
Media Framing ◽  
Cross Sectional ◽  
Shared Space ◽  
Canadian Broadcasting Corporation ◽  
Social Media Platforms

The Olympic Games offer scholars the opportunity to better understand how broadcasters visually frame male and female athletes to their large audiences. Traditionally, scholars have focused their efforts on the televised Olympic broadcasts and photojournalism coverage in newspaper and magazines. Scholarship has historically found that female athletes were underrepresented in event coverage and framed along gender stereotypes; however, in more recent Olympic Games, research has shown the news media has provided more equitable coverage between the genders. Yet digital and social media platforms (SMPs) play a significantly larger role in how Olympic broadcasters share content and engage with audiences. Utilizing media framing theory, this study examines how gender is framed on the Olympic Instagram accounts of the two official North American rights holders: the National Broadcasting Corporation (NBC) and the Canadian Broadcasting Corporation (CBC). Researchers collected a cross-sectional sample from the 2016 Summer Games in Rio de Janeiro, Brazil, and the 2018 Winter Games in Pyeongchang, South Korea. Results indicate that NBC and CBC were generally equitable in SMP coverage of men’s and women’s athletic achievements.

scholarly journals Impute.me: An Open-Source, Non-profit Tool for Using Data From Direct-to-Consumer Genetic Testing to Calculate and Interpret Polygenic Risk Scores

2020 ◽  
Vol 11 ◽  
Author(s):  
Lasse Folkersen ◽  
Oliver Pain ◽  
Andrés Ingason ◽  
Thomas Werge ◽  
Cathryn M. Lewis ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Open Source ◽  
Risk Scores ◽  
Non Profit ◽  
Polygenic Risk ◽  
Direct To Consumer ◽  
Using Data

Vascular Risk Moderates Associations between Hippocampal Subfield Volumes and Memory

2013 ◽  
Vol 25 (11) ◽  
pp. 1851-1862 ◽  
Author(s):  
Andrew R. Bender ◽  
Ana M. Daugherty ◽  
Naftali Raz
Keyword(s):  
Dentate Gyrus ◽  
Memory Performance ◽  
Complex Structure ◽  
Vascular Risk Factor ◽  
Advanced Age ◽  
Vascular Risk ◽  
Measurement Occasion ◽  
Age Related ◽  
Path Models ◽  
Using Data

Advanced age and vascular risk negatively affect episodic memory. The hippocampus (HC) is a complex structure, and little is known about the roles of different HC regions in age-related memory declines. Using data from an ongoing longitudinal study, we investigated whether memory functions are related to volumes of specific HC subregions (CA1-2, CA3-4/dentate gyrus, and subiculum). Furthermore, we inquired if arterial hypertension, a common age-related vascular risk factor, modifies age-related differences in HC regional volumes, concurrent memory performance, and improvement in memory over multiple administrations. Healthy adults (n = 49, 52–82 years old) completed associative recognition and free recall tasks. In grouped path models, covariance structures differed between hypertensive and normotensive participants. Whereas larger CA3-4/dentate gyrus volumes predicted greater improvement in associative memory over repeated tests regardless of vascular risk, CA1-2 volumes were associated with improvement in noun recall only in hypertensive participants. Only among hypertensive participants, CA1-2 volumes negatively related to age and CA3-4/dentate gyrus and CA1-2 volumes were associated with performance at the last measurement occasion. These findings suggest that relatively small regions of the HC may play a role in age-related memory declines and that vascular risk factors associated with advanced age may modify that relationship.

scholarly journals Performance of Open Source Precise Point Positioning Software Using Single-Frequency GPS Data

2006 ◽  
Vol 41 (2) ◽  
pp. 79-86 ◽  
Author(s):  
Chalermchon Satirapod ◽  
Somchai Kriengkraiwasin
Keyword(s):  
Open Source ◽  
Precise Point Positioning ◽  
Main Tool ◽  
Single Frequency ◽  
Gps Data ◽  
Differential Gps ◽  
Satellite Clock ◽  
Positioning Accuracy ◽  
Point Positioning ◽  
Station Location

Performance of Open Source Precise Point Positioning Software Using Single-Frequency GPS Data This research aims to assess the performance of GPS Precise Point Positioning (PPP) with code and carrier phase observations from L1 signal collected from geodetic GPS receiver around the world. A simple PPP software developed for processing the single frequency GPS data is used as a main tool to assess a positioning accuracy. The precise orbit and precise satellite clock corrections were introduced into the software to reduce the orbit and satellite clock errors, while ionosphere-free code and phase observations were constructed to mitigate the ionospheric delay. The remaining errors (i.e. receiver clock error, ambiguity term) are estimated using Extended Kalman Filter technique. The data retrieved from 5 IGS stations located in different countries were used in this study. In addition, three different periods of data were downloaded for each station. The obtained data were then cut into 5-min, 10-min, 15-min and 30-min data segments, and each data segment was individually processed with the developed PPP software to produce final coordinates. Results indicate that the use of 5-min data span can provide a horizontal positioning accuracy at the same level as a pseudorange-based differential GPS technique. Furthermore, results confirm effects of station location and seasonal variation on obtainable accuracies.

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