Using Location Data From Mobile Phones to Study Participation in Mass Protests

2020 ◽  
pp. 004912412091492
Author(s):  
Assaf Rotman ◽  
Michael Shalev
Keyword(s):  
Temporal Resolution ◽  
Mobile Phones ◽  
Mass Mobilization ◽  
Study Participation ◽  
Data Set ◽  
Mobile Location ◽  
Location Data ◽  
Wide Range ◽  
Potential Applications ◽  
Privacy Issues

Automatically collected behavioral data on the location of users of mobile phones offer an unprecedented opportunity to measure mobilization in mass protests, while simultaneously expanding the range of researchable questions. Location data not only improve estimation of the number and composition of participants in large demonstrations. Thanks to high spatial and temporal resolution they also reveal when, where, and with whom different sociopolitical sectors join a protest campaign. This article compares the features and advantages of this type of data with other methods of measuring who participates in street protests. The steps in preparing a usable data set are explained with reference to a six-week campaign of mass mobilization in Israel in 2011. Findings based on the Israeli data set illustrate a wide range of potential applications, pertaining to both the determinants and consequences of protest participation. Limitations of mobile location data and the privacy issues it raises are also discussed.

scholarly journals Mobility Trends and their effect on Traffic Safety During the Covid-19 Pandemic: Case Study Republic of Croatia

2021 ◽  
Vol 67 (4) ◽  
pp. 17-20
Author(s):  
Ana Globočnik Žunac ◽  
Predrag Brlek ◽  
Ivan Cvitković ◽  
Goran Kaniški
Keyword(s):  
Traffic Safety ◽  
Travel Behavior ◽  
Human Mobility ◽  
Transport Systems ◽  
Data Set ◽  
Mobile Location ◽  
Location Data ◽  
Wide Availability ◽  
Accident Data ◽  
The Impact

Safety analysis focuses on how traffic safety can change while mobility analysis is used to determine how people change travel behavior. The integration of mobility, safety and behavioral data related to COVID-19 can provide valuable insights to decision makers. Wide availability of mobile sensors has given us the opportunity to be able to assess changes in the performance and mobility of transport systems in, almost real time. The researchers also measured the impact of COVID-19 on human mobility using public mobile location data available from many companies such as Google and Apple, which is very useful for changing human mobility. The platforms produce aggregated metrics of daily mobility, including the purpose of travel, the mode of travel, and imputations of social demographics. Based on a comprehensive data set of people who participated in the collected accident data and mobile device data, we record the impact of COVID-19 on traffic safety. The paper systematically and statistically approaches the assessment of road safety in Croatia during the COVID-19 pandemic.

scholarly journals Mobility Trends and their effect on Traffic Safety During the Covid-19 Pandemic: Case Study Republic of Croatia

2021 ◽  
Vol 67 (4) ◽  
pp. 17-20
Author(s):  
Ana Globočnik Žunac ◽  
Predrag Brlek ◽  
Ivan Cvitković ◽  
Goran Kaniški
Keyword(s):  
Traffic Safety ◽  
Travel Behavior ◽  
Human Mobility ◽  
Transport Systems ◽  
Data Set ◽  
Mobile Location ◽  
Location Data ◽  
Wide Availability ◽  
Accident Data ◽  
The Impact

Safety analysis focuses on how traffic safety can change while mobility analysis is used to determine how people change travel behavior. The integration of mobility, safety and behavioral data related to COVID-19 can provide valuable insights to decision makers. Wide availability of mobile sensors has given us the opportunity to be able to assess changes in the performance and mobility of transport systems in, almost real time. The researchers also measured the impact of COVID-19 on human mobility using public mobile location data available from many companies such as Google and Apple, which is very useful for changing human mobility. The platforms produce aggregated metrics of daily mobility, including the purpose of travel, the mode of travel, and imputations of social demographics. Based on a comprehensive data set of people who participated in the collected accident data and mobile device data, we record the impact of COVID-19 on traffic safety. The paper systematically and statistically approaches the assessment of road safety in Croatia during the COVID-19 pandemic.

scholarly journals Liberation Technology: Mobile Phones and Political Mobilization in Africa

Econometrica ◽  
2020 ◽  
Vol 88 (2) ◽  
pp. 533-567 ◽  
Author(s):  
Marco Manacorda ◽  
Andrea Tesei
Keyword(s):  
Mobile Phones ◽  
Imperfect Information ◽  
Political Mobilization ◽  
Digital Information ◽  
Mass Mobilization ◽  
Multiple Sources ◽  
Data Set ◽  
Economic Downturns ◽  
Information And Communication ◽  
The Cost

Can digital information and communication technology foster mass political mobilization? We use a novel georeferenced data set for the entire African continent between 1998 and 2012 on the coverage of mobile phone signal together with georeferenced data from multiple sources on the occurrence of protests and on individual participation in protests to bring this argument to empirical scrutiny. We find that while mobile phones are instrumental to mass mobilization, this only happens during economic downturns, when reasons for grievance emerge and the cost of participation falls. The results are in line with insights from a network model with imperfect information and strategic complementarities in protest occurrence. Mobile phones make individuals more responsive to both changes in economic conditions—a mechanism that we ascribe to enhanced information—and to their neighbors' participation—a mechanism that we ascribe to enhanced coordination.

scholarly journals An introduction to learning algorithms and potential applications in geomorphometry and Earth surface dynamics

2016 ◽  
Vol 4 (2) ◽  
pp. 445-460 ◽  
Author(s):  
Andrew Valentine ◽  
Lara Kalnins
Keyword(s):  
Learning Algorithm ◽  
Learning Algorithms ◽  
Earth Surface ◽  
Surface Dynamics ◽  
Data Set ◽  
Wide Range ◽  
Computational Implementation ◽  
Potential Applications ◽  
Abstract Learning

Abstract. “Learning algorithms” are a class of computational tool designed to infer information from a data set, and then apply that information predictively. They are particularly well suited to complex pattern recognition, or to situations where a mathematical relationship needs to be modelled but where the underlying processes are not well understood, are too expensive to compute, or where signals are over-printed by other effects. If a representative set of examples of the relationship can be constructed, a learning algorithm can assimilate its behaviour, and may then serve as an efficient, approximate computational implementation thereof. A wide range of applications in geomorphometry and Earth surface dynamics may be envisaged, ranging from classification of landforms through to prediction of erosion characteristics given input forces. Here, we provide a practical overview of the various approaches that lie within this general framework, review existing uses in geomorphology and related applications, and discuss some of the factors that determine whether a learning algorithm approach is suited to any given problem.

Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

2019 ◽  
Vol 16 (7) ◽  
pp. 808-817 ◽  
Author(s):  
Laxmi Banjare ◽  
Sant Kumar Verma ◽  
Akhlesh Kumar Jain ◽  
Suresh Thareja
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Aromatase Inhibitors ◽  
Direct Synthesis ◽  
3D Qsar ◽  
Chemotherapeutic Agents ◽  
Modeling Tools ◽  
Data Set ◽  
Wide Range ◽  
Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

scholarly journals A Self-Spatial Adaptive Weighting Based U-Net for Image Segmentation

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 348
Author(s):  
Choongsang Cho ◽  
Young Han Lee ◽  
Jongyoul Park ◽  
Sangkeun Lee
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Feature Maps ◽  
Data Set ◽  
Feature Map ◽  
Adaptive Weighting ◽  
Spatially Adaptive ◽  
Wide Range ◽  
Decoder Architecture

Semantic image segmentation has a wide range of applications. When it comes to medical image segmentation, its accuracy is even more important than those of other areas because the performance gives useful information directly applicable to disease diagnosis, surgical planning, and history monitoring. The state-of-the-art models in medical image segmentation are variants of encoder-decoder architecture, which is called U-Net. To effectively reflect the spatial features in feature maps in encoder-decoder architecture, we propose a spatially adaptive weighting scheme for medical image segmentation. Specifically, the spatial feature is estimated from the feature maps, and the learned weighting parameters are obtained from the computed map, since segmentation results are predicted from the feature map through a convolutional layer. Especially in the proposed networks, the convolutional block for extracting the feature map is replaced with the widely used convolutional frameworks: VGG, ResNet, and Bottleneck Resent structures. In addition, a bilinear up-sampling method replaces the up-convolutional layer to increase the resolution of the feature map. For the performance evaluation of the proposed architecture, we used three data sets covering different medical imaging modalities. Experimental results show that the network with the proposed self-spatial adaptive weighting block based on the ResNet framework gave the highest IoU and DICE scores in the three tasks compared to other methods. In particular, the segmentation network combining the proposed self-spatially adaptive block and ResNet framework recorded the highest 3.01% and 2.89% improvements in IoU and DICE scores, respectively, in the Nerve data set. Therefore, we believe that the proposed scheme can be a useful tool for image segmentation tasks based on the encoder-decoder architecture.

scholarly journals Japan’s voluntary lockdown: further evidence based on age-specific mobile location data

2021 ◽  
Author(s):  
Tsutomu Watanabe ◽  
Tomoyoshi Yabu
Keyword(s):  
Age Groups ◽  
Evidence Based ◽  
Intervention Effect ◽  
Information Effect ◽  
Mobile Location ◽  
Serious Illness ◽  
Location Data ◽  
Voluntary Response ◽  
Younger Age ◽  
Age Profile

AbstractChanges in people’s behavior during the COVID-19 pandemic can be regarded as the result of two types of effects: the “intervention effect” (changes resulting from government orders for people to change their behavior) and the “information effect” (voluntary changes in people’s behavior based on information about the pandemic). Using age-specific mobile location data, we examine how the intervention and information effects differ across age groups. Our main findings are as follows. First, the age profile of the intervention effect shows that the degree to which people refrained from going out was smaller for older age groups, who are at a higher risk of serious illness and death, than for younger age groups. Second, the age profile of the information effect shows that the degree to which people stayed at home tended to increase with age for weekends and holidays. Thus, while Acemoglu et al. (2020) proposed targeted lockdowns requiring stricter lockdown policies for the oldest group in order to protect those at a high risk of serious illness and death, our findings suggest that Japan’s government intervention had a very different effect in that it primarily reduced outings by the young, and what led to the quarantining of older groups at higher risk instead was people’s voluntary response to information about the pandemic. Third, the information effect has been on a downward trend since the summer of 2020. It is relatively more pronounced among the young, so that the age profile of the information effect remains upward sloping.

scholarly journals A Slot-Die Technique for the Preparation of Continuous, High-Area, Chitosan-Based Thin Films

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1566
Author(s):  
Oliver J. Pemble ◽  
Maria Bardosova ◽  
Ian M. Povey ◽  
Martyn E. Pemble
Keyword(s):  
Thin Films ◽  
Mechanical Properties ◽  
High Volume ◽  
Mechanical Anisotropy ◽  
Diverse Range ◽  
Direction Parallel ◽  
High Area ◽  
Wide Range ◽  
Slot Die ◽  
Potential Applications

Chitosan-based films have a diverse range of potential applications but are currently limited in terms of commercial use due to a lack of methods specifically designed to produce thin films in high volumes. To address this limitation directly, hydrogels prepared from chitosan, chitosan-tetraethoxy silane, also known as tetraethyl orthosilicate (TEOS) and chitosan-glutaraldehyde have been used to prepare continuous thin films using a slot-die technique which is described in detail. By way of preliminary analysis of the resulting films for comparison purposes with films made by other methods, the mechanical strength of the films produced was assessed. It was found that as expected, the hybrid films made with TEOS and glutaraldehyde both show a higher yield strength than the films made with chitosan alone. In all cases, the mechanical properties of the films were found to compare very favorably with similar measurements reported in the literature. In order to assess the possible influence of the direction in which the hydrogel passes through the slot-die on the mechanical properties of the films, testing was performed on plain chitosan samples cut in a direction parallel to the direction of travel and perpendicular to this direction. It was found that there was no evidence of any mechanical anisotropy induced by the slot die process. The examples presented here serve to illustrate how the slot-die approach may be used to create high-volume, high-area chitosan-based films cheaply and rapidly. It is suggested that an approach of the type described here may facilitate the use of chitosan-based films for a wide range of important applications.

scholarly journals Health Benefits of Uses and Applications of Moringa oleifera in Bakery Products

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 318
Author(s):  
Paula García Milla ◽  
Rocío Peñalver ◽  
Gema Nieto
Keyword(s):  
Moringa Oleifera ◽  
Essential Amino Acids ◽  
Bakery Products ◽  
Unani Medicine ◽  
Functional Value ◽  
Organoleptic Characteristics ◽  
Wide Range ◽  
Potential Applications ◽  
Medicinal Properties ◽  
Excellent Source

Moringa oleifera belongs to the Moringaceae family and is the best known of the native Moringa oleifera genus. For centuries, it has been used as a system of Ayurvedic and Unani medicine and has a wide range of nutritional and bioactive compounds, including proteins, essential amino acids, carbohydrates, lipids, fibre, vitamins, minerals, phenolic compounds, phytosterols and others. These characteristics allow it to have pharmacological properties, including anti-diabetic, anti-inflammatory, anticarcinogenic, antioxidant, cardioprotective, antimicrobial and hepatoprotective properties. The entire Moringa oleifera plant is edible, including its flowers, however, it is not entirely safe, because of compounds that have been found mainly in the root and bark, so the leaf was identified as the safest. Moringa oleifera is recognised as an excellent source of phytochemicals, with potential applications in functional and medicinal food preparations due to its nutritional and medicinal properties; many authors have experimented with incorporating it mainly in biscuits, cakes, brownies, meats, juices and sandwiches. The results are fascinating, as the products increase their nutritional value; however, the concentrations cannot be high, as this affects the organoleptic characteristics of the supplemented products. The aim of this study is to review the application of Moringa oleifera in bakery products, which will allow the creation of new products that improve their nutritional and functional value.

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