Regional insights on tobacco-related tweets: unveiling user opinions and usage patterns.

Introduction: Tobacco consumption and its impact on health remain high worldwide. Additionally, it is a contentious issue generating significant controversy. Twitter has proven to be a useful platform for evaluating public health topics related to population health behaviors, and tobacco consumption. Objective: The objective of this study is to analyze the content of tweets related to tobacco. Moreover, geolocation data will be considered to understand regional differences. Methods: Tweets published between 2018 and 2022, in both English and Spanish, containing the keyword "tobacco," were analyzed. A total of 56,926 tweets were obtained. The tweets were classified into different categories. 550 tweets were manually analyzed, and an automated and computerized classification was performed for the remaining and largest subset of tweets. Results: The analysis yielded 30,812 classifiable tweets. Healthcare professionals were the most frequent contributors to the topic (50.2%), with the most common theme being general information about the toxic effects of tobacco. 57.9% of the tweets discussed the harmful effects of tobacco on health, with fear being the predominant emotion. The largest number of tweets were located in America. Conclusions: Our study revealed a substantial number of tweets highlighting the health risks and negative perceptions of tobacco consumption. Africa showed the lowest percentage of tweets discussing the health risks associated with tobacco, coinciding with the continent having the least developed anti-tobacco policies. Healthcare professionals emerged as the most prominent users discussing the topic, which is encouraging as they play a crucial role in disseminating accurate and scientific health information.

Passive Polarized Vision for Autonomous Vehicles: A Review.

This review article aims to address common research questions in passive polarized vision for robotics. What kind of polarization sensing can we embed into robots? Can we find our geolocation and true north heading by detecting light scattering from the sky as animals do? How should polarization images be related to the physical properties of reflecting surfaces in the context of scene understanding? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying future directions in passive polarized vision for robotics. After an introduction, three key interconnected areas will be covered in the following sections: embedded polarization imaging; polarized vision for robotics navigation; and polarized vision for scene understanding. We will then discuss how polarized vision, a type of vision commonly used in the animal kingdom, should be implemented in robotics; this type of vision has not yet been exploited in robotics service. Passive polarized vision could be a supplemental perceptive modality of localization techniques to complement and reinforce more conventional ones.

Combining acoustic telemetry with archival tagging to investigate the spatial dynamic of the understudied pollack, Pollachius pollachius.

Combining fish tracking methods is a promising way of leveraging the strengths of each approach while mitigating their individual weaknesses. Acoustic telemetry provides presence information as the fish move within receiver range, eliminating the need for tag recovery. Archival tags, on the other hand, record environmental variables on tag retrieval, enabling continuous path reconstruction of a fish beyond coastal regions. This study capitalizes on the combination of both methods for geolocating pollack, Pollachius pollachius, an understudied species of the northeast Atlantic, where declining stocks are raising concern. Essential knowledge of population structure and connectivity between essential habitats is critically lacking and could help inform stock assessment and management. The aims of the study were (1) to evaluate the feasibility of double-tagging pollack, known for being challenging to tag, and (2) to track seasonal movements across the Channel to gain first insights into pollack spatial ecology. In 2022, an extensive network of acoustic receivers was been deployed in the Channel along the French, English, and Belgian coasts as part of the Fish Intel project. We tagged 83 pollack with acoustic transmitters, among which 48 were double-tagged with data storage tags. Post-tagging survival assessment, conducted on a subset of 35 individuals, revealed a successful procedure with a 97% short-term survival rate. By October 2023, the acoustic telemetry network detected 30 out of 83 pollack at least once, with no large-scale movements observed across the Channel. Presence in the network fluctuates seasonally, peaking in summer, particularly among immature fish. Integrating acoustic detections with temperature and depth time series in a geolocation model enabled trajectory reconstruction of 10 recaptured pollack, seven of which were detected by the network. This combined tracking approach revealed coastal movements along the coast of Brittany in France, highlighting the ecological significance of the Iroise Sea for pollack throughout the year, particularly in summer. The geolocation model also suggested movements towards the entrance of the western Channel. This study highlights the complementarity of acoustic telemetry and archival tagging in reconstructing fish movements in their natural environment. As data accumulate, these innovative tracking methods promise to continually unveil new insights into the spatial ecology of the understudied pollack, which is essential for the species' management.

Utilization of the social media platform Snapchat in the care of an acutely suicidal individual.

Background/Case Presentation: An 18-year-old female college student shared an electronic message with her friends in which she discussed plans to harm herself through the ingestion of a highly toxic substance. Concerned friends activated emergency healthcare resources, who were dispatched to the individual's residence. Based on the known toxicity of the substance, locating the individual expeditiously to ensure her safety and well-being remained paramount. Upon arrival of collegiate-based health services, emergency medical services, and law enforcement, however, the individual was unable to be located. University healthcare and prehospital providers quickly recognized that the individual's recent location was visible to her friends through the social media platform Snapchat. Based on information gathered from her shared friends on the social media platform, a geo-location was identified. Law enforcement and EMS personnel canvased the identified area, successfully locating the individual. Conclusion: This case highlights the innovative use of smartphone technology to locate a person experiencing an acute medical emergency who hadn't summoned the services on her own.

Bridging and Bonding Social Capital by Analyzing the Demographics, User Activities, and Social Network Dynamics of Sexual Assault Centers on Twitter: Mixed Methods Study.

BACKGROUND: Social media platforms have gained popularity as communication tools for organizations to engage with clients and the public, disseminate information, and raise awareness about social issues. From a social capital perspective, relationship building is seen as an investment, involving a complex interplay of tangible and intangible resources. Social media-based social capital signifies the diverse social networks that organizations can foster through their engagement on social media platforms. Literature underscores the great significance of further investigation into the scope and nature of social media use, particularly within sectors dedicated to service delivery, such as sexual assault organizations. OBJECTIVE: This study aims to fill a research gap by investigating the use of Twitter by sexual assault support agencies in Canada. It seeks to understand the demographics, user activities, and social network structure within these organizations on Twitter, focusing on building social capital. The research questions explore the demographic profile, geographic distribution, and Twitter activity of these organizations as well as the social network dynamics of bridging and bonding social capital. METHODS: This study used purposive sampling to investigate sexual assault centers in Canada with active Twitter accounts, resulting in the identification of 124 centers. The Twitter handles were collected, yielding 113 unique handles, and their corresponding Twitter IDs were obtained and validated. A total of 294,350 tweets were collected from these centers, covering >93.54% of their Twitter activity. Preprocessing was conducted to prepare the data, and descriptive analysis was used to determine the center demographics and age. Furthermore, geolocation mapping was performed to visualize the center locations. Social network analysis was used to explore the intricate relationships within the network of sexual assault center Twitter accounts, using various metrics to assess the network structure and connectivity dynamics. RESULTS: The results highlight the substantial presence of sexual assault organizations on Twitter, particularly in provinces such as Ontario, British Columbia, and Quebec, underscoring the importance of tailored engagement strategies considering regional disparities. The analysis of Twitter account creation years shows a peak in 2012, followed by a decline in new account creations in subsequent years. The monthly tweet activity shows November as the most active month, whereas July had the lowest activity. The study also reveals variations in Twitter activity, account creation patterns, and social network dynamics, identifying influential social queens and marginalized entities within the network. CONCLUSIONS: This study presents a comprehensive landscape of the demographics and activities of sexual assault centers in Canada on Twitter. This study suggests that future research should explore the long-term consequences of social media use and examine stakeholder perceptions, providing valuable insights to improve communication practices within the nonprofit human services sector and further the missions of these organizations.

Explore variation of salivary bacteria across time and geolocations.

Saliva is an informative body fluid that can be found at various crime scenes, and the salivary bacterial community has been revealed it is a potential auxiliary target for forensic identification. However, the variation of salivary bacterial community composition across time and geolocation needs to be explored. The study was designed to be carried out during the winter vacation that was across about 50 days and eight geographic locations. The high throughput sequencing was performed with the V3-V4 region of the16S rRNA gene to explore salivary bacterial community composition. An overall slight fluctuation of the salivary bacteria was observed, which primarily occurred in the relative abundance of the salivary bacterial taxa. The results of principal coordinate analysis and hierarchical clustering showed samples were clustered by the individuals. All individuals could be correctly identified with the random forest model. In summation, although the relative abundance of salivary bacteria varied across the changes of time and geolocation, the individualized characteristic of salivary bacteria remained steady, which is beneficial for the salivary bacterial application in personal identification.

Use of strontium isotope ratios in potential geolocation of Ajnala skeletal remains: a forensic archeological study.

Stable isotope methods for provenance of unidentified human remains are relatively a newer field of enquiry in forensic archeology. It is of great interest for forensic experts these days. The application of strontium isotope analyses for estimating geolocation of archeological remains is of great interest in bioarcheology and modern forensics. The strontium (Sr) isotope composition of human bones and teeth has been widely used to reconstruct an individual's geo-affiliation, residential mobility, and migration history. Thousands of unknown human remains, reportedly belonging to 282 Indian soldiers of 26th Native Bengal regiment and killed in 1857, were exhumed non-scientifically from an abandoned well situated underneath a religious structure at Ajnala (Amritsar, India). Whether these remains belonged to the individuals, local or non-local to the site, was the important forensic archeological question to be answered by doing their thorough forensic anthropological examinations. In the present study, 27 mandibular teeth (18 s molars, 6 first molars, and 3 premolars) collected from the Ajnala skeletal assemblage were processed for strontium isotope analysis, and the measured ratios were compared with published isotope baseline data to estimate the locality status of these remains. The Sr isotopic values were concentrated in the range of 0.7175 to 0.7270. The comparative analysis of isotopic ratios revealed that most individuals buried in the Ajnala well have 87Sr/86Sr values close to the river as well as groundwater of the Gangetic plain (less radiogenic 87Sr/86Sr ~ 0.716); most likely originated near Varanasi (Uttar Pradesh, India) region, whereas the individuals with higher 87Sr/86Sr ratios (~ 0.7200) probably resided in the West Bengal and Bihar areas where the river as well as groundwater of the Gangetic plain is relatively more radiogenic. Thus, the strontium isotope results reveal that the Ajnala individuals did not grow up or live in the Amritsar region during their childhood, and this observation complemented the previous forensic anthropological and molecular findings. There is very little Indian data on the bioavailable strontium, so the inferences from the present study estimating Sr isotope abundances are expected to provide baseline data for future forensic provenance studies that will contribute to the global efforts of mapping Sr isotope variations by the isotope community.

Sea ice concentration decline in an important Adélie penguin molt area.

Unlike in many polar regions, the spatial extent and duration of the sea ice season have increased in the Ross Sea sector of the Southern Ocean during the satellite era. Simultaneously, populations of Adélie penguins, a sea ice obligate, have been stable or increasing in the region. Relationships between Adélie penguin population growth and sea ice concentration (SIC) are complex, with sea ice driving different, sometimes contrasting, demographic patterns. Adélie penguins undergo a complete molt annually, replacing all their feathers while fasting shortly after the breeding season. Unlike most penguin species, a majority of Adélies are thought to molt on sea ice, away from the breeding colonies, which makes this period particularly difficult to study. Here, we evaluate the hypothesis that persistent areas of high SIC provide an important molting habitat for Adélie penguins. We analyzed data from geolocating dive recorders deployed year-round on 195 adult penguins at two colonies in the Ross Sea from 2017 to 2019. We identified molt by detecting extended gaps in postbreeding diving activity and used associated locations to define two key molting areas. Remotely sensed data indicated that SIC during molt was anomalously low during the study and has declined in the primary molt area since 1980. Further, annual return rates of penguins to breeding colonies were positively correlated with SIC in the molt areas over 20 y. Together these results suggest that sea ice conditions during Adélie penguin molt may represent a previously underappreciated annual bottleneck for adult survival.

Diurnal migration patterns in willow warblers differ between the western and eastern flyways.

It is a long-standing view that the main mechanism maintaining narrow migratory divides in passerines is the selection against intermediate and suboptimal migratory direction, but empirical proof of this is still lacking. We present novel results from a willow warbler migratory divide in central Sweden from where birds take the typical SW and SE as well as intermediate routes to winter quarters in Africa. We hypothesized that individuals that take the intermediate route are forced to migrate in daytime more often when crossing wide ecological barriers than birds that follow the typical western or eastern flyways. Analyses of geolocator tracks of willow warblers breeding across the entire Sweden, including the migratory divide, provided no support for our hypothesis. Instead, birds that migrated along the western flyway were the most likely to undertake full day flights. The probability of migrating for a full day when crossing major barriers declined linearly from west to east. We speculate that this difference is possibly caused by more challenging conditions in the western part of the Sahara Desert, such as the lack of suitable day-time roost sites. However, it may equally likely be that willow warblers benefit from migrating in daytime if favorable tailwinds offer assistance.

Capturing emergency dispatch address points as geocoding candidates to quantify delimited confidence in residential geolocation.

BACKGROUND: In response to citizens' concerns about elevated cancer incidence in their locales, US CDC proposed publishing cancer incidence at sub-county scales. At these scales, confidence in patients' residential geolocation becomes a key constraint of geospatial analysis. To support monitoring cancer incidence in sub-county areas, we presented summary metrics to numerically delimit confidence in residential geolocation. RESULTS: We defined a concept of Residential Address Discriminant Power (RADP) as theoretically perfect within all residential addresses and its practical application, i.e., using Emergency Dispatch (ED) Address Point Candidates of Equivalent Likelihood (CEL) to quantify Residential Geolocation Discriminant Power (RGDP) to approximate RADP. Leveraging different productivity of probabilistic, deterministic, and interactive geocoding record linkage, we simultaneously detected CEL for 5,807 cancer cases reported to North Carolina Central Cancer Registry (NC CCR)- in January 2022. Batch-match probabilistic and deterministic algorithms matched 86.0% cases to their unique ED address point candidates or a CEL, 4.4% to parcel site address, and 1.4% to street centerline. Interactively geocoded cases were 8.2%. To demonstrate differences in residential geolocation confidence between enumeration areas, we calculated sRGDP for cancer cases by county and assessed the existing uncertainty within the ED data, i.e., identified duplicate addresses (as CEL) for each ED address point in the 2014 version of the NC ED data and calculated ED_sRGDP by county. Both summary RGDP (sRGDP) (0.62-1.00) and ED_sRGDP (0.36-1.00) varied across counties and were lower in rural counties (p < 0.05); sRGDP correlated with ED_sRGDP (r = 0.42, p < 0.001). The discussion covered multiple conceptual and economic issues attendant to quantifying confidence in residential geolocation and presented a set of organizing principles for future work. CONCLUSIONS: Our methodology produces simple metrics - sRGDP - to capture confidence in residential geolocation via leveraging ED address points as CEL. Two facts demonstrate the usefulness of sRGDP as area-based summary metrics: sRGDP variability between counties and the overall lower quality of residential geolocation in rural vs. urban counties. Low sRGDP for the cancer cases within the area of interest helps manage expectations for the uncertainty in cancer incidence data. By supplementing cancer incidence data with sRGDP and ED_sRGDP, CCRs can demonstrate transparency in geocoding success, which may help win citizen trust.

SkyPole-A method for locating the north celestial pole from skylight polarization patterns.

True north can be determined on Earth by three means: magnetic compasses, stars, and via the global navigation satellite systems (GNSS), each of which has its own drawbacks. GNSS are sensitive to jamming and spoofing, magnetic compasses are vulnerable to magnetic interferences, and the stars can be used only at night with a clear sky. As an alternative to these methods, nature-inspired navigational cues are of particular interest. Celestial polarization, which is used by insects such as Cataglyphis ants, can provide useful directional cues. Migrating birds calibrate their magnetic compasses by observing the celestial rotation at night. By combining these cues, we have developed a bioinspired optical method for finding the celestial pole during the daytime. This method, which we have named SkyPole, is based on the rotation of the skylight polarization pattern. A polarimetric camera was used to measure the degree of skylight polarization rotating with the Sun. Image difference processes were then applied to the time-varying measurements in order to determine the north celestial pole's position and thus the observer's latitude and bearing with respect to the true north.

Geolocation prediction from STR genotyping: a pilot study in five geographically distinct global populations.

BACKGROUND: Traditional CE-based STR profiles are highly useful for the purpose of individualisation. However, they do not give any additional information without the presence of the reference sample for comparison. AIM: To assess the usability of STR-based genotypes for the prediction of an individual's geolocation. SUBJECTS AND METHODS: Genotype data from five geographically distinct populations, i.e. Caucasian, Hispanic, Asian, Estonian, and Bahrainian, were collected from the published literature. RESULTS: A significant difference (p < 0.05) in the observed genotypes was found between these populations. D1S1656 and SE33 showed substantial differences in their genotype frequencies across the tested populations. SE33, D12S391, D21S11, D19S433, D18S51, and D1S1656 were found to have the highest occurrence of "unique genotype's" in different populations. In addition, D12S391 and D13S317 exhibited distinct population-specific "most frequent genotypes." CONCLUSIONS: Three different prediction models have been proposed for genotype to geolocation prediction, i.e. (i) use of unique genotypes of a population, (ii) use of the most frequent genotype, and (iii) a combinatorial approach of unique and most frequent genotypes. These models could aid the investigating agencies in cases where no reference sample is available for comparison of the profile.

The "allergic nose as a pollen detector" concept: e-Diaries to predict pollen trends.

Hirst pollen traps and operator pollen recognition are worldwide used by aerobiologists, providing essential services for the diagnosis and monitoring of allergic patients. More recently, semiautomated or fully automated detector systems have been developed, which facilitate prediction of pollen exposure and risk for the individual patient. In parallel, smartphone apps consisting of short questionnaires filled in daily by the patient/user provide daily scores, time trajectories, and descriptive reports of the severity of respiratory allergies in patients with pollen allergy. The usual scientific and clinical approach to this matter is to monitor the environment (pollen concentration) in order to predict the risk of symptoms (allergic rhinitis) in a population. We discuss here the opposite, contraintuitive possibility, that is, the use of e-diaries to collect daily information of mono-sensitized pollen-allergic patients in order to predict the clinically efficient airborne exposure to a given pollen, area, and time period. In line with the "Patient as Sensor" concept, proposed in 2013 by Bernd Resch, the "allergic nose" may be used as a pollen detector in addition to existing calibrated hardware sensors, namely the pollen stations, thus contributing with individual measurements, sensations, and symptoms' perception. The target of this review is to present a novel concept of pollen monitoring based on "pollen-detector" patients to inspire future cooperative studies aimed at investigating and hopefully validating our hypothesis.

Habitat use, survival, and migration of a little-known East Asian endemic, the yellow-throated bunting Emberiza elegans.

Basic information on the ecology of species is key for their conservation. Here we study the ecology of the little-known yellow-throated bunting Emberiza elegans based on a multi-year study on its breeding grounds in the Russian Far East. For the first time in this species, we quantified breeding habitat parameters, calculated sex-specific apparent survival, and determined individual nonbreeding locations using light-level geolocation. We found that the habitat around song posts of male yellow-throated buntings is characterized by tree and shrub layers on richly littered moist ground. Habitat use overlaps with co-occurring Tristram's Buntings Emberiza tristrami and Black-faced Buntings E. spodocephala, but territories differ especially in tree cover and litter cover. Based on 4 years of color-ringing data of 72 individuals, we calculated an apparent survival rate of 36%, with higher survival estimates for male than for female yellow-throated buntings. We found no effect of carrying a geolocator on survival. We retrieved six geolocators from males. All birds migrated south-westward during autumn and spent the nonbreeding season at locations in China 700-1700 km away from their breeding sites. At least two individuals spent the boreal winter outside of the known range in northern or central China. Birds left the breeding area between early October and early November and returned between mid-March and mid-April. Our data on habitat use, survival rate, and migratory connectivity will help to assess threats to the populations of this enigmatic species, which might include habitat loss due to forest fires on the breeding grounds, and unsustainable harvest for consumption during the nonbreeding season.

Probing sociodemographic influence on code-switching and language choice in Quebec with geolocation of tweets.

This paper investigates the influence of the relative size of speech communities on language use in multilingual regions and cities. Due to peoples' everyday mobility inside a city, it is still unclear whether the size of a population matters for language use on a sub-city scale. By testing the correlation between the size of a population and language use on various spatial scales, this study will contribute to a better understanding of the extent to which sociodemographic factors influence language use. The present study investigates two particular phenomena that are common to multilingual speakers, namely language mixing or Code-Switching and using multiple languages without mixing. Demographic information from a Canadian census will make predictions about the intensity of Code-Switching and language use by multilinguals in cities of Quebec and neighborhoods of Montreal. Geolocated tweets will be used to identify where these linguistic phenomena occur the most and the least. My results show that the intensity of Code-Switching and the use of English by bilinguals is influenced by the size of anglophone and francophone populations on various spatial scales such as the city level, land use level (city center vs. periphery of Montreal), and large urban zones on the sub-city level, namely the western and eastern urban zones of Montreal. However, the correlation between population figures and language use is difficult to measure and evaluate on a much smaller sub-urban scale such as the city block scale due to factors such as population figures missing from the census and people's mobility. A qualitative evaluation of language use on a small spatial scale seems to suggest that other social influences such as the location context or topic of discussion are much more important predictors for language use than population figures. Methods will be suggested for testing this hypothesis in future research. I conclude that geographic space can provide us information about the relation between language use in multilingual cities and sociodemographic factors such as a speech community's size and that social media is a valuable alternative data source for sociolinguistic research that offers new insights into the mechanisms of language use such as Code-Switching.

Application of Gaussian Mixtures in a Multimodal Kalman Filter to Estimate the State of a Nonlinearly Moving System Using Sparse Inaccurate Measurements in a Cellular Radio Network.

Kalman filter is a well-established accuracy correction method in control, guidance, and navigation. With the popularity of mobile communication and ICT, Kalman Filter has been used in many new applications related to positioning based on spatiotemporal data from the cellular network. Despite the low accuracy compared to Global Positioning System, the method is an excellent supplement to other positioning technologies. It is often used in sensor fusion setups as a complementary source. One of the reasons for the Kalman Filter's inaccuracy lies in naive radio coverage approximation techniques based on multivariate normal distributions assumed by previous studies. Therefore, in this paper, we evaluated those disadvantages and proposed a Gaussian mixtures model to address the non-arbitrary shape of the radio cells' coverage area. Having incorporated the Gaussian mixtures model into Switching Kalman Filter, we achieved better accuracy in positioning within the cellular network.

Tracing recent outdoor geolocation by analyzing microbiota from shoe soles and shoeprints even after indoor walking.

The microbial communities on shoe soles and shoeprints could carry microbial information about where someone walked. This is possible evidence to link a suspect in a crime case to a geographic location. A previous study had shown that the microbiota found on shoe soles depend on the microbiota of the soil on which people walk. However, there is a turnover of microbial communities on shoe soles during walking. The impact of microbial community turnover on tracing recent geolocation from shoe soles has not been adequately studied. In addition, it is still unclear whether the microbiota of shoeprints can be used to determine recent geolocation. In this preliminary study, we investigated whether the microbial characteristics of shoe soles and shoeprints can be used to trace geolocation and whether this information can be destroyed by walking on indoor floors. In this study, participants were asked to walk outdoors on exposed soil, then walk indoors on a hard wood floor. High-throughput sequencing of the 16S rRNA gene was performed to characterize the microbial communities of shoe soles, shoeprints, indoor dust, and outdoor soil. Samples of shoe soles and shoeprints were collected at steps 5, 20, and 50 while walking indoors. The PCoA result showed that the samples were clustered by geographic origin. The shoeprint showed a more rapid turnover of microbial community than the shoe sole during indoor walking. The result of FEAST showed that the microbial communities of shoe sole and shoeprint were mainly (shoe sole, 86.21∼92.34 %; shoeprint, 61.66∼90.41 %) from the soil of the outdoor ground where the individual recently walked, and a small portion (shoe sole, 0.68∼3.33 %; shoeprint, 1.43∼27.14 %) from the indoor dust. Based on the matching of microbial communities between geolocation and shoe sole or shoeprint, we were able to infer the recent geolocation of the individual with relatively high accuracy using the random forest prediction model (shoe sole: 100.00 %, shoeprint: 93.33∼100.00 %). Overall, we are able to accurately infer the geolocation of an individual's most recent outdoor walk based on the microbiota of shoe sole and shoeprint, even though these microbiotas show a turnover when walking indoor floor. The pilot study was expected to provide a potential method for tracing recent geolocation of suspects.

Geolocation Patterns, Wi-Fi Connectivity Rates, and Psychiatric Symptoms Among Urban Homeless Youth: Mixed Methods Study Using Self-report and Smartphone Data.

BACKGROUND: Despite significant research done on youth experiencing homelessness, few studies have examined movement patterns and digital habits in this population. Examining these digital behaviors may provide useful data to design new digital health intervention models for youth experiencing homelessness. Specifically, passive data collection (data collected without extra steps for a user) may provide insights into lived experience and user needs without putting an additional burden on youth experiencing homelessness to inform digital health intervention design. OBJECTIVE: The objective of this study was to explore patterns of mobile phone Wi-Fi usage and GPS location movement among youth experiencing homelessness. Additionally, we further examined the relationship between usage and location as correlated with depression and posttraumatic stress disorder (PTSD) symptoms. METHODS: A total of 35 adolescent and young adult participants were recruited from the general community of youth experiencing homelessness for a mobile intervention study that included installing a sensor data acquisition app (Purple Robot) for up to 6 months. Of these participants, 19 had sufficient passive data to conduct analyses. At baseline, participants completed self-reported measures for depression (Patient Health Questionnaire-9 [PHQ-9]) and PTSD (PTSD Checklist for DSM-5 [PCL-5]). Behavioral features were developed and extracted from phone location and usage data. RESULTS: Almost all participants (18/19, 95%) used private networks for most of their noncellular connectivity. Greater Wi-Fi usage was associated with a higher PCL-5 score (P=.006). Greater location entropy, representing the amount of variability in time spent across identified clusters, was also associated with higher severity in both PCL-5 (P=.007) and PHQ-9 (P=.045) scores. CONCLUSIONS: Location and Wi-Fi usage both demonstrated associations with PTSD symptoms, while only location was associated with depression symptom severity. While further research needs to be conducted to establish the consistency of these findings, they suggest that the digital patterns of youth experiencing homelessness offer insights that could be used to tailor digital interventions.

Tracking Changes in Mobility Before and After the First SARS-CoV-2 Vaccination Using Global Positioning System Data in England and Wales (Virus Watch): Prospective Observational Community Cohort Study.

BACKGROUND: Evidence suggests that individuals may change adherence to public health policies aimed at reducing the contact, transmission, and spread of the SARS-CoV-2 virus after they receive their first SARS-CoV-2 vaccination when they are not fully vaccinated. OBJECTIVE: We aimed to estimate changes in median daily travel distance of our cohort from their registered addresses before and after receiving a SARS-CoV-2 vaccine. METHODS: Participants were recruited into Virus Watch starting in June 2020. Weekly surveys were sent out to participants, and vaccination status was collected from January 2021 onward. Between September 2020 and February 2021, we invited 13,120 adult Virus Watch participants to contribute toward our tracker subcohort, which uses the GPS via a smartphone app to collect data on movement. We used segmented linear regression to estimate the median daily travel distance before and after the first self-reported SARS-CoV-2 vaccine dose. RESULTS: We analyzed the daily travel distance of 249 vaccinated adults. From 157 days prior to vaccination until the day before vaccination, the median daily travel distance was 9.05 (IQR 8.06-10.09) km. From the day of vaccination to 105 days after vaccination, the median daily travel distance was 10.08 (IQR 8.60-12.42) km. From 157 days prior to vaccination until the vaccination date, there was a daily median decrease in mobility of 40.09 m (95% CI -50.08 to -31.10; P<.001). After vaccination, there was a median daily increase in movement of 60.60 m (95% CI 20.90-100; P<.001). Restricting the analysis to the third national lockdown (January 4, 2021, to April 5, 2021), we found a median daily movement increase of 18.30 m (95% CI -19.20 to 55.80; P=.57) in the 30 days prior to vaccination and a median daily movement increase of 9.36 m (95% CI 38.6-149.00; P=.69) in the 30 days after vaccination. CONCLUSIONS: Our study demonstrates the feasibility of collecting high-volume geolocation data as part of research projects and the utility of these data for understanding public health issues. Our various analyses produced results that ranged from no change in movement after vaccination (during the third national lock down) to an increase in movement after vaccination (considering all periods, up to 105 days after vaccination), suggesting that, among Virus Watch participants, any changes in movement distances after vaccination are small. Our findings may be attributable to public health measures in place at the time such as movement restrictions and home working that applied to the Virus Watch cohort participants during the study period.

A Real-Time Registration Algorithm of UAV Aerial Images Based on Feature Matching.

This study aimed to achieve the accurate and real-time geographic positioning of UAV aerial image targets. We verified a method of registering UAV camera images on a map (with the geographic location) through feature matching. The UAV is usually in rapid motion and involves changes in the camera head, and the map is high-resolution and has sparse features. These reasons make it difficult for the current feature-matching algorithm to accurately register the two (camera image and map) in real time, meaning that there will be a large number of mismatches. To solve this problem, we used the SuperGlue algorithm, which has a better performance, to match the features. The layer and block strategy, combined with the prior data of the UAV, was introduced to improve the accuracy and speed of feature matching, and the matching information obtained between frames was introduced to solve the problem of uneven registration. Here, we propose the concept of updating map features with UAV image features to enhance the robustness and applicability of UAV aerial image and map registration. After numerous experiments, it was proved that the proposed method is feasible and can adapt to the changes in the camera head, environment, etc. The UAV aerial image is stably and accurately registered on the map, and the frame rate reaches 12 frames per second, which provides a basis for the geo-positioning of UAV aerial image targets.