Individual Mobility Research Articles

Ancient Plasmodium genomes shed light on the history of human malaria

Malaria-causing protozoa of the genus Plasmodium have exerted one of the strongest selective pressures on the human genome, and resistance alleles provide biomolecular footprints that outline the historical reach of these species1. Nevertheless, debate persists over when and how malaria parasites emerged as human pathogens and spread around the globe1,2. To address these questions, we generated high-coverage ancient mitochondrial and nuclear genome-wide data from P. falciparum, P. vivax and P. malariae from 16 countries spanning around 5,500 years of human history. We identified P. vivax and P. falciparum across geographically disparate regions of Eurasia from as early as the fourth and first millennia bce, respectively; for P. vivax, this evidence pre-dates textual references by several millennia3. Genomic analysis supports distinct disease histories for P. falciparum and P. vivax in the Americas: similarities between now-eliminated European and peri-contact South American strains indicate that European colonizers were the source of American P. vivax, whereas the trans-Atlantic slave trade probably introduced P. falciparum into the Americas. Our data underscore the role of cross-cultural contacts in the dissemination of malaria, laying the biomolecular foundation for future palaeo-epidemiological research into the impact of Plasmodium parasites on human history. Finally, our unexpected discovery of P. falciparum in the high-altitude Himalayas provides a rare case study in which individual mobility can be inferred from infection status, adding to our knowledge of cross-cultural connectivity in the region nearly three millennia ago.

The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social Media.

Understanding human movement patterns is crucial for comprehending how a city functions. It is also important for city planners and policymakers to create more efficient plans and policies for urban areas. Traditionally, human movement patterns were analyzed using origin-destination surveys, travel diaries, and other methods. Now, these patterns can be identified from various geospatial big data sources, such as mobile phone data, floating car data, and location-based social media (LBSM) data. These extensive datasets primarily identify individual or collective human movement patterns. However, the impact of spatial scale on the analysis of human movement patterns from these large geospatial data sources has not been sufficiently studied. Changes in spatial scale can significantly affect the results when calculating human movement patterns from these data. In this study, we utilized Weibo datasets for three different cities in China including Beijing, Guangzhou, and Shanghai. We aimed to identify the effect of different spatial scales on individual human movement patterns as calculated from LBSM data. For our analysis, we employed two indicators as follows: an external activity space indicator, the radius of gyration (ROG), and an internal activity space indicator, entropy. These indicators were chosen based on previous studies demonstrating their efficiency in analyzing sparse datasets like LBSM data. Additionally, we used two different ranges of spatial scales-10-100 m and 100-3000 m-to illustrate changes in individual activity space at both fine and coarse spatial scales. Our results indicate that although the ROG values show an overall increasing trend and the entropy values show an overall decreasing trend with the increase in spatial scale size, different local factors influence the ROG and entropy values at both finer and coarser scales. These findings will help to comprehend the dynamics of human movement across different scales. Such insights are invaluable for enhancing overall urban mobility and optimizing transportation systems.

Leveraging Ecological Momentary Assessment Data to Characterize Individual Mobility: Exploratory Pilot Study in Rural Uganda.

The geographical environments within which individuals conduct their daily activities may influence health behaviors, yet little is known about individual-level geographic mobility and specific, linked behaviors in rural low- and middle-income settings. Nested in a 3-month ecological momentary assessment intervention pilot trial, this study aims to leverage mobile health app user GPS data to examine activity space through individual spatial mobility and locations of reported health behaviors in relation to their homes. Pilot trial participants were recruited from the Rakai Community Cohort Study-an ongoing population-based cohort study in rural south-central Uganda. Participants used a smartphone app that logged their GPS coordinates every 1-2 hours for approximately 90 days. They also reported specific health behaviors (alcohol use, cigarette smoking, and having condomless sex with a non-long-term partner) via the app that were both location and time stamped. In this substudy, we characterized participant mobility using 3 measures: average distance (kilometers) traveled per week, number of unique locations visited (deduplicated points within 25 m of one another), and the percentage of GPS points recorded away from home. The latter measure was calculated using home buffer regions of 100 m, 400 m, and 800 m. We also evaluated the number of unique locations visited for each specific health behavior, and whether those locations were within or outside the home buffer regions. Sociodemographic information, mobility measures, and locations of health behaviors were summarized across the sample using descriptive statistics. Of the 46 participants with complete GPS data, 24 (52%) participants were men, 30 (65%) participants were younger than 35 years, and 33 (72%) participants were in the top 2 socioeconomic status quartiles. On median, participants traveled 303 (IQR 152-585) km per week. Over the study period, participants on median recorded 1292 (IQR 963-2137) GPS points-76% (IQR 58%-86%) of which were outside their 400-m home buffer regions. Of the participants reporting drinking alcohol, cigarette smoking, and engaging in condomless sex, respectively, 19 (83%), 8 (89%), and 12 (86%) reported that behavior at least once outside their 400-m home neighborhood and across a median of 3.0 (IQR 1.5-5.5), 3.0 (IQR 1.0-3.0), and 3.5 (IQR 1.0-7.0) unique locations, respectively. Among residents in rural Uganda, an ecological momentary assessment app successfully captured high mobility and health-related behaviors across multiple locations. Our findings suggest that future mobile health interventions in similar settings can benefit from integrating spatial data collection using the GPS technology in mobile phones. Leveraging such individual-level GPS data can inform place-based strategies within these interventions for promoting healthy behavior change.

A Sociological Case Study Based on Cultural Capital and Intergenerational Social Mobility

Cultural capital and intergenerational social mobility are important concepts in the field of sociology, which have significant implications for studying various sociological events and common phenomena in society. This article uses these two important concepts to study and analyze the actual case of news protagonist Percy, who hopes to work as a chef in the future but is obstructed by his family. Through case analysis, this article explores the cultural capital involved in this case and how it specifically affects the upward social mobility of individuals or families, and provides some sociological perspectives to analyze specific cases.

Evidence for dynastic succession among early Celtic elites in Central Europe

The early Iron Age (800 to 450 BCE) in France, Germany and Switzerland, known as the ‘West-Hallstattkreis’, stands out as featuring the earliest evidence for supra-regional organization north of the Alps. Often referred to as ‘early Celtic’, suggesting tentative connections to later cultural phenomena, its societal and population structure remain enigmatic. Here we present genomic and isotope data from 31 individuals from this context in southern Germany, dating between 616 and 200 BCE. We identify multiple biologically related groups spanning three elite burials as far as 100 km apart, supported by trans-regional individual mobility inferred from isotope data. These include a close biological relationship between two of the richest burial mounds of the Hallstatt culture. Bayesian modelling points to an avuncular relationship between the two individuals, which may suggest a practice of matrilineal dynastic succession in early Celtic elites. We show that their ancestry is shared on a broad geographic scale from Iberia throughout Central-Eastern Europe, undergoing a decline after the late Iron Age (450 BCE to ~50 CE).

Gait analysis and geriatric syndromes: An association among elderly patients attending a teaching hospital of Delhi

ABSTRACT Background: Gait abnormalities are prevalent, affecting a substantial portion of the elderly population, and leading to mobility limitations, reduced quality of life, falls, hospitalizations, and premature death. Objectives: The study aims to assess gait patterns among individuals aged 75 years and above attending the geriatric OPD of a tertiary care hospital in New Delhi and evaluate their association with various geriatric syndromes. Materials and Methods: This cross-sectional study, conducted at a tertiary care hospital in Delhi, from May 2019 to November 2021, involved 100 participants aged 75 and above. It encompassed a thorough assessment protocol covering demographics, health history, clinical and functional evaluations, depression, cognition, balance, frailty, urinary incontinence, polypharmacy, nutrition, comorbidities, and gait analysis. Results: In this study of elderly individuals, the mean age was 78.56 years, and the mean BMI was 23.11. The participants had an average of 1.74 comorbidities, with hypertension being the most prevalent (62%), followed by diabetes (25%), chronic obstructive airway disease (COAD) (11%), and coronary artery disease (15%). Geriatric assessments revealed varying proportions of frailty (34%), polypharmacy (40%), and urinary incontinence (9%). The mean scores for activities of daily living, instrumental activities of daily living, nutritional status, cognitive function, Timed Up and Go Test, and depression scale were also reported. Various gait parameters demonstrated significant correlations with these geriatric factors, including frailty, comorbidities, BMI, and mobility scores. Conclusion: The study identified significant associations between gait patterns and various geriatric syndromes, emphasizing the importance of gait analysis in assessing the health and mobility of elderly individuals.

Comparison of Yoga with exercise in ankylosing spondylitis on mobility and functional capacity.

To compare the effects of Yoga with traditional exercise on the mobility and functional capacity of individuals with ankylosing spondylitis (AS). The participants of the study were recruited at the rheumatology department, adhering to the study's inclusion and exclusion criteria. Participants were randomized into two groups (Group A - Yoga, and Group B - exercise).The candidates participated in an 8-week intervention consisting of 3 weekly sessions of either Yoga or Exercise intervention. Outcomes were collected at pre-treatment, at 8 weeks, and at 12 weeks. The within-group comparison showed an improvement in all outcome measures with p < .05 between post-treatment and the follow-up. In the yoga group, there was an improvement in the measures of BASMI (p = .001), BASFI (p = .005), PSQI (p = .021), CE (p = .053) and NPRS (p = .001). Similarly, in the exercise group, there was an improvement in BASMI (p = .002), BASFI (p = .003), PSQI (p = .010), CE (p = .004) and NPRS (p = .001). In the between group comparison at post-treatment, there were no statistically significant differences in BASMI (yoga = 3.0 ± 1.50, exercise = 2.3 ± 1.38), PSQI (yoga = 5.3 ± 1.50, exercise = 4.9 ± 1.17) and NPRS (yoga = 1.3 ± 2.22, exercise = 0.4 ± 0.50) CE (yoga = 4.0 ± 1.18, exercise = 3.4 ± 0.96), BASFI (yoga = 1.8 ± 2.14, exercise = 2.1 ± 1.87). The results demonstrated a statistically significant improvement in within-group scores of mobility, functional capacity, sleep quality and pain in AS patients of both intervention programs but there were no significant differences between the groups.

Method for monitoring and forecasting landslide phenomenon based on machine learning

A landslide involves the downward movement of a mass of rock, debris, earth, or soil. Landslides happen when gravitational forces and other types of shear stresses on a slope surpass the shear strength of the materials. Additionally, landslides can be triggered by processes that weaken the shear strength of the slope's material. Shear strength primarily depends on two factors such as frictional strength, which is the resistance to movement between the interacting particles of the slope material, and cohesive strength, which is the bonding between those particles. A landslide is a terrible natural disaster that causes much damage to both human life and the economy. It often occurs in steep mountainous areas or hilly regions, ranging in scale from medium to large. It progresses slowly (20–50 mm/year), but when it occurs, it can move at a speed of 3 m/s. Therefore, early detection or prevention of this disaster is an essential and significant task. This paper developed a method to collect and analyze data, with the purpose of determining the possibility of landslide occurrences to reduce its potential losses.•The proposed method is convenient for users to grasp information of landslide phenomenon.•A machine learning model is applied to forecast landslide phenomenon.•Internet of things (IoT) system is utilized to manage and send a warning text to individual email address and mobile devices.

Social inequality and the changing patterns of travel in the pandemic and post-pandemic era

The COVID-19 pandemic has had an unprecedented impact on mobility patterns resulting in a significant literature investigating travel behaviours over the course of the pandemic. Missing from much existing work on pandemic mobility is an explicit handling of the time-of-day of travel, which in previous literature has been shown to be an important factor in understanding mobility and, importantly, in understanding the impact on transport networks. In this article, we present a novel analysis of anonymised individual daily mobility patterns in the UK over a 30-month period covering the COVID-19 pandemic using privacy-preserving mobile phone GPS data, collected via integration of software development kits (SDKs) into mobile apps. Our analysis is based on time series clustering of mobility profiles at an hourly level of resolution and enables us to characterize five distinct daily mobility patterns. This typology appears remarkably robust over time, albeit with varying levels of each pattern during the course of the study period. We analyse the relative frequency of these patterns in relation to two dimensions of neighbourhood deprivation in England, with a particular focus on understanding mobility post-lockdown and for over a year after the final restrictions were lifted in the UK. Our results show that although overall mobility patterns have largely returned to their pre-pandemic levels, there remain persistent inequalities in relation to ‘traditional commute’, ‘highly mobile’ and ‘out in the evening’ activity patterns. This finding is expected to have important ongoing policy implications.

Sabine-Florence Fabijanec, Zrinka Novak, and Zoran Ladić, eds. Social and Individual Spatial Mobility in Late Medieval and Renaissance Croatia in European Context

Sabine-Florence Fabijanec, Zrinka Novak, and Zoran Ladić, eds. <i>Social and Individual Spatial Mobility in Late Medieval and Renaissance Croatia in European Context</i>

Analytical and Experimental Research for Development of the Airless Tires for Urban Micromobility Means

It is currently recognized that electric vehicles are the optimal type of passenger transport for urban usage. However, there are very few people willing to buy them, since today electric cars are very expensive. So the development of the personal light electric transport segment (electric bicycles, scooters, motorcycles, etc.) becomes very relevant. At the same time, the introduction of new technologies (in particular, 3D printing) and constructions (airless wheels) for their mass production is of particular importance. The range of problems that can be solved by modern additive technologies is expanding every day. FDM technology is one of the most commonly used additive methods. It is not only widely available, but it also provides significant possibilities for decision-making. However, most developments in this area are focused on obtaining the geometric accuracy of shapes without taking into account the mechanical properties of materials used. Therefore, the purpose of this study is to investigate experimentally the influence of filling density of parts manufactured by 3D printing on their mechanical properties and application of obtained results for the production of airless tires by using FDM technology.

Exploring the impacts of individual residential mobility, housing, and social disorganization on recidivism among parolees

The impact of housing and individual residential mobility on recidivism is nuanced. Individuals may move from prosocial environments to criminogenic environments, or from neighborhoods that are more, or less, socioeconomically disadvantaged. We explore these phenomena using data on individuals on parole in the District of Columbia with community-level Census data. We hypothesize that residential mobility will affect recidivism through changes in both housing types and neighborhood characteristics. Findings suggest that people immediately placed into treatment-oriented or transitional housing had lower rates of rearrest than those in other housing situations. Results of the community-level measures of social disorganization were mixed.

Age-related changes in reticulospinal contributions to anticipatory postural adjustments between back extensors and abdominal muscles.

Anticipatory postural adjustments (APAs) give feedforward postural control of the trunk, but they are delayed with ageing, affecting balance and mobility in older individuals. The reticulospinal tract contributes to postural control of the trunk; however, the extent to which age-related changes affect the reticulospinal contributions to APAs of the trunk remains unknown in humans. Here, we tested the hypothesis that a startling acoustic sound, which activates the reticulospinal tract, improves delayed APAs in older individuals. Twenty-two old (75±6years) and 20 healthy young adults (21±4years) performed a self-initiated fast bilateral shoulder flexion or shoulder extension task in response to visual, visual and auditory (80dB), or visual and startling (115dB) cues. Electromyography (EMG) was recorded from bilateral anterior deltoid (AD) and erector spinae (ES) during shoulder flexion and from bilateral posterior deltoid (PD) and rectus abdominis (RA) during shoulder extension. EMG onset of all muscles shortened during the startling cue in both age groups, suggesting a non-specific modulation of the reticulospinal tract on prime movers (AD or PD) and non-prime movers (ES or RA). Interestingly, APAs of the ES were accelerated in older participants to a similar degree as in younger participants during the startling cue. Conversely, APAs of the RA were not influenced by the startling cue in older participants. Our results suggest differential effects of ageing on functional contributions of the reticulospinal tract to APAs between back extensors and abdominal muscles.

Towards environment perception for walking-aid robots: an improved staircase shape feature extraction method

This paper introduces an innovative staircase shape feature extraction method for walking-aid robots to enhance environmental perception and navigation. We present a robust method for accurate feature extraction of staircases under various conditions, including restricted viewpoints and dynamic movement. Utilizing depth camera-mounted robots, we transform three-dimensional (3D) environmental point cloud into two-dimensional (2D) representations, focusing on identifying both convex and concave corners. Our approach integrates the Random Sample Consensus algorithm with K-Nearest Neighbors (KNN)-augmented Iterative Closest Point (ICP) for efficient point cloud registration. The results show an improvement in trajectory accuracy, with errors within the centimeter range. This work overcomes the limitations of previous approaches and is of great significance for improving the navigation and safety of walking assistive robots, providing new possibilities for enhancing the autonomy and mobility of individuals with physical disabilities.

Static and dynamic stiffness optimization on the body structure of an electric quadricycle

Reducing vehicle vibrations is of particular importance due to the adverse effect of vibrations on the ride comfort of passengers. Electric quadricycles are growing rapidly because they are quieter and less polluting than fossil-fuelled vehicles, and these reasons make them a green alternative to personal transportation, and their popularity increases day by day. In this article, the optimization of the body structure of EQ10, an electric quadricycle under development, is discussed to reduce the weight and vibrations transmitted to the passengers with the constraints of bending stiffness and torsional stiffness and yield stress of the elements. The vibrations transmitted to the occupants are measured beneath the driver’s seat by reading the acceleration resulting from the EQ10 excitation sources vibrations. First, a finite element model of the body structure was designed. Then, for optimization, the EQ10 body structure is divided into 29 modules, and in the optimization process, the thickness of these 29 modules is considered as a design variable. The BIGOPT gradient-based method was chosen to solve the optimization problem due to its superior performance to other numerical solution algorithms. To calculate static and dynamic stiffness, modal analyses, and frequency transfer function are conducted to evaluate its general behavior under various functional conditions. Following optimization, results show that the bending and torsional stiffness increased by 45% and 31%, respectively; such fascinating results could not have been obtained without the methods employed in this investigation.

Residential mobility and suicide in Belgium

Using Belgian administrative datasets (National Register, Census, and death certificates) on individuals aged 20–64 (N=7,246,740 individuals and 4,109 suicides), the study examined the association between mobility and suicide in the context of union transitions and different life stages. Using Cox proportional hazard models, we found that, in general, moving was associated with an increased risk of suicide than immobility, except for moves in the context of union transitions. Additionally, results highlighted that union dissolutions were associated with a higher risk of suicide – regardless of residential mobility. Moreover, mobility (compared to immobility) for individuals who were in stable situations (single or partnered) or who were in their mid-adulthood was associated with higher risks of suicide. Finally, middle-aged adults (aged 40–54) presented higher suicide risks in all cases of residential mobility, including if accompanied by union transitions.

Sistem Keamanan Kendaraan Jarak Jauh Menggunakan GPS Berbasis NODEMCU ESP8266

The use of motorcycles as a means of personal transportation is a practical and easy-to-use transportation option in various crowded road conditions. In general, vehicle security systems are still very weak, and additional security systems are needed to prevent theft, especially in older vehicles. To increase security on motorbikes, researchers developed a security system that can monitor the location of motorbikes that can be monitored and controlled via an Android application. In making this prototype, the NodeMCU ESP8266 microcontroller as the Internet of Things (IoT), Ublox Neo-6M GPS module, and relays to control motorcycle electricity. The GPS module is used to determine the location based on the latitude and longitude of the motorcycle directly and will be sent to the server and then displayed through the Android application. In addition to displaying location coordinates, this application can also control motorcycle electricity with NodeMCU ESP8266 to activate relays connected to motorcycle electricity to function as turning on or off the motorcycle engine and there is a location history menu obtained from the GPS module.

Firewood transport and invasive insect spread in Michigan

Transportation of firewood can be a vector for invasive insect spread resulting in damage to surrounding areas. In 2016 and 2021, surveys were conducted at campgrounds around Michigan to understand where campers were sourcing their firewood, awareness of the ‘Do not move firewood’ campaign, knowledge of invasive insects and pests, reactions to a potential ban on bringing firewood to campgrounds, and perspective on kiln-dried firewood – all potential policy levers to reduce the spread of invasive insects. Results indicated that campaign awareness slightly decreased between the survey years, personal firewood transport has decreased, and knowledge of invasives remains low. There is an opportunity for intensifying invasive species and firewood outreach efforts, however, regulation (and enforcement) may be more effective among those who would not comply or support a ban.

SOLAR BASED WHEEL CHAIR FOR DISABLED

The Solar Based Wheelchair for Disabled (SBWCD) is a groundbreaking project aimed at enhancing mobility and independence for individuals with disabilities by harnessing the power of solar energy. Traditional wheelchairs often rely on manual propulsion or battery-powered motors, which can be limiting in terms of range, accessibility to charging stations, and environmental impact. In response to these challenges, the SBWCD project introduces a novel approach by integrating solar panels into the design of wheelchairs to harness solar energy and convert it into electrical power for propulsion. This innovative solution offers numerous benefits, including extended range, reduced reliance on grid electricity, and decreased carbon footprint. The SBWCD features a lightweight and durable frame equipped with high-efficiency solar panels mounted on the backrest and armrests, maximizing exposure to sunlight while maintaining user comfort and ergonomics. The solar panels are connected to an onboard battery system, which stores excess energy generated during daylight hours for use during periods of low sunlight or at night. This hybrid power system ensures continuous operation of the wheelchair regardless of environmental conditions, providing users with greater autonomy and freedom of movement. Moreover, the SBWCD is designed with user-centric features and accessibility in mind. Adjustable seating, armrests, and footrests accommodate users of varying sizes and preferences, while ergonomic controls and intuitive interfaces ensure ease of operation for individuals with limited mobility or dexterity. Additionally, safety features such as anti-tip mechanisms, seat belts, and obstacle detection systems enhance user confidence and mitigate risks associated with wheelchair use in diverse environments. In summary, the Solar Based Wheelchair for Disabled (SBWCD) project represents a significant advancement in assistive technology, offering a sustainable and user-friendly solution for individuals with disabilities. By harnessing the abundant and renewable energy of the sun, SBWCD empowers users to navigate their surroundings with greater independence, efficiency, and environmental consciousness. As the demand for accessible and eco-friendly mobility solutions continues to grow, the SBWCD project serves as a beacon of innovation and inclusivity in the field of assistive technology.

The Application of Plural Panelist Synthesis Method in Identifying Determinant Factors That Influence Economic Growth

This research aims to study intra-generational income mobility and poverty, and it also seeks to characterize and measure individual mobility by analyzing the duration of poverty, consecutive versus transient poverty, and the likelihood of re-entry. Researchers used a synthetic panel approach to estimate individual income in the second round based on data from the first round. This approach allows research to look at changes in individual income over time, even though actual panel data is unavailable. Based on research results, it show that the main factor influencing stagnation is the difficulty of leaving poverty, not the problem of entering poverty. In addition, analyses that consider the entire period also provide different results regarding the level of permanence in poverty. Synthetic panel analysis shows that the individuals who move out of poverty are those who were poor at the start of each period studied, not those who already had incomes above the poverty line. In addition, these results also show that the proportion of individuals who experience poverty in a shorter period is greater than that of those who experience poverty for four years. The analysis shows changes in poverty dynamics between the two periods studied. Successive poverty dominates, meaning that individuals who fall into poverty tend to remain poor over that period. However, the predominance is shifting towards transient poverty, where individuals experience poverty for shorter periods, moving in and out of poverty within that period.