Mobility Analysis Research Articles

Gait planning of a 4–5R rolling mechanism based on the planar 6R single-loop chain

Abstract. This paper proposes a 4–5R rolling mechanism based on the spatial extension design of a planar 6R single-loop chain. By analyzing the locomotion of the planar equivalent form, a modular gait theory integrating different modes of gait with high efficiency, low energy consumption, and high speed is established. A unified kinematic strategy expression, encapsulated in the form of the gait period table, is tailored for the kinematic chain's gait on the flat terrain. A contrast gait is conducted to ascertain its velocity parameters and volatility of the center of mass (CM). By optimizing the corresponding indicators, two distinct gait patterns are achieved: a faster speed gait that prioritizes increased speed and a steady gait that emphasizes stability with reduced CM volatility. Drawing from the mobility analysis and simulation outcomes of the planar 6R single-loop kinematic chain, a theory of locomotion for a closed-chain linkage mechanism in space is proposed. A locomotion strategy on the flat ground is derived, and a unified evaluation index is proposed. Finally, the feasibility of the two working modes is verified using a physical prototype. The theoretical work in this paper simplifies the design process of closed-chain linkage robots and improves the mobility performance of closed-chain linkage robots. It lays the foundation for researching new types of closed-chain linkage robots.

Simulating Impacts from Transit Service Enhancements in the San Francisco Bay Area

Preemptively assessing the potential impacts of large transportation projects is an essential step in achieving better outcomes. However, for transformative public transit projects, it can be difficult to weigh the many complicated downstream impacts on individual travelers in a coherent, cost-effective, and comprehensive way. This research focuses on leveraging the Behavior, Energy, Autonomy & Mobility Comprehensive Regional Evaluator (BEAM CORE) to gauge regional responses to changes in existing and planned public transit services, capturing service performance, system impacts, and users’ responses. We applied BEAM CORE to a case study in the San Francisco Bay Area to simulate the effects of recent and upcoming transit projects, showcasing its potential for transportation planning. By simulating individual traveler movements, it becomes possible to delve deeply into the equity and accessibility ramifications of transit system enhancements. The analysis of ridership, mobility, accessibility, and equity presented for this study highlights the benefits of this method in providing a clear understanding of the performances of public transit projects, facilitating more informed and efficient decision-making for transport stakeholders. The results obtained from BEAM CORE aligned closely with expectations and observed data, demonstrating its effectiveness and reliability. Finally, because of the BEAM CORE model’s responsiveness to changes in the systems, the method can in the future be applied not only to test existing or planned interventions but to a large variety of hypothetical scenarios to identify the optimal solution, including other transport modes.

What determines travel time and distance decay in spatial interaction and accessibility?

The concept of ‘distance decay’ curves is used in spatial interaction and accessibility analysis to represent the diminishing likelihood of visiting places with increasing travel impedance, mainly distance and travel time. The shape of the resulting impedance decay curves varies by several factors, but these influential factors are often dismissed in favor of just travel mode. In this study, we examine which factors should be used to distinguish impedance functions for use. Using data from a large national travel survey, we first show that the impedance curves are well approximated by functions of the exponential family and the related Tanner function. We use two methods – variable-wise function fit and Shapley additive explanations – to conclude the importance of four factors for developing impedance functions. These are travel mode, trip purpose, urbanity class of trip origin and destination, and the socioeconomic status grouping of the travelers. We then show that the use of a generalized impedance function can significantly over- or underestimate spatial accessibility compared to factor-specific impedance function, with up to 80 % overestimation on average in the case of public transit and 16 % overestimation for low socio-economic status travelers. These findings highlight the importance of the choice of impedance function which has applications in spatial economics, transportation planning, and human mobility analyses.

Design principles for accurate folding of DNA origami

We describe design principles for accurate folding of three-dimensional DNA origami. To evaluate design rules, we reduced the problem of DNA strand routing to the known problem of shortest-path finding in a weighted graph. To score candidate DNA strand routes we used a thermodynamic model that accounts for enthalpic and entropic contributions of initial binding, hybridization, and DNA loop closure. We encoded and analyzed new and previously reported design heuristics. Using design principles emerging from this analysis, we redesigned and fabricated multiple shapes and compared their folding accuracy using electrophoretic mobility analysis and electron microscopy imaging. Redesigned shapes showed 6- to 30-fold improvements in yield compared to original designs. We demonstrate accurate folding can be achieved by optimizing staple routes using our model and provide a computational framework for applying our methodology to any design.

Comparing GPS and cell-based mobile phone data to identify activity participation during the COVID-19 pandemic

This study conducts a detailed analysis of population mobility during the COVID-19 pandemic, utilizing a unique approach that contrasts two types of mobile phone data: GPS-based and cell-based. The primary objective is to evaluate the effects of governmental restrictions on a variety of activities including school attendance, work, shopping, and leisure. We compare both data sets by using a set of defined criteria, including anticipated activity reductions during full and partial closures, as well as the timing of activity changes in response to policy implementations. Our research reveals that while cell-based data lacks the precision to differentiate between various out-of-home activities effectively, GPS-based data, especially when integrated with OpenStreetMap, proves significantly more adept at identifying and categorizing specific activity types. The GPS-based data shows, for example, that school activities fell by more than 80% while work activities were only reduced by around 50%.

Cross-Interactions of Aβ Peptides Implicated in Alzheimer's Disease Shape Amyloid Oligomer Structures and Aggregation.

A defining hallmark of Alzheimer's disease (AD) is the synaptic aggregation of the amyloid β (Aβ) peptide. In vivo, Aβ production results in a diverse mixture of variants, of which Aβ40, Aβ42, and Aβ43 are profusely present in the AD brain, and their relative abundance is recognized to play a role in disease onset and progression. Nonetheless, the occurrence of Aβ40, Aβ42, and Aβ43 hetero-oligomerization and the subsequent effects on Aβ aggregation remain elusive and were investigated here. Using thioflavin-T (ThT)-monitored aggregation assays and native mass spectrometry coupled to ion mobility analysis (IM-MS), we first show that all Aβ peptides are aggregation-competent and self-assemble into homo-oligomers with distinct conformational populations, which are more pronounced between Aβ40 than the longer variants. ThT assays were then conducted on binary mixtures of Aβ variants, revealing that Aβ42 and Aβ43 aggregate independently from Aβ40 but significantly speed up Aβ40 fibrillation. Aβ42 and Aβ43 were observed to aggregate concurrently and mutually accelerate fibril formation, which likely involves hetero-oligomerization. Accordingly, native MS analysis revealed pairwise oligomerization between all variants, with the formation of heterodimers and heterotrimers. Interestingly, IM-MS indicates that hetero-oligomers containing longer Aβ variants are enriched in conformers with lower collision cross-sections when compared to their homo-oligomer counterparts. This suggests that Aβ42 and Aβ43 are capable of remodeling the oligomer structure toward a higher compaction level. Altogether, our findings provide a mechanistic description for the hetero-oligomerization of Aβ variants implicated in AD, contributing to rationalizing their in vivo proteotoxic interplay.

Parallel–Serial Robotic Manipulators: A Review of Architectures, Applications, and Methods of Design and Analysis

Parallel–serial (hybrid) manipulators represent robotic systems composed of kinematic chains with parallel and serial structures. These manipulators combine the benefits of both parallel and serial mechanisms, such as increased stiffness, high positioning accuracy, and a large workspace. This study discusses the existing architectures and applications of parallel–serial robots and the methods of their design and analysis. The paper reviews around 500 articles and presents over 150 architectures of manipulators used in machining, medicine, and pick-and-place tasks, humanoids and legged systems, haptic devices, simulators, and other applications, covering both lower mobility and kinematically redundant robots. After that, the paper considers how researchers have developed and analyzed these manipulators. In particular, it examines methods of type synthesis, mobility, kinematic, and dynamic analysis, workspace and singularity determination, performance evaluation, optimal design, control, and calibration. The review concludes with a discussion of current trends in the field of parallel–serial manipulators and potential directions for future studies.

Full Forward Kinematics of Lower-Mobility Planar Parallel Continuum Robots

In rigid lower-mobility parallel manipulators the motion of the end-effector is partially constrained due to a combination of passive kinematic pairs and rigid components. Translational mechanisms, such as the Delta manipulator, are the most common ones among this type of mechanisms. When flexible elements are introduced, as in Parallel Continuum Manipulators, the constraint is no longer rigid, and new challenges arise in performing certain motions depending on the degree of compliance. Mobility analysis shifts from being purely a geometric issue to one that heavily relies on force distribution within the mechanism. Simply converting classical lower-mobility rigid parallel mechanisms into Parallel Continuum Mechanisms may yield unexpected outcomes. This work, making use of a planar parallel continuum Delta manipulator, on the one hand, presents two different approaches to solve the Forward Kinematics of planar continuum manipulators, and, on the other hand, explores some challenges and issues in assessing the resultant workspace for different design alternatives of this kind of flexible manipulators.

Determining Validity and Reliability of an In-Field Performance Analysis System for Swimming.

To permit the collection of quantitative data on start, turn and clean swimming performances in any swimming pool, the aims of the present study were to (1) validate a mobile in-field performance analysis system (PAS) against the Kistler starting block equipped with force plates and synchronized to a 2D camera system (KiSwim, Kistler, Winterthur, Switzerland), (2) assess the PAS's interrater reliability and (3) provide percentiles as reference values for elite junior and adult swimmers. Members of the Swiss junior and adult national swimming teams including medalists at Olympic Games, World and European Championships volunteered for the present study (n = 47; age: 17 ± 4 [range: 13-29] years; World Aquatics Points: 747 ± 100 [range: 527-994]). All start and turn trials were video-recorded and analyzed using two methods: PAS and KiSwim. The PAS involves one fixed view camera recording overwater start footage and a sport action camera that is moved underwater along the side of the pool perpendicular to the swimming lane on a 1.55 m long monostand. From a total of 25 parameters determined with the PAS, 16 are also measurable with the KiSwim, of which 7 parameters showed satisfactory validity (r = 0.95-1.00, p < 0.001, %-difference < 1%). Interrater reliability was determined for all 25 parameters of the PAS and reliability was accepted for 21 of those start, turn and swimming parameters (ICC = 0.78-1.00). The percentiles for all valid and reliable parameters provide reference values for assessment of start, turn and swimming performance for junior and adult national team swimmers. The in-field PAS provides a mobile method to assess start, turn and clean swimming performance with high validity and reliability. The analysis template and manual included in the present article aid the practical application of the PAS in research and development projects as well as academic works.

Mobile app review analysis for crowdsourcing of software requirements: a mapping study of automated and semi-automated tools

Mobile app reviews are valuable for gaining user feedback on features, usability, and areas for improvement. Analyzing these reviews manually is difficult due to volume and structure, leading to the need for automated techniques. This mapping study categorizes existing approaches for automated and semi-automated tools by analyzing 180 primary studies. Techniques include topic modeling, collocation finding, association rule-based, aspect-based sentiment analysis, frequency-based, word vector-based, and hybrid approaches. The study compares various tools for analyzing mobile app reviews based on performance, scalability, and user-friendliness. Tools like KEFE, MERIT, DIVER, SAFER, SIRA, T-FEX, RE-BERT, and AOBTM outperformed baseline tools like IDEA and SAFE in identifying emerging issues and extracting relevant information. The study also discusses limitations such as manual intervention, linguistic complexities, scalability issues, and interpretability challenges in incorporating user feedback. Overall, this mapping study outlines the current state of feature extraction from app reviews, suggesting future research and innovation opportunities for extracting software requirements from mobile app reviews, thereby improving mobile app development.

The Distribution of Land in Luxembourg (1766–1872): Family-Level Wealth Persistence in the Midst of Institutional Change

The paper analyzes family-level wealth inequality and social mobility in Dudelange (Luxembourg) over five generations between 1766 and 1872, a period that saw the end of feudal social relations. While the integration of Luxembourg into the French revolutionary regime produced a reduction in the Gini coefficient for the ownership of land, the social mobility analysis reveals a relative stability of family positions within the land-wealth distribution throughout the period. This shows that family-level transmission mechanisms limit social mobility and strongly advantage those with ancestors owning property wealth, even when there are significant changes in the organization of property relations.

Spatiotemporal Evolution of the Yellow Fever Epidemic in Southeast Brazil from 2016 to 2019.

Background: Yellow fever (YF) is a zoonotic disease transmitted by mosquitoes among humans and nonhuman primates. Although urban YF is eradicated, the sylvatic YF has reemerged in some areas of Brazil in the twenty-first century. From 2016 to 2019, a sylvatic YF epidemic occurred in Southeast Brazil, where it had been eradicated in the 1940s. Methods: This study's objective was to describe the epidemic in the states of the Southeast region, based on descriptive, cluster, and mobility analyses. Results: Both the descriptive and cluster analyses showed that the YF cases spread from the state of Minas Gerais southward, causing peaks in cases during the summer months. None of the state capitals was included in the clusters, but the connectivity between the municipalities in Greater Metropolitan São Paulo highlighted potential paths of spread. Despite differences in sociodemographic profiles between the Southeast and North of Brazil (the latter region considered endemic), the epidemiological profile was similar, except for patients' occupation, which was not related to rural work in the Southeast. Conclusion: The results contributed to our understanding of the paths by which YF spread across Southeast Brazil and the epidemiological profile in an area that had gone decades without autochthonous cases.

Characterization of highly conducting Ionic Liquid (EMI-BF4)mEMIn+ nanoclusters injected into dielectrics to produce compound electrosprays.

Electrospraying of dielectric liquids presents unique challenges compared to conducting liquids, as it requires external charge injection. This manuscript further explores the Charge Injection Atomization (CIA) technique, which employs two concentric capillaries to create a compound electrospray. The inner liquid is an ionic liquid (IL), which injects nanodrops and perhaps also ions into the dielectric. The evaporation of the dielectric liberates these charged particles into the gas phase, where they are analyzed with a Differential Mobility Analyzer (DMA). The mobility spectra show very narrow peaks of high mobility (corresponding to ions) and broader, lower mobility peaks representing IL nanodrops. In this work, the effects of both the ionic liquid and dielectric flow rates on droplet diameter and charge are thoroughly studied. Through a simple assumption that the mobility of the droplets agrees with Stokes-Millikan and the condition that the droplets are spherical of known density, the diameter and mass over charge, are determined, revealing average values ranging from 7 to 90 kDa and diameters from 3 to 35 nm. The charge density of the droplets seems to suggest that they are charged to a fraction between 50-100% of the Rayleigh limit and are affected mostly by the ionic liquid flow rate as expected. Given the broad interest of IL, the controlled size production of nanoclusters in dielectrics can have important implications in synthesis and catalysis, polymer chemistry, electrochemistry, microemulsions and biotechnology.

Mapping Rural Mobility in the Global South: Case Studies of Participatory GIS Approach for Assessments of Daily Movement Needs and Practice in Nepal and Kenya

This paper investigates rural mobility in the Global South using a participatory GIS approach to address the lack of mobility data that hampers sustainable planning to support rural development and resilience. Limited rural mobility due to poor infrastructure and financial constraints hinders social and economic activities, impeding development. The study aims to explore the socio-economic impacts of limited mobility, identify software needs for data-scarce environments, and map daily mobility patterns. Fieldwork was conducted in Kenya (2022) and Nepal (2023), collecting geographic data related to mobility. The methodology included community engagement and digital mapping using the QField app for precise data collection. The study highlights the use of participatory GIS to fill data gaps, enabling more accurate mobility assessments. Community engagement revealed gender-specific mobility patterns, with women facing particular challenges in daily activities. The study emphasizes the need for adaptable data models to reflect community-specific mobility needs and the integration of qualitative insights to propose effective and sustainable mobility solutions. This research contributes to understanding rural mobility in the Global South and demonstrates the effectiveness of participatory GIS in overcoming data scarcity and enhancing mobility analysis.

Advanced Analysis of Scalability and Mobility in Cloud Servers using Logistic Regression Models.

With the rapid expansion of cloud computing, efficiently managing scalability and mobility has become paramount. This paper presents an in-depth examination of how logistic regression models can predict and optimize these two critical aspects of cloud infrastructure. By analyzing various cloud configurations, workload patterns, and system performance data, the logistic regression framework forecasts resource needs and identifies potential bottlenecks. The study incorporates real-world applications and case studies to demonstrate the practical benefits of logistic regression in enhancing cloud performance. Additionally, the paper compares logistic regression with other predictive models and explores future advancements in cloud optimization through AI-driven automation and real-time machine learning. The findings underscore the importance of predictive analytics in maintaining seamless cloud operations and provide actionable insights for cloud architects aiming to design more resilient and efficient cloud systems.

Analysis and Comparison of Social Media Applications Using Forensic Software on Mobile Devices

With the integration of mobile systems into daily life, social media applications used especially on Android and iOS platforms contain a significant amount of sensitive information. Social media applications on mobile systems have huge personal and sensitive content. Therefore, it is important to design effective techniques for forensic analysis of social media applications and to detect personal data. In this research, three different paid mobile forensic software and 4 different brands and models of smartphones with different operating systems were used and analyzed. The study shows that private messages, e-mails, time information, shared data, location and time information, and other personal data can be obtained by a forensic expert who performs an examination, and it is seen that one software can access the deleted data, but another software cannot access it. In proportion to the technology used in today’s world, mobile forensics incidents are increasing day by day, and a competitive environment is created among the software used to illuminate these incidents. With this competition, software companies dealing with forensic informatics are trying to obtain different data to illuminate forensic events that may occur due to the active use of social media accounts with the developing technology, and software that does not meet the needs in the face of this situation remains in the background. The criminal elements in the investigation areas of mobile forensics differ daily, and the scope of crimes in the virtual environment is expanding with the developing technology. Therefore, mobile forensic analysis applications should be successful in social media applications other than standard data.

Spatial analysis of population mobility in China in recent years: a study based on Baidu migration big data

Spatial analysis of population mobility in China in recent years: a study based on Baidu migration big data

Water Uptake of Airborne Cells of P. syringae Measured with a Hygroscopicity Tandem Differential Mobility Analyzer.

Airborne microorganisms impact cloud formation and are involved in disease spreading. The ability of airborne cells to survive and express genes may be limited by reduced water availability in the atmosphere and depend on the ability of the cells to attract water vapor at subsaturated conditions, i.e., their hygroscopicity. We assessed hygroscopic properties of the plant pathogen Pseudomonas syringae, known to participate in cloud formation. We used a hygroscopicity tandem differential mobility analyzer to examine both hydration and dehydration behavior in the relative humidity (RH) range 5-90%. The cells were aerosolized either from Milli-Q water or from a 35 g L-1 NaCl solution, resulting in pure cells or cells associated with NaCl. Pure cells exhibited no deliquescence/efflorescence and a small gradual water uptake reaching a maximum growth factor (GF) of 1.09 ± 0.01 at 90% RH. For cells associated with NaCl, we observed deliquescence and a much larger maximum GF of 1.74 ± 0.03 at 90% RH. Deliquescence RH was comparable to that of pure NaCl, highlighting the major role of the salt associated with the cells. It remains to be investigated how the observed hygroscopic properties relate to survival, metabolic, and ice-nucleation activities of airborne P. syringae.

An Efficient Attentive-GRU Structure for Uncertainty Modelling of Crowdsourced Human Trajectories Under Building-obscured Urban Scenes

Abstract. Uncertainty modelling is regarded as one of the core components in the field of human mobility analysis and urban navigation, that can affect the performance of human behaviour modelling and location information acquisition. Existing uncertainty modelling algorithms towards the human movement trajectory are subjected to random and highly dynamic human motion characteristics and sampling and observation errors of Global Navigation Satellite System (GNSS) signals caused by the occlusion of buildings in urban scenes, which lead to the insufficient spatiotemporal correlation and poor accuracy of uncertainty modelling. To fill in this gap, this paper proposes an efficient attentive-GRU structure for uncertainty modelling of crowdsourced human trajectories under building-obscured urban scenes, that takes into account both temporal correlation and spatial correlation of human-originated GNSS trajectories and related motion features. A period of human motion data is modelled instead of only one or adjacent location points to avoid interference factors caused by the obstruction of urban buildings, and time-varying measurement and sampling errors are further estimated and combined with comprehensive human motion features to improve the accuracy of final uncertainty modelling. Comprehensive experiments indicate that compared with existing uncertainty modelling methods including physical models and deep-learning models, the proposed attentive-GRU structure realizes much better performance under different accuracy indexes.

Long-term validation of inner-urban mobility metrics derived from Twitter/X

Urban mobility analysis using Twitter as a proxy has gained significant attention in various application fields; however, long-term validation studies are scarce. This paper addresses this gap by assessing the reliability of Twitter data for modeling inner-urban mobility dynamics over a 27-month period in the. metropolitan area of Rio de Janeiro, Brazil. The evaluation involves the validation of Twitter-derived mobility estimates at both temporal and spatial scales, employing over 1.6 × 1011 mobile phone records of around three million users during the non-stationary mobility period from April 2020 to. June 2022, which coincided with the COVID-19 pandemic. The results highlight the need for caution when using Twitter for short-term modeling of urban mobility flows. Short-term inference can be influenced by Twitter policy changes and the availability of publicly accessible tweets. On the other hand, this long-term study demonstrates that employing multiple mobility metrics simultaneously, analyzing dynamic and static mobility changes concurrently, and employing robust preprocessing techniques such as rolling window downsampling can enhance the inference capabilities of Twitter data. These novel insights gained from a long-term perspective are vital, as Twitter - rebranded to X in 2023 - is extensively used by researchers worldwide to infer human movement patterns. Since conclusions drawn from studies using Twitter could be used to inform public policy, emergency response, and urban planning, evaluating the reliability of this data is of utmost importance.