Mobility Analysis Research Articles

Structural Analysis and Mass Optimization of Mobility Walkers Using Lightweight Polymer Matrix Composites

Structural Analysis and Mass Optimization of Mobility Walkers Using Lightweight Polymer Matrix Composites

Electron–photon–phonon interactions in Dirac semimetals: Magneto-optical absorption and mobility analysis

We study the magneto-optical properties of Dirac semimetal (DSM) slabs with particular emphasis on Cd3As2 through electron–photon–phonon interactions, focusing on the magneto-optical absorption coefficient (MOAC) and full-width at half maximum (FWHM). Studying the Landau level (LL) energy of DSMs in the (xy) plane and the z-direction revealed a unique deviation from the square root dependence on the magnetic field, distinguishing DSMs from other semiconductors. At high magnetic fields, the electron–hole symmetry in the LL spectrum is broken, indicating a topological phase in DSMs. For undoped DSMs, MOAC is driven by interband transitions, with peaks from one-photon absorption being smaller and positioned to the left of two-photon ones. Increasing the magnetic field increases peak values. FWHM for one- and two-photon processes increases with the magnetic field and follows a T dependence on temperature. In doped DSMs, both intraband and interband transitions occur, with new interband peaks emerging at higher temperatures near the Fermi energy. Increased electron density shifts the peak position slightly toward higher energy. Peaks from optical phonon emission are consistently higher and located to the right of those from optical phonon absorption, indicating a stronger emission process. The FWHM data allow for the estimation of electron mobilities, and using a reasonable broadening parameter, our predicted mobility values agree with experimental results.

Determination of tetramethylammonium hydroxide in air using ion chromatography or ultra-performance liquid chromatography - high-resolution mass spectrometry

Tetramethylammonium hydroxide (TMAH) is extensively utilized in the semiconductor and optoelectronic industries, serving as either a developer or an etchant. TMAH possesses acute toxicity and alkaline corrosiveness, having caused several fatal and injurious accidents in Taiwan. However, there is currently a lack of methods available for assessing TMAH exposure. This study developed a method involving sampling with quartz fiber filters followed by ultrasonic agitation in 10 mL mobile phase, filtering, and analysis using either ion chromatography (IC) or ultra-performance liquid chromatography - high-resolution mass spectrometry (UPLC-HRMS). Utilizing the characteristics of HRMS, the compound analyzed was identified as tetramethylammonium ion (TMA+) through mass spectrometry analysis. The method exhibits excellent trapping capacity and recovery rate. The linear range of TMA+ for IC is 0.3 to 100 μg/mL, with a correlation coefficient of R = 0.9998. The linear range of TMA+ for UPLC-HRMS is 0.002 to 1 μg/mL, with a correlation coefficient of R = 0.996. The recovery rates for IC and HRMS were 116.6% and 90.6%, with corresponding coefficient of variation (CV) of 2.25% and 3.53%, respectively. Samples can be stored at room temperature for 28 days. Verification of this method was conducted at the TMAH factory, and the air concentrations measured in the TMAH filling area were 3.29 and 4.75 μg/m3 from IC and UPLC-HRMS, respectively. This method will be applied in the on-site analysis of occupational hazards for operators in chemical plants, technology factories, and recycling plants, aiming to evaluate risk values to protect the safety and health of workers and prevent occupational diseases.

Fast mobility analysis for generative design applications through a real vector space representation of mobilities

During the early stages of design, mechanisms are commonly modeled as perfect joints assembled with infinitely rigid bodies. This representation enables the prediction of the system’s mobilities through a mobility analysis. However, traditional mobility analysis tools can be computationally expensive or lack critical information, such as the type or direction of mobilities. It hinders the generation of topology and configuration through generative design schemes.In this paper, we propose an alternative approach to mobility analysis based on a real vector space representation of mobilities. Our method provides relevant information for early design steps while being computationally effective through a novel formulation of series and parallel assembly topological operations. A benchmark on four selected use cases highlights an acceleration of 3 to 4 orders of magnitude compared to traditional approaches. Additionally, design rules on the joints’ positions can be automatically generated with our approach. It enables the automation of the complete design process, including topology and configuration. As such, we provide guidelines to develop a generative design scheme dedicated to the synthesis of guiding mechanisms.

The Impact of Fractures on Shale Oil and Gas Enrichment and Mobility: A Case Study of the Qingshankou Formation in the Gulong Depression of the Songliao Basin, NE China

To study the impact of faults on the enrichment and mobility of shale oil in the Gulong area, representative rock samples were selected in this paper. Based on geochemical data and chemical kinetics methods, coupled with shale oil enrichment and mobility analysis techniques, the shale oil generation quantity and in situ oil content were evaluated from the perspectives of shale oil generation and micro migration, and the mobility of shale oil was revealed. At the same time, the hydrocarbon expulsion efficiency (HEE) of shale was qualitatively and quantitatively characterized, combined with the development of faults. The research results indicate that the study area mainly develops organic-rich felsic (ORF)/organic-containing felsic (OCF) shale, their proportion in both wells exceeds 65%, and the resource amount is the largest in this type of lithofacies. The development of a fault controls the enrichment of shale oil, and the in situ oil content and oil saturation index (OSI) of the shale in well Y58, which is close to the fault, are significantly worse than those in well S2. Well Y58 has 9.52 mg/g and 424.83 mg/g TOC respectively, while well S2 has 11.34 mg/g and 488.73 mg/g TOC respectively. The fault enhanced the migration of shale oil, increasing the efficiency of oil expulsion. As a result, the components with weak polarity or small molecules, such as saturated hydrocarbons and low carbon number n-alkanes, are prone to migration, reducing the mobility of shale oil.

Analysing Urban Traffic Patterns with Neural Networks and COVID-19 Response Data

Accurate traffic prediction is crucial for urban planning, especially in rapidly growing cities. Traditional models often struggle to account for sudden traffic pattern changes, such as those caused by the COVID-19 pandemic. Neural networks offer a powerful solution, capturing complex, non-linear relationships in traffic data for more precise prediction. This study aims to create a neural network model for predicting vehicle numbers at main intersections in the city. The model is created using real data from the sensors placed across the city of Zilina, Slovakia. By integrating pandemic-related variables, the model assesses the COVID-19 impact on traffic flow. The model was developed using neural networks, following the data-mining methodology CRISP-DM. Before the modelling, the data underwent thorough preparation, emphasising correcting sensor errors caused by communication failures. The model demonstrated high prediction accuracy, with correlations between predicted and actual values ranging from 0.70 to 0.95 for individual sensors and vehicle types. The results highlighted a significant pandemic impact on urban mobility. The model’s adaptability allows for easy retraining for different conditions or cities, making it a robust, adaptable tool for future urban planning and traffic management. It offers valuable insights into pandemic-induced traffic changes and can enhance post-pandemic urban mobility analysis.

Multiple-charging effects on the CCN activity and hygroscopicity of surrogate black carbon particles

Accurate measurements of cloud condensation nuclei (CCN) activity and hygroscopicity of black carbon (BC)-containing particles are particularly important because of the positive climate forcing from these particles. Such measurements are typically conducted on particles selected by a Differential Mobility Analyzer (DMA), which in addition to singly charged particles transmits multiply charged larger particles that have the same electrical mobility. These larger particles activate at lower supersaturations than the singly charged particles, biasing measurements and resulting in overestimation of CCN activity and hygroscopicity parameter (κ). Here, we measure the CCN activity and determine κ for different BC surrogates with electrical mobility diameters from 100 to 200 nm selected 1) only by electrical mobility with a DMA, and 2) by both electrical mobility and mass using a DMA and a Centrifugal Particle Mass Analyzer (CPMA), thus allowing selection of only singly charged particles. We demonstrate the use of the DMA-CPMA system in resolving biases caused by multiply charged particles, and we show that the effect of multiple charging on the CCN activity of the BC particles is strongly influenced by morphology dispersion, i.e., the variability due to the range of morphologies of particles that have the same electrical mobility and mass. Our findings show that electrical mobility-based methods alone are unlikely to lead to accurate results in measurements of CCN activation and hygroscopicity of BC particles, even for those with a more compact morphology.

Exploring the manganese-dependent interaction between a transcription factor and its corresponding DNA: insights from gas-phase electrophoresis on a nES GEMMA instrument

Manganese ion homeostasis is vital for bacteria and is achieved via manganese-dependent transcription factors. Manganese mediation of transcription factor attachment to the corresponding oligonucleotide sequences can be investigated, e.g. via electrophoretic mobility shift assays (EMSA). Formation of specific biocomplexes leads to differences in the migration pattern upon gel electrophoresis. Focusing on electrophoresis in the gas-phase, applying a nano electrospray gas-phase electrophoretic mobility molecular analyzer (nES GEMMA) also known as nES differential mobility analyzer (nES DMA), and on transcription factors (MntR proteins) from Bacillus subtilis and Mycobacterium tuberculosis, we took interest in the gas-phase electrophoresis of the corresponding biospecific complexes. We compared nES GEMMA, separating analytes in the nanometer regime (a few to several hundred nm in diameter) in the gas-phase in their native state according to particle size, to EMSA data. Indeed we were able to demonstrate manganese-mediated attachment of MntR to target genomic sequences with both analytical techniques. Despite some inherent pitfalls of the nES GEMMA method like analyte/instrument surface interactions, we were able to detect the target complexes. Moreover, we were able to calculate the molecular weight (MW) of the obtained species by application of a correlation function based on nES GEMMA obtained data. As gas-phase electrophoresis also offers the possibility of offline hyphenation to orthogonal analysis techniques, we are confident that nES GEMMA measurements are not just complementary to EMSA, but will offer the possibility of further in-depth characterization of biocomplexes in the future.Graphical

Outdoor mobile broadband performance analysis in Malaysia, Singapore, and Thailand

This paper presents the measurement of mobile broadband (MBB) performance and specifies insightful knowledge about 3G and 4G technologies of dense urban and urban morphologies in Malaysia, Thailand, and Singapore. This study will also contribute to planning efficiently for the deployment of 5G network in these three countries. The data to characterize and analyze the MBB performances are gathered through a driving test (DT) conducted in areas of the three countries for two months starting from January to February by utilizing an unbranded smartphone named Samsung Galaxy S6. The performance data in our MBB analysis was collected based on diverse national mobile network operators (MNOs) in outdoor areas of the selected states in the mentioned countries. Four different performance metrics (coverage, speed, latency, and satisfaction) were investigated to assess the network performance for one of MBB's services that contain video streaming services. Within video services, two distinct resolutions including 720p (low) and 1080p (high) for an identical YouTube video were loaded alternately by the same smartphone. The research is meant to mimic real scenarios in the case of the unlocked smartphone to any technology during the time of loading a video, which contributes to knowing the network coverage of 2G, 3G, and 4G technologies in the chosen areas. The analysis of the 2G technology is excluded in the current paper because of the limited data amount of 2G. The MBB performance measurement results in the tested areas revealed that, on average, the 4G network outperformed the 3G network according to the investigated four performance indicators. Therefore, across the tested territories, the 4G technology offered better network coverage compared to the 3G technology. The vMOS scores for 4G technology across video services were more than 3, whereas the 3G technology has achieved scores smaller than 3. Also, the 4G network has achieved E2E RTT-Ping server latency improvements of 89.90%, 59.30%, 67.48%, and 58.04% compared to the 3G network in the urban and dense urban of Klang Valley, Malaysia, urban of Singapore, and urban of Thailand, respectively. Moreover, it is found that 4G technology can provide improvements up to the factors of 1.29, 1.61, 1.98, and 1.35 in the download speed for video streaming compared to the 3G technology for urban and dense urban of Klang Valley, Malaysia, urban of Singapore, and urban of Thailand, respectively.

Quantification of high-density lipoprotein particle number by proton nuclear magnetic resonance: don't believe the numbers.

Proton nuclear magnetic resonance (NMR) can rapidly assess lipoprotein concentrations and sizes in biological samples. It may be especially useful for quantifying high-density lipoprotein (HDL), which exhibits diverse particle sizes and concentrations. We provide a critical review of the strengths and limitations of NMR for quantifying HDL subclasses. Recent studies using NMR have shed light on HDL's role in various disorders, ranging from residual cardiovascular risk to host susceptibility to infection. However, accurately quantifying HDL particle number, size, and concentration (HDL-P) remains a challenge. Discrepancies exist between NMR and other methods such as gel electrophoresis, ion mobility analysis and size-exclusion chromatography in estimating the abundance of HDL species and the ratio of apolipoprotein A-I (APOA1) to HDL particles. NMR is a low-cost method for quantifying HDL-P that is readily applicable to clinical and translational studies. However, inconsistencies between the results of NMR quantification of HDL-P and other independent methods hinder the interpretation of NMR results. Because proton NMR apparently fails to accurately quantify the sizes and concentrations of HDL, the relevance of such studies to HDL biology poses challenges. This limits our understanding of pathophysiological implications of HDL-P as determined by NMR, particularly in determining cardiovascular disease (CVD) risk.

Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.

Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in clinical settings. Major obstacles include uncertainty regarding the best protocol for instrumented mobility testing and subsequent data processing, as well as the added workload and complexity of this multi-step process. To simplify sensor-based mobility testing in diagnosing PD, we analyzed data from 262 PD participants and 50 controls performing several motor tasks wearing a sensor on their lower back containing a triaxial accelerometer and a triaxial gyroscope. Using ensembles of heterogeneous machine learning models incorporating a range of classifiers trained on a set of sensor features, we show that our models effectively differentiate between participants with PD and controls, both for mixed-stage PD (92.6% accuracy) and a group selected for mild PD only (89.4% accuracy). Omitting algorithmic segmentation of complex mobility tasks decreased the diagnostic accuracy of our models, as did the inclusion of kinesiological features. Feature importance analysis revealed that Timed Up and Go (TUG) tasks to contribute the highest-yield predictive features, with only minor decreases in accuracy for models based on cognitive TUG as a single mobility task. Our machine learning approach facilitates major simplification of instrumented mobility testing without compromising predictive performance.

A COMPARATIVE ANALYSIS BETWEEN PERSONAL AND TERRESTRIAL LASER SCANNING FOR THE DOCUMENTATION OF HERITAGE SITES

This paper presents a comparative analysis of mobile and terrestrial laser scanning techniques in the 3D surveying of Bashtova castle in Albania, showcasing the integration's efficacy in capturing a comprehensive and accurate representation of this historical structure. Personal laser scanning (PLS), characterized by its mobility and ability to capture data while in motion, offers advantages in terms of efficiency and coverage of large areas. Conversely, terrestrial laser scanning (TLS), with its stationary setup and high precision, excels in capturing detailed information and intricate architectural features. Thanks to the research on the case study of the Bastova Castle in the article, it can be stated that the integration of data from PLS and TLS is seamless with the help of modern software while respecting the basic photogrammetric-geodetic rules and demonstrates the possibility of creating a complex 3D model, usable for further analyses for architects and conservation professionals, as well as for restorers and civil engineers. Research has shown that the difference between point clouds from PLS and TLS is within one centimeter.

Design, Analysis and Detection of Urban Mobility Patterns in Guayaquil through Supervised Learning Algorithms

This work explores the use of GPS trajectory data (Git Hub) and supervised learning algorithms to analyze mobility patterns in the city of Guayaquil-Ecuador. The analysis reveals that identifying mobility patterns is crucial to improve urban planning and optimize public transport in terms of its innovations from 2024. The methodology has included data collection from various open access sources, data preprocessing and the use of a Random Forest Classifier to detect mobility patterns. The results indicate a model accuracy of 50%, opening the possibilities for future specialized research to optimize the model and collect more data to improve its performance and propose new StartUPS for the city. The data compiled supports the implementation of the Single Card for Public Transport (TUT), which modernizes and unifies the payment system, facilitating the collection of essential data for analysis. The research concludes that the integration of data from applications such as Waze and Moovit is crucial for efficient and sustainable urban planning and that supervised learning algorithms are effective tools for urban mobility analysis and leaving open the possibility of exploring additional data and other algorithms to improve the accuracy of models and the generation of new mobility routes.

Well supplied in life, set aside in death: A multi-isotope study of Justinian plague victims from Saint-Doulchard (France, 7th-8th centuries AD).

Justinian plague and its subsequent outbreaks were major events influencing Early Medieval Europe. One of the affected communities was the population of Saint-Doulchard in France, where plague victim burials were concentrated in a cemetery enclosure ditch. This study aimed to obtain more information about their life-histories using the tools of isotope analysis. Dietary analysis using carbon and nitrogen isotopes was conducted on 97 individuals buried at Le Pressoir in Saint-Doulchard, with 36 of those originating from the enclosure ditch. This sample set includes all individuals analyzed for plague DNA in a previous study. Mobility analysis using strontium isotope analysis supplements the dietary study, with 47 analyzed humans. The results are supported by a reference sample set of 31 animal specimens for dietary analysis and 9 for mobility analysis. The dietary analysis results showed significantly different dietary behavior in individuals from the ditch burials, with better access to higher quality foods richer in animal protein. 87Sr/86Sr ratios are similar for both studied groups and indicate a shared or similar area of origin. The results suggest that the ditch burials contain an urban population from the nearby city of Bourges, which overall had a better diet than the rural population from Saint-Doulchard. It is implied that city's population might have been subjected to high mortality rates during the plague outbreak(s), which led to their interment in nearby rural cemeteries.

Are We Back to Normal? A Bike Sharing Systems Mobility Analysis in the Post-COVID-19 Era

In recent years, numerous cities around the world have adopted bike sharing systems (BSSs). The increasing popularity of these transportation means is directly related to their eco-friendly and health advantages. Several factors affect how citizens make use of BSS, for instance, the size and configuration of a city, where docking stations are located, the associated prices, and others. Moreover, these systems have different usage patterns that vary according to the month, day, or hour but remain constant when compared yearly. However, the onset of the COVID-19 pandemic modified mobility behaviors as various governments around the world implemented mobility restrictions to avoid the spread of the virus. The objective of this investigation is to determine if the usage patterns of BSSs have changed permanently or if we have recovered pre-pandemic levels and usage patterns. Given the special characteristics of each BSS, this study focuses on Barcelona’s BSS, called Bicing. To understand the impact of other BSSs, the further analysis of each system’s unique characteristics is necessary. The study employs bike usage information from the public open data service maintained by Barcelona City Hall, namely, the Open Data BCN website, from January 2019 to December 2023, and it covers mechanical and electrical bikes with more than 4 million records per month. The results show that usage patterns were similar before and after the pandemic; the usage increased in 2021 and 2022 and stabilized in 2023, registering a rise of 17.5% in Bicing usage from 2021 to 2023. However, bike type preferences have changed for reasons unrelated to the pandemic restrictions. The main limitation of this investigation is the lack of continuity in the data due to a change in the company that provides the service in Barcelona. For future research, data from other transportation means can be used to analyze all communication behavior in this city. Additionally, if data are available, a study by gender and age can be performed and used to improve the system for certain groups.

Towards 6G Satellite–Terrestrial Networks: Analysis of Air Mobility Operations

This paper presents an analytical exploration of sixth-generation (6G) satellite–terrestrial integrated networks, focusing specifically on their applications within air mobility operations, such as those involving unmanned aerial vehicles (UAVs). As the integration of satellite and terrestrial networks promises to revolutionize mobile communication by extending coverage and enhancing connectivity, this study delves into two critical aspects: link budget analysis and handover and mobility analysis for UAVs. The link budget analysis assesses the communication requirements necessary to ensure robust and consistent connectivity between satellites and UAVs, accounting for factors such as path loss, antenna gains, and power transmission. Meanwhile, the handover and mobility analysis investigates the challenges and solutions associated with UAVs transitioning between different network nodes and layers in a dynamic aerial environment. This paper utilizes theoretical models and simulations to provide insights into the design and optimization of these networks, aiming to enhance the reliability and efficiency of UAV operations in the context of the emerging 6G landscape. The findings propose not only technological advancements in network architecture but also practical guidelines for the deployment of UAVs in complex environments, marking a significant step toward the realization of a fully integrated, satellite-terrestrial ecosystem.

Impacto de la movilidad académica en la producción científica de los médicos brasileños

In recent years, a significant increase in the exodus of individuals has been observed, motivated by a variety of reasons and circumstances, both in the Brazilian and global context. One of the main driving factors of this migratory flow is the search for higher quality academic training in higher education institutions. In this scenario, this work proposes to analyze data related to the scientific production and academic training of Brazilian doctors, with the objective of understanding the impact of academic mobility on the scientific production of these professionals. To achieve this purpose, information on academic training was extracted from the curricula available on the Lattes Platform. The sample included all CVs that indicated completion of a doctorate, totaling 381,463 records. The results obtained enabled a comprehensive analysis of the academic mobility of Brazilian doctors and its correlation with data related to scientific production. It is hoped that this analysis will contribute to a deeper understanding of the relationship between academic training, mobility and scientific production of Brazilian doctors, providing relevant insights for understanding the challenges and opportunities faced by these professionals in a globalized and highly competitive environment.

A family of folding single-loop metamorphic mechanisms for aerospace manipulators: Synthesis, network, and analysis

Guided by predetermined degrees of freedom for different desired tasks, the type synthesis of single-loop metamorphic mechanisms (SLMMs) has long posed a challenge. Owing to the complexity and coupling of their overconstraints and the variability of constraints arising from bifurcation motions, it is difficult to ensure geometric coordination and synchronous motion for a network of multiple SLMMs. Here, we propose an approach to type synthesize SLMMs using the atlas method. A novel family of SLMMs is further synthesized. The mobility analysis of a selected 7R SLMM is carried out via screw theory. The kinematics and bifurcation phenomena are analyzed and verified through numerical simulation using computer-aided design models. To evaluate the performance of the SLMMs, the mapping relationship between key design parameters and performance indicators, such as the grasping angle, folding angle, and mechanical advantage, is studied. A networking method is then proposed by considering the geometric coordination conditions and variation of the overconstraints of SLMMs. Prototypes of an SLMM and manipulator with optimal geometrical parameters are developed to verify the feasibility and correctness of the proposed method and kinematic analysis.

RescuePY: Simulation-Based Rescue Response Impact Assessment

Mobility in metropolitan regions is changing. The distribution of space in cities, the design of transport modes, and the organization of mobility are being re-thought. However, no matter the changes and innovations on the way to a more sustainable future, essential constants must be upheld: In the event of minor, regionally limited emergencies, medical assistance must reach those in need quickly. When dealing with large-scale emergencies, the ability to evacuate the area promptly must be ensured. The impact analysis of mobility innovations on emergency services within urban areas so far has been based purely on empirical observations using existing data. Currently, it is only possible to analyze what-if considerations in a limited way. Nevertheless, due to the increasingly rapid changes in mobility, a comprehensive and interlinked analysis will be necessary. This is the key contribution of rescuePY: rescuePY is a simulation suite based on the mesoscopic and microscopic simulation environment hybridPY. It allows holistic and microscopic transport modeling of rescue infrastructure to quantify the impact of the mobility transition towards higher sustainability on the performance of rescue services. The main features of this software are: Rescue system assessment for strategic, long-term planning Mobility-influence studies for operative, mid-term planning Activity-based urban evacuation modeling The capabilities of rescuePY are demonstrated by two applications: a simulation- based, mesoscopic system analysis of emergency services in Munich compared to real-world data and microscopic modeling of emergency vehicles (EMVs) in different road architectures. Ongoing developments aim to improve the evaluation methodology for the aggregated impact analysis of mobility innovations on rescue response services.

Hygroscopic Properties of Water-Soluble Counterpart of Ultrafine Particles from Agriculture Crop-Residue Burning in Patiala, Northwestern India

To determine the link between hygroscopicity and the constituent chemical composition of real biomass-burning atmospheric particles, we collected and analyzed aerosols during wheat-straw (April–May), rice-straw (October–November), and no-burning periods (August–September) in 2008 and 2009 in Patiala, Punjab. A hygroscopicity tandem differential mobility analyzer (HTDMA) system was used to measure hygroscopicity at ~5 to ~95% relative humidity (RH) of aerosolized 100 nm particles generated from the water extracts of PM0.4 burning and no-burning aerosol samples. The chemical analyses of the extracts show that organic carbon and water-soluble inorganic-ion concentrations are 2 to 3 times higher in crop-residue burning aerosol samples compared to no-burning aerosols, suggesting the substantial contribution of biomass burning to the carbonaceous aerosols at the sampling site. We observed that aerosolized 100 nm particles collected during the crop-residue burning period show higher and more variable hygroscopic growth factor (g(RH)) ranging from 1.21 to 1.68 at 85% RH, compared to no-burning samples (1.27 to 1.33). Interestingly, crop-residue burning particles also show considerable shrinkage in their size (i.e., g(RH) < 1) at lower RH (<50%) in the dehumidification mode. The increased level of major inorganic ions in biomass-burning period aerosols is a possible reason for higher g(RH) as well as the observed particle shrinkage. Overall, the measured g(RH), together with the correlation observed between aerosol water content and ionic-species volume fraction, and the study of the abundance of individual constituent ionic species suggests that inorganic salts and their proportion in aerosol particles primarily governed the aerosol hygroscopicity.