Spatial-temporal Behavior Research Articles

Elucidating the origin of laser induced nonlinearities in propagation inside transparent medias: A comparative numerical study of silicon and fused silica

Abstract The creation of localized bulk modification using femtosecond pulses inside semiconductors like silicon (Si) is quite challenging whereas it is not difficult to achieve it for dielectric material like fused silica (FS). So, this report addresses the fundamental origin of this issue. By taking simple numerical approach, it has been found that in FS we can deliver stronger fluence due to self-focusing on higher power level as compared to Si. The origin for the above lies on the spatial-temporal pulse-splitting behavior which is dominant in case of FS at the focus, whereas for Si it is only effective after focus. We have also considered the influence of plasma and Kerr terms to elucidate the reason behind such nonlinearities. For FS case, omission of Kerr term dominates whereas for Si the influence of each term does not significantly create self-focusing like FS under a similar focusing condition. This study could make an important guideline for researchers to understand the complexity of laser-matter interaction in transparent materials specifically being studied by many laser processing industries.

Touristic Learning Behaviors and Outcomes in Theme Parks: The Role of Activity and Affectional Contexts

ABSTRACTExisting studies have highlighted the significance of touristic learning; however, few have explored the effectiveness of different learning contexts. This study employs a combination of spatial–temporal behavior analysis and survey research to investigate how activity context (static vs. interactive) and affectional context (positive vs. negative) influence visitors' spatial–temporal behaviors and learning outcomes in zoological theme parks. The results indicated that interactive contexts are more effective than static contexts in extending visitors' duration of stay, increasing the diversity of venues explored, and enhancing both emotion and learning outcomes of visitors. The moderating effect of affectional context is significant, with the positive context notably enhancing emotion and learning outcomes of visitors associated with the interactive context. Additionally, visitors' emotion played a mediating role in the relationship between activity contexts and learning outcomes. These empirical findings offer valuable practical implications for the design of educational experiences within theme parks.

Mapping gender patterns in “dynamic cultural spaces”: the case of Beijing’s open-air antiques “ghost market” at Panjiayuan

Despite the growing recognition of the importance of street vendors and informal markets for urban life and the economy globally, research attention has tended to focus on essential products such as food or clothes and paid less attention to cultural products, such as antiques where potential gender, and other socio-demographic, differences in vending and buying behaviours may systematically differ. To explore these issues, this study employed spatial–temporal behaviour mapping (STBM) and field observations (n = 8587) at Beijing’s Panjiayuan antiques “ghost market” a term reflecting its previously illegal/underground and mobile nature. We monitored four representative sites within the market, four times a day for six consecutive days. The data included five categories of behaviour, four age groups, and two genders. Data were recorded and analysed using ArcGIS. Results showed that, unlike common marketplaces, the antique market is primarily frequented by male vendors and buyers, replicating patterns seen in ancient Chinese paintings of men being involved in the trading of “non-essentials”. Nonetheless, we found differing gender balances depending on the time and day of the week, different age groups, and spatial settings in different market areas. We summarise the nuanced relationships between the emerging gender spatio-temporal behaviour patterns and three key factors, spatial characteristics, physical activities and the social division of labour, in the Chinese context. The study reveals how the varied spatial–temporal patterns of a large antique “ghost market” raise long-established issues of equity and inclusivity and provide empirical insights that could inform decision-making and urban planning, such as better use of dynamic lighting provision to encourage a more gender-balanced experience.

Measurement of 2p-3d absorption in a hot molybdenum plasma

We present measurements of the 2p-3d transition opacity of a hot molybdenum–scandium sample with nearly half-vacant molybdenum M-shell configurations. A plastic-tamped molybdenum–scandium foil sample is radiatively heated to high temperature in a compact D-shaped gold Hohlraum driven by ∼30 kJ laser energy at the SG-100 kJ laser facility. X rays transmitted through the molybdenum and scandium plasmas are diffracted by crystals and finally recorded by image plates. The electron temperatures in the sample in particular spatial and temporal zones are determined by the K-shell absorption of the scandium plasma. A combination of the IRAD3D view factor code and the MULTI hydrodynamic code is used to simulate the spatial distribution and temporal behavior of the sample temperature and density. The inferred temperature in the molybdenum plasma reaches a average of 138 ± 11 eV. A detailed configuration-accounting calculation of the n = 2–3 transition absorption of the molybdenum plasma is compared with experimental measurements and quite good agreement is found. The present measurements provide an opportunity to test opacity models for complicated M-shell configurations.

Spatial clusters, temporal behavior, and risk factors analysis of rabies in livestock in Ecuador

Rabies, a globally distributed and highly lethal zoonotic neglected tropical disease, has a significant impact in South America. In Ecuador, animal rabies cases are primarily linked to livestock, and hematophagous bats play a crucial role in disease transmission. This study aims to identify temporal trends, spatial patterns, and risk factors for animal rabies in Ecuador between 2014 and 2019. Epidemiological survey reports from the official Animal Rabies Surveillance Program of the Phyto and Zoosanitary Regulation and Control Agency of Ecuador (AGROCALIDAD) were used. The Animal Rabies Surveillance Program from AGROCALIDAD consists of an official passive surveillance program that receives reports from farmers or individuals (both trained or untrained) who have observed animals with neurological clinical signs and lesions compatible with bat bites, or who have seen or captured bats on their farms or houses. Once this report is made, AGROCALIDAD personnel is sent for field inspection, having to confirm the suspicion of rabies based on farm conditions and compatibility of signs. AGROCALIDAD personnel collect samples from all suspicious animals, which are further processed and analyzed using the Direct Fluorescent Antibody (DFA) test for rabies confirmatory diagnosis. In this case, study data comprised 846 bovine farms (with intra-farm sample sizes ranging from 1 to 16 samples) located in different ecoregions of Ecuador; out of these, 397 (46.93%) farms tested positive for animal rabies, revealing six statistically significant spatial clusters. Among these clusters, three high-risk areas were identified in the southeast of Ecuador. Seasonality was confirmed by the Ljung-Box test for both the number of cases (p < 0.001) and the positivity rate (p < 0.001). The Pacific Coastal lowlands and Sierra regions showed a lower risk of positivity compared to Amazonia (OR = 0.529; 95% CI = 0.318 – 0.883; p = 0.015 and OR = 0.633; 95% CI = 0.410 – 0.977; p = 0.039, respectively). The breeding of non-bovine animal species demonstrated a lower risk of positivity to animal rabies when compared to bovine (OR = 0.145; 95% CI = 0.062 – 0.339; p < 0.001). Similarly, older animals exhibited a lower risk (OR = 0.974; 95% CI = 0.967 – 0.981; p < 0.001). Rainfall during the rainy season was also found to decrease the risk of positivity to animal rabies (OR = 0.996; 95% CI = 0.995 – 0.998; p < 0.001). This study underscores the significance of strengthening the national surveillance program for the prevention and control of animal rabies in Ecuador and other countries facing similar epidemiological, social, and geographical circumstances.

Exploring gender-based spatio-temporal patterns of informal street vending: A case study in Fangshan District, Beijing, China

Many studies have shown that, due largely to family and socio-cultural influences, women prefer part-time and flexible employment, which aligns with the character of informal street vending. However, unlike many other workers, female vendors must consider the temporary use of space and co-produce an ever-changing environment that interacts with a diverse range of people with heterogeneous demands, a phenomenon that has received little research attention. Using spatial-temporal behavior mapping and on-site observations at three street spaces in Fangshan District, Beijing, China, we examined the spatio-temporal behavioral patterns of female vendors and explored gender differences in the type, mode, spatial meaning, and time of informal vending in the Chinese urban context. Our results indicate that when vending space is limited, male vendors tend to cluster; female vendors are more dispersed, and more likely to occupy spaces with unfavorable selling environments. When there are fewer vendors on the site, female vendors sell closer to the inner side of the street (i.e., less accessibility compared with male vendors). Most female vendors sell relatively lightweight and small goods with low profit margins. Male vendors tend to occupy fixed stalls and utilize heavier transport equipment, while female vendors are more likely to be flexible in location and use lightweight transport equipment. Furthermore, female vendors are more likely than male vendors to operate during weekdays and in daylight hours than on the weekends and at night. We also attempted to understand the potential reasons for gender differences in temporary space use, and informal socio-economic co-production, in urban street contexts. Our study provides further scientific basis for the promotion of more inclusive, vibrant, and healthy urban environments by considering the largely overlooked group of informal female street vendors and their temporary inhabitation and use of urban street space.

Spatiotemporal analysis of wildfire in the Tigris and Euphrates basin: A remote sensing based wildfire potential mapping

In recent years, there has been a significant increase in the occurrence of wildfires in rangelands and forests worldwide. Such events are even more critical in arid and semi-arid regions with sparse rangeland and forest covers. In this paper, we studied how wildfires behave and what drives them, and used a random forest algorithm to map wildfire potential in the Tigris and Euphrates basin. A stratified random sampling method was used to collect 53,053 wildfire points and an equal number of non-wildfire points in rangelands and forests of the basin between 2000 and 2019. The spatial-temporal behavior of environmental parameters affecting wildfire potential was analyzed. Among them, precipitation, temperature, wind speed, vegetation condition index, drought index, actual evapotranspiration, and reference evapotranspiration were identified as the main drivers of wildfires. The performance of our wildfire potential mapping model was compared with the Fire Weather Index (FWI). Our method showed superior results with an overall accuracy of 96% and a kappa coefficient of 93% compared to the FWI which had an overall accuracy of 58% and a kappa coefficient of 17.5%.

Spatial-temporal behaviour of hikers in the southeastern margin of Qinghai-Tibet Plateau: insights from volunteered geographic information

Understanding the macroscopic spatial-temporal behaviour of hikers plays an important role in targeted planning, marketing and management for regional hiking tourism development. The southeastern margin of Qinghai-Tibet Plateau, with abundant outdoor tourism resources and several World Heritage Sites, was chosen as the study area, and the development characteristics of hiking tourism and the spatial-temporal behaviour of its hikers were explored by seasonal intensity index, kernel density analysis, line density analysis and K-means clustering with volunteered geographic information (VGI). The results showed that hikers differed significantly from traditional tourists in terms of travel time, travel mode and destination choice, which provide vital implications for sustainable policy-making and tourism management in general and in the southeastern margin of Qinghai-Tibet Plateau in particular.

Research on time sequence prediction of supersonic cascade flow field based on compressed sensing artificial neural network

The aviation engine that achieves efficient energy conversion is the core power equipment for low-carbon navigation, and the thermal components represented by the combustion chamber greatly affect the stable state of the compressor cascade flow field. Accurate, comprehensive and promptly monitoring of the compressor cascade flow state is related to the safe operation of the engine. A flow field time sequence prediction framework named compressed convolutional gate recurrent unit (CC-GRU) was proposed in this study to predict future supersonic cascade flow parameters based on the flow field at previous moments. CC-GRU embedded convolution into gate recurrent unit (GRU) to deal with the complex spatial-temporal behavior of supersonic cascade flow field. Firstly, unsteady numerical simulations driven by linear changes in back pressure were carried out, and the dataset for model training and validation was obtained to verify the feasibility of time sequence prediction of the cascade flow field. The verification results indicate that the framework can comprehensively predict the flow field with high back pressure in the future according to the flow field with low back pressure in the past period, and further validated the effectiveness of the proposed time sequence prediction model in ground wind tunnel experiments. The CC-GRU model can accurately capture the fine shock wave structure and flow separation zone, with a relative error of less than 10% in predicting the pressure field, and is mainly concentrated within the shock wave structure. Therefore, this research provides new research perspective and technical support for comprehensive and promptly condition monitoring of supersonic cascade flow field.

Anisotropically weighted Lq$L^q$‐Lr$L^r$ estimates of the Oseen semigroup in exterior domains, with applications to the Navier–Stokes flow past a rigid body

AbstractWe consider the spatial–temporal behavior of the Navier–Stokes flow past a rigid body in . This paper develops analysis in Lebesgue spaces with anisotropic weights , which naturally arise in the asymptotic structure of fluid when the translational velocity of the body is parallel to the x1‐direction. We derive anisotropically weighted ‐ estimates for the Oseen semigroup in exterior domains. As applications of those estimates, we study the stability/attainability of the Navier–Stokes flow in anisotropically weighted spaces to get the spatial–temporal behavior of nonstationary solutions.

Measuring visitor flows using mobile positioning data in three Hungarian second-tier cities

PurposeThe research analyses the spatial-temporal behaviour of international visitors using mobile positioning data (MPD) in three second-tier cities in Hungary: Szeged, Debrecen and Pécs. The purpose of this study is to identify the origins of visitors, length of stay, seasonal concentrations and mobility between cities.Design/methodology/approachA large volume of data generated by foreign mobile phone users was processed and analysed for six consecutive months in 2018. The movements of around 3.5 million foreigners visiting Hungary were captured.FindingsThe data showed significant differences in tourist turnover, mobility patterns and flows indicating different levels of tourism activity and potential in the three cities. This included day trips, cross-border tourism, seasonal fluctuations and activity-driven demand (e.g. special events and cultural tourism).Research limitations/implicationsMPD cannot fully explain or predict drivers of visitor behaviour, such as purpose of visit, the precise activities that they undertake there and the experiences that they gain. It can, however, provide information on spatial and temporal flows, patterns and concentrations of visitors.Practical implicationsThe investigated cities should follow distinct tourism development policies to attract more tourists and strengthen the links with their neighbouring destinations at the same time as differentiating themselves through marketing as competitive alternative destinations.Social implicationsAugmenting tourism has socio-economic implications for residents and communities. The development of cultural tourism and local event-based tourism must incorporate community needs.Originality/valueThe paper analyses the extent to which MPD can provide insights into visitors’ spatio-temporal mobility and flows in relatively under-visited second-tier cities and it highlights opportunities and gaps for big data research in an urban context.

Numerical characterization of transient electrohydrodynamic deformation and coalescence of single-core double emulsion droplets by AC field dielectrophoresis

Considering its good biocompatibility, the water-in-oil-in-water type compound double emulsion (DE) droplet serves as an ideal microreaction vessel upon their on-demand electro-coalescence. By coupling phase field description to fluid dielectrophoresis, transient numerical simulation is conducted to characterize the dynamic feature of surface charge wave and electric stress induced at various phase interfaces of single-core DE drops subjected to external AC electric fields. A novel prolate/prolate electro-deformation mode is discovered by numerical analysis for A/B/A type two-phase droplet when both the conductivity and permittivity of oil shell are much smaller than that of water phase. Based upon this, AC electrostatic attraction between two opposing single-core DE droplets is then investigated in a broad parametric space. Collision of two adjacent oil shells is always followed by the dielectrophoretic integration of corresponding water cores wrapped within them, leading to three different possible modes of inter-droplet electro-coalescence under distinct core/shell radius ratio. Our numerical analysis herein unveils for the first time the hitherto unknown spatial-temporal electrohydrodynamic behavior of single-core DE droplets driven by Maxwell-Wagner structural polarization, during their deformation and coalescence as a consequence of an active interplay among those induced droplet dipoles.

Monitoring and analysis of Woda landslide (China) using InSAR and Sentinel-1 data

Detecting the slow motions of highly elevated landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to precipitation. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation.

Mental Health in Urban Environments: Uncovering the Black Box of Person-Place Interactions Requires Interdisciplinary Approaches

Living in urban environments affects individuals' mental health through different pathways. For instance, physical activity and social participation are seen as mediators. However, aiming to understand underlying mechanisms, it is necessary to consider that the individual is interacting with its environment. In this regard, this viewpoint discusses how urban health research benefits from integration of socioecological and interdisciplinary perspectives, combined with innovative ambulatory data assessments that enable researchers to integrate different data sources. It is stated that neither focusing on the objective and accurate assessment of the environment (from the perspective of spatial sciences) nor focusing on subjectively measured individual variables (from the public health as well as a psychosocial perspective) alone is suitable to further develop the field. Addressing person-place interactions requires an interdisciplinary view on the level of theory (eg, which variables should be focused on?), assessment methods (eg, combination of time-varying objective and subjective measures), as well as data analysis and interpretation. Firstly, this viewpoint gives an overview on previous findings addressing the relationship of environmental characteristics to physical activity and mental health outcomes. We emphasize the need for approaches that allow us to appropriately assess the real-time interaction between a person and a specific environment and examine within-subject associations. This requires the assessment of environmental features, the spatial-temporal behavior of the individual, and the subjective experiences of the situation together with other individual factors, such as momentary affective states. Therefore, we finally focused on triggered study designs as an innovative ambulatory data assessment approach that allows us to capture real-time data in predefined situations (eg, while walking through a specific urban area).

Bluetooth beacons based indoor positioning in a shopping malls using machine learning

The adoption of Bluetooth beacon technology demonstrates a broad interest in indoor positioning technology because of its low cost and ease of use. Bluetooth beacons usually have an accuracy of fewer than 4 meters. The use of machine learning (ML) leads to results with greater accuracy compared to using traditional filtering methods. In this paper, we provide indoor localization based on Bluetooth beacons using several different ML techniques. We used ML algorithms to locate customers' devices in shopping malls. The extra-trees classifier and k-neighbors classifier found the device with greater than 90% accuracy. Other algorithms were able to determine the location with less accuracy. The results also showed that Bluetooth technology is a valid solution to find the data used to analyze the spatial-temporal behavior of individuals.

Gamification innovation: understanding industrial tourism products and tourist response

ABSTRACT Industrial tourism has achieved great development. The diversification of tourism demand has led to higher requirements for the innovation of industrial tourism products. Based on theory of tourists’ spatial–temporal behavior and experience economy, this study takes Shanghai M50 park to study the impact of gamification innovation of industrial tourism products. There are few studies on tourists’ internal response and external behavior response. This study confirms for the first time that gamification innovation can extend the travel time and travel distance, improve the travel experience, and enhance tourists’ willingness to revisit and recommend. This study shows gamification innovation improves tourists’ experience.

3D nuclei segmentation for multi-cellular quantification of zebrafish embryos using NISNet3D

Advances in imaging of developing embryos in model organisms such as the fruitfly, zebrafish, and mouse are producing massive data sets that contain 3D images with every cell and readouts of signaling activity in every cell of an embryo. In Zebrafish embryos, determining the locations of nuclei is crucial for the study of the spatial-temporal behavior of these cells and the control of gene expression during the developmental process. Traditional image processing techniques suffer from bad generalizations, often relying on heuristic measurements that narrowly applies to specific data types, microscope settings, or other image characteristics. Machine learning techniques, and more specifically convolutional neural networks, have recently revolutionized image processing and computer vision. A well-known challenge in developing theses algorithms is the lack of curated training data. We developed a new, manually-curated nuclei segmentation data set for four complete embryos containing over 8,000 cells each. The whole-mount zebrafish embryos at different development stages were hand-labeled with 3D volumetric segmentation of nuclei. Two full embryo data sets were used for training the 3D nuclei instance segmentation network NISNet3D, and the other two embryos were used to validate the training results. We provide both qualitative and quantitative evaluation results for each of the volumes using multiple evaluation metrics. We also provide the fully curated and manually segmented embryo data sets, along with raw images, for the image processing community.

On the Spatial-Temporal Behavior, and on the Relationship Between Water Quality and Hydrometeorological Information to Predict Dissolved Oxygen in Tropical Reservoirs. Case Study: La Miel, Hydropower Dam

Hydropower is currently one of the leading renewable energy sources in developing countries. Despite the benefits that it can provide, it also triggers significant environmental impacts, such as changes in the reservoirs’ water quality. In quantifying those changes, dissolved oxygen (DO) is used as one of the water quality indicators and is the most used variable to quantify water quality and analyze water pollution. This paper aims to establish a relationship between water quality and hydrometeorological variables in tropical reservoirs to better estimate dissolved oxygen. Univariate and multivariate techniques were used to analyze temporal and spatial changes in watersheds to better select vital variables for the forecast model, such as Vector Autoregression (VAR). The results show that, for all monitoring stations, the water quality variables associated with the DO process are COD, BOD, and PO₄. Likewise, precipitation and flow discharge were the hydrometeorological parameters that had the most significant impact on DO. Also, the principal component analysis (PCA) allowed us to identify that the strength of the relationships between water quality and hydrometeorology changes depending on the location of the monitoring site. Finally, the implementation of a VAR model showed good performance metrics for dissolved oxygen predictions based on all analyses.

Dual photopatterning of rotational fingerprint superstructures

Controlling architecture of hierarchical microstructures in liquid crystals (LCs) plays a crucial role in the development of novel soft-matter-based devices. Chiral LC fingerprints are considered as a prospective candidate for various applications; however, the efficient and real-time command of fingerprint landscapes still needs to be improved. Here, we achieve elaborate rotational fingerprint superstructures via dual photopatterning semifree chiral LC films, which combine the photoalignment technique and a dynamic light patterning process. An intriguing spatial-temporal rotational behavior is presented during the patterning of chiral superstructures. This work opens new avenues for the applications of chiral LCs in soft actuators, sensing, and micromanufacturing.

A weakening-healing law to simulate stick-slip behavior of rock joint and the associated seismicity

The variation of frictional strength of asperities is one of the fundamental mechanisms that govern earthquake cycles. The rate - and - state friction (RSF) law has been widely employed to explain earthquake phenomena. In RSF, the frictional strength of fault depends upon the current slipping velocity and the conditions on the slipping surface (i.e., the state), which depends partly on the prior sliding history. In this study, we proposed a simplified weakening-healing law to describe the slip behavior of individual asperity. In the weakening-healing law, the friction strength linearly decreases to the residual value with shear displacement when slip occurs, and immediately recovers to its original value once slip terminates. In the numerical model, a power-law distribution is used to introduce asperity heterogeneity (e.g., size, frictional strength, and stiffness) on a rock joint. A displacement-based moment tensor method is used to calculate the seismic moment during fault slipping. The simulated b-value (magnitude-frequency distribution) and its evolution during stick-slip phases are compared with published experiments. Slip nucleation, growth, coalescence, and the associated spatial-temporal behavior of the simulated seismicity are delineated. Although this preliminary study focuses on simplified conditions (small-scale smooth rock joint sheared under constant normal pressure and shear rate), our method successfully duplicates laboratory observed stick-slip behavior, b-value evolution, slip nucleation process, etc., providing a promising way to mimic more realistic natural earthquake phenomena.