Spatiotemporal Aspect Research Articles

Green Roof Substrate Microbes Compose a Core Community of Stress-Tolerant Taxa.

Extensive green roofs provide for many ecosystem services in urban environments. The efficacy of these services is influenced by the vegetation structure. Despite their key role in plant performance and productivity, but also their contribution to nitrogen fixation or carbon sequestration, green roof microbial communities have received little attention so far. No study included a spatiotemporal aspect to investigate the core microbiota residing in the substrates of extensive green roofs, although these key taxa are hypothesized to be amongst the most ecologically important taxa. Here, we identified the core microbiota residing in extensive green roof substrates and investigated whether microbial community composition is affected by the vegetation that is planted on extensive green roofs. Eleven green roofs from three different cities in Flanders (Belgium), planted either with a mixture of grasses, wildflowers and succulents (Sedum spp.; Sedum-herbs-grasses roofs) or solely species of Sedum (Sedum-moss roofs), were seasonally sampled to investigate prokaryotic and fungal communities via metabarcoding. Identifying the key microbial taxa revealed that most taxa are dominant phylotypes in soils worldwide. Many bacterial core taxa are capable of nitrogen fixation, and most fungal key taxa are stress-tolerant saprotrophs, endophytes, or both. Considering that soil microbes adapted to the local edaphic conditions have been found to improve plant fitness, further investigation of the core microbiome is warranted to determine the extent to which these stress-tolerant microbes are beneficial for the vegetational layer. Although Sedum-herbs-grasses roofs contained more plant species than Sedum-moss roofs, we observed no discriminant microbial communities between both roof types, likely due to sharing the same substrate textures and the vegetational layers that became more similar throughout time. Future studies are recommended to comprehensively characterize the vegetational layer and composition to examine the primary drivers of microbial community assembly processes.

Ecological and microbiological monitoring of soils in places of mass recreation

Introduction. There are presented results of a comprehensive ecological and microbiological assessment of soils located in the central part of the recreational zone of the city of Petrozavodsk, located in the middle taiga area. The study of chemical and microbiological properties of the soils of the park zone in the spatio-temporal aspect is of great importance for assessing the current state of soils and the trend of their development in conditions of anthropogenic impact, and can be the basis for urban ecological monitoring also. 
 The aim of the study is ecological and microbiological monitoring of soils in places of mass recreation of the urban population (Petrozavodsk).
 Materials and methods. The object of the study was the soils of the plots located in the central part of the city. The soils located on the territory of the Kivach Nature Reserve were selected as a control. The acid-base properties of soils, the content of heavy metals, as well as the state of the microbiotic component of soils were evaluated. Based on the data on the content of heavy metals, the degree of soil contamination with heavy metals was determined. 
 Results. Based on the data of a comprehensive study, the current state of the soils of the recreational zone of Petrozavodsk has been established. The comparative analysis of changes in chemical and microbiological properties, as well as data on the soil pollution coefficient in the space-time interval revealed a decrease in anthropogenic impact on soils. Changing the category of soil pollution is an important tool of environmental protection measures carried out on the territory of the city.
 Limitations. Work in the field of urban-ecological research is complicated by the lack of local regulatory documents that substantiate the hygienic standards for chemicals polluting the soil; limited monitoring points and work with mixed soil samples, which creates a problem of representativeness of the obtained data. 
 Conclusion. The favourable conditions for the formation of soils in the park zone affect on their soil properties, which generally meet the hygienic requirements imposed on them. The established higher indicators of the soil pollution coefficient in certain areas indicate a high anthropogenic pressure in the past, are the basis for continuing research, the need for periodic work, as well as expanding the range of soil indicators used for early diagnosis of their degradation.

THE QUALITY FACTOR IN THE DEVELOPMENT OF REGIONS AND LIVING CONDITIONS

Topicality. It is considered an indisputable factor that quality is one of the decisive factors of both any production activity and the development of any socio-economic system. Quality problems arise in almost all spheres and at all stages of human activity. Quality is the leading category of production, goods, services, works, etc. In the modern conditions of the widespread complication of life at all levels of the organization of the human community, the problems of a new understanding of the issues of the quality of development and life of a person and society as a whole, the formation of new methodologies for learning about the quality of development are actualized. This formulation of the problem is connected with the need to solve both scientific and practical tasks of improving the management of the quality of development and the quality of human life.Aim and tasks. The aim of this work is to pay attention to the issue of improving methodological and methodical approaches to understanding problems that are becoming more complicated and increasingly relevant, modern problems of the quality of development in the spatio-temporal aspect and improving the quality of life of the population of Ukraine.
 Materials and methods. Scientific articles, monographic publications, abstracts of dissertations served as materials for this study. The work used methods of content analysis, systems approach, in particular methods of parametric systems theory.
 Research results. In accordance with the tasks set, the article discusses one of the main problems of modern development - the problem of quality. Quality as a category of the theory of social progress is considered not only in the traditional representation of the quality of production, but also as a category of the theory of territorial development, in particular the quality of the development of regions and the quality of life of the population, which is conditioned. In the work, special attention is paid to the understanding of the quality of the development of the objects being studied from the standpoint of the parametric theory of systems, which uses the methodology of the "ternary description language" (TMD) of complex developing objects.
 Conclusion. The methodological and methodical approaches to the systematic presentation of the quality of development of regions and the quality of life of the population considered in the work determine some specific ways of solving the problems of survival in complex conflicts and crisis situations of modern development.

Towards a low-carbon economy: how does green credit affect carbon productivity?

As a financial instrument and a crucial component of the environmental governance system, the comprehensive impacts of green credit on both the economy and the environment remain unclear. This study examines Chinese provincial data from 2001 to 2018 and employs multiple models to assess the dynamic effects of green credit on carbon productivity. The findings indicate a significant positive influence of green credit on carbon productivity within local and surrounding areas. Furthermore, the promotion effect of green credit on carbon productivity is mainly through energy structure transformation, upgrading of industrial structure and green technology innovation. Interestingly, when considering the spatiotemporal aspect, we observe an initial marginal negative impact of green credit on carbon productivity, which subsequently transitions to a positive effect. The regions demonstrating the highest positive impacts of green credit are primarily concentrated in the southwestern region rich in renewable energy and the economically developed eastern coastal region.

A Multipath Model for Disturbance Propagation in Electrical Power Networks

This paper deals with the nature of propagation of disturbance spectrum through the power lines of an electric power system. A multi-path propagation model is proposed based on the reflection and refraction theory of wave propagation. The developed model captures the spatio-temporal aspect of disturbance propagation and is validated for a wide band of frequency. The proof of concept for the developed model is shown on a 2-bus system with a disturbance at a point between the buses. Results are validated in time domain with electromagnetic transient simulation programming.

ГИДРОЛОГИЧЕСКИЙ ПРОФИЛЬ ВОДОСБОРА БАССЕЙНА ТРАНСГРАНИЧНОЙ РЕКИ ШУ

An analysis of changes in the hydrological indicators of the catchment area of the transboundary Shu River basin in the spatio-temporal aspect, based on information and analytical materials from the hy-drological posts of Kochkarka, Orto-Tokai, Milyanfan, Tashotkol, the Furmanovs hydroelectric com-plex and Ulanbel in a long period of observations covering 1931…2020, shows the presence of their constant fluctuations over the years under the influence of natural and anthropogenic factors. The hy-drological regime of the catchment area of the transboundary Shu River basin on a spatio-temporal scale with a positive or negative trend in the average annual water discharge is determined by the gen-eral nature of natural factors and changes due to increased anthropogenic activity on river systems. The results obtained indicate that the influence of natural and anthropogenic factors are less pronounced in the mountainous and foothill geographic zones than in the foothill-plain and desert zones of the catch-ment area of the transboundary river Shu.

The Assessment of COVID-19 Vulnerability Risk for Crisis Management

The subject of this article is to determine COVID-19 vulnerability risk and its change over time in association with the state health care system, turnover, and transport to support the crisis management decision-making process. The aim was to determine the COVID-19 Vulnerability Index (CVI) based on the selected criteria. The risk assessment was carried out with methodology that includes the application of multicriteria analysis and spatiotemporal aspect of available data. Particularly the Spatial Multicriteria Analysis (SMCA) compliant with the Analytical Hierarchy Process (AHP), which incorporated selected population and environmental criteria were used to analyse the ongoing pandemic situation. The influence of combining several factors in the pandemic situation analysis was illustrated. Furthermore, the static and dynamic factors to COVID-19 vulnerability risk were determined to prevent and control the spread of COVID-19 at the early stage of the pandemic situation. As a result, areas with a certain level of risk in different periods of time were determined. Furthermore, the number of people exposed to COVID-19 vulnerability risk in time was presented. These results can support the decision-making process by showing the area where preventive actions should be considered.

Fast evaluation of pressure and saturation predictions with a deep learning surrogate flow model

Numerical models for flow through porous media are essential for forecasting subsurface fluid flow response to support optimal decision-making to develop subsurface resources such as groundwater, geothermal, and oil and gas. For reservoir engineering, numerical flow simulation modeling is applied to support and maximize well ultimate recovery and recoverable reserves to maximize project economics and safety while minimizing environmental impacts. Subsurface models explore subsurface uncertainty based on integrating geological, geophysical, petrophysical, and reservoir engineering data and expert interpretations.To evaluate uncertainty, we rely on multiple geostatistical subsurface heterogeneity realizations paired with flow simulation forecasts to test the sensitivity of various reservoir development parameters and build an uncertainty model of reservoir performance. However, with large reservoir models, numerical flow simulation time increases, leading to a significant amount of professional time and computational effort that increases project costs, and increases cycle times resulting in delay or diminished decision quality. This issue motivates the utilization of surrogate, computationally efficient approximative flow models. Current methods focus on prediction accuracy and minimizing prediction error. When uncertainty is significant, prediction accuracy is insufficient, and we must consider the entire uncertainty distribution.We propose a new and general workflow to generate accurate and precise machine learning-based surrogate flow models to predict the relationship between the reservoir rock and fluids, development parameters, and the reservoir flow simulation responses. We train a deep convolutional neural network using the results from a three-dimensional two-phase flow simulator. Next, we use the trained model to generate ensemble predictions from the flow surrogate to evaluate the uncertainty based on the development parameters and geological information.The machine learning-based surrogate model uses exhaustive subsurface predictor features, porosity, permeability, well position, and an engineered feature representing non-dimensional time as input to predict exhaustive subsurface response features, pressure, and saturation distribution over discrete time steps as the output. The proposed workflow integrates the spatiotemporal aspect of subsurface flow modeling. It allows the practitioner engineer to explore subsurface uncertainty without the entire computational cost of numerical flow simulation to support optimum, timely development decision-making.

Spatiotemporal Aspect and Meaning of the Brazier-Shaped Pottery Excavated from Wooden Chamber Tombs in Jin·Byeonhan region

노형토기는 대부광구호나 대부직구호와 함께 진·변한 후기와질토기의 주요 기종 중 하나로, 생활유구보다 주로 분묘에서 출토된다. 대부광부호나 대부직구호와는 달리 4세기를 즈음하여 도질의 노형기대로 변화하는 노형토기는 시간에 따라 크기가 분화되고, 부장량이 증가하면서 목곽묘 내 특정한 위치에 부장되는 등 후기와질토기의 다른 기종과는 출토맥락을 달리한다. 노형토기의 이러한 점은 진·변한에서 신라, 가야로의 전환을 설명해 줄 수 있을 것이라는 판단에서 이 글에서는 노형토기 부장양상에 대한 시·공적 의미를 해석해보았다. 분석 결과 노형토기는 중형에서 시간에 따라 대형과 소형으로 크기의 분화와 부장양의 증가가 있었다. 따라서 노형 토기의 크기와 부장량, 부장위치에 따른 부장유형은 목곽묘 구조와 상관관계를 보이면서 지역적 차이를 드러낸다. 단독곽에서는 중형의 노형토기, 주·부곽에서는 대, 중, 소형의 노형토기가 부장되며 목곽 내 여러 곳에 부장되는 등 부장양상은 시간에 따라 분화된 모습을 보이지만, 공시적으로는 지역색을 보여서 경주와 포항, 울산 그리고 부산과 김해 등 3개의 지역권 설정이 가능하게 되었다. 이 글에서는 노형토기의 부장양상에서 보이는 3세기대의 경주-포항, 울산, 부산-김해 세 지역권을 진·변한에서의 지역 간 분화로 해석하였다.

“The Tale of Igor's Campaign” in N. Gumilyov's lyrics of the later period

This research is dedicated to spatiotemporal aspect of “The Tale of Igor’s Campaign” in N. Gumilyov’s lyrics of later period. Based on the lyrical works written over the period from 1913 to 1921, the author contemplates on the role of the Old Russian epic for the poet’s ideology. A hypothesis advanced that the text of the tale is one of the most constructive in worldview of the poet. The article employs the comparative-historical and structural-semiotic methods (juxtaposition of semantics facts that go back to the text  of the “Tale of Igor’s Campaign” and contained in N. Gumilyov's poetry) for establishing correspondence or semantic changes of words in the original text. The method of parallel text search is applied. Textual analysis of the fragments of N. Gumilyov's works and “The Tale of Igor’s Campaign” is conducted. The article is first to determine and substantiate the interrelation between N. Gumilyov’s poem “War” (1914) and text of the “Tale of Igor’s Campaign”. Detailed analysis is given to the image of the “sowing” and “reaping” Russian warriors. In his later works, Gumilyov associates the “Tale of Igor’s Campaign” with the highest ethical values, history of Russian and world culture, which underlines the historicism of Gumilyov’s thinking. The article reveals the “horse”, “warrior”, “quiver”, “saber” contained in the text of the tale reflect the true life of N. Gumilyov.

Learn From the Rumors

The COVID-19 pandemic is an ongoing global pandemic, which has caused global social and economic disruption. In addition to physical illness, people have to endure the intrusion of rumors psychologically. Thus, it is critical to summarize the correlating infodemic, a significant part of COVID-19, to eventually defeat the epidemic. This article aims to mine the topic distribution and evolution patterns of online rumors by comparing and contrasting COVID-19 rumors from the two most popular rumor-refuting platforms—Jiaozhen in China and Full Fact in the United Kingdom (UK)—via a novel topic mining model, text clustering based on bidirectional encoder representations from transformers (BERT), and lifecycle theory. This comparison and contrast can enrich the research of infodemiology based on the spatio-temporal aspect, providing practical guidance for governments, rumor-refuting platforms, and individuals. The comparative study highlights the similarities and differences of online rumors about global public health emergencies across countries.

Effect mechanism of biochar application on soil structure and organic matter in semi-arid areas

There are global concerns regarding soil remediation and water conservation in arid and semi-arid areas. Studying the mechanism and factors influencing soil structure and organic matter content is very important for soil remediation and the rational utilization of water resources. We tracked the changes in soil aggregates and organic matter content during the growth period of maize using different application rates of straw biochar (10, 20, 30, and 50 t/ha) to investigate the effects of biochar on the structure of weakly alkaline soil. The results were as follows: 1) Biochar significantly increased the content of water-stable soil aggregates. The content of water-stable macroaggregates (≥0.25 mm) increased by 8.3–35.0%, and the increase was the highest (35%) when biochar was applied at a rate of 30 t/ha 2) After applying biochar, the content of air-dried aggregates on the surface layer increased by 112.6–168.5%. 3). Biochar increased the organic matter content to varying degrees from the spatiotemporal aspect. In terms of soil depth, organic matter content increased by 2.15–5.88 g/kg. The jointing stage, which the time demand for organic matter is the highest, organic matter content increased by 35.4% when biochar was applied at 50 t/ha 4) We established a three-dimensional surface correlation equation based on the synergistic relationships among biochar, water-stable aggregates, and organic matter content. The particle size of soil aggregates was the highest when the biochar application rate was 29.38 t/ha and the organic matter content increased by 25.7%. It provided evidence that applies to biochar has good potential for water-saving irrigation and soil remediation.

Spatio-Temporal Aspect of Suicide and Suicidal Ideation: An Application of SaTScan to Detect Hotspots in Four Major Cities of Tamil Nadu

Spatio-Temporal Aspect of Suicide and Suicidal Ideation: An Application of SaTScan to Detect Hotspots in Four Major Cities of Tamil Nadu

Coal mining as a factor of environmental risks in the development of the hunting sector in Industrial Regions

The matter of efficient utilization of natural resources has reached a fundamentally new level of significance in modern science and practice. The present research featured the effect of coal mining on the integrity of hunting grounds and the population of game species. The paper introduces the problem of methodological errors in wild fauna counting, which can lead to unreliable population data. Coal mining and coal utilization cause major environmental problems by producing serious and often irreversible impact on the terrestrial compartment. The study focused on the environmental risks to hunting grounds and their exposure to man-induced factors associated with industrial activities. The author performed a detailed analysis of the population and use of game species in the Kemerovo region (Kuzbass). The research featured two public hunting grounds of Mezhdurechensk urban district No.1 and Belovo municipal district No.1. The research demonstrated some dynamics in the local forest coverage and game population in the spatio-temporal aspect for a five-year period. The comparative analysis of the hunting resources in various economic zones of the Kemerovo region revealed no natural population decrease related to the increasing industrial presence.

Activation Strategies in Image-Guided Nanotherapeutic Delivery

Therapeutic nanomaterials serve as an important platform for drug delivery under image guidance. Despite significant growth and broad applications, their design specifics remain a subject of continued interest primarily due to multifunctional factors involved, ranging from nanomaterial properties, imaging modalities, and therapeutic agents to activation strategies. This review article summarizes key findings on their design characteristics with a particular interest in strategies developed for therapeutic activation (release). First, their activation can be controlled using either an endogenous factor including low pH and glutathione or an external stimulation by light, ultrasound, or electromagnetic field. The former is passively controlled from a spatiotemporal aspect compared to the latter, which is otherwise actively controlled through drug linker photolysis, nanomaterial disassembly, or gate opening. Second, light stimulation serves a most notable strategy due to its essential role in controlled drug release, photothermal activation (hyperthermia), and photodynamic production of reactive oxygen species (ROS). Third, some of those activation strategies that rely on ultrasound, photothermal, photoacoustic, magnetic field, or X-ray radiation are dually functional due to their role in imaging modalities. In summary, this review article presents recent advances and new insights that pertain to nanotherapeutic delivery systems. It also addresses their technical limitations associated with tissue penetration (light), spatial resolution (ultrasound, hyperthermia), and occurrence of cellular resistance (ROS).

Spatial data systems support for the internet of things

The Internet of Things (IoT) has recently received significant attention. An IoT device may possess an array of sensors that for example monitors the air temperature, carbon monoxide level, wifi signals, and sound intensity. IoT data is initially created on the device, then sent over to a central database system (e.g., the cloud) that organizes and prepares such data for the ongoing use by myriad applications, which include but are not limited to smart home, smart city, the industrial internet, connected cars, and connected health. Data generated by IoT devices is inherently spatial and temporal. For instance, an audio signal represents the variation of the sound intensity (retrieved by a sound sensor) over the time dimension. Furthermore, IoT devices are either installed in a static location (e.g., a building, a traffic intersection) or can be attached to moving objects such as a connected vehicle or a wearable device. In this article, we argue that existing IoT data systems do not properly consider the SpatioTemporal aspect of such data. Hence, the article represents a call for action to the SIGSPATIAL community in order to conduct research on building systems and applications that treat both the spatial and temporal dimensions of IoT data as first class citizens.

Análisis de indicadores ambientales espacio-temporales de agua, suelo y vegetación

Los indicadores ambientales son de suma importancia porque proveen información cuantitativa y cualitativa para evaluar el uso, disponibilidad y alteración de los recursos naturales. El presente ensayo tuvo como objetivo revisar del año 2006 a 2018 indicadores ambientales con un enfoque espacial y temporal, utilizados para evaluar la condición del ambiente. Posteriormente, se clasificó la información consultada en tres grupos principales de indicadores de agua, suelo y vegetación. Después se determinó las potencialidades de los diferentes métodos de indicadores ambientales, dentro de estos hallazgos relevantes se observó que cada metodología depende de la calidad de la información y de los objetivos de cada estudio. Dentro de las metodologías analizadas las de mayor relevancia por la precisión de sus resultados obtenidos, fueron los índices de vegetación y análisis multicriterio, ya que permite percibir explícitamente los parámetros de la zona que han sido modificados por actividades humanas. Se concluye que las metodologías de indicadores ambientales dependen del aspecto espacio-temporales y la calidad de los datos, así como del recurso natural a evaluar.

Action Recognition With Spatio–Temporal Visual Attention on Skeleton Image Sequences

Action recognition with 3D skeleton sequences is becoming popular due to its speed and robustness. The recently proposed Convolutional Neural Networks (CNN) based methods have shown good performance in learning spatio-temporal representations for skeleton sequences. Despite the good recognition accuracy achieved by previous CNN based methods, there exist two problems that potentially limit the performance. First, previous skeleton representations are generated by chaining joints with a fixed order. The corresponding semantic meaning is unclear and the structural information among the joints is lost. Second, previous models do not have an ability to focus on informative joints. The attention mechanism is important for skeleton based action recognition because there exist spatio-temporal key stages while the joint predictions can be inaccurate. To solve these two problems, we propose a novel CNN based method for skeleton based action recognition. We first redesign the skeleton representations with a depth-first tree traversal order, which enhances the semantic meaning of skeleton images and better preserves the associated structural information. We then propose the idea of a two-branch attention architecture that focuses on spatio-temporal key stages and filters out unreliable joint predictions. A base attention model with the simplest structure is first introduced. By improving the structures in both branches, we further propose a Global Long-sequence Attention Network (GLAN). Furthermore, in order to adjust the kernel's spatio-temporal aspect ratios and better capture long term dependencies, we propose a Sub-Sequence Attention Network (SSAN) that takes sub-image sequences as inputs. Our experiment results on NTU RGB+D and SBU Kinetic Interaction outperforms the state-of-the-art. The model is further validated on noisy estimated poses from UCF101 and Kinetics.

A System of Mining Semantic Trajectory Patterns from GPS Data of Real Users

Positioning devices allow users’ movement to be recorded. The GPS (Global Positioning System) trajectory data typically consists of spatiotemporal points, which make up the major part of the big data concerning urban life. Existing knowledge extraction methods about the trajectory share a general limitation—they only investigate data from a spatiotemporal aspect, but fail to take the semantic information of trajectories into consideration. Therefore, extracting the semantic information of trajectories with the context of big data is challenging pattern recognition task that has practical application prospects. In this paper, a system is proposed to extract the semantic trajectory patterns of positioning device users. Firstly, a spatiotemporal threshold and clustering based pre-processing model is proposed to process the raw data. Then, we design a probabilistic generative model to annotate the semantic information of each trajectory after the pre-processing procedure. Finally, we apply the PrefixSpan algorithm to mine the semantic trajectory patterns. We verify our system on a large dataset of users’ real trajectories over a period of 5 years in Beijing, China. The results of the experiment indicate that our system produces meaningful patterns.

Automatic moving foreground extraction using random walks

<p>In this paper, we propose a novel approach for automatic foreground extraction in video frames by analyzing the spatiotemporal aspect. We divide our contribution to tree steps: Automatic seeds detection, formulating the energy function, and using the random walk algorithm to minimize this function. First, we detect seeds by extracting a sparse of good features to track in the current frame and compute the difference between those pixels and its adjacent in the previous frame, the difference of pixels is treated in HSV color space to make the result more accurate, we thresholds this difference, and we classify moving and stationary pixels. Secondly, we formulate our foreground extraction as a graph based problem, then we define an energy function to evaluate spatiotemporal smoothness. Finally, we applied the random walk algorithm with seeds detected in the first step to minimize the energy function problem, the solution leads to evaluate the potential that every pixel in the video sequences is marked in motion or a stationary pixel. We suggest that our unsupervised method has the potential to be used for many kinds of motion detection and real-time video.</p>