Search results for: Spatio-temporal analysis

Authors: Ankan Roy, Niharika, Samir Kumar Patra

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Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.

Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions

Procedia PDF Downloads 134

Authors: Krešimir Begović, Miloš Rydval, Jan Tumajer, Kristyna Svobodová, Thomas Langbehn, Yumei Jiang, Vojtech Čada, Vaclav Treml, Ryszard Kaczka, Miroslav Svoboda

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Environmental changes have increased the frequency and intensity of climatic extremes, particularly hotter droughts, leading to altered tree growth patterns and multi-year lags in tree recovery. The effects of shifting climatic conditions on tree growth are inhomogeneous across species’ natural distribution ranges, with large spatial heterogeneity and inter-population variability, but generally have significant consequences for contemporary forest dynamics and future ecosystem functioning. Despite numerous studies on the impacts of regional drought effects, large uncertainties remain regarding the mechanistic basis of drought legacy effects on wood formation and the ability of individual species to cope with increasingly drier growing conditions and rising year-to-year climatic variability. To unravel the complexity of climate-growth interactions and assess species-specific responses to severe droughts, we combined forward modeling of tree growth (VS-lite model) with correlation analyses against climate (temperature, precipitation, and the SPEI-3 moisture index) and growth responses to extreme drought events from multiple tree-ring parameters (tree-width and blue intensity parameters). We used an extensive dataset with over 1000 tree-ring samples from 23 nature forest reserves across an altitudinal range in Czechia and Slovakia. Our results revealed substantial spatiotemporal variability in growth responses to summer season temperature and moisture availability across species and tree-ring parameters. However, a general trend of increasing spring moisture-growth sensitivity in recent decades was observed in the Scots pine mountain forests and lowland forests of both species. The VS-lite model effectively captured nonstationary climate-growth relationships and accurately estimated high-frequency growth variability, indicating a significant incidence of regional drought events and growth reductions. Notably, growth reductions during extreme drought years and discrete legacy effects identified in individual wood components were most pronounced in the lowland forests. Together with the observed growth declines in recent decades, these findings suggest an increasing vulnerability of Norway spruce and Scots pine in dry lowlands under intensifying climatic constraints.

Keywords: dendroclimatology, Vaganova–Shashkin lite, conifers, central Europe, drought, blue intensity

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Authors: Md. Jahoor Alam

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Recent studies suggest that Glucose controls several lifesaving pathways. Glucose molecule is reported to be responsible for the production of ROS (reactive oxygen species). In the present work, a p53-MDM2-Glucose model is developed in order to study spatiotemporal properties of the p53 pathway. The systematic model is mathematically described. The model is numerically simulated using high computational facility. It is observed that the variation in glucose concentration level triggers the system at different states, namely, oscillation death (stabilized), sustain and damped oscillations which correspond to various cellular states. The transition of these states induced by glucose is phase transition-like behaviour. Further, the amplitude of p53 dynamics with the variation of glucose concentration level follows power law behaviour, As(k) ~ kϒ, where, ϒ is a constant. Further Stochastic approach is needed for understanding of realistic behaviour of the model. The present model predicts the variation of p53 states under the influence of glucose molecule which is also supported by experimental facts reported by various research articles.

Keywords: oscillation, temporal behavior, p53, glucose

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Authors: Weishou Shen, Chunyan Yang, Zhongliang Li

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The crop climate productivity and the distribution of cropland reflect long-term adaption of agriculture to climate. In order to fully understand the impact of climate change on cropland ecosystem in Tibet, the spatiotemporal changes of crop climate productivity and cropland distribution were analyzed with the help of GIS and RS software. Results indicated that the climate change to the direction of wet and warm in Tibet in the recent 30 years, with a rate of 0.79℃/10 yr and 23.28 mm/10yr respectively. Correspondingly, the climate productivity increased gradually, with a rate of 346.3kg/(hm2•10a), of which, the fastest-growing rate of the crop climate productivity is in Southern Tibet Mountain- plain-valley. During the study period, the total cropland area increased from 32.54 million ha to 37.13 million ha, and cropland has expanded to higher altitude area and northward. Overall, increased cropland area and crop climate productivity due to climate change plays a positive role for agriculture in Tibet.

Keywords: climate change, productivity, cropland area, Tibet plateau

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Authors: Said Ettaieb, Kamel Hamrouni, Su Ruan

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This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

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Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

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Authors: Chiang Wei, Hui-Chung Yeh, Yen-Chang Chen

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The objective of this study is to estimate the rainfall using the new generation Himawari-8 meteorological satellite with multi-band, high-bit format, and high spatiotemporal resolution, ground rainfall data at the Chen-Yu-Lan watershed of Joushuei River Basin (443.6 square kilometers) in Central Taiwan. Accurate and fine-scale rainfall information is essential for rugged terrain with high local variation for early warning of flood, landslide, and debris flow disasters. 10-minute and 2 km pixel-based rainfall of Typhoon Megi of 2016 and meiyu on June 1-4 of 2017 were tested to demonstrate the new generation Himawari-8 meteorological satellite can capture rainfall variation in the rugged mountainous area both at fine-scale and watershed scale. The results provide the valuable rainfall information for early warning of future disasters.

Keywords: estimation, Himawari-8, rainfall, satellite imagery

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: Shah Fahad

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Managing the Urban Heat Island (UHI) effects is a pressing concern for achieving sustainable urban development and ensuring thermal comfort in major cities of developing nations, such as Lahore, Pakistan. The current UHI effect is mostly triggered by climate change and rapid urbanization. This study explored UHI over the Lahore district and its adjoining urban and rural-urban fringe areas. Landsat satellite data was utilized to investigate spatiotemporal patterns of Land Use and Land Cover changes (LULC), Land Surface Temperature (LST), UHI, Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and Urban Thermal Field Variance Index (UTFVI). The built-up area increased very fast, with a coverage of 22.99% in 2000, 36.06% in 2010, and 47.17% in 2020, while vegetation covered 53.21 % in 2000 and 46.16 % in 2020. It also revealed a significant increase in the mean LST, from 33°C in 2000 to 34.8°C in 2020. The results indicated a significantly positive correlation between LST and NDBI, a weak correlation was also observed between LST and NDVI. The study used scatterplots to show the correlation between NDBI and NDVI with LST, results revealed that the NDBI and LST had an R² value of 0.6831 in 2000 and 0.06541 in 2022, while NDVI and LST had an R² value of 0.0235 in 1998 and 0.0295 in 2022. Proper environmental planning is vital in specific locations to enhance quality of life, protect the ecosystem, and mitigate climate change impacts.

Keywords: land use land cover, spatio-temporal analysis, remote sensing, land surface temperature, urban heat island, lahore pakistan

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Authors: Shai Gabay

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The tunnel effect describes the phenomenon where a moving object seems to persist even when temporarily hidden from view. Numerous studies indicate that humans, infants, and nonhuman primates possess object persistence, relying on spatiotemporal cues to track objects that are dynamically occluded. While this ability is associated with neural activity in the cerebral neocortex of humans and mammals, the role of subcortical mechanisms remains ambiguous. In our current investigation, we explore the functional contribution of monocular aspects of the visual system, predominantly subcortical, to the representation of occluded objects. This is achieved by manipulating whether the reappearance of an object occurs in the same or different eye from its disappearance. Additionally, we employ Archerfish, renowned for their precision in dislodging insect prey with water jets, as a phylogenetic model to probe the evolutionary origins of the tunnel effect. Our findings reveal the active involvement of subcortical structures in the mental representation of occluded objects, a process evident even in species that do not possess cortical tissue.

Keywords: archerfish, tunnel effect, mental representations, monocular channels, subcortical structures

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Authors: Chiqian Zhang, Kyle D. McIntosh, Nathan Sienkiewicz, Ian Struewing, Erin A. Stelzer, Jennifer L. Graham, Jingrang Lu

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Phytoplankton plays an essential role in freshwater aquatic ecosystems and is the primary group synthesizing organic carbon and providing food sources or energy to ecosystems. Therefore, the identification and quantification of phytoplankton are important for estimating and assessing ecosystem productivity (carbon fixation), water quality, and eutrophication. Microscopy is the current gold standard for identifying and quantifying phytoplankton composition and abundance. However, microscopic analysis of phytoplankton is time-consuming, has a low sample throughput, and requires deep knowledge and rich experience in microbial morphology to implement. To improve this situation, quantitative polymerase chain reaction (qPCR) was considered for phytoplankton identification and quantification. Using qPCR to assess phytoplankton composition and abundance, however, has not been comprehensively evaluated. This study focused on: 1) conducting a comprehensive performance comparison of qPCR and microscopy techniques in identifying and quantifying phytoplankton and 2) examining the use of qPCR as a tool for assessing eutrophication. Twelve large rivers located throughout the United States were evaluated using data collected from 2017 to 2019 to understand the relation between qPCR-based phytoplankton abundance and eutrophication. This study revealed that temporal variation of phytoplankton abundance in the twelve rivers was limited within years (from late spring to late fall) and among different years (2017, 2018, and 2019). Midcontinent rivers had moderately greater phytoplankton abundance than eastern and western rivers, presumably because midcontinent rivers were more eutrophic. The study also showed that qPCR- and microscope-determined phytoplankton abundance had a significant positive linear correlation (adjusted R² 0.772, p-value < 0.001). In addition, phytoplankton abundance assessed via qPCR showed promise as an indicator of the eutrophication status of those rivers, with oligotrophic rivers having low phytoplankton abundance and eutrophic rivers having (relatively) high phytoplankton abundance. This study demonstrated that qPCR could serve as an alternative tool to traditional microscopy for phytoplankton quantification and eutrophication assessment in freshwater rivers.

Keywords: phytoplankton, eutrophication, river, qPCR, microscopy, spatiotemporal variation

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Authors: Artur Krukowski, Emmanouela Vogiatzaki

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The article presents an ongoing work in research projects such as SCAN4RECO or ARCH, both funded by the European Commission under Horizon 2020 program. The former one concerns multimodal and multispectral scanning of Cultural Heritage assets for their digitization and conservation via spatiotemporal reconstruction and 3D printing, while the latter one aims to better preserve areas of cultural heritage from hazards and risks. It co-creates tools that would help pilot cities to save cultural heritage from the effects of climate change. It develops a disaster risk management framework for assessing and improving the resilience of historic areas to climate change and natural hazards. Tools and methodologies are designed for local authorities and practitioners, urban population, as well as national and international expert communities, aiding authorities in knowledge-aware decision making. In this article we focus on 3D modelling of object geometry using primarily photogrammetric methods to achieve very high model accuracy using consumer types of devices, attractive both to professions and hobbyists alike.

Keywords: 3D modelling, UAS, cultural heritage, preservation

Procedia PDF Downloads 127

Authors: Ibrahim A. Adeniran, Rui F. Zhu, Man S. Wong

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Owing to the insufficiency in the spatial representativeness and continuity of in situ temperature measurements from weather stations (WS), the use of temperature measurement from WS for large-range diurnal analysis in heterogenous landscapes has been limited. This has made the accurate estimation of land surface temperature (LST) from remotely sensed data more crucial. Moreover, the study of dynamic interaction between the atmosphere and the physical surface of the Earth could be enhanced at both annual and diurnal scales by using optimal LST data derived from satellite sensors. The tradeoff between the spatial and temporal resolution of LSTs from satellite’s thermal infrared sensors (TIRS) has, however, been a major challenge, especially when high spatiotemporal LST data are recommended. It is well-known from existing literature that polar satellites have the advantage of high spatial resolution, while geostationary satellites have a high temporal resolution. Hence, this study is aimed at designing a framework for the cross-comparison of LST data from polar and geostationary satellites in a heterogeneous landscape. This could help to understand the relationship between the LST estimates from the two satellites and, consequently, their integration in diurnal LST analysis. Landsat-8 satellite data will be used as the representative of the polar satellite due to the availability of its long-term series, while the Himawari-8 satellite will be used as the data source for the geostationary satellite because of its improved TIRS. For the study area, Hong Kong Special Administrative Region (HK SAR) will be selected; this is due to the heterogeneity in the landscape of the region. LST data will be retrieved from both satellites using the Split window algorithm (SWA), and the resulting data will be validated by comparing satellite-derived LST data with temperature data from automatic WS in HK SAR. The LST data from the satellite data will then be separated based on the land use classification in HK SAR using the Global Land Cover by National Mapping Organization version3 (GLCNMO 2013) data. The relationship between LST data from Landsat-8 and Himawari-8 will then be investigated based on the land-use class and over different seasons of the year in order to account for seasonal variation in their relationship. The resulting relationship will be spatially and statistically analyzed and graphically visualized for detailed interpretation. Findings from this study will reveal the relationship between the two satellite data based on the land use classification within the study area and the seasons of the year. While the information provided by this study will help in the optimal combination of LST data from Polar (Landsat-8) and geostationary (Himawari-8) satellites, it will also serve as a roadmap in the annual and diurnal urban heat (UHI) analysis in Hong Kong SAR.

Keywords: automatic weather station, Himawari-8, Landsat-8, land surface temperature, land use classification, split window algorithm, urban heat island

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Authors: Zenebu Adere Tola

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Informal settlements behave dynamically over space and time and the number of people living in such housing areas is growing worldwide. In the cities of developing countries especially in sub-Saharan Africa, poverty, unemployment rate, poor living condition, lack transparency and accountability, lack of good governance are the major factors to contribute for the people to hold land informally and built houses for residential or other purposes. In most of Ethiopian cities informal settlement is highly seen in peripheral areas this is because people can easily to hold land for housing from local farmers, brokers, speculators without permission from concerning bodies. In Adama informal settlement has created risky living conditions and led to environmental problems in natural areas the main reason for this was the lack of sufficient knowledge about informal settlement development. On the other side there is a strong need to transform informal into formal settlements and to gain more control about the actual spatial development of informal settlements. In another hand to tackle the issue it is at least very important to understand the scale of the problem. To understand the scale of the problem it is important to use up-to-date technology. For this specific problem, it is good to use high-resolution imagery to detect informal settlement in Adama city. The main objective of this study is to assess the spatiotemporal dynamics and environmental impacts of informal settlement using OBIA. Specifically, the objective of this study is to; identify informal settlement in the study area, determine the change in the extent and pattern of informal settlement and to assess the environmental and social impacts of informal settlement in the study area. The methods to be used to detect the informal settlement is object-oriented image analysis. Consequently, reliable procedures for detecting the spatial behavior of informal settlements are required in order to react at an early stage to changing housing situations. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning. Using data for this study aerial photography for growth and change of informal settlements in Adama city. Software ECognition software for classy to built-up and non-built areas. Thus, obtaining spatial information about informal settlement areas which is up to date is vital for any actions of enhancement in terms of urban or regional planning.

Keywords: informal settlement, change detection, environmental impact, object based analysis

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Authors: Francisco Miroslav Ulloa-Stanojlovic, Gina Polo, Ricardo Augusto Dias

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In Brazil, there is a high incidence of rabies in herbivores of economic interest (HEI) transmitted by the common vampire bat Desmodus rotundus, the presence of human rabies cases and the huge economic losses in the world's largest cattle industry, it is important to assist the National Program for Control of Rabies in herbivores in Brazil, that aims to reduce the incidence of rabies in HEI populations, mainly through epidemiological surveillance, vaccination of herbivores and control of vampire-bat roosts. Material and Methods: A spatiotemporal retrospective Kulldorff's spatial scan statistic based on a Poisson model and Monte Carlo simulation and an Anselin's Local Moran's I statistic were used to uncover spatial clustering of HEI rabies from 2000 – 2014. Results: Were identify three important clusters with significant year-to-year variation (Figure 1). In 2000, was identified one area of clustering in the North region, specifically in the State of Tocantins. Between the year 2000 and 2004, a cluster centered in the Midwest and Southeast region including the States of Goiás, Minas Gerais, Rio de Janeiro, Espirito Santo and São Paulo was prominent. And finally between 2000 and 2005 was found an important cluster in the North, Midwest and South region. Conclusions: The HEI rabies is endemic in the country, in addition, appears to be significant differences among the States according to their surveillance services, that may be difficulting the control of the disease, also other factors could be influencing in the maintenance of this problem like the lack of information of vampire-bat roosts identification, and limited human resources for realization of field monitoring. A review of the program control by the authorities it’s necessary.

Keywords: Brazil, Desmodus rotundus, herbivores, rabies

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Authors: Ella Sèdé Maforikan

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Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Yu Bingqing

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Research on the meteorological observation data of conventional meteorological stations in Jiangnan area from 2001 to 2020 and digital elevation DEM, the "golden section" comfort index calculation method was used to refine the spatial estimation of climate comfort in Jiangnan area under undulating terrain on the Gis platform, and its spatiotemporal distribution characteristics in the region were analyzed. The results can provide reference for the development and utilization of climate resources in Jiangnan area.The results show that: ① there is a significant spatial difference between winter and summer climate comfort from low latitude to high latitude. ②There is a significant trend of decreasing climate comfort from low altitude to high altitude in winter, but the opposite is true in summer. ③There is a trend of decreasing climate comfort from offshore to inland in winter, but the difference is not significant in summer. The climate comfort level in the natural lake area is higher in summer than in the surrounding areas, but not in winter. ⑤ In winter and summer, altitude has the greatest influence on the difference in comfort level.

Keywords: vernacular courtyards, thermal environment, depth-to-height ratio, climate adaptability，Southeast China

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Authors: Parisa Mansour

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Understanding how vision works in both health and disease involves understanding the anatomy and physiology of the eye as well as the neural pathways involved in visual perception. The development of imaging techniques for the visual system is essential for understanding the neural foundation of visual function or impairment. MRI provides a way to examine neural circuit structure and function without invasive procedures, allowing for the detection of brain tissue abnormalities in real time. One of the advanced MRI methods is manganese-enhanced MRI (MEMRI), which utilizes active manganese contrast agents to enhance brain tissue signals in T1-weighted imaging, showcasing connectivity and activity levels. The way manganese ions build up in the eye, and visual pathways can be due to their spread throughout the body or by moving locally along axons in a forward direction and entering neurons through calcium channels that are voltage-gated. The paramagnetic manganese contrast is utilized in MRI for various applications in the visual system, such as imaging neurodevelopment and evaluating neurodegeneration, neuroplasticity, neuroprotection, and neuroregeneration. In this assessment, we outline four key areas of scientific research where MEMRI can play a crucial role - understanding brain structure, mapping nerve pathways, monitoring nerve cell function, and distinguishing between different types of glial cell activity. We discuss various studies that have utilized MEMRI to investigate the visual system, including delivery methods, spatiotemporal features, and biophysical analysis. Based on this literature, we have pinpointed key issues in the field related to toxicity, as well as sensitivity and specificity of manganese enhancement. We will also examine the drawbacks and other options to MEMRI that could offer new possibilities for future exploration.

Keywords: glial activity, manganese-enhanced magnetic resonance imaging, neuroarchitecture, neuronal activity, neuronal tract tracing, visual pathway, eye

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Authors: Ainoa Guinart, Maria Korpidou, Daniel Doellerer, Cornelia Palivan, Ben L. Feringa

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Stimuli responsive systems arise from the need to meet unsolved needs of current molecular drugs. Our study presents the design of a delivery system with high spatiotemporal control and tuneable release profiles. We study the incorporation of a hydrophobic synthetic molecular motor into PDMS-b-PMOXA block copolymer vesicles to create a self-assembled system. We prove their successful incorporation and selective activation by low powered visible light (λ 430 nm, 6.9 mW). We trigger the release of a fluorescent dye with high release efficiencies over sequential cycles (up to 75%) with the ability to turn on and off the release behaviour on demand by light irradiation. Low concentrations of photo-responsive units are proven to trigger release down to 1 mol% of molecular motor. Finally, we test our system in relevant physiological conditions using a lung cancer cell line and the encapsulation of an approved drug. Similar levels of cell viability are observed compared to the free-given drugshowing the potential of our platform to deliver functional drugs on demand with the same efficiency and lower toxicity.

Keywords: molecular motor, polymer, drug delivery, light-responsive, cancer, selfassembly

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Authors: Ragini Verma, J. Ponmozhi

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The oral cavity is home to a wide variety of microorganisms that lead to various diseases and even oral cancer. Despite advancements in the diagnosis and detection at the initial phase, the situation hasn’t improved much. Saliva-on-a-chip is an innovative point-of-care platform for early diagnosis of oral cancer and other oral diseases in live and dead cells using a microfluidic device with a current perspective. Some of the major challenges, like real-time imaging of the oral cancer microbes, high throughput values, obtaining a high spatiotemporal resolution, etc. were faced by the scientific community. Integrated microfluidics and microscopy provide powerful approaches to studying the dynamics of oral pathology, microbe interaction, and the oral microenvironment. Here we have developed a saliva-on-chip (salivary microbes) device to monitor the effect on oral cancer. Adhesion of cancer-causing F. nucleatum; subsp. Nucleatum and Prevotella intermedia in the device was observed. We also observed a significant reduction in the oral cancer growth rate when mortality and morbidity were induced. These results show that this approach has the potential to transform the oral cancer and early diagnosis study.

Keywords: microfluidic device, oral cancer microbes, early diagnosis, saliva-on-chip

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

Procedia PDF Downloads 177

Authors: Nawel Ganaoui, Chadli Souhila, Gahdab Chakal

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This study presents the results of a comparative research aiming to examine the distribution of beetles in four agroecosystems in the Tiaret region, located in northwestern Algeria, during the year 2023. This study was initiated across 04 stations that were randomly distributed within the Ksar Chellala region and selected based on their plant composition. The sampling method used was based on pitfall traps, which were filled two-thirds with a solution of saltwater supplemented with vinegar. In total, 40 species of beetles belonging to 9 families were identified. Among them, tenebrionids were the most abundant group (43%), followed by scarab beetles (30%) The comparison between the four types of agroecosystems - olive culture, sheep farming, cereal cultivation, and Pomegranate cultivation- in this region revealed that cereal cultivation harbored the greatest species diversity (30 species), followed by the sheep farming site (32 species), and then the other sites based on their ecological importance and trophic interactions, these beetle species were mainly categorized as coprophages, phytophages, and predators. The spatiotemporal evolution of beetle activity highlighted peaks of rich-ness and abundance, mainly during the dry period (from April to May), while the cold period (January) showed the low-est levels. The specific diversity of beetles varied significantly from one habitat to another.

Keywords: agroecosystem, beetle, entomology, steppe regoin

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Authors: S. Benessam, T. H. Debieche, S. Amiour, A. Chine, S. Khelili

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Iron is naturally present in groundwater, it comes from the dissolution of the geological formations (clay, schist, mica-schist, gneiss…). Its chemical form and mobility in water are controlled mainly by two physicochemical parameters (Eh and pH). In order to determine its spatiotemporal evolution in groundwater, a two-monthly monitoring of the physicochemical parameters and major elements in the water of the alluvial sheet of Nil river (North-eastern Algerian) was carried out during the period from November 2013 to January 2015. The results show that iron is present in weak concentrations in the upstream part of the alluvial sheet and with raised concentrations, which can exceed the standard of potable drinking water (0.2 mg/L), in the central and downstream parts of the alluvial sheet. This variation of the concentrations is related to the important variation of Eh between the upstream part (200 mV) where the aquiver is unconfined (oxidizing medium) and the central and downstream parts (-100 mV) where the aquifer is confined (reducing medium). Iron in the oxidizing part is presented with the complexes form, where it precipitates or/and adsorbed by the geological formations. On the other hand in the reducing parts, it is released in water. In this study, one will discuss also the mobility and the chemical forms of iron according to the rains and pumping.

Keywords: groundwater, iron, mobility, speciation

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Authors: Azadeh Jafari, Mohammad Taghi Karimi, Azadeh Nadi

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Background: Scoliosis is the lateral curvature of the spine which may influence the abilities of the subjects during standing and walking. Most of the scoliotic subjects use orthosis to reduce the curve and to decrease the risk of curve progression. There was lack of information regarding the effects of orthosis on kinematic and joint contact force. Therefore, this research was done to highlight the effects of orthosis on the aforementioned parameters. Method: 5 scoliotic subjects were recruited in this study, with single curve less than 40 (females with age 13.2 ± 1.7). They were asked to walk with and without orthosis. The kinematic of the joints, force applied on the legs, moments transmitted through the joints and joint contact forces were evaluated in this study. Moreover, the lengths of muscles were determined by use of computer muscle control approach in OpenSim. Results: There was a significant difference between the second peak of vertical ground reaction force while walking with and without orthosis (p-value < 0.05). There was no difference between spatiotemporal gait parameters while walking with and without orthosis (P-value > 0.05). The mean values of joint contact forces (vertical component) increased by the use of orthosis, but the difference was not significant (p-value > 0.05). Conclusion: Although the kinematic of most of the body joints was not influenced by the use of orthosis, the joint contact force may be increased by orthosis. The increase in joint contact force may be due to the performance of orthosis which restricts the motions of pelvic and increases compensatory mechanism used by the subjects to decrease the side effects of the orthosis.

Keywords: scoliosis, joint contact force, kinetic, kinematic

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Authors: Moschos Vogiatzis, K. Perakis

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Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: classification, land use/land cover, mapping, random forest

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Authors: Gurjeet Singh, Rabindra K. Panda

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Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

Procedia PDF Downloads 278

Authors: Prabal Singh Verma

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Electrostatic Waves in plasma have emerged as a new source for the acceleration of charged particles. The accelerated particles have a wide range of applications, for example in cancer therapy to cutting and melting of hard materials. The maximum acceleration can only be achieved when the amplitude of the plasma wave stays below a critical limit known as wave-breaking amplitude. Beyond this limit amplitude of the wave diminishes dramatically as the coherent energy of the wave starts to convert into random kinetic energy. In this work, spatiotemporal evolution of non-relativistic electrostatic waves in a cold plasma has been studied in the wave-breaking regime using a 1D particle-in-cell simulation (PIC). It is found that plasma gets heated after the wave-breaking but a fraction of initial energy always remains with the remnant wave in the form of Bernstein-Greene-Kruskal (BGK) mode in warm plasma. Another interesting finding of this work is that the frequency of the resultant BGK wave is found be below electron plasma frequency which decreases with increasing initial amplitude and the acceleration mechanism after the wave-breaking is also found to be different from the previous work. In order to explain the results observed in the numerical experiments, a simplified theoretical model is constructed which exhibits a good agreement with the simulation. In conclusion, it is shown in this work that electrostatic waves get shower after the wave-breaking and a fraction of initial coherent energy always remains with remnant wave. These investigations have direct relevance in wakefield acceleration experiments.

Keywords: nonlinear plasma waves, longitudinal, wave-breaking, wake-field acceleration

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Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Sinwook Park, Gilad Yossifon

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The presence of a floating electrode array located within the depletion layer formed due to concentration-polarization (CP) across a microchannel-membrane device, produces not only induced-charge electro-osmosis (ICEO) vortex and but also a bipolar current resulting from faradaic reactions. It has been shown that there exists an optimal SiO2 layer thickness of ~50nm which is sufficient to suppress bipolar currents (at least up to 5V applied voltage) but still enables ICEO vortices that stir the depletion layer, thereby affecting its I-V response. This effect is pronounced beyond the limiting current where the existence of the depletion layer results in increased local electric field due to decreased solution conductivity. This comprehensive study of the interaction of embedded electrodes with the induced CP in microchannel-perm selective medium systems, allows one to choose the thickness of the thin dielectric coating to either enhance the mixing as a means to control the diffuse layer, or suppress it, for example, in the case where electrodes are intended for local measurements of the solution conductivity with minimal invasion. In addition, the use of alternating-current electro-osmosis by activating electrodes results in further enhancement of the fluid stirring and opens new routes for on-demand spatiotemporal control of the CP length. In addition, the use of embedded heaters within the depletion layer generates electro-thermal vortices that in turn also control the CP length.

Keywords: AC electrokinetics, microchannel, concentration-polarization, bipolar current

Procedia PDF Downloads 500