Search results for: geo spatial database

Authors: Leo Nnamdi Ozurumba-Dwight

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Messenger ribooxynucleic acid (mRNA) molecules are compositional, protein-based. These proteins, encoding mRNA molecules (which collectively connote the transcriptome), when analyzed by RNA sequencing (RNAseq), unveils the nature of gene expression in the RNA. The obtained gene expression provides clues of cellular traits and their dynamics in presentations. These can be studied in relation to function and responses. RNAseq is a practical concept in Genomics as it enables detection and quantitative analysis of mRNA molecules. Single cell and spatial transcriptomics both present varying avenues for expositions in genomic characteristics of single cells and pooled cells in disease conditions such as cancer, auto-immune diseases, hematopoietic based diseases, among others, from investigated biological tissue samples. Single cell transcriptomics helps conduct a direct assessment of each building unit of tissues (the cell) during diagnosis and molecular gene expressional studies. A typical technique to achieve this is through the use of a single-cell RNA sequencer (scRNAseq), which helps in conducting high throughput genomic expressional studies. However, this technique generates expressional gene data for several cells which lack presentations on the cells’ positional coordinates within the tissue. As science is developmental, the use of complimentary pre-established tissue reference maps using molecular and bioinformatics techniques has innovatively sprung-forth and is now used to resolve this set back to produce both levels of data in one shot of scRNAseq analysis. This is an emerging conceptual approach in methodology for integrative and progressively dependable transcriptomics analysis. This can support in-situ fashioned analysis for better understanding of tissue functional organization, unveil new biomarkers for early-stage detection of diseases, biomarkers for therapeutic targets in drug development, and exposit nature of cell-to-cell interactions. Also, these are vital genomic signatures and characterizations of clinical applications. Over the past decades, RNAseq has generated a wide array of information that is igniting bespoke breakthroughs and innovations in Biomedicine. On the other side, spatial transcriptomics is tissue level based and utilized to study biological specimens having heterogeneous features. It exposits the gross identity of investigated mammalian tissues, which can then be used to study cell differentiation, track cell line trajectory patterns and behavior, and regulatory homeostasis in disease states. Also, it requires referenced positional analysis to make up of genomic signatures that will be sassed from the single cells in the tissue sample. Given these two presented approaches to RNA transcriptomics study in varying quantities of cell lines, with avenues for appropriate resolutions, both approaches have made the study of gene expression from mRNA molecules interesting, progressive, developmental, and helping to tackle health challenges head-on.

Keywords: transcriptomics, RNA sequencing, single cell, spatial, gene expression.

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: Agnieszka Dubiel, Artur Grabowski, Tomasz Przerywacz, Mateusz Roganowicz, Patrycja Zioty

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Food waste is one of the most significant challenges humanity is facing nowadays. Every year, reports from global organizations show the scale of the phenomenon, although society's awareness is still insufficient. One-third of the food produced in the world is wasted at various points in the food supply chain. Wastes are present from the delivery through the food preparation and distribution to the end of the sale and consumption. The first step in understanding and resisting the phenomenon is a thorough analysis of the everyday behaviors of humanity. This concept is understood as finding the correlation between the type of food and the reason for throwing it out and wasting it. Those actions were identified as a critical step in the start of work to develop technology to prevent food waste. In this paper, the problem mentioned above was analyzed by focusing on the inhabitants of Central Europe, especially Poland, aged 20-30. This paper provides an insight into collecting data through dedicated software and an organized database. The proposed database contains information on the amount, type, and reasons for wasting food in households. A literature review supported the work to answer research questions, compare the situation in Poland with the problem analyzed in other countries, and find research gaps. The proposed article examines the cause of food waste and its quantity in detail. This review complements previous reviews by emphasizing social and economic innovation in Poland's food waste management. The paper recommends a course of action for future research on food waste management and prevention related to the handling and disposal of food, emphasizing households, i.e., the last link in the supply chain.

Keywords: food waste, food waste reduction, consumer food waste, human-food interaction

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Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

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Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: avatar, dictionary, HamNoSys, hearing impaired, Indian sign language (ISL), sign language

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Authors: Geminne Manzano, Porfirio Aliño, Clairecynth Yu, Lilibeth Salvador-Reyes, Viviene Santiago

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Many marine benthic organisms produce secondary metabolites that serve as ecological roles to different biological and environmental factors. The secondary metabolites found in these organisms like algae, sponges, tunicates and worms exhibit variation at different scales. Understanding the chemical variation can be essential in deriving the evolutionary and ecological function of the secondary metabolites that may explain their patterns. Ecological surveys were performed on two collection sites representing from two Philippine marine biogeographic regions – in Oriental Mindoro located on the West Philippine Sea (WPS) and in Zamboanga del Sur located at Celebes Sea (CS), where a total of 39 Xestospongia sp. sponges were collected using SCUBA. The sponge samples were transported to the laboratory for taxonomic identification and chemical analysis. Biological and environmental factors were investigated to determine their relation to the abundance and distribution patterns and its spatial variability of their secondary metabolite production. Extracts were subjected to thin-layer chromatography and anti-proliferative assays to confirm the presence of Renieramycin-M and to test its cytotoxicity. The blue sponges were found to be more abundant on the WPS than in CS. Both the benthic community and the fish community in Oriental Mindoro, WPS and Zamboanga del Sur, CS sites are characterized by high species diversity and abundance and a very high biomass category. Environmental factors like depth and monsoonal exposure were also compared showing that wave exposure and depth are associated with the abundance and distribution of the sponges. Renieramycin-M presence using the TLC profiles between the sponge extracts from WPS and from CS showed differences in the Reniermycin-M presence and the presence of other functional groups were observed between the two sites. In terms of bioactivity, different responses were also exhibited by the sponge extracts coming from the different region. Different responses were also noted on its bioactivity depending on the cell lines tested. Exploring the influence of ecological parameters on the chemical variation can provide deeper chemical ecological insights in the knowledge and their potential varied applications at different scales. The results of this study provide further impetus in pursuing studies into patterns and processes of the chemical diversity of the Philippine blue sponge, Xestospongia sp. and the chemical ecological significance of the coral triangle.

Keywords: chemical ecology, porifera, renieramycin-m, spatial variability, Xestospongia sp.

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Authors: Deng Tingting

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The coordinated and integrated development of regions is an inevitable requirement for China to move towards high-quality, sustainable development. As one of the regions with the best economic foundation and the strongest economic strength in western China, it is a typical area with national importance and strong network connection characteristics in terms of the comprehensive effect of linking the inland hinterland and connecting the western and national urban networks. The integrated development of the Chengdu-Chongqing economic circle is of great strategic significance for the rapid and high-quality development of the western region. In the context of new urbanization, this paper takes 16 urban units within the economic circle as the research object, based on the 5-year panel data of population, regional economy, and spatial construction and development from 2016 to 2020, using the entropy method and Theil index to analyze the three target layers, and cause analysis. The research shows that there are temporal and spatial differences in the Chengdu-Chongqing economic circle, and there are significant differences between the core city and the surrounding cities. Therefore, by reforming and innovating the regional coordinated development mechanism, breaking administrative barriers, and strengthening the "polar nucleus" radiation function to release the driving force for economic development, especially in the gully areas of economic development belts, not only promote the coordinated development of internal regions but also promote the coordinated and sustainable development of the western region and take a high-quality development path.

Keywords: Chengdu-Chongqing economic circle, new urbanization, coordinated regional development, Theil Index

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Authors: Sabina Auhunas

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These days in Ukraine, Open Science dramatically develops for the sake of scientists of all branches, providing an opportunity to take a more close look on the studies by foreign scientists, as well as to deliver their own scientific data to national and international journals. However, when it comes to the generalization of data on science activities by Ukrainian scientists, these data are often integrated into E-systems that operate inconsistent and barely related information sources. In order to resolve these issues, developed countries productively use E-systems, designed to store and manage research data, such as Current Research Information Systems that enable combining uncompiled data obtained from different sources. An algorithm for selecting SARS-CoV-2 research articles was designed, by means of which we collected the set of papers published by Ukrainian scientists and uploaded by August 1, 2020. Resulting metadata (document type, open access status, citation count, h-index, most cited documents, international research funding, author counts, the bibliographic relationship of journals) were taken from Scopus and Web of Science databases. The study also considered the info from COVID-19/SARS-CoV-2-related documents published from December 2019 to September 2020, directly from documents published by authors depending on territorial affiliation to Ukraine. These databases are enabled to get the necessary information for bibliometric analysis and necessary details: copyright, which may not be available in other databases (e.g., Science Direct). Search criteria and results for each online database were considered according to the WHO classification of the virus and the disease caused by this virus and represented (Table 1). First, we identified 89 research papers that provided us with the final data set after consolidation and removing duplication; however, only 56 papers were used for the analysis. The total number of documents by results from the WoS database came out at 21641 documents (48 affiliated to Ukraine among them) in the Scopus database came out at 32478 documents (41 affiliated to Ukraine among them). According to the publication activity of Ukrainian scientists, the following areas prevailed: Education, educational research (9 documents, 20.58%); Social Sciences, interdisciplinary (6 documents, 11.76%) and Economics (4 documents, 8.82%). The highest publication activity by institution types was reported in the Ministry of Education and Science of Ukraine (its percent of published scientific papers equals 36% or 7 documents), Danylo Halytsky Lviv National Medical University goes next (5 documents, 15%) and P. L. Shupyk National Medical Academy of Postgraduate Education (4 documents, 12%). Basically, research activities by Ukrainian scientists were funded by 5 entities: Belgian Development Cooperation, the National Institutes of Health (NIH, U.S.), The United States Department of Health & Human Services, grant from the Whitney and Betty MacMillan Center for International and Area Studies at Yale, a grant from the Yale Women Faculty Forum. Based on the results of the analysis, we obtained a set of published articles and preprints to be assessed on the variety of features in upcoming studies, including citation count, most cited documents, a bibliographic relationship of journals, reference linking. Further research on the development of the national scientific E-database continues using brand new analytical methods.

Keywords: content analysis, COVID-19, scientometrics, text mining

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Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

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A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

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Authors: Rizki Oktariza, Sri Fauza Pratiwi, Hilza Ikhsanti

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Human depends on fossil fuels as the bigger sources of considerable energy in all sectors. Based on that cases, we are needed alternative energy to supplies needed for fuel, one of them by using energy fuel from the biodiesel. The raw materials that can be used for producing the biodiesel energy are Jatropha curcas L. In Indonesia, the availability of land for the development of the Jatropha curcas L which has very appropriate Indonesia reached 14.2 million hectares, with an area of suitable in Kalimantan around 10 million hectares. In Central Kalimantan, as one of the provinces of Kalimantan, has considerable potential planting Jatropha curcas L because of the physical condition and have a largest of the agricultural land. To support the potential of Jatropha curcas L in Central Kalimantan, spatial analysis is needed to find out the appropriate areas for Jatropha curcas L growing land. The suitability of region is influenced by several variables i.e., rainfall, the slope of the land, the surface temperature and the altitude of a region. The compliance of criteria are divided into four criteria: high suitable (S1), moderately suitable (S2), marginally suitable (S3), not suitable (N). The suitability of the region is based on these variables and made an overlay analysis of these variables by using Geographic Information System. Based on this overlay analysis will results a map of the suitability area for planting Jatropha curcas L, which is distribution criteria is high suitable (S1) of 213,245 ha, moderately suitable (S2) of 14,389,353 ha, marginally suitable (S3) 360,357 ha, not suitable (N) 0.020 ha.

Keywords: geographic information system, Jatropha curcas L., overlay, the suitable area

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Authors: Tagore Sai Priya Nunna, Ankhi Banerjee

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The rapid growth of the tourism industry in India in the last few years after the economic crisis in 2009 has been one of the significant causes that led to the Land Use Land Cover change (LULC) of most tourism destinations. The tourist regions are subjected to significant increase in built-up due to increased construction activities for developing accommodation facilities further boosting tourism demand. This research attempts to analyse the changing LULC and the growth pattern of the built-up area within tourist destinations. Four popular tourist destinations, which promises various types of tourism activity and which are significantly dependent on tourism for economic growth, are selected for the study. The study uses remotely sensed data for analysis of land use change through supervised segmentation into five broad classes. Further, the landuse map is reclassified into binary classes to extract the built-up area. The growth patterns of the built-up are analysed in terms of size, shape, direction and form of growth, through a set of spatial metrics. Additionally, a detailed analysis of the existing development pattern corresponding to planned development zones was performed to identify unplanned growth spots in the study regions. The findings of the study provide insights into how tourism has contributed to significant changes in LULC around tourist sites. Also, the study highlights the growth pattern of built-up areas with respect to the type of tourism activity and geographical characteristics. The research attempts to address the need of integrating spatial metrics for the development of sustainable tourism plans as part of the goals of sustainable development.

Keywords: built-up, growth, patterns, tourism, sustainable

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Authors: Zair Nadje, Attoui Badra, Miloudi Abdelmonem

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This study aims to assess sensitivity to nitrate pollution and monitor the temporal evolution of nitrate contents in groundwater using statistical models and map their spatial distribution. The nitrate levels observed in the waters of the town of El-Oued differ from one aquifer to another. Indeed, the waters of the Quaternary aquifer are the richest in nitrates, with average annual contents varying from 6 mg/l to 85 mg/l, for an average of 37 mg/l. These levels are higher than the WHO standard (50 mg/l) for drinking water. At the water level of the Terminal Complex (CT) aquifer, the annual average nitrate levels vary from 14 mg/l to 37 mg/l, with an average of 18 mg/l. In the Terminal Complex, excessive nitrate levels are observed in the central localities of the study area. The spatial distribution of nitrates in the waters of the Quaternary aquifer shows that the majority of the catchment points of this aquifer are subject to nitrate pollution. This study shows that in the waters of the Terminal Complex aquifer, nitrate pollution evolves in two major areas. The first focus is South-North, following the direction of underground flow. The second is West-East, progressing towards the East zone. The temporal distribution of nitrate contents in the water of the Terminal Complex aquifer in the city of El-Oued showed that for decades, nitrate contents have suffered a decline after an increase. This evolution of nitrate levels is linked to demographic growth and the rapid urbanization of the city of El-Oued.

Keywords: anthropogenic activities, groundwater, nitrates, pollution, arid zones city of El-Oued, Algeria

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Authors: Alina Svechkina, Boris A. Portnov

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In line with a rapid increase in pollution sources and enforcement of stricter air pollution regulation, which lowers pollution levels, it becomes more difficult to identify actual risk sources behind the observed morbidity patterns, and new approaches are required to identify potential risks and take preventive actions. In the present study, we discuss a probabilistic approach to the spatial identification of a priori unidentified environmental health hazards. The underlying assumption behind the tested approach is that the observed adverse health patterns (morbidity, mortality) can become a source of information on the geographic location of environmental risk factors that stand behind them. Using this approach, we analyzed sources of environmental exposure using data on mortality rates available for the year 2015 for NUTS 3 (Nomenclature of Territorial Units for Statistics) subdivisions of the European Union. We identified several areas in the southwestern part of Europe as primary risk sources for the observed mortality patterns. Multivariate regressions, controlled by geographical location, climate conditions, GDP (gross domestic product) per capita, dependency ratios, population density, and the level of road freight revealed that mortality rates decline as a function of distance from the identified hazard location. We recommend the proposed approach an exploratory analysis tool for initial investigation of regional patterns of population morbidity patterns and factors behind it.

Keywords: mortality, environmental hazards, air pollution, distance decay gradient, multi regression analysis, Europe, NUTS3

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Authors: Hesam Gholami

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Elevated suspended sediment loads in riverine systems resulting from accelerated erosion due to human activities are a serious threat to the sustainable management of watersheds and ecosystem services therein worldwide. Therefore, mitigation of deleterious sediment effects as a distributed or non-point pollution source in the catchments requires reliable provenance information. Sediment tracing or sediment fingerprinting, as a combined process consisting of sampling, laboratory measurements, different statistical tests, and the application of mixing or unmixing models, is a useful technique for discriminating the sources of sediments. From 1996 to the present, different aspects of this technique, such as grouping the sources (spatial and individual sources), discriminating the potential sources by different statistical techniques, and modification of mixing and unmixing models, have been introduced and modified by many researchers worldwide, and have been applied to identify the provenance of fine materials in agricultural, rural, mountainous, and coastal catchments, and in large catchments with numerous lakes and reservoirs. In the last two decades, efforts exploring the uncertainties associated with sediment fingerprinting results have attracted increasing attention. The frameworks used to quantify the uncertainty associated with fingerprinting estimates can be divided into three groups comprising Monte Carlo simulation, Bayesian approaches and generalized likelihood uncertainty estimation (GLUE). Given the above background, the primary goal of this study was to apply geochemical fingerprinting within the GLUE framework in the estimation of sub-basin spatial sediment source contributions in the arid Mehran River catchment in southern Iran, which drains into the Persian Gulf. The accuracy of GLUE predictions generated using four different sets of statistical tests for discriminating three sub-basin spatial sources was evaluated using 10 virtual sediments (VS) samples with known source contributions using the root mean square error (RMSE) and mean absolute error (MAE). Based on the results, the contributions modeled by GLUE for the western, central and eastern sub-basins are 1-42% (overall mean 20%), 0.5-30% (overall mean 12%) and 55-84% (overall mean 68%), respectively. According to the mean absolute fit (MAF; ≥ 95% for all target sediment samples) and goodness-of-fit (GOF; ≥ 99% for all samples), our suggested modeling approach is an accurate technique to quantify the source of sediments in the catchments. Overall, the estimated source proportions can help watershed engineers plan the targeting of conservation programs for soil and water resources.

Keywords: sediment source tracing, generalized likelihood uncertainty estimation, virtual sediment mixtures, Iran

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: Rasha Ahmadi

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Glioblastoma is one of the most frequent brain malignancies, having a high mortality rate and limited survival in individuals with this malignancy. Despite different treatments and surgery, recurrence of glioblastoma cancer stem cells may arise as a subsequent tumor. For this reason, it is crucial to research the markers associated with glioblastoma stem cells and specifically their microenvironment. In this study, using bioinformatics analysis, we analyzed and nominated genes in the microenvironment pathways of glioblastoma stem cells. In this study, an appropriate database was selected for analysis by referring to the GEO database. This dataset comprised gene expression patterns in stem cells derived from glioblastoma patients. Gene clusters were divided as high and low expression. Enrichment databases such as Enrichr, STRING, and GEPIA were utilized to analyze the data appropriately. Finally, we extracted the potential genes 2700 high-expression and 1100 low-expression genes are implicated in the metabolic pathways of glioblastoma cancer progression. Cellular senescence, MAPK, TNF, hypoxia, zimosterol biosynthesis, and phosphatidylinositol metabolism pathways were substantially expressed and the metabolic pathways were downregulated. After assessing the association between protein networks, MSMP, SOX2, FGD4 ,and CNTNAP3 genes with high expression and DMKN and SBSN genes with low were selected. All of these genes were observed in the survival curve, with a survival of fewer than 10 percent over around 15 months. hsa-mir-192-5p, hsa-mir-129-5p, hsa-mir-215-5p, hsa-mir-335-5p, and hsa-mir-340-5p played key function in glioblastoma cancer stem cells microenviroments. We introduced critical genes through integrated and regular bioinformatics studies by assessing the amount of gene expression profile data that can play an important role in targeting genes involved in the energy and microenvironment of glioblastoma cancer stem cells. Have. This study indicated that hsa-mir-192-5p, and hsa-mir-129-5p are appropriate candidates for this.

Keywords: Glioblastoma, Cancer Stem Cells, Biomarker Discovery, Gene Expression Profiles, Bioinformatics Analysis, Tumor Microenvironment

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Authors: Lucie Jirotková, Daniel Macek, Andrea Palazzo, Veronika Malinová

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Currently, the implementation of 3D models in the construction industry is gaining popularity. Countries around the world are developing their own modelling standards and implement the use of 3D models into their individual permitting processes. Another theme that needs to be addressed are public building spaces and their subsequent maintenance, where the usage of BIM methodology is directly offered. The significant benefit of the implementation of Building Information Management is the information transfer. The 3D model contains not only the spatial representation of the item shapes but also various parameters that are assigned to the individual elements, which are easily traceable, mainly because they are all stored in one place in the BIM model. However, it is important to keep the data in the models up to date to achieve useability of the model throughout the life cycle of the building. It is now becoming standard practice to use BIM models in the construction of buildings, however, the building environment is very often neglected. Especially in large-scale development projects, the public space of buildings is often forwarded to municipalities, which obtains the ownership and are in charge of its maintenance. A 3D model of the building surroundings would include both the above-ground visible elements of the development as well as the underground parts, such as the technological facilities of water features, electricity lines for public lighting, etc. The paper shows the possibilities of a model in the field of information for the handover of premises, the following maintenance and decision making. The attributes and spatial representation of the individual elements make the model a reliable foundation for the creation of "Smart Cities". The paper analyses the current use of the BIM methodology and presents the state-of-the-art possibilities of development.

Keywords: BIM model, urban space, BIM methodology, facility management

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Authors: Annet Namusoke, Annet Namayanja, Peter Wasswa, Shakirah Nampijja

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Common bean cultivar G2333 which offers broad resistance for anthracnose has been widely used as a source of resistance in breeding for anthracnose resistance. The cultivar is pyramided with three genes namely CO-4, CO-5 and CO-7 and of these three genes, the CO-4 gene has been found to offer the broadest resistance. The main aim of this work was to identify and validate easily assayable PCR based co-dominant molecular markers for selection of the CO-4 gene in segregating populations derived from crosses of G2333 with RWR 1946 and RWR 2075, two commercial Andean cultivars highly susceptible to anthracnose. Marker sequences for the study were obtained by blasting the sequence of the COK-4 gene in the Phaseolus gene database. Primer sequence pairs that were not provided from the Phaseolus gene database were designed by the use of Primer3 software. PCR conditions were optimized and the PCR products were run on 6% HPAGE gel. Results of the polymorphism test indicated that out of 18 identified markers, only two markers namely BM588 and BM211 behaved co-dominantly. Phenotypic evaluation for reaction to anthracnose disease was done by inoculating 21days old seedlings of three parents, F1 and F2 populations with race 7 of Colletotrichum lindemuthianum in the humid chamber. DNA testing of the BM588 marker onto the F2 segregating population of the crosses RWR 1946 x G 2333 and RWR 2075 x G2333 further revealed that the marker BM588 co-segregated with disease resistance with co-dominance of two alleles of 200bp and 400bp, fitting the expected segregation ratio of 1:2:1. The BM588 marker was significantly associated with disease resistance and gave promising results for marker assisted selection of the CO-4 gene in the breeding lines. Activities to validate the BM211 marker are also underway.

Keywords: codominant, Colletotrichum lindemuthianum, MAS, Phaseolus vulgaris

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Authors: Y. T. van Popta

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This paper focuses on the never thoroughly examined yet in native relevant late medieval maritime cultural landscape of the former Zuiderzee (A.D. 1170-1932) in the center part of the Netherlands. Especially the northeastern part of the region, nowadays known as the Noordoostpolder, testifies of the dynamic battle of the Dutch against the water. This highly dynamic maritime region developed from a lake district into a sea and eventually into a polder. By linking physical and cognitive datasets from the Noordoostpol-der region in a spatial environment, new information on a late medieval maritime culture is brought to light, giving the opportunity to: (i) create a modern day perception on the late medieval maritime cultural landscape of the region and (ii) to underline the value of interdisciplinary and spatial research in maritime archaeology in general. Since the large scale reclamations of the region (A.D. 1932-1968), many remains have been discovered of a drowned and eroded late medieval maritime culture, represented by lost islands, drowned settlements, cultivated lands, shipwrecks and socio-economic networks. Recent archaeological research has proved the existence of this late medieval maritime culture by the discovery of the remains of the drowned settlement Fenehuysen (Veenhuizen) and its surroundings. The fact that this settlement and its cultivated surroundings remained hidden for so long proves that a large part of the maritime cultural landscape is ‘invisible’ and can only be found by extensive interdisciplinary research.

Keywords: drowned settlements, late middle ages, lost islands, maritime cultural landscape, the Netherlands

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Authors: Višnjica Vučetić, Mislav Anić, Jelena Bašić, Petra Sviličić, Ivana Tomašević

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The Agroclimatic Atlas of Croatia (Atlas) for the periods 1981–2010 and 1991–2020 is monograph of six chapters in digital form. Detailed descriptions of particular agroclimatological data are given in separate chapters as follows: agroclimatic indices based on air temperature (degree days, Huglin heliothermal index), soil temperature, water balance components (precipitation, potential evapotranspiration, actual evapotranspiration, soil moisture content, runoff, recharge and soil moisture loss) and fire weather indices. The last chapter is a description of the digital methods for the spatial interpolations (R and GIS). The Atlas comprises textual description of the relevant climate characteristic, maps of the spatial distribution of climatological elements at 109 stations (26 stations for soil temperature) and tables of the 30-year mean monthly, seasonal and annual values of climatological parameters at 24 stations. The Atlas was published in 2021, on the seventieth anniversary of the agrometeorology development at the Meteorological and Hydrological Service of Croatia. It is intended to support improvement of sustainable system of agricultural production and forest protection from fire and as a rich source of information for agronomic and forestry experts, but also for the decision-making bodies to use it for the development of strategic plans.

Keywords: agrometeorology, agroclimatic indices, soil temperature, water balance components, fire weather index, meteorological and hydrological service of Croatia

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Authors: Abdulaziz Alakeel, Abdulrahman Alomair, Mohammed Fouda

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Introduction: Methotrexate (MTX) is an antimetabolite used to treat multiple conditions, including neoplastic diseases, severe psoriasis, and rheumatoid arthritis. Skin cancer is the out-of-control growth of abnormal cells in the epidermis, the outermost skin layer, caused by unrepaired DNA damage that triggers mutations. These mutations lead the skin cells to multiply rapidly and form malignant tumors. The aim of this review is to evaluate the risk of skin cancer associated with the use of methotrexate and to suggest regulatory recommendations if required. Methodology: Signal Detection team at Saudi Food and Drug Authority (SFDA) performed a safety review using National Pharmacovigilance Center (NPC) database as well as the World Health Organization (WHO) VigiBase, alongside with literature screening to retrieve related information for assessing the causality between skin cancer and methotrexate. The search conducted in July 2020. Results: Four published articles support the association seen while searching in literature, a recent randomized control trial published in 2020 revealed a statistically significant increase in skin cancer among MTX users. Another study mentioned methotrexate increases the risk of non-melanoma skin cancer when used in combination with immunosuppressant and biologic agents. In addition, the incidence of melanoma for methotrexate users was 3-fold more than the general population in a cohort study of rheumatoid arthritis patients. The last article estimated the risk of cutaneous malignant melanoma (CMM) in a cohort study shows a statistically significant risk increase for CMM was observed in MTX exposed patients. The WHO database (VigiBase) searched for individual case safety reports (ICSRs) reported for “Skin Cancer” and 'Methotrexate' use, which yielded 121 ICSRs. The initial review revealed that 106 cases are insufficiently documented for proper medical assessment. However, the remaining fifteen cases have extensively evaluated by applying the WHO criteria of causality assessment. As a result, 30 percent of the cases showed that MTX could possibly cause skin cancer; five cases provide unlikely association and five un-assessable cases due to lack of information. The Saudi NPC database searched to retrieve any reported cases for the combined terms methotrexate/skin cancer; however, no local cases reported up to date. The data mining of the observed and the expected reporting rate for drug/adverse drug reaction pair is estimated using information component (IC), a tool developed by the WHO Uppsala Monitoring Centre to measure the reporting ratio. Positive IC reflects higher statistical association, while negative values translated as a less statistical association, considering the null value equal to zero. Results showed that a combination of 'Methotrexate' and 'Skin cancer' observed more than expected when compared to other medications in the WHO database (IC value is 1.2). Conclusion: The weighted cumulative pieces of evidence identified from global cases, data mining, and published literature are sufficient to support a causal association between the risk of skin cancer and methotrexate. Therefore, health care professionals should be aware of this possible risk and may consider monitoring any signs or symptoms of skin cancer in patients treated with methotrexate.

Keywords: methotrexate, skin cancer, signal detection, pharmacovigilance

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Authors: C. U. Om Kumar, S. Kishore, A. Geetha

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An Operating system (OS) is software that manages computer hardware and software resources by providing services to computer programs. One of the important user expectations of the operating system is to provide the practice of defending information from unauthorized access, disclosure, modification, inspection, recording or destruction. Operating system is always vulnerable to the attacks of malwares such as computer virus, worm, Trojan horse, backdoors, ransomware, spyware, adware, scareware and more. And so the anti-virus software were created for ensuring security against the prominent computer viruses by applying a dictionary based approach. The anti-virus programs are not always guaranteed to provide security against the new viruses proliferating every day. To clarify this issue and to secure the computer system, our proposed expert system concentrates on authorizing the processes as wanted and unwanted by the administrator for execution. The Expert system maintains a database which consists of hash code of the processes which are to be allowed. These hash codes are generated using MD5 message-digest algorithm which is a widely used cryptographic hash function. The administrator approves the wanted processes that are to be executed in the client in a Local Area Network by implementing Client-Server architecture and only the processes that match with the processes in the database table will be executed by which many malicious processes are restricted from infecting the operating system. The add-on advantage of this proposed Expert system is that it limits CPU usage and minimizes resource utilization. Thus data and information security is ensured by our system along with increased performance of the operating system.

Keywords: virus, worm, Trojan horse, back doors, Ransomware, Spyware, Adware, Scareware, sticky software, process table, MD5, CPU usage and resource utilization

Procedia PDF Downloads 428

Authors: Scott A. Ochsner, Christopher M. Watkins, Apollo McOwiti, David L. Steffen Lauren B. Becnel, Neil J. McKenna

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Understanding signaling by nuclear receptors (NRs) requires an appreciation of their cognate ligand- and tissue-specific transcriptomes. While target gene regulation data are abundant in this field, they reside in hundreds of discrete publications in formats refractory to routine query and analysis and, accordingly, their full value to the NR signaling community has not been realized. One of the mandates of the Nuclear Receptor Signaling Atlas (NURSA) is to facilitate access of the community to existing public datasets. Pursuant to this mandate we are developing a freely-accessible community web resource, Transcriptomine, to bring together the sum total of available expression array and RNA-Seq data points generated by the field in a single location. Transcriptomine currently contains over 25,000,000 gene fold change datapoints from over 1200 contrasts relevant to over 100 NRs, ligands and coregulators in over 200 tissues and cell lines. Transcriptomine is designed to accommodate a spectrum of end users ranging from the bench researcher to those with advanced bioinformatic training. Visualization tools allow users to build custom charts to compare and contrast patterns of gene regulation across different tissues and in response to different ligands. Our resource affords an entirely new paradigm for leveraging gene expression data in the NR signaling field, empowering users to query gene fold changes across diverse regulatory molecules, tissues and cell lines, target genes, biological functions and disease associations, and that would otherwise be prohibitive in terms of time and effort. Transcriptomine will be regularly updated with gene lists from future genome-wide expression array and expression-sequencing datasets in the NR signaling field.

Keywords: target gene database, informatics, gene expression, transcriptomics

Procedia PDF Downloads 275

Authors: Muhammad Ameer Nawaz Akram

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The 21st century has been revealed that many individuals around the world are living in urban settlements than in rural zones. The evolution of numerous cities in emerging and newly developed countries is accompanied by the rise of slums. The precise definition of a slum varies countries to countries, but the universal harmony is that slums are dilapidated settlements facing severe poverty and have lacked access to sanitation, water, electricity, good living styles, and land tenure. The slum settlements always vary in unique patterns within and among the countries and cities. The core objective of this study is the spatial identification and classification of slums in Gujrat city Pakistan from very high-resolution GeoEye-1 (0.41m) satellite imagery. Slums were first identified using GPS for sample site identification and ground-truthing; through this process, 425 slums were identified. Then Object-Oriented Analysis (OOA) was applied to classify slums on digital image. Spatial analysis softwares, e.g., ArcGIS 10.3, Erdas Imagine 9.3, and Envi 5.1, were used for processing data and performing the analysis. Results show that OOA provides up to 90% accuracy for the identification of slums. Jalal Cheema and Allah Ho colonies are severely affected by slum settlements. The ratio of criminal activities is also higher here than in other areas. Slums are increasing with the passage of time in urban areas, and they will be like a hazardous problem in coming future. So now, the executive bodies need to make effective policies and move towards the amelioration process of the city.

Keywords: slums, GPS, satellite imagery, object oriented analysis, zonal change detection

Procedia PDF Downloads 136

Authors: Katyana A. Vert-Pre, James T. Thorson, Thomas Trancart, Eric Feunteun

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In marine ecosystems, spatial and temporal species structure is an important component of ecosystems’ response to anthropological and environmental factors. Although spatial distribution patterns and fish temporal series of abundance have been studied in the past, little research has been allocated to the joint dynamic spatio-temporal functional patterns in marine ecosystems and their use in multispecies management and conservation. Each species represents a function to the ecosystem, and the distribution of these species might not be random. A heterogeneous functional distribution will lead to a more resilient ecosystem to external factors. Applying a Vector-Autoregressive Spatio-Temporal (VAST) model for count data, we estimate the spatio-temporal distribution, shift in time, and abundance of 140 species of the Eastern English Chanel, Bay of Biscay and Mediterranean Sea. From the model outputs, we determined spatio-temporal clusters, calculating p-values for hierarchical clustering via multiscale bootstrap resampling. Then, we designed a functional map given the defined cluster. We found that the species distribution within the ecosystem was not random. Indeed, species evolved in space and time in clusters. Moreover, these clusters remained similar over time deriving from the fact that species of a same cluster often shifted in sync, keeping the overall structure of the ecosystem similar overtime. Knowing the co-existing species within these clusters could help with predicting data-poor species distribution and abundance. Further analysis is being performed to assess the ecological functions represented in each cluster.

Keywords: cluster distribution shift, European marine ecosystems, functional distribution, spatio-temporal model

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Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

Procedia PDF Downloads 134

Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Smart cities and intelligent transportation systems rely heavily on effective traffic management and infrastructure planning. This research tackles the data scarcity challenge by generating realistically synthetic traffic data from the PeMS-Bay dataset, enhancing predictive modeling accuracy and reliability. Advanced techniques like TimeGAN and GaussianCopula are utilized to create synthetic data that mimics the statistical and structural characteristics of real-world traffic. The future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is anticipated to capture both spatial and temporal correlations, further improving data quality and realism. Each synthetic data generation model's performance is evaluated against real-world data to identify the most effective models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are employed to model and predict complex temporal dependencies within traffic patterns. This holistic approach aims to identify areas with low vehicle counts, reveal underlying traffic issues, and guide targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study facilitates data-driven decision-making that improves urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory (LSTM), synthetic data generation, traffic management

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Authors: Nawaf Al Khashram, Graham Arnold, Weijie Wang

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Background—Gait classifying allows clinicians to differentiate gait patterns into clinically important categories that help in clinical decision making. Reliable comparison of gait data between normal and patients requires knowledge of the gait parameters of normal children's specific age group. However, there is still a lack of the gait database for normal children of different ages. Objectives—The aim of this study is to investigate the kinematics of the lower limb joints during gait for normal children in different age groups. Methods—Fifty-three normal children (34 boys, 19 girls) were recruited in this study. All the children were aged between 5 to 16 years old. Age groups were defined as three types: young child aged (5-7), child (8-11), and adolescent (12-16). When a participant agreed to take part in the project, their parents signed a consent form. Vicon® motion capture system was used to collect gait data. Participants were asked to walk at their comfortable speed along a 10-meter walkway. Each participant walked up to 20 trials. Three good trials were analyzed using the Vicon Plug-in-Gait model to obtain parameters of the gait, e.g., walking speed, cadence, stride length, and joint parameters, e.g. joint angle, force, moments, etc. Moreover, each gait cycle was divided into 8 phases. The range of motion (ROM) angle of pelvis, hip, knee, and ankle joints in three planes of both limbs were calculated using an in-house program. Results—The temporal-spatial variables of three age groups of normal children were compared between each other; it was found that there was a significant difference (p < 0.05) between the groups. The step length and walking speed were gradually increasing from young child to adolescent, while cadence was gradually decreasing from young child to adolescent group. The mean and standard deviation (SD) of the step length of young child, child and adolescent groups were 0.502 ± 0.067 m, 0.566 ± 0.061 m and 0.672 ± 0.053 m, respectively. The mean and SD of the cadence of the young child, child and adolescent groups were 140.11±15.79 step/min, 129±11.84 step/min, and a 115.96±6.47 step/min, respectively. Moreover, it was observed that there were significant differences in kinematic parameters, either whole gait cycle or each phase. For example, RoM of knee angle in the sagittal plane in whole cycle of young child group is (65.03±0.52 deg) larger than child group (63.47±0.47 deg). Conclusion—Our result showed that there are significant differences between each age group in the gait phases and thus children walking performance changes with ages. Therefore, it is important for the clinician to consider age group when analyzing the patients with lower limb disorders before any clinical treatment.

Keywords: age group, gait analysis, kinematics, normal children

Procedia PDF Downloads 120

Authors: Anjan Hazra, Nirjhar Dasgupta, Chandan Sengupta, Sauren Das

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Tea (Camellia sinensis) has received substantial attention from the scientific world time to time, not only for its commercial importance, but also for its demand to the health-conscious people across the world for its extensive use as potential sources of antioxidant supplement. These health-benefit traits primarily rely on some regulatory networks of different metabolic pathways. Development of microsatellite markers from the conserved genomic regions is being worthwhile for studying the genetic diversity of closely related species or self-pollinated species. Although several SSR markers have been reported, in tea the trait-specific Simple Sequence Repeats (SSRs) are yet to be identified, which can be used for marker assisted breeding technique. MicroRNAs are endogenous, noncoding, short RNAs directly involved in regulating gene expressions at the post-transcriptional level. It has been found that diversity in miRNA gene interferes the formation of its characteristic hair pin structure and the subsequent function. In the present study, the precursors of small regulatory RNAs (microRNAs) has been fished out from tea Expressed Sequence Tag (EST) database. Furthermore, the simple sequence repeat motifs within the putative miRNA precursor genes are also identified in order to experimentally validate their existence and function. It is already known that genic-SSR markers are very adept and breeder-friendly source for genetic diversity analysis. So, the potential outcome of this in-silico study would provide some novel clues in understanding the miRNA-triggered polymorphic genic expression controlling specific metabolic pathways, accountable for tea quality.

Keywords: micro RNA, simple sequence repeats, tea quality, trait specific marker

Procedia PDF Downloads 313

Authors: Radwa Saad

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The Sahara is normatively treated as a barrier separating “two Africas"; one to the North with closer affinity to the Arab world, and one to the South that encompasses a diverse range of racial, ethnic and religious groups, commonly referred to as "Sub-Saharan Africa". This dichotomy however was challenged by many anticolonial leaders and intellectuals seeking to advance counter-hegemonic narratives that treat the Sahara as a bridge facilitating a long history of exchange, collaboration, and fusion between different civilizations on the continent. This paper reexamines the discourses governing the geographic distinction between North Africa and Sub-Saharan Africa. It argues that demarcating the African continent along the lines of the Sahara is part-and-parcel of a Euro-centric spatial imaginary that has served to enshrine a racialized global hierarchy of power. By drawing on Edward Said’s concept of ‘imagined geography’ and Charles Mill’s notion of “the racial contract”, it demonstrates how spatial boundaries often coincide with racial epistemologies to reinforce certain geopolitical imaginaries, whilst silencing others. It further draws on the works of two notable post-colonial figures - Gamal Abdel Nasser and Leopold Senghor - to explore alternative spatial imaginaries while highlighting some of the tensions embedded in advancing a trans-Saharan political project. Firstly, it deconstructs some of the normative claims used to justify the distinction between North and “sub-Saharan” Africa across political, literary and disciplinary boundaries. Secondly, it draws parallels between Said’s and Mills’ work to demonstrate how geographical boundaries and demarcations have been constructed to create racialized subjects and reinforce a hierarchy of color that favors European standpoints and epistemologies. Third, it draw on Leopard Senghor’s The Foundations of Africanité and Gamal Abdel Nasser’s The Philosophy of the Egyptian Revolution to examine some of the competing strands of unity that emerged out of the Saharan discourse. In these texts, one can identify a number of convergences and divergences in how post-colonial African elites attempts to reclaim and rearticulate the function of the Sahara along different epistemic, political and cultural premises. It concludes with reflections on some of the policy challenges that emerge from reinforcing the Saharan divide, particularly in the realm of peace and security.

Keywords: regional integration, politics of knowledge production, arab-african relations, african solutions to african problems

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Authors: Suresh Kumar Bandooni, Mirana Laishram

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The Mid Himalaya of Garhwal Himalaya in Uttarakhand (India) has a complex Physiographic features withdiversified climatic conditions and therefore it is suspect to environmental vulnerability. Thenatural disasters and also anthropogenic activities accelerate the rate of environmental vulnerability. To analyse the environmental vulnerability, we have used geoinformatics technologies and numerical models and it is adoptedby using Spatial Principal Component Analysis (SPCA). The model consist of many factors such as slope, landuse/landcover, soil, forest fire risk, landslide susceptibility zone, human population density and vegetation index. From this model, the environmental vulnerability integrated index (EVSI) is calculated for Pasol Gad Watershed of Garhwal Himalaya for the years 1987, 2000, and 2013 and the Vulnerability is classified into five levelsi.e. Very low, low, medium, high and very highby means of cluster principle. The resultsforeco-environmental vulnerability distribution in study area shows that medium, high and very high levels are dominating in the area and it is mainly caused by the anthropogenic activities and natural disasters. Therefore, proper management forconservation of resources is utmost necessity of present century. It is strongly believed that participation at community level along with social worker, institutions and Non-governmental organization (NGOs) have become a must to conserve and protect the environment.

Keywords: eco-environment vulnerability, spatial principal component analysis, remote sensing, geographic information system, institutions, Himalaya

Procedia PDF Downloads 263