Search results for: rainfall driven inflow/infiltration

Authors: Swee Yang Low, Dong Eon Kim, Canh Tien Trinh Nguyen, Yixiong Cai, Shie-Yui Liong

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Nee Soon swamp forest is one of the last vestiges of tropical wetland in Singapore. Understanding the hydrological regime of the swamp forest and implications for water quality is critical to guide stakeholders in implementing effective measures to preserve the wetland against anthropogenic impacts. In particular, although current field measurement data do not indicate a concern with organic pollution, reviewing the ways in which the wetland responds to elevated organic waste influx (and the corresponding impact on dissolved oxygen, DO) can help identify potential hotspots, and the impact on the outflow from the catchment which drains into downstream controlled watercourses. An integrated water quality model is therefore developed in this study to investigate spatial and temporal concentrations of DO levels and organic pollution (as quantified by biochemical oxygen demand, BOD) within the catchment’s river network under hypothetical, projected scenarios of spiked upstream inflow. The model was developed using MIKE HYDRO for modelling the study domain, as well as the MIKE ECO Lab numerical laboratory for characterising water quality processes. Model parameters are calibrated against time series of observed discharges at three measurement stations along the river network. Over a simulation period of April 2014 to December 2015, the calibrated model predicted that a continuous spiked inflow of 400 mg/l BOD will elevate downstream concentrations at the catchment outlet to an average of 12 mg/l, from an assumed nominal baseline BOD of 1 mg/l. Levels of DO were decreased from an initial 5 mg/l to 0.4 mg/l. Though a scenario of spiked organic influx at the swamp forest’s undeveloped upstream sub-catchments is currently unlikely to occur, the outcomes nevertheless will be beneficial for future planning studies in understanding how the water quality of the catchment will be impacted should urban redevelopment works be considered around the swamp forest.

Keywords: hydrology, modeling, water quality, wetland

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Authors: Meiyan Gao, Zongmin Wang, Haibo Yang, Qiuhua Liang

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Under the background of global climate change and rapid development of modern urbanization, the frequency of climate disasters such as extreme precipitation in cities around the world is gradually increasing. In this paper, Hi-PIMS model is used to simulate the "720" flood in Zhengzhou, and the continuous stages of flood resilience are determined with the urban flood stages are divided. The flood resilience curve under the influence of multiple factors were determined and the urban flood toughness was evaluated by combining the results of resilience curves. The flood resilience of urban unit grid was evaluated based on economy, population, road network, hospital distribution and land use type. Firstly, the rainfall data of meteorological stations near Zhengzhou and the remote sensing rainfall data from July 17 to 22, 2021 were collected. The Kriging interpolation method was used to expand the rainfall data of Zhengzhou. According to the rainfall data, the flood process generated by four rainfall events in Zhengzhou was reproduced. Based on the results of the inundation range and inundation depth in different areas, the flood process was divided into four stages: absorption, resistance, overload and recovery based on the once in 50 years rainfall standard. At the same time, based on the levels of slope, GDP, population, hospital affected area, land use type, road network density and other aspects, the resilience curve was applied to evaluate the urban flood resilience of different regional units, and the difference of flood process of different precipitation in "720" rainstorm in Zhengzhou was analyzed. Faced with more than 1,000 years of rainstorm, most areas are quickly entering the stage of overload. The influence levels of factors in different areas are different, some areas with ramps or higher terrain have better resilience, and restore normal social order faster, that is, the recovery stage needs shorter time. Some low-lying areas or special terrain, such as tunnels, will enter the overload stage faster in the case of heavy rainfall. As a result, high levels of flood protection, water level warning systems and faster emergency response are needed in areas with low resilience and high risk. The building density of built-up area, population of densely populated area and road network density all have a certain negative impact on urban flood resistance, and the positive impact of slope on flood resilience is also very obvious. While hospitals can have positive effects on medical treatment, they also have negative effects such as population density and asset density when they encounter floods. The result of a separate comparison of the unit grid of hospitals shows that the resilience of hospitals in the distribution range is low when they encounter floods. Therefore, in addition to improving the flood resistance capacity of cities, through reasonable planning can also increase the flood response capacity of cities. Changes in these influencing factors can further improve urban flood resilience, such as raise design standards and the temporary water storage area when floods occur, train the response speed of emergency personnel and adjust emergency support equipment.

Keywords: urban flood resilience, resilience assessment, hydrodynamic model, resilience curve

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Authors: C. Paglia, C. Mosca

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Synthetic resin floorsare often used in sport infrastructure. These organic materials are often in contact with a bituminous substrate, which in turn is placed on the ground. In this work, the damage of a basket resin field surface was characterized by means of visual inspection, optical microscopy, resin thickness measurements, adhesion strength, water vapor transmission capacity, capillary water adsorption, granulometry of the bituminous conglomerate, the surface properties, and the water ground infiltration speed. The infiltration speed indicates water pemeability. This was due to its composition: clean sand mixed with gravel. Relatively good adhesion was present between the synthetic resin and the bituminous layer. The adhesion resistance of the bituminous layer was relatively low. According to the required bitumoniousasphalt-concrete mixes AC 11 S, the placed material was more porous. Insufficient constipation was present. The spaces values were above the standard limits, while the apparent densities were lower compared to the conventional AC 11 mixtures. The microstructure outlines the high permeability and porosity of the bituminous layer. The synthetic resin wasvapourproof and did not exhibit capillary adsorption. It exhibited a lower thickness as required, and no multiple placing steps were observed. Multiple cavities were detected along with the interface between the bituminous layer and the resin coating with no intermediate layers. The layer for the pore filling in the bituminous surface was not properly applied. The swelling bubbles on the synthetic pavement were caused by the humidity in the bituminous layer. Water or humidity were present prior to the application of the resin, and the effect was worsened by the upward movement of the water from the ground.

Keywords: resin, floor, damage, durability

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Authors: Naren Bag, S. Bhattacharyya, Partha P. Gopmandal

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In this study, we have analyzed the transport of analytes under a two dimensional steady incompressible flow of power-law fluids through rectangular nanochannel. A mathematical model based on the Cauchy momentum-Nernst-Planck-Poisson equations is considered to study the combined effect of mixed electroosmotic (EO) and pressure driven (PD) flow. The coupled governing equations are solved numerically by finite volume method. We have studied extensively the effect of key parameters, e.g., flow behavior index, concentration of the electrolyte, surface potential, imposed pressure gradient and imposed electric field strength on the net average flow across the channel. In addition to study the effect of mixed EOF and PD on the analyte distribution across the channel, we consider a nonlinear model based on general convective-diffusion-electromigration equation. We have also presented the retention factor for various values of electrolyte concentration and flow behavior index.

Keywords: electric double layer, finite volume method, flow behavior index, mixed electroosmotic/pressure driven flow, non-Newtonian power-law fluids, numerical simulation

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Authors: Qiong Li

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This study investigated in which condition computer-mediated communication (CMC) could promote pragmatic development. The focal feature included four Chinese sentence final particles (SFPs), a, ya, ba, and ne. They occur frequently in Chinese, and function as mitigators to soften the tone of speech. However, L2 acquisition of SFPs is difficult, suggesting the necessity of additional exposure to or explicit instruction on Chinese SFPs. This study follows this line and aims to explore two research questions: (1) Is CMC combined with data-driven instruction more effective than CMC alone in promoting L2 Chinese learners’ SFP use? (2) How does L2 Chinese learners’ SFP use change over time, as compared to the production of native Chinese speakers? The study involved 19 intermediate-level learners of Chinese enrolled at a private American university. They were randomly assigned to two groups: (1) the control group (N = 10), which was exposed to SFPs through CMC alone, (2) the treatment group (N = 9), which was exposed to SFPs via CMC and data-driven instruction. Learners interacted with native speakers on given topics through text-based CMC over Skype. Both groups went through six 30-minute CMC sessions on a weekly basis, with a one-week interval after the first two CMC sessions and a two-week interval after the second two CMC sessions (nine weeks in total). The treatment group additionally received a data-driven instruction after the first two sessions. Data analysis focused on three indices: token frequency, type frequency, and acceptability of SFP use. Token frequency was operationalized as the raw occurrence of SFPs per clause. Type frequency was the range of SFPs. Acceptability was rated by two native speakers using a rating rubric. The results showed that the treatment group made noticeable progress over time on the three indices. The production of SFPs approximated the native-like level. In contrast, the control group only slightly improved on token frequency. Only certain SFPs (a and ya) reached the native-like use. Potential explanations for the group differences were discussed in two aspects: the property of Chinese SFPs and the role of CMC and data-driven instruction. Though CMC provided the learners with opportunities to notice and observe SFP use, as a feature with low saliency, SFPs were not easily noticed in input. Data-driven instruction in the treatment group directed the learners’ attention to these particles, which facilitated the development.

Keywords: computer-mediated communication, data-driven instruction, pragmatic development, second language Chinese, sentence final particles

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Authors: R. Rajeswari

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An investigation was carried out to know the SOC stock and its change over time in benchmark soils of different agroclimatic zones of Tamil Nadu. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern. Soil map prepared on 1:50,000 scale from Natural Resources Information System (NRIS) employed under satellite data (IRS-1C/1D-PAN sharpened LISS-III image) was used to estimate SOC stock in different agroclimatic zones of Tamil Nadu. Fifteen benchmark soils were selected in different agroclimatic zones of Tamil Nadu based on their land use and the areal extent to assess SOC level and its change overtime. This revealed that, between eleven years of period (1997 - 2007). SOC buildup was higher in soils under horticulture system, followed by soils under rice cultivation. Among different agroclimatic zones of Tamil Nadu hilly zone have the highest SOC stock, followed by north eastern, southern, western, cauvery delta, north western, and high rainfall zone. Although organic carbon content in the soils of North eastern, southern, western, North western, Cauvery delta were less than high rainfall zone, the SOC stock was high. SOC density was higher in high rainfall and hilly zone than other agroclimatic zones of Tamil Nadu. Among low rainfall regions of Tamil Nadu cauvery delta zone recorded higher SOC density. Roth.C model was used to assess SOC stock under existing and alternate cropping pattern in viz., Periyanaickenpalayam series (western zone), Peelamedu series (southern zone), Vallam series (north eastern zone), Vannappatti series (north western zone) and Padugai series (cauvery delta zone). Padugai series recorded higher TOC, BIO, and HUM, followed by Periyanaickenpalayam series, Peelamedu series, Vallam series, and Vannappatti series. Vannappatti and Padugai series develop high TOC, BIO, and HUM under existing cropping pattern. Periyanaickenpalayam, Peelamedu, and Vallam series develop high TOC, BIO, and HUM under alternate cropping pattern. Among five selected soil series, Periyanaickenpalayam, Peelamedu, and Padugai series recorded 0.75 per cent TOC during 2025 and 2018, 2100 and 2035, 2013 and 2014 under existing and alternate cropping pattern, respectively.

Keywords: agro climatic zones, benchmark soil, land use, soil organic carbon

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Authors: F. Esfandyari Darabad, Z. Samadi

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The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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Authors: Edward Sarich, Jack Ryan

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In contrast to learning new vocabulary incidentally in one’s first language, foreign language vocabulary is often acquired purposefully, because a lack of natural exposure requires it to be studied in an artificial environment. It follows then that foreign language vocabulary may be more efficiently acquired if it is purpose-driven, or linked to a clear and desirable outcome. The research described in this paper relates to the early stages of what is seen as a long-term effort to measure the effectiveness of a methodology for purpose-driven foreign language vocabulary instruction, specifically by analyzing whether directed studying from high-frequency vocabulary lists leads to an improvement in Test of English for International Communication (TOEIC) scores. The research was carried out in two sections of a first-year university English composition class at a small university in Japan. The results seem to indicate that purposeful study from relevant high-frequency vocabulary lists can contribute to raising TOEIC scores and that the test preparation methodology used in this study was thought by students to be beneficial in helping them to prepare to take this high-stakes test.

Keywords: corpus vocabulary, language asssessment, second language vocabulary acquisition, TOEIC test preparation

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Authors: Sujo Meghwar, Zulfqar Ali laghari, Kanji Harijan, Muhib Ali Lagari, G. M. Mastoi, Ali Mohammad Rind

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Thar Desert is the most populous Desert of the world. Climate variation in Thar Desert has induced an increase in the magnitude of drought. The variation in climate variation has caused a decrease in natural vegetations. Some plant species are eliminated forever. We have applied the SPI (standardized precipitation index) climate model to investigate the drought induced by climate change. We have gathered the anthropogenic response through a developed questionnaire. The data was analyzed in SPSS version 18. The met-data of two meteorological station elaborated by the time series has suggested an increase in temperature from 1-2.5 centigrade, the decrease in rain fall rainfall from 5-25% and reduction in humidity from 5-12 mm in the 20th century. The anthropogenic responses indicate high impact of climate change on human life and vegetations. Triangle data, we have collected, gives a new insight into the understanding of an association between climate change, drought and human activities.

Keywords: Thar desert, human impact, vegetations, temperature, rainfall, humidity

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Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Shidvash Vakilipour, Masoud Mohammadi, Rouzbeh Riazi, Scott Ormiston, Kimia Amiri, Sahar Barati

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An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.

Keywords: cell-centered finite volume method, coupled solver, exponential differencing scheme (EDS), physical influence scheme (PIS), pressure weighted interpolation method (PWIM), skew upwind differencing scheme (SUDS)

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Authors: Nji Queenta Ngum, Mwanza Mulunda

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Introduction Most African research reports on the frequent aflatoxin contamination of various foodstuffs, with researchers rarely specifying which of the Aspergillus species are present in these commodities. Numerous research works provide evidence of the ability of fungi to grow, thrive, and interact with other crop species and focus on the fact that these processes are largely affected by climatic variables. South Africa is a water-stressed country with high spatio-temporal rainfall variability; moreover, temperatures have been projected to rise at a rate twice the global rate. This weather pattern change may lead to crop stress encouraging mold contamination with subsequent mycotoxin production. In this study, the biodiversity and distribution of Aspergillus species with their corresponding toxins in maize from six distinct maize producing regions with different weather patterns in South Africa were investigated. Materials And Methods By applying cultural and molecular methods, a total of 1028 maize samples from six distinct agro-climatic regions were examined for contamination by the Aspergillus species while the high performance liquid chromatography (HPLC) method was applied to analyse the level of contamination by aflatoxins. Results About 30% of the overall maize samples were contaminated by at least one Aspergillus species. Less than 30% (28.95%) of the 228 isolates subjected to the aflatoxigenic test was found to possess at least one of the aflatoxin biosynthetic genes. Furthermore, almost 20% were found to be contaminated with aflatoxins, with mean total aflatoxin concentration levels of 64.17 ppb. Amongst the contaminated samples, 59.02% had mean total aflatoxin concentration levels above the SA regulatory limit of 20ppb for animals and 10 for human consumption. Conclusion In this study, climate variables (rainfall reduction) were found to significantly (p<0.001) influence the occurrence of the Aspergillus species (especially Aspergillus fumigatus) and the production of aflatoxin in South Africa commercial maize by maize variety, year of cultivation as well as the agro-climatic region in which the maize is cultivated. This included, amongst others, a reduction in the average annual rainfall of the preceding year to about 21.27 mm, and, as opposed to other regions whose average maximum rainfall ranged between 37.24 – 44.1 mm, resulted in a significant increase in the aflatoxin contamination of maize.

Keywords: aspergillus species, aflatoxins, diversity, drought, food safety, HPLC and PCR techniques

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Authors: Ji-Yuan Lin, Yu-Ming Liou, Yi-Ting Chen, Chen-Syuan Lin

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Soil water index obtained by tank model is now commonly used in soil and sand disaster alarm system in Japan. Comparing with the rainfall trigging index in Taiwan, the tank model is easy to predict the slope water content on large-scale landslide. Therefore, this study aims to estimate the threshold value of large-scale landslide using the soil water index Sixteen typhoons and heavy rainfall events, were selected to establish the, to relationship between landslide event and soil water index. Finally, the proposed threshold values for landslides on country road No.89 are suggested in this study. The study results show that 95% landslide cases occurred in soil water index more than 125mm, and 30% of the more serious slope failure occurred in the soil water index is greater than 250mm. Beside, this study speculates when soil water index more than 250mm and the difference value between second tank and third tank less than -25mm, it leads to large-scale landslide more probably.

Keywords: soil water index, tank model, landslide, threshold values

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Authors: Liping Li, Wenan Tan, Na Wang

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With the rapid development of information technology, project management has gained more and more attention recently. Based on CDIO, this paper proposes some teaching reform ideas for software project management curriculum. We first change from Teacher-centered classroom to Student-centered and adopt project-driven, scenario animation show, teaching rhythms, case study and team work practice to improve students' learning enthusiasm. Results showed these attempts have been well received and very effective; as well, students prefer to learn with this curriculum more than before the reform.

Keywords: CDIO, teaching reform, engineering education, project-driven, scenario animation simulation

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Authors: Sahar Nasr, Lin Li, Edwin Wang

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Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Cheong Hyeon Oh, Dongho Nam, Byungsik Kim

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Due to the recent climate change, flood damage caused by local floods and typhoons has frequently occurred, the incidence rate and intensity of wildfires are greatly increased due to increased temperatures and changes in precipitation patterns. Wildfires cause primary damage, such as loss of forest resources, as well as secondary disasters, such as landslides, floods, and debris flow. In many countries around the world, damage and economic losses from secondary damage are occurring as well as the direct effects of forest fires. Therefore, in this study, the Rainfall-Runoff model(S-RAT) was used for the wildfire affected areas in Gangneung and Goseong, which occurred on April 2019, when the stability of vegetation and soil were destroyed by wildfires. Rainfall data from Typhoon Rusa were used in the S-RAT model, and flood discharge was calculated according to changes in land cover before and after wildfire damage. The results of the calculation showed that flood discharge increased significantly due to changes in land cover, as the increase in flood discharge increases the possibility of the occurrence of the debris flow and the extent of the damage, the debris flow height and range were calculated before and after forest fire using RAMMS. The analysis results showed that the height and extent of damage increased after wildfire, but the result value was underestimated due to the characteristics that using DEM and maximum flood discharge of the RAMMS model. This research was supported by a grant(2017-MOIS31-004) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety (MOIS). This paper work (or document) was financially supported by Ministry of the Interior and Safety as 'Human resoure development Project in Disaster management'.

Keywords: wildfire, debris flow, land cover, rainfall-runoff meodel S-RAT, RAMMS, height

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Authors: Abolghasem Akbari

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The Natural Resources Conservation Service Curve Number (NRCS-CN) method is widely used for predicting direct runoff from rainfall. It employs the hydrologic soil groups and land use information along with period soil moisture conditions to derive NRCS-CN. This method has been well documented and available in popular rainfall-runoff models such as HEC-HMS, SWAT, SWMM and much more. Despite all benefits and advantages of this well documented and easy-to-use method, it does not take into account the effect of terrain slope and drainage area. This study aimed to first investigate the effect of slope on CN and then slope-adjusted runoff potential map is generated for Kuantan River Basin, Malaysia. The Hanng method was used to adjust CN values provided in National Handbook of Engineering and The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) version 2 is used to derive slope map with the spatial resolution of 30 m for Kuantan River Basin (KRB). The study significantly enhanced the application of GIS tools and recent advances in earth observation technology to analyze the hydrological process.

Keywords: Kuantan, ASTER-GDEM, SCS-CN, runoff

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Authors: P. M. Kundu, L. R. Singo, J. O. Odiyo

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Luvuvhu River catchment in South Africa experiences floods resulting from heavy rainfall of intensities exceeding 15 mm per hour associated with the Inter-tropical Convergence Zone (ITCZ). The generation of runoff is triggered by the rainfall intensity and soil moisture status. In this study, remote sensing and GIS techniques were used to analyze the hydrologic response to land cover changes. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method using a diffusive wave transfer model that enabled the calculation of response functions between start and end point. Flood frequency analysis was determined using theoretical probability distributions. Spatial data on land cover was obtained from multi-temporal Landsat images while data on rainfall, soil type, runoff and stream discharges was obtained by direct measurements in the field and from the Department of Water. A digital elevation model was generated from contour maps available at http://www.ngi.gov.za. The results showed that land cover changes had impacted negatively to the hydrology of the catchment. Peak discharges in the whole catchment were noted to have increased by at least 17% over the period while flood volumes were noted to have increased by at least 11% over the same period. The flood time to peak indicated a decreasing trend, in the range of 0.5 to 1 hour within the years. The synergism between remotely sensed digital data and GIS for land surface analysis and modeling was realized, and it was therefore concluded that hydrologic modeling has potential for determining the influence of changes in land cover on the hydrologic response of the catchment.

Keywords: catchment, digital elevation model, hydrological model, routing, runoff

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Authors: Dibakar Sahoo, Sridevi Gummadi

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The focus of the study is to empirically analyse the climatic impacts on foodgrain yield and its variability across seasons and altitudes in Odisha, one of the most vulnerable states in India. The study uses Just-Pope Stochastic Production function by using two-step Feasible Generalized Least Square (FGLS): mean equation estimation and variance equation estimation. The study uses the panel data on foodgrain yield, rainfall and temperature for 13 districts during the period 1984-2013. The study considers four seasons: winter (December-February), summer (March-May), Rainy (June-September) and autumn (October-November). The districts under consideration have been categorized under three altitude regions such as low (< 70 masl), middle (153-305 masl) and high (>305 masl) altitudes. The results show that an increase in the standard deviations of monthly rainfall during rainy and autumn seasons have an adversely significant impact on the mean yield of foodgrains in Odisha. The summer temperature has beneficial effects by significantly increasing mean yield as the summer season is associated with harvesting stage of Rabi crops. The changing pattern of temperature has increasing effect on the yield variability of foodgrains during the summer season, whereas it has a decreasing effect on yield variability of foodgrains during the Rainy season. Moreover, the positive expected signs of trend variable in both mean and variance equation suggests that foodgrain yield and its variability increases with time. On the other hand, a change in mean levels of rainfall and temperature during different seasons has heterogeneous impacts either harmful or beneficial depending on the altitudes. These findings imply that adaptation strategies should be tailor-made to minimize the adverse impacts of climate change and variability for sustainable development across seasons and altitudes in Odisha agriculture.

Keywords: altitude, adaptation strategies, climate change, foodgrain

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Authors: Ying Li, Zaisheng Hong, Weihong Wang

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With the rapid enlargement of the size of Chinese universities, newly built campuses are springing up everywhere in recent years. It is urged to build eco-green campus because the role of higher education institutions in the transition to a more sustainable society has been highlighted for almost three decades. On condition that a new campus is usually built on an undeveloped site, where the basic infrastructure is not completed, finding proper strategies in planning and design of the campus becomes a primary concern. Low Impact Development (LID) options have been proposed as an alternative approach to make better use of rainwater in planning and design of an undeveloped site. On the basis of analyzing the natural circumstance, geographic condition, and other relative information, four main LID approaches are coordinated in this study of Hebei Union University, which are ‘Storage’, ‘Retaining’, ‘Infiltration’ and ‘Purification’. ‘Storage’ refers to a big central lake in the campus for rainwater harvesting. ‘Retaining’ means rainwater gardens scattered in the campus, also being known as bioretention areas which mimic the naturally created pools of water, to decrease surface flow runoff. ‘Infiltration’ is designed of grassed swales, which also play a part of floodway channel. ‘Purification’ is known as either natural or artificial wetland to reduce pollutants such as nitrogen and phosphorous in the waterbody. With above mentioned measures dealing with the synthetic use of rainwater in the acid & alkali area in the coastal district, an eco-green campus construction and an ecological sustainability will be realized, which will give us more enlightenment and reference.

Keywords: newly built campus, low impact development, planning design, rainwater reuse

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Authors: H. H. Elewa, E. M. Ramadan, A. M. Nosair

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Rainfall water harvesting is considered as an important tool for overcoming water scarcity in arid and semi-arid region. Wadi Watir in the southeastern part of Sinai Peninsula is considered as one of the main and active basins in the Gulf of Aqaba drainage system. It is characterized by steep hills mainly consist of impermeable rocks, whereas the streambeds are covered by a highly permeable mixture of gravel and sand. A comprehensive approach involving the integration of geographic information systems, remote sensing and watershed modeling was followed to identify the RWH capability in this area. Eight thematic layers, viz volume of annual flood, overland flow distance, maximum flow distance, rock or soil infiltration, drainage frequency density, basin area, basin slope and basin length were used as a multi-parametric decision support system for conducting weighted spatial probability models (WSPMs) to determine the potential areas for the RWH. The WSPMs maps classified the area into five RWH potentiality classes ranging from the very low to very high. Three performed WSPMs' scenarios for W. Watir reflected identical results among their maps for the high and very high RWH potentiality classes, which are the most suitable ones for conducting surface water harvesting techniques. There is also a reasonable match with respect to the potentiality of runoff harvesting areas with a probability of moderate, low and very low among the three scenarios. WSPM results have shown that the high and very high classes, which are the most suitable for the RWH are representing approximately 40.23% of the total area of the basin. Accordingly, several locations were decided for the establishment of water harvesting dams and cisterns to improve the water conditions and living environment in the study area.

Keywords: Sinai, Wadi Watir, remote sensing, geographic information systems, watershed modeling, runoff water harvesting

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Authors: Pius Borona, Cheikh Mbow, Issa Ouedraogo

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In the Sahel, climate variability has been associated with a complex web of direct and indirect impacts. This natural phenomenon has been an impediment to agro-pastoral communities who experience uncertainty while involving in farming activities which is also their key source of livelihood. In this scenario, the role of climate variability in influencing the performance, quantity and quality of staple cereals yields, vital for food and nutrition security has been a topic of importance. This response of crops and subsequent yield variability is also a subject of immense debate due to the complexity of crop development at different stages. This complexity is further compounded by influence of slowly changing non-climatic factors. With these challenges in mind, the present paper initially explores the occurrence of climate variability at an inter annual and inter decadal level in South Burkina Faso. This is evidenced by variation of the total annual rainfall and the number of rainy days among other climatic descriptors. Further, it is shown how district-scale cereal yields in the study area including maize, sorghum and millet casually associate variably to the inter-annual variation of selected climate variables. Statistical models show that the three cereals widely depict sensitivity to the length of the growing period and total dry days in the growing season. Maize yields on the other hand relate strongly to the rainfall amount variation (R2=51.8%) showing high moisture dependence during critical growth stages. Our conclusions emphasize on adoption of efficient water utilization platforms especially those that have evidently increased yields and strengthening of forecasts dissemination.

Keywords: climate variability, cereal yields, seasonality, rain fed farming, Burkina Faso, rainfall

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Authors: Hannah Gutmann, Rick Richardson, Richard Bryant

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Intrusive memories following a traumatic event are not uncommon. However, in some individuals, these memories become maladaptive and lead to prolonged stress reactions. A seminal model of PTSD explains that aberrant processing during trauma may lead to prolonged stress reactions and intrusive memories. This model explains that elevated arousal at the time of the trauma promotes data driven processing, leading to fragmented and intrusive memories. This study investigated the role of elevated arousal on the development of intrusive memories. We measured salivary markers of arousal and investigated what impact this had on data driven processing, memory fragmentation, and subsequently, the development of intrusive memories. We assessed 100 healthy participants to understand their processing style, arousal, and experience of intrusive memories. Participants were randomised to a control or experimental condition, the latter of which was designed to increase their arousal. Based on current theory, participants in the experimental condition were expected to engage in more data driven processing and experience more intrusive memories than participants in the control condition. This research aims to shed light on the mechanisms underlying the development of intrusive memories to illustrate ways in which therapeutic approaches for PTSD may be augmented for greater efficacy.

Keywords: stress, cortisol, SAA, PTSD, intrusive memories

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Authors: Mounia El Hafyani, Khalid El Himdi

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Precipitation is one of the key variables in water resource planning. The importance of modeling wet and dry durations is a crucial pointer in engineering hydrology. The objective of this study is to model and analyze the distribution of wet and dry durations. For this purpose, the daily rainfall data from 1967 to 2017 of the Moroccan city of Kenitra’s station are used. Three models are implemented for the distribution of wet and dry durations, namely the first-order Markov chain, the second-order Markov chain, and the truncated negative binomial law. The adherence of the data to the proposed models is evaluated using Chi-square and Kolmogorov-Smirnov tests. The Akaike information criterion is applied to assess the most effective model distribution. We go further and study the law of the number of wet and dry days among k consecutive days. The calculation of this law is done through an algorithm that we have implemented based on conditional laws. We complete our work by comparing the observed moments of the numbers of wet/dry days among k consecutive days to the calculated moment of the three estimated models. The study shows the effectiveness of our approach in modeling wet and dry durations of daily precipitation.

Keywords: Markov chain, rainfall, truncated negative binomial law, wet and dry durations

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Authors: Hosam A. Shawky, Amr A. Abdel Fatah, Moustafa M. S. Abo ElFad, Abdel Hameed M. El-Aassar

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Water desalination projects based on reverse osmosis technology are being introduced in Egypt to combat drinking water shortage in remote areas. Reverse osmosis (RO) desalination is a pressure driven process. This paper focuses on the design of an integrated brackish water and seawater RO desalination and solar Photovoltaic (PV) technology. A small Mobile PV driven RO desalination plant prototype without batteries is designed and tested. Solar-driven reverse osmosis desalination can potentially break the dependence of conventional desalination on fossil fuels, reduce operational costs, and improve environmental sustainability. Moreover, the innovative features incorporated in the newly designed PV-RO plant prototype are focusing on improving the cost effectiveness of producing drinkable water in remote areas. This is achieved by maximizing energy yield through an integrated automatic single axis PV tracking system with programmed tilting angle adjustment. An autonomous cleaning system for PV modules is adopted for maximizing energy generation efficiency. RO plant components are selected so as to produce 4-5 m3/day of potable water. A basic criterion in the design of this PV-RO prototype is to produce a minimum amount of fresh water by running the plant during peak sun hours. Mobility of the system will provide potable water to isolated villages and population as well as ability to provide good drinking water to different number of people from any source that is not drinkable.

Keywords: design, reverse osmosis, photovoltaic, energy, desalination, Egypt

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Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

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To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

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Authors: Sara Zadehomidi

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Iran, a geographically arid and semi-arid country, experiences varying levels of rainfall across its territory. Five major and important rivers, namely Karun, Dez, Karkheh, Jarrahi, and Hendijan, are valuable assets of the Khuzestan province. To address various needs, including those of farmers (especially during hot seasons with no rainfall), drinking water requirements, industrial and environmental, and most importantly, electricity production, dams have been constructed on several of these rivers, with some dams still under construction. The outflow of water from dam reservoirs must be managed in a way that not only preserves the reservoir's potential effectively but also ensures the maximum revenue from electricity generation. Furthermore, it should meet the other mentioned requirements. In this study, scientific methods such as optimization using Lingo software were employed to achieve these objectives. The results, when executed and adhering to the proposed electricity production program with Lingo software, indicate a 35.7% increase in electricity sales revenue over a one-year examination period. Considering that several electricity plants are currently under construction, the importance and necessity of utilizing computer systems for expediting and optimizing the electricity generation program planning from electricity plants will become evident in the future.

Keywords: Ahvaz, electricity generation programs, Iran, optimizing

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Authors: Shahriar Sepahvand, Mohammad Ali Davarpanah

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Infections caused by Acinetobacter baumannii are among the common hospital-acquired infections that have seen an increase in antibiotic resistance in recent years. Colistin is the last treatment option against this pathogen. The aim of this study is to investigate the histopathology of BALB/C mice receiving sensitive and resistant strains of Acinetobacter baumannii to colistin. A total of 68 female laboratory mice weighing 30 to 40 grams of the BALB/C breed were studied in this research for three weeks under appropriate laboratory conditions in terms of food and environment. The experimental groups included: control group, second group, third group, fourth group. Lung, liver, spleen, and kidney tissues were removed from anesthetized mice and, after washing in physiological serum, were fixed in 10% formalin for 14 days. For dehydration, alcohol with ascending degrees of 70, 80, 90, and 100 was used. After clearing and soaking in paraffin, the samples were embedded in paraffin. Then, sections with a thickness of 5 microns were prepared and, after staining by hematoxylin-eosin, the samples were ready for study with a light microscope. In liver, spleen, lung, and kidney tissues of mice receiving the colistin-sensitive strain of Acinetobacter baumannii, infiltration of inflammatory cells and hyperemia were observed compared to control group mice. Liver and lung tissues of mice receiving strains of Acinetobacter baumannii resistant to colistin showed tissue destruction in addition to infiltration of inflammatory cells and hyperemia, with more destruction observed in lung tissue.

Keywords: acinetobacter baumannii, colistin antibiotic, histopathological examination, resistant

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