Search results for: small signal model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21372

Search results for: small signal model

10782 Evaluation of the Gamma-H2AX Expression as a Biomarker of DNA Damage after X-Ray Radiation in Angiography Patients

Authors: Reza Fardid, Aliyeh Alipour

Abstract:

Introduction: Coronary heart disease (CHD) is the most common and deadliest diseases. A coronary angiography is an important tool for the diagnosis and treatment of this disease. Because angiography is performed by exposure to ionizing radiation, it can lead to harmful effects. Ionizing radiation induces double-stranded breaks in DNA, which is a potentially life-threatening injury. The purpose of the present study is an investigation of the phosphorylation of histone H2AX in the location of the double-stranded break in Peripheral blood lymphocytes as an indication of Biological effects of radiation on angiography patients. Materials and Methods: This method is based on measurement of the phosphorylation of histone (gamma-H2AX, gH2AX) level on serine 139 after formation of DNA double-strand break. 5 cc of blood from 24 patients with angiography were sampled before and after irradiation. Blood lymphocytes were removed, fixed and were stained with specific ϒH2AX antibodies. Finally, ϒH2AX signal as an indicator of the double-strand break was measured with Flow Cytometry Technique. Results and discussion: In all patients, an increase was observed in the number of breaks in double-stranded DNA after irradiation (20.15 ± 14.18) compared to before exposure (1.52 ± 0.34). Also, the mean of DNA double-strand break was showed a linear correlation with DAP. However, although induction of DNA double-strand breaks associated with radiation dose in patients, the effect of individual factors such as radiosensitivity and regenerative capacity should not be ignored. If in future we can measure DNA damage response in every patient angiography and it will be used as a biomarker patient dose, will look very impressive on the public health level. Conclusion: Using flow cytometry readings which are done automatically, it is possible to detect ϒH2AX in the number of blood cells. Therefore, the use of this technique could play a significant role in monitoring patients.

Keywords: coronary angiography, DSB of DNA, ϒH2AX, ionizing radiation

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10781 First Record of Eotragus noyei from the Middle Siwalik Dhok Pathan Formation of Pakistan

Authors: Abdul M. Khan, Hafiza I. Naz, Ayesha Iqbal, Muhammad Akhtar

Abstract:

The fossil remains described in this study have been recovered during fieldwork by the authors from the Dhok Pathan Formation of Middle Siwaliks Pakistan in December, 2015. The sample comprises maxillary and mandibular fragments along with isolated upper and lower teeth. The morphometric analysis of the specimens led us to recognize the sample as belonging to Eotragus noyei, which has been considered as the smallest and the oldest bovid in the Siwaliks. Eotragus noyei is characterized by brachydont teeth, finely rugose enamel, more inclined buccal walls of the molars and small lingual cingula. The inclination of the metaconal area has caused rotation of the metastyle in relation to the antero-posterior tooth axis and thus situated more lingually. The protocone in second upper premolar is well developed and situated posteriorly and also has an anterior lingual constriction. The metaconule in the third upper molar is smaller than the protocone. The dentition in Eotragus noyei is smaller in size as compared to Eotragus sansaniensis and Eotragus lampangensis. In Eotragus noyei the buccal walls in molars are more inclined while in Eotragus sansaniensis they are less inclined. The genus Eotragus has been reported previously in the Lower and Middle Siwaliks of Pakistan; however, the recognition of the present sample as Eotragus noyei has extended the range of this species from Lower to the Middle Siwaliks of Pakistan.

Keywords: Boselaphini, Chakwal, Dhok Pathan, late miocene

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10780 Exaptive Urbanism: Evolutionary Biology and the Regeneration of Mumbai’s Dhobighat

Authors: Piyush Bajpai, Sneha Pandey

Abstract:

Mumbai’s Dhobighat, 150 year old largest open laundry in the world, is the true live-work place and only source of income for some of Mumbai’s highest density ‘urban poor’ residents. The regeneration of Dhobighat, due to its ultra prime location and complex socio-political culture has been a complex issue. This once flourishing urban industrial core has been degrading for the past several decades mainly due to the decline of the open laundry business, the site’s over burdened infrastructure and conflicting socio-political and economic forces. The phenomena of ‘exaptation’ or ‘co-option’ has been observed by evolutionary biologists as a process responsible for producing highly tenacious and resilient offsprings within a species. The reddish egret uses its wings to cast shadow in shallow waters to attract small fish and hunt them. An unrelated feature used opportunistically to produce a very favorable result. How can this idea of co-option be applied to resolve the complex issue of Dhobighat’s regeneration? Our paper proposes a new methodology/approach for the regeneration of Dhobighat through the lens of evolutionary biology. Forces and systems (social, political, economic, cultural and ecological) that seem conflicting or unrelated by nature are opportunistically transformed into symbiotic and complimentary relationships that produce an inclusive, resilient and holistic solution for the regeneration of Dhobighat.

Keywords: urban regeneration, exaptation, resilience, Dhobighat, Mumbai

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10779 Rapid Start-Up and Efficient Long-Term Nitritation of Low Strength Ammonium Wastewater with a Sequencing Batch Reactor Containing Immobilized Cells

Authors: Hammad Khan, Wookeun Bae

Abstract:

Major concerns regarding nitritation of low-strength ammonium wastewaters include low ammonium loading rates (usually below 0.2 kg/m3-d) and uncertainty about long-term stability of the process. The purpose of this study was to test a sequencing batch reactor (SBR) filled with cell-immobilized polyethylene glycol (PEG) pellets to see if it could achieve efficient and stable nitritation under various environmental conditions. SBR was fed with synthetic ammonium wastewater of 30±2 mg-N/L and pH: 8±0.05, maintaining the dissolved oxygen concentration of 1.7±0.2 mg/L and the temperature at 30±1oC. The reaction was easily converted to partial nitrification mode within a month by feeding relatively high ammonium substrate (~100 mg-N/L) in the beginning. We observed stable nitritation over 300 days with high ammonium loading rates (as high as ~1.1 kg-N/m3-d), nitrite accumulation rates (mostly over 97%) and ammonium removal rate (mostly over 95%). DO was a major limiting substrate when the DO concentration was below ~4 mg/L and the NH4+-N concentration was above 5 mg/L, giving almost linear increase in the ammonium oxidation rate with the bulk DO increase. Low temperatures mainly affected the reaction rate, which could be compensated for by increasing the pellet volume (i.e. biomass). Our results demonstrated that an SBR filled with small cell-immobilized PEG pellets could achieve very efficient and stable nitritation of a low-strength ammonium wastewater.

Keywords: ammonium loading rate (ALR), cell-immobilization, long-term nitritation, sequencing batch reactor (SBR), sewage treatment

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10778 Understanding the Endogenous Impact of Tropical Cyclones Floods and Sustainable Landscape Management Innovations on Farm Productivity in Malawi

Authors: Innocent Pangapanga, Eric Mungatana

Abstract:

Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

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10777 Sensing Mechanism of Nano-Toxic Ions Using Quartz Crystal Microbalance

Authors: Chanho Park, Juneseok You, Kuewhan Jang, Sungsoo Na

Abstract:

Detection technique of nanotoxic materials is strongly imperative, because nano-toxic materials can harmfully influence human health and environment as their engineering applications are growing rapidly in recent years. In present work, we report the DNA immobilized quartz crystal microbalance (QCM) based sensor for detection of nano-toxic materials such as silver ions, Hg2+ etc. by using functionalization of quartz crystal with a target-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz crystal is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated fast and in situ detection of nanotoxic materials using quartz crystal microbalance. We report the label-free and highly sensitive detection of silver ion for present case, which is a typical nano-toxic material by using QCM and silver-specific DNA. The detection is based on the measurement of frequency shift of Quartz crystal from constitution of the cytosine-Ag+-cytosine binding. It is shown that the silver-specific DNA measured frequency shift by QCM enables the capturing of silver ions below 100pM. The results suggest that DNA-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nano-toxic ions, quartz crystal microbalance, frequency shift, target-specific DNA

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10776 Complicating Representations of Domestic Violence Perpetration through a Qualitative Content Analysis and Socio-Ecological Approach

Authors: Charlotte Lucke

Abstract:

This study contributes to the body of literature that analyzes and complicates oversimplified and sensationalized representations of trauma and violence through a close examination and complication of representations of perpetrators of domestic violence in the mass media. This study determines the ways the media frames perpetrators of domestic violence through a qualitative content analysis and socio-ecological approach to the perpetration of violence. While the qualitative analysis has not been carried out, through preliminary research, this study hypothesizes that the media represents perpetrators through tropes such as the 'predator' or 'offender,' or as a demonized 'other.' It is necessary to expose and work through such stereotypes because cultivation theory demonstrates that the mass media determines societal beliefs about and perceptions of the world. Thus, representations of domestic violence in the mass media can lead people to believe that perpetrators of violence are mere animals or criminals and overlook the trauma that many perpetrators experience. When the media represents perpetrators as pure evil, monsters, or absolute 'others,' it leaves out the complexities of what moves people to commit domestic violence. By analyzing and placing media representations of perpetrators into conversation with the socio-ecological approach to violence perpetration, this study complicates domestic violence stereotypes. The socio-ecological model allows researchers to consider the way the interplay between individuals and their families, friends, communities, and cultures can move people to act violently. Using this model, along with psychological and psychoanalytic approaches to the etiology of domestic violence, this paper argues that media stereotypes conceal the way people’s experiences of trauma, along with community and cultural norms, perpetuates the cycle of systemic trauma and violence in the home.

Keywords: domestic violence, media images, representing trauma, theorising trauma

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10775 Cellular Uptake and Endocytosis of Doxorubicin Loaded Methoxy Poly (Ethylene Glycol)-Block-Poly (Glutamic Acid) [DOX/mPEG-b-PLG] Nanoparticles against Human Breast Cancer Cell Lines

Authors: Zaheer Ahmad, Afzal Shah

Abstract:

pH responsive block copolymers consist of mPEG and glutamic acid units were syntheiszed in different formulations. The synthesized polymers were structurally investigated. Doxorubicin Hydrocholide (DOX-HCl) as a chemotherapy medication for the treatment of cancer was selected. DOX-HCl was loaded and their drug loading content and drug loading efficiency were determined. The nanocarriers were obtained in small size, well shaped and slightly negative surface charge. The release study was carried out both at pH 7.4 and 5.5 and it was revealed that the release was sustained and in controlled manner and there was no initial burst release. The in vitro release study was further carried out for different formulations with different glutamic acid moieties. Time dependent cell proliferation inhibition of the free drug and drug loaded nanoparticles against human breast cancer cell lines MCF-7 and Zr-75-30 was observed. Cellular uptakes and endocytosis were investigated by confocal laser scanning microscopy (CLSM) and flow cytometery. The biocompatibility, optimum size, shape and surface charge of the developed nanoparticles make the nanoparticles an efficient drug delivery carrier.

Keywords: doxorubicin, glutamic acid, cell proliferation inhibition, breast cancer cell

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10774 Research on Urban Design Method of Ancient City Guided by Catalyst Theory

Authors: Wang Zhiwei, Wang Weiwu

Abstract:

The process of urbanization in China has entered a critical period of transformation from urban expansion and construction to delicate urban design, thus forming a new direction in the field of urban design. So far, catalyst theory has become a prominent guiding strategy in urban planning and design. In this paper, under the background of urban renewal, catalyst theory is taken as the guiding ideology to explore the method of urban design in shouxian county. Firstly, this study briefly introduces and analyzes the catalyst theory. Through field investigation, it is found that the city has a large number of idle Spaces, such as abandoned factories and schools. In the design, the idle Spaces in the county town are utilized and interlinked in space, and functional interaction is carried out from the pattern of the county town. On the one hand, the results showed that the catalyst theory can enhance the vitality of the linear street space with a small amount of monomer construction. On the other hand, the city can also increase the cultural and economic sites of the city without damaging the historical relics and the sense of alterations of the ancient city, to improve the quality of life and quality of life of citizens. The city micro-transformation represented by catalyst theory can help ancient cities like shouxian to realize the activation of the old city and realize the gradual development.

Keywords: catalytic theory, urban design, China's ancient city, Renaissance

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10773 Effects of Different Dietary Crude Fiber Levels on the Growth Performance of Finishing Su-Shan Pigs

Authors: Li Bixia, Ren Shouwen, Fu Yanfeng, Tu Feng, Xiaoming Fang, Xueming Wang

Abstract:

The utilization of dietary crude fiber in different breed pigs is not the same. Su-shan pigs are a new breed formed by crossing Taihu pigs and Yorkshire pigs. In order to understand the resistance of Su-shan pigs to dietary crude fiber, 150 Su-shan pigs with 60 kg of average body weight and similar body conditions were allocated to three groups randomly, and there are 50 pigs in each group. The percentages of dietary crude fiber were 8.35%, 9.10%, and 11.39%, respectively. At the end of the experiment, 15 pigs randomly selected from each group were slaughtered. The results showed as follows: average daily gain of the 9.10% group was higher than that of the 8.35% group and the 11.39% group; there was a significant difference between the 9.10% group and the 8.35% group (p < 0.05. Levels of urea nitrogen, total cholesterol and high density lipoprotein in the 9.10% group were significantly higher than those in the 8.35% group and the 11.39% group (p < 0.05). Ratios of meat to fat in the 9.10% group and the 11.39% group were significantly higher than that in the 8.35% group (p < 0.05). Lean percentage of 9.10% group was higher than that of 8.35% group and 11.39% group, but there was no significant difference in three groups (p > 0.05). The weight of small intestine and large intestine in the 11.39% group was higher than that in the 8.35% group, and the 9.10% group and the difference reached a significant level (p < 0.05). In conclusion, increasing dietary crude fiber properly could reduce fat percentage, and improve the ratio of meat to fat of finishing Su-shan pigs. The digestion and metabolism of dietary crude fiber promoted the development of stomach and intestine of finishing Su-shan pig.

Keywords: Su-shan pigs, dietary crude fiber, growth performance, serum biochemical indexes

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10772 Electronic Spectral Function of Double Quantum Dots–Superconductors Nanoscopic Junction

Authors: Rajendra Kumar

Abstract:

We study the Electronic spectral density of a double coupled quantum dots sandwich between superconducting leads, where one of the superconducting leads (QD1) are connected with left superconductor lead and (QD1) also connected right superconductor lead. (QD1) and (QD2) are coupling to each other. The electronic spectral density through a quantum dots between superconducting leads having s-wave symmetry of the superconducting order parameter. Such junction is called superconducting –quantum dot (S-QD-S) junction. For this purpose, we have considered a renormalized Anderson model that includes the double coupled of the superconducting leads with the quantum dots level and an attractive BCS-type effective interaction in superconducting leads. We employed the Green’s function technique to obtain superconducting order parameter with the BCS framework and Ambegaoker-Baratoff formalism to analyze the electronic spectral density through such (S-QD-S) junction. It has been pointed out that electronic spectral density through such a junction is dominated by the attractive the paring interaction in the leads, energy of the level on the dot with respect to Fermi energy and also on the coupling parameter of the two in an essential way. On the basis of numerical analysis we have compared the theoretical results of electronic spectral density with the recent transport existing theoretical analysis. QDs is the charging energy that may give rise to effects based on the interplay of Coulomb repulsion and superconducting correlations. It is, therefore, an interesting question to ask how the discrete level spectrum and the charging energy affect the DC and AC Josephson transport between two superconductors coupled via a QD. In the absence of a bias voltage, a finite DC current can be sustained in such an S-QD-S by the DC Josephson effect.

Keywords: quantum dots, S-QD-S junction, BCS superconductors, Anderson model

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10771 Development of Methods for Plastic Injection Mold Weight Reduction

Authors: Bita Mohajernia, R. J. Urbanic

Abstract:

Mold making techniques have focused on meeting the customers’ functional and process requirements; however, today, molds are increasing in size and sophistication, and are difficult to manufacture, transport, and set up due to their size and mass. Presently, mold weight saving techniques focus on pockets to reduce the mass of the mold, but the overall size is still large, which introduces costs related to the stock material purchase, processing time for process planning, machining and validation, and excess waste materials. Reducing the overall size of the mold is desirable for many reasons, but the functional requirements, tool life, and durability cannot be compromised in the process. It is proposed to use Finite Element Analysis simulation tools to model the forces, and pressures to determine where the material can be removed. The potential results of this project will reduce manufacturing costs. In this study, a light weight structure is defined by an optimal distribution of material to carry external loads. The optimization objective of this research is to determine methods to provide the optimum layout for the mold structure. The topology optimization method is utilized to improve structural stiffness while decreasing the weight using the OptiStruct software. The optimized CAD model is compared with the primary geometry of the mold from the NX software. Results of optimization show an 8% weight reduction while the actual performance of the optimized structure, validated by physical testing, is similar to the original structure.

Keywords: finite element analysis, plastic injection molding, topology optimization, weight reduction

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10770 Assessment of Landfill Pollution Load on Hydroecosystem by Use of Heavy Metal Bioaccumulation Data in Fish

Authors: Gintarė Sauliutė, Gintaras Svecevičius

Abstract:

Landfill leachates contain a number of persistent pollutants, including heavy metals. They have the ability to spread in ecosystems and accumulate in fish which most of them are classified as top-consumers of trophic chains. Fish are freely swimming organisms; but perhaps, due to their species-specific ecological and behavioral properties, they often prefer the most suitable biotopes and therefore, did not avoid harmful substances or environments. That is why it is necessary to evaluate the persistent pollutant dispersion in hydroecosystem using fish tissue metal concentration. In hydroecosystems of hybrid type (e.g. river-pond-river) the distance from the pollution source could be a perfect indicator of such a kind of metal distribution. The studies were carried out in the Kairiai landfill neighboring hybrid-type ecosystem which is located 5 km east of the Šiauliai City. Fish tissue (gills, liver, and muscle) metal concentration measurements were performed on two types of ecologically-different fishes according to their feeding characteristics: benthophagous (Gibel carp, roach) and predatory (Northern pike, perch). A number of mathematical models (linear, non-linear, using log and other transformations) have been applied in order to identify the most satisfactorily description of the interdependence between fish tissue metal concentration and the distance from the pollution source. However, the only one log-multiple regression model revealed the pattern that the distance from the pollution source is closely and positively correlated with metal concentration in all predatory fish tissues studied (gills, liver, and muscle).

Keywords: bioaccumulation in fish, heavy metals, hydroecosystem, landfill leachate, mathematical model

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10769 Count of Trees in East Africa with Deep Learning

Authors: Nubwimana Rachel, Mugabowindekwe Maurice

Abstract:

Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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10768 An Acerbate Psychotics Symptoms, Social Support, Stressful Life Events, Medication Use Self-Efficacy Impact on Social Dysfunction: A Cross Sectional Self-Rated Study of Persons with Schizophrenia Patient and Misusing Methamphetamines

Authors: Ek-Uma Imkome, Jintana Yunibhand, Waraporn Chaiyawat

Abstract:

Background: Persons with schizophrenia patient and misusing methamphetamines suffering from social dysfunction that impact on their quality of life. Knowledge of factors related to social dysfunction will guide the effective intervention. Objectives: To determine the direct effect, indirect effect and total effect of an acerbate Psychotics’ Symptoms, Social Support, Stressful life events, Medication use self-efficacy impact on social dysfunction in Thai schizophrenic patient and methamphetamine misuse. Methods: Data were collected from schizophrenic and methamphetamine misuse patient by self report. A linear structural relationship was used to test the hypothesized path model. Results: The hypothesized model was found to fit the empirical data and explained 54% of the variance of the psychotic symptoms (X2 = 114.35, df = 92, p-value = 0.05, X2 /df = 1.24, GFI = 0.96, AGFI = 0.92, CFI = 1.00, NFI = 0.99, NNFI = 0.99, RMSEA = 0.02). The highest total effect on social dysfunction was psychotic symptoms (0.67, p<0.05). Medication use self-efficacy had a direct effect on psychotic symptoms (-0.25, p<0.01), and social support had direct effect on medication use self efficacy (0.36, p <0.01). Conclusions: Psychotic symptoms and stressful life events were the significance factors that influenced direct on social dysfunctioning. Therefore, interventions that are designed to manage these factors are crucial in order to enhance social functioning in this population.

Keywords: psychotic symptoms, methamphetamine, schizophrenia, stressful life events, social dysfunction, social support, medication use self efficacy

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10767 Land Suitability Prediction Modelling for Agricultural Crops Using Machine Learning Approach: A Case Study of Khuzestan Province, Iran

Authors: Saba Gachpaz, Hamid Reza Heidari

Abstract:

The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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10766 Experimental Study of Complete Loss of Coolant Flow (CLOF) Test by System–Integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL) with Passive Residual Heat Removal System (PRHRS)

Authors: Jin Hwa Yang, Hwang Bae, Sung Uk Ryu, Byong Guk Jeon, Sung Jae Yi, Hyun Sik Park

Abstract:

Experimental studies using a large-scale thermal-hydraulic integral test facility, System–integrated Modular Advanced Reactor Integral Test Loop (SMART-ITL), have been carried out to validate the performance of the prototype, SMART. After Fukushima accident, the passive safety systems have been dealt as important designs for retaining of nuclear safety. One of the concerned scenarios for evaluating the passive safety system is a Complete Loss of Coolant Flow (CLOF). The flowrate of coolant in the primary system is maintained by Reactor Coolant Pump (RCP). When the supply of electric power of RCP is shut off, the flowrate of coolant decreases sharply, and the temperature of the coolant increases rapidly. Therefore, the reactor trip signal is activated to prevent the over-heating of the core. In this situation, Passive Residual Heat Removal System (PRHRS) plays a significant role to assure the soundness of the SMART. The PRHRS using a two-phase natural circulation is a passive safety system in the SMART to eliminate the heat of steam generator in the secondary system with heat exchanger submarined in the Emergency Cooling Tank (ECT). As the RCPs continue to coast down, inherent natural circulation in the primary system transfers heat to the secondary system. The transferred heat is removed by PRHRS in the secondary system. In this paper, the progress of the CLOF accident is described with experimental data of transient condition performed by SMART-ITL. Finally, the capability of passive safety system and inherent natural circulation will be evaluated.

Keywords: CLOF, natural circulation, PRHRS, SMART-ITL

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10765 Toward the Decarbonisation of EU Transport Sector: Impacts and Challenges of the Diffusion of Electric Vehicles

Authors: Francesca Fermi, Paola Astegiano, Angelo Martino, Stephanie Heitel, Michael Krail

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In order to achieve the targeted emission reductions for the decarbonisation of the European economy by 2050, fundamental contributions are required from both energy and transport sectors. The objective of this paper is to analyse the impacts of a largescale diffusion of e-vehicles, either battery-based or fuel cells, together with the implementation of transport policies aiming at decreasing the use of motorised private modes in order to achieve greenhouse gas emission reduction goals, in the context of a future high share of renewable energy. The analysis of the impacts and challenges of future scenarios on transport sector is performed with the ASTRA (ASsessment of TRAnsport Strategies) model. ASTRA is a strategic system-dynamic model at European scale (EU28 countries, Switzerland and Norway), consisting of different sub-modules related to specific aspects: the transport system (e.g. passenger trips, tonnes moved), the vehicle fleet (composition and evolution of technologies), the demographic system, the economic system, the environmental system (energy consumption, emissions). A key feature of ASTRA is that the modules are linked together: changes in one system are transmitted to other systems and can feed-back to the original source of variation. Thanks to its multidimensional structure, ASTRA is capable to simulate a wide range of impacts stemming from the application of transport policy measures: the model addresses direct impacts as well as second-level and third-level impacts. The simulation of the different scenarios is performed within the REFLEX project, where the ASTRA model is employed in combination with several energy models in a comprehensive Modelling System. From the transport sector perspective, some of the impacts are driven by the trend of electricity price estimated from the energy modelling system. Nevertheless, the major drivers to a low carbon transport sector are policies related to increased fuel efficiency of conventional drivetrain technologies, improvement of demand management (e.g. increase of public transport and car sharing services/usage) and diffusion of environmentally friendly vehicles (e.g. electric vehicles). The final modelling results of the REFLEX project will be available from October 2018. The analysis of the impacts and challenges of future scenarios is performed in terms of transport, environmental and social indicators. The diffusion of e-vehicles produces a consistent reduction of future greenhouse gas emissions, although the decarbonisation target can be achieved only with the contribution of complementary transport policies on demand management and supporting the deployment of low-emission alternative energy for non-road transport modes. The paper explores the implications through time of transport policy measures on mobility and environment, underlying to what extent they can contribute to a decarbonisation of the transport sector. Acknowledgements: The results refer to the REFLEX project which has received grants from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 691685.

Keywords: decarbonisation, greenhouse gas emissions, e-mobility, transport policies, energy

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10764 Influence of Foundation Size on Seismic Response of Mid-rise Buildings Considering Soil-Structure-Interaction

Authors: Quoc Van Nguyen, Behzad Fatahi, Aslan S. Hokmabadi

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Performance based seismic design is a modern approach to earthquake-resistant design shifting emphasis from “strength” to “performance”. Soil-Structure Interaction (SSI) can influence the performance level of structures significantly. In this paper, a fifteen storey moment resisting frame sitting on a shallow foundation (footing) with different sizes is simulated numerically using ABAQUS software. The developed three dimensional numerical simulation accounts for nonlinear behaviour of the soil medium by considering the variation of soil stiffness and damping as a function of developed shear strain in the soil elements during earthquake. Elastic-perfectly plastic model is adopted to simulate piles and structural elements. Quiet boundary conditions are assigned to the numerical model and appropriate interface elements, capable of modelling sliding and separation between the foundation and soil elements, are considered. Numerical results in terms of base shear, lateral deformations, and inter-storey drifts of the structure are compared for the cases of soil-structure interaction system with different foundation sizes as well as fixed base condition (excluding SSI). It can be concluded that conventional design procedures excluding SSI may result in aggressive design. Moreover, the size of the foundation can influence the dynamic characteristics and seismic response of the building due to SSI and should therefore be given careful consideration in order to ensure a safe and cost effective seismic design.

Keywords: soil-structure-interaction, seismic response, shallow foundation, abaqus, rayleigh damping

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10763 Rock Slope Stabilization and Protection for Roads and Multi-Storey Structures in Jabal Omar, Saudi Arabia

Authors: Ibrahim Abdel Gadir Malik, Dafalla Siddig Dafalla, Abdelazim Ibrahim

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Jabal Omar is located in the western side of Makkah city in Saudi Arabia. The proposed Jabal Omar Development project includes several multi-storey buildings, roads, bridges and below ground structures founded at various depths. In this study, geological mapping and site inspection which covered pre-selected areas were carried out within the easily accessed parts. Geological features; including rock types, structures, degree of weathering, and geotechnical hazards were observed and analyzed with specified software and also were documented in form of photographs. The presence of joints and fractures in the area made the rock blocks small and weak. The site is full of jointing; it was observed that, the northern side consists of 3 to 4 jointing systems with 2 random fractures associated with dykes. The southern part is affected by 2 to 3 jointing systems with minor fault and shear zones. From the field measurements and observations, it was concluded that, the Jabal Omar intruded by andesitic and basaltic dykes of different thickness and orientation. These dykes made the outcrop weak, highly deformed and made the rock masses sensitive to weathering.

Keywords: rock, slope, stabilization, protection, Makkah

Procedia PDF Downloads 796
10762 Load Balancing Technique for Energy - Efficiency in Cloud Computing

Authors: Rani Danavath, V. B. Narsimha

Abstract:

Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

Procedia PDF Downloads 434
10761 Evaluating Traffic Congestion Using the Bayesian Dirichlet Process Mixture of Generalized Linear Models

Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

Abstract:

This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

Procedia PDF Downloads 280
10760 Evaluation of Machine Learning Algorithms and Ensemble Methods for Prediction of Students’ Graduation

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

Abstract:

Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

Procedia PDF Downloads 62
10759 Automated Building Internal Layout Design Incorporating Post-Earthquake Evacuation Considerations

Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu

Abstract:

Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.

Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior

Procedia PDF Downloads 85
10758 A User Interface for Easiest Way Image Encryption with Chaos

Authors: D. López-Mancilla, J. M. Roblero-Villa

Abstract:

Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

Procedia PDF Downloads 473
10757 Antioxidant Effects of C-Phycocyanin on Oxidized Astrocyte in Brain Injury Using 2D and 3D Neural Nanofiber Tissue Model

Authors: Seung Ju Yeon, Seul Ki Min, Jun Sang Park, Yeo Seon Kwon, Hoo Cheol Lee, Hyun Jung Shim, Il-Doo Kim, Ja Kyeong Lee, Hwa Sung Shin

Abstract:

In brain injury, depleting oxidative stress is the most effective way to reduce the brain infarct size. C-phycocyanin (C-Pc) is a well-known antioxidant protein that has neuroprotective effects obtained from green microalgae. Astrocyte is glial cell that supports the nerve cell such as neuron, which account for a large portion of the brain. In brain injury, such as ischemia and reperfusion, astrocyte has an important rule that overcomes the oxidative stress and protect from brain reactive oxygen species (ROS) injury. However little is known about how C-Pc regulates the anti-oxidants effects of astrocyte. In this study, when the C-Pc was treated in oxidized astrocyte, we confirmed that inflammatory factors Interleukin-6 and Interleukin-3 were increased and antioxidants enzyme, Superoxide dismutase (SOD) and catalase was upregulated, and neurotrophic factors, brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) was alleviated. Also, it was confirmed to reduce infarct size of the brain in ischemia and reperfusion because C-Pc has anti-oxidant effects in middle cerebral artery occlusion (MCAO) animal model. These results show that C-Pc can help astrocytes lead neuroprotective activities in the oxidative stressed environment of the brain. In summary, the C-PC protects astrocytes from oxidative stress and has anti-oxidative, anti-inflammatory, neurotrophic effects under ischemic situations.

Keywords: c-phycocyanin, astrocyte, reactive oxygen species, ischemia and reperfusion, neuroprotective effect

Procedia PDF Downloads 302
10756 The System Dynamics Research of China-Africa Trade, Investment and Economic Growth

Authors: Emma Serwaa Obobisaa, Haibo Chen

Abstract:

International trade and outward foreign direct investment are important factors which are generally recognized in the economic growth and development. Though several scholars have struggled to reveal the influence of trade and outward foreign direct investment (FDI) on economic growth, most studies utilized common econometric models such as vector autoregression and aggregated the variables, which for the most part prompts, however, contradictory and mixed results. Thus, there is an exigent need for the precise study of the trade and FDI effect of economic growth while applying strong econometric models and disaggregating the variables into its separate individual variables to explicate their respective effects on economic growth. This will guarantee the provision of policies and strategies that are geared towards individual variables to ensure sustainable development and growth. This study, therefore, seeks to examine the causal effect of China-Africa trade and Outward Foreign Direct Investment on the economic growth of Africa using a robust and recent econometric approach such as system dynamics model. Our study impanels and tests an ensemble of a group of vital variables predominant in recent studies on trade-FDI-economic growth causality: Foreign direct ınvestment, international trade and economic growth. Our results showed that the system dynamics method provides accurate statistical inference regarding the direction of the causality among the variables than the conventional method such as OLS and Granger Causality predominantly used in the literature as it is more robust and provides accurate, critical values.

Keywords: economic growth, outward foreign direct investment, system dynamics model, international trade

Procedia PDF Downloads 93
10755 Convertible Lease, Risky Debt and Financial Structure with Growth Option

Authors: Ons Triki, Fathi Abid

Abstract:

The basic objective of this paper is twofold. It resides in designing a model for a contingent convertible lease contract that can ensure the financial stability of a company and recover the losses of the parties to the lease in the event of default. It also aims to compare the convertible lease contract on inefficiencies resulting from the debt-overhang problem and asset substitution with other financing policies. From this perspective, this paper highlights the interaction between investments and financing policies in a dynamic model with existing assets and a growth option where the investment cost is financed by a contingent convertible lease and equity. We explore the impact of the contingent convertible lease on the capital structure. We also check the reliability and effectiveness of the use of the convertible lease contract as a means of financing. Findings show that the rental convertible contract with a sufficiently high conversion ratio has less severe inefficiencies arising from risk-shifting and debt overhang than those entailed by risky debt and pure-equity financing. The problem of underinvestment pointed out by Mauer and Ott (2000) and the problem of overinvestment mentioned by Hackbarth and Mauer (2012) may be reduced under contingent convertible lease financing. Our findings predict that the firm value under contingent convertible lease financing increases globally with asset volatility instead of decreasing with business risk. The study reveals that convertible leasing contracts can stand for a reliable solution to ensure the lessee and quickly recover the counterparties of the lease upon default.

Keywords: contingent convertible lease, growth option, debt overhang, risk-shifting, capital structure

Procedia PDF Downloads 57
10754 Design Optimization of Miniature Mechanical Drive Systems Using Tolerance Analysis Approach

Authors: Eric Mxolisi Mkhondo

Abstract:

Geometrical deviations and interaction of mechanical parts influences the performance of miniature systems.These deviations tend to cause costly problems during assembly due to imperfections of components, which are invisible to a naked eye.They also tend to cause unsatisfactory performance during operation due to deformation cause by environmental conditions.One of the effective tools to manage the deviations and interaction of parts in the system is tolerance analysis.This is a quantitative tool for predicting the tolerance variations which are defined during the design process.Traditional tolerance analysis assumes that the assembly is static and the deviations come from the manufacturing discrepancies, overlooking the functionality of the whole system and deformation of parts due to effect of environmental conditions. This paper presents an integrated tolerance analysis approach for miniature system in operation.In this approach, a computer-aided design (CAD) model is developed from system’s specification.The CAD model is then used to specify the geometrical and dimensional tolerance limits (upper and lower limits) that vary component’s geometries and sizes while conforming to functional requirements.Worst-case tolerances are analyzed to determine the influenced of dimensional changes due to effects of operating temperatures.The method is used to evaluate the nominal conditions, and worse case conditions in maximum and minimum dimensions of assembled components.These three conditions will be evaluated under specific operating temperatures (-40°C,-18°C, 4°C, 26°C, 48°C, and 70°C). A case study on the mechanism of a zoom lens system is used to illustrate the effectiveness of the methodology.

Keywords: geometric dimensioning, tolerance analysis, worst-case analysis, zoom lens mechanism

Procedia PDF Downloads 154
10753 Biotechnological Recycling of Apple By-Products: A Reservoir Model to Produce a Dietary Supplement Fortified with Biogenic Phenolic Compounds

Authors: Ali Zein Aalabiden Tlais, Alessio Da Ros, Pasquale Filannino, Olimpia Vincentini, Marco Gobbetti, Raffaella Di Cagno

Abstract:

This study is an example of apple by-products (AP) recycling through a designed fermentation by selected autochthonous Lactobacillus plantarum AFI5 and Lactobacillus fabifermentans ALI6 used singly or as binary cultures with the selected Saccharomyces cerevisiae AYI7. Compared to Raw-, Unstarted- and Chemically Acidified-AP, Fermented-AP promoted the highest levels of total and insoluble dietary fibers, antioxidant activity, and free phenolics. The binary culture of L. plantarum AFI5 and S. cerevisiae AYI7 had the best effect on the bioavailability phenolic compounds as resulted by the Liquid chromatography-mass spectrometry validated method. The accumulation of phenolic acid derivatives highlighted microbial metabolism during AP fermentation. Bio-converted phenolic compounds were likely responsible for the increased antioxidant activity. The potential health-promoting effects of Fermented-AP were highlighted using Caco-2 cells. With variations among single and binary cultures, fermented-AP counteracted the inflammatory processes and the effects of oxidative stress in Caco-2 cells and preserved the integrity of tight junctions. An alternative and suitable model for food by-products recycling to manufacture a dietary supplement fortified with biogenic compounds was proposed. Highlighting the microbial metabolism of several phenolic compounds, undoubted additional value to such downstream wastes was created.

Keywords: apple by-products, antioxidant, fermentation, phenolic compounds

Procedia PDF Downloads 123