Search results for: artificial potential function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17302

Search results for: artificial potential function

15892 Targeting APP IRE mRNA to Combat Amyloid -β Protein Expression in Alzheimer’s Disease

Authors: Mateen A Khan, Taj Mohammad, Md. Imtaiyaz Hassan

Abstract:

Alzheimer’s disease is characterized by the accumulation of the processing products of the amyloid beta peptide cleaved by amyloid precursor protein (APP). Iron increases the synthesis of amyloid beta peptides, which is why iron is present in Alzheimer's disease patients' amyloid plaques. Iron misregulation in the brain is linked to the overexpression of APP protein, which is directly related to amyloid-β aggregation in Alzheimer’s disease. The APP 5'-UTR region encodes a functional iron-responsive element (IRE) stem-loop that represents a potential target for modulating amyloid production. Targeted regulation of APP gene expression through the modulation of 5’-UTR sequence function represents a novel approach for the potential treatment of AD because altering APP translation can be used to improve both the protective brain iron balance and provide anti-amyloid efficacy. The molecular docking analysis of APP IRE RNA with eukaryotic translation initiation factors yields several models exhibiting substantial binding affinity. The finding revealed that the interaction involved a set of functionally active residues within the binding sites of eIF4F. Notably, APP IRE RNA and eIF4F interaction were stabilized by multiple hydrogen bonds with residues of APP IRE RNA and eIF4F. It was evident that APP IRE RNA exhibited a structural complementarity that tightly fit within binding pockets of eIF4F. The simulation studies further revealed the stability of the complexes formed between RNA and eIF4F, which is crucial for assessing the strength of these interactions and subsequent roles in the pathophysiology of Alzheimer’s disease. In addition, MD simulations would capture conformational changes in the IRE RNA and protein molecules during their interactions, illustrating the mechanism of interaction, conformational change, and unbinding events and how it may affect aggregation propensity and subsequent therapeutic implications. Our binding studies correlated well with the translation efficiency of APP mRNA. Overall, the outcome of this study suggests that the genomic modification and/or inhibiting the expression of amyloid protein by targeting APP IRE RNA can be a viable strategy to identify potential therapeutic targets for AD and subsequently be exploited for developing novel therapeutic approaches.

Keywords: Alzheimer's disease, Protein-RNA interaction analysis, molecular docking simulations, conformational dynamics, binding stability, binding kinetics, protein synthesis.

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15891 Achieving Sustainable Tourism in a Country in Transition: The Case of Myanmar

Authors: Patrick Strefford, Michael Davies, Masahiko Iguchi

Abstract:

The Sustainable Development Goals (SDGs) were adopted in 2015 to end poverty, protect the planet, and ensure prosperity for all. Sustainable tourism is firmly positioned in these Goals, since tourism has significant potential to contribute to inclusive and sustainable economic growth, as well as to promote sustainable use of natural capital. Recognizing this, the new quasi-democratic government of Myanmar has embraced Sustainable Tourism as a core component of its economic reforms and opening up of the country. However, it is also highly likely that the Democrats within the government also support Sustainable Tourism as a potential contributor to the democratization of the country. This paper outlines how the government of Myanmar has understood the concept of Sustainable Tourism, and how it intends to implement and facilitate Sustainable Tourism. This paper, therefore, focuses primarily on the institutional frameworks that have been put in place, a specific one being the Inlay Lake Destination Management Plan, which is one of the four priority destinations identified by the government. The plan aims to improve local infrastructure, manage the local environment and develop local human resources. Importantly, the Plan also includes the establishment of a Destination Management Organization (DMO) to implement and manage Inlay Lake as a Sustainable Tourism destination. This research aims to investigate, for example, the equality in both input to the DMO and benefits accrued to the various stakeholders. How such equality can be ensured and how this can be reliably quantified will be crucial to ultimately evaluating the success of any such plans to implement Sustainable Tourism in Myanmar in the coming years. However, this research paper concludes that while the establishment of the DMO is a positive development, there are considerable institutional, economic and cultural factors that severely limit the ability of the DMO to function as an agent of sustainable tourism implementation.

Keywords: sustainable tourism, myanmar, country in transition, destination management organizations

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15890 Spatial Ecology of an Endangered Amphibian Litoria Raniformis within Modified Tasmanian Landscapes

Authors: Timothy Garvey, Don Driscoll

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Within Tasmania, the growling grass frog (Litoria raniformis) has experienced a rapid contraction in distribution. This decline is primarily attributed to habitat loss through landscape modification and improved land drainage. Reductions in seasonal water-sources have placed increasing importance on permanent water bodies for reproduction and foraging. Tasmanian agricultural and commercial forestry landscapes often feature small artificial ponds, utilized for watering livestock and fighting wildfires. Improved knowledge of how L. raniformis may be exploiting anthropogenic ponds is required for improved conservation management. We implemented telemetric tracking in order to evaluate the spatial ecology of L. raniformis (n = 20) within agricultural and managed forestry sites, with tracking conducted periodically over the breeding season (November/December, January/February, March/April). We investigated (1) potential differences in habitat utilization between agricultural and plantation sites, and (2) the post-breeding dispersal of individual frogs. Frogs were found to remain in close proximity to ponds throughout November/December, with individuals occupying vegetative depauperate water bodies beginning to disperse by January/February. Dispersing individuals traversed exposed plantation understory and agricultural pasture land in order to enter patches of native scrubland. By March/April all individuals captured at minimally vegetated ponds had retreated to adjacent scrub corridors. Animals found in ponds featuring dense riparian vegetation were not recorded to disperse. No difference in behavior was recorded between sexes. Rising temperatures coincided with increased movement by individuals towards native scrub refugia. The patterns of movement reported in this investigation emphasize the significant contribution of manmade water-bodies towards the conservation of L. raniformis within modified landscapes. The use of natural scrubland as cyclical retreats between breeding seasons also highlights the importance of the continued preservation of remnant vegetation corridors. Loss of artificial dams or buffering scrubland in heavily altered landscapes could see the breakdown of the greater L. raniformis meta-population further threatening their regional persistence.

Keywords: habitat loss, modified landscapes, spatial ecology, telemetry

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15889 Protein Crystallization Induced by Surface Plasmon Resonance

Authors: Tetsuo Okutsu

Abstract:

We have developed a crystallization plate with the function of promoting protein crystallization. A gold thin film is deposited on the crystallization plate. A protein solution is dropped thereon, and crystallization is promoted when the protein is irradiated with light of a wavelength that protein does not absorb. Protein is densely adsorbed on the gold thin film surface. The light excites the surface plasmon resonance of the gold thin film, the protein is excited by the generated enhanced electric field induced by surface plasmon resonance, and the amino acid residues are radicalized to produce protein dimers. The dimers function as templates for protein crystals, crystallization is promoted.

Keywords: lysozyme, plasmon, protein, crystallization, RNaseA

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15888 Review of the Nutritional Value of Spirulina as a Potential Replacement of Fishmeal in Aquafeed

Authors: Onada Olawale Ahmed

Abstract:

As the intensification of aquaculture production increases on global scale, the growing concern of fish farmers around the world is related to cost of fish production, where cost of feeding takes substantial percentage. Fishmeal (FM) is one of the most expensive ingredients, and its high dependence in aqua-feed production translates to high cost of feeding of stocked fish. However, to reach a sustainable aquaculture, new alternative protein sources including cheaper plant or animal origin proteins are needed to be introduced for stable aqua-feed production. Spirulina is a cyanobacterium that has good nutrient profile that could be useful in aquaculture. This review therefore emphasizes on the nutritional value of Spirulina as a potential replacement of FM in aqua-feed. Spirulina is a planktonic photosynthetic filamentous cyanobacterium that forms massive populations in tropical and subtropical bodies of water with high levels of carbonate and bicarbonate. Spirulina grows naturally in nutrient rich alkaline lake with water salinity ( > 30 g/l) and high pH (8.5–11.0). Its artificial production requires luminosity (photo-period 12/12, 4 luxes), temperature (30 °C), inoculum, water stirring device, dissolved solids (10–60 g/litre), pH (8.5– 10.5), good water quality, and macro and micronutrient presence (C, N, P, K, S, Mg, Na, Cl, Ca and Fe, Zn, Cu, Ni, Co, Se). Spirulina has also been reported to grow on agro-industrial waste such as sugar mill waste effluent, poultry industry waste, fertilizer factory waste, and urban waste and organic matter. Chemical composition of Spirulina indicates that it has high nutritional value due to its content of 55-70% protein, 14-19% soluble carbohydrate, high amount of polyunsaturated fatty acids (PUFAs), 1.5–2.0 percent of 5–6 percent total lipid, all the essential minerals are available in spirulina which contributes about 7 percent (average range 2.76–3.00 percent of total weight) under laboratory conditions, β-carotene, B-group vitamin, vitamin E, iron, potassium and chlorophyll are also available in spirulina. Spirulina protein has a balanced composition of amino acids with concentration of methionine, tryptophan and other amino acids almost similar to those of casein, although, this depends upon the culture media used. Positive effects of spirulina on growth, feed utilization and stress and disease resistance of cultured fish have been reported in earlier studies. Spirulina was reported to replace up to 40% of fishmeal protein in tilapia (Oreochromis mossambicus) diet and even higher replacement of fishmeal was possible in common carp (Cyprinus carpio), partial replacement of fish meal with spirulina in diets for parrot fish (Oplegnathus fasciatus) and Tilapia (Orechromis niloticus) has also been conducted. Spirulina have considerable potential for development, especially as a small-scale crop for nutritional enhancement and health improvement of fish. It is important therefore that more research needs to be conducted on its production, inclusion level in aqua-feed and its possible potential use of aquaculture.

Keywords: aquaculture, spirulina, fish nutrition, fish feed

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15887 Current Applications of Artificial Intelligence (AI) in Chest Radiology

Authors: Angelis P. Barlampas

Abstract:

Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

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15886 Excess Body Fat as a Store Toxin Affecting the Glomerular Filtration and Excretory Function of the Liver in Patients after Renal Transplantation

Authors: Magdalena B. Kaziuk, Waldemar Kosiba, Marek J. Kuzniewski

Abstract:

Introduction: Adipose tissue is a typical place for storage water-insoluble toxins in the body. It's connective tissue, where the intercellular substance consist of fat, which level in people with low physical activity should be 18-25% for women and 13-18% for men. Due to the fat distribution in the body we distinquish two types of obesity: android (visceral, abdominal) and gynoidal (gluteal-femoral, peripheral). Abdominal obesity increases the risk of complications of the cardiovascular system diseases, and impaired renal and liver function. Through the influence on disorders of metabolism, lipid metabolism, diabetes and hypertension, leading to emergence of the metabolic syndrome. So thus, obesity will especially overload kidney function in patients after transplantation. Aim: An attempt was made to estimate the impact of amount fat tissue on transplanted kidney function and excretory function of the liver in patients after Ktx. Material and Methods: The study included 108 patients (50 females, 58 male, age 46.5 +/- 12.9 years) with active kidney transplant after more than 3 months from the transplantation. An analysis of body composition was done by using electrical bioimpedance (BIA) and anthropometric measurements. Estimated basal metabolic rate (BMR), muscle mass, total body water content and the amount of body fat. Information about physical activity were obtained during clinical examination. Nutritional status, and type of obesity were determined by using indicators: Waist to Height Ratio (WHR) and Waist to Hip Ratio (WHR). Excretory functions of the transplanted kidney was rated by calculating the estimated renal glomerular filtration rate (eGFR) using the MDRD formula. Liver function was rated by total bilirubin and alanine aminotransferase levels ALT concentration in serum. In our patients haemolitic uremic syndrome (HUS) was excluded. Results: In 19.44% of patients had underweight, 22.37% of the respondents were with normal weight, 11.11% had overweight, and the rest were with obese (49.08%). People with android stature have a lower eGFR compared with those with the gynoidal stature (p = 0.004). All patients with obesity had higher amount of body fat from a few to several percent. The higher amount of body fat percentage, the lower eGFR had patients (p <0.001). Elevated ALT levels significantly correlated with a high fat content (p <0.02). Conclusion: Increased amount of body fat, particularly in the case of android obesity can be a predictor of kidney and liver damage. Due to that obese patients should have more frequent control of diagnostic functions of these organs and the intensive dietary proceedings, pharmacological and regular physical activity adapted to the current physical condition of patients after transplantation.

Keywords: obesity, body fat, kidney transplantation, glomerular filtration rate, liver function

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15885 Physics Informed Deep Residual Networks Based Type-A Aortic Dissection Prediction

Authors: Joy Cao, Min Zhou

Abstract:

Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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15884 Urinary Volatile Organic Compound Testing in Fast-Track Patients with Suspected Colorectal Cancer

Authors: Godwin Dennison, C. E. Boulind, O. Gould, B. de Lacy Costello, J. Allison, P. White, P. Ewings, A. Wicaksono, N. J. Curtis, A. Pullyblank, D. Jayne, J. A. Covington, N. Ratcliffe, N. K. Francis

Abstract:

Background: Colorectal symptoms are common but only infrequently represent serious pathology, including colorectal cancer (CRC). A large number of invasive tests are presently performed for reassurance. We investigated the feasibility of urinary volatile organic compound (VOC) testing as a potential triage tool in patients fast-tracked for assessment for possible CRC. Methods: A prospective, multi-centre, observational feasibility study was performed across three sites. Patients referred on NHS fast-track pathways for potential CRC provided a urine sample which underwent Gas Chromatography Mass Spectrometry (GC-MS), Field Asymmetric Ion Mobility Spectrometry (FAIMS) and Selected Ion Flow Tube Mass Spectrometry (SIFT-MS) analysis. Patients underwent colonoscopy and/or CT colonography and were grouped as either CRC, adenomatous polyp(s), or controls to explore the diagnostic accuracy of VOC output data supported by an artificial neural network (ANN) model. Results: 558 patients participated with 23 (4.1%) CRC diagnosed. 59% of colonoscopies and 86% of CT colonographies showed no abnormalities. Urinary VOC testing was feasible, acceptable to patients, and applicable within the clinical fast track pathway. GC-MS showed the highest clinical utility for CRC and polyp detection vs. controls (sensitivity=0.878, specificity=0.882, AUROC=0.884). Conclusion: Urinary VOC testing and analysis are feasible within NHS fast-track CRC pathways. Clinically meaningful differences between patients with cancer, polyps, or no pathology were identified therefore suggesting VOC analysis may have future utility as a triage tool. Acknowledgment: Funding: NIHR Research for Patient Benefit grant (ref: PB-PG-0416-20022).

Keywords: colorectal cancer, volatile organic compound, gas chromatography mass spectrometry, field asymmetric ion mobility spectrometry, selected ion flow tube mass spectrometry

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15883 Experimental Study of the Sound Absorption of a Geopolymer Panel with a Textile Component Designed for a Railway Corridor

Authors: Ludmila Fridrichová, Roman Knížek, Pavel Němeček, Katarzyna Ewa Buczkowska

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The design of the sound absorption panel, which consists of three layers, is presented in this study. The first layer of the panel is perforated and provides sound transmission to the inner part of the panel. The second layer is composed of a bulk material whose purpose is to absorb as much noise as possible. The third layer of the panel has two functions: the first function is to ensure the strength of the panel, and the second function is to reflect the sound back into the bulk layer. Experimental results have shown that the size of the holes in the perforated panel affects the sound absorption of the required frequency. The percentage of filling of the perforated area affects the quantity of sound absorbed.

Keywords: sound absorption, railway corridor, health, textile waste, natural fibres, concrete

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15882 Fuzzy Neuro Approach for Integrated Water Management System

Authors: Stuti Modi, Aditi Kambli

Abstract:

This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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15881 Detection of Alzheimer's Protein on Nano Designed Polymer Surfaces in Water and Artificial Saliva

Authors: Sevde Altuntas, Fatih Buyukserin

Abstract:

Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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15880 A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets

Authors: O. Poleshchuk, E. Komarov

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This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords: interval type-2 fuzzy sets, fuzzy regression, weighted interval

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15879 Evaluation of Advanced Architectures for Commercial Refrigeration Systems Using Low Global Warming Potential Refrigerants

Authors: Fabrizio Codella, Chris Parker, Samer Saab

Abstract:

The Kigali Amendment is driving the adoption of low Global Warming Potential refrigerants in commercial refrigeration systems in over a hundred countries. Several refrigeration systems for the small and large retail stores at mild and hot ambient temperature climates have been compared for hydrofluorocarbons (HFC), hydrofluoroolefins (HFO), transcritical CO₂ and propane, in typical and advanced system architectures. The results of system performance, emissions and lifetime cost have been compared. The greatest benefits were found to be obtained by low global warming potential HFO advanced systems.

Keywords: commercial refrigeration, CO₂, emissions, HFO, lifetime cost, performance

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15878 Machine Learning Predictive Models for Hydroponic Systems: A Case Study Nutrient Film Technique and Deep Flow Technique

Authors: Kritiyaporn Kunsook

Abstract:

Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), decision tree, support vector machines (SVMs), Naïve Bayes, and ensemble classifier by voting are powerful data driven methods that are relatively less widely used in the mapping of technique of system, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, ANNs, decision tree, SVMs, Naïve Bayes, and ensemble classifier by voting in technique of hydroponic systems prospectively modeling are compared based on the accuracy of each model. Classification of hydroponic systems only covers the test samples from vegetables grown with Nutrient film technique (NFT) and Deep flow technique (DFT). The feature, which are the characteristics of vegetables compose harvesting height width, temperature, require light and color. The results indicate that the classification performance of the ANNs is 98%, decision tree is 98%, SVMs is 97.33%, Naïve Bayes is 96.67%, and ensemble classifier by voting is 98.96% algorithm respectively.

Keywords: artificial neural networks, decision tree, support vector machines, naïve Bayes, ensemble classifier by voting

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15877 Implementation of Deep Neural Networks for Pavement Condition Index Prediction

Authors: M. Sirhan, S. Bekhor, A. Sidess

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In-service pavements deteriorate with time due to traffic wheel loads, environment, and climate conditions. Pavement deterioration leads to a reduction in their serviceability and structural behavior. Consequently, proper maintenance and rehabilitation (M&R) are necessary actions to keep the in-service pavement network at the desired level of serviceability. Due to resource and financial constraints, the pavement management system (PMS) prioritizes roads most in need of maintenance and rehabilitation action. It recommends a suitable action for each pavement based on the performance and surface condition of each road in the network. The pavement performance and condition are usually quantified and evaluated by different types of roughness-based and stress-based indices. Examples of such indices are Pavement Serviceability Index (PSI), Pavement Serviceability Ratio (PSR), Mean Panel Rating (MPR), Pavement Condition Rating (PCR), Ride Number (RN), Profile Index (PI), International Roughness Index (IRI), and Pavement Condition Index (PCI). PCI is commonly used in PMS as an indicator of the extent of the distresses on the pavement surface. PCI values range between 0 and 100; where 0 and 100 represent a highly deteriorated pavement and a newly constructed pavement, respectively. The PCI value is a function of distress type, severity, and density (measured as a percentage of the total pavement area). PCI is usually calculated iteratively using the 'Paver' program developed by the US Army Corps. The use of soft computing techniques, especially Artificial Neural Network (ANN), has become increasingly popular in the modeling of engineering problems. ANN techniques have successfully modeled the performance of the in-service pavements, due to its efficiency in predicting and solving non-linear relationships and dealing with an uncertain large amount of data. Typical regression models, which require a pre-defined relationship, can be replaced by ANN, which was found to be an appropriate tool for predicting the different pavement performance indices versus different factors as well. Subsequently, the objective of the presented study is to develop and train an ANN model that predicts the PCI values. The model’s input consists of percentage areas of 11 different damage types; alligator cracking, swelling, rutting, block cracking, longitudinal/transverse cracking, edge cracking, shoving, raveling, potholes, patching, and lane drop off, at three severity levels (low, medium, high) for each. The developed model was trained using 536,000 samples and tested on 134,000 samples. The samples were collected and prepared by The National Transport Infrastructure Company. The predicted results yielded satisfactory compliance with field measurements. The proposed model predicted PCI values with relatively low standard deviations, suggesting that it could be incorporated into the PMS for PCI determination. It is worth mentioning that the most influencing variables for PCI prediction are damages related to alligator cracking, swelling, rutting, and potholes.

Keywords: artificial neural networks, computer programming, pavement condition index, pavement management, performance prediction

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15876 Black Soybeans Show Acute and Chronic Liver Protective Functions against CCl4 Induced Liver Damage

Authors: Cheng-Kuang Hsu, Chih-Hsiang Chang, Chi-Chih Wang

Abstract:

Black soybeans contain high amount of antioxidants including polyphenols, anthocyanins and flavones. The protective function of black soybean against CCl4 (a strong oxidant) induced acute and chronic liver damage was investigated in vivo using SD rats or ICR mouse. The evaluation of CCl4 induced oxidative stress in the liver tissues included the measurements of the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), the concentration of thiobarbituric acid reactive substances (TBARS), the activities of antioxidant enzymes (superoxide dismutase SOD, catalase, and glutathione peroxidase GPx), as well as the level of histological lesion in the liver tissues. For chronic experiment, a decoction at the concentration of 100 or 1000 mg/kg of body weight, produced by baking black soybean at 130°C for 5 min and followed by immerging in 100°C hot water for 20 min, showed the inhibitory effect against CCl4 induced liver damage in SD rats. Hot-water extract (80 °C for 30 min) from un-preheated black soybean at the concentration of 200 mg/kg of body weight could not reduce ALT and AST levels in CCl4 treated SD rats, but the hot-water extract from preheated black soybean did enhance antioxidant enzymes activities, decline ALT and AST levels. Specially, the hot-water extract from the seed cost of black soybean had the highest liver protective function since it can reduce vacuolization and necrosis in the liver tissues. For acute experiment, the hot-water extracts from black soybean and the seed coat, as well as pure cyanidin-3-glucoside (C3G) could reduce ALT and AST levels of CCl4 induced ICR mouse. The decoction and hot-water extract from the seed coat of black soybean had higher total polyphenols, anthocyanins and flavones contents than those extracts from whole black soybean. Such results agreed with high liver protective function in the decoction and hot-water from the seed coat of black soybean. Black soybean showed protective function only after preheating process (baking at 130°C for 5 to 10 min) because preheating treatment damaged the cell wall and made the extraction of the antioxidants more effectively.

Keywords: black soybean, liver protective function, antioxidant, antioxidative stress

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15875 Analysis of Dust Particles in Snow Cover in the Surroundings of the City of Ostrava: Particle Size Distribution, Zeta Potential and Heavy Metal Content

Authors: Roman Marsalek

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In this paper, snow samples containing dust particles from several sampling points around the city of Ostrava were analyzed. The pH values of sampled snow were measured and solid particles analyzed. Particle size, zeta potential and content of selected heavy metals were determined in solid particles. The pH values of most samples lay in the slightly acid region. Mean values of particle size ranged from 290.5 to 620.5 nm. Zeta potential values varied between -5 and -26.5 mV. The following heavy metal concentration ranges were found: copper 0.08-0.75 mg/g, lead 0.05-0.9 mg/g, manganese 0.45-5.9 mg/g and iron 25.7-280.46 mg/g. The highest values of copper and lead were found in the vicinity of busy crossroads, and on the contrary, the highest levels of manganese and iron were detected close to a large steelworks. The proportion between pH values, zeta potentials, particle sizes and heavy metal contents was established. Zeta potential decreased with rising pH values and, simultaneously, heavy metal content in solid particles increased. At the same time, higher metal content corresponded to lower particle size.

Keywords: dust, snow, zeta potential, particles size distribution, heavy metals

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15874 Fundamental Theory of the Evolution Force: Gene Engineering utilizing Synthetic Evolution Artificial Intelligence

Authors: L. K. Davis

Abstract:

The effects of the evolution force are observable in nature at all structural levels ranging from small molecular systems to conversely enormous biospheric systems. However, the evolution force and work associated with formation of biological structures has yet to be described mathematically or theoretically. In addressing the conundrum, we consider evolution from a unique perspective and in doing so we introduce the “Fundamental Theory of the Evolution Force: FTEF”. We utilized synthetic evolution artificial intelligence (SYN-AI) to identify genomic building blocks and to engineer 14-3-3 ζ docking proteins by transforming gene sequences into time-based DNA codes derived from protein hierarchical structural levels. The aforementioned served as templates for random DNA hybridizations and genetic assembly. The application of hierarchical DNA codes allowed us to fast forward evolution, while dampening the effect of point mutations. Natural selection was performed at each hierarchical structural level and mutations screened using Blosum 80 mutation frequency-based algorithms. Notably, SYN-AI engineered a set of three architecturally conserved docking proteins that retained motion and vibrational dynamics of native Bos taurus 14-3-3 ζ.

Keywords: 14-3-3 docking genes, synthetic protein design, time-based DNA codes, writing DNA code from scratch

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15873 Predicting the Potential Geographical Distribution of the Banana Aphid (Pentalonia nigronervosa) as Vector of Banana Bunchy Top Virus Using Diva-GIS

Authors: Marilyn Painagan

Abstract:

This study was conducted to predict the potential geographical distribution of the banana aphid (Pentalonia negronervosa) in North Cotabato through climate envelope approach of DIVA-GIS, a software for analyzing the distribution of organisms to elucidate geographic and ecological patterns. A WorldClim database that was based on weather conditions recorded last 1950 to 2000 with a spatial resolution of approximately 1x1 km. was used in the bioclimatic modelling, this database includes temperature, precipitation, evapotranspiration and bioclimatic variables which was measured at many different locations, a bioclimatic modelling was done in the study. The study revealed that the western part of Magpet and Arakan and the municipality of Antipas are at high potential risk of occurrence of banana aphid while it is not likely to occur in the municipalities of Aleosan, Midsayap, Pikit, M’lang and Tulunan. The result of this study can help developed strategies for monitoring and managing this serious pest of banana and to prepare a mitigation measures on those areas that are potential for future infestation.

Keywords: banana aphid, bioclimatic model, bunchy top, climatic envelope approach

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15872 Implant Guided Surgery and Immediate Loading

Authors: Omid Tavakol, Mahnaz Gholami

Abstract:

Introduction : In this oral presentation the main goal is discussing immediate loading in dental implants , from treatment planning and surgical guide designing to delivery , follow up and occlusal consideration . Methods and materials : first of all systematic reviews about immediate loading will be considered . besides , a comparison will be made between immediate loading and conventional loading in terms of success rate and complications . After that different methods , prosthetic options and materials best used in immediate loading will be explained. Particularly multi unit abutments and their mechanism of function will be explained .Digital impressions and designing the temporaries is the next topic we are to explicate .Next issue is the differences between single unit , multiple unit and full arch implantation in immediate loading .Following we are going to describe methods for tissue engineering and papilla formation after extraction . Last slides are about a full mouth rehabilitation via immediate loading technique from surgical designing to follow up .At the end we would talk about potential complications , how to prevent from occurrence and what to do if we face up with .

Keywords: guided surgery, digital implantology, immediate loading, digital dentistry

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15871 Biogas Potential of Deinking Sludge from Wastepaper Recycling Industry: Influence of Dewatering Degree and High Calcium Carbonate Content

Authors: Moses Kolade Ogun, Ina Korner

Abstract:

To improve on the sustainable resource management in the wastepaper recycling industry, studies into the valorization of wastes generated by the industry are necessary. The industry produces different residues, among which is the deinking sludge (DS). The DS is generated from the deinking process and constitutes a major fraction of the residues generated by the European pulp and paper industry. The traditional treatment of DS by incineration is capital intensive due to energy requirement for dewatering and the need for complementary fuel source due to DS low calorific value. This could be replaced by a biotechnological approach. This study, therefore, investigated the biogas potential of different DS streams (different dewatering degrees) and the influence of the high calcium carbonate content of DS on its biogas potential. Dewatered DS (solid fraction) sample from filter press and the filtrate (liquid fraction) were collected from a partner wastepaper recycling company in Germany. The solid fraction and the liquid fraction were mixed in proportion to realize DS with different water content (55–91% fresh mass). Spiked samples of DS using deionized water, cellulose and calcium carbonate were prepared to simulate DS with varying calcium carbonate content (0– 40% dry matter). Seeding sludge was collected from an existing biogas plant treating sewage sludge in Germany. Biogas potential was studied using a 1-liter batch test system under the mesophilic condition and ran for 21 days. Specific biogas potential in the range 133- 230 NL/kg-organic dry matter was observed for DS samples investigated. It was found out that an increase in the liquid fraction leads to an increase in the specific biogas potential and a reduction in the absolute biogas potential (NL-biogas/ fresh mass). By comparing the absolute biogas potential curve and the specific biogas potential curve, an optimal dewatering degree corresponding to a water content of about 70% fresh mass was identified. This degree of dewatering is a compromise when factors such as biogas yield, reactor size, energy required for dewatering and operation cost are considered. No inhibitory influence was observed in the biogas potential of DS due to the reported high calcium carbonate content of DS. This study confirms that DS is a potential bioresource for biogas production. Further optimization such as nitrogen supplementation due to DS high C/N ratio can increase biogas yield.

Keywords: biogas, calcium carbonate, deinking sludge, dewatering, water content

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15870 Batch-Oriented Setting Time`s Optimisation in an Aerodynamic Feeding System

Authors: Jan Busch, Maurice Schmidt, Peter Nyhuis

Abstract:

The change of conditions for production companies in high-wage countries is characterized by the globalization of competition and the transition of a supplier´s to a buyer´s market. The companies need to face the challenges of reacting flexibly to these changes. Due to the significant and increasing degree of automation, assembly has become the most expensive production process. Regarding the reduction of production cost, assembly consequently offers a considerable rationalizing potential. Therefore, an aerodynamic feeding system has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. In former research activities, this system has been enabled to adjust itself using genetic algorithm. The longer the genetic algorithm is executed the better is the feeding quality. In this paper, the relation between the system´s setting time and the feeding quality is observed and a function which enables the user to achieve the minimum of the total feeding time is presented.

Keywords: aerodynamic feeding system, batch size, optimisation, setting time

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15869 Polymer Dispersed Liquid Crystals Based on Poly Vinyl Alcohol Boric Acid Matrix

Authors: Daniela Ailincai, Bogdan C. Simionescu, Luminita Marin

Abstract:

Polymer dispersed liquid crystals (PDLC) represent an interesting class of materials which combine the ability of polymers to form films and their mechanical strength with the opto-electronic properties of liquid crystals. The proper choice of the two components - the liquid crystal and the polymeric matrix - leads to materials suitable for a large area of applications, from electronics to biomedical devices. The objective of our work was to obtain PDLC films with potential applications in the biomedical field, using poly vinyl alcohol boric acid (PVAB) as a polymeric matrix for the first time. Presenting all the tremendous properties of poly vinyl alcohol (such as: biocompatibility, biodegradability, water solubility, good chemical stability and film forming ability), PVAB brings the advantage of containing the electron deficient boron atom, and due to this, it should promote the liquid crystal anchoring and a narrow liquid crystal droplets polydispersity. Two different PDLC systems have been obtained, by the use of two liquid crystals, a nematic commercial one: 4-cyano-4’-penthylbiphenyl (5CB) and a new smectic liquid crystal, synthesized by us: buthyl-p-[p’-n-octyloxy benzoyloxy] benzoate (BBO). The PDLC composites have been obtained by the encapsulation method, working with four different ratios between the polymeric matrix and the liquid crystal, from 60:40 to 90:10. In all cases, the composites were able to form free standing, flexible films. Polarized light microscopy, scanning electron microscopy, differential scanning calorimetry, RAMAN- spectroscopy and the contact angle measurements have been performed, in order to characterize the new composites. The new smectic liquid crystal has been characterized using 1H-NMR and single crystal X-ray diffraction and its thermotropic behavior has been established using differential scanning calorimetry and polarized light microscopy. The polarized light microscopy evidenced the formation of round birefringent droplets, anchored homeotropic in the first case and planar in the second, with a narrow dimensional polydispersity, especially for the PDLC containing the largest amount of liquid crystal, fact evidenced by SEM, also. The obtained values for the water to air contact angle showed that the composites have a proper hydrophilic-hydrophobic balance, making them potential candidates for bioapplications. More than this, our studies demonstrated that the water to air contact angle varies as a function of PVAB matrix crystalinity degree, which can be controled as a function of time. This fact allowed us to conclude that the use of PVAB as matrix for PDLCs obtaining offers the possibility to modulate their properties for specific applications.

Keywords: 4-cyano-4’-penthylbiphenyl, buthyl-p-[p’-n-octyloxy benzoyloxy] benzoate, contact angle, polymer dispersed liquid crystals, poly vinyl alcohol boric acid

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15868 A Leadership Approach for the Sake of Organizations: Human-Oriented Leadership

Authors: Eser Bingül

Abstract:

The leadership and leaders, also having been a privileged subject of scientific researches in the last century, have become influential in shaping the destiny of the states since the first examples of the warfare history. The issue of leadership, finding a place in the management science, can also be defined as an integration of function within the aspect of leader. In this description, the relationship has come to the foreground which is established between the development of leadership theories and the elements of function which are leader, followers, and condition. While one reason of this analysis in leadership is to keep a lens to the historical background, the main reason has been a questioning the traits and education of leaders who have still affected the nation’s and organization’s fate. The links and analysis established in the definition of leadership have put forward the necessity of solving the unpredictable structure of human nature and behaviors in the focus of leadership approach. On the other hand becoming a model that meets the today’s needs of any system has given a clue that the leaders should turn towards the people. Being aware of this necessity, human-oriented leadership approach aims to gain both followers and their abilities to the system with giving them a deserved esteem and create the team spirit based on mutual trust. Ultimately this approach, with the determined leadership qualities consisting of charisma, ability of communication and trust, will be able to produce the solutions to the instant and long-term problems and uncertainties, derived from the variables of function, for the sake of systems.

Keywords: human nature, leadership, human-oriented approach, social sciences and humanities

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15867 Risk-Sharing Financing of Islamic Banks: Better Shielded against Interest Rate Risk

Authors: Mirzet SeHo, Alaa Alaabed, Mansur Masih

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In theory, risk-sharing-based financing (RSF) is considered a corner stone of Islamic finance. It is argued to render Islamic banks more resilient to shocks. In practice, however, this feature of Islamic financial products is almost negligible. Instead, debt-based instruments, with conventional like features, have overwhelmed the nascent industry. In addition, the framework of present-day economic, regulatory and financial reality inevitably exposes Islamic banks in dual banking systems to problems of conventional banks. This includes, but is not limited to, interest rate risk. Empirical evidence has, thus far, confirmed such exposures, despite Islamic banks’ interest-free operations. This study applies system GMM in modeling the determinants of RSF, and finds that RSF is insensitive to changes in interest rates. Hence, our results provide support to the “stability” view of risk-sharing-based financing. This suggests RSF as the way forward for risk management at Islamic banks, in the absence of widely acceptable Shariah compliant hedging instruments. Further support to the stability view is given by evidence of counter-cyclicality. Unlike debt-based lending that inflates artificial asset bubbles through credit expansion during the upswing of business cycles, RSF is negatively related to GDP growth. Our results also imply a significantly strong relationship between risk-sharing deposits and RSF. However, the pass-through of these deposits to RSF is economically low. Only about 40% of risk-sharing deposits are channeled to risk-sharing financing. This raises questions on the validity of the industry’s claim that depositors accustomed to conventional banking shun away from risk sharing and signals potential for better balance sheet management at Islamic banks. Overall, our findings suggest that, on the one hand, Islamic banks can gain ‘independence’ from conventional banks and interest rates through risk-sharing products, the potential for which is enormous. On the other hand, RSF could enable policy makers to improve systemic stability and restrain excessive credit expansion through its countercyclical features.

Keywords: Islamic banks, risk-sharing, financing, interest rate, dynamic system GMM

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15866 Biomass Availability Matrix: Methodology to Define High Level Biomass Availability for Bioenergy Purposes, a Quebec Case Study

Authors: Camilo Perez Lee, Mark Lefsrud, Edris Madadian, Yves Roy

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Biomass availability is one of the most important aspects to consider when determining the proper location of potential bioenergy plants. Since this aspect has a direct impact on biomass transportation and storage, biomass availability greatly influences the operational cost. Biomass availability is more than the quantity available on a specific region; other elements such as biomass accessibility and potential play an important role. Accessibility establishes if the biomass could be extracted and conveyed easily considering factors such as biomass availability, infrastructure condition and other operational issues. On the other hand, biomass potential is defined as the capacity of a specific region to scale the usage of biomass as an energy source, move from another energy source or to switch the type of biomass to increase their biomass availability in the future. This paper defines methodologies and parameters in order to determine the biomass availability within the administrative regions of the province of Quebec; firstly by defining the forestry, agricultural, municipal solid waste and energy crop biomass availability per administrative region, next its infrastructure accessibility and lastly defining the region potential. Thus, these data are processed to create a biomass availability matrix allowing to define the overall biomass availability per region and to determine the most optional candidates for bioenergy plant location.

Keywords: biomass, availability, bioenergy, accessibility, biomass potential

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15865 Artificial Neural Network for Forecasting of Daily Reservoir Inflow: Case Study of the Kotmale Reservoir in Sri Lanka

Authors: E. U. Dampage, Ovindi D. Bandara, Vinushi S. Waraketiya, Samitha S. R. De Silva, Yasiru S. Gunarathne

Abstract:

The knowledge of water inflow figures is paramount in decision making on the allocation for consumption for numerous purposes; irrigation, hydropower, domestic and industrial usage, and flood control. The understanding of how reservoir inflows are affected by different climatic and hydrological conditions is crucial to enable effective water management and downstream flood control. In this research, we propose a method using a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) to assist the aforesaid decision-making process. The Kotmale reservoir, which is the uppermost reservoir in the Mahaweli reservoir complex in Sri Lanka, was used as the test bed for this research. The ANN uses the runoff in the Kotmale reservoir catchment area and the effect of Sea Surface Temperatures (SST) to make a forecast for seven days ahead. Three types of ANN are tested; Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and LSTM. The extensive field trials and validation endeavors found that the LSTM ANN provides superior performance in the aspects of accuracy and latency.

Keywords: convolutional neural network, CNN, inflow, long short-term memory, LSTM, multi-layer perceptron, MLP, neural network

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15864 Discovering the Real Psyche of Human Beings

Authors: Sheetla Prasad

Abstract:

The objective of this study is ‘discovering the real psyche of human beings for prediction of mode, direction and strength of the potential of actions of the individual. The human face was taken as a source of central point to search for the route of real psyche. Analysis of the face architecture (shape and salient features of face) was done by three directional photographs ( 600 left and right and camera facing) of human beings. The shapes and features of the human face were scaled in 177 units on the basis of face–features locations (FFL). The mathematical analysis was done of FFLs by self developed and standardized formula. At this phase, 800 samples were taken from the population of students, teachers, advocates, administrative officers, and common persons. The finding shows that real psyche has two external rings (ER). These ER are itself generator of two independent psyches (manifested and manipulated). Prima-facie, it was proved that micro differences in FFLs have potential to predict the state of art of the human psyche. The potential of psyches was determined by the saving and distribution of mental energy. It was also mathematically proved.

Keywords: face architecture, psyche, potential, face functional ratio, external rings

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15863 Finite Deformation of a Dielectric Elastomeric Spherical Shell Based on a New Nonlinear Electroelastic Constitutive Theory

Authors: Odunayo Olawuyi Fadodun

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Dielectric elastomers (DEs) are a type of intelligent materials with salient features like electromechanical coupling, lightweight, fast actuation speed, low cost and high energy density that make them good candidates for numerous engineering applications. This paper adopts a new nonlinear electroelastic constitutive theory to examine radial deformation of a pressurized thick-walled spherical shell of soft dielectric material with compliant electrodes on its inner and outer surfaces. A general formular for the internal pressure, which depends on the deformation and a potential difference between boundary electrodes or uniform surface charge distributions, is obtained in terms of special function. To illustrate the effects of an applied electric field on the mechanical behaviour of the shell, three different energy functions with distinct mechanical properties are employed for numerical purposes. The observed behaviour of the shells is preserved in the presence of an applied electric field, and the influence of the field due to a potential difference declines more slowly with the increasing deformation to that produced by a surface charge. Counterpart results are then presented for the thin-walled shell approximation as a limiting case of a thick-walled shell without restriction on the energy density. In the absence of internal pressure, it is obtained that inflation is caused by the application of an electric field. The resulting numerical solutions of the theory presented in this work are in agreement with those predicted by the generally adopted Dorfmann and Ogden model.

Keywords: constitutive theory, elastic dielectric, electroelasticity, finite deformation, nonlinear response, spherical shell

Procedia PDF Downloads 93