Search results for: efficiency analysis and selection bias
Commenced in January 2007
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Edition: International
Paper Count: 34330

Search results for: efficiency analysis and selection bias

29860 Impact of Microwave and Air Velocity on Drying Kinetics and Rehydration of Potato Slices

Authors: Caiyun Liu, A. Hernandez-Manas, N. Grimi, E. Vorobiev

Abstract:

Drying is one of the most used methods for food preservation, which extend shelf life of food and makes their transportation, storage and packaging easier and more economic. The commonly dried method is hot air drying. However, its disadvantages are low energy efficiency and long drying times. Because of the high temperature during the hot air drying, the undesirable changes in pigments, vitamins and flavoring agents occur which result in degradation of the quality parameters of the product. Drying process can also cause shrinkage, case hardening, dark color, browning, loss of nutrients and others. Recently, new processes were developed in order to avoid these problems. For example, the application of pulsed electric field provokes cell membrane permeabilisation, which increases the drying kinetics and moisture diffusion coefficient. Microwave drying technology has also several advantages over conventional hot air drying, such as higher drying rates and thermal efficiency, shorter drying time, significantly improved product quality and nutritional value. Rehydration kinetics of dried product is a very important characteristic of dried products. Current research has indicated that the rehydration ratio and the coefficient of rehydration are dependent on the processing conditions of drying. The present study compares the efficiency of two processes (1: room temperature air drying, 2: microwave/air drying) in terms of drying rate, product quality and rehydration ratio. In this work, potato slices (≈2.2g) with a thickness of 2 mm and diameter of 33mm were placed in the microwave chamber and dried. Drying kinetics and drying rates of different methods were determined. The process parameters included inlet air velocity (1 m/s, 1.5 m/s, 2 m/s) and microwave power (50 W, 100 W, 200 W and 250 W) were studied. The evolution of temperature during microwave drying was measured. The drying power had a strong effect on drying rate, and the microwave-air drying resulted in 93% decrease in the drying time when the air velocity was 2 m/s and the power of microwave was 250 W. Based on Lewis model, drying rate constants (kDR) were determined. It was observed an increase from kDR=0.0002 s-1 to kDR=0.0032 s-1 of air velocity of 2 m/s and microwave/air (at 2m/s and 250W) respectively. The effective moisture diffusivity was calculated by using Fick's law. The results show an increase of effective moisture diffusivity from 7.52×10-11 to 2.64×10-9 m2.s-1 for air velocity of 2 m/s and microwave/air (at 2m/s and 250W) respectively. The temperature of the potato slices increased for higher microwaves power, but decreased for higher air velocity. The rehydration ratio, defined as the weight of the the sample after rehydration per the weight of dried sample, was determined at different water temperatures (25℃, 50℃, 75℃). The rehydration ratio increased with the water temperature and reached its maximum at the following conditions: 200 W for the microwave power, 2 m/s for the air velocity and 75°C for the water temperature. The present study shows the interest of microwave drying for the food preservation.

Keywords: drying, microwave, potato, rehydration

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29859 Assessment of the Impact of CSR on the Business Performance of Australian Banks

Authors: Montoya C.A., Erina J., Erina I.

Abstract:

The purpose of this research is to assess the performance and impact of CSR on business in the banking sector in Australia by applying the financial indicators of 20 ASX banks for the period from 2016-2017. The authors carried out CSR assessment in several stages of research: 1) gathering the nonfinancial and financial indicators of 20 ASX listed banks (available were only 16) from the annual reports of Australian banks for 2016 and 2017; 2) calculation of bank performance indicators using such financial indicators as return on assets (ROA), return on equity (ROE), efficiency ratio and net interest margin; 3) analysis of financial data using cross-sectional regression and answers to the research questions. Based on the obtained research results, the authors obtained answers to the initially raised research questions and came to a conclusion that Q1 - Insignificant positive coefficient result - slight positive relationship between CSR disclosure and business performance 2016; Q2 - Insignificant negative coefficient result - slight negative relationship between CSR disclosure and business performance 2017; Q3 - Insignificant positive coefficient result - slight positive relationship between CSR disclosure and business performance.

Keywords: Australia, banks, business performance, CSR

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29858 Numerical Investigation of Multiphase Flow Structure for the Flue Gas Desulfurization

Authors: Cheng-Jui Li, Chien-Chou Tseng

Abstract:

This study adopts Computational Fluid Dynamics (CFD) technique to build the multiphase flow numerical model where the interface between the flue gas and desulfurization liquid can be traced by Eulerian-Eulerian model. Inside the tower, the contact of the desulfurization liquid flow from the spray nozzles and flue gas flow can trigger chemical reactions to remove the sulfur dioxide from the exhaust gas. From experimental observations of the industrial scale plant, the desulfurization mechanism depends on the mixing level between the flue gas and the desulfurization liquid. In order to significantly improve the desulfurization efficiency, the mixing efficiency and the residence time can be increased by perforated sieve trays. Hence, the purpose of this research is to investigate the flow structure of sieve trays for the flue gas desulfurization by numerical simulation. In this study, there is an outlet at the top of FGD tower to discharge the clean gas and the FGD tower has a deep tank at the bottom, which is used to collect the slurry liquid. In the major desulfurization zone, the desulfurization liquid and flue gas have a complex mixing flow. Because there are four perforated plates in the major desulfurization zone, which spaced 0.4m from each other, and the spray array is placed above the top sieve tray, which includes 33 nozzles. Each nozzle injects desulfurization liquid that consists of the Mg(OH)2 solution. On each sieve tray, the outside diameter, the hole diameter, and the porosity are 0.6m, 20 mm and 34.3%. The flue gas flows into the FGD tower from the space between the major desulfurization zone and the deep tank can finally become clean. The desulfurization liquid and the liquid slurry goes to the bottom tank and is discharged as waste. When the desulfurization solution flow impacts the sieve tray, the downward momentum will be converted to the upper surface of the sieve tray. As a result, a thin liquid layer can be developed above the sieve tray, which is the so-called the slurry layer. And the volume fraction value within the slurry layer is around 0.3~0.7. Therefore, the liquid phase can't be considered as a discrete phase under the Eulerian-Lagrangian framework. Besides, there is a liquid column through the sieve trays. The downward liquid column becomes narrow as it interacts with the upward gas flow. After the flue gas flows into the major desulfurization zone, the flow direction of the flue gas is upward (+y) in the tube between the liquid column and the solid boundary of the FGD tower. As a result, the flue gas near the liquid column may be rolled down to slurry layer, which developed a vortex or a circulation zone between any two sieve trays. The vortex structure between two sieve trays results in a sufficient large two-phase contact area. It also increases the number of times that the flue gas interacts with the desulfurization liquid. On the other hand, the sieve trays improve the two-phase mixing, which may improve the SO2 removal efficiency.

Keywords: Computational Fluid Dynamics (CFD), Eulerian-Eulerian Model, Flue Gas Desulfurization (FGD), perforated sieve tray

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29857 Development of a Multi-Factorial Instrument for Accident Analysis Based on Systemic Methods

Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

Abstract:

The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: accident analysis, multi-factorial error modeling, risk, systemic methods

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29856 Remote Sensing through Deep Neural Networks for Satellite Image Classification

Authors: Teja Sai Puligadda

Abstract:

Satellite images in detail can serve an important role in the geographic study. Quantitative and qualitative information provided by the satellite and remote sensing images minimizes the complexity of work and time. Data/images are captured at regular intervals by satellite remote sensing systems, and the amount of data collected is often enormous, and it expands rapidly as technology develops. Interpreting remote sensing images, geographic data mining, and researching distinct vegetation types such as agricultural and forests are all part of satellite image categorization. One of the biggest challenge data scientists faces while classifying satellite images is finding the best suitable classification algorithms based on the available that could able to classify images with utmost accuracy. In order to categorize satellite images, which is difficult due to the sheer volume of data, many academics are turning to deep learning machine algorithms. As, the CNN algorithm gives high accuracy in image recognition problems and automatically detects the important features without any human supervision and the ANN algorithm stores information on the entire network (Abhishek Gupta., 2020), these two deep learning algorithms have been used for satellite image classification. This project focuses on remote sensing through Deep Neural Networks i.e., ANN and CNN with Deep Sat (SAT-4) Airborne dataset for classifying images. Thus, in this project of classifying satellite images, the algorithms ANN and CNN are implemented, evaluated & compared and the performance is analyzed through evaluation metrics such as Accuracy and Loss. Additionally, the Neural Network algorithm which gives the lowest bias and lowest variance in solving multi-class satellite image classification is analyzed.

Keywords: artificial neural network, convolutional neural network, remote sensing, accuracy, loss

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29855 Advancing Veterinary Health through Sustainable Solutions

Authors: Abdelkader Mohamed Abdelkader Mohamed Gaballah

Abstract:

This study addresses advancements in veterinary health and their significance in enhancing animal care. The primary objective is to meet the increasing needs of veterinarians and farmers by offering sustainable and effective veterinary medicines that comply with safety and efficacy standards. The methodology involves a comprehensive selection process to source high-quality veterinary products from trusted manufacturers while ensuring adherence to environmental sustainability principles. The findings demonstrate that these products significantly contribute to improving animal health, reducing the prevalence of diseases, and supporting sustainable farming practices. In conclusion, the study emphasizes the importance of collaborative efforts within the veterinary pharmaceutical industry to meet global demands and promote sustainable practices in animal care.

Keywords: veterinary medicine, animal health, veterinary pharmaceuticals, livestock management, animal science and care, veterinary drug development, animal nutrition, wellness

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29854 A Study of Anthraquinone Dye Removal by Using Chitosan Nanoparticles

Authors: Pyar S. Jassal, Sonal Gupta, Neema Chand, Rajni Johar

Abstract:

In present study, Low molecular weight chitosan naoparticles (LMWCNP) were synthesized by using low molecular weight chitosan (LMWC) and sodium tripolyphosphate for the adsorption of anthraquinone dyes from waste water. The ionic-gel technique was used for this purpose. Size of nanoparticles was determined by “Scherrer equation”. The absorbance was carried out with UV-visible spectrophotometer for Acid Green 25 (AG25) and Reactive Blue 4 (RB4) dyes solutions at λmax 644 and λmax 598 nm respectively. The removal of dyes was dependent on the pH and the optimum adsorption was between pH 2 to 9. The extraction of dyes was linearly dependent on temperature. The equilibrium parameters, RL was calculated by using the Langmuir isotherm and shows that adsorption of dyes is favorable on the LMWCNP. The XRD images of LMWC show a crystalline nature whereas LMWCNP is amorphous one. The thermo gravimetric analysis (TGA) shows that LMWCNP thermally more stable than LMWC. As the contact time increases, percentage removal of Acid Green 25 and Reactive Blue 4 dyes also increases. TEM images reveal the size of the LMWCNP were in the range of 45-50 nm. The capacity of AG25 dye on LMWC was 5.23 mg/g, it compared with LMWCNP capacity which was 6.83 mg/g respectively. The capacity of RB4 dye on LMWC was 2.30 mg/g and 2.34 mg/g was on LMWCNP.

Keywords: low molecular weight chitosan nanoparticles, anthraquinone dye, removal efficiency, adsorption isotherm

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29853 Hydrothermal Synthesis of V₂O₅-Carbon Nanotube Composite for Supercapacitor Application

Authors: Mamta Bulla, Vinay Kumar

Abstract:

The transition to renewable energy sources is essential due to the finite limitations of conventional fossil fuels, which contribute significantly to environmental pollution and greenhouse gas emissions. Traditional energy storage solutions, such as batteries and capacitors, are also hindered by limitations, particularly in capacity, cycle life, and energy density. Conventional supercapacitors, while able to deliver high power, often suffer from low energy density, limiting their efficiency in storing and providing renewable energy consistently. Renewable energy sources, such as solar and wind, produce power intermittently, so efficient energy storage solutions are required to manage this variability. Advanced materials, particularly those with high capacity and long cycle life, are critical to developing supercapacitors capable of effectively storing renewable energy. Among various electrode materials, vanadium pentoxide (V₂O₅) offers high theoretical capacitance, but its poor conductivity and cycling stability limit practical applications. This study explores the hydrothermal synthesis of a V₂O₅-carbon nanotube (CNT) composite to overcome these drawbacks, combining the high capacitance of V₂O₅ with the exceptional conductivity and mechanical stability of CNTs. The resulting V₂O₅-CNT composite demonstrates enhanced electrochemical performance, showing high specific capacitance of 890 F g⁻¹ at 0.1 A g⁻¹ current density, excellent rate capability, and improved cycling stability, making it a promising candidate for next-generation supercapacitors, with significant improvements in energy storage efficiency and durability.

Keywords: cyclability, energy density, nanocomposite, renewable energy, supercapacitor

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29852 Factors Affecting in Soil Analysis Technique Adopted by the Southern Region Farmers, Syria

Authors: Moammar Dayoub

Abstract:

The study aimed to know the reality of farmers and determine the extent of adoption of the recommendations of the fertilizer and the difficulties and problems they face. The study was conducted on a random sample of farmers consist of 95 farmers who had analysed their field soil in scientific research centres in agricultural southern region through the form specially prepared for this purpose, the results showed that the rate of adoption of the fertilizer recommendations whole amounted to an average of 36.9% in the southern region, The degree of adoption was 34.7% in the region. The results showed that 41% of farmers did not implement the recommendations because of the non-convenient analysis, and 34% due to neglect, and 15% due to the weather and an environment, while 10% of them for lack of manure in the suitable time. The study also revealed that Independent factors affecting the continuing adoption of soil analysis are: farms experience, sampling method in farmer’s schools, irrigated area, and personal knowledge of farmers in analysing the soil. Also, show that the application of fertilizer recommendations led to increased production by 15-20%, this analysis emphasizes the importance of soil analysis and adherence to the recommendations of the research centres.

Keywords: adoption, recommendations of the fertilizer, soil analysis, southern region

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29851 MHC Class II DRB1 Gene Polymorphism in Lori Sheep Breed

Authors: Shahram Nanekarani, Majid Goodarzi, Majid Khosravi

Abstract:

The present study aimed at analyzing of ovine major histocompatibility complex class II (Ovar II) DRB1 gene second exon in Lori Sheep breed. The MHC plays a central role in the control of disease resistance and immunological response. Genomic DNA from blood samples of 124 sheep was extracted and a 296 bp MHC exon 2 fragment was amplified using polymerase chain reaction. PCR products were characterized by the restriction fragment length polymorphism technique using Hin1I restriction enzyme. The PCRRFLP patterns showed three genotypes, AA, AB and BB with frequency of 0.282, 0.573 and 0.145, respectively. There was no significant (P > 0.05) deviation from Hardy–Weinberg equilibrium for this locus in this population. The results of the present study indicate that exon 2 of the Ovar-DRB1 gene is highly polymorphic in Lori sheep and could be considered as an important marker assisted selection, for improvement of immunity in sheep.

Keywords: MHC-DRB1 gene, polymorphism, PCR-RFLP, lori sheep

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29850 Preparation and In vitro Characterization of Nanoparticle Hydrogel for Wound Healing

Authors: Rajni Kant Panik

Abstract:

The aim of the present study was to develop and evaluate mupirocin loaded nanoparticle incorporated into hydrogel as an infected wound healer. Incorporated Nanoparticle in hydrogel provides a barrier that effectively prevents the contamination of the wound and further progression of infection to deeper tissues. Hydrogel creates moist healing environment on wound space with good fluid absorbance. Nanoparticles were prepared by double emulsion solvent evaporation method using different ratios of PLGA polymer and the hydrogels was developed using sodium alginate and gelatin. Further prepared nanoparticles were then incorporated into the hydrogels. The formulations were characterized by FT-IR and DSC for drug and polymer compatibility and surface morphology was studied by TEM. Nanoparticle hydrogel were evaluated for their size, shape, encapsulation efficiency and for in vitro studies. The FT-IR and DSC confirmed the absence of any drug polymer interaction. The average size of Nanoparticle was found to be in range of 208.21-412.33 nm and shape was found to be spherical. The maximum encapsulation efficiency was found to be 69.03%. The in vitro release profile of Nanoparticle incorporated hydrogel formulation was found to give sustained release of drug. Antimicrobial activity testing confirmed that encapsulated drug preserve its effectiveness. The stability study confirmed that the formulation prepared were stable. Present study complements our finding that mupirocin loaded Nanoparticle incorporated into hydrogel has the potential to be an effective and safe novel addition for the release of mupirocin in sustained manner, which may be a better option for the management of wound. These finding also supports the progression of antibiotic via hydrogel delivery system is a novel topical dosage form for the management of wound.

Keywords: hydrogel, nanoparticle, PLGA, wound healing

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29849 Cellulolytic and Xylanolytic Enzymes from Mycelial Fungi

Authors: T. Sadunishvili, L. Kutateladze, T. Urushadze, R. Khvedelidze, N. Zakariashvili, M. Jobava, G. Kvesitadze

Abstract:

Multiple repeated soil-climatic zones in Georgia determines the diversity of microorganisms. Hundreds of microscopic fungi of different genera have been isolated from different ecological niches, including some extreme environments. Biosynthetic ability of microscopic fungi has been studied. Trichoderma ressei, representative of the Ascomycetes secrete cellulolytic and xylanolytic enzymes that act in synergy to hydrolyze polysaccharide polymers to glucose, xylose and arabinose, which can be fermented to biofuels. The other mesophilic strains producing cellulases are Allesheria terrestris, Chaetomium thermophile, Fusarium oxysporium, Piptoporus betulinus, Penicillium echinulatum, P. purpurogenum, Aspergillus niger, A. wentii, A. versicolor, A. fumigatus etc. In the majority of the cases the cellulases produced by strains of genus Aspergillus usually have high β-glucosidase activity and average endoglucanases levels (with some exceptions), whereas strains representing Trichoderma have high endo enzyme and low β-glucosidase, and hence has limited efficiency in cellulose hydrolysis. Six producers of stable cellulases and xylanases from mesophilic and thermophilic fungi have been selected. By optimization of submerged cultivation conditions, high activities of cellulases and xylanases were obtained. For enzymes purification, their sedimentation by organic solvents such as ethyl alcohol, acetone, isopropanol and by ammonium sulphate in different ratios have been carried out. Best results were obtained with precipitation by ethyl alcohol (1:3.5) and ammonium sulphate. The yields of enzyme according to cellulase activities were 80-85% in both cases. Cellulase activity of enzyme preparation obtained from the strain Trichoderma viride X 33 is 126 U/g, from the strain Penicillium canescence D 85–185U/g and from the strain Sporotrichum pulverulentum T 5-0 110 U/g. Cellulase activity of enzyme preparation obtained from the strain Aspergillus sp. Av10 is 120 U/g, xylanase activity of enzyme preparation obtained from the strain Aspergillus niger A 7-5–1155U/g and from the strain Aspergillus niger Aj 38-1250 U/g. Optimum pH and temperature of operation and thermostability, of the enzyme preparations, were established. The efficiency of hydrolyses of different agricultural residues by the microscopic fungi cellulases has been studied. The glucose yield from the residues as a result of enzymatic hydrolysis is highly determined by the ratio of enzyme to substrate, pH, temperature, and duration of the process. Hydrolysis efficiency was significantly increased as a result of different pretreatment of the residues by different methods. Acknowledgement: The Study was supported by the ISTC project G-2117, funded by Korea.

Keywords: cellulase, xylanase, microscopic fungi, enzymatic hydrolysis

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29848 Views of Middle-Aged Women in Malaysia towards Menopause: A Qualitative Study

Authors: Halimatus Sakdiah Minhat, Hamizah Sulaiman

Abstract:

Introduction: Old age is commonly link with menopause among women. The main purpose of this study is to explore the views of middle-aged women and its association with menopause. Methods: Qualitative interviews in the form of focus group discussions (FGD) were conducted among women aged between 35 and 59 years old living in urban localities in two different states in Malaysia. Selection of respondents were conducted using the maximum variation sampling, focussing on five age categories which are between 35 to 39, 40 to 44, 45 to 49, 50 to 54 and 55 to 59 years old. Each FGD involved 5 to 7 respondents and lasted for 1 to 2 hours each. The content of the interviews were recorded, transcribed verbatim after each interview before the next focus group discussion is conducted. Field notes of reflexive observations were recorded by the rapporteur. Individual transcripts were analysed using standard methods of qualitative thematic analysis. The material was read through twice and later coded. The codes were further collapsed into several key themes related to perceptions towards menopause among the respondents. Results: A total number of 36 middle-aged women were consented for the interviews. The contents of the interviews revealed that younger women tend to associate menopause with being old, which were dominated by the younger aged categories of less than 50 years old. Majority of the respondents linked menopause with end of woman’s reproductive capacity or inability to give birth, lethargic or endless feeling of tiredness and insomnia, emotional instability or having more sensitive feelings and also the beginning of many health problems such as osteoarthritis which they perceived very synonyms with being old. Conclusion: The findings of this study indirectly reflect the negative views towards menopause among the middle-aged women in Malaysia. Being residents in the urban areas equipped with advanced technology and health information, do not exclude them from having negative views about menopause. However, this is a qualitative study which only focussing on age ranges, regardless of their socioeconomic and demographic background, which make further studies on related issues are necessaries. The fact that it was a qualitative interview, the findings could not be generalised and only specific to the targeted population.

Keywords: Menopause, Middle-aged women, old, Malaysia

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29847 Human 3D Metastatic Melanoma Models for in vitro Evaluation of Targeted Therapy Efficiency

Authors: Delphine Morales, Florian Lombart, Agathe Truchot, Pauline Maire, Pascale Vigneron, Antoine Galmiche, Catherine Lok, Muriel Vayssade

Abstract:

Targeted therapy molecules are used as a first-line treatment for metastatic melanoma with B-Raf mutation. Nevertheless, these molecules can cause side effects to patients and are efficient on 50 to 60 % of them. Indeed, melanoma cell sensitivity to targeted therapy molecules is dependent on tumor microenvironment (cell-cell and cell-extracellular matrix interactions). To better unravel factors modulating cell sensitivity to B-Raf inhibitor, we have developed and compared several melanoma models: from metastatic melanoma cells cultured as monolayer (2D) to a co-culture in a 3D dermal equivalent. Cell response was studied in different melanoma cell lines such as SK-MEL-28 (mutant B-Raf (V600E), sensitive to Vemurafenib), SK-MEL-3 (mutant B-Raf (V600E), resistant to Vemurafenib) and a primary culture of dermal human fibroblasts (HDFn). Assays have initially been performed in a monolayer cell culture (2D), then a second time on a 3D dermal equivalent (dermal human fibroblasts embedded in a collagen gel). All cell lines were treated with Vemurafenib (a B-Raf inhibitor) for 48 hours at various concentrations. Cell sensitivity to treatment was assessed under various aspects: Cell proliferation (cell counting, EdU incorporation, MTS assay), MAPK signaling pathway analysis (Western-Blotting), Apoptosis (TUNEL), Cytokine release (IL-6, IL-1α, HGF, TGF-β, TNF-α) upon Vemurafenib treatment (ELISA) and histology for 3D models. In 2D configuration, the inhibitory effect of Vemurafenib on cell proliferation was confirmed on SK-MEL-28 cells (IC50=0.5 µM), and not on the SK-MEL-3 cell line. No apoptotic signal was detected in SK-MEL-28-treated cells, suggesting a cytostatic effect of the Vemurafenib rather than a cytotoxic one. The inhibition of SK-MEL-28 cell proliferation upon treatment was correlated with a strong expression decrease of phosphorylated proteins involved in the MAPK pathway (ERK, MEK, and AKT/PKB). Vemurafenib (from 5 µM to 10 µM) also slowed down HDFn proliferation, whatever cell culture configuration (monolayer or 3D dermal equivalent). SK-MEL-28 cells cultured in the dermal equivalent were still sensitive to high Vemurafenib concentrations. To better characterize all cell population impacts (melanoma cells, dermal fibroblasts) on Vemurafenib efficacy, cytokine release is being studied in 2D and 3D models. We have successfully developed and validated a relevant 3D model, mimicking cutaneous metastatic melanoma and tumor microenvironment. This 3D melanoma model will become more complex by adding a third cell population, keratinocytes, allowing us to characterize the epidermis influence on the melanoma cell sensitivity to Vemurafenib. In the long run, the establishment of more relevant 3D melanoma models with patients’ cells might be useful for personalized therapy development. The authors would like to thank the Picardie region and the European Regional Development Fund (ERDF) 2014/2020 for the funding of this work and Oise committee of "La ligue contre le cancer".

Keywords: 3D human skin model, melanoma, tissue engineering, vemurafenib efficiency

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29846 Numerical Iteration Method to Find New Formulas for Nonlinear Equations

Authors: Kholod Mohammad Abualnaja

Abstract:

A new algorithm is presented to find some new iterative methods for solving nonlinear equations F(x)=0 by using the variational iteration method. The efficiency of the considered method is illustrated by example. The results show that the proposed iteration technique, without linearization or small perturbation, is very effective and convenient.

Keywords: variational iteration method, nonlinear equations, Lagrange multiplier, algorithms

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29845 Using Machine Learning to Extract Patient Data from Non-standardized Sports Medicine Physician Notes

Authors: Thomas Q. Pan, Anika Basu, Chamith S. Rajapakse

Abstract:

Machine learning requires data that is categorized into features that models train on. This topic is important to the field of sports medicine due to the many tools it provides to physicians such as diagnosis support and risk assessment. Physician note that healthcare professionals take are usually unclean and not suitable for model training. The objective of this study was to develop and evaluate an advanced approach for extracting key features from sports medicine data without the need for extensive model training or data labeling. An LLM (Large Language Model) was given a narrative (Physician’s Notes) and prompted to extract four features (details about the patient). The narrative was found in a datasheet that contained six columns: Case Number, Validation Age, Validation Gender, Validation Diagnosis, Validation Body Part, and Narrative. The validation columns represent the accurate responses that the LLM attempts to output. With the given narrative, the LLM would output its response and extract the age, gender, diagnosis, and injured body part with each category taking up one line. The output would then be cleaned, matched, and added to new columns containing the extracted responses. Five ways of checking the accuracy were used: unclear count, substring comparison, LLM comparison, LLM re-check, and hand-evaluation. The unclear count essentially represented the extractions the LLM missed. This can be also understood as the recall score ([total - false negatives] over total). The rest of these correspond to the precision score ([total - false positives] over total). Substring comparison evaluated the validation (X) and extracted (Y) columns’ likeness by checking if X’s results were a substring of Y's findings and vice versa. LLM comparison directly asked an LLM if the X and Y’s results were similar. LLM Re-check prompted the LLM to see if the extracted results can be found in the narrative. Lastly, A selection of 1,000 random narratives was also selected and hand-evaluated to give an estimate of how well the LLM-based feature extraction model performed. With a selection of 10,000 narratives, the LLM-based approach had a recall score of roughly 98%. However, the precision scores of the substring comparison and LLM comparison models were around 72% and 76% respectively. The reason for these low figures is due to the minute differences between answers. For example, the ‘chest’ is a part of the ‘upper trunk’ however, these models cannot detect that. On the other hand, the LLM re-check and subset of hand-tested narratives showed a precision score of 96% and 95%. If this subset is used to extrapolate the possible outcome of the whole 10,000 narratives, the LLM-based approach would be strong in both precision and recall. These results indicated that an LLM-based feature extraction model could be a useful way for medical data in sports to be collected and analyzed by machine learning models. Wide use of this method could potentially increase the availability of data thus improving machine learning algorithms and supporting doctors with more enhanced tools.

Keywords: AI, LLM, ML, sports

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29844 Human Resources Management Practices in Hospitality Companies

Authors: Dora Martins, Susana Silva, Cândida Silva

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Human Resources Management (HRM) has been recognized by academics and practitioners as an important element in organizations. Therefore, this paper explores the best practices of HRM and seeks to understand the level of participation in the development of these practices by human resources managers in the hospitality industry and compare it with other industries. Thus, the study compared the HRM practices of companies in the hospitality sector with HRM practices of companies in other sectors, and identifies the main differences between their HRM practices. The results show that the most frequent HRM practices in all companies, independently of its sector of activity, are hiring and training. When comparing hospitality sector with other sectors of activity, some differences were noticed, namely in the adoption of the practices of communication and information sharing, and of recruitment and selection. According to these results, the paper discusses the major theoretical and practical implications. Suggestions for future research are also presented.

Keywords: exploratory study, human resources management practices, human resources manager, hospitality companies, Portuguese companies

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29843 Prediction of the Heat Transfer Characteristics of Tunnel Concrete

Authors: Seung Cho Yang, Jae Sung Lee, Se Hee Park

Abstract:

This study suggests the analysis method to predict the damages of tunnel concrete caused by fires. The result obtained from the analyses of concrete temperatures at a fire in a tunnel using ABAQUS was compared with the test result. After the reliability of the analysis method was verified, the temperatures of a tunnel at a real fire and those of concrete during the fire were estimated to predict fire damages. The temperatures inside the tunnel were estimated by FDS, a CFD model. It was deduced that the fire performance of tunnel lining and the fire damages of the structure at an actual fire could be estimated by the analysis method.

Keywords: fire resistance, heat transfer, numerical analysis, tunnel fire

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29842 Study of Fork Marks on Sapphire Wafers in Plasma Enhanced Chemical Vapor Deposition Tool

Authors: Qiao Pei Wen, Ng Seng Lee, Sae Tae Veera, Chiu Ah Fong, Loke Weng Onn

Abstract:

Thin film thickness uniformity is crucial to get consistent film etch rate and device yield across the wafer. In the capacitive-coupled parallel plate PECVD system; the film thickness uniformity can be affected by many factors such as the heater temperature uniformity, the spacing between top and bottom electrode, RF power, pressure, gas flows and etc. In this paper, we studied how the PECVD SiN film thickness uniformity is affected by the substrate electrical conductivity and the RF power coupling efficiency. PECVD SiN film was deposited on 150-mm sapphire wafers in 200-mm Lam Sequel tool, fork marks were observed on the wafers. On the fork marks area SiN film thickness is thinner than that on the non-fork area. The forks are the wafer handler inside the process chamber to move the wafers from one station to another. The sapphire wafers and the ceramic forks both are insulator. The high resistivity of the sapphire wafers and the forks inhibits the RF power coupling efficiency during PECVD deposition, thereby reducing the deposition rate. Comparing between the high frequency and low frequency RF power (HFRF and LFRF respectively), the LFRF power coupling effect on the sapphire wafers is more dominant than the HFRF power on the film thickness. This paper demonstrated that the SiN thickness uniformity on sapphire wafers can be improved by depositing a thin TiW layer on the wafer before the SiN deposition. The TiW layer can be on the wafer surface, bottom or any layer before SiN deposition.

Keywords: PECVD SiN deposition, sapphire wafer, substrate electrical conductivity, RF power coupling, high frequency RF power, low frequency RF power, film deposition rate, thickness uniformity

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29841 Electro-Optic Parameters of Ferroelectric Particles- Liquid Crystal Composites

Authors: T. D. Ibragimov, A. R. Imamaliyev, G. M. Bayramov

Abstract:

Influence of barium titanate particles on electro-optic properties of liquid crystal 4-cyano-4′-pentylbiphenyl (5CB) with positive dielectric anisotropy and the liquid crystalline (LC) mixture Н-37 consisting of 4-methoxybezylidene-4'–butylaniline and 4-ethoxybezylidene-4'–butylaniline with negative dielectric anisotropy was investigated. It was shown that a presence of particles inside 5СВ and H-37 decreased the clearing temperature from 35.2 °С to 32.5°С and from 61.2 oC to 60.1oC, correspondingly. The threshold voltage of the Fredericksz effect became 0.3 V for the BaTiO3-5CB colloid while the beginning of this effect of the pure 5СВ was observed at 2.1 V. Threshold voltage of the Fredericksz effect increased from 2.8 V to up 3.1 V at additive of particles into H-37. A rise time of the BaTiO3-5CB colloid improved while a decay time worsened in comparison with the pure 5CB at all applied voltages. The inverse trends were observed for the H-37 matrix, namely, a rise time worsened and a decay time improved. Among other things, the effect of fast light modulation was studied at application of the rectangular impulse with direct bias to an electro-optical cell with the BaTiO3 particles+5CB and the pure 5CB. At this case, a rise time of the composite worsened, a decay time improved in comparison with the pure 5CB. The pecularities of electrohydrodynamic instability (EHDI) formation was also investigated into the composite with the H-37 matrix. It was found that the voltage of the EHDI formation decreased, a rise time increased and a decay time decreased in comparison with the pure H-37. First of all, experimental results are explained by appearance of local electric fields near the polarized ferroelectric particles at application of external electric field and an existence of the additional obstacles (particles) for movement of ions.

Keywords: liquid crystal, ferroelectric particles, composite, electro-optics

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29840 Removal of Polycyclic Aromatic Hydrocarbons (PAHS) and the Response of Indigenous Bacteria in Highly Contaminated Aged Soil after Persulfate Oxidation

Authors: Yaling Gou, Sucai Yang, Pengwei Qiao

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Integrated chemical-biological treatment is an attractive alternative to remove polycyclic aromatic hydrocarbons (PAHs) from contaminated soil; wherein indigenous bacteria is the key factor for the biodegradation of residual PAHs concentrations after the application of chemical oxidation. However, the systematical study on the impact of persulfate (PS) oxidation on indigenous bacteria as well as PAHs removal is still scarce. In this study, the influences of different PS dosages (1%, 3%, 6%, and 10% [w/w]), as well as various activation methods (native iron, H2O2, alkaline, ferrous iron, and heat) on PAHs removal and indigenous bacteria in highly contaminated aged soil were investigated. Apparent degradation of PAHs in the soil treated with PS oxidation was observed, and the removal efficiency of total PAHs in the soil ranged from 38.28% to 79.97%. The removal efficiency of total PAHs in the soil increased with increasing consumption of PS. However, the bacterial abundance in soil was negatively affected following oxidation for all of the treatments added with PS, with bacterial abundance in the soil decreased by 0.89~2.88 orders of magnitude compared to the untreated soil. Moreover, the number of total bacteria in the soil decreased as PS consumption increased. Different PS activation methods and PS dosages exhibited different influences on the bacterial community composition. Bacteria capable of degrading PAHs under anoxic conditions were composed predominantly by Proteobacteria and Firmicutes. The total amount of Proteobacteria and Firmicutes also decreased with increasing consumption of PS. The results of this study provide important insight into the design of PAHs contaminated soil remediation projects.

Keywords: activation method, chemical oxidation, indigenous bacteria, polycyclic aromatic hydrocarbon

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29839 Experimental Analysis of the Origins of the Anisotropy Behavior in the 2017 AA Aluminum Alloy

Authors: May Abdelghani

Abstract:

The present work is devoted to the study of the microstructural anisotropy in mechanical cyclic behavior of the 2017AA aluminum alloy which is widely used in the aerospace industry. The main purpose of the study is to investigate the microstructural origins of this anisotropy already confirmed in our previous work in 2017AA aluminum alloy. To do this, we have used the microstructural analysis resources such as Scanning Electron Microscope (SEM) to see the differences between breaks from different directions of cyclic loading. Another resource of investigation was used in this study is that the EBSD method, which allows us to obtain a mapping of the crystallographic texture of our material. According to the obtained results in the microscopic analysis, we are able to identify the origins of the anisotropic behavior at the macroscopic scale.

Keywords: fatigue damage, cyclic behavior, anisotropy, microstructural analysis

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29838 Design, Optimize the Damping System for Optical Scanning Equipment

Authors: Duy Nhat Tran, Van Tien Pham, Quang Trung Trinh, Tien Hai Tran, Van Cong Bui

Abstract:

In recent years, artificial intelligence and the Internet of Things have experienced significant advancements. Collecting image data and real-time analysis and processing of tasks have become increasingly popular in various aspects of life. Optical scanning devices are widely used to observe and analyze different environments, whether fixed outdoors, mounted on mobile devices, or used in unmanned aerial vehicles. As a result, the interaction between the physical environment and these devices has become more critical in terms of safety. Two commonly used methods for addressing these challenges are active and passive approaches. Each method has its advantages and disadvantages, but combining both methods can lead to higher efficiency. One solution is to utilize direct-drive motors for position control and real-time feedback within the operational range to determine appropriate control parameters with high precision. If the maximum motor torque is smaller than the inertial torque and the rotor reaches the operational limit, the spring system absorbs the impact force. Numerous experiments have been conducted to demonstrate the effectiveness of device protection during operation.

Keywords: optical device, collision safety, collision absorption, precise mechanics

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29837 An Efficient Motion Recognition System Based on LMA Technique and a Discrete Hidden Markov Model

Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

Procedia PDF Downloads 214
29836 Analysing Maximum Power Point Tracking in a Stand Alone Photovoltaic System

Authors: Osamede Asowata

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Optimized gain in respect to output power of stand-alone photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident in its low carbon emission and efficiency. Power failure or outage from commercial providers, in general, does not promote development to public and private sector; these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with maximum power point tracking (MPPT) from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0°N, with a corresponding tilt angle of 36°, 26°, and 16°. Preliminary results include regression analysis (normal probability plot) showing the maximum power point in the system as well the best tilt angle for maximum power point tracking.

Keywords: poly-crystalline PV panels, solar chargers, tilt and orientation angles, maximum power point tracking, MPPT, Pulse Width Modulation (PWM).

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29835 Cardiovascular Disease Prediction Using Machine Learning Approaches

Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 159
29834 Assessing the Efficiency of Sports Stadiums in India: An Explorative Study of Socio-Economic Sustainability

Authors: Shivam Adhikary

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Sports stadiums are not merely public amenities for entertainment and recreation for a city. They are buildings with extremely high construction investment and running costs which holds the supreme responsibility of social integration, nation building and financial upliftment of the community apart from its primary motive of conducting and promotion of the sports. But the present scenario of sports performances at international events and growing physical inactivity among the youth in India show that the sports facilities are far behind in achieving these goals. A pilot study of Indira Gandhi Sports complex in Vijayawada, Andhra Pradesh gave an indication of underutilization of sports stadia in India. This probed a crying need for the assessment of the present usage and functioning of the major sports (non-cricketing) facilities within the country. This paper assesses the sustainability of stadiums built for national and international sporting (non-cricket) events in terms of sporting, socio-cultural and financial sustainability by mainly focusing on their usage in non-event days. The criteria for the assessment and comparison of the stadiums within the nation is done using World Stadium Index and GDI (Gross Domestic Income) while with international counterparts using WSI and GNI (Gross National Income). The pilot case of India Gandhi Sports complex in Vijayawada is further investigated for a deeper understanding of the present usage, the existing issues for its underutilization and the way-forward (at least a few) to reach its sustainable potential. The paper finally concludes with the discussion on whether sports stadiums are being utilized to its financial potential and if it is at par with its international counterparts.

Keywords: economic sustainability, social sustainability, sports infrastructure, stadium efficiency

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29833 Advancements in Predicting Diabetes Biomarkers: A Machine Learning Epigenetic Approach

Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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29832 Closing the Gap: Efficient Voxelization with Equidistant Scanlines and Gap Detection

Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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29831 Integrated Process Modelling of a Thermophilic Biogas Plant

Authors: Obiora E. Anisiji, Jeremiah L. Chukwuneke, Chinonso H. Achebe, Paul C. Okolie

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This work developed a mathematical model of a biogas plant from a mechanistic point of view, for urban area clean energy requirement. It aimed at integrating thermodynamics; which deals with the direction in which a process occurs and Biochemical kinetics; which gives the understanding of the rates of biochemical reaction. The mathematical formulation of the proposed gas plant follows the fundamental principles of thermodynamics, and further analysis were accomplished to develop an algorithm for evaluating the plant performance preferably in terms of daily production capacity. In addition, the capacity of the plant is equally estimated for a given cycle of operation and presented in time histories. A nominal 1500m3 biogas plant was studied characteristically and its performance efficiency evaluated. It was observed that the rate of biogas production is essentially a function of enthalpy ratio, the reactor temperature, pH, substrate concentration, rate of degradation of the biomass, and the accumulation of matter in the system due to bacteria growth. The results of this study conform to a very large extent with reported empirical data of some existing plant and further model validations were conducted in line with classical records found in literature.

Keywords: anaerobic digestion, biogas plant, biogas production, bio-reactor, energy, fermentation, rate of production, temperature, therm

Procedia PDF Downloads 439