Search results for: antioxidant potential
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12168

Search results for: antioxidant potential

9888 Limos Lactobacillus Fermentum from Buffalo Milk Is Suitable for Potential Biotechnological Process Development

Authors: Sergio D’Ambrosioa, Azza Dobousa, Chiara Schiraldia, Donatella Ciminib

Abstract:

Probiotics are living microorganisms that give beneficial effects while consumed. Lactic acid bacteria and bifidobacteria are among the most representative strains assessed as probiotics and exploited as food supplements. Numerous studies demonstrated their potential as a therapeutic candidate for a variety of diseases (restoring gut flora, lowering cholesterol, immune response-enhancing, anti-inflammation and anti-oxidation activities). These beneficial actions are also due to biomolecules produced by probiotics, such as exopolysaccharides (EPSs), that demonstrate plenty of beneficial properties such as antimicrobial, antitumor, anti-biofilm, antiviral and immunomodulatory activities. Limosilactobacillus fermentum is a widely studied member of probiotics; however, few data are available on the development of fermentation and downstream processes for the production of viable biomasses for potential industrial applications. However, few data are available on the development of fermentation processes for the large-scale production of probiotics biomass for industrial applications and for purification processes of EPSs at an industrial scale. For this purpose, L. fermentum strain was isolated from buffalo milk and used as a test example for biotechnological process development. The strain was able to produce up to 109 CFU/mL on a (glucose-based) semi-defined medium deprived of animal-derived raw materials up to the pilot scale (150 L), demonstrating improved results compared to commonly used, although industrially not suitable, media-rich of casein and beef extract. Biomass concentration via microfiltration on hollow fibers, and subsequent spray-drying allowed to recover of about 5.7 × 1010CFU/gpowder of viable cells, indicating strain resistance to harsh processing conditions. Overall, these data demonstrate the possibility of obtaining and maintaining adequate levels of viable L. fermentum cells by using a simple approach that is potentially suitable for industrial development. A downstream EPS purification protocol based on ultrafiltration, precipitation and activated charcoal treatments showed a purity of the recovered polysaccharides of about 70-80%.

Keywords: probiotics, fermentation, exopolysaccharides (EPSs), purification

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9887 Preliminary Study of the Potential of Propagation by Cuttings of Juniperus thurefera in Aures (Algeria)

Authors: N. Khater, I. Djbablia, A. Telaoumaten, S. A. Menina, H. Benbouza

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Thureferous Juniper is an endemic cupressacée constitutes a forest cover in the mountains of Aures (Algeria ). It is an heritage and important ecological richness, but continues to decline, highly endangered species in danger of extinction, these populations show significant originality due to climatic conditions of the environment, because of its strength and extraordinary vitality, made a powerful but fragile and unique ecosystem in which natural regeneration by seed is almost absent in Algeria. Because of the quality of seeds that are either dormant or affected at the tree and the ground level by a large number of pests and parasites, which will lead to the total disappearance of this species and consequently leading to the biodiversity. View the ecological and social- economic interest presented by this case, it deserves to be preserved and produced in large quantities in this respect. The present work aims to try to regenerate the Juniperus thurefera via vegetative propagation. We studied the potential of cuttings to form adventitious roots and buds. Cuttings were taken from young subjects from 5 to 20 years treated with indole butyric acid (AIB) and planted out inside perlite under atomizer whose temperature and light are controlled. The results show that the rate of rooting is important and encourages the regeneration of this species through vegetative propagation.

Keywords: juniperus thurefera, indole butyric acid, cutting, buds, rooting

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9886 Development of Sustainable Composite Fabric from Orange Peel for Ladies’ Undergarments: A Different Approach Towards Eco-Friendly Textile Design

Authors: Abdul Hafeez, Samiya Shehzadi

Abstract:

This research paper presents a different approach towards eco-friendly textile design by developing a sustainable composite fabric from orange peel for ladies' undergarments. The research focuses on utilizing orange peel to develop a unique orange leather/composite (fabric) through a process involving heating, extracting, and subsequent sun-drying to obtain the composite. The sustainable composite fabric shows properties that are favorable to the development of environmentally friendly undergarments, which not only offer UV protection but also possess healing properties for the skin. Through comprehensive testing and analysis, it has been determined that the orange peel composite fabric has zero harmful effects on the skin, making it a safe and desirable material for intimate wear. Furthermore, the research suggests that the orange peel composite fabric has the potential to reduce the rate of cancer cell growth. While the exact mechanisms and factors contributing to this effect require further investigation, the initial findings indicate promising aspects of the fabric in terms of potential cancer-preventive properties. Research contribution to the field of sustainable textile design by introducing a usual and eco-friendly approach utilizing orange peel waste. This work opens up avenues for further exploration and development of innovative materials that are both sustainable and beneficial for human health.

Keywords: sustainability, composite textiles, extracting, undergarments, eco-friendly, orange peels

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9885 The Potential Effectiveness of Marine Algae in Removal of Heavy Metal from Aqueous Medium

Authors: Wed Albalawi, Ebtihaj Jambi, Maha Albazi, Shareefa AlGhamdi

Abstract:

Heavy metal pollution has become a hard threat to marine ecosystems alongside extremely industrialized and urban (urbanized) zones because of their toxicity, resolution, and non-biodegradable nature. Great interest has been given to a new technique -biosorption- which exploits the cell envelopes of organisms to remove metals from water solutions. The main objective of the present study is to explore the potential of marine algae from the Red Sea for the removal of heavy metals from an aqueous medium. The subsequent objective is to study the effect of pH and agitation time on the adsorption capacity of marine algae. Randomly chosen algae from the Red Sea (Jeddah) with known altitude and depth were collected. Analysis of heavy metal ion concentration was measured by ICP-OES (Inductively coupled plasma - optical emission spectrometry) using air argon gas. A standard solution of heavy metal ions was prepared by diluting the original standard solution with ultrapure water. Types of seaweed were used to study the effect of pH on the biosorption of different heavy metals. The biosorption capacity of Cr is significantly lower in Padina Pavonica (P.P) compared to the biosorption capacity in Sargassum Muticum (S.M). The S.M exhibited significantly higher in Cr removal than the P.P at pH 2 and pH 7. However, the P.P exhibited significantly higher in Cr removal than the S.M at pH 3, pH 4, pH 5, pH 6, and pH 8. In conclusion, the dried cells of algae can be used as an effective tool for the removal of heavy metals.

Keywords: biosorption, heavy metal, pollution, pH value, brown algae

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9884 Electroactive Fluorene-Based Polymer Films Obtained by Electropolymerization

Authors: Mariana-Dana Damaceanu

Abstract:

Electrochemical oxidation is one of the most convenient ways to obtain conjugated polymer films as polypyrrole, polyaniline, polythiophene or polycarbazole. The research in the field has been mainly directed to the study of electrical conduction properties of the materials obtained by electropolymerization, often the main reason being their use as electroconducting electrodes, and very little attention has been paid to the morphological and optical quality of the films electrodeposited on flat surfaces. Electropolymerization of the monomer solution was scarcely used in the past to manufacture polymer-based light-emitting diodes (PLED), most probably due to the difficulty of obtaining defectless polymer films with good mechanical and optical properties, or conductive polymers with well controlled molecular weights. Here we report our attempts in using electrochemical deposition as appropriate method for preparing ultrathin films of fluorene-based polymers for PLED applications. The properties of these films were evaluated in terms of structural morphology, optical properties, and electrochemical conduction. Thus, electropolymerization of 4,4'-(9-fluorenylidene)-dianiline was performed in dichloromethane solution, at a concentration of 10-2 M, using 0.1 M tetrabutylammonium tetrafluoroborate as electrolyte salt. The potential was scanned between 0 and 1.3 V on the one hand, and 0 - 2 V on the other hand, when polymer films with different structures and properties were obtained. Indium tin oxide-coated glass substrate of different size was used as working electrode, platinum wire as counter electrode and calomel electrode as reference. For each potential range 100 cycles were recorded at a scan rate of 100 mV/s. The film obtained in the potential range from 0 to 1.3 V, namely poly(FDA-NH), is visible to the naked eye, being light brown, transparent and fluorescent, and displays an amorphous morphology. Instead, the electrogrowth poly(FDA) film in the potential range of 0 - 2 V is yellowish-brown and opaque, presenting a self-assembled structure in aggregates of irregular shape and size. The polymers structure was identified by FTIR spectroscopy, which shows the presence of broad bands specific to a polymer, the band centered at approx. 3443 cm-1 being ascribed to the secondary amine. The two polymer films display two absorption maxima, at 434-436 nm assigned to π-π* transitions of polymers, and another at 832 and 880 nm assigned to polaron transitions. The fluorescence spectra indicated the presence of emission bands in the blue domain, with two peaks at 422 and 488 nm for poly (FDA-NH), and four narrow peaks at 422, 447, 460 and 484 nm for poly(FDA), peaks originating from fluorene-containing segments of varying degrees of conjugation. Poly(FDA-NH) exhibited two oxidation peaks in the anodic region and the HOMO energy value of 5.41 eV, whereas poly(FDA) showed only one oxidation peak and the HOMO level localized at 5.29 eV. The electrochemical data are discussed in close correlation with the proposed chemical structure of the electrogrowth films. Further research will be carried out to study their use and performance in light-emitting devices.

Keywords: electrogrowth polymer films, fluorene, morphology, optical properties

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9883 Organic Geochemistry and Oil-Source Correlation of Cretaceous Sediments in the Kohat Basin, Pakistan

Authors: Syed Mamoon Siyar, Fayaz Ali, Sajjad Ahmad, Samina Jahandad, George Kontakiotis, Hammad T. Janjuhah, Assimina Antonarakou, Waqas Naseem

Abstract:

The Cretaceous Chichali Formation in the Chanda-01, Chanda-02, Chanda-03 and Mela-05 wells and the oil samples from Chanda-01 and Chanda-01 wells located in the Kohat Basin, Pakistan, were analyzed with the objectives of evaluating the hydrocarbon generation potential, source, thermal maturity and depositional of organic matter, and oil-source correlation by employing geochemical screening techniques and biomarker studies. The total organic carbon (TOC) values in Chanda-02, Chanda-03 and Mela-05 indicate, in general, poor to fair, fair and fair to good source rock potential with low genetic potential, respectively. The nature of organic matter has been determined by standard cross plots of Rock Eval pyrolysis parameters, indicating that studied cuttings from the Chichali Formation dominantly contain type III kerogen at present and show maturity for oil generation in the studied wells. The organic petrographic study also confirmed the vitrinite (type III) as a major maceral in the investigated Chichali Shales and its reflectance values show maturity for oil. The different ratios of non-biomarkers and biomarkers i.e., steranes, terpenes and aromatics parameters, indicate the marine source of organic matter deposited in the anoxic environment for the Chichali Formation in Chanda-01 and Chanda-02 wells and mixed source input of organic matter deposited in suboxic conditions for oil in the same wells. The CPI, and different biomarkers parameters such as C29 S/S+R, ββ/αα+ββ), M29/H30, Ts/Ts+Tm, H31 (S/S+R) and aromatic compounds methyl phenanthrene index (MPI) and organic petrographic analysis (vitrinite reflectance) suggest mature stage of oil generation for Chichali Shales and oil samples in the study area with little high thermal maturity in case of oils. Based on source and thermal maturity biomarkers and non-biomarkers parameters, the produced oils have no correlation with the Cretaceous Chichali Formation in the studied Chanda-01 and Chanda-02 wells in Kohat Basin, Pakistan, but it has been suggested that these oils have been generated by the strata containing high terrestrial organic input compare to Chichali Shales.

Keywords: Organic geochemistry, Chichali Shales and crude oils, Kohat Basin, Pakistan

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9882 Evaluation of Nuts as a Source of Selenium in Diet

Authors: Renata Markiewicz-Żukowska, Patryk Nowakowski, Sylwia K. Naliwajko, Jakub M. Bołtryk, Katarzyna Socha, Anna Puścion-Jakubik, Jolanta Soroczyńska, Maria H. Borawska

Abstract:

Selenium (Se) is an essential element for human health. As an integral part of glutathione peroxidase, it has antioxidant, anti-inflammatory and anticancer activities. Unfortunately, Se dietary intake is often insufficient, especially in regions where the soil is low in Se. Therefore, in search for good sources of Se, the content of this element in food products should be monitored. Food product can be considered as a source of Se when its standard portion covers above 15% of recommended daily allowance. In the case of nuts, 42g is recognized as the standard portion. The aim of this study was to determine the Se content in nuts and to answer the question of whether the studied nuts can be considered as a source of Se in the diet. The material for the study consisted of 10 types of nuts (12 samples of each one): almonds, Brazil nuts, cashews, hazelnuts, macadamia nuts, peanuts, pecans, pine nuts, pistachios and walnuts. The nuts were mineralized using microwave technique (Berghof, Germany). The content of Se was determined by atomic absorption spectrometry method with electrothermal atomization in a graphite tube with Zeeman background correction (Hitachi, Japan). The accuracy of the method was verified on certified reference material: Simulated Diet D. The statistical analysis was performed using Statistica v. 13.0 software. Statistical significance was determined at p < 0.05 level. The highest content of Se was found in Brazil nuts (4566.21 ± 3393.9 µg/kg) and the lowest in almonds (36.07 ± 18.8 µg/kg). A standard portion (42g) of almonds, brazil nuts, cashews, hazelnuts, macadamia nuts, peanuts, pecans, pine nuts, pistachios and walnuts covers the recommended daily allowance for Se respectively in: 2, 192, 28, 2, 16, 7, 4, 3, 12, 6%. Brazil nuts, cashews and macadamia nuts can be considered as a good source of Se in diet.

Keywords: atomic absorption spectrometry, diet, nuts, selenium

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9881 The Searching Artificial Intelligence: Neural Evidence on Consumers' Less Aversion to Algorithm-Recommended Search Product

Authors: Zhaohan Xie, Yining Yu, Mingliang Chen

Abstract:

As research has shown a convergent tendency for aversion to AI recommendation, it is imperative to find a way to promote AI usage and better harness the technology. In the context of e-commerce, this study has found evidence that people show less avoidance of algorithms when recommending search products compared to experience products. This is due to people’s different attribution of mind to AI versus humans, as suggested by mind perception theory. While people hold the belief that an algorithm owns sufficient capability to think and calculate, which makes it competent to evaluate search product attributes that can be obtained before actual use, they doubt its capability to sense and feel, which is essential for evaluating experience product attributes that must be assessed after experience in person. The result of the behavioral investigation (Study 1, N=112) validated that consumers show low purchase intention to experience products recommended by AI. Further consumer neuroscience study (Study 2, N=26) using Event-related potential (ERP) showed that consumers have a higher level of cognitive conflict when faced with AI recommended experience product as reflected by larger N2 component, while the effect disappears for search product. This research has implications for the effective employment of AI recommenders, and it extends the literature on e-commerce and marketing communication.

Keywords: algorithm recommendation, consumer behavior, e-commerce, event-related potential, experience product, search product

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9880 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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9879 Domestic Solar Hot Water Systems in Order to Reduce the Electricity Peak Demand in Assalouyeh

Authors: Roya Moradifar, Bijan Honarvar, Masoumeh Zabihi

Abstract:

The personal residential camps of South Pars gas complex are one of the few places where electric energy is used for the bath water heating. The widespread use of these devices is mainly responsible for the high peak of the electricity demand in the residential sector. In an attempt to deal with this issue, to reduce the electricity usage of the hot water, as an option, solar hot water systems have been proposed. However, despite the high incidence of solar radiation on the Assaloyeh about 20 MJ/m²/day, currently, there is no technical assessment quantifying the economic benefits on the region. The present study estimates the economic impacts resulting by the deployment of solar hot water systems in residential camp. Hence, the feasibility study allows assessing the potential of solar water heating as an alternative to reduce the peak on the electricity demand. In order to examine the potential of using solar energy in Bidkhoon residential camp two solar water heater packages as pilots were installed for restaurant and building. Restaurant package was damaged due to maintenance problems, but for the building package, we achieved the result of the solar fraction total 83percent and max energy saving 2895 kWh, the maximum reduction in CO₂ emissions calculated as 1634.5 kg. The results of this study can be used as a support tool to spread the use solar water heaters and create policies for South Pars Gas Complex.

Keywords: electrical energy, hot water, solar, South Pars Gas complex

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9878 Major Depressive Disorder: Diagnosis based on Electroencephalogram Analysis

Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

Abstract:

In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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9877 Efficiency of Membrane Distillation to Produce Fresh Water

Authors: Sabri Mrayed, David Maccioni, Greg Leslie

Abstract:

Seawater desalination has been accepted as one of the most effective solutions to the growing problem of a diminishing clean drinking water supply. Currently, two desalination technologies dominate the market – the thermally driven multi-stage flash distillation (MSF) and the membrane based reverse osmosis (RO). However, in recent years membrane distillation (MD) has emerged as a potential alternative to the established means of desalination. This research project intended to determine the viability of MD as an alternative process to MSF and RO for seawater desalination. Specifically the project involves conducting a thermodynamic analysis of the process based on the second law of thermodynamics to determine the efficiency of the MD. Data was obtained from experiments carried out on a laboratory rig. In order to determine exergy values required for the exergy analysis, two separate models were built in Engineering Equation Solver – the ’Minimum Separation Work Model’ and the ‘Stream Exergy Model’. The efficiency of MD process was found to be 17.3 %, and the energy consumption was determined to be 4.5 kWh to produce one cubic meter of fresh water. The results indicate MD has potential as a technique for seawater desalination compared to RO and MSF. However, it was shown that this was only the case if an alternate energy source such as green or waste energy was available to provide the thermal energy input to the process. If the process was required to power itself, it was shown to be highly inefficient and in no way thermodynamically viable as a commercial desalination process.

Keywords: desalination, exergy, membrane distillation, second law efficiency

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9876 Isolation and Screening of Fungal Strains for β-Galactosidase Production

Authors: Parmjit S. Panesar, Rupinder Kaur, Ram S. Singh

Abstract:

Enzymes are the biocatalysts which catalyze the biochemical processes and thus have a wide variety of applications in the industrial sector. β-Galactosidase (E.C. 3.2.1.23) also known as lactase, is one of the prime enzymes, which has significant potential in the dairy and food processing industries. It has the capability to catalyze both the hydrolytic reaction for the production of lactose hydrolyzed milk and transgalactosylation reaction for the synthesis of prebiotics such as lactulose and galactooligosaccharides. These prebiotics have various nutritional and technological benefits. Although, the enzyme is naturally present in almonds, peaches, apricots and other variety of fruits and animals, the extraction of enzyme from these sources increases the cost of enzyme. Therefore, focus has been shifted towards the production of low cost enzyme from the microorganisms such as bacteria, yeast and fungi. As compared to yeast and bacteria, fungal β-galactosidase is generally preferred as being extracellular and thermostable in nature. Keeping the above in view, the present study was carried out for the isolation of the β-galactosidase producing fungal strain from the food as well as the agricultural wastes. A total of more than 100 fungal cultures were examined for their potential in enzyme production. All the fungal strains were screened using X-gal and IPTG as inducers in the modified Czapek Dox Agar medium. Among the various isolated fungal strains, the strain exhibiting the highest enzyme activity was chosen for further phenotypic and genotypic characterization. The strain was identified as Rhizomucor pusillus on the basis of 5.8s RNA gene sequencing data.

Keywords: beta-galactosidase, enzyme, fungal, isolation

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9875 Investigating the Potential of VR in Language Education: A Study of Cybersickness and Presence Metrics

Authors: Sakib Hasn, Shahid Anwar

Abstract:

This study highlights the vital importance of assessing the Simulator Sickness Questionnaire and presence measures as virtual reality (VR) incorporation into language teaching gains popularity. To address user discomfort, which prevents efficient learning in VR environments, the measurement of SSQ becomes crucial. Additionally, evaluating presence metrics is essential to determine the level of engagement and immersion, both crucial for rich language learning experiences. This paper designs a VR-based Chinese language application and proposes a thorough test technique aimed at systematically analyzing SSQ and presence measures. Subjective tests and data analysis were carried out to highlight the significance of addressing user discomfort in VR language education. The results of this study shed light on the difficulties posed by user discomfort in VR language learning and offer insightful advice on how to improve VR language learning applications. Furthermore, the outcome of the research explores ‘VR-based language education,’ ‘inclusive language learning platforms," and "cross-cultural communication,’ highlighting the potential for VR to facilitate language learning across diverse cultural backgrounds. Overall, the analysis results contribute to the enrichment of language learning experiences in the virtual realm and underscore the need for continued exploration and improvement in this field.

Keywords: virtual reality (VR), language education, simulator sickness questionnaire, presence metrics, VR-based Chinese language education

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9874 The Glycitin and 38 Combination Inhibit the UV-Induced Wrinkle Fomation in Human Primary Fibroblast

Authors: Manh Tin Ho, Phorl Sophors, Ga Young Seo, Young Mee Kim, Youngho Lim, Moonjae Cho

Abstract:

UV radiation in sunlight is one of the most potential factor induced skin ageing and photocarcinogenesis. UV may induce the melanin production and wrinkle formation. Recently, the natural secondary compounds have been reported that had the beneficial protective effects from UV light. In this study, we investigated the effects of two different compounds, glycitin and 38, on human dermal fibroblast. We first only treated the 38 on melanocyte cell to test the proliferation inhibition of 38 on this cell line. Then, we induced the combination of glycitin and 38 on human dermal fibroblast in 48h and investigate the proliferation, collagen production and the metalloproteinase family expression. The 38 alone could inhibit the proliferation of melanocyte which indicated the reduction of melanin production. The combination of glycitin and 38 truly increased the fibroblast proliferation and even they could recover the UV-induced and H2O2-induced damaged fibroblast proliferation. The co-treatment also promoted the collagen IV expression significantly and accelerated the total collagen secretion. In addition, metalloproteinase (MMPs) family such as MMP1, MMP2, MMP7 was down-regulated in transcriptional level. In conclusion, the combination of glycitin and 38 has induced the fibroblast proliferation even when it was damaged by UV exposure and H2O2, whereas augmented collagen production and inhibited the MMPs caused the wrinkle formation and decreased the melanocyte proliferation, suggested an potential UV-protective therapy.

Keywords: UV radiation, wrinkle, ageing, glycitin, dermal fibroblast

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9873 Improvisation of N₂ Foam with Black Rice Husk Ash in Enhanced Oil Recovery

Authors: Ishaq Ahmad, Zhaomin Li, Liu Chengwen, Song yan Li, Wang Lei, Zhoujie Wang, Zheng Lei

Abstract:

Because nanoparticles have the potential to improve foam stability, only a small amount of surfactant or polymer is required to control gas mobility in the reservoir. Numerous researches have revealed that this specific application is in use. The goal is to improve foam formation and foam stability. As a result, the foam stability and foam ability of black rice husk ash were investigated. By injecting N₂ gases into a core flood condition, black rice husk ash was used to produce stable foam. The properties of black rice husk ash were investigated using a variety of characterization techniques. The black rice husk ash was mixed with the best-performing anionic foaming surfactants at various concentrations (ppm). Sodium dodecyl benzene sulphonate was the anionic surfactant used (SDBS). In this article, the N₂ gas- black rice husk ash (BRHA) with high Silica content is shown to be beneficial for foam stability and foam ability. For the test, a 30 cm sand pack was prepared. For the experiment, N₂ gas cylinders and SDBS surfactant liquid cylinders were used. Two N₂ gas experiments were carried out: one without a sand pack and one with a sand pack and oil addition. The black rice husk and SDBS surfactant concentration was 0.5 percent. The high silica content of black rice husk ash has the potential to improve foam stability in sand pack conditions, which is beneficial. On N₂ foam, there is an increase in black rice husk ash particles, which may play an important role in oil recovery.

Keywords: black rice husk ash nanoparticle, surfactant, N₂ foam, sand pack

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9872 Extraction, Recovery and Bioactivities of Chlorogenic Acid from Unripe Green Coffee Cherry Waste of Coffee Processing Industry

Authors: Akkasit Jongjareonrak, Supansa Namchaiya

Abstract:

Unripe green coffee cherry (UGCC) accounting about 5 % of total raw material weight receiving to the coffee bean production process and is, in general, sorting out and dump as waste. The UGCC is known to rich in phenolic compounds such as caffeoylquinic acids, feruloylquinic acids, chlorogenic acid (CGA), etc. CGA is one of the potent bioactive compounds using in the nutraceutical and functional food industry. Therefore, this study aimed at optimization the extraction condition of CGA from UGCC using Accelerated Solvent Extractor (ASE). The ethanol/water mixture at various ethanol concentrations (50, 60 and 70 % (v/v)) was used as an extraction solvent at elevated pressure (10.34 MPa) and temperatures (90, 120 and 150 °C). The recovery yield of UGCC crude extract, total phenolic content, CGA content and some bioactivities of UGCC extract were investigated. Using of ASE at lower temperature with higher ethanol concentration provided higher CGA content in the UGCC crude extract. The maximum CGA content was observed at the ethanol concentration of 70% ethanol and 90 °C. The further purification of UGCC crude extract gave a higher purity of CGA with a purified CGA yield of 4.28 % (w/w, of dried UGCC sample) containing 72.52 % CGA equivalent. The antioxidant activity and antimicrobial activity of purified CGA extract were determined. The purified CGA exhibited the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity at 0.88 mg Trolox equivalent/mg purified CGA sample. The antibacterial activity against Escherichia coli was observed with the minimum inhibitory concentration (MIC) at 3.12 mg/ml and minimum bactericidal concentration (MBC) at 12.5 mg/ml. These results suggested that using of high concentration of ethanol and low temperature under elevated pressure of ASE condition could accelerate the extraction of CGA from UGCC. The purified CGA extract could be a promising alternative source of bioactive compound using for nutraceutical and functional food industry.

Keywords: bioactive, chlorogenic acid, coffee, extraction

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9871 Wastewater Treatment and Bio-Electricity Generation via Microbial Fuel Cell Technology Operating with Starch Proton Exchange Membrane

Authors: Livinus A. Obasi, Augustine N. Ajah

Abstract:

Biotechnology in recent times has tried to develop a mechanism whereby sustainable electricity can be generated by the activity of microorganisms on waste and renewable biomass (often regarded as “negative value”) in a device called microbial fuel cell, MFC. In this paper, we established how the biocatalytic activities of bacteria on organic matter (substrates) produced some electrons with the associated removal of some water pollution parameters; Biochemical oxygen demand (BOD), chemical oxygen demand (COD) to the tune of 77.2% and 88.3% respectively from a petrochemical sanitary wastewater. The electricity generation was possible by conditioning the bacteria to operate anaerobically in one chamber referred to as the anode while the electrons are transferred to the fully aerated counter chamber containing the cathode. Power densities ranging from 12.83 mW/m2 to 966.66 mW/m2 were achieved using a dual-chamber starch membrane MFC experimental set-up. The maximum power density obtained in this research shows an improvement in the use of low cost MFC set up to achieve power production. Also, the level of organic matter removal from the sanitary waste water by the operation of this device clearly demonstrates its potential benefit in achieving an improved benign environment. The beauty of the MFCs is their potential utility in areas lacking electrical infrastructures like in most developing countries.

Keywords: bioelectricity, COD, microbial fuel cell, sanitary wastewater, wheat starch

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9870 Experimental Design for Formulation Optimization of Nanoparticle of Cilnidipine

Authors: Arti Bagada, Kantilal Vadalia, Mihir Raval

Abstract:

Cilnidipine is practically insoluble in water which results in its insufficient oral bioavailability. The purpose of the present investigation was to formulate cilnidipine nanoparticles by nanoprecipitation method to increase the aqueous solubility and dissolution rate and hence bioavailability by utilizing various experimental statistical design modules. Experimental design were used to investigate specific effects of independent variables during preparation cilnidipine nanoparticles and corresponding responses in optimizing the formulation. Plackett Burman design for independent variables was successfully employed for optimization of nanoparticles of cilnidipine. The influence of independent variables studied were drug concentration, solvent to antisolvent ratio, polymer concentration, stabilizer concentration and stirring speed. The dependent variables namely average particle size, polydispersity index, zeta potential value and saturation solubility of the formulated nanoparticles of cilnidipine. The experiments were carried out according to 13 runs involving 5 independent variables (higher and lower levels) employing Plackett-Burman design. The cilnidipine nanoparticles were characterized by average particle size, polydispersity index value, zeta potential value and saturation solubility and it results were 149 nm, 0.314, 43.24 and 0.0379 mg/ml, respectively. The experimental results were good correlated with predicted data analysed by Plackett-Burman statistical method.

Keywords: dissolution enhancement, nanoparticles, Plackett-Burman design, nanoprecipitation

Procedia PDF Downloads 158
9869 D3Advert: Data-Driven Decision Making for Ad Personalization through Personality Analysis Using BiLSTM Network

Authors: Sandesh Achar

Abstract:

Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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9868 Relationship of Oxidative Stress to Elevated Homocysteine and DNA Damage in Coronary Artery Disease Patients

Authors: Shazia Anwer Bukhari, Madiha Javeed Ghani, Muhammad Ibrahim Rajoka

Abstract:

Objective: Biochemical, environmental, physical and genetic factors have a strong effect on the development of coronary disease (CAD). Plasma homocysteine (Hcy) level and DNA damage play a pivotal role in its development and progression. The aim of this study was to investigate the predictive strength of an oxidative stress, clinical biomarkers and total antioxidant status (TAS) in CAD patients to find the correlation of homocysteine, TOS and oxidative DNA damage with other clinical parameters. Methods: Sixty confirmed patients with CAD and 60 healthy individuals as control were included in this study. Different clinical and laboratory parameters were studied in blood samples obtained from patients and control subjects using commercially available biochemical kits and statistical software Results: As compared to healthy individuals, CAD patients had significantly higher concentrations of indices of oxidative stress: homocysteine (P=0.0001), total oxidative stress (TOS) (P=0.0001), serum cholesterol (P=0.04), low density lipoprotein cholesterol (LDL) (P=0.01), high density lipoprotein-cholesterol (HDL) (P=0.0001), and malondialdehyde (MDA) (P=0.001) than those of healthy individuals. Plasma homocysteine level and oxidative DNA damage were positively correlated with cholesterol, triglycerides, systolic blood pressure, urea, total protein and albumin (P values= 0.05). Both Hcy and oxidative DNA damage were negatively correlated with TAS and proteins. Conclusion: Coronary artery disease patients had a significant increase in homocysteine level and DNA damage due to increased oxidative stress. In conclusion, our study shows a significantly increase in lipid peroxidation, TOS, homocysteine and DNA damage in the erythrocytes of patients with CAD. A significant decrease level of HDL-C and TAS was observed only in CAD patients. Therefore these biomarkers may be useful diagnosis of patients with CAD and play an important role in the pathogenesis of CAD.

Keywords: antioxidants, coronary artery disease, DNA damage, homocysteine, oxidative stress, malondialdehyde, 8-Hydroxy-2’deoxyguanosine

Procedia PDF Downloads 484
9867 Harnessing Artificial Intelligence for Early Detection and Management of Infectious Disease Outbreaks

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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9866 ORR Electrocatalyst for Batteries and Fuel Cells Development with SIO₂/Carbon Black Based Composite Nanomaterials

Authors: Maryam Kiani

Abstract:

This study focuses on the development of composite nanomaterials based on SiO₂ and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO₂/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO₂ into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO₂ facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO₂/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: ORR, fuel cells, batteries, electrocatalyst

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9865 A Viable Approach for Biological Detoxification of Non Edible Oil Seed Cakes and Their Utilization in Food Production Using Aspergillus Niger

Authors: Kshitij Bhardwaj, R.K. Trivedi, Shipra Dixit

Abstract:

We used biological detoxification method that converts toxic residue waste of Jatropha curcas oil seeds (non edible oil seed) into industrial bio-products and animal feed material. Present study describes the complete degradation of phorbol esters by Aspergillus Niger strain during solid state fermentation (SSF) of deoiled Jatropha curcas seed cake. Phorbol esters were completely degraded in 15 days under the optimized SSF conditions viz deoiled cake 5.0 gm moistened with 5.0 ml distilled water; inoculum 2 ml of overnight grown Aspergillus niger; incubated at 30◦ C, pH 7.0. This method simultaneously induces the production of Protease enzyme by Aspergillus Niger which has high potential to be used in feedstuffs .The maximum Protease activities obtained were 709.16 mg/ml in Jatropha curcas oil seed cake. The protein isolate had small amounts of phorbol esters, phytic acid, and saponin without any lectin. Its minimum and maximum solubility were at pH 4.0&12.0. Water and oil binding capacities were 3.22 g water/g protein and 1.86 ml oil/g protein respectively.Emulsion activity showed high values in a range of basic pH. We concluded that Jatropha Curcas seed cake has a potential to be used as a novel source of functional protein for food or feed applications.

Keywords: solid state fermentation, Jatropha curcas, oil seed cake, phorbol ester

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9864 Exploitation of Endophytes for the Management of Plant Pathogens

Authors: N. P. Eswara Reddy, S. Thahir Basha

Abstract:

Here, we report the success stories of potential leaf, seed and root endophytes against soil borne as well as foliar plant pathogens which are nutritionally adequate and safe for consumption. Endophytes are the microorganisms that reside asymptomatically in the tissues of higher plants are a robust source of potential biocontrol agents and it is presumed that the survival ability of endophytes may be better when compared to phylloplane microflora. Of all the 68 putative leaf endophytes, the endophytes viz., EB9 (100%), and EB35 (100%) which were superior in controlling Colletotrichum gloeosporioides causing mango anthracnose were identified as Brevundimonas bullata (EB09) and Bacillus thuringiensis (EB35) and further delayed in ripening of mango fruits up to 21 days. As a part, the seed endophyte GSE-4 was identified as Archoromobacter spp. against Sclerotium rolfsii causing stem rot of groundnut and the root endophyte REB-8 against Rhizoctonia bataticola causing dry root rot of chickpea was identified as Bacillus subtilis. Both recorded least percent disease incidence (PDI) and increased plant growth promotion, respectively. Further, the novel Bacillus subtilis (SEB-2) against Macrophomina pahseolina causing charcoal rot of sunflower provides an ample scope for exploring the endophytes at large scale. The talc-based formulations of these endophytes developed can be commercialized after toxicological studies. At the bottom line these unexplored endophytes are the need of the hour against aggressive plant pathogens and to maintain the quality and abundance of food and feed and also to fetch marginal economy to the farmers will be discussed.

Keywords: endophytes, plant pathogens, commercialization, abundance of food

Procedia PDF Downloads 416
9863 Integrating Natural Language Processing (NLP) and Machine Learning in Lung Cancer Diagnosis

Authors: Mehrnaz Mostafavi

Abstract:

The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

Procedia PDF Downloads 98
9862 Reviving Arid Lands: The Transformative Potential of Biochar in Arab Countries' Agriculture

Authors: Ahmed Azizeldein Abubaker Abdelhafez

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This review explores the application of biochar as a strategy for enhancing soil fertility in arid regions, with a focus on Arab countries. Biochar, derived from the carbonization of biomass under low-oxygen conditions, has shown promise in improving the physical and chemical properties of soil, such as increasing water retention and nutrient availability. Despite the challenging conditions of arid and semi-arid regions, characterized by poor soil fertility and severe land degradation, biochar application has emerged as a viable method to enhance agricultural productivity and mitigate environmental issues. This paper examines various aspects of biochar, including production methods, such as pyrolysis and gasification, and the effects of biochar on soil fertility. It discusses different application techniques and presents case studies from Arab countries like Egypt, the United Arab Emirates, Saudi Arabia, Qatar, Oman, and Kuwait, highlighting the successes and challenges faced in implementing biochar technology. The review also addresses the limitations of biochar use in arid regions and suggests future research directions to optimize its effectiveness. Overall, this study underscores the potential of biochar to contribute significantly to sustainable agriculture and ecological restoration in arid environments, advocating for integrated strategies that combine biochar application with other innovative agricultural practices.

Keywords: biochar, soil fertility, arid region, Arab countries, challenges and limitations

Procedia PDF Downloads 41
9861 Finding a Redefinition of the Relationship between Rural and Urban Knowledge

Authors: Bianca Maria Rulli, Lenny Valentino Schiaretti

Abstract:

The considerable recent urbanization has increasingly sharpened environmental and social problems all over the world. During the recent years, many answers to the alarming attitudes in modern cities have emerged: a drastic reduction in the rate of growth is becoming essential for future generations and small scale economies are considered more adaptive and sustainable. According to the concept of degrowth, cities should consider surpassing the centralization of urban living by redefining the relationship between rural and urban knowledge; growing food in cities fundamentally contributes to the increase of social and ecological resilience. Through an innovative approach, this research combines the benefits of urban agriculture (increase of biological diversity, shorter and thus more efficient supply chains, food security) and temporary land use. They stimulate collaborative practices to satisfy the changing needs of communities and stakeholders. The concept proposes a coherent strategy to create a sustainable development of urban spaces, introducing a productive green-network to link specific areas in the city. By shifting the current relationship between architecture and landscape, the former process of ground consumption is deeply revised. Temporary modules can be used as concrete tools to create temporal areas of innovation, transforming vacant or marginal spaces into potential laboratories for the development of the city. The only permanent ground traces, such as foundations, are minimized in order to allow future land re-use. The aim is to describe a new mindset regarding the quality of space in the metropolis which allows, in a completely flexible way, to bring back the green and the urban farming into the cities. The wide possibilities of the research are analyzed in two different case-studies. The first is a regeneration/connection project designated for social housing, the second concerns the use of temporary modules to answer to the potential needs of social structures. The intention of the productive green-network is to link the different vacant spaces to each other as well as to the entire urban fabric. This also generates a potential improvement of the current situation of underprivileged and disadvantaged persons.

Keywords: degrowth, green network, land use, temporary building, urban farming

Procedia PDF Downloads 502
9860 Investigation of Night Cooling Event, Experimental Radiator

Authors: Fatemeh Karampour

Abstract:

In the hot climate countries, especially those countries with great desert area, such as Iran, a considerable part of the energy is consumed due to cooling and air conditioning system in a hot season. So it is important to find a renewable energy supply for cooling systems. Although, there are few consistent researches in this field of renewable energy in compare with other fields. This research is presenting a study on performance of a night cooling radiator and working fluid storage for night time operation and day time resting periods. In these experiments, we didn’t expose any heating load but focused only on the possibility of system combination and its potential cooling effect. A very simple radiator has been designed in south of Iran, Shiraz, in order to perform this study. The radiator has been insulated with polystyrene foam and bubbled plastic sheets have been used as top cover. Using a single bubbled plastic sheet, the radiator temperature reached 0°C which is 20°C lower than minimum ambient temperature. Putting a small storage tank in the line increased the radiator’s minimum temperature at night; however, provided some cool fluid source for hot days of Shiraz that easily reaches 40°C. The results have shown very good cooling potential without heating load and acceptable temperature increasing during hot day with a small, short term storage tank. Future studies can make the system more effective and applicable.

Keywords: night cooling, experimental set up, cooling radiator, chill storage

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9859 The Potential of Tempo-Oxidized Cellulose Nanofibers to Replace EthylenE-propylene-Diene Monomer Rubber

Authors: Sibel Dikmen Kucuk, Yusuf Guner

Abstract:

In recent years, petroleum-based polymers began to be limited due to the effects on the human and environmental point of view in many countries. Thus, organic-based biodegradable materials have attracted much interest in the composite industry because of environmental concerns. As a result of this, it has been asked that inorganic and petroleum-based materials should be reduced and altered with biodegradable materials. In this point, in this study, it is aimed to investigate the potential of the use of TEMPO (2,2,6,6- tetramethylpiperidine 1-oxyl)-mediated oxidation nano-fibrillated cellulose instead of EPDM (ethylene-propylene-diene monomer) rubber, which is a petroleum-based material. Thus, the exchange of petroleum-based EPDM rubber with organic-based cellulose nanofibers, which are environmentally friendly (green) and biodegradable, will be realized. The effect of tempo-oxidized cellulose nanofibers (TCNF) instead of EPDM rubber was analyzed by rheological, mechanical, chemical, thermal, and aging analyses. The aged surfaces were visually scrutinized, and surface morphological changes were examined via scanning electron microscopy (SEM). The results obtained showed that TEMPO oxidation nano-fibrillated cellulose could be used at an amount of 1.0 and 2.2 phr resulting the values stay within tolerance according to customer standard and without any chemical degradation, crack, color change or staining.

Keywords: EPDM, lignin, green materials, biodegradable fillers

Procedia PDF Downloads 123