Search results for: green extraction

Authors: Ghazi Faisal Najmuldeen, Noridah Abdullah, Mimi Sakinah

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Bioethanol is an alcohol made by fermentation, mostly from carbohydrates, Cellulosic biomass, derived from non-food sources, such as castor shell waste, is also being developed as a feedstock for ethanol production Cellulose extracted from biomass sources is considered the future feedstock for many products due to the availability and eco-friendly nature of cellulose. In this study, castor shell (CS) biowaste resulted from the extraction of Castor oil from castor seeds was evaluated as a potential source of cellulose. The cellulose was extracted after pretreatment process was done on the CS. The pretreatment process began with the removal of other extractives from CS, then an alkaline treatment, bleaching process with hydrogen peroxide, and followed by a mixture of acetic and nitric acids. CS cellulose was analysed by infrared absorption spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). The result showed that the overall process was adequate to produce cellulose with high purity and crystallinity from CS waste. The cellulose was then hydrolyzed to produce glucose and then fermented to bioethanol.

Keywords: bioethanol, castor shell, cellulose, biowaste

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Authors: Sara Heidari, Jafar Mohammadzadeh Milani, Elmira Pouladi Borj

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In this research, stability of Ochratoxin A (OTA) during bread making process including fermentation with yeasts (Saccharomyces cerevisiae) and Sourdough (Lactobacillus casei, Lactobacillus rhamnosus, Lactobacillus acidophilus and Lactobacillus fermentum) and baking at 200°C were examined. Bread was prepared on a pilot-plant scale by using wheat flour spiked with standard solution of OTA. During this process, mycotoxin levels were determined after fermentation of the dough with sourdough and three types of yeast including active dry yeast, instant dry yeast and compressed yeast after further baking 200°C by high performance liquid chromatography (HPLC) with fluorescence detector after extraction and clean-up on an immunoaffinity column. According to the results, the highest stability of was observed in the first fermentation (first proof), while the lowest stability was observed in the baking stage in comparison to contaminated flour. In addition, compressed yeast showed the maximum impact on stability of OTA during bread making process.

Keywords: Ochratoxin A, bread, dough, yeast, sourdough

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Authors: Analise Borg, Paul Micallef

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Over the past few years, the online multimedia collection has grown at a fast pace. Several companies showed interest to study the different ways to organize the amount of audio information without the need of human intervention to generate metadata. In the past few years, many applications have emerged on the market which are capable of identifying a piece of music in a short time. Different audio effects and degradation make it much harder to identify the unknown piece. In this paper, an audio fingerprinting system which makes use of a non-parametric based algorithm is presented. Parametric analysis is also performed using Gaussian Mixture Models (GMMs). The feature extraction methods employed are the Mel Spectrum Coefficients and the MPEG-7 basic descriptors. Bin numbers replaced the extracted feature coefficients during the non-parametric modelling. The results show that non-parametric analysis offer potential results as the ones mentioned in the literature.

Keywords: audio fingerprinting, mapping algorithm, Gaussian Mixture Models, MFCC, MPEG-7

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Authors: Tianyu Wang, Nikita Karandikar

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The uncertainty around cost, safety, and feasibility of the decarbonized shipping fuels has made it increasingly complex for the shipping companies to set pricing strategies and forecast their freight revenues going forward. The increase in the green fuel surcharges will ultimately influence the automobile’s consumer prices. The auto shipping demand (ton-miles) has been gradually shifting from long-haul to short-sea trade over the past years following the relocation of the original equipment manufacturer (OEM) manufacturing to regions such as South America and Southeast Asia. The objective of this paper is twofold: 1) to investigate the car-carriers freight revenue development over the years when the trade pattern is gradually shifting towards short-sea exports 2) to empirically identify the quantitative impact of such trade pattern shifting to mainly freight rate, but also vessel size, fleet size as well as Green House Gas (GHG) emission in Roll on-Roll Off (Ro-Ro) shipping. In this paper, a model of analyzing and forecasting ton-miles and freight revenues for the trade routes of AS-NA (Asia to North America), EU-NA (Europe to North America), and SA-NA (South America to North America) is established by deploying Automatic Identification System (AIS) data and the financial results of a selected car carrier company. More specifically, Wallenius Wilhelmsen Logistics (WALWIL), the Norwegian Ro-Ro carrier listed on Oslo Stock Exchange, is selected as the case study company in this paper. AIS-based ton-mile datasets of WALWIL vessels that are sailing into North America region from three different origins (Asia, Europe, and South America), together with WALWIL’s quarterly freight revenues as reported in trade segments, will be investigated and compared for the past five years (2018-2022). Furthermore, ordinary‐least‐square (OLS) regression is utilized to construct the ton-mile demand and freight revenue forecasting. The determinants of trade pattern shifting, such as import tariffs following the China-US trade war and fuel prices following the 0.1% Emission Control Areas (ECA) zone requirement after IMO2020 will be set as key variable inputs to the machine learning model. The model will be tested on another newly listed Norwegian Car Carrier, Hoegh Autoliner, to forecast its 2022 financial results and to validate the accuracy based on its actual results. GHG emissions on the three routes will be compared and discussed based on a constant emission per mile assumption and voyage distances. Our findings will provide important insights about 1) the trade-off evaluation between revenue reduction and energy saving with the new ton-mile pattern and 2) how the trade flow shifting would influence the future need for the vessel and fleet size.

Keywords: AIS, automobile exports, maritime big data, trade flows

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Authors: Selvam Noyel Victoria, Kavita Yadav, Manivannan Ramachandran

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The extract of Tagetes erecta (marigold flower) was used as a green corrosion inhibitor for mild steel (MS) in nitric acid medium. The weight loss measurements were performed to understand the inhibition mechanism. The effect of temperature on the behaviour of mild steel corrosion without and with inhibitor was studied. The temperature studies revealed that the activation energy increased from 12 kJ/mol to 28.8 kJ/mol with the addition of 500 ppm inhibitor concentration. The thermodynamic analysis and the adsorption isotherm studies revealed that the molecules of inhibitor show physical adsorption on the surface of mild steel. Based on weight loss measurements, adsorption of the inhibitor on the surface of mild steel follows Langmuir isotherm.

Keywords: Tagetes erecta, corrosion, adsorption, inhibitor

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Andrés Quiroz, Emilio Hormazabal, Ana Mutis, Fernando Ortega, Manuel Chacón-Fuentes, Leonardo Parra

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Red clover (Trifolium pratense L.) is an important forage species in temperate regions of the world. The main limitation of this species worldwide is a lack of persistence related to the high mortality of plants due to a complex of biotic and abiotic factors, determining a life span of two or three seasons. Because of the importance of red clover in Chile, a red clover breeding program was started at INIA Carillanca Research Center in 1989, with the main objective of improving the survival of plants, forage yield, and persistence. The main selection criteria for selecting new varieties have been based on agronomical parameters and biotic factors. The main biotic factor associated with red clover mortality in Chile is Hylastinus obscurus (Coleoptera: Curculionidae). Both larval and adults feed on the roots, causing weakening and subsequent death of clover plants. Pesticides have not been successful for controlling infestations of this root borer. Therefore, alternative strategies for controlling this pest are a high priority for red clover producers. Currently, the role of semiochemical in the interaction between H. obscurus and red clover plants has been widely studied for our group. Specifically, from the red clover foliage has been identified limonene is eliciting repellency from the root borer. Limonene is generated in the plant from two independent biosynthetic pathways, the mevalonic acid, and deoxyxylulose pathway. Mevalonate pathway enzymes are localized in the cytosol, whereas the deoxyxylulose phosphate pathway enzymes are found in plastids. In summary, limonene can be determinated by enzymatic bioassay using GPP as substrate and by limonene synthase expression. Therefore, the main objective of this work was to study genetic variation of limonene in material provided by INIA´s Red Clover breeding program. Protein extraction was carried out homogenizing 250 mg of leave tissue and suspended in 6 mL of extraction buffer (PEG 1500, PVP-30, 20 mM MgCl2 and antioxidants) and stirred on ice for 20 min. After centrifugation, aliquots of 2.5 mL were desalted on PD-10 columns, resulting in a final volume of 3.5 mL. Protein determination was performed according to Bradford with BSA as a standard. Monoterpene synthase assays were performed with 50 µL of protein extracts transferred into gas-tight 2 mL crimp seal vials after addition of 4 µL MgCl₂ and 41 µL assay buffer. The assay was started by adding 5 µL of a GPP solution. The mixture was incubated for 30 min at 40 °C. Biosynthesized limonene was quantified in a GC equipped with a chiral column and using synthetic R and S-limonene standards. The enzymatic the production of R and S-limonene from different Superqueli-Carillanca genotypes is shown in this work. Preliminary results showed significant differences in limonene content among the genotypes analyzed. These results constitute an important base for selecting genotypes with a high content of this repellent monoterpene towards H. obscurus.

Keywords: head space, limonene enzymatic determination, red clover, Hylastinus obscurus

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Authors: Wei-Bo Hua, Zhuo Zheng, Xiao-Dong Guo, Ben-He Zhong

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The layered structure LiNi1/3Co1/3Mn1/3-xAlxO2 (x = 0 ~ 0.04) series cathode materials were synthesized by a carbonate co-precipitation method, followed by a high temperature calcination process. The influence of Al substitution on the microstructure and electrochemical performances of the prepared materials was investigated by X-Ray diffraction (XRD), scanning electron microscopy (SEM), and galvanostatic charge/discharge test. The results show that the LiNi1/3Co1/3Mn1/3-xAlxO2 has a well-ordered hexagonal "α" -NaFeO2 structure. Although the discharge capacity of Al-doped samples decreases as x increases, LiNi1/3Co1/3Mn1/3-0.02Al0.02O2 exhibits superior capacity retention at high voltage (4.6 V). Therefore, LiNi1/3Co1/3Mn1/3-0.02Al0.02O2 is a promising material for “green” vehicles.

Keywords: lithium ion battery, carbonate co-precipitation, doping, microstructure, electrochemical properties

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Authors: Reza Dehghani Bidgoli

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Although Artemisia species are one of the most important medicinal plants, there are a few reports on chemistry or activity of their essential oils because of low amounts of the oils in this genus. In this study, chemical composition of essential oils leaves and stems of Artemisia sieberi and Artemisia aucheri growing wild in Kashan rangelands, central Iran, have been analyzed using GC–MS technique. Analysis revealed 50 identified compounds, representing 96.55% of the oil and 23 identified compounds representing 97.83% of the oil on Artemisia sieberi and Artemisia aucheri respectively. The yield of essential oil extraction is very higher than those of previous reports. In both plants α-thujene is the main component in both of them, with an extra value, 74.42%, in aucheri species. Several compounds (some with significant compositions), were found in these varieties of Artemisia which are not recorded in previous literature. Antioxidant activities of the essential oils were evaluated for the first time in this research work using β-carotene/linoleic acid assay and found to be surprisingly attributed directly to α-pinene contents in them.

Keywords: essential oil, artemisia aucheri, artemisia sieberi, α-thujene, antioxidant activity

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Authors: Yuchen Niu, Liang Zhao, Fangfang Xie, Weiyu Liu

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In the past decades, rapid urbanization in China has significantly promoted economic growth and caused a large number of environmental problems. In consideration of land resources shortage, high-density cities will become a common phenomenon in the future. How to improve the living environment under high density is a new challenge. Shenzhen is a typical high-density city, but also the forefront of China's development and reform area. This study selects 9 urban parks with different natural attributes in Shenzhen and explores the relationship of natural, economic, and social conditions within the service scope. Based on correlation analysis and system analysis, the results indicate that improvement of park design and management methods contribute to obtaining higher ecological value and promote economic and social development.

Keywords: correlation analysis, high-density city, park improvement, urban green spaces

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Authors: Harpreet Singh

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Finding relevant information on the World Wide Web is becoming highly challenging day by day. Web usage mining is used for the extraction of relevant and useful knowledge, such as user behaviour patterns, from web access log records. Web access log records all the requests for individual files that the users have requested from the website. Web usage mining is important for Customer Relationship Management (CRM), as it can ensure customer satisfaction as far as the interaction between the customer and the organization is concerned. Web usage mining is helpful in improving website structure or design as per the user’s requirement by analyzing the access log file of a website through a log analyzer tool. The focus of this paper is to enhance the accessibility and usability of a guitar selling web site by analyzing their access log through Deep Log Analyzer tool. The results show that the maximum number of users is from the United States and that they use Opera 9.8 web browser and the Windows XP operating system.

Keywords: web usage mining, web mining, log file, data mining, deep log analyzer

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Authors: Ting-Ying Su, Meng-Shiou Lee, Shyang-Chwen Sheu

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Garlic is used commonly as a seasoning around the world. But some people suffer from allergy to garlic. Garlic may also cause burning of mouth, stomach, and throat. In some Buddhist traditions, consuming garlic is not allowed. The objective of this study is to develop a LAMP based method for detection of garlic in food. We designed specific primers targeted on ITS1-5.8S rRNA-ITS2 sequence of garlic DNA. The LAMP assay was performed using a set of four different primers F3, B3, FIP and BIP at 60˚C in less than 60 mins. Results showed that the primer was not cross-reactive to other commonly used spice including Chinese leek, Chinese onion, green onion, onion, pepper, basil, parsley, pepper and ginger. As low as 2% of garlic DNA could be detected. Garlic still could be detected by developed LAMP after boiled at 100˚C for 80 minutes and autoclaved at 121˚C for 60 minutes. Commercial products labeled with garlic ingredient could be identified by the developed method.

Keywords: garlic, loop-mediated isothermal amplification, processing, DNA

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Authors: Francesca Scalisi, Cesare Sposito

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The building construction industry consumes a large amount of resources and energy, both during construction (embodied energy) and during the operational phase (operating energy). This paper presents a review of the literature on low carbon and low embodied energy materials in buildings. The embodied energy comprises the energy consumed during the extraction, processing, transportation, construction, and demolition of building materials. While designing a nearly zero energy building, it is necessary to choose and use materials, components, and technologies that allow to reduce the consumption of energy and also to reduce the emissions in the atmosphere during all the Life Cycle Assessment phases. The appropriate choice of building materials can contribute decisively to reduce the energy consumption of the building sector. The increasing worries for the environmental impact of construction materials are witnessed by a lot of studies. The mentioned worries have brought again the attention towards natural materials. The use of more sustainable construction materials and construction techniques represent a major contribution to the eco-efficiency of the construction industry and thus to a more sustainable development.

Keywords: embodied energy, embodied carbon, life cycle assessment, architecture, sustainability, material construction

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Authors: Ariangelo Hauer Dias Filho, Gustavo Antoniácomi de Carvalho, Benjamim de Melo Carvalho

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The work´s purpose was to evaluate the possibility of manufacturing casting tools utilizing Fused Filament Fabrication, a 3D printing technique, without any post-processing on the printed part. Taguchi Orthogonal array was used to evaluate the influence of extrusion temperature, bed temperature, layer height, and infill on the dimensional accuracy of a 3D-Printed Polymer Model. A Zeiss T-SCAN CS 3D Scanner was used for dimensional evaluation of the printed parts within the limit of ±0,2 mm. The mold capabilities were tested with the printed model to check how it would interact with the green sand. With little adjustments in the 3D model, it was possible to produce rapid tools without the need for post-processing for iron casting. The results are important for reducing time and cost in the development of such tools.

Keywords: additive manufacturing, Taguchi method, rapid tooling, fused filament fabrication, casting mold

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Authors: Randa Boukhris, Alima Damak, Dorra Sellami

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Fingervein biometric authentication is one of the most popular and accurate technologies. However, low cost embedded solution is still an open problem. In this paper, a real-time implementation of fingervein recognition process embedded in Raspberry-Pi has been proposed. The use of Raspberry-Pi reduces overall system cost and size while allowing an easy user interface. Implementation of a target technology has guided to opt some specific parallel and simple processing algorithms. In the proposed system, we use four structural directional kernel elements for filtering finger vein images. Then, a Top-Hat and Bottom-Hat kernel filters are used to enhance the visibility and the appearance of venous images. For feature extraction step, a simple Local Directional Code (LDC) descriptor is applied. The proposed system presents an Error Equal Rate (EER) and Identification Rate (IR), respectively, equal to 0.02 and 98%. Furthermore, experimental results show that real-time operations have good performance.

Keywords: biometric, Bottom-Hat, Fingervein, LDC, Rasberry-Pi, ROI, Top-Hat

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Authors: Naima Umar

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Mid-1960’s has been landmark in the history of Indian agriculture. It was in 1966-67 when a New Agricultural Strategy was put into practice to tide over chronic shortages of food grains in the country. This strategy adopted was the use High-Yielding Varieties (HYV) of seeds (wheat and rice), which was popularly known as the Green Revolution. This phase of agricultural development has saved us from hunger and starvation and made the peasants more confident than ever before, but it has also created a number of socio-economic and environmental implications such as the reduction in area under forest, salinization, waterlogging, soil erosion, lowering of underground water table, soil, water and air pollution, decline in soil fertility, silting of rivers and emergence of several diseases and health hazards. The state of Uttar Pradesh in the north is bounded by the country of Nepal, the states of Uttrakhand on the northwest, Haryana on the west, Rajasthan on the southwest, Madhya Pradesh on the south and southwest, and Bihar on the east. It is situated between 23052´N and 31028´N latitudes and 7703´ and 84039´E longitudes. It is the fifth largest state of the country in terms of area, and first in terms of population. Forming the part of Ganga plain the state is crossed by a number of rivers which originate from the snowy peaks of Himalayas. The fertile plain of the Ganga has led to a high concentration of population with high density and the dominance of agriculture as an economic activity. Present paper highlights the negative impact of new agricultural technology on health of the people and environment and will attempt to find out factors which are responsible for these implications. Karl Pearson’s Correlation coefficient technique has been applied by selecting 1 dependent variable (i.e. Productivity Index) and some independent variables which may impact crop productivity in the districts of the state. These variables have categorized as: X1 (Cropping Intensity), X2 (Net irrigated area), X3 (Canal Irrigated area), X4 (Tube-well Irrigated area), X5 (Irrigated area by other sources), X6 (Consumption of chemical fertilizers (NPK) Kg. /ha.), X7 (Number of wooden plough), X8 (Number of iron plough), X9 (Number of harrows and cultivators), X10 (Number of thresher machines), X11(Number of sprayers), X12 (Number of sowing instruments), X13 (Number of tractors) and X14 (Consumption of insecticides and pesticides (in Kg. /000 ha.). The entire data during 2001-2005 and 2006- 2010 have been taken and 5 years average value is taken into consideration, based on secondary sources obtained from various government, organizations, master plan report, economic abstracts, district census handbooks and village and town directories etc,. put on a standard computer programmed SPSS and the results obtained have been properly tabulated.

Keywords: agricultural technology, environmental implications, health hazards, socio-economic problems

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Authors: Massra M. Sabeima, Myriam lamolle, Mohamedade Farouk Nanne

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Adapting the learning resources of an e-learning system to the characteristics of the learners is an important aspect to consider when designing an adaptive e-learning system. However, this adaptation is not a simple process; it requires the extraction, analysis, and modeling of user information. This implies a good representation of the user's profile, which is the backbone of the adaptation process. Moreover, during the e-learning process, collaboration with similar users (same geographic province or knowledge context) is important. Productive collaboration motivates users to continue or not abandon the course and increases the assimilation of learning objects. The contribution of this work is the following: we propose an adaptive e-learning semantic platform to recommend learning resources to learners, using ontology to model the user profile and the course content, furthermore an implementation of a multi-agent system able to progressively generate the learning graph (taking into account the user's progress, and the changes that occur) for each user during the learning process, and to synchronize the users who collaborate on a learning object.

Keywords: adaptative learning, collaboration, multi-agent, ontology

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Authors: Brandtner-Hafner Martin

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Biocomposites have established themselves as a sustainable material class in the industry. Their advantages include lower density, lower price, and easier recycling compared to conventional materials. Now there are a variety of ways to measure their technical performance. One possibility is mechanical tests, which are widely used and standardized. However, these provide only very limited insights into damage capacity, which is particularly problematic under cracking conditions. To overcome such shortcomings, experimental tests were performed applying the fracture energetically GF-concept to study the structural safety of the interface under crack opening (mode-I loading). Two different types of biocomposites based on extruded henequen-fibers (NFRP) and wood-particles (WPC) in an HDPE matrix were evaluated. The results show that the fracture energy values obtained are higher than those given in the literature. This suggests that alternatives to previous linear elastic testing methods are needed to perform authentic safety evaluations of green plastics.

Keywords: biocomposites, structural safety, Gғ-concept, fracture analysis

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Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

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Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover, this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

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Authors: Rungnapa Chantra

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As health care rapidly changes, the nursing profession is also evolving to improve quality of care while maintaining competency in their practice. The purpose of this study was to investigate the factors of disaster nurse competencies and investigate the predictable variables in disaster nurse competencies in Suratthani Province, Thailand. The sample consisted of 305 nurses who were recruited by simple random sampling. The development questionnaires from ICN Framework and research contains Pre/Mitigation, Preparedness, Response and Recovery/Rehabilitation Competencies (α=0.87). The data were analyzed using Principle Components Extraction and Orthogonal Rotation with Varimax Method. The findings were as follows; four significant factors of disaster nurse competencies in Suratthani Province, Thailand were identified. These factors were described by 62 variables that accounted for 50.01% of the total variance. The results of this study could be for agencies that are responsible for the development of nursing competencies and should be aware of the development of knowledge and skills in disaster management.

Keywords: disaster nursing competency of nurses, nursing informatics, health science, medical

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Authors: Yang Chen

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The property-led regeneration has played an important role in the process of rapid urbanization during the past twenty years in China, but it is also been criticized unsustainable as it always focuses on the economic aspect and overlooks the social issues, especially it has exacerbated the residential segregation in the inner city. Based on author’s studying the area around Nanjing railway station, this paper demonstrates that residential segregation indeed exists in the inner city through synthetic analysis on patterns of residents’ living, consumption and welfare, and to some extent, the segregation distribution characteristics represent in a concentric ring model. According to author’s further investigation on the property right and age of the dwelling buildings, the housing-commercialization-led regeneration is defined as the mainspring of the segregation. To solve these problems, the system of sustainable community should be established in both policy and practice, above all, well-designed public facilities including green infrastructure will be appropriate to promote the residential integration and sustainable development in contemporary China.

Keywords: China, dynamic mechanism, residential segregation, sustainable regeneration

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Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Rashika Sharma

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The campuses at tertiary institutes can act as a social environment for peer to peer connections. However, socialization is not the only aspect that campuses provide. The campus can act as a learning environment that has often been termed as the campus curriculum. Many tertiary institutes have taken steps to make their campus a ‘green campus’ whereby initiatives have been taken to reduce their impact on the environment. However, as visible as these initiatives are, it is debatable whether these have any effect on students’ and their understanding of sustainable campus operations. Therefore, research was conducted to evaluate the effectiveness of sustainable campus operations in raising students’ awareness of sustainability. Students at two vocational institutes participated in this interpretive research with data collected through surveys and focus groups. The findings indicated that majority of vocational education students remained oblivious of sustainability initiatives on campuses.

Keywords: campus learning, education for sustainability, social learning, vocational education

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Authors: Imad H. Hameed, Mohammad A. Jebor, Ammera J. Omer

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The aim of this research is to study the mitochonderial coding region by using the Sanger sequencing technique and establish the degree of variation characteristic of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. Portion of coding region encompassing positions 11719 –12384 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and Detected by using the ABI 3730xL DNA Analyzer. Five new polymorphic positions 11741, 11756, 11878, 11887 and 12133 are described may be suitable sources for identification purpose in future. The calculated value D= 0.95 and RMP=0.048 of the genetic diversity should be understood as high in the context of coding function of the analysed DNA fragment. The relatively high gene diversity and a relatively low random match probability were observed in Iraq population. The obtained data can be used to identify the variable nucleotide positions characterized by frequent occurrence which is most promising for various identifications.

Keywords: coding region, Iraq, mitochondrial DNA, polymorphic positions, sanger technique

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Authors: Ali Fadhel Ahmed, Tuqa Abdulkareem Hameed

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Moringa oleifera (leaves and seeds) ethanolic and aqueous extracts were tested for antibacterial activity. The effect of plant extracts on three types of bacterial species: Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae, was investigated. Using the agar well diffusion method, ethanolic extracts of Moringa oleifera demonstrated a significant antibacterial effect on the forty tested bacterial strains. Seed-induced inhibition zones (ethanolic extracts)were ranged from16 to 24 mm in diameter against S. aureus, respectively, whileE. coli and K. pneumonia had no effect. Gram-positive and Gram-negative bacteria were not affected by alcoholic and aqueous plant leaf extracts. The purpose of this present study was to look at the cytotoxic effects of M.Oleifera plant (alcoholic extracts).

Keywords: moringa oleifera, escherichia coli, klebsiella pneumoniae, staphylococcus aureus

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Authors: Yasaman Tabari-Saadi, Kaiwen Sun, Jialiang Huang, Martin Green, Xiaojing Hao

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Optical and electrical properties of p-type AgBiS₂ absorber material have been improved by copper doping on silver sites. X-Ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analysis suggest that complete solid solutions of Ag₁₋ₓCuₓBiS₂ thin film have been formed. The carrier concentration of pure AgBiS₂ thin film deposited by the chemical process is 4.5*E+14 cm⁻³, and copper doping leads to the improved carrier concentration despite the semiconductor AgBiS₂ remains p-type semiconductor. Copper doping directly changed the absorption coefficient and increased the optical band gap (~1.5eV), which makes it a promising absorber for thin-film solar cell applications.

Keywords: copper doped, AgBiS₂, thin-film solar cell, carrier concentration, p-type semiconductor

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Authors: Lia Marchi, Ernesto Antonini

Abstract:

The impact of industrial sites on people’s living environment both involves detrimental effects on the ecosystem and perceptual-aesthetic interferences with the scenery. These, in turn, affect the economic and social value of the landscape, as well as the wellbeing of workers and local communities. Given the diffusion of the phenomenon and the relevance of its effects, it emerges the need for a joint approach to assess and thus mitigate the impact of factories on the landscape –being this latest assumed as the result of the action and interaction of natural and human factors. However, the impact assessment tools suitable for the purpose are quite heterogeneous and mostly monodisciplinary. On the one hand, green building rating systems (GBRSs) are increasingly used to evaluate the performance of manufacturing sites, mainly by quantitative indicators focused on environmental issues. On the other hand, methods to detect the visual and social impact of factories on the landscape are gradually emerging in the literature, but they generally adopt only qualitative gauges. The research addresses the integration of the environmental impact assessment and the perceptual-aesthetic interferences of factories on the landscape. The GBRSs model is assumed as a reference since it is adequate to simultaneously investigate different topics which affect sustainability, returning a global score. A critical analysis of GBRSs relevant to industrial facilities has led to select the U.S. GBC LEED protocol as the most suitable to the scope. A revision of LEED v4 Building Design+Construction has then been provided by including specific indicators to measure the interferences of manufacturing sites with the perceptual-aesthetic and social aspects of the territory. To this end, a new impact category was defined, namely ‘PA - Perceptual-aesthetic aspects’, comprising eight new credits which are specifically designed to assess how much the buildings are in harmony with their surroundings: these investigate, for example the morphological and chromatic harmonization of the facility with the scenery or the site receptiveness and attractiveness. The credits weighting table was consequently revised, according to the LEED points allocation system. As all LEED credits, each new PA credit is thoroughly described in a sheet setting its aim, requirements, and the available options to gauge the interference and get a score. Lastly, each credit is related to mitigation tactics, which are drawn from a catalogue of exemplary case studies, it also developed by the research. The result is a modified LEED scheme which includes compatibility with the landscape within the sustainability assessment of the industrial sites. The whole system consists of 10 evaluation categories, which contain in total 62 credits. Lastly, a test of the tool on an Italian factory was performed, allowing the comparison of three mitigation scenarios with increasing compatibility level. The study proposes a holistic and viable approach to the environmental impact assessment of factories by a tool which integrates the multiple involved aspects within a worldwide recognized rating protocol.

Keywords: environmental impact, GBRS, landscape, LEED, sustainable factory

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Authors: Juliana Bastos dos Santos, Francisca Dantas Mendes, Abdul Jabbar Mohammad Khatri, Adam Abdul Jabbar Khatri

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This research aims to describe the experimentation of color extraction from household waste, for the application of the natural vegetable dyeing technique, as a more sustainable option for the upcycling process. Based on the research of the case study, this article intends to record the process of collecting the materials, extracting the colors and their applicability. The study aims to deepen the knowledge about possible alternatives that generate less impact on the environment throughout the process of plant stamping and, also, to spread the concepts of sustainability in fashion. Therefore, this content becomes relevant for valuing an artisanal production process, reconnecting with ancestral knowledge. This article also intends to serve as a record of ancestral artisanal processes, based on the indigenous and African matrices that are pillars of Brazilian culture.

Keywords: natural dyeing, sustainability, organic residue, fashion, reuse

Procedia PDF Downloads 177

Authors: Joanna Szymanska, Paulina Wawulska-Marek, Jaroslaw Mizera

Abstract:

Nowadays, the rapid growth of global energy consumption and uncontrolled depletion of natural resources become a serious problem. Shale rocks are the largest and potential global basins containing hydrocarbons, trapped in closed pores of the shale matrix. Regardless of the shales origin, mining conditions are extremely unfavourable due to high reservoir pressure, great depths, increased clay minerals content and limited permeability (nanoDarcy) of the rocks. Taking into consideration such geomechanical barriers, effective extraction of natural gas from shales with plastic zones demands effective operations. Actually, hydraulic fracturing is the most developed technique based on the injection of pressurized fluid into a wellbore, to initiate fractures propagation. However, a rapid drop of pressure after fluid suction to the ground induces a fracture closure and conductivity reduction. In order to minimize this risk, proppants should be applied. They are solid granules transported with hydraulic fluids to locate inside the rock. Proppants act as a prop for the closing fracture, thus gas migration to a borehole is effective. Quartz sands are commonly applied proppants only at shallow deposits (USA). Whereas, ceramic proppants are designed to meet rigorous downhole conditions to intensify output. Ceramic granules predominate with higher mechanical strength, stability in strong acidic environment, spherical shape and homogeneity as well. Quality of ceramic proppants is conditioned by raw materials selection. Aim of this study was to obtain the proppants from aluminosilicates (the kaolinite subgroup) and mix of minerals with a high alumina content. These loamy minerals contain a tubular and platy morphology that improves mechanical properties and reduces their specific weight. Moreover, they are distinguished by well-developed surface area, high porosity, fine particle size, superb dispersion and nontoxic properties - very crucial for particles consolidation into spherical and crush-resistant granules in mechanical granulation process. The aluminosilicates were mixed with water and natural organic binder to improve liquid-bridges and pores formation between particles. Afterward, the green proppants were subjected to sintering at high temperatures. Evaluation of the minerals utility was based on their particle size distribution (laser diffraction study) and thermal stability (thermogravimetry). Scanning Electron Microscopy was useful for morphology and shape identification combined with specific surface area measurement (BET). Chemical composition was verified by Energy Dispersive Spectroscopy and X-ray Fluorescence. Moreover, bulk density and specific weight were measured. Such comprehensive characterization of loamy materials confirmed their favourable impact on the proppants granulation. The sintered granules were analyzed by SEM to verify the surface topography and phase transitions after sintering. Pores distribution was identified by X-Ray Tomography. This method enabled also the simulation of proppants settlement in a fracture, while measurement of bulk density was essential to predict their amount to fill a well. Roundness coefficient was also evaluated, whereas impact on mining environment was identified by turbidity and solubility in acid - to indicate risk of the material decay in a well. The obtained outcomes confirmed a positive influence of the loamy minerals on ceramic proppants properties with respect to the strict norms. This research is perspective for higher quality proppants production with costs reduction.

Keywords: aluminosilicates, ceramic proppants, mechanical granulation, shale gas

Procedia PDF Downloads 160