Search results for: liquid-liquid extraction

Authors: Ming-Hong Chen

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In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Joshue Perez, Javier Araluce

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, the following paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for indepth gesture classification. This tandem of MediaPipe's extraction prowess and MPL's analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System (ROS), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: gesture detection, mediapipe, multiperceptron layer, robot operating system

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Authors: C. Y. Ng, A. M. Johan, A. E. Kajuputra

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Wave-in-deck phenomenon for fixed jacket platforms at shallow water condition has been reported as a notable risk to the workability and reliability of the platform. Reduction in reservoir pressure, due to the extraction of hydrocarbon for an extended period of time, has caused the occurrence of seabed subsidence. Platform experiencing subsidence promotes reduction of air gaps, which eventually allows the waves to attack the bottom decks. The impact of the wave-in-deck generates additional loads to the structure and therefore increases the values of the moment arms. Higher moment arms trigger instability in terms of overturning, eventually decreases the reserve strength ratio (RSR) values of the structure. The mechanics of wave-in-decks, however, is still not well understood and have not been fully incorporated into the design codes and standards. Hence, it is necessary to revisit the current design codes and standards for platform design optimization. The aim of this study is to evaluate the effects of RSR due to wave-in-deck on four-legged jacket platforms in Malaysia. Base shear values with regards to calibration and modifications of wave characteristics were obtained using SESAM GeniE. Correspondingly, pushover analysis is conducted using USFOS to retrieve the RSR. The effects of the contributing factors i.e. the wave height, wave period and water depth with regards to the RSR and base shear values were analyzed and discussed. This research proposal is important in optimizing the design life of the existing and aging offshore structures. Outcomes of this research are expected to provide a proper evaluation of the wave-in-deck mechanics and in return contribute to the current mitigation strategies in managing the issue.

Keywords: wave-in-deck loads, wave effects, water depth, fixed jacket platforms

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Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

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Authors: Okafor E. Ijeoma, Isimi C. Yetunde, Okoh E. Judith, Kunle O. Olobayo, Emeje O. Martins

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Starch has gained interest as a renewable and environmentally compatible polymer due to the increase in its use. However, starch by itself could not be satisfactorily applied in industrial processes due to some inherent disadvantages such as its hydrophilic character, poor mechanical properties, its inability to withstand processing conditions such as extreme temperatures, diverse pH, high shear rate, freeze-thaw variation and dimensional stability. The range of physical properties of parent starch can be enlarged by chemical modification which invariably enhances their use in a number of applications found in industrial processes and food manufacture. In this study, Manihot esculentus starch was subjected to modification by oxidation. Fourier Transmittance Infra- Red (FTIR) and Raman spectroscopies were used to confirm the synthesis while Scanning Electron Microscopy (SEM) and X- Ray Diffraction (XRD) were used to characterize the new polymer. DPPH (2, 2-diphenyl-1-picryl-hydrazyl-hydrate) free radical assay was used to determine the antioxidant property of the oxidized starch. Our results show that the modification had no significant effect on the foaming capacity as well as on the emulsion capacity. Scanning electron microscopy revealed that oxidation did not alter the predominantly circular-shaped starch granules, while the X-ray pattern of both starch, native and modified were similar. FTIR results revealed a new band at 3007 and 3283cm-1. Differential scanning calorimetry returned two new endothermic peaks in the oxidized starch with an improved gelation capacity and increased enthalpy of gelatinization. The IC50 of oxidized starch was notably higher than that of the reference standard, ascorbic acid.

Keywords: antioxidant activity, DPPH, M. esculentus, oxidation, starch

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Authors: Eduzor Esther, Uhiara Ngozi, Ya’u Abubakar Umar, Anayo Jacob Gabriel, Umar Ahmed

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The study investigated the characteristic effect of treating okra seed and soybeans seed oil with crude enzymes extract from malted rice. The oils from okra seeds and soybeans were obtained by solvent extraction method using N-hexane solvent. Soybeans seeds had higher percentage oil yield than okra seed. 250ml of each oil was thoroughly mixed with 5ml of the malted rice extract at 400C for 5mins and then filtered and regarded as treated oil while another batch of 250ml of each oil was not mixed with the malted rice extract and regarded as untreated oil. All the oils were analyzed for specific gravity, refractive index, emulsification capacity, absortivity, TSS and viscosity. Treated okra seed and soybeans oil gave higher values for specific gravity, than the untreated oil for okra seed and soybeans oil respectively. The emulsification capacity values were also higher for treated oils, when compared to the untreated oil, for okra seed and soybeans oil respectively. Treated okra seed and soybeans oil also had higher range of values for absorptivity, than the untreated oil for okra seed and soybeans respectively. The ranges of T.S.S values of the treated oil were also higher, than those of the untreated oil for okra seed and soybeans respectively. The results of viscosity showed that the treated oil had higher values, than the untreated oil for okra seed and soybeans oil respectively. However, the results of refractive index showed that the untreated oils had higher values ranges of than the treated oils for okra seed and soybeans respectively. Treated oil show better quality in respect to the parameters analyst, except the refractive index which is slightly less but also is within the rangiest of standard, the oils are high in unsaturation especially okra oil when compared with soya beans oil. It is recommended that, treated oil of okra seeds and soya beans can serve better than many oils that presently in use such as ground nut oil, palm oil and cotton seeds oil.

Keywords: extract, malted, oil, okra, rice, seed, soybeans

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Authors: Mir Md Abdus Salam, Muhammad Mohsin, Pertti Pulkkinen, Paavo Pelkonen, Ari Pappinen

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Soils contaminated with metals, e.g., copper (Cu), zinc (Zn) and nickel (Ni) are one of the main global environmental problems. Zn is an important element for plant growth, but excess levels may become a threat to plant survival. Soils polluted with metals may also pose risks and hazards to human health. Afforestation based on short rotation Salix crops may be a good solution for the reduction of metals toxicity levels in the soil and in ecosystem restoration of severely polluted sites. In a greenhouse experiment, plant growth and zinc (Zn) uptake by four Salix cultivars grown in Zn contaminated soils collected from a mining area in Finland were tested to assess their suitability for phytoextraction. The sequential extraction technique and inductively coupled plasma‒mass spectrometry (ICP–MS) were used to determine the extractable metals and evaluate the fraction of metals in the soil that could be potentially available for plant uptake. The cultivars displayed resistance to heavily polluted soils throughout the whole experiment. After uptake, the total mean Zn concentrations ranged from 776 to 1823 mg kg⁻¹. The average uptake percentage of Zn across all cultivars and treatments ranged from 97 to 223%. Lime and wood ash addition showed a significant effect on plant dry biomass growth and metal uptake percentage of Zn in most of the cultivars. The results revealed that Salix cultivars have the potential to accumulate and take up significant amounts of Zn. Ecological restoration of polluted soils could be environmentally favorable in conjunction with economically profitable practices, such as forestry and bioenergy production. As such, the utilization of Salix for phytoextraction and bioenergy purposes is of considerable interest.

Keywords: lime, phytoextraction, Salix, wood ash, zinc

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Salah Hosseini, Hadi Ramezani, Bagher Shahbazi, Hossein Rabiei, Jafar Hooshmand, Hiwa Khaldi

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Diversity of energy portfolio and fluctuation of urban energy demand establish the need for more operational flexibility of combined Cooling, Heat, and Power Plants. Currently, the most common way to achieve these specifications is the use of heat storage devices or wet operation of gas turbines. The current work addresses using variable extraction steam turbine in conjugation with a gas turbine inlet cooling system as an alternative way for enhancement of a CCHP cycle operating range. A thermodynamic model is developed and typical apartments building in PARDIS Technology Park (located at Tehran Province) is chosen as a case study. Due to the variable Heat demand and using excess chiller capacity for turbine inlet cooling purpose, the mentioned steam turbine and TIAC system provided an opportunity for flexible operation of the cycle and boosted the independence of the power and heat generation in the CCHP plant. It was found that the ratio of power to the heat of CCHP cycle varies from 12.6 to 2.4 depending on the City heating and cooling demands and ambient condition, which means a good independence between power and heat generation. Furthermore, selection of the TIAC design temperature is done based on the amount of ratio of power gain to TIAC coil surface area, it was found that for current cycle arrangement the TIAC design temperature of 15 C is most economical. All analysis is done based on the real data, gathered from the local weather station of the PARDIS site.

Keywords: CCHP plant, GTG, HRSG, STG, TIAC, operational flexibility, power to heat ratio

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Authors: Bushra

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This paper explores the historical significance, ecological benefits, and contemporary applications of natural dyes in textile dyeing, aiming to provide a comprehensive overview of their potential to contribute to a sustainable fashion industry while minimizing ecological footprints. This research explores the potential of natural dyes as a sustainable alternative to synthetic dyes in the textile industry, examining their historical context, sources, and environmental benefits. Natural dyes come from plants, animals, and minerals, including roots, leaves, bark, fruits, flowers, insects, and metal salts, used as mordants to fix dyes to fabrics. Natural dyeing involves extraction, mordanting, and dyeing techniques. Optimizing these processes can enhance the performance of natural dyes, making them viable for contemporary textile applications based on experimental research. Natural dyes offer eco-friendly benefits like biodegradability, non-toxicity, and resource renewables, reducing pollution, promoting biodiversity, and reducing reliance on petrochemicals. Natural dyes offer benefits but face challenges in color consistency, scalability, and performance, requiring industrial production to meet modern consumer standards for durability and colorfastness. Contemporary initiatives in the textile industry include fashion brands like Eileen Fisher and Patagonia incorporating natural dyes, artisans like India Flint's Botanical Alchemy promoting traditional dyeing techniques, and research projects like the European Union's Horizon 2020 program. Natural dyes offer a sustainable textile industry solution, reducing environmental impact and promoting harmony with nature. Research and innovation are paving the way for widespread adoption, transforming textile dyeing.

Keywords: historical significance, textile industry, natural dyes, sustainability

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Authors: D. Kuvshinov, A. Siswanto, W. Zimmerman

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A phorbol-12-myristate-13-acetate (TPA) is a synthetic analogue of phorbol ester (PE), a natural toxic compound of Euphorbiaceae plant. The oil extracted from plants of this family is useful source for primarily biofuel. However this oil can also be used as a food stock due to its significant nutrition content. The limitations for utilizing the oil as a food stock are mainly due to a toxicity of PE. Nowadays a majority of PE detoxification processes are expensive as include multi steps alcohol extraction sequence. Ozone is considered as a strong oxidative agent. It reaction with PE it attacks the carbon double bond of PE. This modification of PE molecular structure results into nontoxic ester with high lipid content. This report presents data on development of simple and cheap PE detoxification process with water application as a buffer and ozone as reactive component. The core of this new technique is a simultaneous application of new microscale plasma unit for ozone production and patented gas oscillation technology. In combination with a reactor design the technology permits ozone injection to the water-TPA mixture in form of microbubbles. The efficacy of a heterogeneous process depends on diffusion coefficient which can be controlled by contact time and interface area. The low velocity of rising microbubbles and high surface to volume ratio allow fast mass transfer to be achieved during the process. Direct injection of ozone is the most efficient process for a highly reactive and short lived chemical. Data on the plasma unit behavior are presented and influence of the gas oscillation technology to the microbubbles production mechanism has been discussed. Data on overall process efficacy for TPA degradation is shown.

Keywords: microbubble, ozonolysis, synthetic phorbol ester, chemical engineering

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Authors: Djeffal Asma, Zemmouri Noureddine

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In order for building designer to be able to balance environmental concerns with other performance requirements, they need clear and concise information. For certain decisions during the design process, qualitative guidance, such as design checklists or guidelines information may not be sufficient for evaluating the environmental benefits between different building materials, products and designs. In this case, quantitative information, such as that generated through a life cycle assessment, provides the most value. LCA provides a systematic approach to evaluating the environmental impacts of a product or system over its entire life. In the case of buildings life cycle includes the extraction of raw materials, manufacturing, transporting and installing building components or products, operating and maintaining the building. By integrating LCA into building design process, designers can evaluate the life cycle impacts of building design, materials, components and systems and choose the combinations that reduce the building life cycle environmental impact. This article attempts to give an overview of the integration of LCA methodology in the context of building design, and focuses on the use of this methodology for environmental considerations concerning process design and optimization. A multiple case study was conducted in order to assess the benefits of the LCA as a decision making aid tool during the first stages of the building design under specific climate conditions of the North East region of Algeria. It is clear that the LCA methodology can help to assess and reduce the impact of a building design and components on the environment even if the process implementation is rather long and complicated and lacks of global approach including human factors. It is also demonstrated that using LCA as a multi objective optimization of building process will certainly facilitates the improvement in design and decision making for both new design and retrofit projects.

Keywords: life cycle assessment, buildings, sustainability, elementary schools, environmental impacts

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Authors: Rodrigo Antunes, Olga Borisevich, David Demange

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The Tritium Laboratory Karlsruhe (TLK) has identified zeolite membranes as most promising for tritium processes in the future fusion reactors. Tritium diluted in purge gases or gaseous effluents, and present in both molecular and oxidized forms, can be pre-concentrated by a stage of zeolite membranes followed by a main downstream recovery stage (e.g., catalytic membrane reactor). Since 2011 several membrane zeolite samples have been tested to measure the membrane performances in the separation of hydrogen and water vapor from helium streams. These experiments were carried out in the ZIMT (Zeolite Inorganic Membranes for Tritium) facility where mass spectrometry and cold traps were used to measure the membranes’ performances. The membranes were tested at temperatures ranging from 25 °C up to 130 °C, at feed pressures between 1 and 3 bar, and typical feed flows of 2 l/min. During this experimental campaign, several zeolite-type membranes were studied: a hollow-fiber MFI nanocomposite membrane purchased from IRCELYON (France), and tubular MFI-ZSM5, NaA and H-SOD membranes purchased from Institute for Ceramic Technologies and Systems (IKTS, Germany). Among these membranes, only the MFI-based showed relevant performances for the H2/He separation, with rather high permeances (~0.5 – 0.7 μmol/sm2Pa for H2 at 25 °C for MFI-ZSM5), however with a limited ideal selectivity of around 2 for H2/He regardless of the feed concentration. Both MFI and NaA showed higher separation performances when water vapor was used instead; for example, at 30 °C, the separation factor for MFI-ZSM5 is approximately 10 and 38 for 0.2% and 10% H2O/He, respectively. The H-SOD evidenced to be considerably defective and therefore not considered for further experiments. In this contribution, a comprehensive analysis of the experimental methods and results obtained for the separation performance of different zeolite membranes during the past four years in inactive environment is given. These results are encouraging for the experimental campaign with molecular and oxidized tritium that will follow in 2017.

Keywords: gas separation, nuclear fusion, tritium processes, zeolite membranes

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Authors: Bassem Nassar, Wessam Hussein, Medhat Mokhtar

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The crucial concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems in order to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important in order to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the aforementioned problem coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions and the results shows that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: space telemetry monitoring, multivariate analysis, PCA algorithm, space operations

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Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

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Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: Boutemak Khalida, Dahmani Siham

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Garden cress (Lepidium Sativum L.) belonging to the family Brassicaceae, is edible growing annual herb. Its various parts (roots, leaves and seeds) have been used to treat various human ailments. Its seed extracts have been screened for various biological activities like hypotensive, antimicrobial, bronchodilator, hypoglycaemic and antianemic. The aim of the present study is to optimize the process parameters (cellulase concentration and incubation time) of enzymatic pre-treatment of the garden cress seeds and to evaluate the effect of cellulase pre-treatment of the crushed seeds on the oil yield, physico-chemical properties and antibacterial activity and comparing to non-enzymatic method. The optimum parameters of cellulase pre-treatment were as follows: cellulase of 0,1% w/w and incubation time of 2h. After enzymatic pre-treatment, the oil was extracted by n-hexane for 1.5 h, the oil yield was 4,01% for cellulase pre-treatment as against 10,99% in the control sample. The decrease in yield might be caused a result of mucilage. Garden cress seeds are covered with a layer of mucilage which gels on contact with water. At the same time, the antibacterial activity was carried out using agar diffusion method against 4 food-borne pathogens (Escherichia coli, Salmonella typhi,Staphylococcus aureus, Bacillus subtilis). The results showed that bacterial strains are very sensitive to the oil with cellulase pre-treatment. Staphylococcus aureus is extremely sensitive with the largest zone of inhibition (40 mm), Escherichia coli and salmonella typhi had a very sensitive to the oil with a zone of inhibition (26 mm). Bacillus subtilizes is averagely sensitive which gave an inhibition of 16 mm. But it does not exhibit sensivity to the oil without enzymatic pre-treatment with a zone inhibition (< 8 mm). Enzymatic pre-treatment could be useful for antimicrobial activity of the oil, and hold a good potential for use in food and pharmaceutical industries.

Keywords: Lepidium sativum L., cellulase, enzymatic pretreatment, antibacterial activity.

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Authors: Hafida Merzouk

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Urinary tract infections are among the most serious public health issues in all age groups. Thus, the empirical therapy should based on local levels of resistance, as indicated in several studies from different countries, to effectively avoid the emergence of multidrug-resistant bacterial strains and recurrent infections. Numerous effective antibiotic treatments are available, but wouldbe ineffective for treating recurrent cystitis caused by a urinary tract infection, as well as the emergence of drug resistance. That iswhy the aim of this study was to highlight the antibacterial and the antioxidant activity of 11 medicinal plants used traditionally in Algeria against E. coli, the most responsible urinary tract infections. First, the extraction of total polyphenols with aqueous acetone showed variable yields. The highest yield was obtained by Asplenium trichomanes with 27%, followed by Petroselinum crispum and Ciannamomum cassia with an equal yield of 21%. Artemisia herba-alba gave the lowest yield (9%). The extracts of different plants showed variable contents of phenolic compounds. Reducing power and DPPH (2,2-diphenyl-1-picrylhydrazyl) scavenging activity revealed that most of the extracts studied had significant activity. The anti-free radical activity was very high in the extract of A splenium adiantum-nigrum compared with the other extracts studied, but Petroselinum crispum and Parietaria officinalis had the lowest reducing activity; Antibacterial activity was determined on E. coli strainsusing the diffusion, MICs (Minimum Inhibitory Concentrations) and MBCs (Minimum Bactericidal concentrations) methods. The strains tested were sensitive to most extracts studied, except Asplenium adiantum-nigrum extract, for which both strains showed resistance.

Keywords: E. coli, medicinal plants, phenolic compounds, urinary infections

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Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

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Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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Authors: Assia Belfar, Mohamed Hadjadj, Messaouda Dakmouche, Zineb Ghiaba, Mahdi Belguidoum

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Introduction: This study aims to phytochemical screening; Extracting the active compounds and estimate the effectiveness of antioxidant in Medicinal plants desert Limoniastrum guyonianum (Zeïta) from South Algeria. Methods: Total phenolic content and total flavonoid content using Folin-Ciocalteu and aluminum chloride colorimetric methods, respectively. The total antioxidant capacity was estimated by the following methods: DPPH (1.1-diphenyl-2-picrylhydrazyl radical) and reducing power assay. Results: Phytochemical screening of the plant part reveals the presence of phenols, saponins, flavonoids and tannins. While alkaloids and Terpenoids were absent. The Methanolic extract of L. guyonianum was extracted successively with ethyl acetate and butanol. Extraction of yield varied widely in the L. guyonianum ranging from (1.315 % to 4.218%). butanol fraction had the highest yield. The higher content of phenols was recorded in butanol fraction (311.81 ± 0.02mg GAE/g DW), the higher content of flavonoids was found in butanol fraction (9.58 ± 0.33mg QE/g DW). IC50 of inhibition of radical DPPH in ethyl acetate fraction was (0.05 ± 0.01µg/ml) Equal effectiveness with BHT, All extracts showed good activity of ferric reducing power, the higher power was in butanol fraction (16.16 ± 0.05mM). Conclusions: Demonstrated this study that the Methanolic extract of L. guyonianum contain a considerable quantity of phenolic compounds and possess a good antioxidant activity. It can be used as an easily accessible source of Natural Antioxidants and as a possible food supplement and in pharmaceutical industry.

Keywords: flavonoid compound, l. guyonianum, medicinal plants, phenolic compounds, phytochemical screening

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Authors: Debajyoti Bose

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Chitosan has received much attention as a functional biopolymer for diverse applications, especially in pharmaceutics and medicine. Chitosan is a positively charged natural biodegradable and biocompatible polymer. It is a linear polysaccharide consisting of β-1,4 linked monomers of glucosamine and N-acetylglucosamine. Chitosan can be mainly obtained from fungal sources during large fermentation process. In this study,three different fungal strains Aspergillus niger NCIM 1045, Aspergillus oryzae NCIM 645 and Mucor indicus MTCC 3318 were used for the production of chitosan. The growth mediums were optimized for maximum fungal production. The produced chitosan was characterized by determining degree of deacetylation. Chitosan possesses one reactive amino at the C-2 position of the glucosamine residue, and these amines confer important functional properties to chitosan which can be exploited for biofabrication to generate various chemically modified derivatives and explore their potential for pharmaceutical field. Chitosan nanoparticles were prepared by ionic cross-linking with tripolyphosphate (TPP). The major effect on encapsulation and release of protein (e.g. enzyme diastase) in chitosan-TPP nanoparticles was investigated in order to control the loading and release efficiency. It was noted that the chitosan loading and releasing efficiency as a nanocapsule, obtained from different fungal sources was almost near to initial enzyme activity(12026 U/ml) with a negligible loss. This signify, chitosan can be used as a polymeric drug as well as active component or protein carrier material in dosage by design due to its appealing properties such as biocompatibility, biodegradability, low toxicity and relatively low production cost from abundant natural sources. Based upon these initial experiments, studies were also carried out on modification of chitosan based nanocapsules incorporated with physiologically important enzymes and nutraceuticals for target delivery.

Keywords: fungi, chitosan, enzyme, nanocapsule

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Leo Paul Vaurs, Sonia Heaven, Charles Banks

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Municipal solid waste (MSW) is a virtually unlimited source of lignocellulosic material in the form of a waste paper/cardboard mixture which can be converted into fermentable sugars via cellulolytic enzyme hydrolysis in a biorefinery. The extraction of the lignocellulosic fraction and its preparation, however, are energy and water demanding processes. The waste water generated is a rich organic liquor with a high Chemical Oxygen Demand that can be partially cleaned while generating biogas in an Upflow Anaerobic Sludge Blanket bioreactor and be further re-used in the process. In this work, an experiment was designed to determine the critical contaminant concentrations in water affecting either anaerobic digestion or enzymatic hydrolysis by simulating multiple water re-circulations. It was found that re-using more than 16.5 times the same water could decrease the hydrolysis yield by up to 65 % and led to a complete granules desegregation. Due to the complexity of the water stream, the contaminant(s) responsible for the performance decrease could not be identified but it was suspected to be caused by sodium, potassium, lipid accumulation for the anaerobic digestion (AD) process and heavy metal build-up for enzymatic hydrolysis. The experimental data were incorporated into a Water Pinch technology based model that was used to optimize the water re-utilization in the modelled system to reduce fresh water requirement and wastewater generation while ensuring all processes performed at optimal level. Multiple scenarios were modelled in which sub-process requirements were evaluated in term of importance, operational costs and impact on the CAPEX. The best compromise between water usage, AD and enzymatic hydrolysis yield was determined for each assumed contaminant degradations by anaerobic granules. Results from the model will be used to build the first MSW based biorefinery in the USA.

Keywords: anaerobic digestion, enzymatic hydrolysis, municipal solid waste, water optimization

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Authors: Mahesh Kumar Jat, Manisha Choudhary

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Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

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Authors: Ilme Faridatul, Bo Wu

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Bangladesh is often called as a motherland of rivers. It contains about 700 rivers among all these the Padma River is one of the largest rivers of Bangladesh. The change of river bank and erosion has become a common environmental natural hazard in Bangladesh. The river banks are under intense pressure from natural processes such as erosion and accretion as well as anthropogenic processes such as urban growth and pollution. The Padma River is flowing along ten districts of Bangladesh among all these Faridpur district is most vulnerable to river bank erosion. The severity of the river erosion is so high that each year a thousand of populations become homeless and lose their agricultural lands. Though the Faridpur district is most vulnerable to river bank erosion no specific research has been conducted to identify the changing pattern of river bank along this district. The outcome of the research may serve as guidance to prepare river bank monitoring program and management. This research has utilized integrated techniques of remote sensing and geographic information system to monitor the changes from 1995 to 2015 at Faridpur district. To discriminate the land water interface Modified Normalized Difference Water Index (MNDWI) algorithm is applied and on screen digitization approach is used over MNDWI images of 1995, 2002 and 2015 for river bank line extraction. The extent of changes in the river bank along Faridpur district is estimated through overlaying the digitized maps of all three years. The river bank lines are highlighted to infer the erosion and accretion and the changes are calculated. The result shows that the middle of the river is gaining land through sedimentation and the both side river bank is shifting causing severe erosion that consequently resulting the loss of farmland and homestead. Over the study period from 1995 to 2015 it witnessed huge erosion and accretion that played an active role in the changes of the river bank.

Keywords: river bank, erosion and accretion, change monitoring, remote sensing

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Authors: F. Bellali, M. Kharroubi, Y. Rady, N. Bourhim

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In Morocco, fish processing industry is an important source income for a large amount of by-products including skins, bones, heads, guts, and scales. Those underutilized resources particularly scales contain a large amount of proteins and calcium. Sardina plichardus scales from resulting from the transformation operation have the potential to be used as raw material for the collagen production. Taking into account this strong expectation of the regional fish industry, scales sardine upgrading is well justified. In addition, political and societal demands for sustainability and environment-friendly industrial production systems, coupled with the depletion of fish resources, drive this trend forward. Therefore, fish scale used as a potential source to isolate collagen has a wide large of applications in food, cosmetic, and biomedical industry. The main aim of this study is to isolate and characterize the acid solubilize collagen from sardine fish scale, Sardina pilchardus. Experimental design methodology was adopted in collagen processing for extracting optimization. The first stage of this work is to investigate the optimization conditions of the sardine scale deproteinization on using response surface methodology (RSM). The second part focus on the demineralization with HCl solution or EDTA. And the last one is to establish the optimum condition for the isolation of collagen from fish scale by solvent extraction. The advancement from lab scale to pilot scale is a critical stage in the technological development. In this study, the optimal condition for the deproteinization which was validated at laboratory scale was employed in the pilot scale procedure. The deproteinization of fish scale was then demonstrated on a pilot scale (2Kg scales, 20l NaOH), resulting in protein content (0,2mg/ml) and hydroxyproline content (2,11mg/l). These results indicated that the pilot-scale showed similar performances to those of lab-scale one.

Keywords: deproteinization, pilot scale, scale, sardine pilchardus

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Authors: Edward Poluyi, Eghosa Morgan, Charles Poluyi, Chibuikem Ikwuegbuenyi, Grace Imaguezegie

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Background: Current epidemiological studies have examined the associations between moderate and severe traumatic brain injury (TBI) and their risks of developing neurodegenerative diseases. Concussion, also known as mild TBI (mTBI), is however quite distinct from moderate or severe TBIs. Only few studies in this burgeoning area have examined concussion—especially repetitive episodes—and neurodegenerative diseases. Thus, no definite relationship has been established between them. Objectives : This review will discuss the available literature linking concussion and amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease (AD). Materials and Methods: Given the complexity of this subject, a realistic review methodology was selected which includes clarifying the scope and developing a theoretical framework, developing a search strategy, selection and appraisal, data extraction, and synthesis. A detailed literature matrix was set out in order to get relevant and recent findings on this topic. Results: Presently, there is no objective clinical test for the diagnosis of concussion because the features are less obvious on physical examination. Absence of an objective test in diagnosing concussion sometimes leads to skepticism when confirming the presence or absence of concussion. Intriguingly, several possible explanations have been proposed in the pathological mechanisms that lead to the development of some neurodegenerative disorders (such as ALS and AD) and concussion but the two major events are deposition of tau proteins (abnormal microtubule proteins) and neuroinflammation, which ranges from glutamate excitotoxicity pathways and inflammatory pathways (which leads to a rise in the metabolic demands of microglia cells and neurons), to mitochondrial function via the oxidative pathways.

Keywords: amyotrophic lateral sclerosis, Alzheimer's disease, mild traumatic brain injury, neurodegeneration

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Authors: Gizachew Belay Adugna

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Scalable and cost-effective device fabrication techniques are urgent to commercialize the perovskite solar cells (PSCs) for the next photovoltaic (PV) technology. Herein, large-area films of perovskite and hole-transporting materials (HTMs) were developed via a rapid and scalable thermal-assisting bar-coating process in the open air. High-quality and large crystalline grains of MAPbI₃ with homogenous morphology and thickness were obtained on a large-area (10 cm×10 cm) solution-sheared mp-TiO₂/c-TiO₂/FTO substrate. Encouraging photovoltaic performance of 19.02% was achieved for devices fabricated from the bar-coated perovskite film compared to that from the small-scale spin-coated film (17.27%) with 2,2′,7,7′-tetrakis-(N,N-di-p-methoxyphenylamine)-9,9′-spirobifluorene (spiro-OMeTAD) as an HTM whereas a higher power conversion efficiency of 19.89% with improved device stability was achieved by capping a fluorinated (HYC-2) HTM as an alternative to the traditional spiro-OMeTAD. The fluorinated exhibited better molecular packing in the HTM film and deeper HOMO level compared to the nonfluorinated counterpart; thus, improved hole mobility and overall charge extraction in the device were demonstrated. Furthermore, excellent film processability and an impressive PCE of 18.52% were achieved in the large area bar-coated HYC-2 prepared sequentially on the perovskite underlayer in the open atmosphere, compared to the bar-coated spiro-OMeTAD/perovskite (17.51%). This all-solution approach demonstrated the feasibility of high-quality films on a large-area substrate for PSCs, which is a vital step toward industrial-scale PV production.

Keywords: perovskite solar cells, hole transporting materials, up-scaling process, power conversion efficiency

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Authors: Kandi Sridhar, Charles Albert Linton

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Grapes are excellent sources of bioactive compounds, which have been suggested to be responsible for lowering the risk of chronic diseases. Fresh and freeze-dried extracts of Kyoho and Jubilee, commercial grape varieties available in Taiwan and attractive for their quality berries, were investigated for their total phenolics and total flavonoids contents and related dose-dependent antioxidants properties using various in vitro assays. The efficiency of the extraction yield ranged from 7.10 % to 25.53 % (w/w), depending on solvent used. Fresh samples of Kyoho and Jubilee exhibited total polyphenolic contents (351.56 ± 23.08 and 328.67 ± 16.54 µg GAE/mL, respectively), whereas Kyoho freeze-dried methanol: water extracts contains the good levels of total flavonoids (4767.82 ± 22.20 µg QE/mL). Kyoho and Jubilee freeze-dried extracts exhibited the highest total flavonoid contents. There was a weak correlation between total phenolic and flavonoid assays (r= -0.05, R2 = 0.02, p > 0.05). Kyoho fresh and freeze-dried samples showed the DPPH (11.51 – 77.82 %), superoxide scavenging activity (33.61 – 81.95 %), and total antioxidant inhibition (92.01 – 99.28 %), respectively. Total flavonoids were statistically correlated with EC50 DPPH scavenging radicals (r =0.91, p < 0.01), EC50 nitric oxide (r = 0.25, p > 0.05), and EC50 lipid peroxidation radicals (r = 0.38, p > 0.05). These results suggested that the two commercial grape cultivars in Taiwan could be used as a good source of natural antioxidants. Thus, consumption of grapes as a source antioxidant might lower the risk of chronic diseases. Moreover, future studies will investigate and develop phenolic acid profile for the cultivars in Taiwan.

Keywords: antioxidants, EC50 radical scavenging activity, grape cultivars, total phenolics

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Authors: Pablo Andres Flores Siguenza, Noe Rodrigo Guaman Guachichullca

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Sustainable practices have received increasing attention from academics and companies in recent decades due to, among many factors, the market advantages they generate, global commitments, and policies aimed at reducing greenhouse gas emissions, addressing resource scarcity, and rethinking waste management. The search for ways to promote sustainability leads industries to abandon classical methods and resort to the use of innovative strategies, which in turn are based on quantitative analysis methods and tools such as life cycle analysis (LCA), which is the basis for sustainable production and consumption, since it is a method that analyzes objectively, methodically, systematically, and scientifically the environmental impact caused by a process/product during its entire life cycle. The objective of this study is to develop an LCA of the antibacterial gel product throughout its entire supply chain (SC) under the methodology of ISO 14044 with the help of Gabi software and the Recipe 2016 method. The selection of the case study product was made based on its relevance in the current context of the COVID-19 pandemic and its exponential increase in production. For the development of the LCA, data from a Mexican company are used, and 3 scenarios are defined to obtain the midpoint and endpoint environmental impacts both by phases and globally. As part of the results, the most outstanding environmental impact categories are climate change, fossil fuel depletion, and terrestrial ecotoxicity, and the stage that generates the most pollution in the entire SC is the extraction of raw materials. The study serves as a basis for the development of different sustainability strategies, demonstrates the usefulness of an LCA, and agrees with different authors on the role and importance of this methodology in sustainable development.

Keywords: sustainability, sustainable development, life cycle analysis, environmental impact, antibacterial gel

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Authors: O. Ubani, H. I. Atagana, M. S. Thantsha

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This study was conducted to measure the reduction in polycyclic aromatic hydrocarbons (PAHs) content in oil sludge by co-composting the sludge with pig, cow, horse and poultry manures under laboratory conditions. Four kilograms of soil spiked with 800 g of oil sludge was co-composted differently with each manure in a ratio of 2:1 (w/w) spiked soil:manure and wood-chips in a ratio of 2:1 (w/v) spiked soil:wood-chips. Control was set up similar as the one above but without manure. Mixtures were incubated for 10 months at room temperature. Compost piles were turned weekly and moisture level was maintained at between 50% and 70%. Moisture level, pH, temperature, CO2 evolution and oxygen consumption were measured monthly and the ash content at the end of experimentation. Bacteria capable of utilizing PAHs were isolated, purified and characterized by molecular techniques using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE), amplification of the 16S rDNA gene using the specific primers (16S-P1 PCR and 16S-P2 PCR) and the amplicons were sequenced. Extent of reduction of PAHs was measured using automated soxhlet extractor with dichloromethane as the extraction solvent coupled with gas chromatography/mass spectrometry (GC/MS). Temperature did not exceed 27.5O°C in all compost heaps, pH ranged from 5.5 to 7.8 and CO2 evolution was highest in poultry manure at 18.78 µg/dwt/day. Microbial growth and activities were enhanced. Bacteria identified were Bacillus, Arthrobacter and Staphylococcus species. Results from PAH measurements showed reduction between 77 and 99%. The results from the control experiments may be because it was invaded by fungi. Co-composting of spiked soils with animal manures enhanced the reduction in PAHs. Interestingly, all bacteria isolated and identified in this study were present in all treatments, including the control.

Keywords: bioremediation, co-composting, oil refinery sludge, PAHs, bacteria spp, animal manures, molecular techniques

Procedia PDF Downloads 454