Search results for: natural heat transfer convection

Authors: Nalan Kaya, Gonca Ozan, Elif Erdem, Neriman Colakoglu, Enver Ozan

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The toxic effects of tobacco smoke exposure have been detected in numerous studies. Ellagic acid (EA), (2,3,7,8-tetrahydroxy [1]-benzopyranol [5,4,3-cde] benzopyran 5,10-dione), a natural phenolic lactone compound, is found in various plant species including pomegranate, grape, strawberries, blackberries and raspberries. Similar to the other effective antioxidants, EA can safely interact with the free radicals and reduces oxidative stress through the phenolic ring and hydroxyl components in its structure. The aim of the present study was to examine the protective effects of ellagic acid against oxidative damage on lung tissues of rats induced by tobacco smoke. Twenty-four male adult (8 weeks old) Spraque-Dawley rats were divided randomly into 4 equal groups: group I (Control), group II (Tobacco smoke), group III (Tobacco smoke + corn oil) and group IV (Tobacco smoke + ellagic acid). The rats in group II, III and IV, were exposed to tobacco smoke 1 hour twice a day for 12 weeks. In addition to tobacco smoke exposure, 12 mg/kg ellagic acid (dissolved in corn oil), was applied to the rats in group IV by oral gavage. Equal amount of corn oil used in solving ellagic acid was applied to the rats by oral gavage in group III. At the end of the experimental period, rats were decapitated. Lung tissues and blood samples were taken. The lung slides were stained by H&E and Masson’s Trichrome methods. Also, galactin-3 stain was applied. Biochemical analyzes were performed. Vascular congestion and inflammatory cell infiltration in pulmonary interstitium, thickness in interalveolar septum, cytoplasmic vacuolation in some macrophages and galactin-3 positive cells were observed in histological examination of tobacco smoke group. In addition to these findings, hemorrhage in pulmonary interstitium and bronchial lumen was detected in tobacco smoke + corn oil group. Reduced vascular congestion and hemorrhage in pulmoner interstitium and rarely thickness in interalveolar septum were shown in tobacco smoke + EA group. Compared to group-I, group-II GSH level was decreased and MDA level was increased significantly. Nevertheless group-IV GSH level was higher and MDA level was lower than group-II. The results indicate that ellagic acid could protect the lung tissue from the tobacco smoke harmful effects.

Keywords: ellagic acid, lung, rat, tobacco smoke

Procedia PDF Downloads 210

Authors: F. Pires, V. Geraldo, O. N. Oliveira Jr., M. Raposo

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Catechins are powerful antioxidants which have attractive properties useful for tumor therapy. Considering their antioxidant activity, these molecules can act as a scavenger of the reactive oxygen species (ROS), alleviating the damage of cell membrane induced by oxidative stress. The complexity and dynamic nature of the cell membrane compromise the analysis of the biophysical interactions between drug and cell membrane and restricts the transport or uptake of the drug by intracellular targets. To avoid the cell membrane complexity, we used biomimetic systems as liposomes and Langmuir monolayers to study the interaction between catechin and membranes at the molecular level. Liposomes were formed after the dispersion of anionic 1,2-dipalmitoyl-sn-glycero-3-[phospho-rac-(1-glycerol)(sodium salt) (DPPG) phospholipids in an aqueous solution, which mimic the arrangement of lipids in natural cell membranes and allows the entrapment of catechins. Langmuir monolayers were formed after dropping amphiphilic molecules, DPPG phospholipids, dissolved in an organic solvent onto the water surface. In this work, we mixed epigallocatechin-3-gallate (EGCG) with DPPG liposomes and exposed them to ultra-violet radiation in order to evaluate the antioxidant potential of these molecules against oxidative stress induced by radiation. The presence of EGCG in the mixture decreased the rate of lipid peroxidation, proving that EGCG protects membranes through the quenching of the reactive oxygen species. Considering the high amount of hydroxyl groups (OH groups) on structure of EGCG, a possible mechanism to these molecules interact with membrane is through hydrogen bonding. We also investigated the effect of EGCG at various concentrations on DPPG Langmuir monolayers. The surface pressure isotherms and infrared reflection-absorption spectroscopy (PM-IRRAS) results corroborate with absorbance results preformed on liposome-model, showing that EGCG interacts with polar heads of the monolayers. This study elucidates the physiological action of EGCG which can be incorporated in lipid membrane. These results are also relevant for the improvement of the current protocols used to incorporate catechins in drug delivery systems.

Keywords: catechins, lipid membrane, anticancer agent, molecular interactions

Procedia PDF Downloads 227

Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

Procedia PDF Downloads 380

Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

Procedia PDF Downloads 125

Authors: Ahmed M. Eed, Adam H. Burgoyne

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Jojoba (Simmondsia chinensis (Link) Schneider), is a desert shrub which tolerates saline, alkyle soils and drought. The seeds contain a characteristic liquid wax of economic importance in industry as a machine lubricant and cosmetics. A major problem in seed propagation is that jojoba is a dioecious plant whose sex is not easily determined prior to flowering (3-4 years from germination). To overcome this phenomenon, asexual propagation using vegetative methods such as cutting can be used. This research was conducted to find out the effect of different Plant Growth Regulators (PGRs) and rooting media on Jojoba rhizogenesis. An experiment was carried out in a Factorial Completely Randomized Design (FCRD) with three replications, each with sixty cuttings per replication in fiberglass house of Natural Jojoba Corporation at Yemen. The different rooting media used were peat moss + perlite + vermiculite (1:1:1), peat moss + perlite (1:1) and peat moss + sand (1:1). Plant materials used were semi-hard wood cuttings of jojoba plants with length of 15 cm. The cuttings were collected in the month of June during 2012 and 2013 from the sub-terminal growth of the mother plants of Amman farm and introduced to Yemen. They were wounded, treated with Indole butyric acid (IBA), α-naphthalene acetic acid (NAA) or Indole-3-acetic acid (IAA) all @ 4000 ppm (part per million) and cultured on different rooting media under intermittent mist propagation conditions. IBA gave significantly higher percentage of rooting (66.23%) compared to NAA and IAA in all media used. However, the lowest percentage of rooting (5.33%) was recorded with IAA in the medium consisting of peat moss and sand (1:1). No significant difference was observed at all types of PGRs used with rooting media in respect of root length. Maximum number of roots was noticed in medium consisting of peat moss, perlite and vermiculite (1:1:1); peat moss and perlite (1:1) and peat moss and sand (1:1) using IBA, NAA and IBA, respectively. The interaction among rooting media was statistically significant with respect to rooting percentage character. Similarly, the interactions among PGRs were significant in terms of rooting percentage and also root length characters. The results demonstrated suitability of propagation of jojoba plants by semi-hard wood cuttings.

Keywords: cutting, IBA, Jojoba, propagation, rhizogenesis

Procedia PDF Downloads 337

Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

Procedia PDF Downloads 189

Authors: Ajay Kumar Sinha, Sharad Singh, Anukriti Sinha

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Passive energy dissipation method for earthquake protection of structures is undergoing developments for improved performance. Combined use of different types of damping mechanisms has shown positive results in the near past. Different supplemental damping methods like viscous damping, frictional damping and metallic damping are being combined together for optimum performance. The conventional method of connecting passive dampers to structures is a parallel connection between the damper unit and structural member. Researchers are investigating coupling effect of different types of dampers. The most popular choice among the research community is coupling of viscous dampers and frictional dampers. The series and parallel coupling of these damping units are being studied for relative performance of the coupled system on response control of structures against earthquake. In this paper an attempt has been made to couple Fluid Viscous Dampers and Frictional Dampers in series and parallel to form a single unit of damping system. The relative performance of the coupled units has been studied on three dimensional reinforced concrete framed structure. The current theories of structural dynamics in practice for viscous damping and frictional damping have been incorporated in this study. The time history analysis of the structural system with coupled damper units, uncoupled damper units as well as of structural system without any supplemental damping has been performed in this study. The investigations reported in this study show significant improved performance of coupled system. A higher natural frequency of the system outside the forcing frequency has been obtained for structural systems with coupled damper units as against the other cases. The structural response of the structure in terms of storey displacement and storey drift show significant improvement for the case with coupled damper units as against the cases with uncoupled units or without any supplemental damping. The results are promising in terms of improved response of the structure with coupled damper units. Further investigations in this regard for a comparative performance of the series and parallel coupled systems will be carried out to study the optimum behavior of these coupled systems for enhanced response control of structural systems.

Keywords: frictional damping, parallel coupling, response control, series coupling, supplemental damping, viscous damping

Procedia PDF Downloads 445

Authors: Annalisa Gaetani, Anna Nora Tassetti, Gianna Fabi

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The hydroacoustic technology is an efficient tool to study the sea environment: the most recent advancement in artificial habitat mapping involves acoustic systems to investigate fish abundance, distribution and behavior in specific areas. Along with a detailed high-coverage bathymetric mapping of the seabed, the high-frequency Multibeam Echosounder (MBES) offers the potential of detecting fine-scale distribution of fish aggregation, combining its ability to detect at the same time the seafloor and the water column. Surveying fish schools distribution around artificial structures, MBES allows to evaluate how their presence modifies the biological natural habitat overtime in terms of fish attraction and abundance. In the last years, artificial habitat mapping experiences have been carried out by CNR-ISMAR in the Adriatic sea: fish assemblages aggregating at offshore gas platforms and artificial reefs have been systematically monitored employing different kinds of methodologies. This work focuses on two case studies: a gas extraction platform founded at 80 meters of depth in the central Adriatic sea, 30 miles far from the coast of Ancona, and the concrete and steel artificial reef of Senigallia, deployed by CNR-ISMAR about 1.2 miles offshore at a depth of 11.2 m . Relating the MBES data (metrical dimensions of fish assemblages, shape, depth, density etc.) with the results coming from other methodologies, such as experimental fishing surveys and underwater video camera, it has been possible to investigate the biological assemblage attracted by artificial structures hypothesizing which species populate the investigated area and their spatial dislocation from these artificial structures. Processing MBES bathymetric and water column data, 3D virtual scenes of the artificial habitats have been created, receiving an intuitive-looking depiction of their state and allowing overtime to evaluate their change in terms of dimensional characteristics and depth fish schools’ disposition. These MBES surveys play a leading part in the general multi-year programs carried out by CNR-ISMAR with the aim to assess potential biological changes linked to human activities on.

Keywords: artificial habitat mapping, fish assemblages, hydroacustic technology, multibeam echosounder

Procedia PDF Downloads 256

Authors: Paul Essel, Eric T. Glover, Gustav Gbeddy, Yaw Adjei-Kyereme, Abdallah M. A. Dawood, Evans M. Ameho, Emmanuel A. Aberikae

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Radioactive materials mainly in the form of Sealed Radioactive Sources are being used in various sectors (medicine, agriculture, industry, research, and teaching) for the socio-economic development of Ghana. The use of these beneficial radioactive materials has resulted in an inventory of Disused Sealed Radioactive Sources (DSRS) in storage. Most of the DSRS are legacy/historic sources which cannot be returned to their manufacturer or country of origin. Though small in volume, DSRS can be intensively radioactive and create a significant safety and security liability. They need to be managed in a safe and secure manner in accordance with the fundamental safety objective. The Radioactive Waste Management Center (RWMC) of the Ghana Atomic Energy Commission (GAEC) is currently storing a significant volume of DSRS. The initial activities of the DSRS range from 7.4E+5 Bq to 6.85E+14 Bq. If not managed properly, such DSRS can represent a potential hazard to human health and the environment. Storage is an important interim step, especially for DSRS containing very short-lived radionuclides, which can decay to exemption levels within a few years. Long-term storage, however, is considered an unsustainable option for DSRS with long half-lives hence the need for a disposal facility. The GAEC intends to use the International Atomic Energy Agency’s (IAEA’s) Borehole Disposal System (BDS) to provide a safe, secure, and cost-effective disposal option to dispose of its DSRS in storage. The proposed site for implementation of the BDS is on the GAEC premises at Kwabenya. The site has been characterized to gain a general understanding in terms of its regional setting, its past evolution and likely future natural evolution over the assessment time frame. Due to the long half-lives of some of the radionuclides to be disposed of (Ra-226 with half-life of 1600 years), the engineered barriers of the system must be robust to contain these radionuclides for this long period before they decay to harmless levels. There is the need to assess the safety related functions of the engineered barriers of this disposal system.

Keywords: radionuclides, disposal, radioactive waste, engineered barrier

Procedia PDF Downloads 65

Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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Introduction: The elderly population is growing rapidly, and with this growth comes an increased demand for healthcare services. Artificial intelligence (AI) has the potential to revolutionize the delivery of healthcare services to the elderly population. In this study, the various ways in which AI is used to create health content for elderly people and its transformative impact on the healthcare industry will be explored. Method: A systematic review of the literature was conducted to identify studies that have investigated the role of AI in creating health content specifically for elderly people. Several databases, including PubMed, Scopus, and Web of Science, were searched for relevant articles published between 2000 and 2022. The search strategy employed a combination of keywords related to AI, personalized health content, and the elderly. Studies that utilized AI to create health content for elderly individuals were included, while those that did not meet the inclusion criteria were excluded. A total of 20 articles that met the inclusion criteria were identified. Finding: The findings of this review highlight the diverse applications of AI in creating health content for elderly people. One significant application is the use of natural language processing (NLP), which involves the creation of chatbots and virtual assistants capable of providing personalized health information and advice to elderly patients. AI is also utilized in the field of medical imaging, where algorithms analyze medical images such as X-rays, CT scans, and MRIs to detect diseases and abnormalities. Additionally, AI enables the development of personalized health content for elderly patients by analyzing large amounts of patient data to identify patterns and trends that can inform healthcare providers in developing tailored treatment plans. Conclusion: AI is transforming the healthcare industry by providing a wide range of applications that can improve patient outcomes and reduce healthcare costs. From creating chatbots and virtual assistants to analyzing medical images and developing personalized treatment plans, AI is revolutionizing the way healthcare is delivered to elderly patients. Continued investment in this field is essential to ensure that elderly patients receive the best possible care.

Keywords: artificial intelligence, health content, older adult, healthcare

Procedia PDF Downloads 60

Authors: Siavash Ostovar

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The Iranian national Law on the Ramsar Convention (officially known as the Convention of International Wetlands and Aquatic Birds' Habitat Wetlands) was approved by the Senate and became a law in 1974 after the ratification of the National Council. There are other national laws with the aim of preservation of environment in the country. However, Lake Urmia which is declared a wetland of international importance by the Ramsar Convention in 1971 and designated a UNESCO Biosphere Reserve in 1976 is now at the brink of total disappearance due mainly to the climate change, water mismanagement, dam construction, and agricultural deficiencies. Lake Urmia is located in the north western corner of Iran. It is the third largest salt water lake in the world and the largest lake in the Middle East. Locally, it is designated as a National Park. It is, indeed, a unique lake both nationally and internationally. This study investigated how effective the national legal regulation of the ecosystem of Lake Urmia is in Iran. To do so, the Iranian national laws as Enforcement of Ramsar Convention in the country including three nationally established laws of (i) Five sets of laws for the programme of economic, social and cultural development of Islamic Republic of Iran, (ii) The Iranian Penal Code, (iii) law of conservation, restoration and management of the country were investigated. Using black letter law methods, it was revealed that (i) regarding the national five sets of laws; the benchmark to force the implementation of the legislations and policies is not set clearly. In other words, there is no clear guarantee to enforce these legislations and policies at the time of deviation and violation; (ii) regarding the Penal Code, there is lack of determining the environmental crimes, determining appropriate penalties for the environmental crimes, implementing those penalties appropriately, monitoring and training programmes precisely; (iii) regarding the law of conservation, restoration and management, implementation of this regulation is adjourned to preparation, announcement and approval of several categories of enactments and guidelines. In fact, this study used a national environmental catastrophe caused by drying up of Lake Urmia as an excuse to direct the attention to the weaknesses of the existing national rules and regulations. Finally, as we all depend on the natural world for our survival, this study recommended further research on every environmental issue including the Lake Urmia.

Keywords: conservation, environmental law, Lake Urmia, national laws, Ramsar Convention, water management, wetlands

Procedia PDF Downloads 195

Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

Procedia PDF Downloads 178

Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

Procedia PDF Downloads 108

Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

Procedia PDF Downloads 595

Authors: Kyoungrean Kim

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Importance of deep-sea mineral resources is dramatically increasing due to the depletion of land mineral resources corresponding to increasing human’s economic activities. Korea has acquired exclusive exploration licenses at four areas which are the Clarion-Clipperton Fracture Zone in the Pacific Ocean (2002), Tonga (2008), Fiji (2011) and Indian Ocean (2014). The preparation for commercial mining of Nautilus minerals (Canada) and Lockheed martin minerals (USA) is expected by 2020. The London Protocol 1996 (LP) under International Maritime Organization (IMO) and International Seabed Authority (ISA) will set environmental guidelines for deep-sea mining until 2020, to protect marine environment. In this research, the applicability of washing/extraction treatment for the remediation of deep-sea mining tailings was mainly evaluated in order to present preliminary data to develop practical remediation technology in near future. Polymetallic nodule samples were collected at the Clarion-Clipperton Fracture Zone in the Pacific Ocean, then stored at room temperature. Samples were pulverized by using jaw crusher and ball mill then, classified into 3 particle sizes (> 63 µm, 63-20 µm, < 20 µm) by using vibratory sieve shakers (Analysette 3 Pro, Fritsch, Germany) with 63 µm and 20 µm sieve. Only the particle size 63-20 µm was used as the samples for investigation considering the lower limit of ore dressing process which is tens to 100 µm. Rhamnolipid and sodium alginate as biosurfactant and aluminum sulfate which are mainly used as flocculant were used as environmentally friendly additives. Samples were adjusted to 2% liquid with deionized water then mixed with various concentrations of additives. The mixture was stirred with a magnetic bar during specific reaction times and then the liquid phase was separated by a centrifugal separator (Thermo Fisher Scientific, USA) under 4,000 rpm for 1 h. The separated liquid was filtered with a syringe and acrylic-based filter (0.45 µm). The extracted heavy metals in the filtered liquid were then determined using a UV-Vis spectrometer (DR-5000, Hach, USA) and a heat block (DBR 200, Hach, USA) followed by US EPA methods (8506, 8009, 10217 and 10220). Polymetallic nodule was mainly composed of manganese (27%), iron (8%), nickel (1.4%), cupper (1.3 %), cobalt (1.3%) and molybdenum (0.04%). Based on remediation standards of various countries, Nickel (Ni), Copper (Cu), Cadmium (Cd) and Zinc (Zn) were selected as primary target materials. Throughout this research, the use of rhamnolipid was shown to be an effective approach for removing heavy metals in samples originated from manganese nodules. Sodium alginate might also be one of the effective additives for the remediation of deep-sea mining tailings such as polymetallic nodules. Compare to the use of rhamnolipid and sodium alginate, aluminum sulfate was more effective additive at short reaction time within 4 h. Based on these results, sequencing particle separation, selective extraction/washing, advanced filtration of liquid phase, water treatment without dewatering and solidification/stabilization may be considered as candidate technologies for the remediation of deep-sea mining tailings.

Keywords: deep-sea mining tailings, heavy metals, remediation, extraction, additives

Procedia PDF Downloads 150

Authors: Andreas Schweiger, Matthias Gnigler, Elisabeth Wieder, Michael Grobbauer

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Especially in the alpine region, available areas for new residential development are limited. One possible solution is to exploit the potential of existing settlements. Urban redensification, especially the addition of floors to existing buildings, requires efficient, lightweight constructions with short construction times. This topic is being addressed in the five-year Alpine Building Centre. The focus of this cooperation between Salzburg University of Applied Sciences and RSA GH Studio iSPACE is on transdisciplinary research in the fields of building and energy technology, building envelopes and geoinformation, as well as the transfer of research results to industry. One development objective is a system of wood panel system construction with a high degree of prefabrication to optimize the construction quality, the construction time and the applicability for small and medium-sized enterprises. The system serves as a reliable working basis for mastering the complex building task of redensification. The technical solution is the development of an open system in timber frame and solid wood construction, which is suitable for a maximum two-story addition of residential buildings. The applicability of the system is mainly influenced by the existing building stock. Therefore, timber frame and solid timber construction are combined where necessary to bridge large spans of the existing structure while keeping the dead weight as low as possible. Escape routes are usually constructed in reinforced concrete and are located outside the system boundary. Thus, within the framework of the legal and normative requirements of timber construction, a hybrid construction method for redensification created. Component structure, load-bearing structure and detail constructions are developed in accordance with the relevant requirements. The results are directly applicable in individual cases, with the exception of the required verifications. In order to verify the practical suitability of the developed system, stakeholder workshops are held on the one hand, and the system is applied in the planning of a two-storey extension on the other hand. A company-independent construction standard offers the possibility of cooperation and bundling of capacities in order to be able to handle larger construction volumes in collaboration with several companies. Numerous further developments can take place on the basis of the system, which is under open license. The construction system will support planners and contractors from design to execution. In this context, open means publicly published and freely usable and modifiable for own use as long as the authorship and deviations are mentioned. The companies are provided with a system manual, which contains the system description and an application manual. This manual will facilitate the selection of the correct component cross-sections for the specific construction projects by means of all component and detail specifications. This presentation highlights the initial situation, the motivation, the approach, but especially the technical solution as well as the possibilities for the application. After an explanation of the objectives and working methods, the component and detail specifications are presented as work results and their application.

Keywords: redensification, SME, urban development, wood building system

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

Procedia PDF Downloads 293

Authors: Michael Picard

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This proposal offers to shed light on the changing legal geography of the global waste economy. Global waste recycling has become a multi-billion-dollar industry. NASDAQ predicts the emergence of a worldwide 1,296G$ waste management market between 2017 and 2022. Underlining this evolution, a new generation of preferential waste-trade agreements has emerged in the Pacific. In the last decade, Japan has concluded a series of bilateral treaties with Asian countries, and most recently with China. An agreement between Tokyo and Beijing was formalized on 7 May 2008, which forged an economic partnership on waste transfer and mining. The agreement set up International Recycling Zones, where certified recycling plants in China process industrial waste imported from Japan. Under the joint venture, Chinese companies salvage the embedded value from Japanese industrial discards, reprocess them and send them back to Japanese manufacturers, such as Mitsubishi and Panasonic. This circular economy is designed to convert surplus garbage into surplus value. Ever since the opening of Sino-Japanese eco-parks, millions of tons of plastic and e-waste have been exported from Japan to China every year. Yet, quite unexpectedly, China has recently closed its waste market to imports, jeopardizing Japan’s billion-dollar exports to China. China notified the WTO that, by the end of 2017, it would no longer accept imports of plastics and certain metals. Given China’s share of Japanese waste exports, a complete closure of China’s market would require Japan to find new uses for its recyclable industrial trash generated domestically every year. It remains to be seen how China will effectively implement its ban on waste imports, considering the economic interests at stake. At this stage, what remains to be clarified is whether China's ban on waste imports will negatively affect the recycling trade between Japan and China. What is clear, though, is the rapid transformation in the legal geography of waste mining in East-Asia. For decades, East-Asian waste trade had been tied up in an ‘ecologically unequal exchange’ between the Japanese core and the Chinese periphery. This global unequal waste distribution could be measured by the Environmental Stringency Index, which revealed that waste regulation was 39% weaker in the Global South than in Japan. This explains why Japan could legally export its hazardous plastic and electronic discards to China. The asymmetric flow of hazardous waste between Japan and China carried the colonial heritage of international law. The legal geography of waste distribution was closely associated to the imperial construction of an ecological trade imbalance between the Japanese source and the Chinese sink. Thus, China’s recent decision to ban hazardous waste imports is a sign of a broader ecological shift. As a global economic superpower, China announced to the world it would no longer be the planet’s junkyard. The policy change will have profound consequences on the global circulation of waste, re-routing global waste towards countries south of China, such as Vietnam and Malaysia. By the time the Berlin Conference takes place in May 2018, the presentation will be able to assess more accurately the effect of the Chinese ban on the transboundary movement of waste in Asia.

Keywords: Asia, ecological unequal exchange, global waste trade, legal geography

Procedia PDF Downloads 207

Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

Procedia PDF Downloads 441

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

Procedia PDF Downloads 34

Authors: Emily Moore, Andrew Gaukroger, Matthew Solan, Lucy Bailey, Alexandra Boxall, Andrew Carne, Chintu Gadamsetty, Charlotte Morley, Katy Western, Iwona Kolodziejczyk

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Introduction: Rupture of the Achilles tendon is common and has a long recovery period. Most cases are managed non-operatively. Foot and Ankle Surgeons advise an ultrasound scan to check the gap between the torn ends. A large gap (with the ankle in equinus) is a relative indication for surgery. The definitive decision regarding surgical versus non-operative management can only be made once an ultrasound scan is undertaken and the patient is subsequently reviewed by a Foot and Ankle surgeon. To get to this point, the patient journey involves several hospital departments. In nearby trusts, patients reattend for a scan and go to the plaster room both before and after the ultrasound for removal and re-application of the cast. At a third visit to the hospital, the surgeon and patient discuss options for definitive treatment. It may take 2-3 weeks from the initial Emergency Department visit before the final treatment decision is made. This “wasted time” is ultimately added to the recovery period for the patient. In this hospital, Achilles rupture patients are seen in a weekly multidisciplinary OneStop Heel Pain clinic. This pathway was already efficient but subject to occasional frustrating delays if a key staff member was absent. A new pathway was introduced with the goal to reduce delays to a definitive treatment plan. Method: A retrospective series of Achilles tendon ruptures managed according to the 2019 protocol was identified. Time taken from the Emergency Department to have both an ultrasound scan and specialist Foot and Ankle surgical review were calculated. 30 consecutive patients were treated with our new pathway and prospectively followed. The time taken for a scan and for specialist review were compared to the 30 consecutive cases from the 2019 (pre-COVID) cohort. The new pathway includes 1. A new contoured splint applied to the front of the injured limb held with a bandage. This can be removed and replaced (unlike a plaster cast) in the ultrasound department, removing the need for plaster room visits. 2. Urgent triage to a Foot and Ankle specialist. 3. Ultrasound scan for assessment of rupture gap and deep vein thrombosis check. 4. Early decision regarding surgery. Transfer to weight bearing in a prosthetic boot in equinuswithout waiting for the once-a-week clinic. 5. Extended oral VTE prophylaxis. Results: The time taken for a patient to have both an ultrasound scan and specialist review fell > 50%. All patients in the new pathway reached a definitive treatment decision within one week. There were no significant differences in patient demographics or rates of surgical vs non-operative treatment. The mean time from Emergency Department visit to specialist review and ultrasound scan fell from 8.7 days (old protocol) to 2.9 days (new pathway). The maximum time for this fell from 23 days (old protocol) to 6 days (new pathway). Conclusion: Teamwork and innovation have improved the experience for patients with an Achilles tendon rupture. The new pathway brings many advantages - reduced time in the Emergency Department, fewer hospital visits, less time using crutches and reduced overall recovery time.

Keywords: orthopaedics, achilles rupture, ultrasound, innovation

Procedia PDF Downloads 110

Authors: Simona Dostalova, Dita Munzova, Ana Maria Jimenez Jimenez, Marketa Vaculovicova, Vojtech Adam, Rene Kizek

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The boom of nanomedicine in recent years has led to the development of numerous new nanomaterials that can be used as nanocarriers in the drug delivery. These nanocarriers can either be synthetic or natural-based. The disadvantage of many synthetic nanocarriers is their toxicity in patient’s body. Protein cages that can naturally be found in human body do not exhibit such disadvantage. However, the release of cargo from some protein cages in target cells can be problematic. As a special type of protein cages can serve the capsid of many viruses, including phage. Phages infect bacterial cells; therefore they are not harmful to human cells. The targeting of phage particles to cancer cells can be solved by producing of empty phage capsids during which the targeting moieties (e.g. peptides) can be cloned into genes of phage capsid to decorate its surface. Moreover, the produced capsids do not contain viral nucleic acid and are therefore not infectious to beneficial bacteria in the patient’s body. The protein cage composed of viral capsid is larger than other frequently used apoferritin cage but its size is still small enough to benefit from passive targeting by Enhanced Permeability and Retention effect. In this work, bacteriophage λ was used, both whole and its empty capsid for delivery of different cytotoxic drugs (cisplatin, carboplatin, oxaliplatin, etoposide and doxorubicin). Large quantities of phage λ were obtained from phage λ-producing strain of E. coli cultivated in medium with 0.2 % maltose. After killing of E. coli with chloroform and its removal by centrifugation, the phage was concentrated by ultracentrifugation at 130 000 g and 4 °C for 3 h. The encapsulation of the drugs was performed by infusion method and four different concentrations of the drugs were encapsulated (200; 100; 50; 25 µg/ml). Free molecules of drugs were removed by dialysis. The encapsulation was verified using spectrophotometric and electrochemical methods. The amount of encapsulated drug linearly increased with the amount of applied drug (determination coefficient R2=0.8013). 76% of applied drug was encapsulated in phage λ particles (concentration of 10 µg/ml), even with the highest applied concentration of drugs, 200 µg/ml. Only 1% of encapsulated drug was detected in phage DNA. Similar results were obtained with encapsulation in phage empty capsid. Therefore, it can be concluded that the encapsulation of drugs into phage particles is efficient and mostly occurs by interaction of drugs with protein capsid.

Keywords: cytostatics, drug delivery, nanocarriers, phage capsid

Procedia PDF Downloads 488

Authors: Luís R. Silva, Ana C. Gonçalves, Catarina Bento, Fábio Jesus, Branca M. Silva

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Prunus avium Linnaeus, more known as sweet cherry, is one of the most appreciated fruit worldwide. Most of these quantities are produced in Fundão region, being Saco the cultivar most produced. Saco is very rich in bioactive compounds, especially phenolics, and presents great antioxidant capacity. The purpose of the present study was to investigate the chemical profile and biological potential, concerning antioxidant, anti-diabetic activity and protective effects towards erythrocytes by Saco sweet cherry collected from Fundão region (Portugal). The hydroethanolic extracts were prepared and passed through a C18 solid-phase extraction column. The phenolic profile analyzed by LC-DAD method allowed to the identification of 22 phenolic compounds, being 16 non-phenolics and 6 anthocyanins. In respect to non-coloured phenolics, 3-O-caffeoylquinic and ρ-coumaroylquinic acids were the main ones. Concerning to anthocyanins, cyanidin-3-O-rutinoside was found in higher amounts. Relatively to biological potential, Saco showed great antioxidant potential, through DPPH and NO radical assays, with IC50 =16.24 ± 0.46 µg/mL and IC50 = 176.69 ± 3.35 µg/mL for DPPH and NO, respectively. These results were similar to those obtained for ascorbic acid control (IC50 = 16.92 ± 0.69 and IC50 = 162.66 ± 1.31 μg/mL for DPPH and NO, respectively). In respect to antidiabetic potential, Saco revealed capacity to inhibit α-glucosidase in a dose-dependent manner (IC50 = 10.79 ± 0.40 µg/mL), being much active than positive control acarbose (IC50 = 306.66 ± 0.84 μg/mL). Additionally, Saco extracts revealed protective effects against ROO•-mediated toxicity generated by AAPH in human blood erythrocytes, inhibiting hemoglobin oxidation (IC50 = 38.57 ± 0.96 μg/mL) and hemolysis (IC50 = 73.03 ± 1.48 μg/mL), in a concentration-dependent manner. However, Saco extracts were less effective than quercetin control (IC50 = 3.10 μg/mL and IC50 = 0.7 μg/mL for inhibition of hemoglobin oxidation and hemolysis, respectively). The results obtained showed that Saco is an excellent source of phenolic compounds. These ones are natural antioxidant substances, which easily capture reactive species. This work presents new insights regarding sweet cherry antioxidant properties which may be useful for the future development of new therapeutic strategies for preventing or attenuating oxidative-related disorders.

Keywords: antioxidant capacity, health benefits, phenolic compounds, saco

Procedia PDF Downloads 311

Authors: Dhritilekha Deka, Deepak Patwa, Ravi K., Archana M. Nair

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Bioaccumulation of heavy metal contaminants due to intense anthropogenic interference degrades the environment and ecosystem functions. Conventional physicochemical methods involve energy-intensive and costly methodologies. Phytoremediation, on the other hand, provides an efficient nature-based strategy for the reclamation of heavy metal-contaminated sites. However, the slow process and adaptation to high-concentration contaminant sequestration often limit the efficiency of the method. This necessitates natural amendments such as biochar to improve phytoextraction and stabilize the green cover. Biochar is a highly porous structure with high carbon sequestration potential and containing negatively charged functional groups that provide binding sites for the positively charged metals. This study aims to develop and determine the synergy between sugarcane bagasse biochar content and phytoremediation. A 60-day pot experiment using perennial tussock vetiver grass (Chrysopogon zizanioides) was conducted for different biochar contents of 1%, 2%, and 4% for the removal of cadmium and zinc. A concentration of 500 ppm is maintained for the amended and unamended control (CK) samples. The survival rates of the plants, biomass production, and leaf area index were measured for the plant growth characteristics. Results indicate a visible change in the plant growth and the heavy metal concentration with the biochar content. The bioconcentration factor (BCF) in the plant improved significantly for the 4% biochar content by 57% in comparison to the control CK treatment in Cd-treated soils. The Zn soils indicated the highest reduction in the metal concentration by 50% in the 2% amended samples and an increase in the BCF in all the amended samples. The translocation from the rhizosphere to the shoots was low but not dependent on the amendment content and varied for each contaminant type. The root-to-shoot ratio indicates higher values compared to the control samples. The enhanced tolerance capacities can be attributed to the nutrients released by the biochar in the soil. The study reveals the high potential of biochar as a phytoremediation amendment, but its effect is dependent on the soil and heavy metal and accumulator species.

Keywords: phytoextraction, biochar, heavy metals, chrysopogon zizanioides, bioaccumulation factor

Procedia PDF Downloads 60

Authors: Milica Carević, Katarina Banjanac, Marija ĆOrović, Ana Milivojević, Nevena Prlainović, Aleksandar Marinković, Dejan Bezbradica

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Nowadays, considering the growing awareness of functional food beneficial effects on human health, due attention is dedicated to the research in the field of obtaining new prominent products exhibiting improved physiological and physicochemical characteristics. Therefore, different approaches to valuable bioactive compounds synthesis have been proposed. β-Galactosidase, for example, although mainly utilized as hydrolytic enzyme, proved to be a promising tool for these purposes. Namely, under the particular conditions, such as high lactose concentration, elevated temperatures and low water activities, reaction of galactose moiety transfer to free hydroxyl group of the alternative acceptor (e.g. different sugars, alcohols or aromatic compounds) can generate a wide range of potentially interesting products. Up to now, galacto-oligosaccharides and lactulose have attracted the most attention due to their inherent prebiotic properties. The goal of this study was to obtain a novel product sorbitol galactoside, using the similar reaction mechanism, namely transgalactosylation reaction catalyzed by β-galactosidase from Aspergillus oryzae. By using sugar alcohol (sorbitol) as alternative acceptor, a diverse mixture of potential prebiotics is produced, enabling its more favorable functional features. Nevertheless, an introduction of alternative acceptor into the reaction mixture contributed to the complexity of reaction scheme, since several potential reaction pathways were introduced. Therefore, the thorough optimization using response surface method (RSM), in order to get an insight into different parameter (lactose concentration, sorbitol to lactose molar ratio, enzyme concentration, NaCl concentration and reaction time) influences, as well as their mutual interactions on product yield and productivity, was performed. In view of product yield maximization, the obtained model predicted optimal lactose concentration 500 mM, the molar ratio of sobitol to lactose 9, enzyme concentration 0.76 mg/ml, concentration of NaCl 0.8M, and the reaction time 7h. From the aspect of productivity, the optimum substrate molar ratio was found to be 1, while the values for other factors coincide. In order to additionally, improve enzyme efficiency and enable its reuse and potential continual application, immobilization of β-galactosidase onto tailored silica nanoparticles was performed. These non-porous fumed silica nanoparticles (FNS)were chosen on the basis of their biocompatibility and non-toxicity, as well as their advantageous mechanical and hydrodinamical properties. However, in order to achieve better compatibility between enzymes and the carrier, modifications of the silica surface using amino functional organosilane (3-aminopropyltrimethoxysilane, APTMS) were made. Obtained support with amino functional groups (AFNS) enabled high enzyme loadings and, more importantly, extremely high expressed activities, approximately 230 mg proteins/g and 2100 IU/g, respectively. Moreover, this immobilized preparation showed high affinity towards sorbitol galactoside synthesis. Therefore, the findings of this study could provided a valuable contribution to the efficient production of physiologically active galactosides in immobilized enzyme reactors.

Keywords: β-galactosidase, immobilization, silica nanoparticles, transgalactosylation

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Authors: Diana Puigserver Cuerda, Jofre Herrero Ferran, José M. Carmona Perez

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In the transition zone between aquifers and basal aquitards, DNAPL-pools of chlorinated solvents are more recalcitrant than at other depths in the aquifer. Although degradation of carbon tetrachloride (CT) and chloroform (CF) occurs in this zone, this is a slow process, which is why an adequate remediation strategy is necessary. The working hypothesis of this study is that the biostimulation of the transition zone of an aquifer contaminated by CT and CF can be an effective remediation strategy. This hypothesis has been tested in a site on an unconfined aquifer in which the major contaminants were CT and CF of industrial origin and where the hydrochemical background was rich in other compounds that can hinder natural attenuation of chloromethanes. Field studies and five laboratory microcosm experiments were carried out at the level of groundwater and sediments to identify: i) the degradation processes of CT and CF; ii) the structure of microbial communities; and iii) the microorganisms implicated on this degradation. For this, concentration of contaminants and co-contaminants (nitrate and sulfate), Compound Specific Isotope Analysis, molecular techniques (Denaturing Gradient Gel Electrophoresis) and clone library analysis were used. The main results were: i) degradation processes of CT and CF occurred in groundwater and in the lesser conductive sediments; ii) sulfate-reducing conditions in the transition zone were high and similar to those in the source of contamination; iii) two microorganisms (Azospira suillum and a bacterium of the Clostridiales order) were identified in the transition zone at the field and lab experiments that were compatible with the role of carrying out the reductive dechlorination of CT, CF and their degradation products (dichloromethane and chloromethane); iv) these two microorganisms were present at the high starting concentrations of the microcosm experiments (similar to those in the source of DNAPL) and continued being present until the last day of the lactate biostimulation; and v) the lactate biostimulation gave rise to the fastest and highest degradation rates and promoted the elimination of other electron acceptors (e.g. nitrate and sulfate). All these results are evidence that lactate biostimulation can be effective in remediating the source and plume, especially in the transition zone, and highlight the environmental relevance of the treatment of contaminated transition zones in industrial contexts similar to that studied.

Keywords: Azospira suillum, lactate biostimulation of carbon tetrachloride and chloroform, reductive dechlorination, transition zone between aquifer and aquitard

Procedia PDF Downloads 169

Authors: Purva Khurana

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Traditional textile crafts are universally found to have been significantly impeded by the uprise of innovative technologies, but sustained human endeavor, in sync with dynamic market nuances, holds key to these otherwise getting fast-extinct marvels. The metamorphosis of such art-forms into niche markets pre-supposes sharp concentration on adaptability. The author has concentrated on the ancient handicraft of Ikat in Andhra Pradesh (India), a manifestation of their cultural heritage and esoteric cottage industry, so very intrinsic to the development and support of local economy and identity. Like any other traditional practice, ikat weaving has been subjected to the challenges of modernization. However, owing to its unique character, personalize production and adaptability, both of material and process, ikat weaving has stood the test of time by way of judiciously embellishing innovation with contemporary taste. To survive as a living craft as also to justify its role as a universal language of aesthetic sensibility, it is imperative that ikat tradition should lend itself continuous process of experiments, change and growth. Besides, the instant paper aims to examine the contours of ikat production process from its pure form, to more fashion and market oriented production, with upgraded process, material and tools. Over the time, it has adapted well to new style-paradigms, duly matching up with the latest fashion trends, in tandem with the market-sensitivities. Apart, it is an effort to investigate how this craft could respond constructively to the pressure of contemporary technical developments in order to be at cutting edge, while preserving its integrity. In order to approach these issues, the methodology adopted is, conceptual analysis of the craft practices, its unique strength and how they could be used to advance the craft in relation to the emergence of technical developments. The paper summarizes the result of the study carried out by the author on the peculiar advantages of suitably- calibrated vat dyes over natural dyes, in terms of its recycling ability and eco-friendly properties, thus holding definite edge, both in terms of socio-economic as well as environmental concerns.

Keywords: craft, eco-friendly dyes, ikat, metamorphosis

Procedia PDF Downloads 167

Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

Procedia PDF Downloads 72

Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

Abstract:

Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

Abstract:

E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

Procedia PDF Downloads 67