Search results for: artificial magnetic conduction

Authors: Shoury Gupta

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Chatbots are a rapidly growing technological trend that has revolutionized the way businesses interact with their customers. With the advancements in artificial intelligence, chatbots can now mimic human-like conversations and provide instant and efficient responses to customer inquiries. In this research paper, we aim to explore the implications of chatbots on the future of globalization for both businesses and consumers. The paper begins by providing an overview of the current state of chatbots in the global market and their growth potential in the future. The focus is on how chatbots have become a valuable tool for businesses looking to expand their global reach, especially in areas with high population density and language barriers. With chatbots, businesses can engage with customers in different languages and provide 24/7 customer service support, creating a more accessible and convenient customer experience. The paper then examines the impact of chatbots on cross-cultural communication and how they can help bridge communication gaps between businesses and consumers from different cultural backgrounds. Chatbots can potentially facilitate cross-cultural communication by offering real-time translations, voice recognition, and other innovative features that can help users communicate effectively across different languages and cultures. By providing more accessible and inclusive communication channels, chatbots can help businesses reach new markets and expand their customer base, making them more competitive in the global market. However, the paper also acknowledges that there are potential drawbacks associated with chatbots. For instance, chatbots may not be able to address complex customer inquiries that require human input. Additionally, chatbots may perpetuate biases if they are programmed with certain stereotypes or assumptions about different cultures. These drawbacks may have significant implications for businesses and consumers alike. To explore the implications of chatbots on the future of globalization in greater detail, the paper provides a thorough review of existing literature and case studies. The review covers topics such as the benefits of chatbots for businesses and consumers, the potential drawbacks of chatbots, and how businesses can mitigate any risks associated with chatbot use. The paper also discusses the ethical considerations associated with chatbot use, such as privacy concerns and the need to ensure that chatbots do not discriminate against certain groups of people. The ethical implications of chatbots are particularly important given the potential for chatbots to be used in sensitive areas such as healthcare and financial services. Overall, this research paper provides a comprehensive analysis of chatbots and their implications for the future of globalization. By exploring both the potential benefits and drawbacks of chatbot use, the paper aims to provide insights into how businesses and consumers can leverage this technology to achieve greater global reach and improve cross-cultural communication. Ultimately, the paper concludes that chatbots have the potential to be a powerful tool for businesses looking to expand their global footprint and improve their customer experience, but that care must be taken to mitigate any risks associated with their use.

Keywords: chatbots, conversational AI, globalization, businesses

Procedia PDF Downloads 66

Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

Procedia PDF Downloads 297

Authors: Filomena Lopes, Miguel Magalhaes, Carla Santos Pereira, Natercia Durao, Cristina Costa-Lobo

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The option to implement curricular internships with undergraduate students is a pedagogical option with some good results perceived by academic staff, employers, and among graduates in general and IT (Information Technology) in particular. Knowing that this type of exercise has never been so relevant, as one tries to give meaning to the future in a landscape of rapid and deep changes. We have as an example the potential disruptive impact on the jobs of advances in robotics, artificial intelligence and 3-D printing, which is a focus of fierce debate. It is in this context that more and more students and employers engage in the pursuit of career-promoting responses and business development, making their investment decisions of training and hiring. Three decades of experience and research in computer science degree and in information systems technologies degree at the Portucalense University, Portuguese private university, has provided strong evidence of its advantages. The Human Interaction Skills development as well as the attractiveness of such experiences for students are topics assumed as core in the Ccnception and management of the activities implemented in these study cycles. The objective of this paper is to gather evidence of the Human Interaction Skills explained and valued within the curriculum internship experiences of IT students employability. Data collection was based on the application of questionnaire to intern counselors and to students who have completed internships in these undergraduate courses in the last decade. The trainee supervisor, responsible for monitoring the performance of IT students in the evolution of traineeship activities, evaluates the following Human Interaction Skills: Motivation and interest in the activities developed, interpersonal relationship, cooperation in company activities, assiduity, ease of knowledge apprehension, Compliance with norms, insertion in the work environment, productivity, initiative, ability to take responsibility, creativity in proposing solutions, and self-confidence. The results show that these undergraduate courses promote the development of Human Interaction Skills and that these students, once they finish their degree, are able to initiate remunerated work functions, mainly by invitation of the institutions in which they perform curricular internships. Findings obtained from the present study contribute to widen the analysis of its effectiveness in terms of future research and actions in regard to the transition from Higher Education pathways to the Labour Market.

Keywords: human interaction skills, employability, internships, information technology, higher education

Procedia PDF Downloads 263

Authors: Philip Semaha, Zhongfang Lei, Ziwen Zhao, Sen Liu, Zhenya Zhang, Kazuya Shimizu

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The increasing generation of saline wastewater through various industrial activities is becoming a global concern for activated sludge (AS) based biological treatment which is widely applied in wastewater treatment plants (WWTPs). As for the AS process, an increase in wastewater salinity has negative impact on its overall performance. The advent of conventional aerobic granular sludge (AGS) or bacterial AGS biotechnology has gained much attention because of its superior performance. The development of algal-bacterial AGS could enhance better nutrients removal, potentially reduce aeration cost through symbiotic algae-bacterial activity, and thus, can also reduce overall treatment cost. Nonetheless, the potential of salt stress to decrease biomass growth, microbial activity and nutrient removal exist. Up to the present, little information is available on saline wastewater treatment by algal-bacterial AGS. To the authors’ best knowledge, a comparison of the two AGS systems has not been done to evaluate nutrients removal capacity in the context of salinity increase. This study sought to figure out the impact of salinity on the algal-bacterial AGS system in comparison to bacterial AGS one, contributing to the application of AGS technology in the real world of saline wastewater treatment. In this study, the salt concentrations tested were 0 g/L, 1 g/L, 5 g/L, 10 g/L and 15 g/L of NaCl with 24-hr artificial illuminance of approximately 97.2 µmol m¯²s¯¹, and mature bacterial and algal-bacterial AGS were used for the operation of two identical sequencing batch reactors (SBRs) with a working volume of 0.9 L each, respectively. The results showed that salinity increase caused no apparent change in the color of bacterial AGS; while for algal-bacterial AGS, its color was progressively changed from green to dark green. A consequent increase in granule diameter and fluffiness was observed in the bacterial AGS reactor with the increase of salinity in comparison to a decrease in algal-bacterial AGS diameter. However, nitrite accumulation peaked from 1.0 mg/L and 0.4 mg/L at 1 g/L NaCl in the bacterial and algal-bacterial AGS systems, respectively to 9.8 mg/L in both systems when NaCl concentration varied from 5 g/L to 15 g/L. Almost no ammonia nitrogen was detected in the effluent except at 10 g/L NaCl concentration, where it averaged 4.2 mg/L and 2.4 mg/L, respectively, in the bacterial and algal-bacterial AGS systems. Nutrients removal in the algal-bacterial system was relatively higher than the bacterial AGS in terms of nitrogen and phosphorus removals. Nonetheless, the nutrient removal rate was almost 50% or lower. Results show that algal-bacterial AGS is more adaptable to salinity increase and could be more suitable for saline wastewater treatment. Optimization of operation conditions for algal-bacterial AGS system would be important to ensure its stably high efficiency in practice.

Keywords: algal-bacterial aerobic granular sludge, bacterial aerobic granular sludge, Nutrients removal, saline wastewater, sequencing batch reactor

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Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: N. Reza Pour, S. Chuah, T. Vo

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Background: Vertebral artery dissection (VAD) is a rare complication of pregnancy. It can occur spontaneously or following a traumatic event. The pathogenesis is unclear. Predisposing factors include chronic hypertension, Marfan’s syndrome, fibromuscular dysplasia, vasculitis and cystic medial necrosis. Physiological changes of pregnancy have also been proposed as potential mechanisms of injury to the vessel wall. The clinical presentation varies and it can present as a headache, neck pain, diplopia, transient ischaemic attack, or an ischemic stroke. Isolated cases of VAD in pregnancy and puerperium have been reported in the literature. One case was found to have posterior circulation stroke as a result of bilateral VAD and labour was induced at 37 weeks gestation for preeclampsia. Another patient at 38 weeks with severe neck pain that persisted after induction for elevated blood pressure and arteriography showed right VAD postpartum. A single case of lethal VAD in pregnancy with subsequent massive subarachnoid haemorrhage has been reported which was confirmed by the autopsy. Case Presentation: We report two cases of vertebral artery dissection in pregnancy. The first patient was a 32-year-old primigravida presented at the 38th week of pregnancy with the onset of early labour and blood pressure (BP) of 130/70 on arrival. After 2 hours, the patient developed a severe headache with blurry vision and BP was 238/120. Despite treatment with an intravenous antihypertensive, she had eclamptic fit. Magnesium solfate was started and Emergency Caesarean Section was performed under the general anaesthesia. On the second day after the operation, she developed left-sided neck pain. Magnetic Resonance Imaging (MRI) angiography confirmed a short segment left vertebral artery dissection at the level of C3. The patient was treated with aspirin and remained stable without any neurological deficit. The second patient was a 33-year-old primigavida who was admitted to the hospital at 36 weeks gestation with BP of 155/105, constant headache and visual disturbances. She was medicated with an oral antihypertensive agent. On day 4, she complained of right-sided neck pain. MRI angiogram revealed a short segment dissection of the right vertebral artery at the C2-3 level. Pregnancy was terminated on the same day with emergency Caesarean Section and anticoagulation was started subsequently. Post-operative recovery was complicated by rectus sheath haematoma requiring evacuation. She was discharged home on Aspirin without any neurological sequelae. Conclusion: Because of collateral circulation, unilateral vertebral artery dissections may go unrecognized and may be more common than suspected. The outcome for most patients is benign, reflecting the adequacy of the collateral circulation in young patients. Spontaneous VAD is usually treated with anticoagulation or antiplatelet therapy for a minimum of 3-6 months to prevent future ischaemic events, allowing the dissection to heal on its own. We had two cases of VAD in the context of hypertensive disorders of pregnancy with an acceptable outcome. A high level of vigilance is required particularly with preeclamptic patients presenting with head/neck pain to allow an early diagnosis. This is as we hypothesize, early and aggressive management of vertebral artery dissection may potentially prevent further complications.

Keywords: eclampsia, preeclampsia, pregnancy, Vertebral Artery Dissection

Procedia PDF Downloads 252

Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

Procedia PDF Downloads 314

Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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Authors: Yury S. Shpanskiy, Boris V. Kuteev

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Development of a fusion-fission hybrid facility based on superconducting conventional tokamak DEMO-FNS runs in Russia since 2013. The main design goal is to reach the technical feasibility and outline prospects of industrial hybrid technologies providing the production of neutrons, fuel nuclides, tritium, high-temperature heat, electricity and subcritical transmutation in Fusion-Fission Hybrid Systems. The facility should operate in a steady-state mode at the fusion power of 40 MW and fission reactions of 400 MW. Major tokamak parameters are the following: major radius R=3.2 m, minor radius a=1.0 m, elongation 2.1, triangularity 0.5. The design provides the neutron wall loading of ~0.2 MW/m², the lifetime neutron fluence of ~2 MWa/m², with the surface area of the active cores and tritium breeding blanket ~100 m². Core plasma modelling showed that the neutron yield ~10¹⁹ n/s is maximal if the tritium/deuterium density ratio is 1.5-2.3. The design of the electromagnetic system (EMS) defined its basic parameters, accounting for the coils strength and stability, and identified the most problematic nodes in the toroidal field coils and the central solenoid. The EMS generates toroidal, poloidal and correcting magnetic fields necessary for the plasma shaping and confinement inside the vacuum vessel. EMC consists of eighteen superconducting toroidal field coils, eight poloidal field coils, five sections of a central solenoid, correction coils, in-vessel coils for vertical plasma control. Supporting structures, the thermal shield, and the cryostat maintain its operation. EMS operates with the pulse duration of up to 5000 hours at the plasma current up to 5 MA. The vacuum vessel (VV) is an all-welded two-layer toroidal shell placed inside the EMS. The free space between the vessel shells is filled with water and boron steel plates, which form the neutron protection of the EMS. The VV-volume is 265 m³, its mass with manifolds is 1800 tons. The nuclear blanket of DEMO-FNS facility was designed to provide functions of minor actinides transmutation, tritium production and enrichment of spent nuclear fuel. The vertical overloading of the subcritical active cores with MA was chosen as prospective. Analysis of the device neutronics and the hybrid blanket thermal-hydraulic characteristics has been performed for the system with functions covering transmutation of minor actinides, production of tritium and enrichment of spent nuclear fuel. A study of FNS facilities role in the Russian closed nuclear fuel cycle was performed. It showed that during ~100 years of operation three FNS facilities with fission power of 3 GW controlled by fusion neutron source with power of 40 MW can burn 98 tons of minor actinides and 198 tons of Pu-239 can be produced for startup loading of 20 fast reactors. Instead of Pu-239, up to 25 kg of tritium per year may be produced for startup of fusion reactors using blocks with lithium orthosilicate instead of fissile breeder blankets.

Keywords: fusion-fission hybrid system, conventional tokamak, superconducting electromagnetic system, two-layer vacuum vessel, subcritical active cores, nuclear fuel cycle

Procedia PDF Downloads 125

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

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The contamination of food by microbial agents is a common problem in the industry, especially regarding the elaboration of animal source products. Incorrect manipulation of the machinery or on the raw materials can cause a decrease in production or an epidemiological outbreak due to intoxication. In order to improve food product quality, different methods have been used to reduce or, at least, to slow down the growth of the pathogens, especially deteriorated, infectious or toxigenic bacteria. These methods are usually carried out under low temperatures and short processing time (abiotic agents), along with the application of antibacterial substances, such as bacteriocins (biotic agents). This, in a controlled and efficient way that fulfills the purpose of bacterial control without damaging the final product. Therefore, the objective of the present study is to design a secondary mathematical model that allows the prediction of both the biotic and abiotic factor impact associated with animal source food processing. In order to accomplish this objective, the authors propose a three-dimensional differential equation model, whose components are: bacterial growth, release, production and artificial incorporation of bacteriocins and changes in pH levels of the medium. These three dimensions are constantly being influenced by the temperature of the medium. Secondly, this model adapts to an idealized situation of cross-contamination animal source food processing, with the study agents being both the animal product and the contact surface. Thirdly, the stochastic simulations and the parametric sensibility analysis are compared with referential data. The main results obtained from the analysis and simulations of the mathematical model were to discover that, although bacterial growth can be stopped in lower temperatures, even lower ones are needed to eradicate it. However, this can be not only expensive, but counterproductive as well in terms of the quality of the raw materials and, on the other hand, higher temperatures accelerate bacterial growth. In other aspects, the use and efficiency of bacteriocins are an effective alternative in the short and medium terms. Moreover, an indicator of bacterial growth is a low-level pH, since lots of deteriorating bacteria are lactic acids. Lastly, the processing times are a secondary agent of concern when the rest of the aforementioned agents are under control. Our main conclusion is that when acclimating a mathematical model within the context of the industrial process, it can generate new tools that predict bacterial contamination, the impact of bacterial inhibition, and processing method times. In addition, the mathematical modeling proposed logistic input of broad application, which can be replicated on non-meat food products, other pathogens or even on contamination by crossed contact of allergen foods.

Keywords: bacteriocins, cross-contamination, mathematical model, temperature

Procedia PDF Downloads 119

Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Deisy Becerra, Edwar Perez, Nicolas Rios, Miguel Asuaje

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Progressing Cavity Pump (PCP) is a type of positive displacement pump that is being awarded greater importance as capable artificial lift equipment in the heavy oil field. The most commonly PCP used is driven single lobe pump that consists of a single external helical rotor turning eccentrically inside a double internal helical stator. This type of pump was analyzed by the experimental and Computational Fluid Dynamic (CFD) approach from the DCAB031 model located in a closed-loop arrangement. Experimental measurements were taken to determine the pressure rise and flow rate with a flow control valve installed at the outlet of the pump. The flowrate handled was measured by a FLOMEC-OM025 oval gear flowmeter. For each flowrate considered, the pump’s rotational speed and power input were controlled using an Invertek Optidrive E3 frequency driver. Once a steady-state operation was attained, pressure rise measurements were taken with a Sper Scientific wide range digital pressure meter. In this study, water and three Newtonian oils of different viscosities were tested at different rotational speeds. The CFD model implementation was developed on Star- CCM+ using an Overset Mesh that includes the relative motion between rotor and stator, which is one of the main contributions of the present work. The simulations are capable of providing detailed information about the pressure and velocity fields inside the device in laminar and unsteady regimens. The simulations have a good agreement with the experimental data due to Mean Squared Error (MSE) in under 21%, and the Grid Convergence Index (GCI) was calculated for the validation of the mesh, obtaining a value of 2.5%. In this case, three different rotational speeds were evaluated (200, 300, 400 rpm), and it is possible to show a directly proportional relationship between the rotational speed of the rotor and the flow rate calculated. The maximum production rates for the different speeds for water were 3.8 GPM, 4.3 GPM, and 6.1 GPM; also, for the oil tested were 1.8 GPM, 2.5 GPM, 3.8 GPM, respectively. Likewise, an inversely proportional relationship between the viscosity of the fluid and pump performance was observed, since the viscous oils showed the lowest pressure increase and the lowest volumetric flow pumped, with a degradation around of 30% of the pressure rise, between performance curves. Finally, the Productivity Index (PI) remained approximately constant for the different speeds evaluated; however, between fluids exist a diminution due to the viscosity.

Keywords: computational fluid dynamic, CFD, Newtonian fluids, overset mesh, PCP pressure rise

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Authors: Dagmara Malina, Katarzyna Bialik-Wąs, Klaudia Pluta

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The growing significance of transdermal systems, in which skin is a route for systemic drug delivery, has generated a considerable amount of data which has resulted in a deeper understanding of the mechanisms of transport across the skin in the context of the controlled and prolonged release of active substances. One of such solutions may be the use of carrier systems based on intelligent polymers with different physicochemical properties. In these systems, active substances, e.g. drugs, can be conjugated (attached), immobilized, or encapsulated in a polymer matrix that is sensitive to specific environmental conditions (e.g. pH or temperature changes). Intelligent polymers can be divided according to their sensitivity to specific environmental stimuli such as temperature, pH, light, electric, magnetic, sound, or electromagnetic fields. Materials & methods—The first stage of the presented research concerned the synthesis of pH-sensitive polymeric carriers by a radical polymerization reaction. Then, the selected active substance (hydrocortisone) was introduced into polymeric carriers. In a further stage, bio-hybrid sodium alginate/poly(vinyl alcohol) – SA/PVA-based hydrogel matrices modified with various carrier-drug systems were prepared with the chemical cross-linking method. The conducted research included the assessment of physicochemical properties of obtained materials i.e. degree of hydrogel swelling and degradation studies as a function of pH in distilled water and phosphate-buffered saline (PBS) at 37°C in time. The gel fraction represents the insoluble gel fraction as a result of inter-molecule cross-linking formation was also measured. Additionally, the chemical structure of obtained hydrogels was confirmed using FT-IR spectroscopic technique. The dynamic light scattering (DLS) technique was used for the analysis of the average particle size of polymer-carriers and carrier-drug systems. The nanocarriers morphology was observed using SEM microscopy. Results & Discussion—The analysis of the encapsulated polymeric carriers showed that it was possible to obtain the time-stable empty pH-sensitive carrier with an average size 479 nm and the encapsulated system containing hydrocortisone with an average 543 nm, which was introduced into hydrogel structure. Bio-hybrid hydrogel matrices are stable materials, and the presence of an additional component: pH-sensitive carrier – hydrocortisone system, does not reduce the degree of cross-linking of the matrix nor its swelling ability. Moreover, the results of swelling tests indicate that systems containing higher concentrations of the drug have a slightly higher sorption capacity in each of the media used. All analyzed materials show stable and statically changing swelling values in simulated body fluids - there is no sudden fluid uptake and no rapid release from the material. The analysis of FT-IR spectra confirms the chemical structure of the obtained bio-hybrid hydrogel matrices. In the case of modifications with a pH-sensitive carrier, a much more intense band can be observed in the 3200-3500 cm⁻¹ range, which most likely originates from the strong hydrogen interactions that occur between individual components.

Keywords: hydrogels, polymer nanocarriers, sodium alginate/poly(vinyl alcohol) matrices, wound dressings.

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

Procedia PDF Downloads 126

Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

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Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

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The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

Procedia PDF Downloads 141

Authors: Henda Gnakate Biba, Ndassa Mouafon Issa

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Dictionaries modeled on the Western model [tonic accent languages] are not suitable and do not account for tonal languages phonologically, which is why the [prosodic and phonological] ethnographic dictionary was designed. It is a glossary that expresses the tones and the rhythm of words. It recreates exactly the speaking or singing of a tonal language, and allows the non-speaker of this language to pronounce the words as if they were a native. It is a dictionary adapted to tonal languages. It was built from ethnomusicological theorems and phonological processes, according to Jean. J. Rousseau 1776 hypothesis /To say and to sing were once the same thing/. Each word in the French dictionary finds its corresponding language, ekaη. And each word ekaη is written on a musical staff. This ethnographic dictionary is also an inventive, original and innovative research thesis, but it is also an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and, world music or, variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, language, entenglement, science, research

Procedia PDF Downloads 38

Authors: Anita Conti, Riccardo Ossanna, Lindsey A. Quintero, Giamaica Conti, Andrea Sbarbati

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Ischemia/reperfusion (IR) injury induces muscle fiber atrophy and skeletal muscle fiber death with subsequently functionality loss. The heterogeneous pool of cells, especially mesenchymal stem cells, contained in the stromal vascular fraction (SVF) of adipose tissue could promote muscle fiber regeneration. To prevent SVF dispersion, it has been proposed the use of injectable biopolymers that work as cells carrier. A significant element of the extracellular matrix is hyaluronic acid (HA), which has been widely used in regenerative medicine as a cell scaffold given its biocompatibility, degradability, and the possibility of chemical functionalization. Connective tissue micro-fragments enriched with SVF obtained from mechanical disaggregation of adipose tissue were evaluated for IR muscle injury regeneration using low molecular weight HA as a scaffold. IR induction. Hindlimb ischemia was induced in 9 athymic nude mice through the clamping of the right quadriceps using a plastic band. Reperfusion was induced by cutting the plastic band after 3 hours of ischemic period. Contralateral (left) muscular tissue was used as healthy control. Treatment. Twenty-four hours after the IR induction, animals (n=3) were intramuscularly injected with 100 µl of SVF mixed with HA (SVF-HA). Animals treated with 100 µl of HA (n=3) and 100 µl saline solution (n=3) were used as control. Treatment monitoring. All animals were in vivo monitored by magnetic resonance imaging (MRI) at 5, 7, 14 and 18 days post-injury (dpi). High-resolution morphological T2 weighed, quantitative T2 map and Dynamic Contrast-Enhanced (DCE) images were acquired in order to assess the regenerative potential of SVF-HA treatment. Ex vivo evaluation. After 18 days from IR induction, animals were sacrificed, and the muscles were harvested for histological examination. At 5 dpi T2 high-resolution MR images clearly reveal the presence of an extensive edematous area due to IR damage for all groups identifiable as an increase of signal intensity (SI) of muscular and surrounding tissue. At 7 dpi, animals of the SVF-HA group showed a reduction of SI, and the T2relaxation time of muscle tissue of the HA-SVF group was 29±0.5ms, comparable with the T2relaxation time of contralateral muscular tissue (30±0.7ms). These suggest a reduction of edematous overflow and swelling. The T2relaxation time at 7dpi of HA and saline groups were 84±2ms and 90±5ms, respectively, which remained elevated during the rest of the study. The evaluation of vascular regeneration showed similar results. Indeed, DCE-MRI analysis revealed a complete recovery of muscular tissue perfusion after 14 dpi for the SVF-HA group, while for the saline and HA group, controls remained in a damaged state. Finally, the histological examination of SVF-HA treated animals exhibited well-defined and organized fibers morphology with a lateralized nucleus, similar to contralateral healthy muscular tissue. On the contrary, HA and saline-treated animals presented inflammatory infiltrates, with HA slightly improving the diameter of the fibers and less degenerated tissue. Our findings show that connective tissue micro-fragments enriched with SVF induce higher muscle homeostasis and perfusion restoration in contrast to control groups.

Keywords: ischemia/reperfusion injury, regenerative medicine, resonance imaging, stromal vascular fraction

Procedia PDF Downloads 89

Authors: Zeyu Zhou, Ziyu Zhao, Xiaochen Yang, Ling AI, Heng Zhai, Stuart Holmes

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As a promising sustainable alternative to traditional fossil fuels, fuel cell technology is highly favoured due to its enhanced working efficiency and reduced emissions. In the context of high-temperature fuel cells (operating above 100 °C), the most commonly used proton exchange membrane (PEM) is the Polybenzimidazole (PBI) doped phosphoric acid (PA) membrane. Grafting is a promising strategy to advance PA-doped PBI PEM technology. The existing grafting modification on PBI PEMs mainly focuses on grafting phosphate-containing or alkaline groups onto the PBI molecular chains. However, quaternary ammonium-based grafting approaches face a common challenge. To initiate the N-alkylation reaction, deacidifying agents such as NaH, NaOH, KOH, K2CO3, etc., can lead to ionic crosslinking between the quaternary ammonium group and PBI. Polyvinylpyrrolidone (PVP) is another widely used polymer, the N-heterocycle groups within PVP endow it with a significant ability to absorb PA. Recently, PVP has attracted substantial attention in the field of fuel cells due to its reduced environmental impact and impressive fuel cell performance. However, due to the the poor compatibility of PVP in PBI, few research apply PVP in PA-doped PBI PEMs. This work introduces an innovative strategy to graft PVP onto PBI to form a network-like polymer. Due to the absence of quaternary ammonium groups, PVP does not pose issues related to crosslinking with PBI. Moreover, the nitrogen-containing functional groups on PVP provide PBI with a robust phosphoric acid retention ability. The nuclear magnetic resonance (NMR) hydrogen spectrum analysis results indicate the successful completion of the grafting reaction where N-alkylation reactions happen on both sides of the grafting agent 1,4-bis(chloromethyl)benzene. On one side, the reaction takes place with the hydrogen atoms on the imidazole groups of PBI, while on the other side, it reacts with the terminal amino group of PVP. The XPS results provide additional evidence from the perspective of the element. On synthesized PBI-g-PVP surfaces, there is an absence of chlorine (chlorine in grafting agent 1,4-bis(chloromethyl)benzene is substituted) element but a presence of sulfur element (sulfur element in terminal amino PVP appears in PBI), which demonstrates the occurrence of the grafting reaction and PVP is successfully grafted onto PBI. Prepare these modified membranes into MEA. It was found that during the fuel cell operation, all the grafted membranes showed substantial improvement in maximum current density and peak power density compared to unmodified one. For PBI-g-PVP 30, with a grafting degree of 22.4%, the peak power density reaches 1312 mW cm⁻², marking a 59.6% enhancement compared to the pristine PBI membrane. The improvement is caused by the improved PA binding ability of the membrane after grafting. The AST test result shows that the grafting membranes have better long-term durability and performance than unmodified membranes attributed to the presence of added PA binding sites, which can effectively prevent the PA leaching caused by proton migration. In conclusion, the test results indicate that grafting PVP onto PBI is a promising strategy which can effectively improve the fuel cell performance.

Keywords: fuel cell, grafting modification, PA doping ability, PVP

Procedia PDF Downloads 41

Authors: B. Lefranc, C. Aufauvre-Poupon, C. Martin-Krumm, M. Trousselard

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Isolated and confined environments (ICE) present several challenges which may adversely affect human’s psychology and physiology. Submariners in Sub-Surface Ballistic Nuclear (SSBN) mission exposed to these environmental constraints must be able to perform complex tasks as part of their normal duties, as well as during crisis periods when emergency actions are required or imminent. The operational and environmental constraints they face contribute to challenge human adaptability. The impact of such a constrained environment has yet to be explored. Establishing a knowledge framework is a determining factor, particularly in view of the next long space travels. Ensuring that the crews are maintained in optimal operational conditions is a real challenge because the success of the mission depends on them. This study focused on the evaluation of the impact of stress on mental health and sensory degradation of submariners during a mission on SSBN using cardiac biosignal (heart rate variability, HRV) clustering. This is a pragmatic exploratory study of a prospective cohort included 19 submariner volunteers. HRV was recorded at baseline to classify by clustering the submariners according to their stress level based on parasympathetic (Pa) activity. Impacts of high Pa (HPa) versus low Pa (LPa) level at baseline were assessed on emotional state and sensory perception (interoception and exteroception) as a cardiac biosignal during the patrol and at a recovery time one month after. Whatever the time, no significant difference was found in mental health between groups. There are significant differences in the interoceptive, exteroceptive and physiological functioning during the patrol and at recovery time. To sum up, compared to the LPa group, the HPa maintains a higher level in psychosensory functioning during the patrol and at recovery but exhibits a decrease in Pa level. The HPa group has less adaptable HRV characteristics, less unpredictability and flexibility of cardiac biosignals while the LPa group increases them during the patrol and at recovery time. This dissociation between psychosensory and physiological adaptation suggests two treatment modalities for ICE environments. To our best knowledge, our results are the first to highlight the impact of physiological differences in the HRV profile on the adaptability of submariners. Further studies are needed to evaluate the negative emotional and cognitive effects of ICEs based on the cardiac profile. Artificial intelligence offers a promising future for maintaining high level of operational conditions. These future perspectives will not only allow submariners to be better prepared, but also to design feasible countermeasures that will help support analog environments that bring us closer to a trip to Mars.

Keywords: adaptation, exteroception, HRV, ICE, interoception, SSBN

Procedia PDF Downloads 150

Authors: David Edgar

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To understand how the brain’s subconscious and conscious functions, we must conquer the physics of Unity, which leads to duality’s algorithm. Where the subconscious (bottom-up) and conscious (top-down) processes function together to produce and consume intelligence, we use terms like ‘time is relative,’ but we really do understand the meaning. In the brain, there are different processes and, therefore, different observers. These different processes experience time at different rates. A sensory system such as the eyes cycles measurement around 33 milliseconds, the conscious process of the frontal lobe cycles at 300 milliseconds, and the subconscious process of the thalamus cycle at 5 milliseconds. Three different observers experience time differently. To bridge observers, the thalamus, which is the fastest of the processes, maintains a synchronous state and entangles the different components of the brain’s physical process. The entanglements form a synchronous cohesion between the brain components allowing them to share the same state and execute in the same measurement cycle. The thalamus uses the shared state to control the firing sequence of the brain’s linear subconscious process. Sharing state also allows the brain to cheat on the amount of sensory data that must be exchanged between components. Only unpredictable motion is transferred through the synchronous state because predictable motion already exists in the shared framework. The brain’s synchronous subconscious process is entirely based on energy conservation, where prediction regulates energy usage. So, the eyes every 33 milliseconds dump their sensory data into the thalamus every day. The thalamus is going to perform a motion measurement to identify the unpredictable motion in the sensory data. Here is the trick. The thalamus conducts its measurement based on the original observation time of the sensory system (33 ms), not its own process time (5 ms). This creates a data payload of synchronous motion that preserves the original sensory observation. Basically, a frozen moment in time (Flat 4D). The single moment in time can then be processed through the single state maintained by the synchronous process. Other processes, such as consciousness (300 ms), can interface with the synchronous state to generate awareness of that moment. Now, synchronous data traveling through a separate faster synchronous process creates a theoretical time tunnel where observation time is tunneled through the synchronous process and is reproduced on the other side in the original time-relativity. The synchronous process eliminates time dilation by simply removing itself from the equation so that its own process time does not alter the experience. To the original observer, the measurement appears to be instantaneous, but in the thalamus, a linear subconscious process generating sensory perception and thought production is being executed. It is all just occurring in the time available because other observation times are slower than thalamic measurement time. For life to exist in the physical universe requires a linear measurement process, it just hides by operating at a faster time relativity. What’s interesting is time dilation is not the problem; it’s the solution. Einstein said there was no universal time.

Keywords: neural synchronization, natural intelligence, 99.95% IoT data transmission savings, artificial subconscious intelligence (ASI)

Procedia PDF Downloads 104

Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

Procedia PDF Downloads 99

Authors: Takaaki Nemoto

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Case presentation: A 69-year-old Japanese man presented with a low-grade fever and fatigue that had persisted for one month. The patient had an aortic dissection on the aortic arch 13 years prior, an abdominal aortic aneurysm seven years prior, and an aortic dissection on the distal aortic arch one year prior, which were all treated with artificial blood-vessel replacement surgery. Laboratory tests revealed an inflammatory response (CRP 7.61 mg/dl), high serum creatinine (Cr 1.4 mg/dL), and elevated transaminase (AST 47 IU/L, ALT 45 IU/L). The patient was admitted to our hospital on suspicion of prosthetic vascular graft infection. Following further workups on the inflammatory response, an enhanced chest computed tomography (CT) and a non-enhanced chest DWI (MRI) were performed. The patient was diagnosed with a pulmonary fistula and a prosthetic vascular graft infection on the distal aortic arch. After admission, the patient was administered Ceftriaxion and Vancomycine for 10 days, but his fever and inflammatory response did not improve. On day 13 of hospitalization, a lung fistula repair surgery and an omental filling operation were performed, and Meropenem and Vancomycine were administered. The fever and inflammatory response continued, and therefore we took repeated blood cultures. M. fortuitum was detected in a blood culture on day 16 of hospitalization. As a result, we changed the treatment regimen to Amikacin (400 mg/day), Meropenem (2 g/day), and Cefmetazole (4 g/day), and the fever and inflammatory response began to decrease gradually. We performed a test of sensitivity for Mycobacterium fortuitum, and found that the MIC was low for fluoroquinolone antibacterial agent. The clinical course was good, and the patient was discharged after a total of 8 weeks of intravenous drug administration. At discharge, we changed the treatment regimen to Levofloxacin (500 mg/day) and Clarithromycin (800 mg/day), and prescribed these two drugs as a long life suppressive therapy. Discussion: There are few cases of prosthetic vascular graft infection caused by mycobacteria, and a standard therapy remains to be established. For prosthetic vascular graft infections, it is ideal to provide surgical and medical treatment in parallel, but in this case, surgical treatment was difficult and, therefore, a conservative treatment was chosen. We attempted to increase the treatment success rate of this refractory disease by conducting a susceptibility test for mycobacteria and treating with different combinations of antimicrobial agents, which was ultimately effective. With our treatment approach, a good clinical course was obtained and continues at the present stage. Conclusion: Although prosthetic vascular graft infection resulting from mycobacteria is a refractory infectious disease, it may be curative to administer appropriate antibiotics based on the susceptibility test in addition to surgical treatment.

Keywords: prosthetic vascular graft infection, lung fistula, Mycobacterium fortuitum, conservative treatment

Procedia PDF Downloads 130

Authors: Andrew Fox, Qingping Yang, Yuanhong Zhao, Tao Zhang

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Furniture is a very significant subdivision of architecture and its inherent interior design activities. The furniture industry has developed from an artisan-driven craft industry, whose forerunners saw themselves manifested in their crafts and treasured a sense of pride in the creativity of their designs, these days largely reduced to an anonymous collective mass-produced output. Although a very conservative industry, there is great potential for the implementation of collaborative digital technologies allowing a reconfigured artisan experience to be reawakened in a new and exciting form. The furniture manufacturing industry, in general, has been slow to adopt new methodologies for a design using artificial and rule-based generative design. This tardiness has meant the loss of potential to enhance its capabilities in producing sustainable, flexible, and mass customizable ‘right first-time’ designs. This paper aims to demonstrate the concept methodology for the creation of alternative and inspiring aesthetic structures for robot-based additive manufacturing (RBAM). These technologies can enable the economic creation of previously unachievable structures, which traditionally would not have been commercially economic to manufacture. The integration of these technologies with the computing power of generative design provides the tools for practitioners to create concepts which are well beyond the insight of even the most accomplished traditional design teams. This paper aims to address the problem by introducing generative design methodologies employing the Autodesk Fusion 360 platform. Examination of the alternative methods for its use has the potential to significantly reduce the estimated 80% contribution to environmental impact at the initial design phase. Though predominantly a design methodology, generative design combined with RBAM has the potential to leverage many lean manufacturing and quality assurance benefits, enhancing the efficiency and agility of modern furniture manufacturing. Through a case study examination of a furniture artifact, the results will be compared to a traditionally designed and manufactured product employing the Ecochain Mobius product life cycle analysis (LCA) platform. This will highlight the benefits of both generative design and robot-based additive manufacturing from an environmental impact and manufacturing efficiency standpoint. These step changes in design methodology and environmental assessment have the potential to revolutionise the design to manufacturing workflow, giving momentum to the concept of conceiving a pre-industrial model of manufacturing, with the global demand for a circular economy and bespoke sustainable design at its heart.

Keywords: robot, manufacturing, generative design, sustainability, circular econonmy, product life cycle assessment, furniture

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Authors: Adam Gushgari

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The SARS-CoV-2 pandemic has catalyzed the rapid adoption of wastewater-based epidemiology (WBE) methodologies both domestically and internationally. To support the rapid scale-up of pandemic-response wastewater surveillance systems, multiple federal agencies (i.e. US CDC), non-government organizations (i.e. Water Environment Federation), and private charities (i.e. Bill and Melinda Gates Foundation) have funded over $220 million USD supporting development and expanding equitable access of surveillance methods. Funds were primarily distributed directly to municipalities under the CARES Act (90.6%), followed by academic projects (7.6%), and initiatives developed by private companies (1.8%). In addition to federal funding for wastewater monitoring primarily conducted at wastewater treatment plants, state/local governments and private companies have leveraged wastewater sampling to obtain health and lifestyle data on student, prison inmate, and employee populations. We explore the viable paths for expansion of the WBE m1ethodology across a variety of analytical methods; the development of WBE-specific samplers and real-time wastewater sensors; and their application to various governments and private sector industries. Considerable investment in, and public acceptance of WBE suggests the methodology will be applied to other future notifiable diseases and health risks. Early research suggests that WBE methods can be applied to a host of additional “biological insults” including communicable diseases and pathogens, such as influenza, Cryptosporidium, Giardia, mycotoxin exposure, hepatitis, dengue, West Nile, Zika, and yellow fever. Interest in chemical insults is also likely, providing community health and lifestyle data on narcotics consumption, use of pharmaceutical and personal care products (PPCP), PFAS and hazardous chemical exposure, and microplastic exposure. Successful application of WBE to monitor analytes correlated with carcinogen exposure, community stress prevalence, and dietary indicators has also been shown. Additionally, technology developments of in situ wastewater sensors, WBE-specific wastewater samplers, and integration of artificial intelligence will drastically change the landscape of WBE through the development of “smart sewer” networks. The rapid expansion of the WBE field is creating significant business opportunities for professionals across the scientific, engineering, and technology industries ultimately focused on community health improvement.

Keywords: wastewater surveillance, wastewater-based epidemiology, smart cities, public health, pandemic management, substance abuse

Procedia PDF Downloads 73

Authors: Lena Lapidot, Amir Amnon, Rita Nosenko, Veitsman Ella, Cohen-Ezra Oranit, Davidov Yana, Segev Shlomo, Koren Omry, Safran Michal, Ben-Ari Ziv

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Introduction: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer related mortality worldwide. Liver Cirrhosis is the main predisposing risk factor for the development of HCC. The factor(s) influencing disease progression from Cirrhosis to HCC remain unknown. Gut microbiota has recently emerged as a major player in different liver diseases, however its association with HCC is still a mystery. Moreover, there might be an important association between the gut microbiota, nutrition, life style and the progression of Cirrhosis and HCC. The aim of our study was to characterize the gut microbial signature in association with life style and nutrition of patients with Cirrhosis, HCC-Cirrhosis and healthy controls. Design: Stool samples were collected from 95 individuals (30 patients with HCC, 38 patients with Cirrhosis and 27 age, gender and BMI-matched healthy volunteers). All participants answered lifestyle and Food Frequency Questionnaires. 16S rRNA sequencing of fecal DNA was performed (MiSeq Illumina). Results: There was a significant decrease in alpha diversity in patients with Cirrhosis (qvalue=0.033) and in patients with HCC-Cirrhosis (qvalue=0.032) compared to healthy controls. The microbiota of patients with HCC-cirrhosis compared to patients with Cirrhosis, was characterized by a significant overrepresentation of Clostridium (pvalue=0.024) and CF231 (pvalue=0.010) and lower expression of Alphaproteobacteria (pvalue=0.039) and Verrucomicrobia (pvalue=0.036) in several taxonomic levels: Verrucomicrobiae, Verrucomicrobiales, Verrucomicrobiaceae and the genus Akkermansia (pvalue=0.039). Furthermore, we performed an analysis of predicted metabolic pathways (Kegg level 2) that resulted in a significant decrease in the diversity of metabolic pathways in patients with HCC-Cirrhosis (qvalue=0.015) compared to controls, one of which was amino acid metabolism. Furthermore, investigating the life style and nutrition habits of patients with HCC-Cirrhosis, we found significant correlations between intake of artificial sweeteners and Verrucomicrobia (qvalue=0.12), High sugar intake and Synergistetes (qvalue=0.021) and High BMI and the pathogen Campylobacter (qvalue=0.066). Furthermore, overweight in patients with HCC-Cirrhosis modified bacterial diversity (qvalue=0.023) and composition (qvalue=0.033). Conclusions: To the best of the our knowledge, we present the first report of the gut microbial composition in patients with HCC-Cirrhosis, compared with Cirrhotic patients and healthy controls. We have demonstrated in our study that there are significant differences in the gut microbiome of patients with HCC-cirrhosis compared to Cirrhotic patients and healthy controls. Our findings are even more pronounced because the significantly increased bacteria Clostridium and CF231 in HCC-Cirrhosis weren't influenced by diet and lifestyle, implying this change is due to the development of HCC. Further studies are needed to confirm these findings and assess causality.

Keywords: Cirrhosis, Hepatocellular carcinoma, life style, liver disease, microbiome, nutrition

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Authors: H. Mayton, X. Yan, A. G. Taylor

Abstract:

Infested tomato seeds were used to investigate the influence of Xanthomonas euvesicatoria on germination and seed to seedling transmission in a controlled environment and greenhouse assays in an effort to develop effective seed treatments and characterize seed borne transmission of bacterial leaf spot of tomato. Bacterial leaf spot of tomato, caused by four distinct Xanthomonas species, X. euvesicatoria, X. gardneri, X. perforans, and X. vesicatoria, is a serious disease worldwide. In the United States, disease prevention is expensive for commercial growers in warm, humid regions of the country, and crop losses can be devastating. In this study, four different infested tomato seed lots were extracted from tomato fruits infected with bacterial leaf spot from a field in New York State in 2017 that had been inoculated with X. euvesicatoria. In addition, vacuum infiltration at 61 kilopascals for 1, 5, 10, and 15 minutes and seed soaking for 5, 10, 15, and 30 minutes with different bacterial concentrations were used to artificially infest seed in the laboratory. For controlled environment assays, infested tomato seeds from the field and laboratory were placed othe n moistened blue blotter in square plastic boxes (10 cm x 10 cm) and incubated at 20/30 ˚C with an 8/16 hour light cycle, respectively. Infested tomato seeds from the field and laboratory were also planted in small plastic trays in soil (peat-lite medium) and placed in the greenhouse with 24/18 ˚C day and night temperatures, respectively, with a 14-hour photoperiod. Seed germination was assessed after eight days in the laboratory and 14 days in the greenhouse. Polymerase chain reaction (PCR) using the hrpB7 primers (RST65 [5’- GTCGTCGTTACGGCAAGGTGGTG-3’] and RST69 [5’-TCGCCCAGCGTCATCAGGCCATC-3’]) was performed to confirm presence or absence of the bacterial pathogen in seed lots collected from the field and in germinating seedlings in all experiments. For infested seed lots from the field, germination was lowest (84%) in the seed lot with the highest level of bacterial infestation (55%) and ranged from 84-98%. No adverse effect on germination was observed from artificially infested seeds for any bacterial concentration and method of infiltration when compared to a non-infested control. Germination in laboratory assays for artificially infested seeds ranged from 82-100%. In controlled environment assays, 2.5 % were PCR positive for the pathogen, and in the greenhouse assays, no infected seedlings were detected. From these experiments, X. euvesicatoria does not appear to adversely influence germination. The lowest rate of germination from field collected seed may be due to contamination with multiple pathogens and saprophytic organisms as no effect of artificial bacterial seed infestation in the laboratory on germination was observed. No evidence of systemic movement from seed to seedling was observed in the greenhouse assays; however, in the controlled environment assays, some seedlings were PCR positive. Additional experiments are underway with green fluorescent protein-expressing isolates to further characterize seed to seedling transmission of the bacterial leaf spot pathogen in tomato.

Keywords: bacterial leaf spot, seed germination, tomato, Xanthomonas euvesicatoria

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Authors: Shereen Ismail Fawaz, Shin-Ichi Izumi, Nouran Mohamed Salah, Heba G. Saber, Ibrahim Mohamed Roushdi

Abstract:

Background: Multiple sclerosis (MS) is a chronic, inflammatory, mainly demyelinating disease of the central nervous system, more common in young adults. Cerebellar involvement is one of the most disabling lesions in MS and is usually a sign of disease progression. It plays a major role in the planning, initiation, and organization of movement via its influence on the motor cortex and corticospinal outputs. Therefore, it contributes to controlling movement, motor adaptation, and motor learning, in addition to its vast connections with other major pathways controlling balance, such as the cerebellopropriospinal pathways and cerebellovestibular pathways. Hence, trying to stimulate the cerebellum by facilitatory protocols will add to our motor control and balance function. Non-invasive brain stimulation, both repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS), has recently emerged as effective neuromodulators to influence motor and nonmotor functions of the brain. Anodal tDCS has been shown to improve motor skill learning and motor performance beyond the training period. Similarly, rTMS, when used at high frequency (>5 Hz), has a facilitatory effect on the motor cortex. Objective: Our aim was to determine the effect of high-frequency rTMS over the cerebellum in improving balance and functional ambulation of multiple sclerosis patients with Ataxia. Patients and methods: This was a randomized single-blinded placebo-controlled prospective trial on 40 patients. The active group (N=20) received real rTMS sessions, and the control group (N=20) received Sham rTMS using a placebo program designed for this treatment. Both groups received 12 sessions of high-frequency rTMS over the cerebellum, followed by an intensive exercise training program. Sessions were given three times per week for four weeks. The active group protocol had a frequency of 10 Hz rTMS over the cerebellar vermis, work period 5S, number of trains 25, and intertrain interval 25s. The total number of pulses was 1250 pulses per session. The control group received Sham rTMS using a placebo program designed for this treatment. Both groups of patients received an intensive exercise program, which included generalized strengthening exercises, endurance and aerobic training, trunk abdominal exercises, generalized balance training exercises, and task-oriented training such as Boxing. As a primary outcome measure the Modified ICARS was used. Static Posturography was done with: Patients were tested both with open and closed eyes. Secondary outcome measures included the expanded Disability Status Scale (EDSS) and 8 Meter walk test (8MWT). Results: The active group showed significant improvements in all the functional scales, modified ICARS, EDSS, and 8-meter walk test, in addition to significant differences in static Posturography with open eyes, while the control group did not show such differences. Conclusion: Cerebellar high-frequency rTMS could be effective in the functional improvement of balance in MS patients with ataxia.

Keywords: brain neuromodulation, high frequency rTMS, cerebellar stimulation, multiple sclerosis, balance rehabilitation

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Authors: Nasser Koleini Mamaghani, Sara Mostowfi

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The complexity of public space design makes it difficult for designers to simultaneously consider all issues for thorough decision-making. Among public spaces, the public space around people’s house is the most prominent space that affects and impacts people’s daily life. Considering recreational public spaces in cities, their main purpose would be to design for experiences that enable a deep feeling of peace and a moment of being away from the hectic daily life. Respecting human emotions and restoring natural environments, although difficult and to some extent out of reach, are key issues for designing such spaces. In this paper we propose to analyse the structure of recreational public spaces and the related emotional impressions. Furthermore, we suggest investigating how these structures influence people’s choice for public spaces by using differential semantics. According to Kansei methodology, in order to evaluate a situation appropriately, the assessment variables must be adapted to the user’s mental scheme. This means that the first step would have to be the identification of a space’s conceptual scheme. In our case study, 32 Kansei words and 4 different locations, each with a different sensual experience, were selected. The 4 locations were all parks in the city of Tehran (Iran), each with a unique structure and artifacts such as a fountain, lighting, sculptures, and music. It should be noted that each of these parks has different combination and structure of environmental and artificial elements like: fountain, lightning, sculpture, music (sound) and so forth. The first one was park No.1, a park with natural environment, the selected space was a fountain with motion light and sculpture. The second park was park No.2, in which there are different styles of park construction: ways from different countries, the selected space was traditional Iranian architecture with a fountain and trees. The third one was park No.3, the park with modern environment and spaces, and included a fountain that moved according to music and lighting. The fourth park was park No.4, the park with combination of four elements: water, fire, earth, wind, the selected space was fountains squirting water from the ground up. 80 participant (55 males and 25 females) aged from 20-60 years participated in this experiment. Each person filled the questionnaire in the park he/she was in. Five-point semantic differential scale was considered to determine the relation between space details and adjectives (kansei words). Received data were analyzed by multivariate statistical technique (factor analysis using SPSS statics). Finally the results of this analysis are criteria as inspiration which can be used in future space designing for creating pleasant feeling in users.

Keywords: environmental design, differential semantics, Kansei engineering, subjective preferences, space

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Authors: Roberta Pecoraro

Abstract:

The focus of this work was to investigate the potential toxic effect of titanium dioxide-reduced graphene oxide (TiO₂-rGO) nanocomposites on nauplii of microcrustacean Artemia sp. In order to assess the nanocomposite’s toxicity, a short-term test was performed by exposing nauplii to solutions containing TiO₂-rGO. To prepare titanium dioxide-reduced graphene oxide (TiO₂-rGO) nanocomposites, a green procedure based on solar photoreduction was proposed; it allows to obtain the photocatalysts by exploiting the photocatalytic properties of titania activated by the solar irradiation in order to avoid the high temperatures and pressures required for the standard hydrothermal synthesis. Powders of TiO₂-rGO supplied by the Department of Chemical Sciences (University of Catania) are indicated as TiO₂-rGO at 1% and TiO₂-rGO at 2%. Starting from a stock solution (1mg rGO-TiO₂/10 ml ASPM water) of each type, we tested four different concentrations (serial dilutions ranging from 10⁻¹ to 10⁻⁴ mg/ml). All the solutions have been sonicated for 12 min prior to use. Artificial seawater (called ASPM water) was prepared to guarantee the hatching of the cysts and to maintain nauplii; the durable cysts used in this study, marketed by JBL (JBL GmbH & Co. KG, Germany), were hydrated with ASPM water to obtain nauplii (instar II-III larvae). The hatching of the cysts was carried out in the laboratory by immersing them in ASPM water inside a 500 ml beaker and keeping them constantly oxygenated thanks to an aerator for the insufflation of microbubble air: after 24-48 hours, the cysts hatched, and the nauplii appeared. The nauplii in the second and third stages of development were collected one-to-one, using stereomicroscopes, and transferred into 96-well microplates where one nauplius per well was added. The wells quickly have been filled with 300 µl of each specific concentration of the solution used, and control samples were incubated only with ASPM water. Replication was performed for each concentration. Finally, the microplates were placed on an orbital shaker, and the tests were read after 24 and 48 hours from inoculating the solutions to assess the endpoint (immobility/death) for the larvae. Nauplii that appeared motionless were counted as dead, and the percentages of mortality were calculated for each treatment. The results showed a low percentage of immobilization both for TiO₂-rGO at 1% and TiO₂-rGO at 2% for all concentrations tested: for TiO₂-rGO at 1% was below 12% after 24h and below 15% after 48h; for TiO₂-rGO at 2% was below 8% after 24h and below 12% after 48h. According to other studies in the literature, the results have not shown mortality nor toxic effects on the development of larvae after exposure to rGO. Finally, it is important to highlight that the TiO₂-rGO catalysts were tested in the solar photodegradation of a toxic herbicide (2,4-Dichlorophenoxyacetic acid, 2,4-D), obtaining a high percentage of degradation; therefore, this alternative approach could be considered a good strategy to obtain performing photocatalysts.

Keywords: Nauplii, photocatalytic properties, reduced GO, short-term toxicity test, titanium dioxide

Procedia PDF Downloads 157