Search results for: reliability-based robust optimization

Authors: Gerald Gwamba, Bo Zhou, Yajun Song, Dong Changyin

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The challenges that sand production presents to the oil and gas industry, particularly while working in poorly consolidated reservoirs, cannot be overstated. From restricting production to blocking production tubing, sand production increases the costs associated with production as it elevates the cost of servicing production equipment over time. Production in reservoirs that present with high viscosities, flow rate, cementation, clay content as well as fine sand contents is even more complex and challenging. As opposed to the one-factor at a-time testing, investigating the interactive effects arising from a combination of several factors offers increased reliability of results as well as representation of actual field conditions. It is thus paramount to investigate the conditions leading to the onset of sanding during production to ensure the future sustainability of hydrocarbon production operations under viscous conditions. We adopt the Design of Experiments (DOE) to analyse, using Taguchi factorial designs, the most significant interactive effects of sanding. We propose an optimized regression model to predict the drawdown time at sand production. The results obtained underscore that reservoirs characterized by varying (high and low) levels of viscosity, flow rate, cementation, clay, and fine sand content have a resulting impact on sand production. The only significant interactive effect recorded arises from the interaction between BD (fine sand content and flow rate), while the main effects included fluid viscosity and cementation, with percentage significances recorded as 31.3%, 37.76%, and 30.94%, respectively. The drawdown time model presented could be useful for predicting the time to reach the maximum drawdown pressure under viscous conditions during the onset of sand production.

Keywords: factorial designs, DOE optimization, sand production prediction, drawdown time, regression model

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Authors: Tuğçe Kiper Elibol, İbrahim Uslan, Mehmet Ali Guler, Murat Buyuk, Uğur Yolum

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According to the FAA report, 142603 bird strikes were reported for a period of 24 years, between 1990 – 2013. Bird strike with aerospace structures not only threaten the flight security but also cause financial loss and puts life in danger. The statistics show that most of the bird strikes are happening with the nose and the leading edge of the wings. Also, a substantial amount of bird strikes is absorbed by the jet engines and causes damage on blades and engine body. Crash proof designs are required to overcome the possibility of catastrophic failure of the airplane. Using computational methods for bird strike analysis during the product development phase has considerable importance in terms of cost saving. Clearly, using simulation techniques to reduce the number of reference tests can dramatically affect the total cost of an aircraft, where for bird strike often full-scale tests are considered. Therefore, development of validated numerical models is required that can replace preliminary tests and accelerate the design cycle. In this study, to verify the simulation parameters for a bird strike analysis, several different numerical options are studied for an impact case against a primitive structure. Then, a representative bird mode is generated with the verified parameters and collided against the leading edge of a training aircraft wing, where each structural member of the wing was explicitly modeled. A nonlinear explicit dynamics finite element code, LS-DYNA was used for the bird impact simulations. SPH methodology was used to model the behavior of the bird. Dynamic behavior of the wing superstructure was observed and will be used for further design optimization purposes.

Keywords: bird impact, bird strike, finite element modeling, smoothed particle hydrodynamics

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Authors: Ivan A. Sandoval Salazar, Silvia F. Valderrama

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The microalgae oil emerges as a promising source of raw material for many industrial applications. Thus, this study had as a main focus on the cultivation of the microalgae species Desmodesmus sp. in laboratory scale with a view to maximizing biomass production and triglyceride content in the lipid fraction. Initially, culture conditions were selected to optimize biomass production, which was subsequently subjected to nutritional stress by varying nitrate and phosphate concentrations in order to increase the content and productivity of fatty acids. The culture medium BOLD 3N, nitrate and phosphate, light intensity 250,500 and 1000 μmol photons.m².s⁻¹, photoperiod of 12:12 were evaluated. Under the best conditions of the tests, a maximum cell division of 1.13 div.dia⁻¹ was obtained on the sixth day of culture, beginning of the exponential phase, and a maximum concentration of 8.42x107 cell.mL⁻¹ and dry biomass of 3.49 gL⁻¹ on the 20th day, in the stationary phase. The lipid content in the first stage of culture was approximately 8% after 12 days and at the end of the culture in the stationary phase ranged from 12% to 16% (20 days). In the microalgae grown at 250 μmol fotons.m2.s-1 the fatty acid profile was mostly polyunsaturated (52%). The total of unsaturated fatty acids, identified in this species of microalga, reached values between 70 and 75%, being qualified for use in the food and pharmaceutical industry. In addition, this study showed that the cultivation conditions influenced mainly the production of polyunsaturated fatty acids, with the predominance of γ-linolenic acid. However, in the cultures submitted to the highest the intensity of light (1000 μmol photons.m².s⁻¹) and low concentrations of nitrate and phosphate, saturated and monounsaturated fatty acids, which present greater oxidative stability, were identified mainly (60 to 70 %) being qualified for the production of biodiesel and for oleochemistry.

Keywords: microalgae, Desmodesmus sp, fatty acids, biodiesel

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Authors: Albert Oluwole Uzodimma Authority

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Nigeria is a diverse nation with a rich cultural heritage that has produced numerous art musicians and a vast range of art songs. The compositional styles, tonal rhythm, text rhythm, word painting, and text-tone relationship vary extensively from one dialect to another, indicating the need for standardized tools for the structural and analytical deconstruction of Nigerian indigenous art music. The purpose of this research is to examine the structures of Nigerian indigenous art music and outline some crucibles for analyzing it, by investigating how dialectical inflection influences the choice of text tone, scale mode, tonal rhythm, and the general ambiance of Nigerian art music. The research used a structured questionnaire to collect data from 50 musicologists, out of which 41 responded. The study's focus was on the works of two prominent twentieth-century composers, Stephen Olusoji, and Nwamara Alvan-Ikoku, titled "Oyigiyigi" and "O Chineke, Inozikwa omee," respectively. The data collected was presented in percentages using pie charts and tables. The study shows that in Nigerian Indigenous music, several aspects are to be considered for proper analysis, such as linguistic sensitivity, dialectical inflection influences text-tone relationship, text rhythm and tonal rhythm, which help to convey the proper meanings of messages in songs. It also highlights the lack of standardized rubrics for analysis, which necessitated the proposal of robust criteria for analyzing African music, known as Neo-Eclectic-Crucibles. Hinging on eclectic approach, this research makes significant contributions to music scholarship by addressing the need for standardized tools and crucibles for the structural and analytical deconstruction of Nigerian indigenous art music. It provides a template for further studies leading to standardized rubrics for analyzing African music. This research collected data through a structured questionnaire and analyzed it using pie charts and tables to present the findings accurately. The analysis focused on the respondents' perspectives on the research objectives and structural analysis of two indigenous music compositions by Olusoji and Nwamara. This research answers the questions on the structures and analytical crucibles used in Nigerian indigenous art music, how dialectical inflection influences text-tone relationship, scale mode, tonal rhythm, and the general ambiance of Nigerian art music. This paper demonstrates the need for standardized tools and crucibles for the structural and analytical deconstruction of Nigerian indigenous art music. It highlights several aspects that are crucial to analyzing Nigerian indigenous music and proposes the Neo-Eclectic-Crucibles criteria for analyzing African music. The contribution of this research to music scholarship is significant, providing a template for further studies and research in the field.

Keywords: art-music, crucibles, dialectical inflections, indigenous, text-tone, tonal rhythm, word-painting

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Authors: Suman Som, Abhijit Maity, Sunil B. Daschakraborty, Sujit Chaudhuri, Manik Pradhan

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Background: Helicobacter pylori is a common and important human pathogen and the primary cause of peptic ulcer disease and gastric cancer. Currently H. pylori infection is detected by both invasive and non-invasive way but the diagnostic accuracy is not up to the mark. Aim: To set up an optimal diagnostic cut-off value of 13C-Urea Breath Test to detect H. pylori infection and evaluate a novel c-PDR methodology to overcome of inconclusive grey zone. Materials and Methods: All 83 subjects first underwent upper-gastrointestinal endoscopy followed by rapid urease test and histopathology and depending on these results; we classified 49 subjects as H. pylori positive and 34 negative. After an overnight, fast patients are taken 4 gm of citric acid in 200 ml water solution and 10 minute after ingestion of the test meal, a baseline exhaled breath sample was collected. Thereafter an oral dose of 75 mg 13C-Urea dissolved in 50 ml water was given and breath samples were collected upto 90 minute for 15 minute intervals and analysed by laser based high precisional cavity enhanced spectroscopy. Results: We studied the excretion kinetics of 13C isotope enrichment (expressed as δDOB13C ‰) of exhaled breath samples and found maximum enrichment around 30 minute of H. pylori positive patients, it is due to the acid mediated stimulated urease enzyme activity and maximum acidification happened within 30 minute but no such significant isotopic enrichment observed for H. pylori negative individuals. Using Receiver Operating Characteristic (ROC) curve an optimal diagnostic cut-off value, δDOB13C ‰ = 3.14 was determined at 30 minute exhibiting 89.16% accuracy. Now to overcome grey zone problem we explore percentage dose of 13C recovered per hour, i.e. 13C-PDR (%/hr) and cumulative percentage dose of 13C recovered, i.e. c-PDR (%) in exhaled breath samples for the present 13C-UBT. We further explored the diagnostic accuracy of 13C-UBT by constructing ROC curve using c-PDR (%) values and an optimal cut-off value was estimated to be c-PDR = 1.47 (%) at 60 minute, exhibiting 100 % diagnostic sensitivity , 100 % specificity and 100 % accuracy of 13C-UBT for detection of H. pylori infection. We also elucidate the gastric emptying process of present 13C-UBT for H. pylori positive patients. The maximal emptying rate found at 36 minute and half empting time of present 13C-UBT was found at 45 minute. Conclusions: The present study exhibiting the importance of c-PDR methodology to overcome of grey zone problem in 13C-UBT for accurate determination of infection without any risk of diagnostic errors and making it sufficiently robust and novel method for an accurate and fast non-invasive diagnosis of H. pylori infection for large scale screening purposes.

Keywords: 13C-Urea breath test, c-PDR methodology, grey zone, Helicobacter pylori

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Authors: Mateusz Szul, Tomasz Iluk, Aleksander Sobolewski

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Small-scale, distributed energy systems enabling cogeneration of heat and power based on gasification of sewage sludge, are considered as the most efficient and environmentally friendly ways of their treatment. However, economic aspects of such an investment are very demanding; therefore, for such a small scale sewage sludge gasification installation to be profitable, it needs to be efficient and simple at the same time. The article presents results of research on air gasification of sewage sludge in fixed bed GazEla reactor. Two of the most important aspects of the research considered the influence of the composition of sewage sludge blends with other feedstocks on properties of generated syngas and ash sintering problems occurring at the fixed bed. Different means of the fuel pretreatment and blending were proposed as a way of dealing with the above mentioned undesired characteristics. Influence of RDF (Refuse Derived Fuel) and biomasses in the fuel blends were evaluated. Ash properties were assessed based on proximate, ultimate, and ash composition analysis of the feedstock. The blends were specified based on complementary characteristics of such criteria as C content, moisture, volatile matter, Si, Al, Mg, and content of basic metals in the ash were analyzed, Obtained results were assessed with use of experimental gasification tests and laboratory ISO-procedure for analysis of ash characteristic melting temperatures. Optimal gasification process conditions were determined by energetic parameters of the generated syngas, its content of tars and lack of ash sinters within the reactor bed. Optimal results were obtained for co-gasification of herbaceous biomasses with sewage sludge where LHV (Lower Heating Value) of the obtained syngas reached a stable value of 4.0 MJ/Nm3 for air/steam gasification.

Keywords: ash fusibility, gasification, piston engine, sewage sludge

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Authors: Jonathan Martino, Kristof Harri

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In some cases, the increase in computing resources makes simulation methods more affordable. The increase in processing speed also allows real time analysis or even more rapid tests analysis offering a real tool for test prediction and design process optimization. Vibration tests are no exception to this trend. The so called ‘Virtual Vibration Testing’ offers solution among others to study the influence of specific loads, to better anticipate the boundary conditions between the exciter and the structure under test, to study the influence of small changes in the structure under test, etc. This article will first present a virtual vibration test modeling with a main focus on the shaker model and will afterwards present the experimental parameters determination. The classical way of modeling a shaker is to consider the shaker as a simple mechanical structure augmented by an electrical circuit that makes the shaker move. The shaker is modeled as a two or three degrees of freedom lumped parameters model while the electrical circuit takes the coil impedance and the dynamic back-electromagnetic force into account. The establishment of the equations of this model, describing the dynamics of the shaker, is presented in this article and is strongly related to the internal physical quantities of the shaker. Those quantities will be reduced into global parameters which will be estimated through experiments. Different experiments will be carried out in order to design an easy and practical method for the identification of the shaker parameters leading to a fully functional shaker model. An experimental modal analysis will also be carried out to extract the modal parameters of the shaker and to combine them with the electrical measurements. Finally, this article will conclude with an experimental validation of the model.

Keywords: lumped parameters model, shaker modeling, shaker parameters, state-space, virtual vibration

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Authors: Jennifer Wright

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The recent rise of powerful terrorist groups such as ISIS and Al-Qaeda brings up concerns about nuclear terrorism as well as a focus on nuclear security, specifically the physical security of nuclear weapons and fissile material storage sites in countries where powerful nonstate actors are present. Particularly because these non-state actors, who lack their own sovereign territory, cannot be ‘deterred’ in the traditional sense. In light of the current threat environment, it’s necessary to now rethink these strategies in the 21st century – a multipolar world with the presence of powerful non-state actors. As a country in the spotlight for its low ranking on the Nuclear Threat Initiative’s (NTI) Nuclear Security Index, Pakistan is a relevant example to explore the question of whether the presence of non-state actors poses a real risk to nuclear security today. It’s necessary to take a look at their nuclear security policies to determine if they’re robust enough to deal with political instability and violence in the country. After carrying out interviews with experts in May 2017 in Islamabad on nuclear security and nuclear terrorism, this paper aims to highlight findings by providing a Pakistan-centric view on the subject and give experts there a chance to counter criticism. Western media would have us fearful of nuclear security mechanisms in Pakistan after reports that areas such as cybersecurity and accounting and control of materials are weak, as well as sensitive nuclear material being transported in unmarked, unguarded vehicles. Also reported are cases where terrorist groups carried out targeted attacks against Pakistani military bases or secure sites where nuclear material is stored. One specific question asked of each interviewee in Islamabad was Do you feel the threat of nuclear terrorism calls into question the reliance on deterrence? Their responses will be elaborated on in the longer paper, but overall they demonstrate views that deterrence still serves a purpose for state-to-state security strategy, but not for a state in countering nonstate threats. If nuclear security is lax enough for these non-state actors to get their hands on either an intact nuclear weapon or enough military-grade fissile material to build a nuclear weapon, then what would stop them from launching a nuclear attack? As deterrence is a state-centric strategy, it doesn’t work to deter non-state actors from carrying out an attack on another state, as they lack their own territory, and as such, are not fearful of a reprisal attack. Deterrence will need to be addressed, and its relevance analyzed to determine its utility in the current security environment. The aim of this research is to demonstrate the real risk of nuclear terrorism by pointing to weaknesses in global nuclear security, particularly in Pakistan. The research also aims to provoke thought on the weaknesses of deterrence as a whole. Original thinking is needed as we attempt to adequately respond to the 21st century’s current threat environment.

Keywords: deterrence, non-proliferation, nuclear security, nuclear terrorism

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Authors: Ioanna Taouki, Marie Lallier, David Soto

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Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: Roopa Singh, Anurag Singh, Ajay

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Agriculture contributes a major share in the national economy of India. A major portion of Indian economy (about 70%) depends upon agriculture as it forms the main source of income. About 43% of India’s geographical area is used for agricultural activity which involves 65-75% of total population of India. The given work deals with the Fast moving Consumer Goods (FMCG) industries and their inventories which use agricultural produce as their raw material or input for their final product. Since the beginning of inventory practices, many developments took place which can be categorised into three phases, based on the review of various works. The first phase is related with development and utilization of Economic Order Quantity (EOQ) model and methods for optimizing costs and profits. Second phase deals with inventory optimization method, with the purpose of balancing capital investment constraints and service level goals. The third and recent phase has merged inventory control with electrical control theory. Maintenance of inventory is considered negative, as a large amount of capital is blocked especially in mechanical and electrical industries. But the case is different in food processing and agro-based industries and their inventories due to cyclic variation in the cost of raw materials of such industries which is the reason for selection of these industries in the mentioned work. The application of electrical control theory in inventory control makes the decision-making highly instantaneous for FMCG industries without loss in their proposed profits, which happened earlier during first and second phases, mainly due to late implementation of decision. The work also replaces various inventories and work-in-progress (WIP) related errors with their monetary values, so that the decision-making is fully target-oriented.

Keywords: control theory, inventory control, manufacturing sector, EOQ, feedback, FMCG sector

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Leizhang Wang, Baocang Wang

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General Sieve Kernel (G6K) is considered as currently the fastest algorithm for the shortest vector problem (SVP) and record holder of open SVP challenge. We study the lattice basis quality improvement effects of the Workout proposed in G6K, which is composed of a series of pumps to solve SVP. Firstly, we use a low-dimensional pump output basis to propose a predictor to predict the quality of high-dimensional Pumps output basis. Both theoretical analysis and experimental tests are performed to illustrate that it is more computationally expensive to solve the LWE problems by using a G6K default SVP solving strategy (Workout) than these lattice reduction algorithms (e.g. BKZ 2.0, Progressive BKZ, Pump, and Jump BKZ) with sieving as their SVP oracle. Secondly, the default Workout in G6K is optimized to achieve a stronger reduction and lower computational cost. Thirdly, we combine the optimized Workout and the Pump output basis quality predictor to further reduce the computational cost by optimizing LWE instances selection strategy. In fact, we can solve the TU LWE challenge (n = 65, q = 4225, = 0:005) 13.6 times faster than the G6K default Workout. Fourthly, we consider a combined two-stage (Preprocessing by BKZ- and a big Pump) LWE solving strategy. Both stages use dimension for free technology to give new theoretical security estimations of several LWE-based cryptographic schemes. The security estimations show that the securities of these schemes with the conservative Newhope’s core-SVP model are somewhat overestimated. In addition, in the case of LAC scheme, LWE instances selection strategy can be optimized to further improve the LWE-solving efficiency even by 15% and 57%. Finally, some experiments are implemented to examine the effects of our strategies on the Normal Form LWE problems, and the results demonstrate that the combined strategy is four times faster than that of Newhope.

Keywords: LWE, G6K, pump estimator, LWE instances selection strategy, dimension for free

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Authors: S. P. Bansal, Mukesh Kumar Sharma, Ankit Prabhakar

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Luhri Hydroelectric Project Stage-I (210 MW) is a run of the river type development with a dam toe surface powerhouse (122m long, 50.50m wide, and 65.50m high) on the right bank of river Satluj in Himachal Pradesh, India. The project is located in the inner lesser Himalaya between Dhauladhar Range in the south and higher Himalaya in the north in the seismically active region. At the project, the location river is confined within narrow V-shaped valleys with little or no flat areas close to the river bed. Nearly 120m high cut slopes behind the powerhouse are proposed from the powerhouse foundation level of 795m to ± 915m to accommodate the surface powerhouse. The stability of 120m high cut slopes is a prime concern for the reason of risk involved. The slopes behind the powerhouse will be excavated in mainly in augen gneiss, fresh to weathered in nature, and biotite rich at places. The foliation joints are favorable and dipping inside the hill. Two valleys dipping steeper joints will be encountered on the slopes, which can cause instability during excavation. Geological exploration plays a vital role in designing and optimization of cut slopes. SWEDGE software has been used to analyze the geometry and stability of surface wedges in cut slopes. The slopes behind powerhouse have been analyzed in three zones for stability analysis by providing a break in the continuity of cut slopes, which shall provide quite substantial relief for slope stabilization measure. Pseudo static analysis has been carried out for the stabilization of wedges. The results indicate that many large wedges are forming, which have a factor of safety less than 1. The stability measures (support system, bench width, slopes) have been planned so that no wedge failure may occur in the future.

Keywords: cut slopes, geotechnical investigations, Himalayan geology, surface powerhouse, wedge failure

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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This paper proposes a method to optimize the layout of an emergency department (ED) based on real executions of care processes by considering several planning objectives simultaneously. Recently, demand for healthcare services has been dramatically increased. As the demand for healthcare services increases, so do the need for new healthcare buildings as well as the need for redesign and renovating existing ones. The importance of implementation of a standard set of engineering facilities planning and design techniques has been already proved in both manufacturing and service industry with many significant functional efficiencies. However, high complexity of care processes remains a major challenge to apply these methods in healthcare environments. Process mining techniques applied in this study to tackle the problem of complexity and to enhance care process analysis. Process related information such as clinical pathways extracted from the information system of an ED. A 0-1 goal programming approach is then proposed to find a single layout that simultaneously satisfies several goals. The proposed model solved by optimization software CPLEX 12. The solution reached using the proposed method has 42.2% improvement in terms of walking distance of normal patients and 47.6% improvement in walking distance of critical patients at minimum cost of relocation. It has been observed that lots of patients must unnecessarily walk long distances during their visit to the emergency department because of an inefficient design. A carefully designed layout can significantly decrease patient walking distance and related complications.

Keywords: healthcare operation management, goal programming, facility layout problem, process mining, clinical processes

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Authors: Julio Aguirre, Yohnny Campana, Elmer Guerrero, Daniel De La Torre Ugarte

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A well-developed transportation network is a necessary condition for a country to derive full benefits from good trade and macroeconomic policies. Road infrastructure plays a key role in the economic development of rural areas of developing countries; where agriculture is the main economic activity. The ability to move agricultural production from the place of production to the market, and then to the place of consumption, greatly influence the economic value of farming activities, and of the resources involved in the production process, i.e., labor and land. Consequently, investment in transportation networks contributes to enhance or overcome the natural advantages or disadvantages that topography and location have imposed over the agricultural sector. This is of particular importance when dealing with countries, like Peru, with a great topographic diversity. The objective of this research is to estimate the impacts of road infrastructure on the performance of the agricultural sector. Specific variables of interest are changes in travel time, shifts of production for self-consumption to production for the market, changes in farmers income, and impacts on the diversification of the agricultural sector. In the study, a cross-section model with instrumental variables is the central methodological instrument. The data is obtained from agricultural and transport geo-referenced databases, and the instrumental variable specification utilized is based on the Kruskal algorithm. The results show that the expansion of road connectivity reduced farmers' travel time by an average of 3.1 hours and the proportion of output sold in the market increases by up to 40 percentage points. The increase in connectivity has an unexpected increase in the districts index of diversification of agricultural production. The results are robust to the inclusion of year and region fixed-effects, and to control for geography (i.e., slope and altitude), population variables, and mining activity. Other results are also very eloquent. For example, a clear positive impact can be seen in access to local markets, but this does not necessarily correlate with an increase in the production of the sector. This can be explained by the fact that agricultural development not only requires provision of roads but additional complementary infrastructure and investments intended to provide the necessary conditions so that producers can offer quality products (improved management practices, timely maintenance of irrigation infrastructure, transparent management of water rights, among other factors). Therefore, complementary public goods are needed to enhance the effects of roads on the welfare of the population, beyond enabling them to increase their access to markets.

Keywords: agriculture devolepment, market access, road connectivity, regional development

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Authors: Ena Arora, Rong Fan, Aleksandr Fuks, Kolawole Felix Akinnawonu

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Introduction: Leiomyomas are benign tumors that are derived from the overgrowth of uterine smooth muscle cells. Women with symptomatic leiomyomas who desire future fertility, myomectomy should be the standard surgical treatment. Perioperative hemorrhage is a common complication in myomectomy. We performed the study to investigate blood transfusion rate in abdominal myomectomies, risk factors influencing blood loss and modalities to improve perioperative blood loss. Methods: Retrospective chart review was done for patients who underwent myomectomy from 2016 to 2022 at Queens hospital center, New York. We looked at preoperative patient demographics, clinical characteristics, intraoperative variables, and postoperative outcomes. Mann-Whitney U test were used for parametric and non-parametric continuous variable comparisons, respectively. Results: A total of 159 myomectomies were performed between 2016 and 2022, including 1 laparoscopic, 65 vaginal and 93 abdominal. 44 patients received blood transfusion during or within 72 hours of abdominal myomectomy. The blood transfusion rate was 47.3%. Blood transfusion rate was found to be twice higher than the average documented rate in literature which is 20%. Risk factors identified were black race, preoperative hematocrit<30%, preoperative blood transfusion within 72 hours, large fibroid burden, prolonged surgical time, and abdominal approach. Conclusion: Preoperative optimization with iron supplements or GnRH agonists is important for patients undergoing myomectomy. Interventions to decrease intra operative blood loss should include cell saver, tourniquet, vasopressin, misoprostol, tranexamic acid and gelatin-thrombin matrix hemostatic sealant.

Keywords: myomectomy, perioperative blood loss, cell saver, tranexamic acid

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Arkadiusz Zurek

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The potential of using drones is visible in many areas of logistics, especially in terms of their use for monitoring and control of many processes. The technologies implemented in the last decade concern new possibilities for companies that until now have not even considered them, such as warehouse inventories. Unmanned aerial vehicles are no longer seen as a revolutionary tool for Industry 4.0, but rather as tools in the daily work of factories and logistics operators. The research problem is to develop a method for measuring the weight of goods in a selected link of the clothing supply chain by drones. However, the purpose of this article is to analyze the causes of errors in traditional measurements, and then to identify adverse events related to the use of drones for the inventory of a heap of textiles intended for production purposes. On this basis, it will be possible to develop guidelines to eliminate the causes of these events in the measurement process using drones. In a real environment, work was carried out to determine the volume and weight of textiles, including, among others, weighing a textile sample to determine the average density of the assortment, establishing a local geodetic network, terrestrial laser scanning and photogrammetric raid using an unmanned aerial vehicle. As a result of the analysis of measurement data obtained in the facility, the volume and weight of the assortment and the accuracy of their determination were determined. In this article, this work presents how such heaps are currently being tested, what adverse events occur, indicate and describes the current use of photogrammetric techniques of this type of measurements so far performed by external drones for the inventory of wind farms or construction of the station and compare them with the measurement system of the aforementioned textile heap inside a large-format facility.

Keywords: drones, unmanned aerial system, UAS, indoor system, security, process automation, cost optimization, photogrammetry, risk elimination, industry 4.0

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Authors: Farah Islam, Md. Monirul Islam, Mosammat Salma Akter, Goutam Kumar Kundu

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The continuous variability of climate and the risk associated with it have a significant impact on the fisheries leading to a global concern for about half a billion fishery-based livelihoods. Though in the context of Bangladesh mounting evidence on the impacts of climate change on fishery-based livelihoods or their socioeconomic conditions are present, the country’s inland fisheries sector remains in a negligible corner as compared to the coastal areas which are spotted on the highlight due to its higher vulnerability to climatic hazards. The available research on inland fisheries, particularly river fisheries, has focussed mainly on fish production, pollution, fishing gear, fish biodiversity and livelihoods of the fishers. This study assesses the impacts of climate variability and changes on the Jamuna (a transboundary river called Brahmaputra in India) River fishing communities and their coping and adaptation strategies. This study has used primary data collected from Kalitola Ghat and Debdanga fishing communities of the Jamuna River during May, August and December 2015 using semi-structured interviews, oral history interviews, key informant interviews, focus group discussions and impact matrix as well as secondary data. This study has found that both communities are exposed to storms, floods and land erosions which impact on fishery-based livelihood assets, strategies, and outcomes. The impact matrix shows that human and physical capitals are more affected by climate hazards which in turn affect financial capital. Both communities have been responding to these exposures through multiple coping and adaptation strategies. The coping strategies include making dam with soil, putting jute sac on the yard, taking shelter on boat or embankment, making raised platform or ‘Kheua’ and involving with temporary jobs. While, adaptation strategies include permanent migration, change of livelihood activities and strategies, changing fishing practices and making robust houses. The study shows that migration is the most common adaptation strategy for the fishers which resulted in mostly positive outcomes for the migrants. However, this migration has impacted negatively on the livelihoods of existing fishers in the communities. In sum, the Jamuna river fishing communities have been impacted by several climatic hazards and they have traditionally coped with or adapted to the impacts which are not sufficient to maintain sustainable livelihoods and fisheries. In coming decades, this situation may become worse as predicted by latest scientific research and an enhanced level of response would be needed.

Keywords: climatic hazards, impacts and adaptation, fisherfolk, the Jamuna River

Procedia PDF Downloads 290

Authors: Pierre Tize Mha, Mohammad Jahazi, Amèvi Togne, Olivier Pantalé

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Large-size forged blocks made of medium carbon high-strength steels are extensively used in the automotive industry as dies for the production of bumpers and dashboards through the plastic injection process. The manufacturing process of the large blocks starts with ingot casting, followed by open die forging and a quench and temper heat treatment process to achieve the desired mechanical properties and numerical simulation is widely used nowadays to predict these properties before the experiment. But the temperature gradient inside the specimen remains challenging in the sense that the temperature before loading inside the material is not the same, but during the simulation, constant temperature is used to simulate the experiment because it is assumed that temperature is homogenized after some holding time. Therefore to be close to the experiment, real distribution of the temperature through the specimen is needed before the mechanical loading. Thus, We present here a robust algorithm that allows the calculation of the temperature gradient within the specimen, thus representing a real temperature distribution within the specimen before deformation. Indeed, most numerical simulations consider a uniform temperature gradient which is not really the case because the surface and core temperatures of the specimen are not identical. Another feature that influences the mechanical properties of the specimen is recrystallization which strongly depends on the deformation conditions and the type of deformation like Upsetting, Cogging...etc. Indeed, Upsetting and Cogging are the stages where the greatest deformations are observed, and a lot of microstructural phenomena can be observed, like recrystallization, which requires in-depth characterization. Complete dynamic recrystallization plays an important role in the final grain size during the process and therefore helps to increase the mechanical properties of the final product. Thus, the identification of the conditions for the initiation of dynamic recrystallization is still relevant. Also, the temperature distribution within the sample and strain rate influence the recrystallization initiation. So the development of a technique allowing to predict the initiation of this recrystallization remains challenging. In this perspective, we propose here, in addition to the algorithm allowing to get the temperature distribution before the loading stage, an analytical model leading to determine the initiation of this recrystallization. These two techniques are implemented into the Abaqus finite element software via the UAMP and VUHARD subroutines for comparison with a simulation where an isothermal temperature is imposed. The Artificial Neural Network (ANN) model to describe the plastic behavior of the material is also implemented via the VUHARD subroutine. From the simulation, the temperature distribution inside the material and recrystallization initiation is properly predicted and compared to the literature models.

Keywords: dynamic recrystallization, finite element modeling, artificial neural network, numerical implementation

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Authors: Frederic Schenker, Jonathan J. Hendriks, Gianluca Nicchiotti

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In a product industrialization perspective, the end-product shall always be at the peak of technological advancement and developed in the shortest time possible. Thus, the constant growth of complexity and a shorter time-to-market calls for important changes on both the technical and business level. Undeniably, the common understanding of the system is beclouded by its complexity which leads to the communication gap between the engineers and the sale department. This communication link is therefore important to maintain and increase the information exchange between departments to ensure a punctual and flawless delivery to the end customer. This evolution brings engineers to reason with more hindsight and plan ahead. In this sense, they use new viewpoints to represent the data and to express the model deliverables in an understandable way that the different stakeholder may identify their needs and ideas. This article focuses on the usage of Model-Based System Engineering (MBSE) in a perspective of system industrialization and reconnect the engineering with the sales team. The modeling method used and presented in this paper concentrates on displaying as closely as possible the needs of the customer. Firstly, by providing a technical solution to the sales team to help them elaborate commercial offers without omitting technicalities. Secondly, the model simulates between a vast number of possibilities across a wide range of components. It becomes a dynamic tool for powerful analysis and optimizations. Thus, the model is no longer a technical tool for the engineers, but a way to maintain and solidify the communication between departments using different views of the model. The MBSE contribution to cost optimization during New Product Introduction (NPI) activities is made explicit through the illustration of a case study describing the support provided by system models to architectural choices during the industrialization of a novel optical sensor.

Keywords: analytical model, architecture comparison, MBSE, product industrialization, SysML, system thinking

Procedia PDF Downloads 139

Authors: Andres Diaz Garcia

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The successful technological development of any bioproduct, including those of the biostimulant type, requires to adequately completion of a series of stages allied to different disciplines that are related to microbiological, engineering, pharmaceutical chemistry, legal and market components, among others. Engineering as a discipline has a key contribution in different aspects of fermentation processes such as the design and optimization of culture media, the standardization of operating conditions within the bioreactor and the scaling of the production process of the active ingredient that it will be used in unit operations downstream. However, all aspects mentioned must take into account many biological factors of the microorganism such as the growth rate, the level of assimilation to various organic and inorganic sources and the mechanisms of action associated with its biological activity. This paper focuses on the practical experience within the Colombian Corporation for Agricultural Research (Agrosavia), which led to the development of a biostimulant bioproduct based on native rhizobacteria Bacillus amyloliquefaciens, oriented mainly to plant growth promotion in cape gooseberry nurseries and fruit crops in Colombia, and the challenges that were overcome from the expertise in the area of engineering. Through the application of strategies and engineering tools, a culture medium was optimized to obtain concentrations higher than 1E09 CFU (colony form units)/ml in liquid fermentation, the process of biomass production was standardized and a scale-up strategy was generated based on geometric (H/D of bioreactor relationships), and operational criteria based on a minimum dissolved oxygen concentration and that took into account the differences in the capacity of control of the process in the laboratory and pilot scales. Currently, the bioproduct obtained through this technological process is in stages of registration in Colombia for cape gooseberry fruits for export.

Keywords: biochemical engineering, liquid fermentation, plant growth promoting, scale-up process

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Authors: S. Rashmi, Devashish Das, N. Spoorthi, H. V. Manasa

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Energy is essential and plays an important role for overall development of a nation. The global economy literally runs on energy. The use of fossil fuels as energy is now widely accepted as unsustainable due to depleting resources and also due to the accumulation of greenhouse gases in the environment, renewable and carbon neutral biodiesel are necessary for environment and economic sustainability. Unfortunately biodiesel produced from oil crop, waste cooking oil and animal fats are not able to replace fossil fuel. Fossil fuels remain the dominant source of primary energy, accounting for 84% of the overall increase in demand. Today biodiesel has come to mean a very specific chemical modification of natural oils. Objectives: To produce biodiesel from yellow oleander seed oil, to test the yield of biodiesel using different types of catalyst (KOH & NaOH). Methodology: Oil is extracted from dried yellow oleander seeds using Soxhlet extractor and oil expeller (bulk). The FFA content of the oil is checked and depending on the FFA value either two steps or single step process is followed to produce biodiesel. Two step processes includes esterfication and transesterification, single step includes only transesterification. The properties of biodiesel are checked. Engine test is done for biodiesel produced. Result: It is concluded that biodiesel quality parameters such as yield(85% & 90%), flash point(1710C & 1760C),fire point(1950C & 1980C), viscosity(4.9991 and 5.21 mm2/s) for the biodiesel from seed oil of Thevetiaperuviana produced by using KOH & NaOH respectively. Thus the seed oil of Thevetiaperuviana is a viable feedstock for good quality fuel.The outcomes of our project are a substitute for conventional fuel, to reduce petro diesel requirement,improved performance in terms of emissions. Future prospects: Optimization of biodiesel production using response surface method.

Keywords: yellow oleander seeds, biodiesel, quality parameters, renewable sources

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Authors: Vinay Kumar Vanjakula, Frank Adam

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The generation of electricity through wind power is one of the leading renewable energy generation methods. Due to abundant higher wind speeds far away from shore, the construction of offshore wind turbines began in the last decades. However, the installation of offshore foundation-based (monopiles) wind turbines in deep waters are often associated with technical and financial challenges. To overcome such challenges, the concept of floating wind turbines is expanded as the basis of the oil and gas industry. For such a floating system, stabilization in harsh conditions is a challenging task. For that, a robust heavy-weight gravity anchor is needed. Transportation of such anchor requires a heavy vessel that increases the cost. To lower the cost, the gravity anchor is designed with ballast chambers that allow the anchor to float while towing and filled with water when lowering to the planned seabed location. The presence of such a large structure may influence the flow field around it. The changes in the flow field include, formation of vortices, turbulence generation, waves or currents flow breaking and pressure differentials around the seabed sediment. These changes influence the installation process. Also, after installation and under operating conditions, the flow around the anchor may allow the local seabed sediment to be carried off and results in Scour (erosion). These are a threat to the structure's stability. In recent decades, rapid developments of research work and the knowledge of scouring on fixed structures (bridges and monopiles) in rivers and oceans have been carried out, and very limited research work on scouring around a bluff-shaped gravity anchor. The objective of this study involves the application of different numerical models to simulate the anchor towing under waves and calm water conditions. Anchor lowering involves the investigation of anchor movements at certain water depths under wave/current. The motions of anchor drift, heave, and pitch is of special focus. The further study involves anchor scour, where the anchor is installed in the seabed; the flow of underwater current around the anchor induces vortices mainly at the front and corners that develop soil erosion. The study of scouring on a submerged gravity anchor is an interesting research question since the flow not only passes around the anchor but also over the structure that forms different flow vortices. The achieved results and the numerical model will be a basis for the development of other designs and concepts for marine structures. The Computational Fluid Dynamics (CFD) numerical model will build in OpenFOAM and other similar software.

Keywords: anchor lowering, anchor towing, gravity anchor, computational fluid dynamics, scour

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Authors: Valiollah Babaeipour, Mahdi Rahaie

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food supplements are rich in specific nutrients and bioactive compounds that eliminate free radicals and improve cellular metabolism. The major bioactive compounds are found in bran and cereal sprouts. Secondary metabolites of these microorganisms have antioxidant properties that can be used alone or in combination with chemotherapy and radiation therapy to treat cancer. Biologically active compounds such as benzoquinone derivatives extracted from fermented wheat germ extract (FWGE) have several positive effects on the overall state of human health and strengthen the immune system. The present work describes the discontinuous fermentation of raw wheat germ for FWGE production through the simultaneous culture process using the probiotic strains of Saccharomyces cerevisiae, Lactobacillus plantarum, and the possibility of using solid waste. To increase production efficiency, first to select important factors in the optimization of each fermentation process, using a factorial statistical scheme of stirring fraction (120 to 200 rpm), dilution of solids to solvent (1 to 8-12), fermentation time (16 to 24 hours) and strain to wheat germ ratio (20% to 50%) were studied and then simultaneous culture was performed to increase the yields of 2 and 6 dimethoxybenzoquinone (2,6-DMBQ). Since 2 and 6 dimethoxy benzoquinone were fermented as the main biologically active compound in wheat germ extract, UV-Vis analysis was performed to confirm the presence of 2 and 6 dimethoxy benzoquinone in the final product. In addition, 2,6-DMBQ of some products was isolated in a non-polar C-18 column and quantified using high performance liquid chromatography (HPLC). Based on our findings, it can be concluded that the increase of 2 and 6 dimethoxybenzoquinone in the simultaneous culture of Saccharomyces cerevisiae - Lactobacillus plantarum compared to pure culture of Saccharomyces cerevisiae (from 1.89 mg / g) to 28.9% (2.66 mg / g) Increased.

Keywords: wheat germ, FWGE, saccharomyces cerevisiae, lactobacillus plantarum, co-culture, 2, 6-DMBQ

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Authors: Anaelle Gabet, Helene Metivier, Christine De Brauer, Gilles Mailhot, Marcello Brigante

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The presence of micropollutants in surface waters has been widely reported around the world, particularly downstream from wastewater treatment plants (WWTPs). Rural WWTPs constitute more than 90 % of the total WWTPs in France. Like conventional ones, they are not able to fully remove micropollutants. Estrogens are excreted by human beings every day and several studies have highlighted their endocrine disruption properties on river wildlife. They are mainly estrone (E1), 17β-estradiol (E2) and 17α-ethinylestradiol (EE2). Rural WWTPs require cheap and robust tertiary processes. UVC activation of H₂O₂ for HO· generation, a very reactive molecule, has demonstrated its effectiveness. However, UVC rays are dangerous to manipulate and energy-consuming. This is why the ability of UVA rays was investigated in this study. Moreover, the use of S₂O₈²⁻ for SO₄·- generation as an alternative to HO· has emerged in the last few years. Such processes have been widely studied on a lab scale. However, pilot-scale works constitute fewer studies. This study was carried out on a 20-L pilot composed of a 1.12-L UV reactor equipped with a polychromatic UVA lamp or a monochromatic (254 nm) UVC lamp fed in recirculation. Degradation rates of a mixture of spiked E1, E2 and EE2 (5 µM each) were followed by HPLC-UV. Results are expressed in UV dose (mJ.cm-2) received by the compounds of interest to compare UVC and UVA. In every system, estrogen degradation rates followed pseudo-first-order rates. First, experiments were carried out in tap water. All estrogens underwent photolysis under UVC rays, although E1 photolysis is higher. However, only very weak photolysis was observed under UVA rays. Preliminary studies on both oxidants have shown that S₂O₈²⁻ photolysis constants are higher than H₂O₂ under both UVA and UVC rays. Therefore, estrogen degradation rates are about ten times higher in the presence of 1 mM of S₂O₈²⁻ than with one mM of H₂O₂ under both radiations. In the same conditions, the mixture of interest required about 40 times higher UV dose when using UVA rays compared to UVC. However, the UVA/S₂O₈²⁻ system only requires four times more UV dose than the conventional UVC/H₂O₂ system. Further studies were carried out in WWTP effluent with the UVC lamp. When comparing these results to the tap water ones, estrogen degradation rates were more inhibited in the S₂O₈²⁻ system than with H₂O₂. It seems that SO₄·- undergo higher quenching by a real effluent than HO·. Preliminary experiments have shown that natural organic matter is mainly responsible for the radical quenching and that HO and SO₄ both had similar second-order reaction rate constants with dissolved organic matter. However, E1, E2 and EE2 second-order reaction rate constants are about ten times lower with SO₄ than with HO. In conclusion, the UVA/S₂O₈²⁻ system showed encouraging results for the use of UVA rays but further studies in WWTP effluent have to be carried out to confirm this interest. The efficiency of other pollutants in the real matrix also needs to be investigated.

Keywords: AOPs, decontamination, estrogens, radicals, wastewater

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Authors: Elvis Nyirenda

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This research study work was done to evaluate and propose an optimum measure to enhance the uptake of clean energy technologies such as solar photovoltaics, the study also aims at enhancing the country’s energy mix from the overdependence on hydro power which is susceptible to droughts and climate change challenges The country in the years 2015 - 2016 and 2018 - 2019 had received rainfall below average due to climate change and a shift in the weather pattern; this resulted in prolonged power outages and load shedding for more than 10 hours per day. ZESCO Limited, the utility company that owns infrastructure in the generation, transmission, and distribution of electricity (state-owned), is seeking alternative sources of energy in order to reduce the over-dependence on hydropower stations. One of the alternative sources of energy is Solar Energy from the sun. However, solar power is intermittent in nature and to smoothen the load curve, investment in robust energy storage facilities is of great importance to enhance security and reliability of electricity supply in the country. The methodology of the study looked at the historical performance of the Kafue gorge upper power station and utilised the hourly generation figures as input data for generation modelling in Homer software. The average yearly demand was derived from the available data on the system SCADA. The two dams were modelled as natural battery with the absolute state of charging and discharging determined by the available water resource and the peak electricity demand. The software Homer Energy System is used to simulate the scheme incorporating a pumped storage facility and Solar photovoltaic systems. The pumped hydro scheme works like a natural battery for the conservation of water, with the only losses being evaporation and water leakages from the dams and the turbines. To address the problem of intermittency on the solar resource and the non-availability of water for hydropower generation, the study concluded that utilising the existing Hydro power stations, Kafue Gorge upper and Kafue Gorge Lower to work conjunctively with Solar energy will reduce power deficits and increase the security of supply for the country. An optimum capacity of 350MW of solar PV can be integrated while operating Kafue Gorge power station in both generating and pumping mode to enable efficient utilisation of water at Kafue Gorge upper Dam and Kafue Gorge Lower dam.

Keywords: hydropower, solar power systems, energy storage, photovoltaics, solar irradiation, pumped hydro storage system, supervisory control and data acquisition, Homer energy

Procedia PDF Downloads 94

Authors: S. D. N. K. Bathige, G. I. Godahewa, Navaneethaiyer Umasuthan, Jehee Lee

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Kunitz-type serine protease inhibitors (KTIs) are identified in various organisms including animals, plants and microbes. These proteins shared single or multiple Kunitz inhibitory domains link together or associated with other types of domains. Characteristic Kunitz type domain composed of around 60 amino acid residues with six conserved cysteine residues to stabilize by three disulfide bridges. KTIs are involved in various physiological processes, such as ion channel blocking, blood coagulation, fibrinolysis and inflammation. In this study, two Kunitz-type domain containing protein was identified from rock bream database and designated as RbKunitz. The coding sequence of RbKunitz encoded for 507 amino acids with 56.2 kDa theoretical molecular mass and 5.7 isoelectric point (pI). There are several functional domains including MANEC superfamily domain, PKD superfamily domain, and LDLa domain were predicted in addition to the two characteristic Kunitz domain. Moreover, trypsin interaction sites were also identified in Kunitz domain. Homology analysis revealed that RbKunitz shared highest identity (77.6%) with Takifugu rubripes. Completely conserved 28 cysteine residues were recognized, when comparison of RbKunitz with other orthologs from different taxonomical groups. These structural evidences indicate the rigidity of RbKunitz folding structure to achieve the proper function. The phylogenetic tree was constructed using neighbor-joining method and exhibited that the KTIs from fish and non-fish has been evolved in separately. Rock bream was clustered with Takifugu rubripes. The SYBR Green qPCR was performed to quantify the RbKunitz transcripts in different tissues and challenged tissues. The mRNA transcripts of RbKunitz were detected in all tissues (muscle, spleen, head kidney, blood, heart, skin, liver, intestine, kidney and gills) analyzed and highest transcripts level was detected in gill tissues. Temporal transcription profile of RbKunitz in rock bream blood tissues was analyzed upon LPS (lipopolysaccharide), Poly I:C (Polyinosinic:polycytidylic acid) and Edwardsiella tarda challenge to understand the immune responses of this gene. Compare to the unchallenged control RbKunitz exhibited strong up-regulation at 24 h post injection (p.i.) after LPS and E. tarda injection. Comparatively robust expression of RbKunits was observed at 3 h p.i. upon Poly I:C challenge. Taken together all these data indicate that RbKunitz may involve into to immune responses upon pathogenic stress, in order to protect the rock bream.

Keywords: Kunitz-type, rock bream, immune response, serine protease inhibitor

Procedia PDF Downloads 359

Authors: Maali-Amel Mersel, Lajos Fodor, Otto Horvath

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Photocatalytic H₂ production by H₂S decomposition is regarded to be an environmentally friendly process to produce carbon-free energy through direct solar energy conversion. For this purpose, sulphide-based materials, as photocatalysts, were widely used due to their excellent solar spectrum responses and high photocatalytic activity. The loading of proper co-catalysts that are based on cheap and earth-abundant materials on those semiconductors was shown to play an important role in the improvement of their efficiency. In this research, CdS-ZnS composite was studied because of its controllable band gap and excellent performance for H₂ evolution under visible light irradiation. The effects of the modification of this photocatalyst with different types of materials and the influence of the preparation parameters on its H₂ production activity were investigated. The CdS-ZnS composite with an enhanced photocatalytic activity for H₂ production was synthesized from ammine complexes. Two types of modification were used: compounds of Ni-group metals (NiS, PdS, and Pt) were applied as co-catalyst on the surface of CdS-ZnS semiconductor, while NiS, MnS, CoS, Ag₂S, and CuS were used as a dopant in the bulk of the catalyst. It was found that 0.1% of noble metals didn’t remarkably influence the photocatalytic activity, while the modification with 0.5% of NiS was shown to be more efficient in the bulk than on the surface. The modification with other types of metals results in a decrease of the rate of H₂ production, while the co-doping seems to be more promising. The preparation parameters (such as the amount of ammonia to form the ammine complexes, the order of the preparation steps together with the hydrothermal treatment) were also found to highly influence the rate of H₂ production. SEM, EDS and DRS analyses were made to reveal the structure of the most efficient photocatalysts. Moreover, the detection of the conduction band electron on the surface of the catalyst was also investigated. The excellent photoactivity of the CdS-ZnS catalysts with and without modification encourages further investigations to enhance the hydrogen generation by optimization of the reaction conditions.

Keywords: H₂S, photoactivity, photocatalytic H₂ production, CdS-ZnS

Procedia PDF Downloads 105