Search results for: hierarchical structure model

Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

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Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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Authors: Ruchi Pathania, Ahmad Ahmad, Shireesh Srivastava

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Cyanobacteria is a promising microbe that can capture and convert atmospheric CO₂ and light into valuable industrial bio-products like biofuels, biodegradable plastics, etc. Among their most attractive traits are faster autotrophic growth, whole year cultivation using non-arable land, high photosynthetic activity, much greater biomass and productivity and easy for genetic manipulations. Cyanobacteria store carbon in the form of glycogen which can be hydrolyzed to release glucose and fermented to form bioethanol or other valuable products. Marine cyanobacterial species are especially attractive for countries with scarcity of freshwater. We recently identified a marine native cyanobacterium Synechococcus sp. BDU 130192 which has good growth rate and high level of polyglucans accumulation compared to Synechococcus PCC 7002. In this study, firstly we sequenced the whole genome and the sequences were annotated using the RAST server. Genome scale metabolic model (GSMM) was reconstructed through COBRA toolbox. GSMM is a computational representation of the metabolic reactions and metabolites of the target strain. GSMMs construction through the application of Flux Balance Analysis (FBA), which uses external nutrient uptake rates and estimate steady state intracellular and extracellular reaction fluxes, including maximization of cell growth. The model, which we have named isyn942, includes 942 reactions and 913 metabolites having 831 metabolic, 78 transport and 33 exchange reactions. The phylogenetic tree obtained by BLAST search revealed that the strain was a close relative of Synechococcus PCC 7002. The flux balance analysis (FBA) was applied on the model iSyn942 to predict the theoretical yields (mol product produced/mol CO₂ consumed) for native and non-native products like acetone, butanol, etc. under phototrophic condition by applying metabolic engineering strategies. The reported strain can be a viable strain for biotechnological applications, and the model will be helpful to researchers interested in understanding the metabolism as well as to design metabolic engineering strategies for enhanced production of various bioproducts.

Keywords: cyanobacteria, flux balance analysis, genome scale metabolic model, metabolic engineering

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Authors: Lei Ren, Michael Hartnett, Stephen Nash

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The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

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Authors: Muhammad Shahzad Tufail, Iram Liaqat

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Silver nanoparticles (AgNPs) have wider biomedical applications due to their intensive antimicrobial activities. However, toxicity and side effects of nanomaterials like AgNPs is a subject of great controversy towards the further studies in this direction. In this study, biogenically synthesized AgNPs, previously characterized via ultraviolet (UV) visible spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD) and fourier transform infrared spectroscopy (FTIR), were subjected to toxicity evaluation using mice model. Albino male mice (BALB/c) were administered with 50 mgkg-1, 100 mgkg-1 and 150 mgkg-1 of AgNPs, respectively, except for control for 30 days. Log-probit regression analysis was used to measure the dosage response to determine the median lethal dose (LD50). Exposure to AgNPs caused significant changes in the levels of serum AST (P ˂ 0.05) at the 100mgkg-1 and 150mgkg-1 of AgNPs exposure, while ALT and serum creatinine (P ˃ 0.05) levels remained normal. Histopathology of male albino mice liver and kidney was studied after 30 days experimental period. Results revealed that mice exposed to heavy dose (150 mgkg-1) of AgNPs showed cell distortion, necrosis and detachment of hepatocytes in the liver. Regarding kidney, at lower concentration, normal renal structure with normal glomeruli was observed. However, at higher concentration (150 mgkg-1), kidneys showed smooth surface and dark red colour with proliferation of podocytes. It can be concluded from present study that biologically synthesized AgNPs are small to be eliminated easily by kidney and therefore the liver and kidney did not show toxicity at low concentrations.

Keywords: silver nanoparticles, pseudomonas aeruginosa, male albino mice, toxicity assessment

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Authors: M. Macchiaroli, L. Dolores, V. Pellecchia

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With the recent Resolution n. 580/2019/R/idr, the Italian Regulatory Authority for Energy, Networks, and Environment (ARERA) for the Urban Water Management has introduced, for water managements characterized by persistent critical issues regarding the planning and organization of the service and the implementation of the necessary interventions for the improvement of infrastructures and management quality, a new mechanism for determining tariffs: the regulatory scheme of Convergence. The aim of this regulatory scheme is the overcoming of the Water Service Divided in order to improve the stability of the local institutional structures, technical quality, contractual quality, as well as in order to guarantee transparency elements for Users of the Service. Convergence scheme presupposes the identification of the cost items to be considered in the tariff in parametric terms, distinguishing three possible cases according to the type of historical data available to the Manager. The study, in particular, focuses on operations that have neither data on tariff revenues nor data on operating costs. In this case, the Manager's Constraint on Revenues (VRG) is estimated on the basis of a reference benchmark and becomes the starting point for defining the structure of the tariff classes, in compliance with the TICSI provisions (Integrated Text for tariff classes, ARERA's Resolution n. 665/2017/R/idr). The proposed model implements the recent studies on optimization models for the definition of tariff classes in compliance with the constraints dictated by TICSI in the application of the Convergence mechanism, proposing itself as a support tool for the Managers and the local water regulatory Authority in the decision-making process.

Keywords: decision-making process, economic evaluation of projects, optimizing tools, urban water management, water tariff

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Authors: Mauricio E. Cruz, Ilse Cervantes, Manuel J. Fabela

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The evaluation of the maneuverability of road vehicles is generally carried out through the use of specialized computer programs due to the advantages they offer compared to the experimental method. These programs are based on purely geometric considerations of the characteristics of the vehicles, such as main dimensions, the location of the axles, and points of articulation, without considering parameters such as weight distribution and magnitude, tire properties, etc. In this paper, we address the problem of maneuverability in a semi-trailer truck to navigate urban streets, maneuvering yards, and parking lots, using the Ackerman principle to propose a kinematic model that, through geometric considerations, it is possible to determine the space necessary to maneuver safely. The model was experimentally validated by conducting maneuverability tests with an articulated vehicle. The measurements were made through a GPS that allows us to know the position, trajectory, and speed of the vehicle, an inertial motion unit (IMU) that allows measuring the accelerations and angular speeds in the semi-trailer, and an instrumented steering wheel that allows measuring the angle of rotation of the flywheel, the angular velocity and the torque applied to the flywheel. To obtain the steering angle of the tires, a parameterization of the complete travel of the steering wheel and its equivalent in the tires was carried out. For the tests, 3 different angles were selected, and 3 turns were made for each angle in both directions of rotation (left and right turn). The results showed that the proposed kinematic model achieved 95% accuracy for speeds below 5 km / h. The experiments revealed that that tighter maneuvers increased significantly the space required and that the vehicle maneuverability was limited by the size of the semi-trailer. The maneuverability was also tested as a function of the vehicle load and 3 different load levels we used: light, medium, and heavy. It was found that the internal turning radii also increased with the load, probably due to the changes in the tires' adhesion to the pavement since heavier loads had larger contact wheel-road surfaces. The load was found as an important factor affecting the precision of the model (up to 30%), and therefore I should be considered. The model obtained is expected to be used to improve maneuverability through a robust control system.

Keywords: articuled vehicle, experimental validation, kinematic model, maneuverability, semi-trailer truck

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Authors: J. P. P. Andrade, V. A. F. Campos

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This work presents an application of Linear Matrix Inequalities (LMI) for the robust control of an F-16 aircraft through an algorithm ensuring the damping factor to the closed loop system. The results show that the zero and gain settings are sufficient to ensure robust performance and stability with respect to various operating points. The technique used is the pole placement, which aims to put the system in closed loop poles in a specific region of the complex plane. Test results using a dynamic model of the F-16 aircraft are presented and discussed.

Keywords: F-16 aircraft, linear matrix inequalities, pole placement, robust control

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Authors: Massy Guillaume

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Introduction: The implementation of creativity in educational policies or curricula raises several issues, including the evaluation of creativity and the means to do so. This doctoral research focuses on the appropriation and transposition of creativity assessment models by future teachers. Our objective is to identify the elements of the models that are most transferable to practice in order to improve their implementation in the students' curriculum while seeking to create a new model for assessing creativity in the school environment. Methods: In order to meet our objective, this preliminary quantitative exploratory study by questionnaire was conducted at two points in the participants' training: at the beginning of the training module and throughout the practical work. The population is composed of 40 people of diverse origins with an average age of 26 (s:8,623) years. In order to be as close as possible to our research objective and to test our questionnaires, we set up a pre-test phase during the spring semester of 2022. Results: The results presented focus on aspects of the OECD Creative Competencies Assessment Model. Overall, 72% of participants support the model's focus on skill levels as appropriate for the school context. More specifically, the data indicate that the separation of production and process in the rubric facilitates observation by the assessor. From the point of view of transposing the grid into teaching practice, the participants emphasised that production is easier to plan and observe in students than in the process. This difference is reinforced by a lack of knowledge about certain concepts such as innovation or risktaking in schools. Finally, the qualitative results indicate that the addition of multiple levels of competencies to the OECD rubric would allow for better implementation in the classroom. Conclusion: The identification by the students of the elements allowing the evaluation of creativity in the school environment generates an innovative approach to the training contents. These first data, from the test phase of our research, demonstrate the difficulty that exists between the implementation of an evaluation model in a training program and its potential transposition by future teachers.

Keywords: creativity, evaluation, schooling, training

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Authors: Ainura Tursunalieva, Irene Hudson

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Continuous improvement of both the quality and safety of health care is an important goal in Australia and internationally. The intensive care unit (ICU) receives patients with a wide variety of and severity of illnesses. Accurately identifying patients at risk of developing complications or dying is crucial to increasing healthcare efficiency. Thus, it is essential for clinicians and researchers to have a robust framework capable of evaluating the risk profile of a patient. ICU scoring systems provide such a framework. The Acute Physiology and Chronic Health Evaluation III and the Simplified Acute Physiology Score II are ICU scoring systems frequently used for assessing the severity of acute illness. These scoring systems collect multiple risk factors for each patient including physiological measurements then render the assessment outcomes of individual risk factors into a single numerical value. A higher score is related to a more severe patient condition. Furthermore, the Mortality Probability Model II uses logistic regression based on independent risk factors to predict a patient’s probability of mortality. An important overlooked limitation of SAPS II and MPM II is that they do not, to date, include interaction terms between a patient’s vital signs. This is a prominent oversight as it is likely there is an interplay among vital signs. The co-existence of certain conditions may pose a greater health risk than when these conditions exist independently. One barrier to including such interaction terms in predictive models is the dimensionality issue as it becomes difficult to use variable selection. We propose an innovative scoring system which takes into account a dependence structure among patient’s vital signs, such as systolic and diastolic blood pressures, heart rate, pulse interval, and peripheral oxygen saturation. Copulas will capture the dependence among normally distributed and skewed variables as some of the vital sign distributions are skewed. The estimated dependence parameter will then be incorporated into the traditional scoring systems to adjust the points allocated for the individual vital sign measurements. The same dependence parameter will also be used to create an alternative copula-based model for predicting a patient’s probability of mortality. The new copula-based approach will accommodate not only a patient’s trajectories of vital signs but also the joint dependence probabilities among the vital signs. We hypothesise that this approach will produce more stable assessments and lead to more time efficient and accurate predictions. We will use two data sets: (1) 250 ICU patients admitted once to the Chui Regional Hospital (Kyrgyzstan) and (2) 37 ICU patients’ agitation-sedation profiles collected by the Hunter Medical Research Institute (Australia). Both the traditional scoring approach and our copula-based approach will be evaluated using the Brier score to indicate overall model performance, the concordance (or c) statistic to indicate the discriminative ability (or area under the receiver operating characteristic (ROC) curve), and goodness-of-fit statistics for calibration. We will also report discrimination and calibration values and establish visualization of the copulas and high dimensional regions of risk interrelating two or three vital signs in so-called higher dimensional ROCs.

Keywords: copula, intensive unit scoring system, ROC curves, vital sign dependence

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: Adebayo J. Julius, Oluremi N. Iluyomade

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Livelihood in Nigeria is a paradox of poverty amidst plenty. The Country is endowed with a good climate for agriculture, naturally growing fruit trees and vegetables, and undomesticated water resources. In spite of all its endowment, Nigeria continues to live in poverty year in year out. Rural communities adopted for this study are Ido, Omi-Adio, Onigambari, Okija and Lambata, 500 questionnaires were administered to solicit information from the respondents. This study focused on comparative analysis of the utilization of community informatics for sustainable livelihoods through agriculture. The idea projected in this study is that small strategic changes in the modus operandi of social informatics can have a significant impact on the sustainability of livelihoods. This paper carefully explored the theories of community informatics and its efficacies in dealing with sustainability issues. This study identified, described and evaluates the roles of community informatics in some sectors of the economy, different analytical tools to benchmark the influence of social informatics in agriculture against what is obtainable in agricultural sectors of the economy were used. It further employed comparative analysis to build a case model for sustainable livelihood in agriculture through community informatics.

Keywords: informatics, model, rural community, livelihood, Nigeria

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Authors: Michael Campbell, Malaz Elsaddig, Kevin Jones

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Background: Despite encouraging progress, global maternal mortality has remained stubbornly high since the declaration of the Millennium development goals. Sub-Saharan Africa accounts for well over half of maternal deaths with Post-Partum Haemorrhage (PPH) being the lead cause. ‘In house’ simulation training delivered by local doctors may be a sustainable approach for improving emergency obstetric care. The aim of this study was to evaluate the use of a Train-the-Trainer (TtT) model in a rural Ugandan hospital to ascertain whether it can feasibly improve practitioners’ management of PPH. Methods: Three Ugandan doctors underwent a training course to enable them to design and deliver simulation training. These doctors used MamaNatalie® models to simulate PPH scenarios for midwives, nurses and medical students. The main outcome was improvement in participants’ knowledge and confidence, assessed using self-reported scores on a 10-point scale. Results: The TtT model produced significant improvements in the confidence and knowledge scores of the ten participants. The mean confidence score rose significantly (p=0.0005) from 6.4 to 8.6 following the simulation training. There was also a significant increase in the mean knowledge score from 7.2 to 9.0 (p=0.04). Medical students demonstrated the greatest overall increase in confidence scores whilst increases in knowledge scores were largest amongst nurses. Conclusions: This study demonstrates that a TtT model can be used in a low resource setting to improve healthcare professionals’ confidence and knowledge in managing obstetric emergencies. This Train-the-Trainer model represents a sustainable approach to addressing skill deficits in low resource settings. We believe that its expansion across healthcare institutions in Sub-Saharan Africa will help to reduce the region’s high maternal mortality rate and step closer to achieving the ambitions of the Millennium development goals.

Keywords: low resource setting, post-partum haemorrhage, simulation training, train the trainer

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Authors: Hayat Omar

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Languages provide speakers with a wide range of linguistic units to organize and deliver information. There are several ways to verbally express the mental representations of events. According to the linguistic tools they have acquired, speakers select the one that brings out the most communicative effect to convey their message. Our study focuses on two markers, -mm and dämmo, in Amharic (Ethiopian Semitic language). Our aim is to examine, from a developmental perspective, how they are used by speakers. We seek to distinguish the communicative and pragmatic functions indicated by means of these markers. To do so, we created a corpus of sixty narrative productions of children from 5-6, 7-8 to 10-12 years old and adult Amharic speakers. The experimental material we used to collect our data is a series of pictures without text 'Frog, Where are you?'. Although -mm and dämmo are each used in specific contexts, they are sometimes analyzed as being interchangeable. The suffix -mm is complex and multifunctional. It marks the end of the negative verbal structure, it is found in the relative structure of the imperfect, it creates new words such as adverbials or pronouns, it also serves to coordinate words, sentences and to mark the link between macro-propositions within a larger textual unit. -mm was analyzed as marker of insistence, topic shift marker, element of concatenation, contrastive focus marker, 'bisyndetic' coordinator. On the other hand, dämmo has limited function and did not attract the attention of many authors. The only approach we could find analyzes it in terms of 'monosyndetic' coordinator. The paralleling of these two elements made it possible to understand their distinctive functions and refine their description. When it comes to marking a referent, the choice of -mm or dämmo is not neutral, depending on whether the tagged argument is newly introduced, maintained, promoted or reintroduced. The presence of these morphemes explains the inter-phrastic link. The information is seized by anaphora or presupposition: -mm goes upstream while dämmo arrows downstream, the latter requires new information. The speaker uses -mm or dämmo according to what he assumes to be known to his interlocutors. The results show that -mm and dämmo, although all the speakers use them both, do not always have the same scope according to the speaker and vary according to the age. dämmo is mainly used to mark a contrastive topic to signal the concomitance of events. It is more commonly used in young children’s narratives (F(3,56) = 3,82, p < .01). Some values of -mm (additive) are acquired very early while others are rather late and increase with age (F(3,56) = 3,2, p < .03). The difficulty is due not only because of its synthetic structure but primarily because it is multi-purpose and requires a memory work. It highlights the constituent on which it operates to clarify how the message should be interpreted.

Keywords: acquisition, cohesion, connection, contrastive topic, contrastive focus, discourse marker, pragmatics

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Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Marzieh Khedmati, Shannon L. Bartelt-Hunt

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Vegetative Filter Strips (VFS) are used for controlling the volume of runoff and decreasing contaminant concentrations in runoff before entering water bodies. Many studies have investigated the role of VFS in sediment and nutrient removal, but little is known about their efficiency for the removal of emerging contaminants such as antimicrobial resistance genes (ARGs). Vegetative Filter Strip Modeling System (VFSMOD) was used to simulate the efficiency of VFS in this regard. Several studies demonstrated the ability of VFSMOD to predict reductions in runoff volume and sediment concentration moving through the filters. The objectives of this study were to calibrate the VFSMOD with experimental data and assess the efficiency of the model in simulating the filter behavior in removing ARGs (ermB) and tylosin. The experimental data were obtained from a prior study conducted at the University of Nebraska (UNL) Rogers Memorial Farm. Three treatment factors were tested in the experiments, including manure amendment, narrow grass hedges and rainfall events. Sediment Delivery Ratio (SDR) was defined as the filter efficiency and the related experimental and model values were compared to each other. The VFS Model generally agreed with the experimental results and as a result, the model was used for predicting filter efficiencies when the runoff data are not available. Narrow Grass Hedges (NGH) were shown to be effective in reducing tylosin and ARGs concentration. The simulation showed that the filter efficiency in removing ARGs is different for different soil types and filter lengths. There is an optimum length for the filter strip that produces minimum runoff volume. Based on the model results increasing the length of the filter by 1-meter leads to higher efficiency but widening beyond that decreases the efficiency. The VFSMOD, which was proved to work well in estimation of VFS trapping efficiency, showed confirming results for ARG removal.

Keywords: antimicrobial resistance genes, emerging contaminants, narrow grass hedges, vegetative filter strips, vegetative filter strip modeling system

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Authors: Merouane Salhi, Toufik Zebbiche, Omar Abada

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When the stagnation pressure of perfect gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with this pressure. The gas does not remain perfect. Its state equation change and it becomes a real gas. In this case, the effects of molecular size and inter molecular attraction forces intervene to correct the state equation. The aim of this work is to show and discuss the effect of stagnation pressure on supersonic thermo dynamical, physical and geometrical flow parameters, to find a general case for real gas. With the assumptions that Berthelot’s state equation accounts for molecular size and inter molecular force effects, expressions are developed for analyzing supersonic flow for thermally and calorically imperfect gas lower than the dissociation molecules threshold. The designs parameters for supersonic nozzle like thrust coefficient depend directly on stagnation parameters of the combustion chamber. The application is for air. A computation of error is made in this case to give a limit of perfect gas model compared to real gas model.

Keywords: supersonic flow, real gas model, Berthelot’s state equation, Simpson’s method, condensation function, stagnation pressure

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Authors: Raghad Alhusari, Farag Omar, Moustafa Fadel

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A traditional greenhouse is a metal frame agricultural building used for cultivation plants in a controlled environment isolated from external climatic changes. Using greenhouses in agriculture is an efficient way to reduce the water consumption, where agriculture field is considered the biggest water consumer world widely. Controlling greenhouse environment yields better productivity of plants but demands an increase of electric power. Although various control approaches have been used towards greenhouse automation, most of them are applied to traditional greenhouses with ventilation fans and/or evaporation cooling system. Such approaches are still demanding high energy and water consumption. The aim of this research is to develop a fuzzy control system that minimizes water and energy consumption by utilizing outside weather conditions and underground heat exchanger to maintain the optimum climate of the greenhouse. The proposed control system is implemented on an experimental model of thermally isolated greenhouse structure with dimensions of 6x5x2.8 meters. It uses fans for extracting heat from the ground heat exchanger system, motors for automatic open/close of the greenhouse windows and LED as lighting system. The controller is integrated also with environmental condition sensors. It was found that using the air-to-air horizontal ground heat exchanger with 90 mm diameter and 2 mm thickness placed 2.5 m below the ground surface results in decreasing the greenhouse temperature of 3.28 ˚C which saves around 3 kW of consumed energy. It also eliminated the water consumption needed in evaporation cooling systems which are traditionally used for cooling the greenhouse environment.

Keywords: automation, earth-to-air heat exchangers, fuzzy control, greenhouse, sustainable buildings

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Authors: Enyia James Diwa, Dodeye Ina Igbong, Archibong Eso Archibong

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The creep life of an industrial gas turbine is determined through a physics-based model used to investigate the high pressure temperature (HPT) of the blade in use. A performance model was carried out via the Cranfield University TURBOMATCH simulation software to size the blade and to determine the corresponding stress. Various effects such as radial temperature distortion factor, turbine entry temperature, ambient temperature, blade metal temperature, and compressor degradation on the blade creep life were investigated. The output results show the difference in creep life and the location of failure along the span of the blade enabling better-informed advice for the gas turbine operator.

Keywords: creep, living, performance, degradation

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Authors: H. Hotait, X. Chiementin, L. Rasolofondraibe

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This paper presents a continuous work to detect the abnormal state in the rolling bearing by studying the vibration signature analysis and calculation of the remaining useful life. To achieve these aims, two methods; the first method is the classification to detect the degradation state by the AOM-OPTICS (Acousto-Optic Modulator) method. The second one is the prediction of the degradation state using least-squares support vector regression and then compared with the linear degradation model. An experimental investigation on ball-bearing was conducted to see the effectiveness of the used method by applying the acquired vibration signals. The proposed model for predicting the state of bearing gives us accurate results with the experimental and numerical data.

Keywords: bearings, automatization, optimization, prognosis, classification, defect detection

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

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Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, prediction modeling, rail track degradation

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Authors: H. Aksas, H. Babaci, K. Louhab

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In this paper, a comparative study of the adsorption of Chromium and dyes, onto mixture biosorbents, olive stones and date pits at different percentage was investigated in aqueous solution. The study of various parameters: Effect of contact time, pH, temperature and initial concentration shows that these materials possess a high affinity for the adsorption of chromium for the adsorption of dye bezaktiv yellow HE-4G. To deepen the comparative study of the adsorption of chromium and dye with the use of different blends of olive stones and date pits, the following models are studied: Langmuir, Freundlich isotherms and Dubinin- Radushkvich (D-R) were used as the adsorption equilibrium data model. Langmuir isotherm model was the most suitable for the adsorption of the dye bezaktiv HE-4G and the D-R model is most suitable for adsorption Chrome. The pseudo-first-order model, pseudo-second order and intraparticle diffusion were used to describe the adsorption kinetics. The apparent activation energy was found to be less than 8KJ/mol, which is characteristic of a controlled chemical reaction for the adsorption of two materials. t was noticed that adsorption of chromium and dye BEZAKTIV HE-YELLOW 4G follows the kinetics of the pseudo second order. The study of the effect of temperature was quantified by calculating various thermodynamic parameters such as Gibbs free energy, enthalpy and entropy changes. The resulting thermodynamic parameters indicate the endothermic nature of the adsorption of Cr (VI) ions and the dye Bezaktiv HE-4G. But these materials are very good adsorbents, as they represent a low cost. in addition, it has been noticed that the greater the quantity of olive stone in the mixture increases, the adsorption ability of the dye or chromium increases.

Keywords: chromium ions, anions dye, sorption, mixed adsorbents, olive stone, date pits

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Authors: Nazia Mustafa, Aneela Maqsood

Abstract:

Pediatric Quality of Life Inventory is the most widely used instrument for assessing children and adolescent health-related quality of life and has shown excellent markers of reliability and validity. The current study was carried out with the objectives of translation and cross-language validation along with the determination of factor Structure and psychometric properties of the Urdu version. It was administered on 154 Primary School Children with age range 10 to12 years (M= 10.86, S.D = 0.62); including boys (n=92) and girls (n = 62). The sample was recruited from two randomly selected schools from the Rawalpindi district of Pakistan. Results of the pilot phase revealed that the instrument had good reliability (Urdu Version α = 0.798; English Version α = 0.795) as well as test-retest correlation coefficients over a period of 15 days (r = 0.85). Exploratory factor analysis (EFA) resulted in three factorial structures; Social/School Functioning (k = 8), Psychological Functioning (k = 7) and Physical Functioning (k = 6) considered suitable for our sample instead of four factors. Bartlett's test of sphericity showed inter-correlation between variables. However, factor loadings for items 22 and 23 of the School Functioning subscale were problematic. The model was fit to the data after their removal with Cronbach’s Alpha Reliability coefficient of the scale (k = 21) as 0.87 and for subscales as 0.75, 0.77 and 0.73 for Social/School Scale, Psychological subscale and Physical subscale, respectively. These results supported the feasibility and reliability of the Urdu version of the Pediatric Quality of Life Inventory as a reliable and effective tool for the measurement of quality of life among Pediatrics Pakistani population.

Keywords: primary school children, paediatric quality of life, exploratory factor analysis, Pakistan

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Authors: Jamal Fayazi, Farhad Anoosheh, Mohammad R. Ghorbani, Ali R. Paydar

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In this study, to determine the best non-linear regression model describing the growth curve of native poultry, 9657 chicks of generations 18, 19, and 20 raised in Mazandaran breeding center were used. Fowls and roosters of this center distributed in south of Caspian Sea region. To estimate the genetic variability of none linear regression parameter of growth traits, a Gibbs sampling of Bayesian analysis was used. The average body weight traits in the first day (BW1), eighth week (BW8) and twelfth week (BW12) were respectively estimated as 36.05, 763.03, and 1194.98 grams. Based on the coefficient of determination, mean squares of error and Akaike information criteria, Gompertz model was selected as the best growth descriptive function. In Gompertz model, the estimated values for the parameters of maturity weight (A), integration constant (B) and maturity rate (K) were estimated to be 1734.4, 3.986, and 0.282, respectively. The direct heritability of BW1, BW8 and BW12 were respectively reported to be as 0.378, 0.3709, 0.316, 0.389, 0.43, 0.09 and 0.07. With regard to estimated parameters, the results of this study indicated that there is a possibility to improve some property of growth curve using appropriate selection programs.

Keywords: direct heritability, Gompertz, growth traits, maturity weight, native poultry

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Authors: Noureddine Radouai

Abstract:

Corruption is an endemic phenomenon in many countries around the globe. Morocco, as an authoritarian regime, relies on corruption for monarchy survival. I analyze the Makhzen structure and methods that it follows to exchange corruption for political loyalty. The abuse of power in Morocco is sponsored by the monarch itself as it is its way to remain its importance in the regime.

Keywords: corruption, Clientelism, authoritarian regime, Morocco

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Authors: Ashique Mahmud, MD. Ataul Gani Osmani, Shoria Sharmin

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In the first quarter of the twenty-first century, the most substantial global concern is environmental contamination, and it has gained the prioritization of both the national and international community. Keeping in mind this crucial fact, this study conducted different statistical and econometrical methods to identify whether the gross national income of the country has a significant impact on electricity production from nonrenewable sources and different air pollutants like carbon dioxide, nitrous oxide, and methane emissions. Besides, the primary objective of this research was to analyze whether the environmental Kuznets curve hypothesis holds for the examined variables. After analyzing different statistical properties of the variables, this study came to the conclusion that the environmental Kuznets curve hypothesis holds for gross national income and carbon dioxide emission in Bangladesh in the short run as well as the long run. This study comes to this conclusion based on the findings of ordinary least square estimations, ARDL bound tests, short-run causality analysis, the Error Correction Model, and other pre-diagnostic and post-diagnostic tests that have been employed in the structural model. Moreover, this study wants to demonstrate that the outline of gross national income and carbon dioxide emissions is in its initial stage of development and will increase up to the optimal peak. The compositional effect will then force the emission to decrease, and the environmental quality will be restored in the long run.

Keywords: environmental Kuznets curve hypothesis, carbon dioxide emission in Bangladesh, gross national income in Bangladesh, autoregressive distributed lag model, granger causality, error correction model

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Authors: Sepideh Samadzadehyazdi, Mohammad Javad Khalili, Sarvenaz Samadzadehyazdi, Mohammad Javad Mahdavinejad

Abstract:

The term ‘Windphil Architecture’ refers to the building that facilitates natural ventilation by architectural elements. Natural ventilation uses the natural forces of wind pressure and stacks effect to direct the movement of air through buildings. Natural ventilation is increasingly being used in contemporary buildings to minimize the consumption of non-renewable energy and it is an effective way to improve indoor air quality. The main objective of this paper is to identify the strategies of using natural ventilation in Iranian modern buildings. In this regard, the research method is ‘descriptive-analytical’ that is based on comparative techniques. To simulate wind flow in the interior spaces of case studies, FLUENT software has been used. Research achievements show that it is possible to use natural ventilation to create a thermally comfortable indoor environment. The natural ventilation strategies could be classified into two groups of environmental characteristics such as public space structure, and architectural characteristics including building form and orientation, openings, central courtyards, wind catchers, roof, wall wings, semi-open spaces and the heat capacity of materials. Having investigated modern buildings of Iran, innovative elements like wind catchers and wall wings are less used than the traditional architecture. Instead, passive ventilation strategies have been more considered in the building design as for the roof structure and openings.

Keywords: natural ventilation strategies, wind catchers, wind flow, Iranian modern buildings

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Authors: H. Triki, Y. Hamaizi, A. El-Akrmi

Abstract:

We consider the higher order nonlinear Schrödinger equation model with fourth-order dispersion, cubic-quintic terms, and self-steepening. This equation governs the propagation of fem to second pulses in optical fibers. We present new bright and dark solitary wave type solutions for such a model under certain parametric conditions. This kind of solution may be useful to explain some physical phenomena related to wave propagation in a nonlinear optical fiber systems supporting high-order nonlinear and dispersive effects.

Keywords: nonlinear Schrödinger equation, high-order effects, soliton solution

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Authors: M. F. Slim, A. Alhussein, F. Sanchette, M. François

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Thin films are widely used in various applications to enhance the surface properties and characteristics of materials. They are used in many domains such as: biomedical, automotive, aeronautics, military, electronics and energy. Depending on the elaboration technique, the elastic behavior of thin films may be different from this of bulk materials. This dependence on the elaboration techniques and their parameters makes the control of the elasticity constants of coated components necessary. Our work is focused on the characterization of the elasticity constants of isotropic thin films by means of Impulse Excitation Techniques. The tests rely on the measurement of the sample resonance frequency before and after deposition. In this work, a finite element model was performed with ABAQUS software. This model was then compared with the analytical approaches used to determine the Young’s and shear moduli. The best model to determine the film Young’s modulus was identified and a relation allowing the determination of the shear modulus of thin films of any thickness was developed. In order to confirm the model experimentally, Tungsten films were deposited on glass substrates by DC magnetron sputtering of a 99.99% purity tungsten target. The choice of tungsten was done because it is well known that its elastic behavior at crystal scale is ideally isotropic. The macroscopic elasticity constants, Young’s and shear moduli and Poisson’s ratio of the deposited film were determined by means of Impulse Excitation Technique. The Young’s modulus obtained from IET was compared with measurements by the nano-indentation technique. We did not observe any significant difference and the value is in accordance with the one reported in the literature. This work presents a new methodology on the determination of the elasticity constants of thin films using Impulse Excitation Technique. A formulation allowing the determination of the shear modulus of a coating, whatever the thickness, was developed and used to determine the macroscopic elasticity constants of tungsten films. The developed model was validated numerically and experimentally.

Keywords: characterization, coating, dynamical resonant method, Poisson's ratio, PVD, shear modulus, Young's modulus

Procedia PDF Downloads 354