Search results for: workflow provenance

Authors: Jelena Nedeljković Trailović, Marko Vasiljević, Jog Raj, Hunor Farkaš, Branko Petrujkić, Stamen Radulović, Gorana Popvić

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The experiment was performed on a total of 99 one-day-old broilers of Cob 500 provenance, which were divided into IX equal groups. Broilers of the E-I group were fed 0.25 mg T-2 toxin/kg feed, E-II and E-III groups 0.25 mg T-2 toxin/kg feed with the addition of 1 kg/t and 3 kg/t of the mycotoxin detoxification agent MDA, respectively. The E-IV group received 1 mg of T-2 toxin/kg of feed, and the broilers of E-V and E-VI groups received 1 mg of T-2 toxin/kg of feed with the addition of 1 kg/t and 3 kg/t of the MDA detoxification preparation, respectively. The E-VII group received commercial feed without toxins and additives, the E-VIII and E-IX groups received feed with 1kg/t and 3kg/t of the MDA detoxification preparation. The trial lasted 42 days. Observing the results obtained on the 42nd day of the experiment, we can conclude that the change in the absolute mass of the spleen occurred in the broilers of the E-IV group (1.66±0.14)g, which was statistically significantly lower compared to the broilers of the E-V and E-VI groups (2.58±0.15 and 2.68±0.23)g. Heart mass was significantly statistically lower in broilers of group E-IV (9.1±0.38)g compared to broilers of group E-V and E-VI (12.23±0.5 and 11.43±0.51)g. It can be concluded that the broilers that received 1 kg/t and 3 kg/t of the detoxification preparation had an absolute mass of organs within physiological limits. Broilers of the E-IV group achieved the lowest BM during the experiment (on the 42nd day of the experiment 1879±52.73)g, they were significantly statistically lower than the BW of broilers of all experimental groups. This trend is observed from the beginning to the end of the experiment. The protective effect of the detoxification preparation can be seen in broilers of the E-V group, that had a significantly statistically higher BM on the 42nd day of the experiment (2225±58.81)g compared to broilers of group E-IV. Broilers of E-VIII group (2452±46.71) g, which received commercial feed with the addition of 1 kg/t MDA preparation, had the highest BMI at the end of the experiment. At the end of the trial on the 42nd day, blood samples were collected from broilers of the experimental groups that received T-2 toxin and MR detoxification preparations in different concentrations. Also, liver and breast musculature samples were collected for testing for the presence and content of T-2 toxin, HT-2 toxin, T-2 tetraol and T-2 triol. Due to very rapid elimination from the blood, no remains of T-2 toxin and its metabolites were detected in the blood of broilers of groups E-I to E-VI. In the breast muscles, T-2 toxin residues below LoQ < 0.2 (μg/kg) were detected in all groups that received T-2 toxin in food, the highest value was recorded in the E-IV group (0.122 μg/kg and the lowest in E -VI group 0.096 μg/kg). No T-2 toxin residues were detected in the liver. Remains of HT-2 were detected in the breast muscles and livers of broilers from E-IV, E-V and E-VI groups, LoQ < 1 (μg/kg); for the breast muscles: 0.054, 0.044 and 0.041 μg/kg, and for the liver: 0.473, 0.231 and 0.185 μg/kg. Summing up all the results, a partial protective effect of the detoxification preparation, added to food in the amount of 1kg/t, can be seen.

Keywords: T-2 toxin, bloiler, MDA, mycotoxuns

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

Procedia PDF Downloads 140

Authors: Mohamed Al Araby, Amany Salman, Mostafa Amin, Mohamed Madbully, Dalia Keraa, Mariam Ali, Marah Abdelfatah, Mariam Ahmed, Ahmed Hassab

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In recent years, the architecture, engineering, and construction (A.E.C.) industry have been exposed to important innovations, most notably the global integration of digital design and fabrication (D.D.F.) processes in the industry’s workflow. Despite this evolution in that sector, Africa was excluded from the examination of this development. The reason behind this exclusion is the preconceived view of it as a developing region that still employs traditional methods of construction. The primary objective of this review is to investigate the trend of digital construction (D.C.) in the African environment and the difficulties in its regular utilization of it. This objective can be attained by recognizing the notion of distributed computing in Africa and evaluating the impact of the projects deploying this technology on both the immediate and broader contexts. The paper’s methodology begins with the collection of data from 224 initiatives throughout Africa. Then, 50 of these projects were selected based on the criteria of the project's recency, typology variety, and location diversity. After that, a literature-based comparative analysis was undertaken. This study’s findings reveal a pattern of motivation for applying digital fabrication processes. Moreover, it is essential to evaluate the socio-economic effects of these projects on the population living near the analyzed subject. The last step in this study is identifying the influence on the neighboring nations.

Keywords: Africa, digital construction, digital design, fabrication

Procedia PDF Downloads 127

Authors: Sai Rajeev Reddy, Ishita Roy, M. Anji Reddy

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The paper describes the importance of preventive measures and immediate Emergency logistics during accidents and unfortunate Disasters for the Hyderabad Metro Rails in their various stages of construction. This is the need of the modern generation where accidents, explosions, attacks and sudden crisis are frequent casualties which take huge tolls of life in the present world. The paper utilizes the workflow and application of Geographical information System (GIS) to provide information about problems and crisis structures for efficient Metro Transportation in the city. The study analyzes the difficulties and problems which cause accidents during operation and maintenance stages of the Metro Rail. The paper focuses upon the intermediate and firsthand information of Crisis with the help of GIS technology to share Disaster data for effective measures by the Cyber Police stations, Emergency Responders, Hospitals and First Aid Centre to act immediately and save lives. The results and conclusions have nevertheless proved very informative and useful for the safety board authorities of the Hyderabad Metro Rail. The operation and Maintenance are integral stages in the development of any Multipurpose transportation Projects and are usually prone to various Disasters and tragedies. Hence, the GIS technologies help in distribution of information among the masses with the web Technologies and advanced software developed to prevent and manage crisis widely and in a cost-benefits manner.

Keywords: Geographical Information System, emergency assessment, accident zones, surveillance

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Authors: Clement Leroy, Guillaume Boitel

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This paper presents a comparative benchmarking review of a steady and transient three-dimensional (3D) flow computations in centrifugal pump using commercial (AnsysCFX) and open source (OpenFOAM) computational fluid dynamics (CFD) software. In centrifugal rotor-dynamic pump, the fluid enters in the impeller along to the rotating axis to be accelerated in order to increase the pressure, flowing radially outward into another stage, vaned diffuser or volute casing, from where it finally exits into a downstream pipe. Simulations are carried out at the best efficiency point (BEP) and part load, for single-phase flow with several turbulence models. The results are compared with overall performance report from experimental data. The use of CFD technology in industry is still limited by the high computational costs, and even more by the high cost of commercial CFD software and high-performance computing (HPC) licenses. The main objectives of the present study are to define OpenFOAM methodology for high-quality 3D steady and transient turbomachinery CFD simulation to conduct a thorough time-accurate performance analysis. On the other hand a detailed comparisons between computational methods, features on latest Ansys release 18 and OpenFOAM is investigated to assess the accuracy and industrial applications of those solvers. Finally an automated connected workflow (IoT) for turbine blade applications is presented.

Keywords: benchmarking, CFX, internet of things, openFOAM, time-accurate, turbomachinery

Procedia PDF Downloads 178

Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

Procedia PDF Downloads 243

Authors: Pachawo Bisani, Goodall Nyirenda

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The Malawi National Antiretroviral Therapy (NART) Electronic Medical Record (EMR) system was designed and developed with guidance from the Ministry of Health through the Department of HIV and AIDS (DHA) with the aim of supporting the management of HIV patient data and reporting in high prevalence ART clinics. As of 2021, the system has been scaled up to over 206 facilities across the country. The system is integrated with the clinical decision support system (CDSS) to assist healthcare providers in making a decision about an individual patient at a particular point in time. Despite NART EMR undergoing several evaluations and assessments, little has been done to evaluate the clinical decision support system in the NART EMR system. Hence, the study aimed to evaluate the use of CDSS in the NART EMR system in Malawi. The study adopted a mixed-method approach, and data was collected through interviews, observations, and questionnaires. The study has revealed that the CDSS tools were integrated into the ART clinic workflow, making it easy for the user to use it. The study has also revealed challenges in system reliability and information accuracy. Despite the challenges, the study further revealed that the system is effective and efficient, and overall, users are satisfied with the system. The study recommends that the implementers focus more on the logic behind the clinical decision-support intervention in order to address some of the concerns and enhance the accuracy of the information supplied. The study further suggests consulting the system's actual users throughout implementation.

Keywords: clinical decision support system, electronic medical record system, usability, antiretroviral therapy

Procedia PDF Downloads 60

Authors: Andrea M. Rivas-Castillo, Marlenne Gómez-Ramirez, Isela Rodríguez-Pozos, Norma G. Rojas-Avelizapa

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Spent catalysts are considered as hazardous residues of major concern, mainly due to the simultaneous presence of several metals in elevated concentrations. Although hydrometallurgical, pyrometallurgical and chelating agent methods are available to remove and recover some metals contained in spent catalysts; these procedures generate potentially hazardous wastes and the emission of harmful gases. Thus, biotechnological treatments are currently gaining importance to avoid the negative impacts of chemical technologies. To this end, diverse microorganisms have been used to assess the removal of metals from spent catalysts, comprising bacteria, archaea and fungi, whose resistance and metal uptake capabilities differ depending on the microorganism tested. Acidophilic sulfur oxidizing bacteria have been used to investigate the biotreatment and extraction of valuable metals from spent catalysts, namely Acidithiobacillus thiooxidans and Acidithiobacillus ferroxidans, as they present the ability to produce leaching agents such as sulfuric acid and sulfur oxidation intermediates. In the present work, the ability of A. thiooxidans DSM 26636 for the bioleaching of metals contained in five different spent catalysts was assessed by growing the culture in modified Starkey mineral medium (with elemental sulfur at 1%, w/v), and 1% (w/v) pulp density of each residue for up to 21 days at 30 °C and 150 rpm. Sulfur-oxidizing activity was periodically evaluated by determining sulfate concentration in the supernatants according to the NMX-k-436-1977 method. The production of sulfuric acid was assessed in the supernatants as well, by a titration procedure using NaOH 0.5 M with bromothymol blue as acid-base indicator, and by measuring pH using a digital potentiometer. On the other hand, Inductively Coupled Plasma - Optical Emission Spectrometry was used to analyze metal removal from the five different spent catalysts by A. thiooxidans DSM 26636. Results obtained show that, as could be expected, sulfuric acid production is directly related to the diminish of pH, and also to highest metal removal efficiencies. It was observed that Al and Fe are recurrently removed from refinery spent catalysts regardless of their origin and previous usage, although these removals may vary from 9.5 ± 2.2 to 439 ± 3.9 mg/kg for Al, and from 7.13 ± 0.31 to 368.4 ± 47.8 mg/kg for Fe, depending on the spent catalyst proven. Besides, bioleaching of metals like Mg, Ni, and Si was also obtained from automotive spent catalysts, which removals were of up to 66 ± 2.2, 6.2±0.07, and 100±2.4, respectively. Hence, the data presented here exhibit the potential of A. thiooxidans DSM 26636 for the simultaneous bioleaching of metals contained in spent catalysts from diverse provenance.

Keywords: bioleaching, metal removal, spent catalysts, Acidithiobacillus thiooxidans

Procedia PDF Downloads 109

Authors: Riccardo Pasquali, Keith Harlin, Mark Muller

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The ShallowTherm project is focussed on developing and applying a methodology for extrapolating relatively sparsely sampled thermal conductivity measurements across Ireland using mapped Litho-Electrical (LE) units. The primary data used consist of electrical resistivities derived from the Geological Survey Ireland Tellus airborne electromagnetic dataset, GIS-based maps of Irish geology, and rock thermal conductivities derived from both the current Irish Ground Thermal Properties (IGTP) database and a new programme of sampling and laboratory measurement. The workflow has been developed across three case-study areas that sample a range of different calcareous, arenaceous, argillaceous, and volcanic lithologies. Statistical analysis of resistivity data from individual geological formations has been assessed and integrated with detailed lithological descriptions to define distinct LE units. Thermal conductivity measurements from core and hand samples have been acquired for every geological formation within each study area. The variability and consistency of thermal conductivity measurements within each LE unit is examined with the aim of defining a characteristic thermal conductivity (or range of thermal conductivities) for each LE unit. Mapping of LE units, coupled with characteristic thermal conductivities, provides a method of defining thermal conductivity properties at a regional scale and facilitating the design of ground source heat pump closed-loop collectors.

Keywords: thermal conductivity, ground source heat pumps, resistivity, heat exchange, shallow geothermal, Ireland

Procedia PDF Downloads 146

Authors: Marie Davin, Marie-Laure Fauconnier, Gilles Colinet

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In Wallonia, there are 6,000 estimated brownfields (rising to over 3.5 million in Europe) that require remediation. Polycyclic Aromatic Hydrocarbons (PAHs) are a class of recalcitrant carcinogenic/mutagenic organic compounds of major concern as they accumulate in the environment and represent 17% of all encountered pollutants. As an alternative to environmentally aggressive, expensive and often disruptive soil remediation strategies, a lot of research has been directed to developing techniques targeting organic pollutants. The following experiment, based on the observation that PAHs soil content decreases in the presence of plants, aimed at improving our understanding of the underlying mechanisms involved in phytoremediation. It focusses on plant root exudates and whether they improve PAHs solubilization, which would make them more available for bioremediation by soil microorganisms. The effect of saponin, a natural surfactant found in some plant roots such as members of the Fabaceae family, on PAHs solubilization was also investigated as part of the implementation of the experimental protocol. The experiments were conducted on soil collected from a brownfield in Saint-Ghislain (Belgium) and presenting weathered PAHs contamination. Samples of soil were extracted with different solutions containing either plant root exudates or commercial saponin. Extracted PAHs were determined in the different aqueous solutions using High-Performance Liquid Chromatography and Fluorimetric Detection (HPLC-FLD). Both root exudates of alfalfa (Medicago sativa L.) or red clover (Trifolium pratense L.) and commercial saponin were tested in different concentrations. Distilled water was used as a control. First of all, results show that PAHs are more extracted using saponin solutions than distilled water and that the amounts generally rise with the saponin concentration. However, the amount of each extracted compound diminishes as its molecular weight rises. Also, it appears that passed a certain surfactant concentration, PAHs are less extracted. This suggests that saponin might be investigated as a washing agent in polluted soil remediation techniques, either for ex-situ or in-situ treatments, as an alternative to synthetic surfactants. On the other hand, preliminary results on experiments using plant root exudates also show differences in PAHs solubilization compared to the control solution. Further results will allow discussion as to whether or not there are differences according to the exudates provenance and concentrations.

Keywords: brownfield, Medicago sativa, phytoremediation, polycyclic aromatic hydrocarbons, root exudates, saponin, solubilization, Trifolium pratense

Procedia PDF Downloads 226

Authors: Akshay S. Dalvi, Hazim El-Mounayri

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The internal and the external interactions between the complex structural and behavioral characteristics of the complex energy system result in unpredictable emergent behaviors. These emergent behaviors are not well understood, especially when modeled using the traditional top-down systems engineering approach. The intrinsic nature of current complex energy systems has called for an elegant solution that provides an integrated framework in Model-Based Systems Engineering (MBSE). This paper mainly presents a MBSE driven approach to define and handle the complexity that arises due to emergent behaviors. The approach provides guidelines for developing system architecture that leverages in predicting the complexity index of the system at different levels of abstraction. A framework that integrates indefinite and definite modeling aspects is developed to determine the complexity that arises during the development phase of the system. This framework provides a workflow for modeling complex systems using Systems Modeling Language (SysML) that captures the system’s requirements, behavior, structure, and analytical aspects at both problem definition and solution levels. A system architecture for a district cooling plant is presented, which demonstrates the ability to predict the complexity index. The result suggests that complex energy systems like district cooling plant can be defined in an elegant manner using the unconventional modified MBSE driven approach that helps in estimating development time and cost.

Keywords: district cooling plant, energy systems, framework, MBSE

Procedia PDF Downloads 106

Authors: Nahed Al-Hajeri

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There are several reasons which lead to a delay in project completion, out of all, one main reason is the delay in deliverable processing, i.e. submission and review of documents. Most of the project cycles start with a list of deliverables but without a sequence of submission of the same, means without a direction to move, leading to overlapping of activities and more interdependencies. Hence Project Design Deliverables (PDD) is developed as a solution to Organize Transmittals (Documents/Drawings) received from contractors/consultants during different phases of an EPC (Engineering, Procurement, and Construction) projects, which gives proper direction to the stakeholders from the beginning, to reduce inter-discipline dependency, avoid overlapping of activities, provide a list of deliverables, sequence of activities, etc. PDD attempts to provide a list and sequencing of the engineering documents/drawings required during different phases of a Project which will benefit both client and Contractor in performing planned activities through timely submission and review of deliverables. This helps in ensuring improved quality and completion of Project in time. The successful implementation begins with a detailed understanding the specific challenges and requirements of the project. PDD will help to learn about vendor document submissions including general workflow, sequence and monitor the submission and review of the deliverables from the early stages of Project. This will provide an overview for the Submission of deliverables by the concerned during the projects in proper sequence. The goal of PDD is also to hold responsible and accountability of all stakeholders during complete project cycle. We believe that successful implementation of PDD with a detailed list of documents and their sequence will help organizations to achieve the project target.

Keywords: EPC (Engineering, Procurement, and Construction), project design deliverables (PDD), econometrics sciences, management sciences

Procedia PDF Downloads 372

Authors: Susanna Pho

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With the rise in frequency of high impact flooding events and continued growth across the state, communities in Florida are increasingly turning to innovative higher regulatory standards to keep residents safe. Using models and maps that take future conditions into account can help coastal communities at high risk of flooding adapt, but the associated responsibilities of enforcing and educating stakeholders about floodplain management can be a barrier to adoption. This is especially true in communities that are already managing multiple maps, as adding more regulatory mapping may overwhelm resource-constrained building departments. Without effective workflow solutions, even small tasks like communicating regulations to residents or determining the most restrictive mapping for a permit application can become challenging when dealing with complex maps. Using the case study of Forerunner’s work with a partner community, this session will outline how the community combines technology with robust outreach strategies to boost resident communication. We’ll discuss how software like Forerunner can help communities pull together disparate datasets and mobilize information for property-specific outreach to provide smarter resources to a variety of stakeholders. it’ll explore how incorporating digital workflows into outreach can ensure faster response time, better compliance enforcement, and stronger data continuity. The presentation will also include suggestions on how other communities might be able to leverage data to strengthen their floodplain management programs.

Keywords: floodplain management, flood response, flood risk adaptation, flood protection - products and processes, flood risk assessment and recovery, innovative approaches

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Authors: Luis Guiliana, Andrea Osorio

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The lack of comprehension of the reservoir geomechanics conditions may cause operational problems that cost to the industry billions of dollars per year. The drilling operations at the Ceuta Field, Area 2 South, Maracaibo Lake, have been very expensive due to problems associated with drilling. The principal objective of this investigation is to develop a 3D geomechanical model in this area, in order to optimize the future drillings in the field. For this purpose, a 1D geomechanical model was built at first instance, following the workflow of the MEM (Mechanical Earth Model), this consists of the following steps: 1) Data auditing, 2) Analysis of drilling events and structural model, 3) Mechanical stratigraphy, 4) Overburden stress, 5) Pore pressure, 6) Rock mechanical properties, 7) Horizontal stresses, 8) Direction of the horizontal stresses, 9) Wellbore stability. The 3D MEM was developed through the geostatistic model of the Eocene C-SUP VLG-3676 reservoir and the 1D MEM. With this data the geomechanical grid was embedded. The analysis of the results threw, that the problems occurred in the wells that were examined were mainly due to wellbore stability issues. It was determined that the stress field change as the stratigraphic column deepens, it is normal to strike-slip at the Middle Miocene and Lower Miocene, and strike-slipe to reverse at the Eocene. In agreement to this, at the level of the Eocene, the most advantageous direction to drill is parallel to the maximum horizontal stress (157º). The 3D MEM allowed having a tridimensional visualization of the rock mechanical properties, stresses and operational windows (mud weight and pressures) variations. This will facilitate the optimization of the future drillings in the area, including those zones without any geomechanics information.

Keywords: geomechanics, MEM, drilling, stress

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Authors: Daniel Mueller, Melanie Breitbach, Stefan Cornelius, Sarah Pakulla-Dickel, Margaretha Koenig, Anke Prochnow, Mario Scherer

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The European STR standard set (ESS) of loci as well as the new expanded CODIS core loci set as recommended by the CODIS Core Loci Working Group, has led to a higher standardization and harmonization in STR analysis across borders. Various multiplex PCRs assays have since been developed for the analysis of these 17 ESS or 23 CODIS expansion STR markers that all meet high technical demands. However, forensic analysts are often faced with difficult STR results and the questions thereupon. What is the reason that no peaks are visible in the electropherogram? Did the PCR fail? Was the DNA concentration too low? QIAGEN’s newest Investigator STR kits contain a novel Quality Sensor (QS) that acts as internal performance control and gives useful information for evaluating the amplification efficiency of the PCR. QS indicates if the reaction has worked in general and furthermore allows discriminating between the presence of inhibitors or DNA degradation as a cause for the typical ski slope effect observed in STR profiles of such challenging samples. This information can be used to choose the most appropriate rework strategy.Based on the latest PCR chemistry called FRM 2.0, QIAGEN now provides the next technological generation for STR analysis, the Investigator ESSplex SE QS and Investigator 24plex QS Kits. The new PCR chemistry ensures robust and fast PCR amplification with improved inhibitor resistance and easy handling for a manual or automated setup. The short cycling time of 60 min reduces the duration of the total PCR analysis to make a whole workflow analysis in one day more likely. To facilitate the interpretation of STR results a smart primer design was applied for best possible marker distribution, highest concordance rates and a robust gender typing.

Keywords: PCR, QIAGEN, quality sensor, STR

Procedia PDF Downloads 466

Authors: Hadayat Ullah, Pervez Khalid, Saad Ahmed Mashwani, Zaheer Abbasi, Mubashir Mehmood, Muhammad Jahangir, Ehsan ul Haq

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The aim of the study is to explore subsurface structures through data that is acquired from the seismic survey to delineate the characteristics of the reservoir through petrophysical analysis. Ghazij Shale of Eocene age is regional seal rock in this field. In this research work, 3D property models of subsurface were prepared by applying Petrel software to identify various lithologies and reservoir fluids distribution throughout the field. The 3D static modeling shows a better distribution of the discrete and continuous properties in the field. This model helped to understand the reservoir properties and enhance production by selecting the best location for future drilling. A complete workflow is proposed for formation evaluation, electrofacies modeling, and structural interpretation of the subsurface geology. Based on the wireline logs, it is interpreted that the thickness of the Pab Sandstone varies from 250 m to 350 m in the entire study area. The sandstone is massive with high porosity and intercalated layers of shales. Faulted anticlinal structures are present in the study area, which are favorable for the accumulation of hydrocarbon. 3D structural models and various seismic attribute models were prepared to analyze the reservoir character of this clastic reservoir. Based on wireline logs and seismic data, clean sand, shaly sand, and shale are marked as dominant facies in the study area. However, clean sand facies are more favorable to act as a potential net pay zone.

Keywords: cretaceous, pab sandstone, petrophysics, electrofacies, hydrocarbon

Procedia PDF Downloads 117

Authors: Felicia Orah Rein Moshe

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Soil erosion has become a priority global concern, impairing water quality and degrading ecosystem services. In Mediterranean climates, following a long dry period, the onset of rain occurs when agricultural soils are often bare and most vulnerable to erosion. Early storms transport sediments and sediment-bound pollutants into streams, along with dissolved chemicals. This results in loss of valuable topsoil, water quality degradation, and potentially expensive dredged-material disposal costs. Information on the provenance of fine sediment and priority sources of adsorbed pollutants represents a critical need for developing effective control strategies aimed at source reduction. Modifying sediment traps designed for marine systems, this study tested a cost-effective method to collect suspended sediments on a catchment scale to characterize stream water quality during first-flush storm events in a flashy Eastern Mediterranean coastal perennial stream. This study investigated the Kishon Basin, deploying sediment traps in 23 locations, including 4 in the mainstream and one downstream in each of 19 tributaries, enabling the characterization of sediment as a vehicle for transporting chemicals. Further, it enabled direct comparison of sediment-bound pollutants transported during the first-flush winter storms of 2020 from each of 19 tributaries, allowing subsequent ecotoxicity ranking. Sediment samples were successfully captured in 22 locations. Pesticides, pharmaceuticals, nutrients, and metal concentrations were quantified, identifying a total of 50 pesticides, 15 pharmaceuticals, and 22 metals, with 16 pesticides and 3 pharmaceuticals found in all 23 locations, demonstrating the importance of this transport pathway. Heavy metals were detected in only one tributary, identifying an important watershed pollution source with immediate potential influence on long-term dredging costs. Simultaneous sediment sampling at first flush storms enabled clear identification of priority tributaries and their chemical contributions, advancing a new national watershed monitoring approach, facilitating strategic plan development based on source reduction, and advancing the goal of improving the farm-stream interface, conserving soil resources, and protecting water quality.

Keywords: adsorbed pollution, dredged material, heavy metals, suspended sediment, water quality monitoring

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Authors: Juni C. Kim, Anna R. Robuck, Douglas I. Walker

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The human exposome, which includes chemical exposures over the lifetime and their effects, is now recognized as an important measure for understanding human health; however, the complexity of the data makes the identification of environmental chemicals challenging. The goal of our project was to establish a computational workflow for the improved identification of environmental pollutants containing chlorine or bromine. Using the “pattern. search” function available in the R package NonTarget, we wrote a multifunctional script that searches mass spectral clusters from untargeted gas-chromatography high-resolution mass spectrometry (GC-HRMS) for the presence of spectra consistent with chlorine and bromine-containing organic compounds. The “pattern. search” function was incorporated into a different function that allows the evaluation of clusters containing multiple analyte fragments, has multi-core support, and provides a simplified output identifying listing compounds containing chlorine and/or bromine. The new function was able to process 46,000 spectral clusters in under 8 seconds and identified over 150 potential halogenated spectra. We next applied our function to a deidentified dataset from patients diagnosed with primary biliary cholangitis (PBC), primary sclerosing cholangitis (PSC), and healthy controls. Twenty-two spectra corresponded to potential halogenated compounds in the PSC and PBC dataset, including six significantly different in PBC patients, while four differed in PSC patients. We have developed an improved algorithm for detecting halogenated compounds in GC-HRMS data, providing a strategy for prioritizing exposures in the study of human disease.

Keywords: exposome, metabolome, computational metabolomics, high-resolution mass spectrometry, exposure, pollutants

Procedia PDF Downloads 95

Authors: Sofia Sehli, Zainab El Ouafi, Casey Eddington, Soumaya Jbara, Kasambula Arthur Shem, Islam El Jaddaoui, Ayorinde Afolayan, Olaitan I. Awe, Allissa Dillman, Hassan Ghazal

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The ability to promptly sequence whole genomes at a relatively low cost has revolutionized the way we study the microbiome. Microbiologists are no longer limited to studying what can be grown in a laboratory and instead are given the opportunity to rapidly identify the makeup of microbial communities in a wide variety of environments. Analyzing whole genome sequencing (WGS) data is a complex process that involves multiple moving parts and might be rather unintuitive for scientists that don’t typically work with this type of data. Thus, to help lower the barrier for less-computationally inclined individuals, TAXAPRO was developed at the first Omics Codeathon held virtually by the African Society for Bioinformatics and Computational Biology (ASBCB) in June 2021. TAXAPRO is an advanced metagenomics pipeline that accurately assembles organelle genomes from whole-genome sequencing data. TAXAPRO seamlessly combines WGS analysis tools to create a pipeline that automatically processes raw WGS data and presents organism abundance information in both a tabular and graphical format. TAXAPRO was evaluated using COVID-19 patient gut microbiome data. Analysis performed by TAXAPRO demonstrated a high abundance of Clostridia and Bacteroidia genera and a low abundance of Proteobacteria genera relative to others in the gut microbiome of patients hospitalized with COVID-19, consistent with the original findings derived using a different analysis methodology. This provides crucial evidence that the TAXAPRO workflow dispenses reliable organism abundance information overnight without the hassle of performing the analysis manually.

Keywords: metagenomics, shotgun metagenomic sequence analysis, COVID-19, pipeline, bioinformatics

Procedia PDF Downloads 176

Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Jaiyeop Lee

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Global pandemic coronavirus disease (COVID-19) caused by Severe acute respiratory syndrome SARS-CoV-2, to control the spread of the COVID-19 pandemic, wastewater surveillance has been used to monitor SARS-CoV2 prevalence in the community. The challenging part is establishing wastewater surveillance; there is a need for a well-equipped laboratory for wastewater sample analysis. According to many previous studies, reverse transcription-polymerase chain reaction (RT-PCR) based molecular tests are the most widely used and popular detection method worldwide. However, the RT-qPCR based approaches for the detection or quantification of SARS-CoV-2 genetic fragments ribonucleic acid (RNA) from wastewater require a specialized laboratory, skilled personnel, expensive instruments, and a workflow that typically requires 6 to 8 hours to provide results for just minimum samples. Rapid and reliable alternative detection methods are needed to enable less-well-qualified practitioners to set up and provide sensitive detection of SARS-CoV-2 within wastewater at less-specialized regional laboratories. Therefore, scientists and researchers are conducting experiments for rapid detection methods of COVID-19; in some cases, the structural and molecular characteristics of SARS-CoV-2 are unknown, and various strategies for the correct diagnosis of COVID-19 have been proposed by research laboratories, which are presented in the present study. The ongoing research and development of these highly sensitive and rapid technologies, namely RT-LAMP, ELISA, Biosensors, GeneXpert, allows a wide range of potential options not only for SARS-CoV-2 detection but also for other viruses as well. The effort of this study is to discuss the above effective and regional rapid detection and quantification methods in community wastewater as an essential step in advancing scientific goals.

Keywords: rapid detection, SARS-CoV-2, sensitive detection, wastewater surveillance

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Authors: Amit Kumar, Rajdeep Chakrabarty, Ganesh Gupta

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This paper illustrates the detailed accreditation process of Accreditation Board of Engineering and Technology (ABET) for accrediting engineering and Technology programs. ABET is a non-governmental agency that accredits engineering and technology, applied and natural sciences, and computing sciences programs. ABET was founded on 10th May 1932 and was founded by Institute of Electrical and Electronics Engineering. International industries accept ABET accredited institutes having the highest standards in their academic programs. In this accreditation, there are eight criteria in general; criterion 1 describes the student outcome evaluations, criteria 2 measures the program's educational objectives, criteria 3 is the student outcome calculated from the marks obtained by students, criteria 4 establishes continuous improvement, criteria 5 focus on curriculum of the institute, criteria 6 is about faculties of this institute, criteria 7 measures the facilities provided by the institute and finally, criteria 8 focus on institutional support towards staff of the institute. In this paper, we focused on the calculative part of each criterion with equations and suitable examples, the files and documentation required for each criterion, and the total workflow of the process. The references and the values used to illustrate the calculations are all taken from the samples provided at ABET's official website. In the final section, we also discuss the criterion-wise score weightage followed by evaluation with timeframe and deadlines.

Keywords: Engineering Accreditation Committee, Computing Accreditation Committee, performance indicator, Program Educational Objective, ABET Criterion 1 to 7, IEEE, National Board of Accreditation, MOOCS, Board of Studies, stakeholders, course objective, program outcome, articulation, attainment, CO-PO mapping, CO-PO-SO mapping, PDCA cycle, degree certificates, course files, course catalogue

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Authors: Jorge Prada, Christina Cordes, Carsten Harms, Walter Lang

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The development of microfluidic-based biosensors over the last years has shown an increasing employ of thermoplastic polymers as constitutive material. Their low-cost production, high replication fidelity, biocompatibility and optical-mechanical properties are sought after for the implementation of disposable albeit functional lab-on-chip solutions. Among the range of thermoplastic materials on use, the Cyclo-Olefin Copolymer (COC) stands out due to its optical transparency, which makes it a frequent choice as manufacturing material for fluorescence-based biosensors. Moreover, several processing techniques to complete a closed COC microfluidic biosensor have been discussed in the literature. The reported techniques differ however in their implementation, and therefore potentially add more or less complexity when using it in a mass production process. This work introduces and reports results on the application of a purely thermal bonding process between COC substrates, which were produced by the hot-embossing process, and COC foils containing screen-printed circuits. The proposed procedure takes advantage of the transition temperature difference between two COC grades foils to accomplish the sealing of the microfluidic channels. Patterned heat injection to the COC foil through the COC substrate is applied, resulting in consistent channel geometry uniformity. Measurements on bond strength and bursting pressure are shown, suggesting that this purely thermal bonding process potentially renders a technique which can be easily adapted into the thermoplastic microfluidic chip production workflow, while enables a low-cost as well as high-quality COC biosensor manufacturing process.

Keywords: biosensor, cyclo-olefin copolymer, hot embossing, thermal bonding, thermoplastics

Procedia PDF Downloads 216

Authors: Patricia M. B. Saint-Vincent, Anna Furches, Stephanie Galanie, Erica Teixeira Prates, Piet Jones, Nancy Engle, David Kainer, Wellington Muchero, Daniel Jacobson, Timothy J. Tschaplinski

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Uridine diphosphate-glycosyltransferases (UGTs) are enzymes that catalyze sugar transfer to a variety of plant metabolites. UGT substrates, which include plant secondary metabolites involved in lignification, demonstrate new activities and incorporation when glycosylated. Knowledge of UGT function, substrate specificity, and enzyme products is important for plant engineering efforts, especially related to increasing plant biomass through lignification. UGTs in Populus trichocarpa, a biofuel feedstock, and model woody plant, were selected from a pool of gene candidates using rapid prioritization strategies. A functional genomics workflow, consisting of a metabolite genome-wide association study (mGWAS), expression of synthetic codon-optimized genes, and high-throughput biochemical assays with mass spectrometry-based analysis, was developed for determining the substrates and products of previously-uncharacterized enzymes. A total of 40 UGTs from P. trichocarpa were profiled, and the biochemical assay results were compared to predicted mGWAS connections. Assay results confirmed seven of 11 leaf mGWAS associations and demonstrated varying levels of substrate specificity among candidate UGTs. P. trichocarpa UGT substrate processing confirms the role of these newly-characterized enzymes in lignan, flavonoid, and phytohormone metabolism, with potential implications for cell wall biosynthesis, nitrogen uptake, and biotic and abiotic stress responses.

Keywords: Populus, metabolite-gene associations, GWAS, bio feedstocks, glycosyltransferase

Procedia PDF Downloads 86

Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

Procedia PDF Downloads 166

Authors: Ion Robu, Claudiu Mazilu, Radu Deju

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Natural aggregates (gravel and crushed) are essential non-renewable resources which are used for infrastructure works and civil engineering. In European Union member states from Southeast Europe, it is estimated that the construction industry will grow by 4.2% thereafter complicating aggregate supply management. In addition, a significant additional problem that can be associated to the aggregates industry is wasting potential resources through waste dumping of inert waste, especially waste from construction and demolition activities. In 2012, in Romania, less than 10% of construction and demolition waste (including concrete) are valorized, while the European Union requires that by 2020 this proportion should be at least 70% (Directive 2008/98/EC on waste, transposed into Romanian legislation by Law 211/2011). Depending on the efficiency of waste processing and the quality of recycled aggregate concrete (RCA) obtained, poor quality aggregate can be used as foundation material for roads and at the high quality for new concrete on construction. To obtain good quality concrete using recycled aggregate is necessary to meet the minimum requirements defined by the rules for the manufacture of concrete with natural aggregate. Properties of recycled aggregate (density, granulosity, granule shape, water absorption, weight loss to Los Angeles test, attached mortar content etc.) are the basis for concrete quality; also establishing appropriate proportions between components and the concrete production methods are extremely important for its quality. This paper presents a study on the use of recycled aggregates, from a concrete of specified class, to acquire new cement concrete with different percentages of recycled aggregates. To achieve recycled aggregates several batches of concrete class C16/20, C25/30 and C35/45 were made, the compositions calculation being made according NE012/2007 CP012/2007. Tests for producing recycled aggregate was carried out using concrete samples of the established three classes after 28 days of storage under the above conditions. Cubes with 150mm side were crushed in a first stage with a jaw crusher Liebherr type set at 50 mm nominally. The resulting material was separated by sieving on granulometric sorts and 10-50 sort was used for preliminary tests of crushing in the second stage with a jaw crusher BB 200 Retsch model, respectively a hammer crusher Buffalo Shuttle WA-12-H model. It was highlighted the influence of the type of crusher used to obtain recycled aggregates on granulometry and granule shape and the influence of the attached mortar on the density, water absorption, behavior to the Los Angeles test etc. The proportion of attached mortar was determined and correlated with provenance concrete class of the recycled aggregates and their granulometric sort. The aim to characterize the recycled aggregates is their valorification in new concrete used in construction. In this regard have been made a series of concrete in which the recycled aggregate content was varied from 0 to 100%. The new concrete were characterized by point of view of the change in the density and compressive strength with the proportion of recycled aggregates. It has been shown that an increase in recycled aggregate content not necessarily mean a reduction in compressive strength, quality of the aggregate having a decisive role.

Keywords: recycled concrete aggregate, characteristics, recycled aggregate concrete, properties

Procedia PDF Downloads 184

Authors: Walid Ibrahim, Abdul Kasem, Sudeendra Doddi, Ilaria Giono, Tareq Sabagh, Muhammad Ammar, Nermin Osman

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Background: wire-guided localization (WL) is the most widely used method for the localization of non-palpable breast lesions. SAVI SCOUT occult lesion localization (SSL) is a new technique in breast-conservative surgery. SSL has the potential benefit of improving radiology workflow as well as accurate localization. Purpose: The purpose of this study is to compare the breast tissue specimen volume and weight and margin excision between WL and SSL. Materials and methods: A single institution retrospective analysis of 377 female patients who underwent wide local breast excision with SAVI SCOUT and or wire-guided technique between 2018 and 2021 in a UK University teaching hospital. Breast department. Breast tissue specimen volume and weight, and margin excision have been evaluated in the three groups of different localization. Results: Three hundred and seventy-seven patients were studied. Of these, 261 had wire localization, 88 had SCOUT and 28 had dual localization techniques. Tumor size ranged from 1 to 75mm (Median 20mm). The pathology specimen weight ranged from 1 to 466gm (Median 46.8) and the volume ranged from 1.305 to 1560cm³ (Median 106.32 cm³). SCOUT localization was associated with a significantly low specimen weight than wire or the dual technique localization (Median 41gm vs 47.3gm and 47gm, p = 0.029). SCOUT was not associated with better specimen volume with a borderline significance in comparison to wire and combined techniques (Median 108cm³ vs 105cm³ and 105cm³, p = 0.047). There was a significant correlation between tumor size and pathology specimen weight in the three groups. SCOUT showed a better >2mm safety margin in comparison to the other 2 techniques (p = 0.031). Conclusion: Preoperative SCOUT localization is associated with better specimen weight and better specimen margin. SCOUT did not show any benefits in terms of specimen volume which may be due to difficulty in getting the accurate specimen volume due to the irregularity of the soft tissue specimen.

Keywords: scout, wire, localization, breast

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Authors: Karolina Wieczorek, Sophie Wiliams

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Introduction: Patient data is often collected in Electronic Health Record Systems (EHR) for purposes such as providing care as well as reporting data. This information can be re-used to validate data models in clinical trials or in epidemiological studies. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. Mentioning a disease in a discharge letter does not necessarily mean that a patient suffers from this disease. Many of them discuss a diagnostic process, different tests, or discuss whether a patient has a certain disease. The COVID-19 dataset in this study used natural language processing (NLP), an automated algorithm which extracts information related to COVID-19 symptoms, complications, and medications prescribed within the hospital. Free-text patient clinical patient notes are rich sources of information which contain patient data not captured in a structured form, hence the use of named entity recognition (NER) to capture additional information. Methods: Patient data (discharge summary letters) were exported and screened by an algorithm to pick up relevant terms related to COVID-19. Manual validation of automated tools is vital to pick up errors in processing and to provide confidence in the output. A list of 124 Systematized Nomenclature of Medicine (SNOMED) Clinical Terms has been provided in Excel with corresponding IDs. Two independent medical student researchers were provided with a dictionary of SNOMED list of terms to refer to when screening the notes. They worked on two separate datasets called "A” and "B”, respectively. Notes were screened to check if the correct term had been picked-up by the algorithm to ensure that negated terms were not picked up. Results: Its implementation in the hospital began on March 31, 2020, and the first EHR-derived extract was generated for use in an audit study on June 04, 2020. The dataset has contributed to large, priority clinical trials (including International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) by bulk upload to REDcap research databases) and local research and audit studies. Successful sharing of EHR-extracted datasets requires communicating the provenance and quality, including completeness and accuracy of this data. The results of the validation of the algorithm were the following: precision (0.907), recall (0.416), and F-score test (0.570). Percentage enhancement with NLP extracted terms compared to regular data extraction alone was low (0.3%) for relatively well-documented data such as previous medical history but higher (16.6%, 29.53%, 30.3%, 45.1%) for complications, presenting illness, chronic procedures, acute procedures respectively. Conclusions: This automated NLP algorithm is shown to be useful in facilitating patient data analysis and has the potential to be used in more large-scale clinical trials to assess potential study exclusion criteria for participants in the development of vaccines.

Keywords: automated, algorithm, NLP, COVID-19

Procedia PDF Downloads 66

Authors: J. Bartnicka, J. A. Piedrabuena, R. Portilla, L. Moyano - Cuevas, J. B. Pagador, P. Augat, J. Tokarczyk, F. M. Sánchez Margallo

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Orthopaedic surgeries are characterized by a high degree of complexity. This is reflected by four main groups of resources: 1) surgical team which is consisted of people with different competencies, educational backgrounds and positions; 2) information and knowledge about medical and technical aspects of surgery; 3) medical equipment including surgical tools and materials; 4) space infrastructure which is important from an operating room layout point of view. These all components must be integrated and build a homogeneous organism for achieving an efficient and ergonomically correct surgical workflow. Taking this as a background, there was formulated a concept of international project, called “Online Vocational Training course on ergonomics for orthopaedic Minimally Invasive” (Train4OrthoMIS), which aim is to develop an e-learning tool available in 4 languages (English, Spanish, Polish and German). In the article, there is presented the first project research outcomes focused on three aspects: 1) ergonomic needs of surgeons who work in hospitals around different European countries, 2) the concept of structure of e-learning course, 3) the definition of tools and methods for knowledge assessment adjusted to users’ expectation. The methodology was based on the expert panels and two types of surveys: 1) on training needs, 2) on evaluation and self-assessment preferences. The major findings of the study allowed describing the subjects of four training modules and learning sessions. According to peoples’ opinion there were defined most expected test methods which are single choice test and right after quizzes: “True or False” and “Link elements”. The first project outcomes confirmed the necessity of creating a universal training tool for orthopaedic surgeons regardless of the country in which they work. Because of limited time that surgeons have, the e-learning course should be strictly adjusted to their expectation in order to be useful.

Keywords: international e-learning, ergonomics, orthopaedic surgery, Train4OrthoMIS

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

Procedia PDF Downloads 297