An application of fuzzy BWM for risk assessment in offshore oil projects

The purpose of this paper is to examine the existing risks for the offshore project and risk weighting using the fuzzy best worst method (FBWM). In offshore oil projects, we face six major risks. Each of these risks is divided into smaller risks leaving us to have a total of 34 risks. Some of these risks are internal and some are external risks. In this method, first, the experts of this field determined the best and the worst type of risk. Then, using the experts’ opinions, the study compared the remaining risks with the two selected risks and the other weights are determined. In our survey, “Technical Risk and Project Execution” is the most important risk factor followed by “Political Risk and Sanctions”, “Market risk”, “Manage-ment risk”, “Financial risk and currency fluctuations” and “Environmental risk”

Sonosynthesis of microcellulose from kenaf fiber: optimization of process parameters

Green composites using cellulose fibers as a reinforcement material provide a sustainable and renewable alternative to petroleum-based polymers. However, controlling the usage of chemicals and processing parameters to extract the cellulose could be sometimes difficult. Therefore, this study aims to optimize the conditions for extracting the microcellulose from kenaf fibers using central composite design (CCD), a statistical tool in design of experiments. Three factors and three levels were chosen for carrying out the analysis. The design was based on sodium hydroxide (NaOH) dosage, Sodium Chlorite (NaClO2) dosage and sonication time as independent variables, while dependent variables were the fiber size and degradation point. Later, size responses were fitted using quadratic polynomial model and degradation responses using 2-factor interaction model (2FI). The R2 values of 0.89 and 0.83 were obtained for the quadratic and the 2FI model, respectively. Further, surface morphology, thermal analysis, Fourier transform infrared (FTIR) spectroscopy and X-Ray diffraction (XRD) were also used for design validation. Optimal parameters for microcellulose extraction were found to be 0.15 g of NaOH at first stage, 4.6 mL of NaClO2 at second stage, and 10 min of sonication during third stage

Vestibular schwannoma with contralateral facial pain – case report

BACKGROUND: Vestibular schwannoma (acoustic neuroma) most commonly presents with ipsilateral disturbances of acoustic, vestibular, trigeminal and facial nerves. Presentation of vestibular schwannoma with contralateral facial pain is quite uncommon. CASE PRESENTATION: Among 156 cases of operated vestibular schwannoma, we found one case with unusual presentation of contralateral hemifacial pain. CONCLUSION: The presentation of contralateral facial pain in the vestibular schwannoma is rare. It seems that displacement and distortion of the brainstem and compression of the contralateral trigeminal nerve in Meckel's cave by the large mass lesion may lead to this atypical presentation. The best practice in these patients is removal of the tumour, although persistent contralateral pain after operation has been reported

Latest advances and challenges in carbon capture using bio-based sorbents: A state-of-the-art review

Copyright © 2022 The Authors. Effective decarbonisation is key to ensuring the temperature rise does not exceed the 2 °C set by the Paris accords. Adsorption is identified as a key technology for post-combustion carbon capture. This rise in prominence of such processes is owed to the fact that application of solid sorbents does not lead to the generation of secondary waste streams. In fact, sorbents can be produced from waste material (e.g. bio-based sorbents). Bio-based sorbents have become an increasingly attractive option; food waste, agricultural and municipal sources can be employed as precursors. These sorbents can be physically and chemically activated and then further modified to produce sorbents that can capture CO2 effectively. The employment of these types of sorbents, however, often entails geological and operational challenges. Understanding how these sorbents can be deployed at scale and the geological challenges associated with bio-based sorbents are key research areas that must be further investigated. Process modelling and machine learning can provide insights into these challenges especially within optimization of adsorption processes and sorbent development. This paper aims to provide a state-of-the-art review of the synthesis of bio-based sorbents and their application within post-combustion carbon capture processes as well as the recent trends of utilizing machine learning for the development of these sorbents, and the design of the corresponding adsorption processes alike.UK's Engineering and Physical Sciences Research Council (EPSRC) under the project titled “Multiphysics and Multiscale Modelling for Safe and Feasible CO2 Capture and Storage - EP/T033940/1″; UK Carbon Capture and Storage Research Centre (EP/W002841/1) through the flexible funded research programme “Investigation of Environmental and Operational Challenges of Adsorbents Synthesised from Industrial Grade Biomass Combustion Residues”

Play dough as an educational tool for visualization of complicated cerebral aneurysm anatomy

BACKGROUND: Imagination of the three-dimensional (3D) structure of cerebral vascular lesions using two-dimensional (2D) angiograms is one of the skills that neurosurgical residents should achieve during their training. Although ongoing progress in computer software and digital imaging systems has facilitated viewing and interpretation of cerebral angiograms enormously, these facilities are not always available. METHODS: We have presented the use of play dough as an adjunct to the teaching armamentarium for training in visualization of cerebral aneurysms in some cases. RESULTS: The advantages of play dough are low cost, availability and simplicity of use, being more efficient and realistic in training the less experienced resident in comparison with the simple drawings and even angiographic views from different angles without the need for computers and similar equipment. The disadvantages include the psychological resistance of residents to the use of something in surgical training that usually is considered to be a toy, and not being as clean as drawings or computerized images. CONCLUSION: Although technology and computerized software using the patients' own imaging data seems likely to become more advanced in the future, use of play dough in some complicated cerebral aneurysm cases may be helpful in 3D reconstruction of the real situation

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Search for direct stau production in events with two hadronic tau-leptons in root s=13 TeV pp collisions with the ATLAS detector

A search for the direct production of the supersymmetric partners ofτ-leptons (staus) in final stateswith two hadronically decayingτ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of139fb−1, recorded with the ATLAS detector at the LargeHadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected StandardModel background is observed. Limits are derived in scenarios of direct production of stau pairs with eachstau decaying into the stable lightest neutralino and oneτ-lepton in simplified models where the two staumass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidencelevel for a massless lightest neutralino

DijetGAN:A Generative-Adversarial Network Approach for the Simulation of QCD Dijet Events at the LHC

A Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production of pairs of jets at the LHC. The GAN is trained on events generated using MadGraph5 + Pythia8, and Delphes3 fast detector simulation. We demonstrate that a number of kinematic distributions both at Monte Carlo truth level and after the detector simulation can be reproduced by the generator network with a very good level of agreement. The code can be checked out or forked from the publicly accessible online repository https://gitlab.cern.ch/disipio/DiJetGAN .Comment: 17 pages, 8 figure

Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data

BACKGROUND: In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in prediction of outcomes in head trauma and studied the reproducibility of the findings. METHODS: 1000 Logistic regression and ANN models based on initial clinical data related to the GCS, tracheal intubation status, age, systolic blood pressure, respiratory rate, pulse rate, injury severity score and the outcome of 1271 mainly head injured patients were compared in this study. For each of one thousand pairs of ANN and logistic models, the area under the receiver operating characteristic (ROC) curves, Hosmer-Lemeshow (HL) statistics and accuracy rate were calculated and compared using paired T-tests. RESULTS: ANN significantly outperformed logistic models in both fields of discrimination and calibration but under performed in accuracy. In 77.8% of cases the area under the ROC curves and in 56.4% of cases the HL statistics for the neural network model were superior to that for the logistic model. In 68% of cases the accuracy of the logistic model was superior to the neural network model. CONCLUSIONS: ANN significantly outperformed the logistic models in both fields of discrimination and calibration but lagged behind in accuracy. This study clearly showed that any single comparison between these two models might not reliably represent the true end results. External validation of the designed models, using larger databases with different rates of outcomes is necessary to get an accurate measure of performance outside the development population