Journal articles: 'BBN modelling'

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Wee, Yit Yin, Shing Chiang Tan, and KuokKwee Wee. "Reducing the Complexity of Casual Representation in Bayesian Belief Network." F1000Research 10 (December 6, 2021): 1243. http://dx.doi.org/10.12688/f1000research.73480.1.

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Background: Bayesian Belief Network (BBN) is a well-established causal framework that is widely adopted in various domains and has a proven track record of success in research and application areas. However, BBN has weaknesses in causal knowledge elicitation and representation. The representation of the joint probability distribution in the Conditional Probability Table (CPT) has increased the complexity and difficulty for the user either in comprehending the causal knowledge or using it as a front-end modelling tool. Methods: This study aims to propose a simplified version of the BBN ─ Bayesian causal model, which can represent the BBN intuitively and proposes an inference method based on the simplified version of BBN. The CPT in the BBN is replaced with the causal weight in the range of[-1,+1] to indicate the causal influence between the nodes. In addition, an inferential algorithm is proposed to compute and propagate the influence in the causal model. Results: A case study is used to validate the proposed inferential algorithm. The results show that a Bayesian causal model is able to predict and diagnose the increment and decrement as in BBN. Conclusions: The Bayesian causal model that serves as a simplified version of BBN has shown its advantages in modelling and representation, especially from the knowledge engineering perspective.

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Ale, Ben, Coen van Gulijk, Anca Hanea, Daniela Hanea, Patrick Hudson, Pei-Hui Lin, and Simone Sillem. "Towards BBN based risk modelling of process plants." Safety Science 69 (November 2014): 48–56. http://dx.doi.org/10.1016/j.ssci.2013.12.007.

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Sleiman, Joseph, David J. Savage, Benjamin Switzer, Colleen Y. Colbert, Cory Chevalier, Kathleen Neuendorf, and David Harris. "Teaching residents how to break bad news: piloting a resident-led curriculum and feedback task force as a proof-of-concept study." BMJ Simulation and Technology Enhanced Learning 7, no. 6 (June 22, 2021): 568–74. http://dx.doi.org/10.1136/bmjstel-2021-000897.

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BackgroundBreaking bad news (BBN) is a critically important skill set for residents. Limited formal supervision and unpredictable timing of bad news delivery serve as barriers to the exchange of meaningful feedback.Purpose of studyThe goal of this educational innovation was to improve internal medicine residents’ communication skills during challenging BBN encounters. A formal BBN training programme and innovative on-demand task force were part of this two-phase project.Study designInternal medicine residents at a large academic medical centre participated in an interactive workshop focused on BBN. Workshop survey results served as a needs assessment for the development of a novel resident-led BBN task force. The task force was created to provide observations at the bedside and feedback after BBN encounters. Training of task force members incorporated video triggers and a feedback checklist. Inter-rater reliability was analysed prior to field testing, which provided data on real-world implementation challenges.Results148 residents were trained during the 2-hour communications skills workshop. Based on survey results, 73% (108 of 148) of the residents indicated enhanced confidence in BBN after participation. Field testing of the task force on a hospital ward revealed potential workflow barriers for residents requesting observations and prompted troubleshooting. Solutions were implemented based on field testing results.ConclusionsA trainee-led BBN task force and communication skills workshop is offered as an innovative model for improving residents’ interpersonal and communication skills in BBN. We believe the model is both sustainable and reproducible. Lessons learnt are offered to aid in implementation in other settings.

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Zhan, Yuexing, and Xinrui Niu. "Tuning methods and mechanical modelling of hydrogels." Bioinspired, Biomimetic and Nanobiomaterials 4, no. 2 (June 2015): 140–54. http://dx.doi.org/10.1680/bbn.14.00029.

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Philip, Babitha, and Hamad Al Jassmi. "A Bayesian Approach towards Modelling the Interrelationships of Pavement Deterioration Factors." Buildings 12, no. 7 (July 18, 2022): 1039. http://dx.doi.org/10.3390/buildings12071039.

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In this study, Bayesian Belief Networks (BBN) are proposed to model the relationships between factors contributing to pavement deterioration, where their values are probabilistically estimated based on their interdependencies. Such probabilistic inferences are deemed to provide a reasonable alternative over costly data collection campaigns and assist in road condition diagnoses and assessment efforts in cases where data are only partially available. The BBN models examined in this study are based on a vast database of pavement deterioration factors including road distress data, namely cracking, deflection, the International Roughness Index (IRI) and rutting, from major road sections in the United Arab Emirates (UAE) along with the corresponding traffic and climatic factors. The dataset for the analysis consisted of 3272 road sections, each of 10 m length. The test results showed that the most critical parameter representing the whole process of road deterioration is the IRI with the highest nodal force. Additionally, IRI is strongly correlated with rutting and deflection, with mutual information of 0.147 and 0.143, respectively. Furthermore, a Bayesian network structure with a contingency table fit of over 90% illustrates how the road distress parameters change in the presence of external factors, such as traffic and climatic conditions.

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Ghahramani, Afshin, John McLean Bennett, Aram Ali, Kathryn Reardon-Smith, Glenn Dale, Stirling D. Roberton, and Steven Raine. "A Risk-Based Approach to Mine-Site Rehabilitation: Use of Bayesian Belief Network Modelling to Manage Dispersive Soil and Spoil." Sustainability 13, no. 20 (October 13, 2021): 11267. http://dx.doi.org/10.3390/su132011267.

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Dispersive spoil/soil management is a major environmental and economic challenge for active coal mines as well as sustainable mine closure across the globe. To explore and design a framework for managing dispersive spoil, considering the complexities as well as data availability, this paper has developed a Bayesian Belief Network (BBN)-a probabilistic predictive framework to support practical and cost-effective decisions for the management of dispersive spoil. This approach enabled incorporation of expert knowledge where data were insufficient for modelling purposes. The performance of the model was validated using field data from actively managed mine sites and found to be consistent in the prediction of soil erosion and ground cover. Agreement between predicted soil erosion probability and field observations was greater than 74%, and greater than 70% for ground cover protection. The model performance was further noticeably improved by calibration of Conditional Probability Tables (CPTs). This demonstrates the value of the BBN modelling approach, whereby the use of currently best-available data can provide a practical result, with the capacity for significant model improvement over time as more (targeted) data come to hand.

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Ghahramani, Afshin, John McLean Bennett, Aram Ali, Kathryn Reardon-Smith, Glenn Dale, Stirling D. Roberton, and Steven Raine. "A Risk-Based Approach to Mine-Site Rehabilitation: Use of Bayesian Belief Network Modelling to Manage Dispersive Soil and Spoil." Sustainability 13, no. 20 (October 13, 2021): 11267. http://dx.doi.org/10.3390/su132011267.

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Dispersive spoil/soil management is a major environmental and economic challenge for active coal mines as well as sustainable mine closure across the globe. To explore and design a framework for managing dispersive spoil, considering the complexities as well as data availability, this paper has developed a Bayesian Belief Network (BBN)-a probabilistic predictive framework to support practical and cost-effective decisions for the management of dispersive spoil. This approach enabled incorporation of expert knowledge where data were insufficient for modelling purposes. The performance of the model was validated using field data from actively managed mine sites and found to be consistent in the prediction of soil erosion and ground cover. Agreement between predicted soil erosion probability and field observations was greater than 74%, and greater than 70% for ground cover protection. The model performance was further noticeably improved by calibration of Conditional Probability Tables (CPTs). This demonstrates the value of the BBN modelling approach, whereby the use of currently best-available data can provide a practical result, with the capacity for significant model improvement over time as more (targeted) data come to hand.

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Bruen, Michael, Thibault Hallouin, Michael Christie, Ronan Matson, Ewa Siwicka, Fiona Kelly, Craig Bullock, Hugh B. Feeley, Edel Hannigan, and Mary Kelly-Quinn. "A Bayesian Modelling Framework for Integration of Ecosystem Services into Freshwater Resources Management." Environmental Management 69, no. 4 (February 16, 2022): 781–800. http://dx.doi.org/10.1007/s00267-022-01595-x.

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AbstractModels of ecological response to multiple stressors and of the consequences for ecosystem services (ES) delivery are scarce. This paper describes a methodology for constructing a BBN combining catchment and water quality model output, data, and expert knowledge that can support the integration of ES into water resources management. It proposes “small group” workshop methods for elucidating expert knowledge and analyses the areas of agreement and disagreement between experts. The model was developed for four selected ES and for assessing the consequences of management options relating to no-change, riparian management, and decreasing or increasing livestock numbers. Compared with no-change, riparian management and a decrease in livestock numbers improved the ES investigated to varying degrees. Sensitivity analysis of the expert information in the BBN showed the greatest disagreements between experts were mainly for low probability situations and thus had little impact on the results. Conversely, in our applications, the best agreement between experts tended to occur for the higher probability, more likely, situations. This has implications for the practical use of this type of model to support catchment management decisions. The complexity of the relationship between management measures, the water quality and ecological responses and resulting changes in ES must not be a barrier to making decisions in the present time. The interactions of multiple stressors further complicate the situation. However, management decisions typically relate to the overall character of solutions and not their detailed design, which can follow once the nature of the solution has been chosen, for example livestock management or riparian measures or both.

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Allik, Henno, Stewart Moore, Elizabeth O'Neil, and Eric Tenenbaum. "Finite element analysis on the BBN butterfly multiprocessor." Computers & Structures 27, no. 1 (January 1987): 13–21. http://dx.doi.org/10.1016/0045-7949(87)90177-5.

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Mat Alipiah, Roseliza, Fathilah Ismail, Siti Aisyah Saat, and Ahmad Puad Mat Som. "Modelling the Impacts of Aquaculture in Wetland Ecosystems for Sustainable Aquaculture Management: An Integrated Ecosystem Approach." International Journal of Engineering & Technology 7, no. 4.34 (December 13, 2018): 197. http://dx.doi.org/10.14419/ijet.v7i4.34.23887.

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This research integrates information from both environmental and social sciences to inform effective management of the wetlands. A three-stage research framework was developed for modelling the drivers and pressures imposed on the wetlands and their impacts to the ecosystem and the local communities. Firstly, a Bayesian Belief Network (BBN) was used to predict the probability of anthropogenic activities affecting the delivery of different key wetland ecosystem services under different management scenarios. Secondly, Choice Experiment (CE) was used to quantify the relative preferences which key wetland stakeholder group (aquaculturists) held for delivery of different levels of these key ecosystem services. Thirdly, a Multi-Criteria Decision Analysis (MCDA) was applied to produce an ordinal ranking of the alternative management scenarios accounting for their impacts upon ecosystem service delivery as perceived through the preferences of the aquaculturists. This integrated ecosystem management approach was applied to a wetland ecosystem in Setiu, Terengganu, Malaysia which currently supports a significant level of aquaculture activities. This research has produced clear guidelines to inform policy makers considering alternative wetland management scenarios: Intensive Aquaculture, Conservation or Ecotourism, in addition to the Status Quo. The findings of this research are as follows. The BBN revealed that current aquaculture activity is likely to have significant impacts on water column nutrient enrichment, but trivial impacts on caged fish biomass, especially under the Intensive Aquaculture scenario. Secondly, the best fitting CE models identified several stakeholder sub-groups for aquaculturists, each with distinct sets of preferences for the delivery of key ecosystem services. Thirdly the MCDA identified Conservation as the most desirable scenario overall based on ordinal ranking in the eyes of most of the stakeholder sub-groups. Ecotourism and Status Quo scenarios were the next most preferred and Intensive Aquaculture was the least desirable scenario. The methodologies developed through this research provide an opportunity for improving planning and decision making processes that aim to deliver sustainable management of wetland ecosystems in Malaysia.

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Shaaban, Mostafa, Carmen Schwartz, Joseph Macpherson, and Annette Piorr. "A Conceptual Model Framework for Mapping, Analyzing and Managing Supply–Demand Mismatches of Ecosystem Services in Agricultural Landscapes." Land 10, no. 2 (January 29, 2021): 131. http://dx.doi.org/10.3390/land10020131.

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Appreciation for agricultural sustainability and ecosystem services (ESS) has received considerable attention from the scientific community. However, research has not yet systematically and sufficiently considered the spatial dimension of ESS trade-offs as a source of conflicts. Moreover, approaches for ESS management that address a wide range of beneficiaries and their interactions at landscape scale are lacking. Our main research question is how to motivate different beneficiaries of agricultural landscapes to cooperate in reducing supply–demand mismatches and accompanied conflicts, as well as to assess how different scenarios would impact relevant Sustainable Development Goals (SDGs). We present a novel and conceptual integrated model in which we employ a combination of three methodological tools: participatory geographic information system (PGIS), agent-based modelling (ABM) and a Bayesian belief network (BBN). The objective of our model simulation is to identify and manage site-specific spatial trade-off patterns and to provide decision support for shifting competitive behavior of individual stakeholders in satisfying their demand for ESS to a collective and cooperative scheme, while jointly striving to attain relevant targets outlined in the SDGs. Attached to this work is a short video depicting our conceptual model. We strongly suggest that tackling a complex social-ecological system necessitates a highly integrated modelling approach that fosters the transition from farm- to landscape-scale management, from individualistic to collective action, and from competitive to cooperative behavior.

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Maathuis, Clara, and Sabarathinam Chockalingam. "Modelling the Influential Factors Embedded in the Proportionality Assessment in Military Operations." International Conference on Cyber Warfare and Security 18, no. 1 (February 28, 2023): 218–26. http://dx.doi.org/10.34190/iccws.18.1.939.

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The ongoing decade was believed to be a peaceful one. However, contemporary conflicts, and in particular, ongoing wars prove the opposite as they show the increase in context complexity when defining their goals as well as execution strategies for building means and methods for achieving them by gaining advantage against their adversaries through the engagement of well-established targets. At the core of the engagement decision relies the principle of proportionality which brings in a direct relation the expected unintended effects on civilian side with the anticipated intended effects on military side. While the clusters of effects involved in the proportionality assessment are clear, the process itself is subjective, governed by different dimensions of uncertainty, and represents the responsibility of military Commanders. Thus, a complex socio-technical process where different clusters of influential factors (e.g., military, technical, socio-ethical) play a role in the decisions made. Having said that, the objective of this research is to capture and cluster these factors, and further to model their influence in the proportionality decision-making process. This decision support system produces military targeting awareness to the agents involved in the processes of building, executing, and assessing military operations. To accomplish the aim of this research, a Design Science Research methodological approach is taken for capturing and modelling the influential factors as a socio-technical artefact in the form of a Bayesian Belief Network (BBN) model. The model proposed is further evaluated through demonstration on three different cases in respect to real military operations incidents and scenarios existing in the scientific literature in this research field. Hence, through this demonstration, it is illustrated and interpreted how the factors identified influence proportionality decisions when assessing target engagement as being proportional or disproportional. In these cases, corresponding measures for strengthening proportionality and reducing disproportionality in military operations are considered.

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Kallen, Victor, Muhammad Tahir, Andrew Bedard, Bart Bongers, Natal van Riel, and Nico van Meeteren. "Aging and Allostasis: Using Bayesian Network Analytics to Explore and Evaluate Allostatic Markers in the Context of Aging." Diagnostics 11, no. 2 (January 21, 2021): 157. http://dx.doi.org/10.3390/diagnostics11020157.

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Allostatic load reflects the cumulative strain on organic functions that may gradually evolve into overt disease. Our aim was to evaluate the allostatic parameters in the context of aging, and identify the parameters that may be suitable for an allostatic load index for elderly people (>60 years). From previously published studies, 11 allostatic (bio)markers could be identified that sustain sufficient variability with aging to capture meaningful changes in health status. Based on reported statistics (prevalence of a biomarker and its associated outcome, and/or an odds/risk ratio relating these two), seven of these could be adopted in a Bayesian Belief Network (BBN), providing the probability of “disturbed” allostasis in any given elder. Additional statistical analyses showed that changes in IL-6 and BMI contributed the most to a “disturbed” allostasis, indicating their prognostic potential in relation to deteriorating health in otherwise generally healthy elderly. In this way, and despite the natural decline in variance that irrevocably alters the prognostic relevance of most allostatic (bio)markers with aging, it appeared possible to outline an allostatic load index specifically for the elderly. The allostatic parameters here identified might consequently be considered a useful basis for future quantitative modelling in the context of (healthy) aging.

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Raevsky, O. A., S. L. Solodova, O. E. Raevskaya, Y. V. Liplavskiy, and R. M. Mannhold. "Computer classification models on the relationship between chemical structures of compounds and drugs with their blood brain barrier penetration." Biomeditsinskaya Khimiya 58, no. 3 (2012): 246–56. http://dx.doi.org/10.18097/pbmc20125803246.

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Ability of drugs to cross blood-brain barrier (BBB) (BBB+ for BBB-penetrating and BBB- for non-penetrating compounds) is one of the most important properties of chemicals acting on the central nervous system (CNS). This work presents the results of modelling of the relationship between chemicals structure and BBB-crossing ability. The data set included 1513 compounds BBB+/- (1276 BBB+ and 237 BBB-). Computer modelling of structure-activity relationship was realized by two directions: using the "read-across" method and linear discriminant analysis (LDA) based on physico-chemical descriptors. It was found that a sum of donor-acceptor factors is the principal parameter, which define BBB penetration.

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Lawson, Sarah J., Martin Cope, Sunhee Lee, Ian E. Galbally, Zoran Ristovski, and Melita D. Keywood. "Biomass burning at Cape Grim: exploring photochemistry using multi-scale modelling." Atmospheric Chemistry and Physics 17, no. 19 (October 5, 2017): 11707–26. http://dx.doi.org/10.5194/acp-17-11707-2017.

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Abstract. We have tested the ability of a high-resolution chemical transport model (CTM) to reproduce biomass burning (BB) plume strikes and ozone (O3) enhancements observed at Cape Grim in Tasmania, Australia, from the Robbins Island fire. The CTM has also been used to explore the contribution of near-field BB emissions and background sources to O3 observations under conditions of complex meteorology. Using atmospheric observations, we have tested model sensitivity to meteorology, BB emission factors (EFs) corresponding to low, medium, and high modified combustion efficiency (MCE), and spatial variability. The use of two different meteorological models (TAPM–CTM and CCAM–CTM) varied the first (BB1) plume strike time by up to 15 h and the duration of impact between 12 and 36 h, and it varied the second (BB2) plume duration between 50 and 57 h. Meteorology also had a large impact on simulated O3, with one model (TAPM–CTM) simulating four periods of O3 enhancement, while the other model (CCAM) simulating only one period. Varying the BB EFs, which in turn varied the non-methane organic compound (NMOC) ∕ oxides of nitrogen (NOx) ratio, had a strongly non-linear impact on simulated O3 concentration, with either destruction or production of O3 predicted in different simulations. As shown in previous work (Lawson et al., 2015), minor rainfall events have the potential to significantly alter EF due to changes in combustion processes. Models that assume fixed EF for O3 precursor species in an environment with temporally or spatially variable EF may be unable to simulate the behaviour of important species such as O3. TAPM–CTM is used to further explore the contribution of the Robbins Island fire to the observed O3 enhancements during BB1 and BB2. Overall, TAPM–CTM suggests that the dominant source of O3 observed at Cape Grim was aged urban air (age = 2 days), with a contribution of O3 formed from local BB emissions. This work shows the importance of assessing model sensitivity to meteorology and EF and the large impact these variables can have in particular on simulated destruction or production of O3 in regional atmospheric chemistry simulations. This work also shows the importance of using models to elucidate the contribution from different sources to atmospheric composition, where this is difficult using observations alone.

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Vignone, Domenico, Odalys Gonzalez Paz, Ivan Fini, Antonella Cellucci, Giulio Auciello, Maria Rosaria Battista, Isabelle Gloaguen, et al. "Modelling the Human Blood–Brain Barrier in Huntington Disease." International Journal of Molecular Sciences 23, no. 14 (July 15, 2022): 7813. http://dx.doi.org/10.3390/ijms23147813.

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While blood–brain barrier (BBB) dysfunction has been described in neurological disorders, including Huntington’s disease (HD), it is not known if endothelial cells themselves are functionally compromised when promoting BBB dysfunction. Furthermore, the underlying mechanisms of BBB dysfunction remain elusive given the limitations with mouse models and post mortem tissue to identify primary deficits. We established models of BBB and undertook a transcriptome and functional analysis of human induced pluripotent stem cell (iPSC)-derived brain-like microvascular endothelial cells (iBMEC) from HD patients or unaffected controls. We demonstrated that HD-iBMECs have abnormalities in barrier properties, as well as in specific BBB functions such as receptor-mediated transcytosis.

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Romero, Enrique, Marcelo Sánchez, Xuerui Gai, Mauricio Barrera, and Antonio Lloret. "Mechanical behavior of an unsaturated clayey silt: an experimental and constitutive modelling study." Canadian Geotechnical Journal 56, no. 10 (October 2019): 1461–74. http://dx.doi.org/10.1139/cgj-2018-0117.

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This paper reports an experimental study and subsequent constitutive modelling focused on the stress-strain and volumetric responses during deviatoric stress application of a partially saturated clayey silt. The material was statically and isotropically compacted at constant water content towards a pre-defined pre-consolidation stress. A series of strain-controlled triaxial compression tests on a state of the art device and isotropic experiments are presented and discussed. The triaxial tests started at the same stress state (i.e., identical matric suction and mean net stress) and were conducted at the same constant suction. Several stress paths under isotropic conditions (i.e., drying–wetting, loading–unloading, and wetting–drying) were followed to induce different overconsolidated states before shearing the specimens. The test results are initially interpreted using the elastoplastic Barcelona Basic Model (BBM). Independent tests were selected to determine the model parameters associated with the volumetric behavior of the soil. The BBM was not able to capture the dilatant behavior observed during shearing. An enhancement of the BBM is proposed in this work, which includes both, a more general hardening law and sub-loading concepts. The main capabilities and limitations of the original BBM and the enhanced model are discussed and compared. The modified BBM was able to handle the dilatancy observed in the experiments and provided a more realistic description of the experimental stress-strain response.

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Kisała, Joanna, Kinga I. Hęclik, Krzysztof Pogocki, and Dariusz Pogocki. "Essentials and Perspectives of Computational Modelling Assistance for CNS-oriented Nanoparticle-based Drug Delivery Systems." Current Medicinal Chemistry 25, no. 42 (February 6, 2019): 5894–913. http://dx.doi.org/10.2174/0929867325666180517095742.

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The blood-brain barrier (BBB) is a complex system controlling two-way substances traffic between circulatory (cardiovascular) system and central nervous system (CNS). It is almost perfectly crafted to regulate brain homeostasis and to permit selective transport of molecules that are essential for brain function. For potential drug candidates, the CNSoriented neuropharmaceuticals as well as for those of primary targets in the periphery, the extent to which a substance in the circulation gains access to the CNS seems crucial. With the advent of nanopharmacology, the problem of the BBB permeability for drug nano-carriers gains new significance. Compared to some other fields of medicinal chemistry, the computational science of nano-delivery is still premature to offer the black-box type solutions, especially for the BBB-case. However, even its enormous complexity can spell out the physical principles, and as such subjected to computation. The basic understanding of various physicochemical parameters describing the brain uptake is required to take advantage of their usage for the BBB-nano delivery. This mini-review provides a sketchy introduction of essential concepts allowing application of computational simulation to the BBB-nano delivery design.

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Chen, Carla C. M., David G. Bourne, Christopher C. Drovandi, Kerrie Mengersen, Bette L. Willis, M. Julian Caley, and Yui Sato. "Modelling environmental drivers of black band disease outbreaks in populations of foliose corals in the genus Montipora." PeerJ 5 (June 12, 2017): e3438. http://dx.doi.org/10.7717/peerj.3438.

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Seawater temperature anomalies associated with warming climate have been linked to increases in coral disease outbreaks that have contributed to coral reef declines globally. However, little is known about how seasonal scale variations in environmental factors influence disease dynamics at the level of individual coral colonies. In this study, we applied a multi-state Markov model (MSM) to investigate the dynamics of black band disease (BBD) developing from apparently healthy corals and/or a precursor-stage, termed ‘cyanobacterial patches’ (CP), in relation to seasonal variation in light and seawater temperature at two reef sites around Pelorus Island in the central sector of the Great Barrier Reef. The model predicted that the proportion of colonies transitioning from BBD to Healthy states within three months was approximately 57%, but 5.6% of BBD cases resulted in whole colony mortality. According to our modelling, healthy coral colonies were more susceptible to BBD during summer months when light levels were at their maxima and seawater temperatures were either rising or at their maxima. In contrast, CP mostly occurred during spring, when both light and seawater temperatures were rising. This suggests that environmental drivers for healthy coral colonies transitioning into a CP state are different from those driving transitions into BBD. Our model predicts that (1) the transition from healthy to CP state is best explained by increasing light, (2) the transition between Healthy to BBD occurs more frequently from early to late summer, (3) 20% of CP infected corals developed BBD, although light and temperature appeared to have limited impact on this state transition, and (4) the number of transitions from Healthy to BBD differed significantly between the two study sites, potentially reflecting differences in localised wave action regimes.

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Novanti, Devi, Hajrul Multazam, Novira Laily Husna, Ossy Sanityasa Rahajeng, Selfina L, and Rani Nooraeni. "Pemodelan dan Peramalan Harga Penutupan Saham Perbankan dengan Metode ARIMA dan Family ARCH." ESTIMASI: Journal of Statistics and Its Application 1, no. 2 (July 3, 2020): 94. http://dx.doi.org/10.20956/ejsa.v1i2.9637.

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Modelling the stock closing price stock is useful so that the investors are expected to be able to understand the situation of the stock, in order to make the right decision when they want to buy or sell their stocks. This study uses the ARIMA and Family ARCH methods in modelling the volatility of four banking stocks that are in high demand by the public, which are Bank BRI (BBRI), Bank BNI (BBNI), Bank Mandiri (BMRI), and Bank BCA (BBCA) from January 1st 2017 until January 31st 2020. Stock returns are modelled by using the ARIMA model, then proceeded with the heteroscedasticity testing. Based on the test, we obtained the results of BBRI, BMRI, and BBCA are heteroscedastic. While BBNI are homoscedastic. The volatility models obtained from the test are BBNI has ARIMA models ([6,13], 1, [6,13]), BBRI has ARI models ([2,24,28), 1,0) -ARCH (1), BMRI has an ARIMA (2,1,4) -GARCH (1,1) model, and BBCA has ARI ([1,2], 1,0) -GARCH (1,1) model. Based on the rising value of the stock price, we suggest the best stock for the investors is BBRI because it has the largest increase of 10% followed by BBCA and BMRI

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Kalinowski, M. B. "Atmospheric transport modelling related to radionuclide monitoring in support of the Comprehensive Nuclear-Test-Ban Treaty verification." Kerntechnik 66, no. 3 (June 1, 2001): 129–33. http://dx.doi.org/10.1515/kern-2001-0064.

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Abstract Global monitoring for relevant radionuclides in the atmosphere serves as part of the International Monitoring System to verify compliance with the Comprehensive Nuclear-Test-Ban-Treaty (CTBT). Atmospheric transport modelling can be applied to support these measurements and to get indications for possible source locations of detected relevant anthropogenic nuclides. This paper puts a focus on those issues that are of relevance to the International Data Centre (IDC). Possible methods of atmospheric transport modelling are outlined. The current tentative implementation at the IDC is described here.

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Rai, Saurabh. "GTN Damage Modelling of the AA6063 Using Image Processing." Brilliant Engineering 3, no. 1 (December 9, 2021): 1–4. http://dx.doi.org/10.36937/ben.2022.4400.

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In this paper, an innovative way of calculating the Gurson–Tvergaard–Needleman parameter has been developed for AA 6063. AA 6063 is an aluminum alloy comprising the alloying ingredients magnesium and silicon. The Aluminum Association maintains the standard that governs its composition. It has strong mechanical properties and may be heat treated and welded. Image processing technique has been used to calculate the damage constant for the AA 6063. The image of the sample has been taken under a microscope of undeformed and fractured material. Then the images are analyzed using the Open CV tool in a python open-source environment. The initial and final void fraction of the sheet has been calculated. Damage models, particularly the Gurson–Tvergaard–Needleman (GTN) model, are widely used in numerical simulation of material deformations. Each damage model has some constants which must be identified for each material. The direct identification methods are costly and time-consuming. A combination of experimental, numerical simulation and optimization have been used to determine the constants in the current work. Numerical simulation of the dynamic test was performed utilizing the constants obtained from quasi-static experiments. The results showed a high precision in predicting the specimen's profile in the dynamic testing.

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Verscheijden, Laurens F. M., Jan B. Koenderink, Saskia N. de Wildt, and Frans G. M. Russel. "Differences in P-glycoprotein activity in human and rodent blood–brain barrier assessed by mechanistic modelling." Archives of Toxicology 95, no. 9 (July 15, 2021): 3015–29. http://dx.doi.org/10.1007/s00204-021-03115-y.

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AbstractVariation in the efficacy and safety of central nervous system drugs between humans and rodents can be explained by physiological differences between species. An important factor could be P-glycoprotein (Pgp) activity in the blood–brain barrier (BBB), as BBB expression of this drug efflux transporter is reportedly lower in humans compared to mouse and rat and subject to an age-dependent increase. This might complicate animal to human extrapolation of brain drug disposition and toxicity, especially in children. In this study, the potential species-specific effect of BBB Pgp activity on brain drug exposure was investigated. An age-dependent brain PBPK model was used to predict cerebrospinal fluid and brain mass concentrations of Pgp substrate drugs. For digoxin, verapamil and quinidine, in vitro kinetic data on their transport by Pgp were derived from literature and used to scale to in vivo parameters. In addition, age-specific digoxin transport was simulated for children with a postnatal age between 25 and 81 days. BBB Pgp activity in the model was optimized using measured CSF data for the Pgp substrates ivermectin, indinavir, vincristine, docetaxel, paclitaxel, olanzapine and citalopram, as no useful in vitro data were available. Inclusion of Pgp activity in the model resulted in optimized predictions of their brain concentration. Total brain-to-plasma AUC values (Kp,brain) in the simulations without Pgp were divided by the Kp,brain values with Pgp. Kp ratios ranged from 1 to 45 for the substrates investigated. Comparison of human with rodent Kp,brain ratios indicated ≥ twofold lower values in human for digoxin, verapamil, indinavir, paclitaxel and citalopram and ≥ twofold higher values for vincristine. In conclusion, BBB Pgp activity appears species-specific. An age-dependent PBPK model-based approach could be useful to extrapolate animal data to human adult and paediatric predictions by taking into account species-specific and developmental BBB Pgp expression.

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Boujelben, Ahmed, Michael Watson, Steven McDougall, Yi-Fen Yen, Elizabeth R. Gerstner, Ciprian Catana, Thomas Deisboeck, et al. "Multimodality imaging and mathematical modelling of drug delivery to glioblastomas." Interface Focus 6, no. 5 (October 6, 2016): 20160039. http://dx.doi.org/10.1098/rsfs.2016.0039.

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Patients diagnosed with glioblastoma, an aggressive brain tumour, have a poor prognosis, with a median overall survival of less than 15 months. Vasculature within these tumours is typically abnormal, with increased tortuosity, dilation and disorganization, and they typically exhibit a disrupted blood–brain barrier (BBB). Although it has been hypothesized that the ‘normalization’ of the vasculature resulting from anti-angiogenic therapies could improve drug delivery through improved blood flow, there is also evidence that suggests that the restoration of BBB integrity might limit the delivery of therapeutic agents and hence their effectiveness. In this paper, we apply mathematical models of blood flow, vascular permeability and diffusion within the tumour microenvironment to investigate the effect of these competing factors on drug delivery. Preliminary results from the modelling indicate that all three physiological parameters investigated—flow rate, vessel permeability and tissue diffusion coefficient—interact nonlinearly to produce the observed average drug concentration in the microenvironment.

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Filho, José, and Edson Gonçalves. "Jump Diffusion Modelling for the Brazilian Short-Term Interest Rate." Brazilian Business Review 12, no. 1 (February 5, 2015): 80–103. http://dx.doi.org/10.15728/bbr.2015.12.1.4.

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Verheggen, Inge C. M., Joost J. A. de Jong, Martin P. J. van Boxtel, Alida A. Postma, Jacobus F. A. Jansen, Frans R. J. Verhey, and Walter H. Backes. "Imaging the role of blood–brain barrier disruption in normal cognitive ageing." GeroScience 42, no. 6 (October 6, 2020): 1751–64. http://dx.doi.org/10.1007/s11357-020-00282-1.

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AbstractTo investigate whether blood–brain barrier (BBB) disruption is a potential mechanism of usual age-related cognitive decline, we conducted dynamic contrast–enhanced (DCE) MRI to measure BBB leakage in a healthy sample, and investigated the association with longitudinal cognitive decline. In a sample of neurologically and cognitively healthy, older individuals, BBB leakage rate in the white and grey matter and hippocampus was measured using DCE MRI with pharmacokinetic modelling. Regression analysis was performed to investigate whether the leakage rate was associated with decline in cognitive performance (memory encoding, memory retrieval, executive functioning and processing speed) over 12 years. White and grey matter BBB leakages were significantly associated with decline in memory retrieval. No significant relations were found between hippocampal BBB leakage and cognitive performance. BBB disruption already being associated with usual cognitive ageing, supports that this neurovascular alteration is a possible explanation for the cognitive decline inherent to the ageing process. More insight into BBB leakage during the normal ageing process could improve estimation and interpretation of leakage rate in pathological conditions. The current results might also stimulate the search for strategies to maintain BBB integrity and help increase the proportion people experiencing successful ageing. Netherlands Trial Register number: NL6358, date of registration: 2017-03-24.

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Huang, Qiao, Guangwu Chen, Yafei Wang, Shaoqing Chen, Lixiao Xu, and Rui Wang. "Modelling the global impact of China’s ban on plastic waste imports." Resources, Conservation and Recycling 154 (March 2020): 104607. http://dx.doi.org/10.1016/j.resconrec.2019.104607.

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Yinka-Banjo, Chika O., Isaac O. Osunmakinde, and Antoine Bagula. "Collision Avoidance in Unstructured Environments for Autonomous Robots: A Behavioural Modelling Approach." Advanced Materials Research 403-408 (November 2011): 3559–69. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3559.

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Collision avoidance is one of the important safety key operations that needs attention in the navigation system of an autonomous robot. In this paper, a Behavioural Bayesian Network approach is proposed as a collision avoidance strategy for autonomous robots in an unstructured environment with static obstacles. In our approach, an unstructured environment was simulated and the information of the obstacles generated was used to build the Behavioural Bayesian Network Model (BBNM). This model captures uncertainties from the unstructured environment in terms of probabilities, and allows reasoning with the probabilities. This reasoning ability enables autonomous robots to navigate in any unstructured environment with a higher degree of belief that there will be no collision with obstacles. Experimental evaluations of the BBNM show that when the robot navigates in the same unstructured environment where knowledge of the obstacles is captured, there is certainty in the degree of belief that the robot can navigate freely without any collision. When the same model was tested for navigation in a new unstructured environment with uncertainties, the results showed a higher assurance or degrees of belief that the robot will not collide with obstacles. The results of our modelling approach show that Bayesian Networks (BNs) have good potential for guiding the behaviour of robots when avoiding obstacles in any unstructured environment.

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Destriana, Rachmat, Hengki Rusdianto, Denis Chandra Prabowo, Dirgahayu Erri, and Jordy Lasmana Putra. "Interactive Application Development Using Augmented Reality Concept for Catalog Tire in Planet Ban Store Pasar Kemis." Jurnal Teknik Komputer 9, no. 1 (January 23, 2023): 41–45. http://dx.doi.org/10.31294/jtk.v9i1.14088.

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Currently, the company competes to maximize the role of technology in innovating and developing its business. One of them is PT Planet Ban Pasar Kemis in terms of promoting the latest tire products. In this case, researchers want to change the way Planet Ban promotes which has so far only used a 2D tire catalog by utilizing Android-based AR techniques. This makes it difﬁcult for customers to understand the tire products of PT Planet Ban Pasar Kemis. But with AR, customers only need to scan 2D catalog images with Android to see the tire model into 3D form. The system development method used by researchers is the waterfall method where the sequence and steps of research have been structured by the condition of PT Planet Ban. As for System Analysis and Design, researchers use Uniﬁed Modelling Language or UML methods, while product design uses blenders and unity to apply 2D catalog images into 3D models. To measure the success rate of the application, researchers conducted a testing phase using the black box testing method with results that match the test scenario so that the application can be used according to the needs of the user.

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Singh, N., D. Tampubolon, and V. S. S. Yadavalli. "Time series modelling of the Kobe-Osaka earthquake recordings." International Journal of Mathematics and Mathematical Sciences 29, no. 8 (2002): 467–79. http://dx.doi.org/10.1155/s0161171202007548.

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A problem of great interest in monitoring a nuclear test ban treaty (NTBT) is related to interpreting properly the differences between a waveform generated by a nuclear explosion and that generated by an earthquake. With a view of comparing these two types of waveforms, Singh (1992) developed a technique for identifying a model in time domain. Fortunately this technique has been found useful in modelling the recordings of the killer earthquake occurred in the Kobe-Osaka region of Japan at 5.46 am on 17 January, 1995. The aim of the present study is to show how well the method for identifying a model (developed by Singh (1992)) can be used for describing the vibrations of the above mentioned earthquake recorded at Charters Towers in Queensland, Australia.

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Radić-Perić, J. "Thermodynamic Modelling of Boron Nitride Formation in Thermal Plasma." Materials Science Forum 518 (July 2006): 349–54. http://dx.doi.org/10.4028/www.scientific.net/msf.518.349.

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The synthesis of solid BN in thermal plasma is investigated theoretically by computing the equilibrium composition of a gas mixture containing boron, nitrogen, hydrogen and argon. The calculations are done for the temperature range between 500 and 6000 K and the total pressure in the system of 1 bar. They are based on the fact that thermal plasma is in local thermodynamic equilibrium, which makes possible theoretical determination (by employing the Gibbs free energy data for the compounds present in the system) of its equilibrium composition. From the calculated compositions of investigated gas systems, the temperature zones with saturated and/or oversaturated vapour of B and B2N are determined and the formation mechanism of BN in solid state is proposed.

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Hanly, John G., Alexandra Legge, Lyna Kamintsky, Alon Friedman, Javeria A. Hashmi, Steven D. Beyea, John Fisk, et al. "Role of autoantibodies and blood–brain barrier leakage in cognitive impairment in systemic lupus erythematosus." Lupus Science & Medicine 9, no. 1 (June 2022): e000668. http://dx.doi.org/10.1136/lupus-2022-000668.

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ObjectiveCognitive impairment is common in patients with SLE but the cause is unknown. The current cross-sectional study examined the association between select SLE-related autoantibodies, other serological biomarkers and extensive blood–brain barrier (BBB) leakage in patients with SLE with and without cognitive impairment. In addition, we determined whether the relationship between SLE autoantibodies, other biomarkers and cognitive impairment differed depending on the presence or absence of concurrent extensive BBB leakage.MethodsConsecutive patients with SLE, recruited from a single academic medical centre, underwent formal neuropsychological testing for assessment of cognitive function. On the same day, BBB permeability was determined using dynamic contrast-enhanced MRI scanning. SLE autoantibodies and other serological biomarkers were measured. Regression modelling was used to determine the association between cognitive impairment, extensive BBB leakage and autoantibodies/biomarkers.ResultsThere were 102 patients with SLE; 90% were female and 88% were Caucasian, with a mean±SD age of 48.9±13.8 years. The mean±SD SLE disease duration was 14.8±11.0 years. Impairment in one or more cognitive tests was present in 47 of 101 (47%) patients and included deficits in information processing speed (9%), attention span (21%), new learning (8%), delayed recall (15%) and executive abilities (21%). Extensive BBB leakage was present in 20 of 79 (25%) patients and was associated with cognitive impairment (15 of 20 (75%) vs 24 of 59 (41%); p=0.01) and shorter disease duration (median (IQR): 7 (8–24 years) vs 15 (2–16 years); p=0.02). No serological parameters were associated with extensive BBB leakage and there was no statistically significant association between cognitive impairment and circulating autoantibodies even after adjusting for BBB leakage.ConclusionsExtensive BBB leakage alone was associated with cognitive impairment. These findings suggest that BBB leakage is an important contributor to cognitive impairment, regardless of circulating SLE-related autoantibodies.

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Higham, Charles, and Thomas Higham. "A new chronological framework for prehistoric Southeast Asia, based on a Bayesian model from Ban Non Wat." Antiquity 83, no. 319 (March 1, 2009): 125–44. http://dx.doi.org/10.1017/s0003598x00098136.

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AbstractThe authors offer a new chronological framework for prehistoric Southeast Asia, based mainly on the Bayesian modelling of 75 radiocarbon dates from well-stratified excavations at Ban Non Wat. The results are revolutionary. Neolithic practice now begins in the second millennium and hierarchical state-forming activity is dated to a ‘starburst’ around 1000 BC. The authors reflect on the social implications of the new model – and on the criteria for an ever stronger chronology.

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Kumar, Sunil, and Devendra Kumar. "Fractional modelling for BBM-Burger equation by using new homotopy analysis transform method." Journal of the Association of Arab Universities for Basic and Applied Sciences 16, no. 1 (October 2014): 16–20. http://dx.doi.org/10.1016/j.jaubas.2013.10.002.

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Ntshabele, Koketso, Bassey Isong, Naison Gasela, and Adnan M. Abu-Mahfouz. "A Trusted Security Key Management Server in LoRaWAN: Modelling and Analysis." Journal of Sensor and Actuator Networks 11, no. 3 (September 5, 2022): 52. http://dx.doi.org/10.3390/jsan11030052.

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The traditional Long-Range Wide-Area Network (LoRaWAN) uses an Advanced Encryption Standard (AES) 128 bit symmetric key to secure entities and data against several attacks. However, due to the existence of heterogeneous applications, designing a globally accepted and resilient LoRaWAN security model is challenging. Although several security models to maximize the security efficiency in LoRaWAN exist using the trusted key server to securely manage the keys, designing an optimum LoRaWAN security model is yet to be fully realized. Therefore, in this paper, we proposed two LoRaWAN security algorithms, A and B, for a trusted key management server (TKMS) to securely manage and distribute the keys amongst the entities. Algorithm B is an enhanced version of Algorithm A, which utilizes the security shortcomings of Algorithm A. We employed two formal analysis methods in the modelling, results analysis, and verification. The Scyther security verification tool was used for algorithm modelling and analysis against all possible attacks, while BAN logic was used to prove the logical correctness of the proposed algorithms. The results indicate that BAN logic feasibly proves the model logic correctness and the security claims employed in Scyther are reliable metrics for assessing the algorithms’ security efficiency. The security claims proved that the security algorithm is more secure and reliable as no attacks were detected across all entities in the enhanced-Algorithm B, unlike in Algorithm A. Moreover, the application of hashing minimizes computation cost and time for authentication and message integrity as compared to symmetric and asymmetric encryption. However, the proposed algorithm is yet to be verified as completely lightweight.

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Wik, T. "Trickling Filters and Biofilm Reactor Modelling." Reviews in Environmental Science and Bio/Technology 2, no. 2-4 (2003): 193–212. http://dx.doi.org/10.1023/b:resb.0000040470.48460.bb.

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García-Salvador, Adrián, Alazne Domínguez-Monedero, Paloma Gómez-Fernández, Amaia García-Bilbao, Susana Carregal-Romero, Joaquín Castilla, and Felipe Goñi-de-Cerio. "Evaluation of the Influence of Astrocytes on In Vitro Blood–Brain Barrier Models." Alternatives to Laboratory Animals 48, no. 4 (July 2020): 184–200. http://dx.doi.org/10.1177/0261192920966954.

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In vitro blood–brain barrier (BBB) models are a useful tool to screen the permeability and toxicity of new drugs. Currently, many different in vitro BBB models coexist, but none stands out as being notably better than the rest. Therefore, there is still a need to evaluate the quality of BBB models under various conditions and assess their ability to mimic the in vivo situation. In this study, two brain endothelial cell lines (bEnd.3 and hCMEC/D3) and two epithelial-like cell lines (MDCKII and Caco-2) were selected for BBB modelling purposes. They were grown as monolayers of a single cell type, under the following conditions: in coculture with either primary or immortalised astrocytes; or in the presence of primary or immortalised astrocyte-derived conditioned media. A total of 20 different BBB models were established in this manner, in order to assess the effects of the astroglial components on the BBB phenotype in each case. To this end, six parameters were studied: the expression of selected tight junction proteins; the enzyme activities of alkaline phosphatase and of gamma glutamyl transpeptidase; the transendothelial/transepithelial electrical resistance (TEER); restriction in paracellular transport; and efflux transporter inhibition were each evaluated and correlated. The results showed that coculturing with either primary or immortalised astrocytes led to a general improvement in all parameters studied, evidencing the contribution of this cell type to effective BBB formation. Furthermore, the permeability coefficient ( P e) of the tracer molecule, Lucifer Yellow, correlated with three of the six parameters studied. In addition, this study highlights the potential for the use of the Lucifer Yellow P e value as an indicator of barrier integrity in in vitro BBB models, which could be useful for screening the permeability of new drugs.

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Delvika, Yuana. "SISTEM INFORMASI MANAJEMEN PERSEDIAAN SUKU CADANG PADA PERUSAHAAN PENYEWAAN KENDARAAN." Jurnal Sistem Teknik Industri 18, no. 2 (August 14, 2018): 84–89. http://dx.doi.org/10.32734/jsti.v18i2.353.

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Persediaan suku cadang tepat waktu merupakan aset yang cukup penting pada perusahaan penyewaan kendaraan khususnya dalam penyelesaian program perawatan dan perbaikan tepat waktu sehingga kendaraan yang siap pakai tersedia pada saat dibutuhkan. Kenyataannya di perusahaan, pada bulan Februari, ada 104 jam waktu menganggur karena menunggu suku cadang tiba di lokasi perbaikan. Pada bulan Maret, ada 169 jam waktu menganggur akibat suku cadang terlambat tiba. Dan pada bulan April, ada 161 jam waktu menganggur untuk menunggu suku cadang tiba. Hal ini menyebabkan seringnya terjadi keterlambatan dalam pengadaan suku cadang sehubungan dengan ketidakjelasan sistem informasi dalam pengelolaan suku cadang. Untuk mengatasi permasalahan di atas, maka dilakukan perancangan data base dan perancangan sistem informasi. Perancangan data base dengan melakukan pengkodean grup suku cadang, pengkodean suku cadang, pengklasifikasian suku cadang dan penentuan elemen-elemen persediaan. Perancangan sistem informasi yang dilakukan dengan metode unified modelling language. Hasil yang diperoleh dengan menerapkan sistem ini adalah pengematan Rp. 9,090,432.56 untuk suku cadang jenis ban, penghematan Rp. 947,025.47 untuk suku cadang jenis ban dalam, penghematan Rp. 1,298,446.09 untuk suku cadang jenis oli, penghematan Rp. 1,198,187.93 untuk suku cadang jenis oli hidrolik, penghematan Rp. 1,559,882.97 untuk suku cadang jenis minyak pelumas, penghematan Rp. 1,285,816.22 untuk suku cadang jenis ban vulkanisir dan penghematan Rp. 5,843,724.47 untuk suku cadang jenis selendang ban.

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Ivan, Ivan. "Model Dinamika Sistem Pasokan dan Distribusi pada Gangguan Pendistribusian BBM PT. Pertamina Padang." Jurnal Optimasi Sistem Industri 11, no. 2 (April 28, 2016): 243. http://dx.doi.org/10.25077/josi.v11.n2.p243-252.2012.

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This paper discusses supply and distribution Bahan Bakar Minyak (BBM) system at PERTAMINA Padang to look a performancy system that disturbance of distribution like replacement Automatic Circuit Breaker (ACB). The replacement of ACB processes about 12 hours and causes the distributing activity of BBM to Stasiun Pengisian Bahan Bakar Umum (SPBU) has to be stopped. It makes impact toward the work ability of supplying and distributing system. Therefore, a planning model which is able to see the impact of ACB replacement toward system behavior of supplying and distributing is needed. Purpose of the modelling is to study the behavioral effects of variable in supply and distribution system using causal loop diagram and stock flow diagram. Result of this diagram has built simulation model to analyze performance system. Verification testing done by the method of checking the level and flow and testing of the coding. Validation of the model while the testing is done by operational graphics and the variability parameter sensitivity analysis. The model was designed and carried out the design of simulated scenarios to determine a strategy for decision-makers to look at the performance of BBM supply and distribution system. Keywords: BBM, supplying, distributing, ACB replacement, dynamic system

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Odjugo, Tega, Yahaya Baba, Aliyu Aliyu, Ndubuisi Okereke, Lekan Oloyede, and Olabisi Onifade. "Optimisation of Artificial Lifts Using Prosper Nodal Analysis for BARBRA-1 Well in Niger Delta." Nigerian Journal of Technological Development 17, no. 3 (October 29, 2020): 150–55. http://dx.doi.org/10.4314/njtd.v17i3.1.

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Hydrocarbon exploration basically requires effective drilling and efficient overpowering of frictional and viscosity forces. Normally, frictional power losses occur in deep well systems and it is essential to analyse each component of any well system to determine where exactly pressure is lost, and this can be done using Nodal Analysis. In this study, nodal analysis has been carried out with the use of PROSPER, a software for well performance, design and optimisation. Artificial lifts can then be used to solve the problem of frictional power losses. To increase the production of Barbra 1 well in the Niger Delta and hence extend its functional life, we have applied nodal analysis. Modelling results for three artificial lift methods; continuous gas lift, intermittent gas lift and electrical submersible pump were found to be 1734.93 bbl/day, 451.50 bbl/day and 2869 bbl/day respectively. The output from the well performance without artificial lift was 1370.99 bbl/day by applying Darcy’s model. Meanwhile, the output from the well without artificial lift is 89.90 bbl/day when aided with productivity index (PI) entry, the normal model for intermittent gas lift. Hence, from the comparative analysis of the results obtained from this study, it was deduced that when artificial lifts are employed, the well output increases significantly from 1370.99bbl/day to 2869 bbl/day (electrical submersible pump). This study concludes that wells such as Barbra 1 are good candidates for artificial lift, and this is evidenced by increasing productivity. Keywords: Production optimisation, nodal analysis, prosper simulator and barbra well.

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Thonse Hawaldar, Iqbal, Bharat Kumar Meher, Puja Kumari, and Santosh Kumar. "Modelling the effects of capital adequacy, credit losses, and efficiency ratio on return on assets and return on equity of banks during COVID-19 pandemic." Banks and Bank Systems 17, no. 1 (March 30, 2022): 115–24. http://dx.doi.org/10.21511/bbs.17(1).2022.10.

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The study aims to determine the impact of Capital Adequacy Ratio, Credit Losses Ratio and Efficiency Ratio on the two significant profitability ratios, namely Return on Assets (ROA) and Return on Equity (ROE), during the pandemic. Panel Data Regression is used to model the effects of Capital Adequacy, Credit Losses and Efficiency Ratio on Return on Assets and Return on Equity of Indian banks. A suitable model has been developed by analyzing the results of the Hausman test and the p-values. It has been found that Capital Adequacy Ratio (CAR) with coefficient value of –0.664, CET1 with coefficient value of 1.83 and efficiency ratio with coefficient value of 1.825 have significantly affected the return on assets as their p-values are less than 0.05. However, the accepted relationship between CAR and ROA, efficiency ratio and ROA were inverse, but their coefficients were significant. The provision for credit losses (PCL) was not affecting the ROA significantly during the pandemic and hence was not considered while framing the model. Again, the dependent variable is the return on equity, except CAR. Other ratios, i.e., CET1, efficiency ratio, and PCL ratio have unacceptable correlations and are even non-significant as their p-values are less than 0.05.

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Zhang, Jiangsong, Xianming Lin, Hui Zhou, Yuanyuan Chen, Shuangkai Xiao, Junyue Jiao, Yibin Zhao, and Zhong Di. "Electroacupuncture: A New Approach to Open the Blood–brain Barrier in Rats Recovering from Middle Cerebral Artery Occlusion." Acupuncture in Medicine 36, no. 6 (December 2018): 377–85. http://dx.doi.org/10.1136/acupmed-2017-011496.

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Objective To examine for an opening effect on the blood–brain barrier (BBB) in intact rats and rats with experimental ischaemia-reperfusion (I/R) during the recovery period after various electroacupuncture (EA) treatments with different time courses, and to determine whether there is a time-dependent effect. An additional objective was to determine whether this method could induce the penetration of nerve growth factor (NGF) through the BBB. Methods A middle cerebral artery occlusion (MCAO) model was first established. We chose different stimulation time courses and observed the effects of EA treatment (100 Hz frequency; 2 mA intensity) at GV20 and GV26 on the BBB in rats recovering from MCAO 3 weeks after modelling. The rats were injected with 2% Evans blue (EB) saline. The brain water content was measured using a wet/dry weighing method. The degree of penetration of EB was detected using spectrophotometry and laser confocal microscopy. The rats were then injected with NGF, and the concentration of NGF in the brain tissues was measured using ELISA. Results The increase in the BBB permeability was most notable following the 8 min EA stimulation (P<0.05), which may be advantageous for the targeted delivery of drugs (such as NGF) into the brain. Additionally, this effect did not appear to cause brain oedema (P>0.05) in healthy or MCAO rats. Conclusions EA treatment for a certain stimulation time at GV20 and GV26 in MCAO rats can increase BBB permeability.

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Setiyani, Lila, and Benny Setiawan. "ANALISIS DAN DESIGN MANAJEMEN CONTROL PRODUKSI MENGGUNAKAN BUSINESS PROCESS IMPROVEMENT DAN UNIFIED MODELLING LANGUAGE (STUDI KASUS: PT. MULTISTRADA)." Jurnal Interkom: Jurnal Publikasi Ilmiah Bidang Teknologi Informasi dan Komunikasi 16, no. 1 (April 28, 2021): 27–37. http://dx.doi.org/10.35969/interkom.v16i1.132.

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Di era industri 4.0 kecepatan dan ketepatan sebuah sistem informasi sangat dibutuhkan di dalam sebuah manufaktur seperti di dalam proses produksi.dimana sebuah laporan sangat diperlukan kecepatan dan ketepatannya dalam penyajian data yang dibutuhkan terhadap user yang berhubungan didalam proses produksi tersebut. PT Multistrada adalah salah satu perusahaan multinasional yang bergerak di bidang ban kendaraan bermotor yang mengaplikasikan sistem informasi untuk mempermudah kontrol dan sebagai dasar acuan pengembangan dan perbaikan berkelanjutan. Permasalahan yang terjadi pada sistem yang sedang berjalan yaitu tidak adanya sistem yang mengakomodir data inventory produksi yang menghambat proses monitoring terhadap keluar masuk barang atau size tyre yang sedang di produksi sebagai acuan pengiriman ban ke gudang logistik. Penelitian ini bertujuan untuk membangun sebuah Aplikasi Management Control Produksi yang dibangun menggunakan metode BPMN, PHP sebagai bahasa pemograman dan menggunakan permodelan sistem Unified Modeling Language (UML).

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Umar, Sarehati, Norhisham Bakhary, and Airil Yasreen Mohd Yassin. "Comparative Study on Design of Experiment in Frequency-Based Response Surface Methodology for Damage Detection." Applied Mechanics and Materials 735 (February 2015): 168–73. http://dx.doi.org/10.4028/www.scientific.net/amm.735.168.

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This paper investigates the performance of design of experiment (DOE) in response surface methodology (RSM) for vibration-based damage detection. The ability of three major types of DOE, namely central composite design (CCD), Box-Behnken (BBD) and D-optimal (Dopt) for damage detection based on modal frequency are investigated and compared. A procedure comprising three main stages—sampling, response surface (RS) modelling and model updating—are employed for damage localisation and quantification. By considering Young’s modulus and modal frequency as respective input and output, a set of samples is generated from each DOE. Full quadratic functions are considered in RS modelling while model updating is performed for damage detection. The performances of DOE are compared based on damage detectability. A numerical simply supported beam is used as case study by considering several single damage cases. The results show that CCD provides better prediction compared to other DOEs.

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Effendi, Rustam, Yasin Efendi, Ainun Najib, Ainun Najib, and Ainun Najib. "PERANCANGAN SISTEM INFORMASI PENJUALAN BERBASIS WEB PADA BENGKEL KARUNIA BAN PAMULANG." Journal of Innovation And Future Technology (IFTECH) 3, no. 1 (February 4, 2021): 49–55. http://dx.doi.org/10.47080/iftech.v3i1.1153.

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The use of technology in the company not only supports business processes but also very important on corporate earning. Business ownerhave always pay attention to the development of the existing technology in order to improve their business success. Therefore many companies want to implement the technology edgein every aspect ofits business processes. Karunia Ban machine shop is a trading company that sells a wide range of tires, especially for goods and service fees. Sales transactions that occur on Karunia Ban shop are still being done manually. Companies often find it difficult to know which sales transaction that are for spare parts or for repair services, so we need an information system tosolve the problem. Information systems is expected to optimize the sales in Karunia Ban machine shop. The methodology that we used to analysis and to develop the structured system are using UML (Unified Modelling Laguage). The expected results from this paper is to establisha procedure that describes a system using UML analysis and design a system that runs the system, the draft also produced a web-based sales application using php and my sql.

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Woodall, Alan A., Emma J. Sandbach, Catherine M. Woodward, Paul Aveyard, and Graham Merrington. "The partial smoking ban in licensed establishments and health inequalities in England: modelling study." BMJ 331, no. 7515 (August 19, 2005): 488–89. http://dx.doi.org/10.1136/bmj.38576.467292.eb.

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Böcker, Thomas, Wolfgang Britz, and Robert Finger. "Modelling the Effects of a Glyphosate Ban on Weed Management in Silage Maize Production." Ecological Economics 145 (March 2018): 182–93. http://dx.doi.org/10.1016/j.ecolecon.2017.08.027.

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van der Hilst, Floor, Judith A. Verstegen, Tetiana Zheliezna, Olga Drozdova, and André P. C. Faaij. "Integrated spatiotemporal modelling of bioenergy production potentials, agricultural land use, and related GHG balances; demonstrated for Ukraine." Biofuels, Bioproducts and Biorefining 8, no. 3 (March 18, 2014): 391–411. http://dx.doi.org/10.1002/bbb.1471.

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Darde, Benjamin, Anh Minh Tang, Jean-Michel Pereira, Patrick Dangla, Jean-Noël Roux, Jean Talandier, and Minh Ngoc Vu. "Modelling the hydromechanical behaviour of expansive granular mixtures upon hydration." E3S Web of Conferences 195 (2020): 02006. http://dx.doi.org/10.1051/e3sconf/202019502006.

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Bentonite pellet-powder mixtures are candidate sealing materials in radioactive waste disposal concepts. The mixture is installed in galleries in dry state as a granular material. The material is progressively hydrated by the pore water of the host rock and becomes homogeneous. Before homogenisation, the granular structure controls the material behaviour. In the present work, a modelling approach able to address particular features of pellet-powder mixtures is introduced. Two domains are considered: i) granular, and ii) homogeneous. The material behaviour before homogenisation is studied through Discrete Element Method (DEM) simulations. Constitutive laws for the granular state are proposed from DEM results. The behaviour of the homogenised material is described by a modified Barcelona Basic Model (BBM). Transition from granular to homogeneous states depends on suction and relative volume fractions of pellets and powder. Swelling pressure tests performed in the laboratory are satisfactorily simulated using this approach.

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Sumfleth, Beike, Stefan Majer, and Daniela Thrän. "Recent Developments in Low iLUC Policies and Certification in the EU Biobased Economy." Sustainability 12, no. 19 (October 2, 2020): 8147. http://dx.doi.org/10.3390/su12198147.

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The development of a sustainable biobased economy (BBE) in Europe is associated with several challenges. Amongst others, lessons learned from the development of the biofuel sector and the complex debate around land use change associated with a growing demand for biomass have to be considered when developing BBE policies. In that regard, strategies to identify and verify feedstocks with low potential risks for direct and indirect land use change (iLUC) impacts are of specific importance. Complementing existing efforts to assess iLUC with modelling activities, the European Commission (EC) has proposed a risk-based approach, aiming to differentiate high and low iLUC risk biomass. Amongst others, different additionality measures can be used to produce certified biomass with low iLUC risk. However, a comprehensive overview and analysis of these additionality measures and the challenges related to their integration in an integer verification approach is still missing. Therefore, we analyse European Union (EU) policies dealing with iLUC, iLUC risk assessment studies, certification approaches, and iLUC modelling studies to identify and develop additionality practices potentially applicable in certification and to show how the potential application of the proposed measures could be realised and verified in practice. We identified five potential practices for low iLUC risk biomass production, which are likely to be used by market actors. For each practice, we identified methods for the determination of low iLUC risk feedstock and products. Finally, our review includes recommendations for follow-up activities towards the actual implementation of additionality measures in biomass certification schemes.

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Journal articles on the topic 'BBN modelling'

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