Parallel simulation and optimization framework of supplies production processes for unconventional emergencies.
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ABSTRACT:
SUBMITTER: Zhu D
PROVIDER: S-EPMC8758009 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionThe management of neurologic emergencies is an important component of critical care fellowship training. Additional training in neurocritical care has been demonstrated to improve clinical outcomes, though exposure to these emergencies during training can be limited.MethodsThree simulation cases are presented as part of a comprehensive neurologic emergencies curriculum for critical care trainees. The cases represent neurologic catastrophes encountered in the intensive care unit consisting of symptomatic hyponatremia, severe alcohol withdrawal syndrome, and brain herniation syndrome. The case descriptions are complete with learning objectives, critical actions checklists, and debriefing material for facilitators, as well as all necessary personnel briefs and required equipment.ResultsThe scenarios were completed over the course of the 2016-2017 academic year by first-year critical care fellows. Following curriculum implementation, there was an improvement in self-perceived confidence of fellows in neurologic emergency management skills.DiscussionThe cases were felt to be realistic and beneficial and led to perceived improvement in management of neurologic emergencies and leadership during clinical crises.
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Project description:Epidemics require dynamic response strategies that encompass a multitude of policy alternatives and that balance health, economic and societal considerations. We propose a simulation–optimization framework to aid policymakers select closure, protection and travel policies to minimize the total number of infections under a limited budget. The proposed framework combines a modified, age-stratified SEIR compartmental model to evaluate the health impact of response strategies and a Genetic Algorithm to effectively search for better strategies. We implemented our framework on a real case study in Nova Scotia to devise optimized response strategies to COVID-19 under different budget scenarios and found a clear trade-off between health and economic considerations. Closure policies seem to be the most sensitive to policy restrictions, followed by travel policies. On the other hand, results suggest that practising social distancing and wearing masks are necessary whenever their economic impacts are bearable. The framework is generic and can be extended to encompass vaccination policies and to use different epidemiological models and optimization methods.
| S-EPMC8641975 | biostudies-literature
Project description:Greenhouse gases such as CO2 are considered effective materials in global warming due to their high absorptivity. So, lowering atmospheric CO2 is one of the most practical strategies. Utilizing carbon dioxide in chemical processes is an applicable method. In this study, Aspen HYSYS 10 was used to investigate how carbon dioxide can be added to the process of dimethyl carbonate production, and the affective parameters of the process, including temperature, residence time, feed ratio, and recycle ratio, were evaluated. It was observed that the production of DMC grew as temperature rose. The simulation results also revealed that a maximum conversion of roughly 8% was attained in the MeOH/EC. Additionally, boosting the recycle ratio is detrimental, and the impact of temperature and MeOH/EC has been enhanced by increasing the residence time. The interactions of the above parameters have been studied by Design Expert 12. The optimum value of effective parameters for the production of dimethyl carbonate has been obtained as follows: temperature of 164.7° C, recycle ratio of 0.2, residence time of 139.45 min, and feed ratio of 5.9%, leading to the conversion of 70%.
| S-EPMC10558474 | biostudies-literature
Project description:BackgroundExperiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling.ResultsWe have developed URDME, a flexible software framework for general stochastic reaction-transport modeling and simulation. URDME uses Unstructured triangular and tetrahedral meshes to resolve general geometries, and relies on the Reaction-Diffusion Master Equation formalism to model the processes under study. An interface to a mature geometry and mesh handling external software (Comsol Multiphysics) provides for a stable and interactive environment for model construction. The core simulation routines are logically separated from the model building interface and written in a low-level language for computational efficiency. The connection to the geometry handling software is realized via a Matlab interface which facilitates script computing, data management, and post-processing. For practitioners, the software therefore behaves much as an interactive Matlab toolbox. At the same time, it is possible to modify and extend URDME with newly developed simulation routines. Since the overall design effectively hides the complexity of managing the geometry and meshes, this means that newly developed methods may be tested in a realistic setting already at an early stage of development.ConclusionsIn this paper we demonstrate, in a series of examples with high relevance to the molecular systems biology community, that the proposed software framework is a useful tool for both practitioners and developers of spatial stochastic simulation algorithms. Through the combined efforts of algorithm development and improved modeling accuracy, increasingly complex biological models become feasible to study through computational methods. URDME is freely available at http://www.urdme.org.
| S-EPMC3439286 | biostudies-literature
Project description:Query optimization is the process of identifying the best Query Execution Plan (QEP). The query optimizer produces a close to optimal QEP for the given queries based on the minimum resource usage. The problem is that for a given query, there are plenty of different equivalent execution plans, each with a corresponding execution cost. To produce an effective query plan thus requires examining a large number of alternative plans. Access plan recommendation is an alternative technique to database query optimization, which reuses the previously-generated QEPs to execute new queries. In this technique, the query optimizer uses clustering methods to identify groups of similar queries. However, clustering such large datasets is challenging for traditional clustering algorithms due to huge processing time. Numerous cloud-based platforms have been introduced that offer low-cost solutions for the processing of distributed queries such as Hadoop, Hive, Pig, etc. This paper has applied and tested a model for clustering variant sizes of large query datasets parallelly using MapReduce. The results demonstrate the effectiveness of the parallel implementation of query workloads clustering to achieve good scalability.
| S-EPMC8176525 | biostudies-literature
Project description: Not available
| S-EPMC2950185 | biostudies-literature
Project description:Spectrum allocation is one of the key issues to improve spectrum efficiency and has become the hot topic in the research of cognitive wireless network. This paper discusses the real-time feature and efficiency of dynamic spectrum allocation and presents a new spectrum allocation algorithm based on the master-slave parallel immune optimization model. The algorithm designs a new encoding scheme for the antibody based on the demand for convergence rate and population diversity. For improving the calculating efficiency, the antibody affinity in the population is calculated in multiple computing nodes at the same time. Simulation results show that the algorithm reduces the total spectrum allocation time and can achieve higher network profits. Compared with traditional serial algorithms, the algorithm proposed in this paper has better speedup ratio and parallel efficiency.
| S-EPMC4164817 | biostudies-other
Project description:Quantitative estimation of the radionuclide activity concentration in positron emission tomography (PET) requires precise modeling of PET physics. The authors are focused on designing unconventional PET geometries for specific applications. This work reports the creation of a generalized reconstruction framework, capable of reconstructing tomographic PET data for systems that use right cuboidal detector elements positioned at arbitrary geometry using a regular Cartesian grid of image voxels.The authors report on a variety of design choices and optimization for the creation of the generalized framework. The image reconstruction algorithm is maximum likelihood-expectation-maximization. System geometry can be specified using a simple script. Given the geometry, a symmetry seeking algorithm finds existing symmetry in the geometry with respect to the image grid to improve the memory usage/speed. Normalization is approached from a geometry independent perspective. The system matrix is computed using the Siddon's algorithm and subcrystal approach. The program is parallelized through open multiprocessing and message passing interface libraries. A wide variety of systems can be modeled using the framework. This is made possible by modeling the underlying physics and data correction, while generalizing the geometry dependent features.Application of the framework for three novel PET systems, each designed for a specific application, is presented to demonstrate the robustness of the framework in modeling PET systems of unconventional geometry. Three PET systems of unconventional geometry are studied. (1) Virtual-pinhole half-ring insert integrated into Biograph-40: although the insert device improves image quality over conventional whole-body scanner, the image quality varies depending on the position of the insert and the object. (2) Virtual-pinhole flat-panel insert integrated into Biograph-40: preliminary results from an investigation into a modular flat-panel insert are presented. (3) Plant PET system: a reconfigurable PET system for imaging plants, with resolution of greater than 3.3 mm, is shown. Using the automated symmetry seeking algorithm, the authors achieved a compression ratio of the storage and memory requirement by a factor of approximately 50 for the half-ring and flat-panel systems. For plant PET system, the compression ratio is approximately five. The ratio depends on the level of symmetry that exists in different geometries.This work brings the field closer to arbitrary geometry reconstruction. A generalized reconstruction framework can be used to validate multiple hypotheses and the effort required to investigate each system is reduced. Memory usage/speed can be improved with certain optimizations.
| S-EPMC4506302 | biostudies-other
Project description:Clinical simulation in obstetrics has turned out to be a tool that can reduce the rate of perinatal morbidity and mortality. The objective of this study was to analyze the impact and evaluate the effects of training with high-fidelity simulation of obstetric emergencies on a multidisciplinary group. The quasi-experimental research study was structured in three phases: a first phase where the most important obstetric emergencies were determined, a second phase of design and development of the selected cases for simulation training, and a third and final phase where the abilities and satisfaction of the multidisciplinary team were analyzed. Three scenarios and their respective evaluation tools of obstetric emergencies were selected for simulation training: postpartum hemorrhage, shoulder dystocia, and breech delivery. The health professionals significantly improved their skills after training, and were highly satisfied with the simulation experience (p < 0.05). An inter-observer agreement between good and excellent reliability was obtained. Regarding conclusions, we can state that high-fidelity obstetric emergency simulation training improved the competencies of the health professionals.
| S-EPMC7915121 | biostudies-literature
Project description:GoalTechnologies that augment human performance are the focus of intensive research and development, driven by advances in wearable robotic systems. Success has been limited by the challenge of understanding human-robot interaction. To address this challenge, we developed an optimization framework to synthesize a realistic human standing long jump and used the framework to explore how simulated wearable robotic devices might enhance jump performance.MethodsA planar, five-segment, seven-degree-of-freedom model with physiological torque actuators, which have variable torque capacity depending on joint position and velocity, was used to represent human musculoskeletal dynamics. An active augmentation device was modeled as a torque actuator that could apply a single pulse of up to 100 Nm of extension torque. A passive design was modeled as rotational springs about each lower limb joint. Dynamic optimization searched for physiological and device actuation patterns to maximize jump distance.ResultsOptimization of the nominal case yielded a 2.27 m jump that captured salient kinematic and kinetic features of human jumps. When the active device was added to the ankle, knee, or hip, jump distance increased to between 2.49 and 2.52 m. Active augmentation of all three joints increased the jump distance to 3.10 m. The passive design increased jump distance to 3.32 m by adding torques of 135, 365, and 297 Nm to the ankle, knee, and hip, respectively.ConclusionDynamic optimization can be used to simulate a standing long jump and investigate human-robot interaction.SignificanceSimulation can aid in the design of performance-enhancing technologies.
| S-EPMC5507207 | biostudies-literature