968 resultados para spatial and stochastic modelling, bio-chemical kinetics, multi-scale simulation, systems biology


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Background: Among other causes the long-term result of hip prostheses in dogs is determined by aseptic loosening. A prevention of prosthesis complications can be achieved by an optimization of the tribological system which finally results in improved implant duration. In this context a computerized model for the calculation of hip joint loadings during different motions would be of benefit. In a first step in the development of such an inverse dynamic multi-body simulation (MBS-) model we here present the setup of a canine hind limb model applicable for the calculation of ground reaction forces. Methods: The anatomical geometries of the MBS-model have been established using computer tomography- (CT-) and magnetic resonance imaging- (MRI-) data. The CT-data were collected from the pelvis, femora, tibiae and pads of a mixed-breed adult dog. Geometric information about 22 muscles of the pelvic extremity of 4 mixed-breed adult dogs was determined using MRI. Kinematic and kinetic data obtained by motion analysis of a clinically healthy dog during a gait cycle (1 m/s) on an instrumented treadmill were used to drive the model in the multi-body simulation. Results and Discussion: As a result the vertical ground reaction forces (z-direction) calculated by the MBS-system show a maximum deviation of 1.75%BW for the left and 4.65%BW for the right hind limb from the treadmill measurements. The calculated peak ground reaction forces in z- and y-direction were found to be comparable to the treadmill measurements, whereas the curve characteristics of the forces in y-direction were not in complete alignment. Conclusion: In conclusion, it could be demonstrated that the developed MBS-model is suitable for simulating ground reaction forces of dogs during walking. In forthcoming investigations the model will be developed further for the calculation of forces and moments acting on the hip joint during different movements, which can be of help in context with the in silico development and testing of hip prostheses.

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In this project, have been studied to determine the appropriate model to spatial, temporal and diversity of demersal fishes in the Sea of Oman, including Trichiuridae, Nemipteridae, Haemulidae, Arridae, Synodontidae, Batoidfishes, Carangidae, Scianidae, Carchariniformes and Serranidae. This research became operational from catch data during 2003 to 2013 (in 2007, due to the lack of ship failed). Processing and calculations was evaluated by using the software Excel, SPSS, Arc GIS and table curve 3D highest biomass and abundance was showed in strata A and C and 10-30 m depth layers was showed the best condition biomass. In other words, highest biomass was showed in the eastern region in the Oman Sea than the central and western regions. Batoidfishes and Trichiuridae had the highest biomass .Depth factors was showed a significant correlation with the biomass. Scianidae, Serranidae and Haemulidae were showed a large decline. Synodontidae was showed a very large increase. The largest of Shannon index belong to central and western region of the Oman Sea. The highest Shannon index was showed 10-20 and 50-100 m, respectively. The Distribution maps based on the biomass was analyzed by using Arc GIS software. So that were identified in the first time in a ten-year period and carefully catch stations any economic of aquatic group. In conclusion, the depth can be found in the pattern of distribution, abundance and diversity of fish from away the beach so that follow specific pattern.

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Angiogenesis is a process by which new blood vessels are formed from the pre-existing vasculature, and it is a key process that leads to tumour development. Some studies have recognized phenolic compounds as chemopreventive agents; flavonoids, in particular, seem to suppress the growth of tumor cells modifying the cell cycle. Herein, the antiangiogenic activity of Roman chamomile (Chamaemelum nobile L.) extracts (methanolic extract and infusion) and the main phenolic compounds present (apigenin, apigenin-7-O-glucoside, caffeic acid, chlorogenic acid, luteolin, and luteolin-7-O-glucoside) was evaluated through enzymatic assays using the tyrosine kinase intracellular domain of the Vascular Endothelium Growth Factor Receptor-2 (VEGFR-2), which is a transmembrane receptor expressed fundamentally in endothelial cells involved in angiogenesis, and molecular modelling studies. The methanolic extract showed a lower IC50 value (concentration that provided 50% of VEGFR-2 inhibition) than the infusion, 269 and 301 μg mL(-1), respectively. Regarding phenolic compounds, luteolin and apigenin showed the highest capacity to inhibit the phosphorylation of VEGFR-2, leading us to believe that these compounds are involved in the activity revealed by the methanolic extract.

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Surface ozone is formed in the presence of NOx (NO + NO2) and volatile organic compounds (VOCs) and is hazardous to human health. A better understanding of these precursors is needed for developing effective policies to improve air quality. To evaluate the year-to-year changes in source contributions to total VOCs, Positive Matrix Factorization (PMF) was used to perform source apportionment using available hourly observations from June through August at a Photochemical Assessment Monitoring Station (PAMS) in Essex, MD for each year from 2007-2015. Results suggest that while gasoline and vehicle exhaust emissions have fallen, the contribution of natural gas sources to total VOCs has risen. To investigate this increasing natural gas influence, ethane measurements from PAMS sites in Essex, MD and Washington, D.C. were examined. Following a period of decline, daytime ethane concentrations have increased significantly after 2009. This trend appears to be linked with the rapid shale gas production in upwind, neighboring states, especially Pennsylvania and West Virginia. Back-trajectory analyses similarly show that ethane concentrations at these monitors were significantly greater if air parcels had passed through counties containing a high density of unconventional natural gas wells. In addition to VOC emissions, the compressors and engines involved with hydraulic fracturing operations also emit NOx and particulate matter (PM). The Community Multi-scale Air Quality (CMAQ) Model was used to simulate air quality for the Eastern U.S. in 2020, including emissions from shale gas operations in the Appalachian Basin. Predicted concentrations of ozone and PM show the largest decreases when these natural gas resources are hypothetically used to convert coal-fired power plants, despite the increased emissions from hydraulic fracturing operations expanded into all possible shale regions in the Appalachian Basin. While not as clean as burning natural gas, emissions of NOx from coal-fired power plants can be reduced by utilizing post-combustion controls. However, even though capital investment has already been made, these controls are not always operated at optimal rates. CMAQ simulations for the Eastern U.S. in 2018 show ozone concentrations decrease by ~5 ppb when controls on coal-fired power plants limit NOx emissions to historically best rates.

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The organophosphate temephos has been the main insecticide used against larvae of the dengue and yellow fever mosquito ( Aedes aegypti ) in Brazil since the mid-1980s. Reports of resistance date back to 1995; however, no systematic reports of widespread temephos resistance have occurred to date. As resistance investigation is paramount for strategic decision-making by health officials, our objective here was to investigate the spatial and temporal spread of temephos resistance in Ae. aegypti in Brazil for the last 12 years using discriminating temephos concentrations and the bioassay protocols of the World Health Organization. The mortality results obtained were subjected to spatial analysis for distance interpolation using semi-variance models to generate maps that depict the spread of temephos resistance in Brazil since 1999. The problem has been expanding. Since 2002-2003, approximately half the country has exhibited mosquito populations resistant to temephos. The frequency of temephos resistance and, likely, control failures, which start when the insecticide mortality level drops below 80%, has increased even further since 2004. Few parts of Brazil are able to achieve the target 80% efficacy threshold by 2010/2011, resulting in a significant risk of control failure by temephos in most of the country. The widespread resistance to temephos in Brazilian Ae. aegypti populations greatly compromise effective mosquito control efforts using this insecticide and indicates the urgent need to identify alternative insecticides aided by the preventive elimination of potential mosquito breeding sites.

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A criterion for selecting a coating for an energy pipeline is that the coating should have a suitable flexibility to meet the high strain demand during hydrostatic testing and during field bending. This requires knowledge of the level of strain demand for the pipeline, and also the maximum strain that could be
tolerated by the coating system. Whereas average strains imposed during manufacturing and construction are reasonably well predicted, there is insufficient understanding on the factors leading to localised deformation of the pipe. Significant work has been carried out in the past to develop tests for assessing
the coatings’ ability to handle a certain amount of strain based on bend testing, tensile testing and burst testing. However, there is a concern as to whether these tests properly represent localised micro-strains associated with construction activities including field bending and pressure testing, particularly pressure testing of pipelines designed for operation at 80% of specified minimum yield strength (SMYS). Consequently coatings considered "suitable" for modern pipelines may fail. The first issue discussed in this paper is main factors affecting strain localisation. The non-deterministic distributions of heterogeneities over the pipe provide a ground to consider the mechanisms of localisation as a stochastic process. An approach is proposed to quantify the maximum localised strain demand through cold field bending and hydrostatic experiments. Another issue discussed in this paper is the experimental assessment of coating flexibility under the effects of localised strains. Preliminary mandrel tests have been carried out to assess the uniformity of the imposed strain. Although mandrel testing has been shown to be a useful method for relative comparison of coating flexibility, it has several weaknesses that could significantly affect the reliability and reproducibility of the results.

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This paper is concerned with stochastic stability of a class of nonlinear discrete-time Markovian jump systems with interval time-varying delay and partially unknown transition probabilities. A new weighted summation inequality is first derived. We then employ the newly derived inequality to establish delay-dependent conditions which guarantee the stochastic stability of the system. These conditions are derived in terms of tractable matrix inequalities which can be computationally solved by various convex optimized algorithms. Numerical examples are provided to illustrate the effectiveness of the obtained results.

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Background: Remote telemonitoring holds great potential to augment management of patients with coronary heart disease (CHD) and atrial fibrillation (AF) by enabling regular physiological monitoring during physical activity. Remote physiological monitoring may improve home and community exercise-based cardiac rehabilitation (exCR) programs and could improve assessment of the impact and management of pharmacological interventions for heart rate control in individuals with AF.

Objective: Our aim was to evaluate the measurement validity and data transmission reliability of a remote telemonitoring system comprising a wireless multi-parameter physiological sensor, custom mobile app, and middleware platform, among individuals in sinus rhythm and AF.

Methods: Participants in sinus rhythm and with AF undertook simulated daily activities, low, moderate, and/or high intensity exercise. Remote monitoring system heart rate and respiratory rate were compared to reference measures (12-lead ECG and indirect calorimeter). Wireless data transmission loss was calculated between the sensor, mobile app, and remote Internet server.

Results: Median heart rate (-0.30 to 1.10 b∙min-1) and respiratory rate (-1.25 to 0.39 br∙min-1) measurement biases were small, yet statistically significant (all P≤.003) due to the large number of observations. Measurement reliability was generally excellent (rho=.87-.97, all P<.001; intraclass correlation coefficient [ICC]=.94-.98, all P<.001; coefficient of variation [CV]=2.24-7.94%), although respiratory rate measurement reliability was poor among AF participants (rho=.43, P<.001; ICC=.55, P<.001; CV=16.61%). Data loss was minimal (<5%) when all system components were active; however, instability of the network hosting the remote data capture server resulted in data loss at the remote Internet server during some trials.

Conclusions: System validity was sufficient for remote monitoring of heart and respiratory rates across a range of exercise intensities. Remote exercise monitoring has potential to augment current exCR and heart rate control management approaches by enabling the provision of individually tailored care to individuals outside traditional clinical environments.

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This paper investigates the manufacturing of aluminium-boron carbide composites using the stir casting method. Mechanical and physical properties tests to obtain hardness, ultimate tensile strength (UTS) and density are performed after solidification of specimens. The results show that hardness and tensile strength of aluminium based composite are higher than monolithic metal. Increasing the volume fraction of B4C, enhances the tensile strength and hardness of the composite; however over-loading of B4C caused particle agglomeration, rejection from molten metal and migration to slag. This phenomenon decreases the tensile strength and hardness of the aluminium based composite samples cast at 800 °C. For Al-15 vol% B4C samples, the ultimate tensile strength and Vickers hardness of the samples that were cast at 1000 °C, are the highest among all composites. To predict the mechanical properties of aluminium matrix composites, two key prediction modelling methods including Neural Network learned by Levenberg-Marquardt Algorithm (NN-LMA) and Thin Plate Spline (TPS) models are constructed based on experimental data. Although the results revealed that both mathematical models of mechanical properties of Al-B4C are reliable with a high level of accuracy, the TPS models predict the hardness and tensile strength values with less error compared to NN-LMA models.

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This study presents the procedure followed to make a prediction of the critical flutter speed for a composite UAV wing. At the beginning of the study, there was no information available on the materials used for the construction of the wing, and the wing internal structure was unknown. Ground vibration tests were performed in order to detect the structure’s natural frequencies and mode shapes. From tests, it was found that the wing possesses a high stiffness, presenting well separated first bending and torsional natural frequencies. Two finite element models were developed and matched to experimental results. It has been necessary to introduce some assumptions, due to the uncertainties regarding the structure. The matching process was based on natural frequencies’ sensitivity with respect to a change in the mechanical properties of the materials. Once experimental results were met, average material properties were also found. Aerodynamic coefficients for the wing were obtained by means of a CFD software. The same analysis was also conducted when the wing is deformed in its first four mode shapes. A first approximation for flutter critical speed was made with the classical V - g technique. Finally, wing’s aeroelastic behavior was simulated using a coupled CFD/CSD method, obtaining a more accurate flutter prediction. The CSD solver is based on the time integration of modal dynamic equations, requiring the extraction of mode shapes from the previously performed finite-element analysis. Results show that flutter onset is not a risk for the UAV, occurring at velocities well beyond its operative range.

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The first goal of this study is to analyse a real-world multiproduct onshore pipeline system in order to verify its hydraulic configuration and operational feasibility by constructing a simulation model step by step from its elementary building blocks that permits to copy the operation of the real system as precisely as possible. The second goal is to develop this simulation model into a user-friendly tool that one could use to find an “optimal” or “best” product batch schedule for a one year time period. Such a batch schedule could change dynamically as perturbations occur during operation that influence the behaviour of the entire system. The result of the simulation, the ‘best’ batch schedule is the one that minimizes the operational costs in the system. The costs involved in the simulation are inventory costs, interface costs, pumping costs, and penalty costs assigned to any unforeseen situations. The key factor to determine the performance of the simulation model is the way time is represented. In our model an event based discrete time representation is selected as most appropriate for our purposes. This means that the time horizon is divided into intervals of unequal lengths based on events that change the state of the system. These events are the arrival/departure of the tanker ships, the openings and closures of loading/unloading valves of storage tanks at both terminals, and the arrivals/departures of trains/trucks at the Delivery Terminal. In the feasibility study we analyse the system’s operational performance with different Head Terminal storage capacity configurations. For these alternative configurations we evaluated the effect of different tanker ship delay magnitudes on the number of critical events and product interfaces generated, on the duration of pipeline stoppages, the satisfaction of the product demand and on the operative costs. Based on the results and the bottlenecks identified, we propose modifications in the original setup.

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Landscape characteristics, disturbances, and temporal variability influence predator-prey relationships, but are often overlooked in experimental studies. In the Everglades, seasonal disturbances force the spatial overlap of predators and prey, potentially increasing predation risk for prey. This study examined seasonal and diel patterns of fish use of canals and assessed predation risk for small fishes using an encounter rate model. I deployed an imaging sonar in Everglades canals to quantify density and swimming speeds of fishes, and detect anti-predator behaviors by small fishes. Generally, seasonal declines of marsh water-levels increased the density of large fishes in canals. Densities of small and large fishes were positively correlated and, as small-fish density increased, schooling frequency also increased. At night, schools disbanded and small fishes were observed congregating along the canal edge. The encounter rate model predicted highest predator-prey encounters during the day, but access to cover may reduce predation risk for small fishes.

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Detection canines represent the fastest and most versatile means of illicit material detection. This research endeavor in its most simplistic form is the improvement of detection canines through training, training aids, and calibration. This study focuses on developing a universal calibration compound for which all detection canines, regardless of detection substance, can be tested daily to ensure that they are working with acceptable parameters. Surrogate continuation aids (SCAs) were developed for peroxide based explosives along with the validation of the SCAs already developed within the International Forensic Research Institute (IFRI) prototype surrogate explosives kit. Storage parameters of the SCAs were evaluated to give recommendations to the detection canine community on the best possible training aid storage solution that minimizes the likelihood of contamination. Two commonly used and accepted detection canine imprinting methods were also evaluated for the speed in which the canine is trained and their reliability. As a result of the completion of this study, SCAs have been developed for explosive detection canine use covering: peroxide based explosives, TNT based explosives, nitroglycerin based explosives, tagged explosives, plasticized explosives, and smokeless powders. Through the use of these surrogate continuation aids a more uniform and reliable system of training can be implemented in the field than is currently used today. By examining the storage parameters of the SCAs, an ideal storage system has been developed using three levels of containment for the reduction of possible contamination. The developed calibration compound will ease the growing concerns over the legality and reliability of detection canine use by detailing the daily working parameters of the canine, allowing for Daubert rules of evidence admissibility to be applied. Through canine field testing, it has been shown that the IFRI SCAs outperform other commercially available training aids on the market. Additionally, of the imprinting methods tested, no difference was found in the speed in which the canines are trained or their reliability to detect illicit materials. Therefore, if the recommendations discovered in this study are followed, the detection canine community will greatly benefit through the use of scientifically validated training techniques and training aids.

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With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.