A General-Purpose Multiphase/Multispecies Model to Predict the Spread, Percutaneous Hazard, and Contact Dynamics for Nonporous and Porous Substrates and Membranes

A computational model to solve the coupled transport equations with chemical reaction and phase change for a liquid sessile droplet or the contact and spread of a sessile droplet between two approaching porous or non-porous surfaces, is developed. The model is general therefore it can be applied to toxic chemicals (contact hazard), drug delivery through porous organs and membranes, combustion processes within porous material, and liquid movements in the ground. The equation of motion and the spread of the incompressible liquid available on the primary surface for transfer into the contacting surface while reacting with other chemicals (or water) and/or the solid substrate are solved in a finite difference domain with adaptive meshing. The comparison with experimental data demonstrated the model is robust and accurate. The impact of the initial velocity on the spread topology and mass transfer into the pores is also addressed

A Simple Laboratory Experiment for the Measurement of Single Phase Permeability

A simple experiment for measuring single-phase permeability of fully saturated porous medium is introduced. The experiment utilizes radial flow of a non-volatile wetting fluid through a porous medium such as ceramic tile, concrete or sand. The radial position of flow front is measured as a function of time and the collected data are analyzed using Darcy\u27s Law to determine the permeability. In addition, the phenomenon of the multiphase flow through the medium with a broad pore size distribution is demonstrated

Cyclostationary Algorithm for Signal Analysis in Cognitive 4G Networks with Spectral Sensing and Resource Allocation

Cognitive Radio (CR) effectively involved in the management of spectrum to perform improved data transmission. CR system actively engaged in the data sensing, learning and dynamic adjustment of radio spectrum parameters with management of unused spectrum in the signal. The spectrum sensing is indispensable in the CR for the management of Primary Users (PUs) and Secondary users (SUs) without any interference. Spectrum sensing is considered as the effective adaptive signal processing model to evaluate the computational complexity model for the signal transmission through Matched filtering, Waveform and Cyclostationary based Energy sensing model. Cyclostationary based model is effective for the energy based sensing model based on unique characteristics with estimation of available channel in the spectrum to extract the received signal in the PU signal. Cyclostationary based model uses the spectrum availability without any periodic property to extract the noise features. This paper developed a Adaptive Cross Score Cyclostationary (ACSCS) to evaluate the spectrum sensing in the CR network. The developed ACSCS model uses the computational complexity with estimation of Signal-to-Interference-and-Noise Ratio (SINR) elimination of cost function. ACSCS model uses the Adaptive Least square Spectral Self-Coherence Restoral (SCORE) with the Adaptive Cross Score (ACS) to overcome the issues in CR. With the derived ACSCS algorithm minimizes the computational complexity based on cost function compared with the ACS algorithm. To minimize the computational complexity pipeline triangular array based Gram-Schmidt Orthogonalization (GSO) structure for the optimization of network. The simulation performance analysis with the ACSCS scheme uses the Rician Multipath Fading channel to estimate detection probability to sense the Receiver Operating Characteristics, detection probability and probability of false alarm using Maximum Likelihood (ML) detector. The ACSC model uses the Square-law combining (SLC) with the moment generation function in the multipath fading channel for the channel sensing with reduced computational complexity. The simulation analysis expressed that ACSC scheme achieves the maximal detection probability value of 1. The analysis expressed that proposed ACSC scheme achieves the improved channel estimation in the 4G communication environment

Anti–Neutrophil Extracellular Trap Antibodies in Antiphospholipid Antibody–Positive Patients: Results From the Antiphospholipid Syndrome Alliance for Clinical Trials and InternatiOnal Networking Clinical Database and Repository

OBJECTIVE: This study aimed to elucidate the presence, antigen specificities, and potential clinical associations of anti–neutrophil extracellular trap (anti-NET) antibodies in a multinational cohort of antiphospholipid (aPL) antibody–positive patients who did not have lupus. METHODS: Anti-NET IgG/IgM levels were measured in serum samples from 389 aPL-positive patients; 308 patients met the classification criteria for antiphospholipid syndrome. Multivariate logistic regression with best variable model selection was used to determine clinical associations. For a subset of the patients (n = 214), we profiled autoantibodies using an autoantigen microarray platform. RESULTS: We found elevated levels of anti-NET IgG and/or IgM in 45% of the aPL-positive patients. High anti-NET antibody levels are associated with more circulating myeloperoxidase (MPO)–DNA complexes, which are a biomarker of NETs. When considering clinical manifestations, positive anti-NET IgG was associated with lesions affecting the white matter of the brain, even after adjusting for demographic variables and aPL profiles. Anti-NET IgM tracked with complement consumption after controlling for aPL profiles; furthermore, patient serum samples containing high levels of anti-NET IgM efficiently deposited complement C3d on NETs. As determined by autoantigen microarray, positive testing for anti-NET IgG was significantly associated with several autoantibodies, including those recognizing citrullinated histones, heparan sulfate proteoglycan, laminin, MPO–DNA complexes, and nucleosomes. Anti-NET IgM positivity was associated with autoantibodies targeting single-stranded DNA, double-stranded DNA, and proliferating cell nuclear antigen. CONCLUSION: These data reveal high levels of anti-NET antibodies in 45% of aPL-positive patients, where they potentially activate the complement cascade. While anti-NET IgM may especially recognize DNA in NETs, anti-NET IgG species appear to be more likely to target NET-associated protein antigens

On the Variability of the Length Weight Relationship for Atlantic Bluefin Tuna, Thunnus thynnus (L.)

Following extensive review, a model of the Atlantic bluefin tuna (ABFT), Thunnus thynnus (L.), length–weight relationship for the eastern Atlantic and Mediterranean (RW = 0.0000188 SFL3.01247; Ec 1) is presented on the basis of samples of ABFT spawners, with an average value of index K = 2.03 ± 0.15SD, collected by the Atlantic traps of Portugal and Spain in the Strait of Gibraltar (1963; 1996–1998; 2000–2012), and a set of samples of juvenile fishes from ICCAT–GBYP (n = 707). The resulting model (Ec 1), together with the model used for the eastern stock assessment (RW = 0.000019607 SFL3.0092; Ec 2) and a recently adopted by ICCAT Standing Committee on Research and Statistics (SCRS) (RW = 0.0000315551 SFL2.898454; EAST) are analyzed in using a bi-variant sample [SFL (cm), RW (kg)] of 474 pairs of data with the aim of validating them and establishing which model(s) best fit the reality represented by the sample and, therefore, will have the greatest descriptive and predictive power. The result of the analysis indicates that the model EAST clearly underestimates the weight of spawning ABFT and that model Ec 2 overestimates it slightly, being model Ec 1 that best explains the data of the sample. The result of the classical statistical analysis is confirmed by means of the quantile regression technique, selecting the quantiles 5, 25, 50, 75, and 95%. Other fisheries and biological indicators also conclude that the model EAST gradually underestimates the weight of ABFT spawners (of 2–3 m) by 9–12.5 %, and does not meet the criterion that for RW = 725 kg (Wmax), SFL = 319.93 ± 11.3 cm (Lmax).Cort, JL.; Estruch Fuster, VD.; Neves Dos Santos, M.; Di Natale, A.; Abid, N.; De La Serna, JM. (2015). On the Variability of the Length Weight Relationship for Atlantic Bluefin Tuna, Thunnus thynnus (L.). Reviews in Fisheries Science & Aquaculture. 23(1):23-38. doi:10.1080/23308249.2015.1008625S2338231Aguado-Giménez, F., & García-García, B. (2005). Changes in some morphometric relationships in Atlantic bluefin tuna (Thunnus thynnus thynnus Linnaeus, 1758) as a result of fattening process. Aquaculture, 249(1-4), 303-309. doi:10.1016/j.aquaculture.2005.04.064Block, B. A., Teo, S. L. H., Walli, A., Boustany, A., Stokesbury, M. J. W., Farwell, C. J., … Williams, T. D. (2005). Electronic tagging and population structure of Atlantic bluefin tuna. Nature, 434(7037), 1121-1127. doi:10.1038/nature03463Chapman, E. W., Jørgensen, C., & Lutcavage, M. E. (2011). Atlantic bluefin tuna (Thunnus thynnus): a state-dependent energy allocation model for growth, maturation, and reproductive investment. Canadian Journal of Fisheries and Aquatic Sciences, 68(11), 1934-1951. doi:10.1139/f2011-109Cort, J. L., Arregui, I., Estruch, V. D., & Deguara, S. (2014). Validation of the Growth Equation Applicable to the Eastern Atlantic Bluefin Tuna,Thunnus thynnus(L.), UsingLmax, Tag-Recapture, and First Dorsal Spine Analysis. Reviews in Fisheries Science & Aquaculture, 22(3), 239-255. doi:10.1080/23308249.2014.931173Cort, J. L., Deguara, S., Galaz, T., Mèlich, B., Artetxe, I., Arregi, I., … Idrissi, M. (2013). Determination ofLmaxfor Atlantic Bluefin Tuna,Thunnus thynnus(L.), from Meta-Analysis of Published and Available Biometric Data. Reviews in Fisheries Science, 21(2), 181-212. doi:10.1080/10641262.2013.793284Fraser, K.Possessed. World Record Holder for Bluefin Tuna. Kingstown, Nova Scotia: T & S Office Essentials and printing, 243 pp. (2008).Fromentin, J.-M., & Powers, J. E. (2005). Atlantic bluefin tuna: population dynamics, ecology, fisheries and management. Fish and Fisheries, 6(4), 281-306. doi:10.1111/j.1467-2979.2005.00197.xHattour, A.Contribution a l’étude des Scombridés de Tunisie. Université de Tunis. Faculté des Sciences, 168 pp. (1979).Karakulak, S., Oray, I., Corriero, A., Deflorio, M., Santamaria, N., Desantis, S., & De Metrio, G. (2004). Evidence of a spawning area for the bluefin tuna (Thunnus thynnus L.) in the eastern Mediterranean. Journal of Applied Ichthyology, 20(4), 318-320. doi:10.1111/j.1439-0426.2004.00561.xKoenker, R., & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33. doi:10.2307/1913643Koenker, R. (2005). Quantile Regression. doi:10.1017/cbo9780511754098Milatou, N., & Megalofonou, P. (2014). Age structure and growth of bluefin tuna (Thunnus thynnus, L.) in the capture-based aquaculture in the Mediterranean Sea. Aquaculture, 424-425, 35-44. doi:10.1016/j.aquaculture.2013.12.037Perçin, F., & Akyol, O. (2009). Lengthâ weight and lengthâ length relationships of the bluefin tuna,Thunnus thynnusL., in the Turkish part of the eastern Mediterranean Sea. Journal of Applied Ichthyology, 25(6), 782-784. doi:10.1111/j.1439-0426.2009.01288.xPercin, F., & Akyol, O. (2010). Some Morphometric Relationships in Fattened Bluefin Tuna, Thunnus thynnus L., from the Turkish Aegean Sea. Journal of Animal and Veterinary Advances, 9(11), 1684-1688. doi:10.3923/javaa.2010.1684.1688Rooker, J. R., Alvarado Bremer, J. R., Block, B. A., Dewar, H., de Metrio, G., Corriero, A., … Secor, D. H. (2007). Life History and Stock Structure of Atlantic Bluefin Tuna (Thunnus thynnus). Reviews in Fisheries Science, 15(4), 265-310. doi:10.1080/10641260701484135Sinovcic, G., Franicevic, M., Zorica, B., & Cikes-Kec, V. (2004). Length-weight and length-length relationships for 10 pelagic fish species from the Adriatic Sea (Croatia). Journal of Applied Ichthyology, 20(2), 156-158. doi:10.1046/j.1439-0426.2003.00519.xTičina, V., Grubišić, L., Šegvić Bubić, T., & Katavić, I. (2011). Biometric characteristics of small Atlantic bluefin tuna (Thunnus thynnus, Linnaeus, 1758) of Mediterranean Sea origin. Journal of Applied Ichthyology, 27(4), 971-976. doi:10.1111/j.1439-0426.2011.01752.

Bringing Research and New Technology into the Undergraduate Curriculum: A Course in Computational Fluid Dynamics

As technology advances in the industries which graduating engineers wish to enter, technology in the undergraduate curriculum must also advance. A course in computational fluid dynamics was recently developed which meets the challenge of bringing advanced topics to undergraduate students. This paper addresses techniques used to enable undergraduates to enter the work force with the ability to solve and physically understand fluid dynamics problems requiring commercially available computational fluid dynamics codes and related software. Student projects involving grid generation, the solution to two-dimensional and three-dimensional problems, and the solution to multi-dimensional species flow problems are presented. Additionally, final term projects obtained from the students’ cooperative employers are discussed