A mesoscale finite element simulation of intermittent plastic flow of micropillar compression under hybrid loading mode

The plastic deformation of the micropillar proceeds as a series of strain bursts, showing an intermittent plastic flow. In this work, we present a stochastic finite element method in crystal plasticity to describe the intermittent characteristic of crystal deformation under the hybrid loading mode (HLM). The microscopic boundary conditions(MBCs) using the HLM are studied and they are demonstrated to be different in various deformation periods such as loading stage, burst slip and holding stage, which occur alternatively as the plastic flow proceeds. In order to determine the MBCs, we use the Monte Carlo (MC) stochastic model to predict the amplitude of the burst displacement and then incorporate such model into our established continuum framework accounting for the characteristics of the strain burst. By implementing this continuum model into the finite element analysis, we predict the plastic flow of single crystal nickel micropillars that deform under uniaxial compression along the [2 6 9] crystalline direction. The simulation results indicate clearly visible strain bursts in the course of plastic deformation, producing a stair-case like stress-strain behavior that agrees well with experimental observations. The computational results reveal that the intermittent flow in the micrometer-scale is intensified due to the increasing amplitude of the strain burst, as well as the occurrence of successive strain bursts rather than the discrete strain bursts, with decreasing of the specimen size. In addition, the micropillar displacement in the context of burst activity predicted from our simulations is similar to the experimental observations. We demonstrate that our simulation method could provide further insights into the intermittent plastic flow characteristics such as burst time duration, micropillar velocity; plus, it is feasible to apply this method to investigate the plastic flow behaviors under complex loading conditions

Multivariate adaptive regression splines for estimating riverine constituent concentrations

Regression-based methods are commonly used for riverine constituent concentration/flux estimation, which is essential for guiding water quality protection practices and environmental decision making. This paper developed a multivariate adaptive regression splines model for estimating riverine constituent concentrations (MARS-EC). The process, interpretability and flexibility of the MARS-EC modelling approach, was demonstrated for total nitrogen in the Patuxent River, a major river input to Chesapeake Bay. Model accuracy and uncertainty of the MARS-EC approach was further analysed using nitrate plus nitrite datasets from eight tributary rivers to Chesapeake Bay. Results showed that the MARS-EC approach integrated the advantages of both parametric and nonparametric regression methods, and model accuracy was demonstrated to be superior to the traditionally used ESTIMATOR model. MARS-EC is flexible and allows consideration of auxiliary variables; the variables and interactions can be selected automatically. MARS-EC does not constrain concentration-predictor curves to be constant but rather is able to identify shifts in these curves from mathematical expressions and visual graphics. The MARS-EC approach provides an effective and complementary tool along with existing approaches for estimating riverine constituent concentrations

Formulation of Berberine Hydrochloride and Hydroxypropyl-&#946-Cyclodextrin Inclusion Complex with Enhanced Dissolution and Reduced Bitterness

Purpose: To prepare and characterize inclusion complex of berberine hydrochloride with hydroxypropyl-â-cyclodextrin in order to achieve enhanced solubility and reduced bitterness of the former.Methods: The inclusion complex of berberine hydrochloride with hydroxypropyl-â-cyclodextrin (1:1) was prepared by freeze-drying method and compared with the the physical mixtures of the compounds. Inclusion complexation was studied by phase solubility diagram, differential thermal analysis, spectrophotometric characterization and dissolution rate. The solubility of the formulations was evaluated by saturation solubility studies while their bitterness was tested in human volunteers.Results: Differential thermal analysis and spectrophotometric characterization indicate that berberine hydrochloride formed inclusion complex with hydroxypropyl-â-cyclodextrin. The phase solubility diagramof berberine hydrochloride with hydroxypropyl-â-cyclodextrin was of AL-type, with a stability constant was 694.5 L/mol at 25 oC. The solubility of berberine hydrochloride was increased by 5.27 times for thecomplex at a concentration of 0.01 mol/L. The dissolution of berberine hydrochloride after 20 min from the inclusion complex, physical mixture and pure berberine hydrochloride was 89.6, 69.8 and 58.8 %, respectively. The bitterness of the inclusion complex was considerably lower than that of the drug alone or the physical mixture with hydroxypropyl-â-cyclodextrin.Conclusion: The inclusion complex demonstrated improved dissolution properties and lowered the bitterness of berberine hydrochloride.Keywords: Berberine hydrochloride, Hydroxypropyl-â-cyclodextrin, Inclusion complex, Solubility,Bitternes

Two years of measurements of atmospheric total gaseous mercury (TGM) at a remote site in Mt. Changbai area, Northeastern China

Total gaseous mercury (TGM) was continuously monitored at a remote site (CBS) in Mt. Changbai area, Northeastern China from 24 October 2008 to 31 October 2010. The overall mean TGM concentration was 1.60±0.51 ng m<sup>−3</sup>, which is lower than those reported from remote sites in Eastern, Southwestern, and Western China, indicating a relatively lower regional anthropogenic mercury (Hg) emission intensity in Northeastern China. Measurements at a site in the vicinity (~1.2 km) of CBS station from August 2005 to July 2006 showed a significantly higher mean TGM concentration of 3.58±1.78 ng m<sup>−3</sup>. The divergent result was partially attributed to fluctuations in the relatively frequencies of surface winds during the two study periods and moreover an effect of local emission sources. The temporal variation of TGM at CBS was influenced by regional sources as well as long-range transported Hg. Regional sources frequently contributing to episodical high TGM concentrations were pin-pointed as a large iron mining district in Northern North Korea and two large power plants and urban areas to the southwest of the sampling site. Source areas in Beijing, Tianjin, southern Liaoning, Hebei, northwestern Shanxi, and northwestern Shandong were found to contribute to elevated TGM observations at CBS via long-range transport. Diurnal pattern of TGM at CBS was mainly controlled by regional sources, likely as well as intrusion of air masses from the free troposphere during summer season. There are no consistent seasonal pattern of TGM at CBS, and the monthly TGM variations showed links with the patterns of regional air movements and long-range transport

Multiple phase tabu search for bipartite boolean quadratic programming with partitioned variables

The Bipartite Boolean Quadratic Programming Problem with Partitioned Variables (BBQP-PV) is an NP-hard problem with many practical applications. In this study, we present an effective multiple phase tabu search algorithm for solving BBQP-PV. The algorithm is characterized by a joint use of three key components: two tabu search phases that employ a simple neighborhood and a very large-scale neighborhood to achieve search intensification, and a hybrid perturbation phase that adaptively chooses a greedy perturbation or a recency-based perturbation for search diversification. Experimental assessment on 50 standard benchmarks indicates that the proposed algorithm is able to obtain improved lower bounds for 5 instances and match the previously best solutions for most instances, while achieving this performance within competitive time. Additional analysis confirms the importance of the innovative search components

Fetal Familial Cerebral Cavernous Malformation With a Novel Heterozygous KRIT1 Pathogenic Variant

OBJECTIVES: To identify fetal familial cerebral cavernous malformation (CCMs) and a novel mutation. METHODS: A 37-year-old pregnant woman (G4P0) presented right-handed numbness since two weeks at 31 weeks of gestation. Evaluation with brain magnetic resonance imaging (MRI) revealed multiple CCMs. As a result, fetal MRI, fetal Whole Exome Sequencing (WES), and maternal Sanger sequencing were performed. RESULTS: The mother's brain MRI demonstrated numerous CCMs involving the brain stem, cerebral hemispheres, and cerebellum. Fetal MRI showed a CCM located in the left frontal lobe in SWI. The neuroimaging characteristics of the mother and the fetus suggested that their CCMs may be familial. Genetic analysis revealed a novel mutation in KRIT1 (c.1A>G, p.0?), also called CCM1, in the mother and the baby. The mother delivered a daughter at 32 weeks of gestation with an Apgar score of 10 by cesarean section. DISCUSSION: This mutation of the initial codon in the KRIT1 gene leads to a phenotype with an early-onset. To our knowledge, this is the first-ever reported case of fetal familial CCM and this novel mutation. Brain MRI has excellent sensitivity and specificity, providing the best option for detecting CCMs, even in utero, primarily when SWI is used

Computation offloading and resource allocation for wireless powered mobile edge computing with latency constraint

In this letter, we consider a multi-user wireless powered mobile edge computing (MEC) system, in which a base station (BS) integrated with an MEC server transfers energy to wireless devices (WDs) as an incentive to encourage them to offload computing tasks to the MEC server. We formulate an optimization problem to contemporaneously maximize the data utility and minimize the energy consumption of the operator under the offloaded delay constraint, by jointly controlling wireless-power allocation at the BS as well as offloaded data size and power allocation at the WDs. To solve this problem, the offloaded delay constraint is first transformed into an offloaded data rate constraint. Then an iterative algorithm is designed to obtain the optimal offloaded data size and power allocation at the WDs by using Lagrangian dual method. The results are applied to derive the optimal wireless-power allocation at the BS. Finally, simulation results show that our algorithm outperforms existing schemes in terms of operator’s reward