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This work develops an efficient and accurate optimization algorithm to study the optimal mixing problem driven by boundary control of unsteady Stokes flows, based on the theoretical foundation laid by Hu and Wu in a series of work. The scalar being mixed is purely advected by the flow and the control is a force exerted tangentially on the domain boundary through the Navier slip conditions. The control design has potential applications in many industrial processes such as rotating wall driven mixing, micromixers with acoustic waves, and artificial cilia mixing. The numerical algorithms have high complexity, high accuracy demand, and high computing expense, due to the multiscale nature of the mixing problem and the optimization requirements. A crucial problem is the computation of the G$\^a$teaux derivative of the cost functional. To this end, a hybrid approach based on variational formula and finite difference is built with high accuracy and efficiency to treat various types of control input functions. We have experimented with various optimization schemes including the steepest descent algorithm, the conjugate gradient method and two line search options (backtracking and exact line search). We are able to identify and implement the best combinations. The numerical simulations show that the mixing efficacy is limited when only one single type of control is applied, but can be enhanced when more diverse control types and more time segmentation are utilized. The mix-norm in the optimal mixings decays exponentially. The numerical study in this work demonstrates that boundary control alone could be an effective strategy for mixing in incompressible flows., Comment: 36 pages

A new approach, iteration projection method, is proposed to solve the saddle point problem obtained after the full discretization of the unsteady Navier-Stokes equations. The proposed method iterates projections in each time step with a proper convection form. We prove that the projection iterations converge with a certain parameter regime. Optimal iteration convergence can be achieved with the modulation of parameter values. This new method has several significant improvements over the Uzawa method and the projection method both theoretically and practically. First, when the iterative projections are fully convergent in each time step, the numerical velocity is weakly divergence free (pointwise divergence free in divergence free finite element methods), and the stability and error estimate are rigorously proven. With proper parameters, this method converges much faster than the Uzawa method. Second, numerical simulations show that with rather relaxed stopping criteria which require only a few iterations each time step, the numerical solution preserves stability and accuracy for high Reynolds numbers, where the convectional projection method would fail. Furthermore, this method retains the efficiency of the traditional projection method by decoupling the velocity and pressure fields, which splits the saddle point system into small elliptic problems. Three dimensional simulations with Taylor-Hood P2/P1 finite elements are presented to demonstrate the performance and efficiency of this method. More importantly, this method is a generic approach and thus there are many potential improvements and extensions of the iterative projection method, including utilization of various convection forms, association with stabilization techniques for high Reynolds numbers, applications to other saddle point problems.

Supplemental material, sj-docx-2-asn-10.1177_17590914221146365 for Neuroprotection by Preconditioning in Mice is Dependent on MyD88-Mediated CXCL10 Expression in Endothelial Cells by Zhihong Chen, Weiwei Hu, Mynor J. Mendez, Zachary C. Gossman, Anthony Chomyk, Brendan T. Boylan, Grahame J. Kidd, Timothy W. Phares, Cornelia C. Bergmann and Bruce D. Trapp in ASN Neuro

Supplemental material, sj-docx-1-asn-10.1177_17590914221146365 for Neuroprotection by Preconditioning in Mice is Dependent on MyD88-Mediated CXCL10 Expression in Endothelial Cells by Zhihong Chen, Weiwei Hu, Mynor J. Mendez, Zachary C. Gossman, Anthony Chomyk, Brendan T. Boylan, Grahame J. Kidd, Timothy W. Phares, Cornelia C. Bergmann and Bruce D. Trapp in ASN Neuro

Supplemental material, sj-docx-2-asn-10.1177_17590914221146365 for Neuroprotection by Preconditioning in Mice is Dependent on MyD88-Mediated CXCL10 Expression in Endothelial Cells by Zhihong Chen, Weiwei Hu, Mynor J. Mendez, Zachary C. Gossman, Anthony Chomyk, Brendan T. Boylan, Grahame J. Kidd, Timothy W. Phares, Cornelia C. Bergmann and Bruce D. Trapp in ASN Neuro

Organic carbon aerosol (OC) is a pivotal component of PM2.5 in the atmospheric environment, yet its emission sources and atmospheric behaviors remain poorly constrained in many regions. In this study, a comprehensive method based on the combination of dual‑carbon isotopes (13C and 14C) and macro tracers was employed in the PRDAIO campaign performed in the megacity of Guangzhou, China. The 14C analysis showed that 60 ± 9 % of OC during the sampling campaign was associated with non-fossil sources such as biomass burning activities and biogenic emissions. It should be noted that this non-fossil contribution in OC would significantly decrease when the air masses came from the eastern cities. Overall, we found that non-fossil secondary OC (SOCNF) was the largest contributor (39 ± 10 %) to OC, followed by fossil secondary OC (SOCFF: 26 ± 5 %), fossil primary OC (POCFF: 14 ± 6 %), biomass burning OC (OCbb: 13 ± 6 %) and cooking OC (OCck: 8 ± 5 %). Also, we established the dynamic variation of 13C as a function of aged OC and the volatile organic compounds (VOCs) oxidized OC to explore the impact of aging processes on OC. Our pilot results showed that atmospheric aging was highly sensitive to the emission sources of seed OC particles, with a higher aging degree (86 ± 4 %) when more non-fossil OC particles were transferred from the northern PRD.

The purpose of this study was to compare the effects of sweet potato peels dietary fiber obtained by different extraction methods on intestinal health. Specifically, four different dietary fibers were extracted by hot water, microwave, ultrasonic and subcritical water methods. And the prebiotics effects of sweet potato peels dietary fibers were explored in an in vitro fermentation model, by determining intestinal gas content, short-chain fatty acid content, pH, ammonia content and the gut microbiota composition. The results showed that dietary fiber obtained by four different extraction methods could be utilized by GM and improve human health by increasing the abundance of beneficial bacteria (e.g., Bifidobacterium, Faecalibacterium, and Prevotella) and reducing the abundance of harmful bacteria (e.g., Proteobacteria, Romboutsia and Dorea), enhancing the relative abundance of SCFA-producing bacteria, promoting the production of short-chain fatty acids, reducing intestinal pH from 6.89 to 4.63 and ammonia. Among them, dietary fiber extracted by ultrasound is better than the other three extraction methods. This study suggests that all the four different extraction methods are available for sweet potato peels dietary fiber, and the extracted dietary fiber could be served as potential functional foods with great development value. In addition, it is beneficial to reduce the environmental pollution of sweet potato peels and improve the high-value processing and utilization of sweet potato by-products.

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Additional file 1. Table S1. Pearson correlations between clinical characteristics and right ventricular systolic function. Table S2. Logistic regression of AASI > 0.55 predicting mean E/e′ > 14. Figure S1. ROC curve for AASI to predict mean E/e′ > 14.

Dempster-Shafer evidence theory (DS theory) is widely used in brain magnetic resonance imaging (MRI) segmentation, due to its efficient combination of the evidence from different sources. In this paper, an improved MRI segmentation method, which is based on fuzzy c-means (FCM) and DS theory, is proposed. Firstly, the average fusion method is used to reduce the uncertainty and the conflict information in the pictures. Then, the neighborhood information and the different influences of spatial location of neighborhood pixels are taken into consideration to handle the spatial information. Finally, the segmentation and the sensor data fusion are achieved by using the DS theory. The simulated images and the MRI images illustrate that our proposed method is more effective in image segmentation.

Multiple-choice reading comprehension (MCRC) is the task of selecting the correct answer from multiple options given a question and an article. Existing MCRC models typically either read each option independently or compute a fixed-length representation for each option before comparing them. However, humans typically compare the options at multiple-granularity level before reading the article in detail to make reasoning more efficient. Mimicking humans, we propose an option comparison network (OCN) for MCRC which compares options at word-level to better identify their correlations to help reasoning. Specially, each option is encoded into a vector sequence using a skimmer to retain fine-grained information as much as possible. An attention mechanism is leveraged to compare these sequences vector-by-vector to identify more subtle correlations between options, which is potentially valuable for reasoning. Experimental results on the human English exam MCRC dataset RACE show that our model outperforms existing methods significantly. Moreover, it is also the first model that surpasses Amazon Mechanical Turker performance on the whole dataset., Comment: 6 pages, 2 tables

In some cases, determining precisely the exact value of the weight is difficult and their values are considered as interval numbers. Therefore, in this paper, we extend the TOPSIS method for solving multiple attribute decision- making problems with interval weight. Firstly, the evaluation on each alternative and the weight of attribute are given as interval numbers. Then, based on the proposed interval t-norm, the original interval decision matrix and interval weight are merged into interval weighted decision matrix. Next, the ranking result of the alternatives is obtained by TOPSIS method. Finally, an example is given to highlight the procedure of the proposed method.

Plated through hole (PTH) plays a critical role in printed circuit board (PCB) reliability. Thermal fatigue deformation of the PTH material is regarded as the primary factor affecting the lifetime of electrical devices. Numerous research efforts have focused on the failure mechanism model of PTH. However, most of the existing models were based on the one-dimensional structure hypothesis without taking the multilayered structure and external pad into consideration. In this paper, the constitutive relation of multilayered PTH is developed to establish the stress equation, and finite element analysis (FEA) is performed to locate the maximum stress and simulate the influence of the material properties. Finally, thermal cycle tests are conducted to verify the accuracy of the life prediction results. This model could be used in fatigue failure portable diagnosis and for life prediction of multilayered PCB.

Recent researches have shown that machine learning based malware detection algorithms are very vulnerable under the attacks of adversarial examples. These works mainly focused on the detection algorithms which use features with fixed dimension, while some researchers have begun to use recurrent neural networks (RNN) to detect malware based on sequential API features. This paper proposes a novel algorithm to generate sequential adversarial examples, which are used to attack a RNN based malware detection system. It is usually hard for malicious attackers to know the exact structures and weights of the victim RNN. A substitute RNN is trained to approximate the victim RNN. Then we propose a generative RNN to output sequential adversarial examples from the original sequential malware inputs. Experimental results showed that RNN based malware detection algorithms fail to detect most of the generated malicious adversarial examples, which means the proposed model is able to effectively bypass the detection algorithms.

A coupled-wave model is developed for photonic-crystal quantum cascade lasers. The analytical model provides an efficient analysis of full three-dimensional large-area device structure, and the validity is confirmed via simulations and previous experimental results., Comment: 21 pages and 8 figures

We discuss the problem of optimal impulse control representing the preventive maintenance of a simple reparable system. The system model is governed by coupled transport and integro-differential equations in a nonreflexive Banach space. The objective of this paper is to construct nonnegative impulse control inputs at given system running times that minimize the probability of the system in failure mode. To guarantee the nonnegativity of the controlled system, we consider the control inputs to depend on the system state. This essentially leads to a bilinear control problem. We first present a rigorous proof of existence of an optimal controller and then apply the variational inequality to derive the first-order necessary conditions of optimality.

Wheat is one of the most important food crops in China and its production is crucial to ensure national food security.In the north of China,wheat plants often suffer from heat and high irradiation stress during grain-filling stage,leading to damage in photosynthetic apparatus and reduction of yield.Especially,the reaction center in photosystem Ⅱ(PS Ⅱ) is prone to various environmental stresses,and the extent of damage depends on the balance between injury and repair.The repair of PSⅡ needs fast turnover of D1 protein,which is the key component of PSⅡ.During the repair of PSⅡ,damaged D1 protein must be degraded and subsequently replaced by new copies quickly.It is well known that Deg1 protease plays an important role in cleavage of damaged D1 protein.However,the dynamic change in Deg1 protease under heat and high light stress is still largely unclear.In this study,we used wheat cultivar "Aikang 58" to determine the effects of heat and high light stress on Deg1 protease and D1 protein levels and PSⅡ performance and further the regulation role of salicylic acid(SA) in the repair of PSⅡ.Wheat leaves of grain-filling stage were pretreated with 0.3 mmol/L SA and distilled water(as control) respectively and then subjected to three temperature and irradiation treatments: moderate temperature and irradiation(25℃,600 μmol m-2 s-1,MTI) for 2h,high temperature and irradiation(38℃,1600 μ mol m-2 s-1,HTI) for 2h,and HTI following by 3h MTI.Fluorescence parameters were measured using a chlorophyll fluorometer.The levels of Deg1 protease and D1 protein were analyzed by western-blotting analysis.The results showed that HTI treatment resulted in degradation of Deg1 protease and D1 protein and reversible damage to PSⅡ function.Compared with control,pretreatment with SA not only retarded degradation of Deg1 protease and D1 protein,maintained higher potential photochemical efficiency(Fv/Fm),actual photochemical efficiency(ΦPSⅡ),electron transfer rate(ETR) of PSⅡ and net photosynthetic rate(Pn) of wheat leaves under HTI,but also accelerated the recovery under non stress condition.It suggests that SA could protect photosynthetic apparatus of wheat against combined stress of heat and high irradiation to some extent via maintaining the turnover of D1 protein.

We present results of the first intercomparison of real-time instruments for gas/particle partitioning of organic species. Four recently-developed instruments that directly measure gas/particle partitioning in near-real time were deployed in Centreville, Alabama during the Southern Oxidant Aerosol Study (SOAS) in 2013. Two instruments were filter inlet for gases and aerosols high-resolution chemical ionization mass spectrometers (FIGAERO-HRToF-CIMS) with acetate (A-CIMS) and iodide (I-CIMS) ionization sources, respectively; the third was a semi-volatile thermal desorption aerosol GC-MS (SV-TAG); and the fourth was a high-resolution thermal desorption proton-transfer reaction mass spectrometer (HR-TD-PTRMS). Signals from these instruments corresponding to several organic acids were chosen for comparison. The campaign average partitioning fractions show good correlation. A similar level of agreement with partitioning theory is observed. Thus the intercomparison exercise shows promise for these new measurements, as well as some confidence on the measurement of low versus high particle-phase fractions. However, detailed comparison show several systematic differences that lie beyond estimated measurement errors. These differences may be due to at least eight different effects: (1) underestimation of uncertainties under low signal-to-noise; (2) inlet and/or instrument adsorption/desorption of gases; (3) differences in particle size ranges sampled; (4) differences in the methods used to quantify instrument backgrounds; (5) errors in high-resolution fitting of overlapping ion groups; (6) differences in the species included in each measurement due to different instrument sensitivities; and differences in (7) negative or (8) positive thermal decomposition (or ion fragmentation) artifacts. The available data are insufficient to conclusively identify the reasons, but evidence from these instruments and available data from an ion mobility spectrometer shows the particular importance of effects 6–8 in several cases. This comparison highlights the difficulty of this measurement and its interpretation in a complex ambient environment, and the need for further improvements in measurement methodologies, including isomer separation, and detailed study of the possible factors leading to the observed differences. Further intercomparisons under controlled laboratory and field conditions are strongly recommended. Copyright © 2017 American Association for Aerosol Research

The fermentation process plays an important role in black tea's quality control and determination. This article presented a portable artificial olfaction system for real-time monitoring of black tea. Herein, a colorimetric sensor array, which was fabricated by printing 12 chemical dyes, including 9 porphyrins/metalloporphyrins and 3 pH indicators on a C2 reverse silica-get flat plate, was utilized to develop the artificial olfaction system for data acquisition. With specific colorific fingerprint of volatile compounds from black tea, fermentation time can be achieved with efficient chemometrics. Additionally, a novel classification algorithm, which combined K-Nearest Neighbor and adaptive boosting, namely KNN-AdaBoost, was proposed with a comparison of two classical classification algorithms (e.g., KNN and BP-ANN). Results demonstrated that the optimum KNN-AdaBoost model was superior to others with discrimination rate of 100% in both the training and prediction set. The overall results sufficiently reveal that the colorimetric sensor has promising applications in real-time fermentation monitoring. Practical applications The fermentation process plays an important role in black tea's quality control and determination. However, traditional analytical chemical methods (i.e., mass spectrometry, liquid chromatography gas, and gas chromatography-mass spectrometry) can monitor the fermentation process and have some drawbacks, such as complicated operation, high costs of implementation, and lengthy analysis time. This research notably proposed a portable artificial olfaction system for real-time monitoring black tea; and examined the feasibility, accuracy and effectiveness of this sensor. The overall results obtained from this study sufficiently reveals that the colorimetric sensor has promising applications in real-time fermentation monitoring.

A strain of transmissible gastroenteritis virus (TGEV), SHXB, was isolated in Shanghai, China. The complete genome of strain SHXB was sequenced, and its sequence was compared those of other TGEV strains in the GenBank database. The comparison showed that there were no insertions or deletions in the 5′ and 3′- non-translated regions, in the nonstructural genes ORF1, ORF3, and ORF7, or in the genes encoding the structural proteins envelope (E), membrane (M) and nucleoprotein (N). A phenomenon in common with other strains was that nucleotide (nt) 655 of the spike (S) gene was G, and a common change in nt 1753 of the S gene was a T-to-G mutation that caused a serine-to-alanine mutation at amino acid 585, which is in the region of the main major antigenic sites A and B of the TGEV S protein. A 6-nt deletion was also found at nt 1123-1128 in all Purdue strains except the strain Virulent Purdue. Phylogenetic analysis showed that TGEV SHXB was closely related to the Purdue strains and shared a common ancestor with the Miller strains as well as strain PRCV-ISU-1. Electronic supplementary material The online version of this article (doi:10.1007/s00705-014-2080-9) contains supplementary material, which is available to authorized users.

In this thesis we present theoretical and numerical results for a feedback control problem defined by a thermal fluid. The problem is motivated by recent interest in designing and controlling energy efficient building systems. In particular, we show that it is possible to locally exponentially stabilize the nonlinear Boussinesq Equations by applying Neumann/Robin type boundary control on a bounded and connected domain. The feedback controller is obtained by solving a Linear Quadratic Regulator problem for the linearized Boussinesq equations. Applying classical results for semilinear equations where the linear term generates an analytic semigroup, we establish that this Riccati-based optimal boundary feedback control provides a local stabilizing controller for the full nonlinear Boussinesq equations. In addition, we present a finite element Galerkin approximation. Finally, we provide numerical results based on standard Taylor-Hood elements to illustrate the theory. Ph. D.

With more and more importance attached on the reliability of electronic products, in order to solve the problems occurred during the fault diagnosis and reasoning of electronic products, this paper takes the simulation-based circuit signal as the project, and in-depth studies information fusion methods for failure mode identification. Then this paper establishes the information fusion model of the fault circuit, and raises the basic probability distribution function for the neural network and enriched the applications of the DS evidence theory. In the end the failure mode identification of the circuit was achieved, which provided support for a higher level to fault reasoning.

In respect of the lack of suitable method of mission reliability prediction for complex product, this paper puts forward a method of mission reliability prediction for circuit based on function simulation and fault reasoning. It builds the topology reasoning model and function simulation model of circuit with the aid of existing mature EDA (Electronic Design Automation) simulation tool, simulates and analyzes hard fault and soft fault of the components composed of circuit separately, and achieves the response of components failure on circuit. Then the idea of Monte Carlo simulation is used to carry on statistical analysis of fault data and calculate the circuit mission reliability. This paper presents the basic idea of this method, expatiates the principle and techniques of circuit functional fault simulation and circuit fault reasoning. Finally, this paper analyzed a representative case using the method mentioned in the paper. It does not need to build product’s reliability model using this method. Automatic reliability prediction could be realized in the same time with circuit design, which provides huge advantage to circuit designer. This paper makes exploratory researches on the method of integrated prediction of performance and reliability, and it is a strong complement to the existing reliability prediction method.

This paper presents a fast intra/inter frame coding algorithm. In H.264/AVC prediction, the rate distortion optimization technique with full mode search is used to select the best mode for each macroblock. To reduce the computational load in mode decision, for intra frames discrete wavelet method used to filter low-pass data; for inter frames the intra mode is skipped according to the motion vector distribution feature. Experimental results revealed that the computation time of the proposed fast algorithm is averagely reduced to 52% of the full search method with slight PSNR degradation.

A new type of RF phase shifter controlled by optical carrier wavelength is experimentally demonstrated. A simple optical waveguide on a 62 mm long LiNbO/sub 3/ substrate showed linear phase shift characteristics of over 15,000 degrees by changing the wavelength from 1540 nm to 1570 nm. This wide range implies applicability to wavelength division multiplexed (WDM) systems, where a simple waveguide behaves as multiple variable phase shifters. By integrating an array of this phase shifter and a slab waveguide, a simple BFN for independently steerable multibeam antenna can be realized.