Simulation of Transients in Natural Gas Networks via A Semi-analytical Solution Approach

Simulation and control of the transient flow in natural gas networks involve solving partial differential equations (PDEs). This paper proposes a semi-analytical solutions (SAS) approach for fast and accurate simulation of the natural gas transients. The region of interest is divided into a grid, and an SAS is derived for each grid cell in the form of the multivariate polynomials, of which the coefficients are identified according to the initial value and boundary value conditions. The solutions are solved in a ``time-stepping'' manner; that is, within one time step, the coefficients of the SAS are identified and the initial value of the next time step is evaluated. This approach achieves a much larger grid cell than the widely used finite difference method, and thus enhances the computational efficiency significantly. To further reduce the computation burden, the nonlinear terms in the model are simplified, which induces another SAS scheme that can greatly reduce the time consumption and have minor impact on accuracy. The simulation results on a single pipeline case and a 6-node network case validate the advantages of the proposed SAS approach in accuracy and computational efficiency

A dynamic Bayesian network approach to protein secondary structure prediction

<p>Abstract</p> <p>Background</p> <p>Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful information relevant to sequence-structure relationship. However, at present, the prediction accuracy of pure HMM-type methods is much lower than that of machine learning-based methods such as neural networks (NN) or support vector machines (SVM).</p> <p>Results</p> <p>In this paper, we report a new method of probabilistic nature for protein secondary structure prediction, based on dynamic Bayesian networks (DBN). The new method models the PSI-BLAST profile of a protein sequence using a multivariate Gaussian distribution, and simultaneously takes into account the dependency between the profile and secondary structure and the dependency between profiles of neighboring residues. In addition, a segment length distribution is introduced for each secondary structure state. Tests show that the DBN method has made a significant improvement in the accuracy compared to other pure HMM-type methods. Further improvement is achieved by combining the DBN with an NN, a method called DBNN, which shows better <it>Q</it>₃accuracy than many popular methods and is competitive to the current state-of-the-arts. The most interesting feature of DBN/DBNN is that a significant improvement in the prediction accuracy is achieved when combined with other methods by a simple consensus.</p> <p>Conclusion</p> <p>The DBN method using a Gaussian distribution for the PSI-BLAST profile and a high-ordered dependency between profiles of neighboring residues produces significantly better prediction accuracy than other HMM-type probabilistic methods. Owing to their different nature, the DBN and NN combine to form a more accurate method DBNN. Future improvement may be achieved by combining DBNN with a method of SVM type.</p

Integrating protein structural dynamics and evolutionary analysis with Bio3D

Abstract Background Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution. Results Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. Conclusions The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .http://deepblue.lib.umich.edu/bitstream/2027.42/109747/1/12859_2014_Article_399.pd

Analysis of nonlinear suspension power harvest potential

Because the power consumption of a controlled suspension is huge, the power harvest potential of a nonlinear controlled suspension is analyzed. Instead of simplifying the suspension to a linear model or adopting some control strategies to solve the problem, this paper investigates the effect of the nonlinear characteristics on the power harvesting potential. A mathematic model is introduced to calculate the nonlinear vibration, and the amount of harvested power was obtained using the multi-scale method. A numerical validation is carried out at the end of this study. The results show that the investigated mechanical parameters affect both the vibration amplitude and the induced current, while the electric parameters only affect the induced current. The power harvesting potential of the nonlinear suspension is generally greater than the linear suspension because the frequency band of the actual pavement also contains bandwidth surrounding the body resonance point. The only exception occurs if the vehicle travels on a road with a particular profile, e.g. a sine curve. To optimize harvested power, it is better to consider the nonlinear characteristics rather than simplifying the suspension to a linear model

Electrically tunable Gilbert damping in van der Waals heterostructures of two-dimensional ferromagnetic metals and ferroelectrics

Tuning the Gilbert damping of ferromagnetic (FM) metals via a nonvolatile way is of importance to exploit and design next-generation novel spintronic devices. Through systematical first-principles calculations, we study the magnetic properties of the van der Waals heterostructure of two-dimensional FM metal CrTe2 and ferroelectric (FE) In2Te3 monolayers. The ferromagnetism of CrTe2 is maintained in CrTe2/In2Te3 and its magnetic easy axis can be switched from in-plane to out-of-plane by reversing the FE polarization of In2Te3. Excitingly, we find that the Gilbert damping of CrTe2 is tunable when the FE polarization of In2Te3 is reversed from upward to downward. By analyzing the k-dependent contributions to the Gilbert damping, we unravel that such tunability results from the changed intersections between the bands of CrTe2 and Fermi level on the reversal of the FE polarizations of In2Te3 in CrTe2/In2Te3. Our work provides an appealing way to electrically tailor Gilbert dampings of two-dimensional FM metals by contacting them with ferroelectrics.Comment: 4 Figures, accepted by Applied Physics Letter

The Prognostic and Therapeutic Value of PD-L1 in Glioma

Glioma is the most common type of primary brain tumors. After standard treatment regimen (surgical section, radiotherapy and chemotherapy), the average survival time remains merely around 14 months for glioblastoma (grade IV glioma). Recent immune therapy targeting to the immune inhibitory checkpoint axis, i.e., programmed cell death protein 1 (PD-1) and its ligand PD-L1 (i.e., CD274 or B7-H1), has achieved breakthrough in many cancers but still not in glioma. PD-L1 is considered a major prognostic biomarker for immune therapy in many cancers, with anti-PD-1 or anti-PD-L1 antibodies being used. However, the expression and subcellular distribution of PD-L1 in glioma cells exhibits great variance in different studies, severely impairing PD-L1's value as therapeutic and prognostic biomarker in glioma. The role of PD-L1 in modulating immune therapy is complicated. In addition, endogenous PD-L1 plays tumorigenic roles in glioma development. In this review, we summarize PD-L1 mRNA expression and protein levels detected by using different methods and antibodies in human glioma tissues in all literatures, and we evaluate the prognostic value of PD-L1 in glioma. We also summarize the relationships between PD-L1 and immune cell infiltration in glioma. The mechanisms regulating PD-L1 expression and the oncogenic roles of endogenous PD-L1 are discussed. Further, the therapeutic results of using anti-PD-1/PD-L1 antibodies or PD-L1 knockdown are summarized and evaluated. In summary, current results support that PD-L1 is not only a prognostic biomarker of immune therapy, but also a potential therapeutic target for glioma

MOL#107706 Title Page Advances in Hypoxia-mediated Mechanisms in Hepatocellular Carcinoma

The number of words in the Abstract: 150 The number of words in the Introduction: 411 The number of words in the mainbody: 4537 The number of words in the Conclusion: 72 ABBREVIATIONS: 2-ME2, 2-Methoxyestradiol; CA-IX, carbonic anhydrase IX; caspase-1, cysteinyl aspartate specific proteinase-1; COX2, cyclooxygenase 2; CT, computerised tomography; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; DEN, diethylnitrosamine; DFS, disease-free survival; EMT, epithelial-mesenchymal transition; ERK, MOL#107706 3 extracellular signal-regulated kinase; H2AX, H2A histone family, member X; GLUT1, glucose transporter 1; HBV, hepatitis B virus; HCC, hepatocelluar carcinoma; HIF-1/2, hypoxia inducible factor-1/2; HMGB1, high-mobility group protein 1; LSD1, lysine-specific demethylase-1; miR/miRNA, MicroRNA; MMPs, matrix metalloproteinases; mtDNA, mitochondrial DNA; NGB, neuroglobin; OS, overall survival; NET1, neuroepithelial cell transforming 1; p70S6K, p70-S6 Kinase 1; PFS, progression-free survival; PK, pyruvate kinase; pVHL, protein of von hippel lindau; Raf, RAF proto-oncogene serine/threonine-protein kinase; RFS, recurrence-free survival; ROS, oxygen reactive species; SDF1 -derived factor-1; TACE, transcatheter arterial chemoembolization; TGF, tumor growth factor; TLR, toll-like receptor; TNM, tumor, node, metastasis

Active control of a nonlinear suspension with output constraints and variable-adaptive-law control

A variable-adaptive-law control algorithm for application to common problems like multi-objective control, actuator output constraints, and suboptimal adaptive laws is proposed in this paper. The multi-objective control problem of a nonlinear suspension is converted to the constrained stability problem of a sprung mass using a quarter nonlinear-suspension model. A variable-adaptive-law controller is then used, along with feedback from the output error, and considering the constraints of the actuator output. The controller modifies the adaptive law to reduce the active control force and restores it to the unsaturated zone. This ensures that the suspension system is always in a controlled state when the output saturation occurs. The controller was simulated for the following two cases: (i) a bump road and (ii) a C-grade road. The analysis is verified by experiments in the end

Adaptive control of a nonlinear suspension with time-delay compensation

This paper addresses the challenge of predictive control of a quarter-car nonlinear suspension and low controller-precision. This is done by designing and implementing an adaptive controller with time-delay compensation. First, a real-time control model is created. Then, time-delay compensation is realized and both frequency-domain and time-domain simulation of the controller performance are conducted. According to the simulation results, the sprung-mass acceleration of the suspension controlled by an adaptive controller with time-delay compensation is superior to that without time-delay compensation. Both the period to settle down and the peak of vibration acceleration are smaller. This means the proposed controller is capable of dealing with problems including variable time delay, nonlinear vibration and predictive control

Optimization of DNA delivery by three classes of hybrid nanoparticle/DNA complexes

Plasmid DNA encoding a luciferase reporter gene was complexed with each of six different hybrid nanoparticles (NPs) synthesized from mixtures of poly (D, L-lactide-co-glycolide acid) (PLGA 50:50) and the cationic lipids DOTAP (1, 2-Dioleoyl-3-Trimethyammonium-Propane) or DC-Chol {3β-[N-(N', N'-Dimethylaminoethane)-carbamyl] Cholesterol}. Particles were 100-400 nm in diameter and the resulting complexes had DNA adsorbed on the surface (out), encapsulated (in), or DNA adsorbed and encapsulated (both). A luciferase reporter assay was used to quantify DNA expression in 293 cells for the uptake of six different NP/DNA complexes. Optimal DNA delivery occurred for 105 cells over a range of 500 ng - 10 μg of NPs containing 20-30 μg DNA per 1 mg of NPs. Uptake of DNA from NP/DNA complexes was found to be 500-600 times as efficient as unbound DNA. Regression analysis was performed and lines were drawn for DNA uptake over a four week interval. NP/DNA complexes with adsorbed NPs (out) showed a large initial uptake followed by a steep slope of DNA decline and large angle of declination; lines from uptake of adsorbed and encapsulated NPs (both) also exhibited a large initial uptake but was followed by a gradual slope of DNA decline and small angle of declination, indicating longer times of luciferase expression in 293 cells. NPs with encapsulated DNA only (in), gave an intermediate activity. The latter two effects were best seen with DOTAP-NPs while the former was best seen with DC-Chol-NPs. These results provide optimal conditions for using different hybrid NP/DNA complexes in vitro and in the future, will be tested in vivo