Dirichlet Priors for MAP Inference of Protein Conformation Abundances from SAXS

Estimation of mixture coefficients of protein conformations in solution find applications in understanding protein behavior. We describe a method for maximum a posteriori (MAP) estimation of the mixture coefficients of ensemble of conformations in a protein mixture solution using measured small angle X-ray scattering (SAXS) intensities. The proposed method builds upon a model for the measurements of crystallographically determined conformations. Assuming that a priori information on the protein mixture is available, and that priori information follows a Dirichlet distribution, we develop a method to estimate the relative abundances with MAP estimator. The Dirichlet distribution depends on concentration parameters which may not be known in practice and thus need to be estimated. To estimate these unknown concentration parameters we developed an expectation-maximization (EM) method. Adenylate kinase (ADK) protein was selected as the test bed due to its known conformations Beckstein et al. (Journal of Molecular Biology, 394(1), 160 1). Known conformations are assumed to form the full vector bases that span the measurement space. In Monte Carlo simulations, mixture coefficient estimation performances of MAP and maximum likelihood (ML) (which assumes a uniform prior on the mixture coefficients) estimators are compared. MAP estimators using known and unknown concentration parameters are also compared in terms of estimation performances. The results show that prior knowledge improves estimation accuracy, but performance is sensitive to perturbations in the Dirichlet distribution’s concentration parameters. Moreover, the estimation method based on EM algorithm shows comparable results to approximately known prior parameters.     

Characterizing interwell connectivity in waterflooded reservoirs using data-driven and reduced-physics models: a comparative study

Waterflooding is a significantly important process in the life of an oil field to sweep previously unrecovered oil between injection and production wells and maintain reservoir pressure at levels above the bubble-point pressure to prevent gas evolution from the oil phase. This is a critical reservoir management practice for optimum recovery from oil reservoirs. Optimizing water injection volumes and optimizing well locations are both critical reservoir engineering problems to address since water injection capacities may be limited depending on the geographic location and facility limits. Characterization of the reservoir connectivity between injection and production wells can greatly contribute to the optimization process. In this study, it is proposed to use computationally efficient methods to have a better understanding of reservoir flow dynamics in a waterflooding operation by characterizing the reservoir connectivity between injection and production wells. First, as an important class of artificial intelligence methods, artificial neural networks are used as a fully data-driven modeling approach. As an additional powerful method that draws analogy between source/sink terms in oil reservoirs and electrical conductors, capacitance–resistance models are also used as a reduced-physics-driven modeling approach. After understanding each method’s applicability to characterize the interwell connectivity, a comparative study is carried out to determine strengths and weaknesses of each approach in terms of accuracy, data requirements, expertise requirements, training algorithm and processing times.

     

Preparation and thermal properties of Alkoxy Silane functionalized polyether sulfone/well‐defined poly(trimethoxysilyl) propyl methacrylate‐based hybrid materials

In this study, novel polyethersulfone (PES) and poly(trimethoxysilyl) propyl methacrylate (PMPS) containing hybrid materials were prepared. PES was functionalized with trimethoxysilane groups by UV‐induced grafting reaction. PMPS was synthesized by atom transfer radical polymerization. In the followed process, the functionalized PES mixed with different amount of PMPS, thermally treated to promote sol–gel crosslinking process to prepare the PES‐based hybrid materials. The trimethoxysilane grafted PES chains are covalently bonded with the well‐defined trimethoxysilane groups of PMPS. The chemical structure of the prepared PES and PMPS is confirmed by Fourier transform infrared analysis. The morphology of the hybrids was investigated by scanning electron microscopy. The results of thermogravimetric analysis show that the thermal stability of the hybrid materials was significantly affected with the addition of PMPS. POLYM. ENG. SCI., 58:1346–1352, 2018. © 2017 Society of Plastics Engineers     

A novel UV‐cured interpenetrating organic–inorganic hybrid polymer network based phase change materials (IPN‐PCM)

The purpose of this paper is to introduce a novel UV‐cured interpenetrating polymer networked phase change materials (IPN‐PCMs), on which no article has been found in the so far published research. Maleated castor oil (MCO) was synthesized via maleinization reaction of castor oil with maleic anhydride. Organic–inorganic hybrid interpenetrating polymer networked (IPN) materials containing both cationic and radical sections and IPN‐PCMs containing tetradecanol, hexadecanol, and octadecanol were prepared. The chemical structure of MCO and organic–inorganic hybrid IPN‐PCMs were determined by using Fourier Transform Infrared Spectroscopy (FT‐IR). Differential scanning calorimetry (DSC) was used for examining the phase‐change behaviors of the materials. Thermal stability was investigated by thermogravimetric analysis (TGA). Moreover, the surface formation of the specimen was investigated by scanning electron microscopy (SEM). In conclusion, our study proved that because of their high latent heat storage scope and high thermal stability, the obtained organic–inorganic hybrid IPN‐PCMs could be used as thermal energy storage materials. POLYM. ENG. SCI., 58:870–875, 2018. © 2017 Society of Plastics Engineers     

Speed Sensorless Direct Torque Control of Induction Motor Drives

Abstract

In this paper, a sliding mode speed observer for direct torque controlled (DTC) induction motor drives is developed. The speed observer accuracy is guaranteed through the current observer. The rotor speed is estimated by the observer based on the measured and estimated stator currents. The system is firstly simulated by MATLAB and then tested by hardware in the loop. Then, the application is implemented on a TMS320C6711, 32-bit fixed point digital signal processor (DSP). The experimental results show the robustness, feasibility, and performance of the proposed observer structure.     

Superporous cryogel/conductive composite systems for potential sensor applications

In situ synthesis of conductive polymers, poly(Aniline) (p(An)), poly(Pyrrole) (p(Py)), and poly(Thiophene) (p(Th)) within network of superporous cryogels with tunable functionalities as neutral poly(acrylamide) (p(AAm), anionic poly(acrylic acid) (p(AAc)), and cationic poly(4-vinylpyridine) (p(4-VP)) were carried out via oxidation polymerization technique. The highest conductivity values were measured for p(AAm)/p(An) semi-IPN cryogel with 1.4 × 10^?2 S.cm^?1 and for p(AAc)/p(Py) cryogel with 3.2 × 10^?4 S.cm^?1. In addition, to increase the amounts of conductive polymers within cryogel networks, reloading/polymerization cycle was carried out thrice, and found that there is no significant increase in the amounts of conductive polymers and the measured conductivity values. The prepared p(AAm), p(AAc), and p(4-VP) cryogels and their corresponding p(An), p(Py), and p(Th) composites were tested potential sensor materials against HCl and NH₃ vapor. The changes on conductivities for bare p(4-VP) cryogel were observed as 70 and 52-fold increase upon HCl and NH₃ gas treatment, respectively. The p(4-VP)/p(An) p(An) composites showed 7-fold conductivity decrease upon the treatments of HCl and NH₃ vapors. The p(AAm)/p(Py) composite responded 2-fold increase upon HCl vapor exposure and 50-fold decrease upon NH₃ vapor exposure. Furthermore, p(AAm)/p(Th) cryogel composite responded 7-fold decrease and 300-fold increase in their conductivities upon HCl and NH₃ vapor exposure, respectively.

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Comparison of total‐etch,self‐etch,and selective etching techniques on class V composite restorations prepared by Er:YAG laser and bur: a scanning electron microscopy study

The purpose of this study was to compare total‐etch, self‐etch, and selective etching techniques on the marginal microleakage of Class V composite restorations prepared by Er:YAG laser and bur. Class V cavities prepared on both buccal and lingual surfaces of 30 premolars by Er:YAG laser or bur and divided into six groups. The occlusal margins were in enamel, and the cervical margins were in cementum. Group‐1: bur preparation(bp)+Adper Single Bond 2 (ASB)+Filtek Z550 (FZ); Group‐2: laser preparation(lp)+(ASB)+(FZ); Group‐3: bp + Clearfil S3 Bond Plus (CSBP)+(FZ); Group‐4: lp+(CSBP) (FZ); Group‐5: bp + acid etching+(CSBP)+(FZ); Group‐6: lp + acid etching+(CSBP)+(FZ). All teeth were stored in distilled water at 37°C for 24 hr, and then thermocycled 1000 times (5–55°C). Five teeth from each group were chosen for the microleakage investigation, and two teeth for the scanning electron microscope evaluation. Teeth which were prepared for the microleakage test were immersed in .5% methylene blue dye for 24 hr. After immersion, the teeth were sectioned and observed under a stereomicroscope for dye penetration. Data were analyzed using Kruskal–Wallis and Mann–Whitney U tests (p < .05). More microleakage was observed in the cervical regions compared to the occlusal regions in Groups 3, 5, and 6, respectively (p < .05). There is no statistically significant difference in Groups 1, 2, and 4, in terms of cervical regions versus occlusal regions (p > .05). No significant differences were observed among any groups in terms of occlusal and cervical surfaces, separately (p > .05). Different etching techniques did not influence microleakage of Class V restorations prepared by Er:YAG laser and bur.     

Modeling,analysis, and screening of cyclic pressure pulsing with nitrogen in hydraulically fractured wells

Cyclic pressure pulsing with nitrogen is studied for hydraulically fractured wells in depleted reservoirs. A compositional simulation model is constructed to represent the hydraulic fractures through local-grid refinement. The process is analyzed from both operational and reservoir/ hydraulic-fracture perspectives. Key sensitivity parameters for the operational component are chosen as the injection rate, lengths of injection and soaking periods and the economic rate limit to shut-in the well. For the reservoir/ hydraulic fracturing components, reservoir permeability, hydraulic fracture permeability, effective thickness and half-length are used. These parameters are varied at five levels. A full-factorial experimental design is utilized to run 1250 cases. The study shows that within the ranges studied, the gas-injection process is applied successfully for a 20-year project period with net present values based on the incremental recoveries greater than zero. It is observed that the cycle rate limit, injection and soaking periods must be optimized to maximize the efficiency. The simulation results are used to develop a neural network based proxy model that can be used as a screening tool for the process. The proxy model is validated with blind-cases with a correlation coefficient of 0.96.     

An algorithm for constructing various kinds of nanojunctions using zig-zag and armchair nanotubes

A method for generating various forms of junctions involving armchair and zig-zag nanotubes, firstly introduced by Zsoldos et al., is developed to cover all types of armchair and zig-zag nanotubes in a systematical way. This method can also be used to produce nanogears and toothed canals. The method is explained and flowcharts are included to aid in programming into a code.