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Open Access Publications from the University of California
Cover page of Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements

Machine learning applied to retrieval of temperature and concentration distributions from infrared emission measurements

(2019)

© 2019 Elsevier Ltd Inversion of temperature and species concentration distributions from radiometric measurements involves solving nonlinear, ill-posed and high-dimensional problems. Machine Learning approaches allow solving such highly nonlinear problems, offering an alternative way to deal with complex and dynamic systems with good flexibility. In this study, we present a machine learning approach for retrieving temperatures and species concentrations from spectral infrared emission measurements in combustion systems. The training spectra for the machine learning model were synthesized through calculations from HITEMP 2010 for gas mixtures of CO2, H2O, and CO. The method was tested for different line-of-sight temperature and concentration distributions, different gas path lengths and different spectral intervals. Experimental validation was carried out by measuring spectral emission from a Hencken flat flame burner with a Fourier-transform infrared spectrometer with different spectral resolutions. The temperature fields above the burner for combustion with equivalence ratios of ϕ = 1, ϕ = 0.8, and ϕ = 1.4 were retrieved and were in excellent agreement with temperatures deduced from Rayleigh scattering thermometry.

Cover page of Structural changes and void generation in low-density amorphous silicon:
  a computational study

Structural changes and void generation in low-density amorphous silicon: a computational study

(2019)

We study the micro-structure of computationally generated amorphous silicon ($a$-Si) and hydrogenated amorphous silicon ($a$-Si:H) as a function of density. We use the WWW Monte Carlo method with the Keating potential, using different fixed densities in the generation process. We find a smooth evolution in bond lengths, bond angles, and bond angle deviations $\Delta \theta$ as the density is changed around the equilibrium value of $4.9\times10^{22}\ $atoms/cm$^3$ to higher and lower values. A significant change occurs at densities below $4.3\times10^{22}\ $atoms/cm$^3$ with an onset of void formation, which is associated with a drop in negative pressure, akin to a cavitation process in liquids. We find both small voids (radius $\sim$ 3 Angstroms) and larger ones (up to 7 Angstroms), as in previous computational studies, which compare well with available experimental data. The voids have an influence on atomic structure up to 4 Angstroms beyond the void surface, and are associated with decreasing structural order, measured by $\Delta\theta$. We also observe an increasing medium-range dihedral order with increasing density. The method used to generate structures with voids does not rely on expensive density functional theory molecular dynamics, and allow voids to form naturally by a physical process, without needing any scheme for adding or removing atoms or an a priori idea of void structure. This work provides a set of void structures for further studies of properties such as the Staebler-Wronski effect.

Cover page of Solid Lubrication with MoS$_2$: A Review

Solid Lubrication with MoS$_2$: A Review

(2019)

Molybdenum disulfide (MoS$_2$) is one of the most broadly utilized solid lubricants with a wide range of applications, including but not limited to those in the aerospace/space industry. Here we present a focused review of solid lubrication with MoS$_2$ by highlighting its structure, synthesis, applications and the fundamental mechanisms underlying its lubricative properties, together with a discussion of their environmental and temperature dependence. An effort is made to cover the main theoretical and experimental studies that constitute milestones in our scientific understanding. The review also includes an extensive overview of the structure and tribological properties of doped MoS$_2$, followed by a discussion of potential future research directions.

Cover page of Genome-wide RNA pol II initiation and pausing in neural progenitors of the rat.

Genome-wide RNA pol II initiation and pausing in neural progenitors of the rat.

(2019)

Global RNA sequencing technologies have revealed widespread RNA polymerase II (Pol II) transcription outside of gene promoters. Small 5'-capped RNA sequencing (Start-seq) originally developed for the detection of promoter-proximal Pol II pausing has helped improve annotation of Transcription Start Sites (TSSs) of genes as well as identification of non-genic regulatory elements. However, apart from the most well studied genomes of human and mouse, mammalian transcription has not been profiled with sufficiently high precision.

We prepared and sequenced Start-seq libraries from rat (Rattus norgevicus) primary neural progenitor cells. Over 48 million uniquely mappable reads from two independent biological replicates allowed us to define the TSSs of 7365 known genes in the rn6 genome, reannotating 2503 TSSs by more than 5 base pairs, characterize promoter-associated antisense transcription, and profile Pol II pausing. By combining TSS data with polyA-selected RNA sequencing, we also identified thousands of potential new genes producing stable RNA as well as non-genic transcripts representing possible regulatory elements.

Our study has produced the first Start-seq dataset for the rat. Apart from profiling transcription initiation, our data reaffirm the prevalence of Pol II pausing across the rat genome and indicate conservation of pausing mechanisms across metazoan genomes. We suggest that pausing location, at least in mammals, is constrained by a distance from initiation of transcription, whether it occurs at or outside of a gene promoter. Abundant antisense transcription initiation around protein coding genes indicates that Pol II recruited to the vicinity of a promoter is distributed to available start sites of transcription at either DNA strand. Transcriptome profiling of neural progenitors presented here will facilitate further studies of other rat cell types as well as other organisms.

Cover page of Colloids in confined liquid crystals: a plot twist in the lock-and-key mechanism.

Colloids in confined liquid crystals: a plot twist in the lock-and-key mechanism.

(2019)

By confining soft materials within tailored boundaries it is possible to design energy landscapes to address and control colloidal dynamics. This provides unique opportunities to create reconfigurable, hierarchically organized structures, a leading challenge in materials science. Example soft matter systems include liquid crystals. For instance, when nematic liquid crystals (NLCs) are confined in a vessel with undulated boundaries, bend and splay distortions can be used to position particles. Here we confine this system in a twist cell. We also study cholesteric liquid crystals, which have an "intrinsic" twist distortion which adds to the ones imposed by the solid boundaries. The cholesteric pitch competes with the other length scales in the system (colloid radius, vessel thickness, wavelength of boundary undulations), enriching the possible configurations. Depending on the pitch-to-radius and pitch-to-thickness ratios the interaction can be attractive or repulsive. By tuning the pitch (i.e. changing the concentration of the chiral dopant), it is possible to selectively promote or inhibit particle trapping at the docking sites.

Cover page of A neural network-evolutionary computational framework for remaining useful life estimation of mechanical systems.

A neural network-evolutionary computational framework for remaining useful life estimation of mechanical systems.

(2019)

This paper presents a framework for estimating the remaining useful life (RUL) of mechanical systems. The framework consists of a multi-layer perceptron and an evolutionary algorithm for optimizing the data-related parameters. The framework makes use of a strided time window along with a piecewise linear model to estimate the RUL for each mechanical component. Tuning the data-related parameters in the optimization framework allows for the use of simple models, e.g. neural networks with few hidden layers and few neurons at each layer, which may be deployed in environments with limited resources such as embedded systems. The proposed method is evaluated on the publicly available C-MAPSS dataset. The accuracy of the proposed method is compared against other state-of-the art methods in the literature. The proposed method is shown to perform better than the compared methods while making use of a compact model.

Cover page of Monitoring earthen archaeological heritage using multi-temporal terrestrial laser scanning and surface change detection

Monitoring earthen archaeological heritage using multi-temporal terrestrial laser scanning and surface change detection

(2019)

Terrestrial laser scanning (TLS) is a three-dimensional survey technique proven successful for in-field stratigraphic and site-wide documentation or damage assessment of archaeological heritage. This study explores the potential utility of TLS and the Multiscale Model to Model Cloud Comparison (M3C2) surface change detection method for monitoring and preserving ancient earthen architecture, and for creating comprehensive site monitoring programs in compliance with UNESCO periodic reporting guidelines. The proposed methodology was tested using 3-D TLS datasets spanning a period of six years to assess the decay of mud brick structures at Çatalhöyük, Turkey in order to understand material loss in walls and buildings, identify potential underlying causes, and create a plan for physical interventions. This paper explains how a multi-temporal laser scanning workflow using the M3C2 method can be leveraged successfully to quantify—with millimeter-level accuracy—the decay of large earthen sites and inform future conservation interventions. This approach allows for the identification of the wall features with the most immediate risk of deterioration based on the detection of patterns of change and calculation of its significance as a preventative measure. Results presented in this paper suggest that the proposed method can be used effectively to enhance site monitoring and perform preventative on-site interventions at large earthen sites earthen sites in the Middle East, Africa, Europe, and the Americas.

Cover page of Spatial Analysis and Heritage Conservation: Leveraging 3-D Data and GIS for Monitoring Earthen Architecture

Spatial Analysis and Heritage Conservation: Leveraging 3-D Data and GIS for Monitoring Earthen Architecture

(2019)

This paper discusses new advances in heritage site monitoring using a geo-spatial method for assessing the state of preservation of earthen architecture overtime as a preventive conservation measure. The proposed method leverages a comprehensive (quantitative-qualitative) approach that gathers multi-temporal data including environmental information collected by means of environmental loggers, qualitative vulnerability assessment of mud-brick walls, and surface change detection information obtained by comparing terrestrial laser scanning point cloud capturing the decay of building’s wall features over time. Producing a detailed spatial understanding of the conservation issues that affect mud-brick walls in large earthen sites, this method can be used by conservators to rapidly identify which buildings require immediate intervention and lay the basis for future evaluation of the conservation actions undertaken. To test the effectiveness of the proposed geospatial model in producing a comprehensive view of the environmental risk and pattern of decay that affect mudbrick structures, this paper presents analyses and results obtained in a six-year study at Çatalhöyük, Turkey. Our results corroborate the effectiveness of the proposed method and prove that it can be successfully employed to create preventive conservation measures at other earthen sites inside and outside the Near East.