DLSIA: Deep Learning for Scientific Image Analysis.

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing. DLSIA features easy-to-use architectures, such as autoencoders, tunable U-Nets and parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse mixed-scale networks (SMSNets), generated using random graphs, sparse connections and dilated convolutions connecting different length scales.

Deploying Machine Learning Based Segmentation for Scientific Imaging Analysis at Synchrotron Facilities.

Scientific user facilities present a unique set of challenges for image processing due to the large volume of data generated from experiments and simulations. Furthermore, developing and implementing algorithms for real-time processing and analysis while correcting for any artifacts or distortions in images remains a complex task, given the computational requirements of the processing algorithms. In a collaborative effort across multiple Department of Energy national laboratories, the "MLExchange" project is focused on addressing these challenges.

MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies.

Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are programmatically demanding and computationally costly. The MLExchange project aims to build a collaborative platform equipped with enabling tools that allow scientists and facility users who do not have a profound ML background to use ML and computational resources in scientific discovery.

A comparison of deep-learning-based inpainting techniques for experimental X-ray scattering.

The implementation is proposed of image inpainting techniques for the reconstruction of gaps in experimental X-ray scattering data. The proposed methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution neural networks and mixed-scale dense networks, to reconstruct the missing information in experimental scattering images. In particular, the recovered pixel intensities are evaluated against their corresponding ground-truth values using the mean absolute error and the correlation coefficient metrics.

EWALD: A macromolecular diffractometer for the second target station.

Revealing the positions of all the atoms in large macromolecules is powerful but only possible with neutron macromolecular crystallography (NMC). Neutrons provide a sensitive and gentle probe for the direct detection of protonation states at near-physiological temperatures and clean of artifacts caused by x rays or electrons. Currently, NMC use is restricted by the requirement for large crystal volumes even at state-of-the-art instruments such as the macromolecular neutron diffractometer at the Spallation Neutron Source.

Sizes of pure and doped helium droplets from single shot x-ray imaging.

Advancements in x-ray free-electron lasers on producing ultrashort, ultrabright, and coherent x-ray pulses enable single-shot imaging of fragile nanostructures, such as superfluid helium droplets. This imaging technique gives unique access to the sizes and shapes of individual droplets. In the past, such droplet characteristics have only been indirectly inferred by ensemble averaging techniques.

High-Performance Hybrid-Global-Deflated-Local Optimization with Applications to Active Learning.

Mathematical optimization lies at the core of many science and industry applications. One important issue with many current optimization strategies is a well-known trade-off between the number of function evaluations and the probability to find the global, or at least sufficiently high-quality local optima. In machine learning (ML), and by extension in active learning - for instance for autonomous experimentation - mathematical optimization is often used to find the underlying uncertain surrogate model from which subsequent decisions are made and therefore ML relies on high-quality optima to obtain the most accurate models.

GPU-accelerated multitiered iterative phasing algorithm for fluctuation X-ray scattering.

The multitiered iterative phasing (MTIP) algorithm is used to determine the biological structures of macromolecules from fluctuation scattering data. It is an iterative algorithm that reconstructs the electron density of the sample by matching the computed fluctuation X-ray scattering data to the external observations, and by simultaneously enforcing constraints in real and Fourier space. This paper presents the first ever MTIP algorithm acceleration efforts on contemporary graphics processing units (GPUs).

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation.

Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins.

Evaluating crystallographic likelihood functions using numerical quadratures.

Intensity-based likelihood functions in crystallographic applications have the potential to enhance the quality of structures derived from marginal diffraction data. Their usage, however, is complicated by the ability to efficiently compute these target functions. Here, a numerical quadrature is developed that allows the rapid evaluation of intensity-based likelihood functions in crystallographic applications.

SAD phasing of XFEL data depends critically on the error model.

A nonlinear least-squares method for refining a parametric expression describing the estimated errors of reflection intensities in serial crystallographic (SX) data is presented. This approach, which is similar to that used in the rotation method of crystallographic data collection at synchrotrons, propagates error estimates from photon-counting statistics to the merged data. Here, it is demonstrated that the application of this approach to SX data provides better SAD phasing ability, enabling the autobuilding of a protein structure that had previously failed to be built.

Ab initio structure determination from experimental fluctuation X-ray scattering data.

Fluctuation X-ray scattering (FXS) is an emerging experimental technique in which X-ray solution scattering data are collected from particles in solution using ultrashort X-ray exposures generated by a free-electron laser (FEL). FXS experiments overcome the low data-to-parameter ratios associated with traditional solution scattering measurements by providing several orders of magnitude more information in the final processed data. Here we demonstrate the practical feasibility of FEL-based FXS on a biological multiple-particle system and describe data-processing techniques required to extract robust FXS data and significantly reduce the required number of snapshots needed by introducing an iterative noise-filtering technique.

Free-electron laser data for multiple-particle fluctuation scattering analysis.

Fluctuation X-ray scattering (FXS) is an emerging experimental technique in which solution scattering data are collected using X-ray exposures below rotational diffusion times, resulting in angularly anisotropic X-ray snapshots that provide several orders of magnitude more information than traditional solution scattering data. Such experiments can be performed using the ultrashort X-ray pulses provided by a free-electron laser source, allowing one to collect a large number of diffraction patterns in a relatively short time. Here, we describe a test data set for FXS, obtained at the Linac Coherent Light Source, consisting of close to 100 000 multi-particle diffraction patterns originating from approximately 50 to 200 Paramecium Bursaria Chlorella virus particles per snapshot.

Structure of photosystem II and substrate binding at room temperature.

Light-induced oxidation of water by photosystem II (PS II) in plants, algae and cyanobacteria has generated most of the dioxygen in the atmosphere. PS II, a membrane-bound multi-subunit pigment protein complex, couples the one-electron photochemistry at the reaction centre with the four-electron redox chemistry of water oxidation at the MnCaO cluster in the oxygen-evolving complex (OEC). Under illumination, the OEC cycles through five intermediate S-states (S to S), in which S is the dark-stable state and S is the last semi-stable state before O-O bond formation and O evolution.

Operational properties of fluctuation X-ray scattering data.

X-ray scattering images collected on timescales shorter than rotation diffusion times using a (partially) coherent beam result in a significant increase in information content in the scattered data. These measurements, named fluctuation X-ray scattering (FXS), are typically performed on an X-ray free-electron laser (XFEL) and can provide fundamental insights into the structure of biological molecules, engineered nanoparticles or energy-related mesoscopic materials beyond what can be obtained with standard X-ray scattering techniques. In order to understand, use and validate experimental FXS data, the availability of basic data characteristics and operational properties is essential, but has been absent up to this point.

Simultaneous detection of electronic structure changes from two elements of a bifunctional catalyst using wavelength-dispersive X-ray emission spectroscopy and in situ electrochemistry.

Multielectron catalytic reactions, such as water oxidation, nitrogen reduction, or hydrogen production in enzymes and inorganic catalysts often involve multimetallic clusters. In these systems, the reaction takes place between metals or metals and ligands to facilitate charge transfer, bond formation/breaking, substrate binding, and release of products. In this study, we present a method to detect X-ray emission signals from multiple elements simultaneously, which allows for the study of charge transfer and the sequential chemistry occurring between elements.

Improved crystal orientation and physical properties from single-shot XFEL stills.

X-ray diffraction patterns from still crystals are inherently difficult to process because the crystal orientation is not uniquely determined by measuring the Bragg spot positions. Only one of the three rotational degrees of freedom is directly coupled to spot positions; the other two rotations move Bragg spots in and out of the reflecting condition but do not change the direction of the diffracted rays. This hinders the ability to recover accurate structure factors from experiments that are dependent on single-shot exposures, such as femtosecond diffract-and-destroy protocols at X-ray free-electron lasers (XFELs).

Helium superfluidity. Shapes and vorticities of superfluid helium nanodroplets.

Helium nanodroplets are considered ideal model systems to explore quantum hydrodynamics in self-contained, isolated superfluids. However, exploring the dynamic properties of individual droplets is experimentally challenging. In this work, we used single-shot femtosecond x-ray coherent diffractive imaging to investigate the rotation of single, isolated superfluid helium-4 droplets containing ~10(8) to 10(11) atoms.

Taking snapshots of photosynthetic water oxidation using femtosecond X-ray diffraction and spectroscopy.

The dioxygen we breathe is formed by light-induced oxidation of water in photosystem II. O2 formation takes place at a catalytic manganese cluster within milliseconds after the photosystem II reaction centre is excited by three single-turnover flashes. Here we present combined X-ray emission spectra and diffraction data of 2-flash (2F) and 3-flash (3F) photosystem II samples, and of a transient 3F' state (250 μs after the third flash), collected under functional conditions using an X-ray free electron laser.

Accurate macromolecular structures using minimal measurements from X-ray free-electron lasers.

X-ray free-electron laser (XFEL) sources enable the use of crystallography to solve three-dimensional macromolecular structures under native conditions and without radiation damage. Results to date, however, have been limited by the challenge of deriving accurate Bragg intensities from a heterogeneous population of microcrystals, while at the same time modeling the X-ray spectrum and detector geometry. Here we present a computational approach designed to extract meaningful high-resolution signals from fewer diffraction measurements.

Studies of IscR reveal a unique mechanism for metal-dependent regulation of DNA binding specificity.

IscR from Escherichia coli is an unusual metalloregulator in that both apo and iron sulfur (Fe-S)-IscR regulate transcription and exhibit different DNA binding specificities. Here, we report structural and biochemical studies of IscR suggesting that remodeling of the protein-DNA interface upon Fe-S ligation broadens the DNA binding specificity of IscR from binding the type 2 motif only to both type 1 and type 2 motifs. Analysis of an apo-IscR variant with relaxed target-site discrimination identified a key residue in wild-type apo-IscR that, we propose, makes unfavorable interactions with a type 1 motif.

Simultaneous femtosecond X-ray spectroscopy and diffraction of photosystem II at room temperature.

Intense femtosecond x-ray pulses produced at the Linac Coherent Light Source (LCLS) were used for simultaneous x-ray diffraction (XRD) and x-ray emission spectroscopy (XES) of microcrystals of photosystem II (PS II) at room temperature. This method probes the overall protein structure and the electronic structure of the Mn4CaO5 cluster in the oxygen-evolving complex of PS II. XRD data are presented from both the dark state (S1) and the first illuminated state (S2) of PS II.

Energy-dispersive X-ray emission spectroscopy using an X-ray free-electron laser in a shot-by-shot mode.

The ultrabright femtosecond X-ray pulses provided by X-ray free-electron lasers open capabilities for studying the structure and dynamics of a wide variety of systems beyond what is possible with synchrotron sources. Recently, this "probe-before-destroy" approach has been demonstrated for atomic structure determination by serial X-ray diffraction of microcrystals. There has been the question whether a similar approach can be extended to probe the local electronic structure by X-ray spectroscopy.

Nanoflow electrospinning serial femtosecond crystallography.

An electrospun liquid microjet has been developed that delivers protein microcrystal suspensions at flow rates of 0.14-3.1 µl min(-1) to perform serial femtosecond crystallography (SFX) studies with X-ray lasers.