The maximum range of perpendicular momentum transfer (qz) has been tripled for X-ray scattering from liquid surfaces when using a double-crystal deflector setup to tilt the incident X-ray beam. This is achieved by employing a higher-energy X-ray beam to access Miller indices of reflecting crystal atomic planes that are three times higher than usual. The deviation from the exact Bragg angle condition induced by misalignment between the X-ray beam axis and the main rotation axis of the double-crystal deflector is calculated, and a fast and straightforward procedure to align them is deduced. An experimental method of measuring scattering intensity along the qz direction on liquid surfaces up to qz = 7 Å−1 is presented, with liquid copper serving as a reference system for benchmarking purposes.

A multi-slit very small angle neutron scattering (MS-VSANS) instrument has been finally accepted at the China Spallation Neutron Source (CSNS). It is the first spallation neutron source based VSANS instrument. MS-VSANS has a good signal-to-noise ratio and can cover a wide scattering vector magnitude range from 0.00028 to 1.4 Å−1. In its primary flight path, a combined curved multichannel beam bender and sections of rotary exchange drums are installed to minimize the background downstream of the instrument. An exchangeable multi-slit beam focusing system is integrated into the primary flight path, enabling access to a minimum scattering vector magnitude of 0.00028 Å−1. MS-VSANS has three modes, namely conventional SANS, polarizing SANS and VSANS modes. In the SANS mode, three motorized high-efficiency 3He tube detectors inside the detector tank cover scattering angles from 0.12 to 35° simultaneously. In the polarizing SANS mode, a double-V cavity provides highly polarized neutrons and a high-efficiency 3He polarization analyser allows full polarization analysis. In the VSANS mode, an innovative high-resolution gas electron multiplier detector covers scattering angles from 0.016 to 0.447°. The absolute scattering intensities of a selection of standard samples are obtained using the direct-beam technique; the effectiveness of this method is verified by testing the standard samples and comparing the results with those from a benchmark instrument. The MS-VSANS instrument is designed to be flexible and versatile and all the design goals have been achieved.

X-ray diffraction from dislocation half-loops consisting of a misfit segment with two threading arms extending from it to the surface is calculated by the Monte Carlo method. The diffraction profiles and reciprocal space maps are controlled by the ratio of the total lengths of the misfit and the threading segments of the half-loops. A continuous transformation from the diffraction characteristic of misfit dislocations to that of threading dislocations with increasing thickness of epitaxial film is studied. Diffraction from dislocations with edge- and screw-type threading arms is considered and the contributions of the two types of dislocations are compared.

Fluctuation X-ray scattering (FXS) offers a complementary approach for nano- and bioparticle imaging with an X-ray free-electron laser (XFEL), by extracting structural information from correlations in scattered XFEL pulses. Here a workflow is presented for single-particle structure determination using FXS. The workflow includes procedures for extracting the rotational invariants from FXS patterns, performing structure reconstructions via iterative phasing of the invariants, and aligning and averaging multiple reconstructions. The reconstruction pipeline is implemented in the open-source software xFrame and its functionality is demonstrated on several simulated structures.

Dark-field X-ray microscopy (DFXM) is a full-field imaging technique that non-destructively maps the structure and local strain inside deeply embedded crystalline elements in three dimensions. In DFXM, an objective lens is placed along the diffracted beam to generate a magnified projection image of the local diffracted volume. This work explores contrast methods and optimizes the DFXM setup specifically for the case of mapping dislocations. Forward projections of detector images are generated using two complementary simulation tools based on geometrical optics and wavefront propagation, respectively. Weak and strong beam contrast and the mapping of strain components are studied. The feasibility of observing dislocations in a wall is elucidated as a function of the distance between neighbouring dislocations and the spatial resolution. Dislocation studies should be feasible with energy band widths of 10−2, of relevance for fourth-generation synchrotron and X-ray free-electron laser sources.

Analysis of small-angle scattering (SAS) data requires intensive modeling to infer and characterize the structures present in a sample. This iterative improvement of models is a time-consuming process. Presented here is Scattering Equation Builder (SEB), a C++ library that derives exact analytic expressions for the form factors of complex composite structures. The user writes a small program that specifies how the sub-units should be linked to form a composite structure and calls SEB to obtain an expression for the form factor. SEB supports e.g. Gaussian polymer chains and loops, thin rods and circles, solid spheres, spherical shells and cylinders, and many different options for how these can be linked together. The formalism behind SEB is presented and simple case studies are given, such as block copolymers with different types of linkage, as well as more complex examples, such as a random walk model of 100 linked sub-units, dendrimers, polymers and rods attached to the surfaces of geometric objects, and finally the scattering from a linear chain of five stars, where each star is built up of four diblock copolymers. These examples illustrate how SEB can be used to develop complex models and hence reduce the cost of analyzing SAS data.

The strong metal–support interaction (SMSI) is a phenomenon observed in supported metal catalyst systems in which reducible metal oxide supports can form overlayers over the surface of active metal nanoparticles (NPs) under a hydrogen (H2) environment at elevated temperatures. SMSI has been shown to affect catalyst performance in many reactions by changing the type and number of active sites on the catalyst surface. Laboratory methods for the analysis of SMSI at the nanoparticle-ensemble level are lacking and mostly based on indirect evidence, such as gas chemisorption. Here, we demonstrate the possibility to detect and characterize SMSIs in Co/TiOx model catalysts using the laboratory X-ray standing wave (XSW) technique for a large ensemble of NPs at the bulk scale. We designed a thermally stable MoNx/SiNx periodic multilayer to retain XSW generation after reduction with H2 gas at 600°C. The model catalyst system was synthesized here by deposition of a thin TiOx layer on top of the periodic multilayer, followed by Co NP deposition via spare ablation. A partial encapsulation of Co NPs by TiOx was identified by analyzing the change in Ti atomic distribution. This novel methodological approach can be extended to observe surface restructuring of model catalysts in situ at high temperature (up to 1000°C) and pressure (≤3 mbar), and can also be relevant for fundamental studies in the thermal stability of membranes, as well as metallurgy.

This article describes a correction procedure for the removal of indirect background contributions to measured small-angle X-ray scattering patterns. The high scattering power of a sample in the ultra-small-angle region may serve as a secondary source for a window placed in front of the detector. The resulting secondary scattering appears as a sample-dependent background in the measured pattern that cannot be directly subtracted. This is an intricate problem in measurements at ultra-low angles, which can significantly reduce the useful dynamic range of detection. Two different procedures are presented to retrieve the real scattering profile of the sample.

X-ray crystallography is an established tool to probe the structure of macromolecules with atomic resolution. Compared with alternative techniques such as single-particle cryo-electron microscopy and micro-electron diffraction, X-ray crystallography is uniquely suited to room-temperature studies and for obtaining a detailed picture of macromolecules subjected to an external electric field (EEF). The impact of an EEF on proteins has been extensively explored through single-crystal X-ray crystallography, which works well with larger high-quality protein crystals. This article introduces a novel design for a 3D-printed in situ crystallization plate that serves a dual purpose: fostering crystal growth and allowing the concurrent examination of the effects of an EEF on crystals of varying sizes. The plate's compatibility with established X-ray crystallography techniques is evaluated.

This paper introduces a new 2D representation of the orientation distribution function for an arbitrary material texture. The approach is based on the isometric square torus mapping of the Clifford torus, which allows for points on the unit quaternion hypersphere (each corresponding to a 3D orientation) to be represented in a periodic 2D square map. The combination of three such orthogonal mappings into a single RGB (red–green–blue) image provides a compact periodic representation of any set of orientations. Square torus representations of five different orientation sampling methods are compared and analyzed in terms of the Riesz s energies that quantify the uniformity of the samplings. The effect of crystallographic symmetry on the square torus map is analyzed in terms of the Rodrigues fundamental zones for the rotational symmetry groups. The paper concludes with example representations of important texture components in cubic and hexagonal materials. The new RGB representation provides a convenient and compact way of generating training data for the automated analysis of material textures by means of neural networks.

The pair angle distribution function (PADF) is a three- and four-atom correlation function that characterizes the local angular structure of disordered materials, particles or nanocrystalline materials. The PADF can be measured using X-ray or electron fluctuation diffraction data, which can be collected by scanning or flowing a structurally disordered sample through a focused beam. It is a natural generalization of established pair distribution methods, which do not provide angular information. The software package pypadf provides tools to calculate the PADF from fluctuation diffraction data. The package includes tools for calculating the intensity correlation function, which is a necessary step in the PADF calculation and also the basis for other fluctuation scattering analysis techniques.

The capillary wave model of a liquid surface predicts both the X-ray specular reflection and the diffuse scattering around it. A quantitative method is presented to obtain the X-ray reflectivity (XRR) from a liquid surface through the diffuse scattering data around the specular reflection measured using a grazing incidence X-ray off-specular scattering (GIXOS) geometry at a fixed horizontal offset angle with respect to the plane of incidence. With this approach the entire Qz-dependent reflectivity profile can be obtained at a single, fixed incident angle. This permits a much faster acquisition of the profile than with conventional reflectometry, where the incident angle must be scanned point by point to obtain a Qz-dependent profile. The XRR derived from the GIXOS-measured diffuse scattering, referred to in this paper as pseudo-reflectivity, provides a larger Qz range compared with the reflectivity measured by conventional reflectometry. Transforming the GIXOS-measured diffuse scattering profile to pseudo-XRR opens up the GIXOS method to widely available specular XRR analysis software tools. Here the GIXOS-derived pseudo-XRR is compared with the XRR measured by specular reflectometry from two simple vapor–liquid interfaces at different surface tension, and from a hexadecyltri­methyl­ammonium bromide monolayer on a water surface. For the simple liquids, excellent agreement (beyond 11 orders of magnitude in signal) is found between the two methods, supporting the approach of using GIXOS-measured diffuse scattering to derive reflectivities. Pseudo-XRR obtained at different horizontal offset angles with respect to the plane of incidence yields indistinguishable results, and this supports the robustness of the GIXOS-XRR approach. The pseudo-XRR method can be extended to soft thin films on a liquid surface, and criteria are established for the applicability of the approach.

Controlling the shape and size dispersivity and crystallinity of nanoparticles (NPs) has been a challenge in identifying these parameters' role in the physical and chemical properties of NPs. The need for reliable quantitative tools for analyzing the dispersivity and crystallinity of NPs is a considerable problem in optimizing scalable synthesis routes capable of controlling NP properties. The most common tools are electron microscopy (EM) and X-ray scattering techniques. However, each technique has different susceptibility to these parameters, implying that more than one technique is necessary to characterize NP systems with maximum reliability. Wide-angle X-ray scattering (WAXS) is mandatory to access information on crystallinity. In contrast, EM or small-angle X-ray scattering (SAXS) is required to access information on whole NP sizes. EM provides average values on relatively small ensembles in contrast to the bulk values accessed by X-ray techniques. Besides the fact that the SAXS and WAXS techniques have different susceptibilities to size distributions, SAXS is easily affected by NP–NP interaction distances. Because of all the variables involved, there have yet to be proposed methodologies for cross-analyzing data from two techniques that can provide reliable quantitative results of dispersivity and crystallinity. In this work, a SAXS/WAXS-based methodology is proposed for simultaneously quantifying size distribution and degree of crystallinity of NPs. The most reliable easy-to-access size result for each technique is demonstrated by computer simulation. Strategies on how to compare these results and how to identify NP–NP interaction effects underneath the SAXS intensity curve are presented. Experimental results are shown for cubic-like CeO2 NPs. WAXS size results from two analytical procedures are compared, line-profile fitting of individual diffraction peaks in opposition to whole pattern fitting. The impact of shape dispersivity is also evaluated. Extension of the proposed methodology for cross-analyzing EM and WAXS data is possible.

Understanding the symmetries described by subperiodic groups – frieze, rod and layer groups – has been instrumental in predicting various properties (band structures, optical absorption, Raman spectra, diffraction patterns, topological properties etc.) of `low-dimensional' crystals. This knowledge is crucial in the tailored design of materials for specific applications across electronics, photonics and materials engineering. However, there are materials that have the property of being periodic only in one direction and whose symmetry cannot be described by the subperiodic rod groups. Describing the symmetry of these materials necessitates the application of line group theory. This paper gives an overview of subperiodic groups while briefly introducing line groups in order to acquaint the crystallographic community with these symmetries and direct them to pertinent literature. Since line groups are generally not sub­periodic, they have thus far remained outside the realm of symmetries traditionally considered in crystallography, although there are numerous `one-dimensional' crystals (i.e. monoperiodic structures) possessing line group symmetry.

It is demonstrated that high-resolution energy-dispersive X-ray fluorescence mapping devices based on a micro-focused beam are not restricted to high-speed analyses of element distributions or to the detection of different grains, twins and subgrains in crystalline materials but can also be used for the detection of dislocations in high-quality single crystals. Si single crystals with low dislocation densities were selected as model materials to visualize the position of dis­locations by the spatially resolved measurement of Bragg-peak intensity fluctuations. These originate from the most distorted planes caused by the stress fields of dislocations. The results obtained by this approach are compared with laboratory-based Lang X-ray topographs. The presented methodology yields comparable results and it is of particular interest in the field of crystal growth, where fast chemical and microstructural characterization feedback loops are indispensable for short and efficient development times. The beam divergence was reduced via an aperture management system to facilitate the visualization of dislocations for virtually as-grown, non-polished and non-planar samples with a very pronounced surface profile.

Recent developments in synchrotron radiation facilities have increased the amount of data generated during acquisitions considerably, requiring fast and efficient data processing techniques. Here, the application of dense neural networks (DNNs) to data treatment of X-ray diffraction computed tomography (XRD-CT) experiments is presented. Processing involves mapping the phases in a tomographic slice by predicting the phase fraction in each individual pixel. DNNs were trained on sets of calculated XRD patterns generated using a Python algorithm developed in-house. An initial Rietveld refinement of the tomographic slice sum pattern provides additional information (peak widths and integrated intensities for each phase) to improve the generation of simulated patterns and make them closer to real data. A grid search was used to optimize the network architecture and demonstrated that a single fully connected dense layer was sufficient to accurately determine phase proportions. This DNN was used on the XRD-CT acquisition of a mock-up and a historical sample of highly heterogeneous multi-layered decoration of a late medieval statue, called `applied brocade'. The phase maps predicted by the DNN were in good agreement with other methods, such as non-negative matrix factorization and serial Rietveld refinements performed with TOPAS, and outperformed them in terms of speed and efficiency. The method was evaluated by regenerating experimental patterns from predictions and using the R-weighted profile as the agreement factor. This assessment allowed us to confirm the accuracy of the results.

The spatial orientation of α lamellae in a metastable β-Ti matrix of Timetal LCB (Ti–6.8 Mo–4.5 Fe–1.5 Al in wt%) was examined and the orientation of the hexagonal close-packed α lattice in the α lamella was determined. For this purpose, a combination of methods of small-angle X-ray scattering, scanning electron microscopy and electron backscatter diffraction was used. The habit planes of α laths are close to {111}β, which corresponds to (1320)α in the hexagonal coordinate system of the α phase. The longest α lamella direction lies approximately along one of the 〈110〉β directions which are parallel to the specific habit plane. Taking into account the average lattice parameters of the β and α phases in aged conditions in Timetal LCB, it was possible to index all main axes and faces of an α lath not only in the cubic coordinate system of the parent β phase but also in the hexagonal system of the α phase.

Small-angle scattering (SAS) is a key experimental technique for analyzing nanoscale structures in various materials. In SAS data analysis, selecting an appropriate mathematical model for the scattering intensity is critical, as it generates a hypothesis of the structure of the experimental sample. Traditional model selection methods either rely on qualitative approaches or are prone to overfitting. This paper introduces an analytical method that applies Bayesian model selection to SAS measurement data, enabling a quantitative evaluation of the validity of mathematical models. The performance of the method is assessed through numerical experiments using artificial data for multicomponent spherical materials, demonstrating that this proposed analysis approach yields highly accurate and interpretable results. The ability of the method to analyze a range of mixing ratios and particle size ratios for mixed components is also discussed, along with its precision in model evaluation by the degree of fitting. The proposed method effectively facilitates quantitative analysis of nanoscale sample structures in SAS, which has traditionally been challenging, and is expected to contribute significantly to advancements in a wide range of fields.

Unlike most of the periodic table, many rare-earth elements display considerable resonant scattering for thermal neutrons. Although this property is accompanied by strong neutron absorption, modern high-intensity neutron sources make diffraction experiments possible with these elements. Computation of scattering intensities is accomplished by fitting the variation in resonant scattering lengths (b0, b' and b'') to a semi-empirical Breit–Wigner formalism, which can be evaluated over the range of neutron energies useful for diffraction, typically E = 10–600 meV; λ = 0.4–2.8 Å (with good extrapolation to longer wavelengths).

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclo­dextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0, which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

The Q resolution in Bonse–Hart double-crystal diffractometers is determined for a given Bragg angle by the value of the crystallographic structure factor. To date, the reflections Si 220 or Si 111 have been used exclusively in neutron scattering, which provide resolutions for triple-bounce crystals of about 2 × 10−5 Å−1 (FWHM). The Darwin width of the GaAs 200 reflection is about a factor of 10 smaller, offering the possibility of a Q resolution of 2 × 10−6 Å−1 provided crystals of sufficient quality are available. This article reports a feasibility study with single-bounce GaAs 200, yielding a Q resolution of 4.6 × 10−6 Å−1, six times superior in comparison with a Si 220 setup.

Small-angle neutron scattering is a widely used technique to study large-scale structures in bulk samples. The largest accessible length scale in conventional Bragg scattering is determined by the combination of the longest available neutron wavelength and smallest resolvable scattering angle. A method is presented that circumvents this limitation and is able to extract larger length scales from the low-q power-law scattering using a modification of the well known Porod law connecting the scattered intensity of randomly distributed objects to their specific surface area. It is shown that in the special case of a highly aligned domain structure the specific surface area extracted from the modified Porod law can be used to determine specific length scales of the domain structure. The analysis method is applied to study the micrometre-sized domain structure found in the intermediate mixed state of the superconductor niobium. The analysis approach allows the range of accessible length scales to be extended from 1 µm to up to 40 µm using a conventional small-angle neutron scattering setup.

Understanding the structure–property relationship in electrocatalysts under working conditions is crucial for the rational design of novel and improved catalytic materials. This paper presents the Aarhus University reactor for electrochemical studies using X-rays (AUREX) operando electrocatalytic flow cell, designed as an easy-to-use versatile setup with a minimal background contribution and a uniform flow field to limit concentration polarization and handle gas formation. The cell has been employed to measure operando total scattering, diffraction and absorption spectroscopy as well as simultaneous combinations thereof on a commercial silver electrocatalyst for proof of concept. This combination of operando techniques allows for monitoring of the short-, medium- and long-range structure under working conditions, including an applied potential, liquid electrolyte and local reaction environment. The structural transformations of the Ag electrocatalyst are monitored with non-negative matrix factorization, linear combination analysis, the Pearson correlation coefficient matrix, and refinements in both real and reciprocal space. Upon application of an oxidative potential in an Ar-saturated aqueous 0.1 M KHCO3/K2CO3 electrolyte, the face-centered cubic (f.c.c.) Ag gradually transforms first to a trigonal Ag2CO3 phase, followed by the formation of a monoclinic Ag2CO3 phase. A reducing potential immediately reverts the structure to the Ag (f.c.c.) phase. Following the electrochemical-reaction-induced phase transitions is of fundamental interest and necessary for understanding and improving the stability of electrocatalysts, and the operando cell proves a versatile setup for probing this. In addition, it is demonstrated that, when studying electrochemical reactions, a high energy or short exposure time is needed to circumvent beam-induced effects.

Presented here is an effective approach to desmearing slit ultra-small-angle neutron scattering (USANS) data, based on complementary small-angle neutron scattering (SANS) measurements, leading to a seamless merging of these data sets. The study focuses on the methodological aspects of desmearing USANS data, which can then be presented in the conventional manner of SANS, enabling a broader pool of data analysis methods. The key innovation lies in the use of smeared SANS data for extrapolating slit USANS, offering a self-consistent integrand function for desmearing with Lake's iterative method. The proposed approach is validated through experimental data on porous anodized aluminium oxide membranes, showcasing its applicability and benefits. The findings emphasize the importance of accurate desmearing for merging USANS and SANS data in the crossover q region, which is particularly crucial for complex scattering patterns.

We present first hard X-ray photoelectron spectroscopy (HAXPES) results of aqueous salt solutions and dispersions of gold nanoparticles in liquid cells equipped with specially designed microfabricated thin silicon nitride membranes, with thickness in the 15–25 nm range, mounted in a high-vacuum-compatible environment. The experiments have been performed at the HAXPES endstation of the GALAXIES beamline at the SOLEIL synchrotron radiation facility. The low-stress membranes are fabricated from 100 mm silicon wafers using standard lithography techniques. Platinum alignment marks are added to the chips hosting the membranes to facilitate the positioning of the X-ray beam on the membrane by detecting the corresponding photoemission lines. Two types of liquid cells have been used, a static one built on an Omicron-type sample holder with the liquid confined in the cell container, and a circulating liquid cell, in which the liquid can flow in order to mitigate the effects due to beam damage. We demonstrate that the membranes are mechanically robust and able to withstand 1 bar pressure difference between the liquid inside the cell and vacuum, and the intense synchrotron radiation beam during data acquisition. This opens up new opportunities for spectroscopic studies of liquids.

The design and first results of a high-transmission soft X-ray spectrometer operated at the X-SPEC double-undulator beamline of the KIT Light Source are presented. As a unique feature, particular emphasis was placed on optimizing the spectrometer transmission by maximizing the solid angle and the efficiencies of spectrometer gratings and detector. A CMOS detector, optimized for soft X-rays, allows for quantum efficiencies of 90% or above over the full energy range of the spectrometer, while simultaneously offering short readout times. Combining an optimized control system at the X-SPEC beamline with continuous energy scans (as opposed to step scans), the high transmission of the spectrometer, and the fast readout of the CMOS camera, enable the collection of entire rapid resonant inelastic soft X-ray scattering maps in less than 1 min. Series of spectra at a fixed energy can be taken with a frequency of up to 5 Hz. Furthermore, the use of higher-order reflections allows a very wide energy range (45 to 2000 eV) to be covered with only two blazed gratings, while keeping the efficiency high and the resolving power E/ΔE above 1500 and 3000 with low- and high-energy gratings, respectively.

The inaugural edition of the Emerging Technologies and Trends in Identity Verification (IDV), KYC, and KYB Report 2024 offers a comprehensive overview of the key technology trends and best practices in digital onboarding for consumers and businesses in 2024.

We enumerate the 55083357 iso-edge subdivisions of six-dimensional translational lattices. We report on the use of the method of canonical forms that allows us to apply hashing techniques used in modern databases.

In this third edition of "Eruptions of Hawaiian Volcanoes—Past, Present, and Future," we include information about Kīlauea’s 2018 eruption in the lower East Rift Zone—the largest and most destructive in at least 200 years—and associated summit-collapse events, the eruptions at Kīlauea’s summit since 2018, and the 2022 eruption of Mauna Loa, which occurred after 38 years of quiescence.

Former Alaska Sen. Mike Gravel, who read the Pentagon Papers into the Congressional Record and confronted Barack Obama about nuclear weapons during a later presidential run, has died. He was 91.; Credit: Charles Dharapak/AP

SEASIDE, Calif. — Mike Gravel, a former U.S. senator from Alaska who read the Pentagon Papers into the Congressional Record and confronted Barack Obama about nuclear weapons during a later presidential run, has died. He was 91.

Gravel, who represented Alaska as a Democrat in the Senate from 1969 to 1981, died Saturday, according to his daughter, Lynne Mosier. Gravel had been living in Seaside, California, and was in failing health, said Theodore W. Johnson, a former aide.

Gravel's two terms came during tumultuous years for Alaska when construction of the trans-Alaska oil pipeline was authorized and when Congress was deciding how to settle Alaska Native land claims and whether to classify enormous amounts of federal land as parks, preserves and monuments.

He had the unenviable position of being an Alaska Democrat when some residents were burning President Jimmy Carter in effigy for his measures to place large sections of public lands in the state under protection from development.

Gravel feuded with Alaska's other senator, Republican Ted Stevens, on the land matter, preferring to fight Carter's actions and rejecting Stevens' advocacy for a compromise.

In the end, Congress passed the Alaska National Interest Lands Conservation Act of 1980, a compromise that set aside millions of acres for national parks, wildlife refuges and other protected areas. It was one of the last bills Carter signed before leaving office.

Gravel's Senate tenure also was notable for his anti-war activity. In 1971, he led a one-man filibuster to protest the Vietnam-era draft and he read into the Congressional Record 4,100 pages of the 7,000-page leaked document known as the Pentagon Papers, the Defense Department's history of the country's early involvement in Vietnam.

Gravel reentered national politics decades after his time in the Senate to twice run for president. Gravel, then 75, and his wife, Whitney, took public transportation in 2006 to announce he was running for president as a Democrat in the 2008 election ultimately won by Obama.

He launched his quest for the 2008 Democratic presidential nomination as a critic of the Iraq war.

"I believe America is doing harm every day our troops remain in Iraq — harm to ourselves and to the prospects for peace in the world," Gravel said in 2006. He hitched his campaign to an effort that would give all policy decisions to the people through a direct vote, including health care reform and declarations of war.

Gravel garnered attention for his fiery comments at Democratic forums.

In one 2007 debate, the issue of the possibility of using nuclear weapons against Iran came up, and Gravel confronted then-Sen. Obama. "Tell me, Barack, who do you want to nuke?" Gravel said. Obama replied: "I'm not planning to nuke anybody right now, Mike."

Gravel then ran as a Libertarian candidate after he was excluded from later Democratic debates.

In an email to supporters, he said the Democratic Party "no longer represents my vision for our great country." "It is a party that continues to sustain war, the military-industrial complex and imperialism — all of which I find anathema to my views," he said.

He failed to get the Libertarian nomination.

Gravel briefly ran for the Democratic nomination for president in 2020. He again criticized American wars and vowed to slash military spending. His last campaign was notable in that both his campaign manager and chief of staff were just 18 at the time of his short-lived candidacy.

"There was never any ... plan that he would do anything more than participate in the debates. He didn't plan to campaign, but he wanted to get his ideas before a larger audience," Johnson said.

Gravel failed to qualify for the debates. He endorsed Vermont Sen. Bernie Sanders in the contest eventually won by now-President Joe Biden.

Gravel was born Maurice Robert Gravel in Springfield, Massachusetts, on May 13, 1930.

In Alaska, he served as a state representative, including a stint as House speaker, in the mid-1960s.

He won his first Senate term after defeating incumbent Sen. Ernest Gruening, a former territorial governor, in the 1968 Democratic primary.

Gravel served two terms until he was defeated in the 1980 Democratic primary by Gruening's grandson, Clark Gruening, who lost the election to Republican Frank Murkowski.

This content is from Southern California Public Radio. View the original story at SCPR.org.

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Source: Streetwise Reports 11/05/2024

Treatment.com AI Inc. (TRUE:CSE; TREIF:OTCMKTS; 939:FRA) has announced the release of its newly updated Medical Education Suite (MES). This release aligns with the company's active participation in a major symposium focused on AI assessment in medical education. The Symposium, hosted by the University of Minnesota Medical School,  drew thought leaders and representatives from over 50 medical schools and national education organizations across the United States and internationally.

The updated MES has been designed to leverage Treatment's proprietary Global Library of Medicine (GLM) to help reduce the administration overhead and associated time and costs for medical schools in running key exams, such as the Objective Structured Clinical Examination (OSCE). Additionally, this updated version of the MES includes "easy to use" features to further support students in their clinical assessment training and exam preparation. This OSCE exam is seen as a critical evaluation used globally to assess the practical skills of medical students. It is now employed in more than 80 countries, with between 200,000 to 300,000 students participating annually.¹

The MES incorporates various AI-driven features, such as automated case generation for OSCE exams, scripts for simulated patients, and instant scoring with personalized feedback. The Suite also introduces new tools, including AI Patient, which supports students preparing for medical exams, and expanded OSCE case packages, which are expected to grow to a library of 100 cases by the end of Q4 2024. Additionally, the AI Prep Tool offers both non-guided and guided exam-simulated modes, assisting students in honing their clinical reasoning.

Kevin Peterson, MD, MPH, Treatment's Chief Medical Officer, delivered a keynote at the Symposium, joining an impressive lineup that includes presenters from Mayo Clinic and the University of Alberta. The company highlights that this Symposium is a crucial opportunity to demonstrate its MES and showcase its growing influence in the field of medical education.

CEO Dr. Essam Hamza emphasized the significance of this event, stating in the press release, "We are excited to showcase our updated medical education software suite at this landmark Symposium. The opportunity to have a positive impact on the medical training of students and, in turn, introduce them to our range of proprietary AI tools is an important inflection point in the company's commercialization timeline."

AI in Healthcare

On October 10, Microsoft emphasized the importance of multimodal AI models for a comprehensive assessment of patient health. The report highlighted the growing importance of using AI to analyze complex, multimodal health data, such as medical imaging, genomics, and clinical records. The integration of these data sources has enabled more precise diagnostics and treatment planning, illustrating the sector's move toward comprehensive AI applications. The healthcare industry has faced challenges like the need for large-scale, integrated datasets and significant computational resources, but advancements have begun to bridge these gaps. Microsoft noted that these developments would help unlock new insights and improve patient care by accelerating innovation and enhancing clinical decision-making across the sector.

On November 4, Forbes reported that AI-powered healthcare tools were no longer merely experimental but were instead delivering real value across the industry. Examples included enhanced diagnostic accuracy through AI algorithms, like those developed by Google Cloud Healthcare, and improved administrative processes through platforms like Cedar's AI-powered billing system. Forbes noted that these developments were reshaping patient care and reducing administrative burdens, offering measurable benefits.

Also, on November 4, Tech Target highlighted the optimism among healthcare professionals regarding generative AI's potential to alleviate administrative burdens. Over 90% of healthcare workers surveyed expressed confidence in generative AI's ability to simplify tasks like prior authorizations and nurse handoff reports. Aashima Gupta from Google Cloud shared insights on these tools' transformative capabilities, while Tony Farah from Highmark Health cited an 85% reduction in provider administrative costs after automating prior authorizations. Helen Waters from Meditech added, "We believe that gen AI and AI overall is transforming how healthcare professionals access and use information to make powerful decisions confidently," reflecting the positive impact of AI tools on healthcare workflows and decision-making.

Company Catalysts

Treatment.com AI Inc. continues to evolve its medical education platform, incorporating advanced AI technologies that could help revolutionize medical education and training. The company is leveraging its Global Library of Medicine, which offers over 10,000 medical reviews and covers more than 1,000 diseases and associated symptoms. These AI-driven tools aim to enhance clinical decision-making while reducing administrative burdens for healthcare institutions.

The updated MES is projected to impact medical training through its comprehensive and AI-enhanced features, as outlined in Treatment's investor presentation. The presentation details the significant market potential, with the AI healthcare market expected to grow from US$11 billion in 2021 to US$187 billion by 2030, according to Statista. In addition to Treatment's announced new functionality, the company has already begun work on further solutions such as AI Doctor in a Pocket and audio/video analysis tools for clinical scoring and diagnostics. The goal of this expanded portfolio is to position the company to help expedite its aggressive growth plans over the next year.

Analysis of Treatment.com AI

Ownership and Share Structure

According to Sedi.ca, insiders own approximately 8% of Treatment.com AI. Retail investors own the remaining 92%. 

The company has 48.99 million outstanding common shares and has 41.3 million free float traded shares.

As of November 4, the market cap is approximately CA$31.35 million. Over the past 52 weeks, the company traded between CA$0.355 and CA$1.11 per share.

¹Source bodies including: https://www.aamc.org/; https://www.uems.eu/; https://www.nmc.org.in/; Education – GMC (gmc-uk.org)

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Important Disclosures:

1. Treatment.com AI has a consulting relationship with Street Smart an affiliate of Streetwise Reports. Street Smart Clients pay a monthly consulting fee between US$8,000 and US$20,000.
2. As of the date of this article, officers and/or employees of Streetwise Reports LLC (including members of their household) own securities of Treatment.com AI.
3. James Guttman wrote this article for Streetwise Reports LLC and provides services to Streetwise Reports as an employee.
4. This article does not constitute investment advice and is not a solicitation for any investment. Streetwise Reports does not render general or specific investment advice and the information on Streetwise Reports should not be considered a recommendation to buy or sell any security. Each reader is encouraged to consult with his or her personal financial adviser and perform their own comprehensive investment research. By opening this page, each reader accepts and agrees to Streetwise Reports' terms of use and full legal disclaimer. Streetwise Reports does not endorse or recommend the business, products, services or securities of any company.
5. This article does not constitute medical advice. Officers, employees and contributors to Streetwise Reports are not licensed medical professionals. Readers should always contact their healthcare professionals for medical advice.

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* Disclosure for the quote from the Clive Maund article published on [Date]

1. For the quoted article (published on [Date]), the Company has paid Street Smart, an affiliate of Streetwise Reports, between US$1,500 and US$2,500.
2. Author Certification and Compensation: [Clive Maund of clivemaund.com] is being compensated as an independent contractor by Street Smart, an affiliate of Streetwise Reports, for writing the article quoted. Maund received his UK Technical Analysts’ Diploma in 1989. The recommendations and opinions expressed in the article accurately reflect the personal, independent, and objective views of the author regarding any and all of the designated securities discussed. No part of the compensation received by the author was, is, or will be directly or indirectly related to the specific recommendations or views expressed

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The quoted article represents the opinion and analysis of Mr. Maund, based on data available to him, at the time of writing. Mr. Maund's opinions are his own, and are not a recommendation or an offer to buy or sell securities. As trading and investing in any financial markets may involve serious risk of loss, Mr. Maund recommends that you consult with a qualified investment advisor, one licensed by appropriate regulatory agencies in your legal jurisdiction and do your own due diligence and research when making any kind of a transaction with financial ramifications. Although a qualified and experienced stock market analyst, Clive Maund is not a Registered Securities Advisor. Therefore Mr. Maund's opinions on the market and stocks cannot be only be construed as a recommendation or solicitation to buy and sell securities.

¹Source bodies including: https://www.aamc.org/; https://www.uems.eu/; https://www.nmc.org.in/; Education – GMC (gmc-uk.org)

( Companies Mentioned: TRUE:CSE; TREIF:OTCMKTS;939:FRA, )

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