Characterization of a material structure with pair distribution function (PDF) analysis typically involves refining a structure model against an experimental data set, but finding or constructing a suitable atomic model for PDF modelling can be an extremely labour-intensive task, requiring carefully browsing through large numbers of possible models. Presented here is POMFinder, a machine learning (ML) classifier that rapidly screens a database of structures, here polyoxometallate (POM) clusters, to identify candidate structures for PDF data modelling. The approach is shown to identify suitable POMs from experimental data, including in situ data collected with fast acquisition times. This automated approach has significant potential for identifying suitable models for structure refinement to extract quantitative structural parameters in materials chemistry research. POMFinder is open source and user friendly, making it accessible to those without prior ML knowledge. It is also demonstrated that POMFinder offers a promising modelling framework for combined modelling of multiple scattering techniques.

Low-energy electron diffraction patterns contain precise information about the structure of the surface studied. However, retrieving the real space lattice periodicity from complex diffraction patterns is challenging, especially when the modeled patterns originate from superlattices with large unit cells composed of several symmetry-equivalent domains without a simple relation to the substrate. This work presents ProLEED Studio software, built to provide simple, intuitive and precise modeling of low-energy electron diffraction patterns. The interactive graphical user interface allows real-time modeling of experimental diffraction patterns, change of depicted diffraction spot intensities, visualization of different diffraction domains, and manipulation of any lattice points or diffraction spots. The visualization of unit cells, lattice vectors, grids and scale bars as well as the possibility of exporting ready-to-publish models in bitmap and vector formats significantly simplifies the modeling process and publishing of results.

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

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. For verification, several DLSIA-instantiated networks and training scripts are employed in multiple applications, including inpainting for X-ray scattering data using U-Nets and MSDNets, segmenting 3D fibers in X-ray tomographic reconstructions of concrete using an ensemble of SMSNets, and leveraging autoencoder latent spaces for data compression and clustering. As experimental data continue to grow in scale and complexity, DLSIA provides accessible CNN construction and abstracts CNN complexities, allowing scientists to tailor their machine learning approaches, accelerate discoveries, foster interdisciplinary collaboration and advance research in scientific image analysis.

Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as `hit' and `miss', respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers.

This work presents observations of symmetry breakages in the intensity distributions of near-zone-axis convergent-beam electron diffraction (CBED) patterns that can only be explained by the symmetry of the specimen and not the symmetry of the unit cell describing the atomic structure of the material. The specimen is an aluminium–copper–tin alloy containing voids many tens of nanometres in size within continuous single crystals of the aluminium host matrix. Several CBED patterns where the incident beam enters and exits parallel void facets without the incident beam being perpendicular to these facets are examined. The symmetries in their intensity distributions are explained by the specimen morphology alone using a geometric argument based on the multislice theory. This work shows that it is possible to deduce nanoscale morphological information about the specimen in the direction of the electron beam – the elusive third dimension in transmission electron microscopy – from the inspection of CBED patterns.

X-ray Laue microdiffraction aims to characterize microstructural and mechanical fields in polycrystalline specimens at the sub-micrometre scale with a strain resolution of ∼10−4. Here, a new and unique Laue microdiffraction setup and alignment procedure is presented, allowing measurements at temperatures as high as 1500 K, with the objective to extend the technique for the study of crystalline phase transitions and associated strain-field evolution that occur at high temperatures. A method is provided to measure the real temperature encountered by the specimen, which can be critical for precise phase-transition studies, as well as a strategy to calibrate the setup geometry to account for the sample and furnace dilation using a standard α-alumina single crystal. A first application to phase transitions in a polycrystalline specimen of pure zirconia is provided as an illustrative example.

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.

Macromolecular crystallography contributes significantly to understanding diseases and, more importantly, how to treat them by providing atomic resolution 3D structures of proteins. This is achieved by collecting X-ray diffraction images of protein crystals from important biological pathways. Spotfinders are used to detect the presence of crystals with usable data, and the spots from such crystals are the primary data used to solve the relevant structures. Having fast and accurate spot finding is essential, but recent advances in synchrotron beamlines used to generate X-ray diffraction images have brought us to the limits of what the best existing spotfinders can do. This bottleneck must be removed so spotfinder software can keep pace with the X-ray beamline hardware improvements and be able to see the weak or diffuse spots required to solve the most challenging problems encountered when working with diffraction images. In this paper, we first present Bragg Spot Detection (BSD), a large benchmark Bragg spot image dataset that contains 304 images with more than 66 000 spots. We then discuss the open source extensible U-Net-based spotfinder Bragg Spot Finder (BSF), with image pre-processing, a U-Net segmentation backbone, and post-processing that includes artifact removal and watershed segmentation. Finally, we perform experiments on the BSD benchmark and obtain results that are (in terms of accuracy) comparable to or better than those obtained with two popular spotfinder software packages (Dozor and DIALS), demonstrating that this is an appropriate framework to support future extensions and improvements.

A deep-learning algorithm is proposed for the inpainting of Bragg coherent diffraction imaging (BCDI) patterns affected by detector gaps. These regions of missing intensity can compromise the accuracy of reconstruction algorithms, inducing artefacts in the final result. It is thus desirable to restore the intensity in these regions in order to ensure more reliable reconstructions. The key aspect of the method lies in the choice of training the neural network with cropped sections of diffraction data and subsequently patching the predictions generated by the model along the gap, thus completing the full diffraction peak. This approach enables access to a greater amount of experimental data for training and offers the ability to average overlapping sections during patching. As a result, it produces robust and dependable predictions for experimental data arrays of any size. It is shown that the method is able to remove gap-induced artefacts on the reconstructed objects for both simulated and experimental data, which becomes essential in the case of high-resolution BCDI experiments.

Using the well known Rn ratio method, a protocol has been elaborated for determining the lattice direction for the 15 most common cubic zone axis spot patterns. The method makes use of the lengths of the three shortest reciprocal-lattice vectors in each pattern and the angles between them. No prior pattern calibration is required for the method to work, as the Rn ratio method is based entirely on geometric relationships. In the first step the pattern is assigned to one of three possible pattern types according to the angles that are measured between the three reciprocal-lattice vectors. The lattice direction [uvw] and possible Bravais type(s) and Laue indices of the corresponding reflections can then be determined by using lookup tables. In addition to determining the lattice direction, this simple geometric analysis allows one to distinguish between the P, I and F Bravais lattices for spot patterns aligned along [013], [112], [114] and [233]. Moreover, the F lattice can always be uniquely identified from the [011] and [123] patterns.

Small-angle X-ray and neutron scattering (SAXS and SANS) patterns from certain semicrystalline polymers and liquid crystals contain discrete reflections from ordered assemblies and central diffuse scattering (CDS) from uncorrelated structures. Systems with imperfectly ordered lamellar structures aligned by stretching or by a magnetic field produce four distinct SAXS patterns: two-point `banana', four-point pattern, four-point `eyebrow' and four-point `butterfly'. The peak intensities of the reflections lie not on a layer line, or the arc of a circle, but on an elliptical trajectory. Modeling shows that randomly placed lamellar stacks modified by chain slip and stack rotation or interlamellar shear can create these forms. On deformation, the isotropic CDS becomes an equatorial streak with an oval, diamond or two-bladed propeller shape, which can be analyzed by separation into isotropic and oriented components. The streak has elliptical intensity contours, a natural consequence of the imperfect alignment of the elongated scattering objects. Both equatorial streaks and two- and four-point reflections can be fitted in elliptical coordinates with relatively few parameters. Equatorial streaks can be analyzed to obtain the size and orientation of voids, fibrils or surfaces. Analyses of the lamellar reflection yield lamellar spacing, stack orientation (interlamellar shear) angle α and chain slip angle ϕ, as well as the size distribution of the lamellar stacks. Currently available computational tools allow these microstructural parameters to be rapidly refined.

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics (e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Ptychography is a powerful computational imaging technique with microscopic imaging capability and adaptability to various specimens. To obtain an imaging result, it requires a phase-retrieval algorithm whose performance directly determines the imaging quality. Recently, deep neural network (DNN)-based phase retrieval has been proposed to improve the imaging quality from the ordinary model-based iterative algorithms. However, the DNN-based methods have some limitations because of the sensitivity to changes in experimental conditions and the difficulty of collecting enough measured specimen images for training the DNN. To overcome these limitations, a ptychographic phase-retrieval algorithm that combines model-based and DNN-based approaches is proposed. This method exploits a DNN-based denoiser to assist an iterative algorithm like ePIE in finding better reconstruction images. This combination of DNN and iterative algorithms allows the measurement model to be explicitly incorporated into the DNN-based approach, improving its robustness to changes in experimental conditions. Furthermore, to circumvent the difficulty of collecting the training data, it is proposed that the DNN-based denoiser be trained without using actual measured specimen images but using a formula-driven supervised approach that systemically generates synthetic images. In experiments using simulation based on a hard X-ray ptychographic measurement system, the imaging capability of the proposed method was evaluated by comparing it with ePIE and rPIE. These results demonstrated that the proposed method was able to reconstruct higher-spatial-resolution images with half the number of iterations required by ePIE and rPIE, even for data with low illumination intensity. Also, the proposed method was shown to be robust to its hyperparameters. In addition, the proposed method was applied to ptychographic datasets of a Simens star chart and ink toner particles measured at SPring-8 BL24XU, which confirmed that it can successfully reconstruct images from measurement scans with a lower overlap ratio of the illumination regions than is required by ePIE and rPIE.

In synchrotron X-ray radiography, achieving high image resolution and an optimal signal-to-noise ratio (SNR) is crucial for the subsequent accurate image analysis. Traditional methods often struggle to balance these two parameters, especially in situ applications where rapid data acquisition is essential to capture specific dynamic processes. For quantitative image data analysis, using monochromatic X-rays is essential. A double multilayer monochromator (DMM) is successfully used for this aim at the BAMline, BESSY II (Helmholtz Zentrum Berlin, Germany). However, such DMMs are prone to producing an unstable horizontal stripe pattern. Such an unstable pattern renders proper signal normalization difficult and thereby causes a reduction of the SNR. We introduce a novel approach to enhance SNR while preserving resolution: dynamic tilting of the DMM. By adjusting the orientation of the DMM during the acquisition of radiographic projections, we optimize the X-ray imaging quality, thereby enhancing the SNR. The corresponding shift of the projection during this movement is corrected in post-processing. The latter correction allows a good resolution to be preserved. This dynamic tilting technique enables the homogenization of the beam profile and thereby effectively reduces noise while maintaining high resolution. We demonstrate that data captured using this proposed technique can be seamlessly integrated into the existing radiographic data workflow, as it does not need hardware modifications to classical X-ray imaging beamline setups. This facilitates further image analysis and processing using established methods.

The UAE has announced the introduction of 'Palm ID' technology, a payment solution that utilises the unique vein patterns in individuals' palms for...

Klarna has secured a deal to offload BNPL loans that it...

Source: Scott Searle 11/08/2024

In line-to-better than expected financial results are good enough pre-launch of the satellite broadband solution, expected in Q4/24, noted a Roth MKM report.

Gogo Inc. (GOGO:NASDAQ) reported its Q3/24 financial results, and they slightly exceeded expectations, reported Scott Searle, managing director at Roth MKM, in a Nov. 5 research note.

The company provides in-flight connectivity services to business aviation markets through its North American terrestrial air-to-ground network.

137% Potential Return

Roth maintained its target price of US$15.50 per share on Gogo, noted Searle.

"We believe this provides a reasonable 12-plus-month target given the expected impact from two major new product cycles as we enter 2025," he wrote, referring to Galileo, the company's global inflight broadband service, and its 5G product line.

In comparison, the company's share price at the time of the report was about US$6.55 per share. From this price, the return to target reflects 137% upside.

Gogo remains a Buy.

Quarter's Highlights

Searle reported that Gogo's Q3/24 service revenue was a beat. At US$81.9 million (US$81.9M), it was slightly higher than that in Q2/24 and driven by modestly better-than-expected aircraft online, Searle reported. This revenue exceeded Roth's estimate by about US$300,000.

Also of note, Galileo is on track to launch in Q4/24, and Gogo continues to grow its portfolio of supplemental type certificates and partners around the world.

A Look Ahead

Gogo's outlook for 2024 of US$400-410M encompasses consensus' estimate, noted Searle. The company, though, has "pulled long-term guidance ahead of the Satcom Direct [acquisition] closing."

Roth expects Galileo and 5G will lead recovery, expected in late 2025.

In other news, noted Searle, Gogo Chairman and Chief Executive Officer Oakleigh Thorne will present at Roth's NYC Tech Event on Nov. 20.

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Important Disclosures:

1. Doresa Banning wrote this article for Streetwise Reports LLC and provides services to Streetwise Reports as an independent contractor.
2. 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.

For additional disclosures, please click here.

Disclosures for Roth MKM, Gogo Inc., November 5, 2024

Regulation Analyst Certification ("Reg AC"): The research analyst primarily responsible for the content of this report certifies the following under Reg AC: I hereby certify that all views expressed in this report accurately reflect my personal views about the subject company or companies and its or their securities. I also certify that no part of my compensation was, is or will be, directly or indirectly, related to the specific recommendations or views expressed in this report.

Disclosures: ROTH makes a market in shares of Gogo, Inc. and as such, buys and sells from customers on a principal basis.

ROTH Capital Partners, LLC expects to receive or intends to seek compensation for investment banking or other business relationships with the covered companies mentioned in this report in the next three months. The material, information and facts discussed in this report other than the information regarding ROTH Capital Partners, LLC and its affiliates, are from sources believed to be reliable, but are in no way guaranteed to be complete or accurate. This report should not be used as a complete analysis of the company, industry or security discussed in the report. Additional information is available upon request. This is not, however, an offer or solicitation of the securities discussed. Any opinions or estimates in this report are subject to change without notice. An investment in the stock may involve risks and uncertainties that could cause actual results to differ materially from the forward-looking statements. Additionally, an investment in the stock may involve a high degree of risk and may not be suitable for all investors. No part of this report may be reproduced in any form without the express written permission of ROTH. Copyright 2024. Member: FINRA/SIPC.

( Companies Mentioned: GOGO:NASDAQ, )

Graphic novelist and artist Charles Burns, at the Mohn Broadcast Center, 9/18/2014. He's just completed his trilogy with the new book Sugar Skull.; Credit: John Rabe

Graphic novelist Charles Burns stopped by the Mohn Broadcast Center to talk with Off-Ramp host John Rabe about "Sugar Skull," which completes the trilogy that includes "X'ed Out" and "The Hive."  He's doing a signing tonight (Thurday, Sept. 18) at Skylight Books, 1818 N. Vermont Avenue in Los Feliz.

Why the trilogy? Burns says, "I had finished another book, "Black Hole," which was this very long graphic novel, all in black and white, and I wanted to do something in color, so I conceived a series of books, based on a series of my life, late '70s, the Punk Era. It started that way, and then it turned into something else."

RELATED: Miniaturist Alan Wolfson, or "Honey! I shrunk the strip club!"

The look of Burns' books:

... is drawn from one of his childhood favorites, the Belgian Tintin, who had all sorts of politically incorrect adventures:

"It's called the clear-line school of comics. And it's exactly what it sounds like: very clear lines, but perfectly rendered in color."

If there's more shadow in Burns' books than in Herge's, that's because the lines between good and bad, dark and light, reality and unreality are blurrier in Burns. The trilogy moves back and forth in time and place, including between the normal world and a bizarre world in which a character named Johnny 23 struggles with many of the same issues the protagonist in the real world, Doug, faces... including a pregnant girlfriend.

(From Sugar Skull, by Charles Burns. )

Are they two separate stories or Doug's subconscious world? Burns won't say. "That's for the reader to figure out. I don't really ever clearly explain those things at all, and I like to leave those things open. Interpretation is great, as far as I'm concerned."

Burns turns 59 on Sept. 27. How does he like approaching 60? "As far as the day-to-day landscape, things are more settled in. But as far as my sweltering, swelling, itching brain, that hasn't changed at all unfortunately."

Source: Streetwise Reports 10/18/2024

Aero Energy Ltd. (AERO:TSXV; AAUGF:OTC; UU3:FRA) has announced significant advancements at its Murmac and Sun Dog uranium projects in Northern Saskatchewan. Read how this and a CA$2.5-million non-brokered private placement aim the company towards further exploration.

Aero Energy Ltd. (AERO:TSXV; AAUGF:OTC; UU3:FRA) has announced significant advancements at its Murmac and Sun Dog uranium projects in Northern Saskatchewan, with the first drill program revealing high-grade uranium potential. Situated near Uranium City on the Athabasca Basin's northern margin, the projects aim to capitalize on basement-hosted uranium deposits similar to high-grade discoveries in the region.

The initial drill campaign completed 16 holes, targeting 12 key areas, with 12 holes yielding anomalous radioactivity. A major highlight is the new high-grade uranium discovery in drill hole M24-017, which intersected 8.4 meters of mineralization at 0.3% U3O8, including assays peaking at 13.8% U3O8 at just 64 meters below surface. The results confirm Aero's exploration model, which focuses on basement-hosted deposits within graphitic structures, a common feature in Athabasca Basin uranium deposits like Arrow and Triple R.

"From the launch of the company in January, we took a very diligent yet aggressive approach to discovery," stated Galen McNamara, CEO of Aero Energy. "The combination of historical data and the results from the first drill program serve as evidence that basement-hosted mineralization akin to the large deposits beneath and adjacent to the Athabasca Basin is present in the area."

The Murmac project spans 25,607 acres and holds a production legacy of approximately 70 million pounds of U3O8. Similarly, the 48,443-acre Sun Dog property hosts the historic Gunnar uranium mine, which once held the title of the world's largest uranium producer. Past exploration focused on fault-hosted mineralization, missing the basement-hosted uranium potential that Aero's recent findings have validated.

Recent exploration efforts included a VTEM Plus survey, flown over 3,350 kilometers, identifying graphite-rich rocks that support Aero's exploration thesis. Additionally, two new occurrences of strong radioactivity were identified at surface-level scout locations: Target A15 showed 60,793 counts per second, and Target P4 displayed 13,533 counts per second. Summer 2024 drilling included 1,550 meters at Murmac and 1,600 meters at Sun Dog, highlighting shallow, high-grade potential in both areas.

In parallel, Aero Energy has announced a CA$2.5 million non-brokered private placement to support further exploration. The proceeds from flow-through units will fund work programs across Murmac, Sun Dog, and the Strike property, with the remaining funds allocated to general working capital.

Why Uranium?

The uranium sector has recently experienced strong growth, largely driven by increasing global demand and efforts to diversify from Russian supply chains. On September 30, The New York Times discussed the resurgence in Western uranium production, highlighting that "uranium mines are ramping up across the West, spurred by rising demand for electricity and federal efforts to cut Russia out of the supply chain." Aero Energy's recent discoveries and forthcoming winter drilling plans at Murmac and Sun Dog reflect this trend, with CEO Galen McNamara remarking, "The combination of historical data and the results from the first drill program serve as evidence that basement-hosted mineralization . . . is present in the area," suggesting strong potential for the Canadian uranium market to contribute to non-Russian nuclear fuel supplies.

Jeff Clark of The Gold Advisor highlighted his continued confidence in the company by stating, "I remain overweight the stock."

On October 9, Reuters reported that demand from U.S. buyers has been on the rise, as "a strong rise in demand from its U.S. customers" pushed Orano's recent plans to expand uranium enrichment in the United States and France. This shift underscores Aero Energy's recent investments in Northern Saskatchewan, where the company has identified high-grade uranium mineralization in both the Murmac and Sun Dog projects, aiming to meet future supply demands with a focus on basement-hosted deposits.

As Forbes reported on October 11, the uranium market experienced renewed momentum after Russian President Vladimir Putin hinted at the possibility of a ban on uranium exports to Western nations. This suggestion "jolted the uranium market," which had been declining after peaking earlier in the year. The price of uranium rebounded to US$83.50 per pound, reflecting rising concerns about potential supply disruptions. Citi analysts noted that “Russia supplies close to 12% of U3O8, 25% of UF6, and 35% of EUP to international markets,” underscoring the challenges that Western nations, particularly the U.S. and Europe, could face in replacing these critical materials. This market dynamic positions uranium companies operating outside of Russia, like those in the Athabasca Basin, to benefit from supply gaps and heightened demand.

MSN reported on October 13 that the UK's nuclear power capacity is set to decrease dramatically in the coming years, with the planned closure of four out of five remaining nuclear plants by 2028. This reduction in capacity is expected to increase pressure on global uranium supplies as demand for nuclear energy continues to rise amid efforts to meet climate goals. The ongoing shift toward low-carbon energy sources, coupled with the planned closures, could create further supply constraints and drive demand for uranium from alternative sources.

Aero's Catalysts

According to the company's October 2024 investor presentation, the ongoing development at Murmac and Sun Dog highlights Aero Energy's strategy to enhance shareholder value by targeting high-grade uranium deposits in underexplored regions. Aero has leveraged recent technology investments, including VTEM Plus aerial surveys, which identified graphite-rich formations favorable for uranium. The exploration efforts build on the CA$7.6 million previously invested by project partners Fortune Bay and Standard Uranium, which has contributed to refining the drill targets. As Aero works with its partners to maximize the impact of this winter's drilling program, the company's strategic location on the north rim of the Athabasca Basin positions it well to expand these discoveries and attract continued investor interest.

The recently announced CA$2.5 million private placement will further strengthen Aero's financial capacity to carry out its targeted drill campaigns and exploration work.

Analyzing Aero

Jeff Clark of The Gold Advisor, in his October 17 update, noted that Aero Energy has "identified more than 70 kilometers of strike to test for high-grade basement-hosted uranium," emphasizing the company's significant exploration potential in a region known for some of the world's richest uranium deposits.

Clark further commented on Aero Energy's recent results, underscoring the importance of drill hole M24-017, which intersected 8.4 meters of uranium mineralization, grading 0.3% U3O8, with assays reaching as high as 13.8% U3O8. He stated, "While not a discovery hole, per se, this hole underscores the company's thesis that these two projects are prospective for the same type of uranium mineralization as Arrow and Triple R." This observation reinforces Aero Energy's exploration model, which targets basement-hosted uranium deposits similar to those found at other significant Athabasca Basin discoveries. [OWNERSHIP_CHART-11173]

Additionally, Clark expressed optimism regarding Aero Energy's current valuation and future prospects, recommending it as a strong buy at current levels. He highlighted his continued confidence in the company by stating, "I remain overweight the stock," suggesting that Aero Energy presents a compelling opportunity for speculative investors in the uranium exploration space.

The recently announced CA$2.5 million private placement was also acknowledged by Clark as a necessary step to fund further exploration activities. While he expressed some caution about potential dilution, he affirmed his overall support for the financing, noting that "its projects are very much worthy of follow-up."

Ownership and Share Structure

According to Refinitiv, management and insiders own 3.11% of Aero Energy. Of those, CEO Galen McNamara has the most at 2.97%. Institutions owns 4.79% with MMCAP Asset Management holding 3.89%. The rest is retail.

Aero has 92.3 million free float shares and a market cap of CA$4.5 million. The 52 week range is CA$0.040–$0.26.

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Important Disclosures:

1) James Guttman wrote this article for Streetwise Reports LLC and provides services to Streetwise Reports as an employee.

2) 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.

For additional disclosures, please click here.

( Companies Mentioned: AERO:TSXV;AAUGF:OTC;UU3:FRA, )

Source: Streetwise Reports 10/24/2024

Skyharbour Resources Ltd. (SYH:TSX.V; SYHBF:OTCQX; SC1P:FSE) has completed its earn-in requirements for a 51% interest at the Russell Lake Uranium Project in the central core of Canada's Eastern Athabasca Basin in Saskatchewan. This comes as the need for more net-zero power is sparking a rebirth of the nuclear industry.

Skyharbour Resources Ltd. (SYH:TSX.V; SYHBF:OTCQX; SC1P:FSE) announced that it has completed its earn-in requirements for a 51% interest at its co-flagship Russell Lake Uranium Project in the central core of Canada's Eastern Athabasca Basin in Saskatchewan.

The company and Rio Tinto have formed a joint venture (JV) to further explore the property, with Skyharbour holding 51% ownership interest and Rio Tinto holding 49%.

This summer, Skyharbour announced that in the first phase of drilling it had found what was historically the best uranium intercept mineralization at the project when hole RSL24-02 at the recently identified Fork Target returned a 2.5-meter-wide intercept of 0.721% U3O8 at a relatively shallow depth of 338.1 meters, including 2.99% U3O8 over 0.5 meters at 339.6 meters.

The second phase of drilling included three holes totaling 1,649 meters, with emphasis "at the MZE (M-Zone Extension) target, approximately 10 km northeast of the Fork target, identified prospective faulted graphitic gneiss accompanied by anomalous sandstone and basement geochemistry," Skyharbour said.

"The discovery of multi-percent, high-grade, sandstone-hosted uranium mineralization at a new target is a major breakthrough in the discovery process at Russell — something that hasn't been seen before at the project with the potential to quickly grow with more drilling," President and Chief Executive Officer Jordan Trimble said at the time.

ANT Survey, Upcoming Drilling Program

The company also announced on Thursday that it had completed an Ambient Noise Tomography (ANT) survey in preparation for further drilling at the Russell Lake Project, set to commence in the fall. The survey used Fleet Space Technologies' Exosphere technology to acquire 3D passive seismic velocity data over the highly prospective Grayling and Fork target areas, where previous drilling has intersected high-grade uranium mineralization.

"The ANT technology has been successfully employed in mapping significant sandstone and basement structures and associated alteration zones related to hydrothermal fluids pathways in the Athabasca Basin," the company said.

Results from the survey will be used to further refine drill targets for the upcoming drilling program. Skyharbour is fully funded and permitted for the follow-up fall drill campaign consisting of approximately 7,000 metres of drilling at its main Russell and Moore Projects, with 2,500 meters of drilling at Moore and 4,500 meters of drilling at Russell.

A Great Neighborhood

Russell Lake is a large, advanced-stage uranium exploration property totaling 73,294 hectares strategically located between Cameco's Key Lake and McArthur River projects and Denison's Wheeler River Project to the west, and Skyharbour's Moore project to the east.

"Skyharbour's acquisition of a majority interest in Russell Lake creates a large, nearly contiguous block of highly prospective uranium claims totaling 108,999 hectares between the Russell Lake and the Moore uranium projects," the company said.

Most of the historical exploration at Russell Lake was conducted before 2010, prior to the discovery of several major deposits in/around the Athabasca Basin, Skyharbour said.

Notable exploration targets on the property include the Grayling Zone, the M-Zone Extension target, the Little Man Lake target, the Christie Lake target, the Fox Lake Trail target and the newly identified Fork Zone target.

"More than 35 kilometers of largely untested prospective conductors in areas of low magnetic intensity also exist on the property," the company noted.

In an updated research note in July, Analyst Sid Rajeev of Fundamental Research Corp. wrote that Skyharbour "owns one of the largest portfolios among uranium juniors in the Athabasca Basin."

"Given the highly vulnerable uranium supply chain, we anticipate continued consolidation within the sector," wrote Rajeev, who rated the stock a Buy with a fair value estimate of CA$1.21 per share. "Additionally, the rapidly growing demand for energy from the AI (artificial intelligence) industry is likely to accelerate the adoption of nuclear power, which should, in turn, spotlight uranium juniors in the coming months."

The Catalyst: Uranium is 'BACK!'

The growth of AI, new data centers, electric vehicle (EV) adoption, and the need for more net-zero power means more nuclear energy and the uranium needed to fuel it.

Uranium prices are expected to move higher by the end of this quarter, when Trading Economics' global macro models and analyses forecast uranium to trade at US$84.15 per pound, Nuclear Newswire reported on Oct. 3. In another year, the site estimates that the metal will trade at US$91.80 per pound.

Just last month, Microsoft Corp. (MSFT:NASDAQ) announced a deal with Constellation Energy Group (CEG:NYSE) to restart and buy all of the power from one of the shut-down reactors at its infamous Three Mile Island plant in Pennsylvania and the Biden administration also announced a plan to restart the Palisades plant in Michigan.

Chris Temple, publisher of The National Investor, recently noted that with the Three Mile Island deal, "uranium/nuclear power is BACK!"[OWNERSHIP_CHART-6026]

"I've watched as the news has continued to point to uranium being in the early innings of this new bull market," Temple wrote. "Yet the markets have been yawning . . . until now."

Ownership and Share Structure

Management, insiders, and close business associates own approximately 5% of Skyharbour.

According to Reuters, President and CEO Trimble owns 1.6%, and Director David Cates owns 0.70%.

Institutional, corporate, and strategic investors own approximately 55% of the company. Denison Mines owns 6.3%, Rio Tinto owns 2.0%, Extract Advisors LLC owns 9%, Alps Advisors Inc. owns 9.91%, Mirae Asset Global Investments (U.S.A) L.L.C. owns 6.29%, Sprott Asset Management L.P. owns 1.5%, and Incrementum AG owns 1.18%, Reuters reported.

There are 182.53 million shares outstanding with 178 million free float traded shares, while the company has a market cap of CA$88.53 million and trades in a 52-week range of CA$0.31 and CA$0.64.

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Important Disclosures:

1. Skyharbour Resources Ltd. is a billboard sponsor of Streetwise Reports and pays SWR a monthly sponsorship fee between US$4,000 and US$5,000.
2. Steve Sobek wrote this article for Streetwise Reports LLC and provides services to Streetwise Reports as an employee.
3. 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.

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( Companies Mentioned: SYH:TSX.V; SYHBF:OTCQX; SC1P:FSE, )

Brad and George Takei, the new typical American married couple.; Credit: John Rabe/Grant Wood/Michael Uhlenkott

John Rabe | Off-Ramp®

UPDATE: “Allegiance” will be performed Feb. 21-April 1, 2018, at the Aratani Theater at the Japanese Cultural and Community Center in downtown L.A.'s Little Tokyo.

ORIGINAL STORY: In an intimate interview, George Takei tells Off-Ramp host John Rabe about crafting the Japanese-American internment camp history into compelling Broadway musical theater. "Allegiance," with Takei, Lea Salonga and Telly Leung, played at the Longacre Theater.

George Takei and his husband Brad were putting their house in mothballs when I arrived for our interview in August. They'd already been spending a lot of time in New York because of George's recurring role on "The Howard Stern Show," but now, with the Broadway opening of "Allegiance" just a couple months away, they were preparing to move for as long as the musical brings in the crowds.

While Brad went off to deal with the mundane domestic tasks around the move, I sat with George in their living room to talk about turning one of America's most shameful episodes — the internment of some 120,000 loyal Japanese-Americans during World War II — into a musical that could make it on the Broadway stage.

George, you just sent an email to your fans with the subject line: "I've Waited 7 Years to Send You this Email. Seven years!" Inside, you wrote: "Few things are as difficult and complex as taking a show to ‪Broadway‬. It's both thrilling and terrifying." What was terrifying?

"The terrifying part is, you've poured your passion, your energy, your resources ...  you make all that investment in that project, and then you're hoping the seats are going to be filled.That 'what if' is terrifying. But in San Diego, we had a sold-out run and broke their 77-year record. But now we're going to Broadway, and that same fear is there. Will they come? What will the critics say? Because it's life or death."

It took a long time just to get a Broadway theater.

"It took a long time to get a theater.You think there are a lot of Broadway theaters, but there are even more productions that want those chunks of New York real estate. So we thought we'd get in line. But then the other discovery we made is that the theater owners have relationships with grizzled old producers who have brought them a vast fortune with enormous hits, and they can cut in line. They have a track record. And so, 'will we ever get a theater' became a big question. But we have this time now — let's use it creatively, productively."

So, Takei says, the team tweaked the show, removing parts that didn't work didn't advance the story, inserting numbers that worked better and kept the story moving. They doubled down on social media, building and proving demand in the show.

"We have a Shubert theater (the Longacre), and Bob Wankel is head guy there, and I remember pouring my heart out, telling the story of my parents, hoping that touches. And he was understanding, but I understood his problem, too. Everybody is trying to get a theater and he has to make a good business decision and was initially skeptical. An internment camp musical? But music has the power to make an anguished painful situation even more moving, even more powerful. It hits you in the heart."

Highlights from "Allegiance" at the Old Globe in San Diego

This is your Broadway debut, right? Are you petrified?

"Yes, yes. I've done a lot of stage work, and I've done a lot of public speaking, but it's Broadway, and I'm a debutante... at 78 years old! And it's the critics, too. The New York Times, Ben Brantley. That's who I'm going to be facing, and so it's both exciting and absolutely filling me with ecstasy, but what makes it ecstatic is the fear."

For much more of our interview with George Takei, listen to the audio by clicking the arrow in the player at the top of the page ... and hear George Takei and John Rabe's duet of "Tiny Bubbles."

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

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