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Machine learning ensembles combine multiple base models to produce a more accurate output. They can be applied to a range of machine learning problems, including anomaly detection. In this paper, we investigate how to maximize the composability and scalability of an FPGA-based streaming ensemble anomaly detector (fSEAD). To achieve this, we propose a flexible computing architecture consisting of multiple partially reconfigurable regions, pblocks, which each implement anomaly detectors. Our proof-of-concept design supports three state-of-the-art anomaly detection algorithms: Loda, RS-Hash and xStream. Each algorithm is scalable, meaning multiple instances can be placed within a pblock to improve performance. Moreover, fSEAD is implemented using High-level synthesis (HLS), meaning further custom anomaly detectors can be supported. Pblocks are interconnected via an AXI-switch, enabling them to be composed in an arbitrary fashion before combining and merging results at run-time to create an ensemble that maximizes the use of FPGA resources and accuracy. Through utilizing reconfigurable Dynamic Function eXchange (DFX), the detector can be modified at run-time to adapt to changing environmental conditions. We compare fSEAD to an equivalent central processing unit (CPU) implementation using four standard datasets, with speed-ups ranging from $3\times$ to $8\times$., Comment: The source code for this paper is available at: https://github.com/bingleilou/fSEAD

FPGAs have distinct advantages as a technology for deploying deep neural networks (DNNs) at the edge. Lookup Table (LUT) based networks, where neurons are directly modelled using LUTs, help maximize this promise of offering ultra-low latency and high area efficiency on FPGAs. Unfortunately, LUT resource usage scales exponentially with the number of inputs to the LUT, restricting PolyLUT to small LUT sizes. This work introduces PolyLUT-Add, a technique that enhances neuron connectivity by combining $A$ PolyLUT sub-neurons via addition to improve accuracy. Moreover, we describe a novel architecture to improve its scalability. We evaluated our implementation over the MNIST, Jet Substructure classification and Network Intrusion Detection benchmark and found that for similar accuracy, PolyLUT-Add achieves a LUT reduction of $1.3-7.7\times$ with a $1.2-2.2\times$ decrease in latency., Comment: To be published in the International Conference on Field-Programmable Logic and Applications (FPL) 2024

Scattering-type scanning near-field optical microscopy (s-SNOM) is a powerful technique for extreme subwavelength imaging and spectroscopy, with around 20 nm spatial resolution. But quantitative relationships between experiment and material properties requires modelling, which can be computationally and conceptually challenging. In this work, we present snompy an open-source Python library which contains implementations of two of the most common s-SNOM models, the finite dipole model (FDM) and the point dipole model (PDM). We show a series of typical uses for this package with demonstrations including simulating nano-Fourier transform infrared (FTIR) spectra and recovering permittivity from experimental s-SNOM data. We also discuss the challenges faced with this sort of modelling, such as competing descriptions of the models in literature, and finite size effects. We hope that snompy will make quantitative s-SNOM modelling more accessible to the wider research community, which will further empower the use of s-SNOM for investigating nanoscale material properties., Comment: 26 pages, 8 figures

The main science aim of the BlackGEM array is to detect optical counterparts to gravitational wave mergers. Additionally, the array will perform a set of synoptic surveys to detect Local Universe transients and short time-scale variability in stars and binaries, as well as a six-filter all-sky survey down to ~22nd mag. The BlackGEM Phase-I array consists of three optical wide-field unit telescopes. Each unit uses an f/5.5 modified Dall-Kirkham (Harmer-Wynne) design with a triplet corrector lens, and a 65cm primary mirror, coupled with a 110Mpix CCD detector, that provides an instantaneous field-of-view of 2.7~square degrees, sampled at 0.564\arcsec/pixel. The total field-of-view for the array is 8.2 square degrees. Each telescope is equipped with a six-slot filter wheel containing an optimised Sloan set (BG-u, BG-g, BG-r, BG-i, BG-z) and a wider-band 440-720 nm (BG-q) filter. Each unit telescope is independent from the others. Cloud-based data processing is done in real time, and includes a transient-detection routine as well as a full-source optimal-photometry module. BlackGEM has been installed at the ESO La Silla observatory as of October 2019. After a prolonged COVID-19 hiatus, science operations started on April 1, 2023 and will run for five years. Aside from its core scientific program, BlackGEM will give rise to a multitude of additional science cases in multi-colour time-domain astronomy, to the benefit of a variety of topics in astrophysics, such as infant supernovae, luminous red novae, asteroseismology of post-main-sequence objects, (ultracompact) binary stars, and the relation between gravitational wave counterparts and other classes of transients, Comment: 14 pages, submitted to Astronomy & Astrophysics

Societies worldwide have witnessed growing rifts separating advocates and opponents of vaccinations and other COVID-19 countermeasures. With the rollout of vaccination campaigns, German-speaking regions exhibited much lower vaccination uptake than other European regions. While Austria, Germany, and Switzerland (the DACH region) caught up over time, it remains unclear which factors contributed to these changes. Scrutinizing public discourses can help shed light on the intricacies of vaccine hesitancy and inform policy-makers tasked with making far-reaching decisions: policies need to effectively curb the spread of the virus while respecting fundamental civic liberties and minimizing undesired consequences. This study draws on Twitter data to analyze the topics prevalent in the public discourse. It further maps the topics to different phases of the pandemic and policy changes to identify potential drivers of change in public attention. We use a hybrid pipeline to detect and analyze vaccination-related tweets using topic modeling, sentiment analysis, and a minimum of social scientific domain knowledge to analyze the discourse about vaccinations in the light of the COVID-19 pandemic in the DACH region. We show that skepticism regarding the severity of the COVID-19 virus and towards efficacy and safety of vaccines were among the prevalent topics in the discourse on Twitter but that the most attention was given to debating the theme of freedom and civic liberties. Especially during later phases of the pandemic, when implemented policies restricted the freedom of unvaccinated citizens, increased vaccination uptake could be observed. At the same time, increasingly negative and polarized sentiments emerge in the discourse. This suggests that these policies might have effectively attenuated vaccination hesitancy but were not successfully dispersing citizens' doubts and concerns., Comment: 34 pages, 9 figures

We report on the implementation of quantum entanglement distribution and quantum state teleportation over a 14.4-km urban dark-fiber link, which is partially underground, partially overhead, and patched in several stations. We characterize the link for its use as a quantum channel and realize its active polarization stabilization. Using a type-II cavity-enhanced SPDC photon pair source, a $^{40}$Ca$^{+}$ single-ion quantum memory, and quantum frequency conversion to the telecom C-band, we demonstrate photon-photon entanglement, ion-photon entanglement, and teleportation of a qubit state from the ion onto a remote telecom photon, all realized over the urban fiber link., Comment: 14 pages, 13 figures, including appendix

The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the upcoming v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development.

Nanoscience at times can seem out of reach to the developing world and the general public, with much of the equipment expensive and knowledge seemingly esoteric to nonexperts. Using only cheap, everyday household items, accessible research with real applications can be shown. Here, graphene suspensions were produced using pencil lead, tap water, kitchen appliances, soaps and coffee filters, with a childrens glue based graphene nanocomposite for highly sensitive pulse measurements demonstrated.

Two dimensional (2D) layered transition-metal-based tellurides (chalcogens) are known to harness their surface atoms characteristics to enhance topographical activities for energy conversion, storage, and magnetic applications. High surface energy due to unsaturated dangling bonds and larger lateral size than the thickness (volume) makes them a potential candidate for emerging electronics. Nevertheless, the gradual stacking of each sheet alters the surface atoms' subtle features, such as lattice expansion, leading to several phenomena and rendering tunable properties. In the present work, we have monitored thickness-dependent properties of the 2D CoTe2 sheets from nanoscale mechanics, tribology, surface potential distributions, interfacial interaction and magnetism using atomically resolved spectroscopy and different surface probe techniques, in conjunction with theoretical investigations: density functional theory (DFT) and molecular dynamics (MD). The variation in properties observed in theoretical investigation unleashes the crucial role of crystal planes of the CoTe2. The presented results are beneficial in expanding the use of 2D telluride family in flexible electronics, piezo sensors, tribo-generator, and next-generation memory devices.

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE) providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe-Salpeter Equation (BSE), variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn-Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support of GPU acceleration has been achieved with minor modifications of the GPAW code thanks to the CuPy library. We end the review with an outlook describing some future plans for GPAW.

Purpose: To identify ocular hypertension (OHT) subtypes with different trends of visual field (VF) progression based on unsupervised machine learning and to discover factors associated with fast VF progression. Participants: A total of 3133 eyes of 1568 ocular hypertension treatment study (OHTS) participants with at least five follow-up VF tests were included in the study. Methods: We used a latent class mixed model (LCMM) to identify OHT subtypes using standard automated perimetry (SAP) mean deviation (MD) trajectories. We characterized the subtypes based on demographic, clinical, ocular, and VF factors at the baseline. We then identified factors driving fast VF progression using generalized estimating equation (GEE) and justified findings qualitatively and quantitatively. Results: The LCMM model discovered four clusters (subtypes) of eyes with different trajectories of MD worsening. The number of eyes in clusters were 794 (25%), 1675 (54%), 531 (17%) and 133 (4%). We labelled the clusters as Improvers, Stables, Slow progressors, and Fast progressors based on their mean of MD decline, which were 0.08, -0.06, -0.21, and -0.45 dB/year, respectively. Eyes with fast VF progression had higher baseline age, intraocular pressure (IOP), pattern standard deviation (PSD) and refractive error (RE), but lower central corneal thickness (CCT). Fast progression was associated with calcium channel blockers, being male, heart disease history, diabetes history, African American race, stroke history, and migraine headaches.

While capable of imaging the atoms constituting thin slabs of material, the achievable resolution of conventional electron imaging techniques in a transmission electron microscope (TEM) is very sensitive to the partial spatial coherence of the electron source, lens aberrations and mechanical instabilities of the microscope. The desire to break free from the limitations of the apparatus spurred the popularity of ptychography, a computational phase retrieval technique that, to some extent, can compensate for the imperfections of the equipment. Recently it was shown that ptychography is capable of resolving specimen features as fine as the blurring due to the vibrations of atoms, a limit defined not by the microscope, but by the investigated sample itself. Here we report on the successful application of a mixed-object formalism in the ptychographic reconstruction that enables the resolution of fluctuations in atomic positions within real space. We show a reconstruction of a symmetric {\Sigma}9 grain boundary in silicon from realistically (molecular dynamics) simulated data. By reconstructing the object as an ensemble of 10 different states we were able to observe movements of atoms in the range of 0.1-0.2 \AA in agreement with the expectation. This is a significant step forward in the field of electron ptychography, as it enables the study of dynamic systems with unprecedented precision and overcomes the resolution limit so far considered to be imposed by the thermal motion of the atoms.

We present optical and near-infrared observations of SN~2022crv, a stripped envelope supernova in NGC~3054, discovered within 12 hrs of explosion by the Distance Less Than 40 Mpc Survey. We suggest SN~2022crv is a transitional object on the continuum between SNe Ib and SNe IIb. A high-velocity hydrogen feature ($\sim$$-$20,000 -- $-$16,000 $\rm km\,s^{-1}$) was conspicuous in SN~2022crv at early phases, and then quickly disappeared around maximum light. By comparing with hydrodynamic modeling, we find that a hydrogen envelope of $\sim 10^{-3}$ \msun{} can reproduce the behaviour of the hydrogen feature observed in SN~2022crv. The early light curve of SN~2022crv did not show envelope cooling emission, implying that SN~2022crv had a compact progenitor with extremely low amount of hydrogen. The analysis of the nebular spectra shows that SN~2022crv is consistent with the explosion of a He star with a final mass of $\sim$4.5 -- 5.6 \msun{} that has evolved from a $\sim$16 -- 22 \msun{} zero-age main sequence star in a binary system with about 1.0 -- 1.7 \msun{} of oxygen finally synthesized in the core. The high metallicity at the supernova site indicates that the progenitor experienced a strong stellar wind mass loss. In order to retain a small amount of residual hydrogen at such a high metallicity, the initial orbital separation of the binary system is likely larger than $\sim$1000~$\rm R_{\odot}$. The near-infrared spectra of SN~2022crv show a unique absorption feature on the blue side of He I line at $\sim$1.005~$\mu$m. This is the first time that such a feature has been observed in a Type Ib/IIb, and could be due to \ion{Sr}{2}. Further detailed modelling on SN~2022crv can shed light on the progenitor and the origin of the mysterious absorption feature in the near infrared., Comment: 33 pages, 23 figures, submitted to ApJ

The sky is the limit with regards to the societal impact nanomaterials can have on our lives. However, in this study we show that their potential is out of this world. The planet Mars has an abundant source of calcium sulfate minerals and in our work, we show that these deposits can be the basis of transformative nanomaterials to potentially support future space endeavors. Through a scalable eco-friendly liquid processing technique performed on two common terrestrial gypsum, our simple method presented a cost-efficient procedure to yield the commercially valuable intermediate phase of gypsum, known as bassanite. Through the liquid exfoliation of bassanite powders, suspensions of large aspect ratio anhydrite nanobelts with long-term stability were characterized through scanning electron microscopy and Raman spectroscopy. Transmission electron microscopy showed nanobelts to have a mesocrystal structure, with distinct nanoparticle constituents making up the lattice. Unexpectedly, anhydrite nanobelts had remarkable electronic properties, namely a bandgap that was easily tuned between semiconducting (~2.2 eV) and insulating (~4 eV) behaviors through dimensional control measured via atomic force microscopy. To demonstrate the application potential of our nanobelts; optoelectronic, electrochemical and nanocomposite measurements were made. For the hydrogen evolution reaction and mechanical reinforcement, selenite-based anhydrite nanobelts displayed superlative performances.

Solid-state spin qubits within silicon crystals at mK temperatures show great promise in the realisation of a fully scalable quantum computation platform. Qubit coherence times are limited in natural silicon owing to coupling to the isotope ${ }^{29} \mathrm{Si}$ which has a non-zero nuclear spin. This work presents a method for the depletion of ${ }^{29} \mathrm{Si}$ in localised volumes of natural silicon wafers by irradiation using a 45 keV ${ }^{28} \mathrm{Si}$ focused ion beam with fluences above $1 \times 10^{19} \, \mathrm{ions} \, \mathrm{cm}^{-2}$. Nanoscale secondary ion mass spectrometry analysis of the irradiated volumes shows unprecedented quality enriched silicon that reaches a minimal residual ${ }^{29} \mathrm{Si}$ value of 2.3 $\pm$ 0.7 ppm and with residual C and O comparable to the background concentration in the unimplanted wafer. Transmission electron microscopy lattice images confirm the solid phase epitaxial re-crystallization of the as-implanted amorphous enriched volume extending over 200 nm in depth upon annealing. The ease of fabrication, requiring only commercially available natural silicon wafers and ion sources, opens the possibility for co-integration of qubits in localised highly enriched volumes with control circuitry in the surrounding natural silicon for large-scale devices., Comment: 8 pages, 4 figures, 2 tables