Chemically Hydrophobic and Structurally Antireflective Nanocoatings in Butterflies.

Moth-eye nanostructures, known for their biological antireflective properties, are formed by a self-assembly mechanism. Understanding and replicating this mechanism on artificial surfaces open avenues for the engineering of bioinspired multifunctional nanomaterials. Analysis of corneal nanocoatings from butterflies of the genus reveals a variety of nanostructures with uniformly strong antiwetting properties accompanied by varying antireflective functionalities.

Enhanced physicochemical properties of chitosan films with generation of kafirin particles: optimization response surface methodology.

Biodegradable food packaging has gained significant attention owing to environmental concerns. Chitosan (CS), a natural polysaccharide, is popular in packaging films, however, its high hydrophilicity, brittleness, and low mechanical strength limit its use. To improve CS film performance, kafirin (Kaf), glycerol (GE), and tannic acid (TA) were added to create biocomposite films.

Machine learning-driven image synthesis and analysis applications for inertial confinement fusion (invited).

Recent fusion breakeven [Abu-Shawareb et al., Phys. Rev.

Enabling Energy-Efficient Deployment of Large Language Models on Memristor Crossbar: A Synergy of Large and Small.

Large language models (LLMs) have garnered substantial attention due to their promising applications in diverse domains. Nevertheless, the increasing size of LLMs comes with a significant surge in the computational requirements for training and deployment. Memristor crossbars have emerged as a promising solution, which demonstrated a small footprint and remarkably high energy efficiency in computer vision (CV) models.

Time Lens Photon Doppler Velocimetry (TL-PDV) for extreme measurements.

Capturing extreme surface velocities with  >50 km/s dynamic range, which arise in shock physics such as inertial confinement fusion (ICF), is beyond the reach of conventional photon Doppler velocimetry (PDV) systems due to the need for extremely large electrical bandwidth under such conditions. The recent ignition in ICF calls for new velocimetry that can measure velocities exceeding 100 km/s. Time lens PDV (TL-PDV) is a solution where the high frequency beat signal from a conventional PDV system is periodically temporally magnified in the optical domain using a time lens.

Digital Holography and 3D Imaging: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

The Optica Topical Meeting on Digital Holography and 3D Imaging (DH) was held 14-17 August 2023 in Boston, Massachusetts. The meeting was organized co-jointly with the Optica Imaging Congress. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007.

Digital Holography and 3D Imaging 2023: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

The Optica Topical Meeting on Digital Holography and 3D Imaging (DH) was held 14-17 August 2023 in Boston, Massachusetts. The meeting was organized co-jointly with the Optica Imaging Congress. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007.

Safety and Effectiveness of Laser or Intense Pulsed Light Treatment for Early Surgical Scar: A Systematic Review and Meta-analysis.

Objective: We aimed to investigate the safety and efficacy of laser or intense pulsed light therapy for early treatment of surgical scar.

Methods: A literature search was conducted for relevant prospective, randomized controlled trials published in PubMed, Embase, Web of Science, Cochrane Library, CNKI, WanFang Database, and VTTMS between January 2006 and January 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was used to extract literature data.

Optimizing for In-Memory Deep Learning With Emerging Memory Technology.

In-memory deep learning executes neural network models where they are stored, thus avoiding long-distance communication between memory and computation units, resulting in considerable savings in energy and time. In-memory deep learning has already demonstrated orders of magnitude higher performance density and energy efficiency. The use of emerging memory technology (EMT) promises to increase density, energy, and performance even further.

Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction.

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets.

Facile construction of agar-based fire-resistant aerogels: A synergistic strategy via in situ generations of magnesium hydroxide and cross-linked Ca-alginate.

Biomass-based aerogel materials have many advantages, such as low thermal conductivity and non-toxicity. These materials are environmentally friendly and have broad development potential in the fields of packaging, cushioning and green building insulation. However, defects, such as low mechanical strength and poor fire safety, greatly limit the application of these materials.

Research Progress of Three-Dimensional Bioprinting Artificial Cardiac Tissue.

Cardiovascular disease is one of the main diseases that endanger human life and health, and heart failure often occurs when the cardiovascular disease develops to the end-stage. Heart transplantation is the most effective treatment. However, there has always been a shortage of living heart organs.

Structural and Optical Properties of High Entropy (La,Lu,Y,Gd,Ce)AlO Perovskite Thin Films.

Mixtures of Ce-doped rare-earth aluminum perovskites are drawing a significant amount of attention as potential scintillating devices. However, the synthesis of complex perovskite systems leads to many challenges. Designing the A-site cations with an equiatomic ratio allows for the stabilization of a single-crystal phase driven by an entropic regime.

Efficient Spiking Neural Networks With Radix Encoding.

Spiking neural networks (SNNs) have advantages in latency and energy efficiency over traditional artificial neural networks (ANNs) due to their event-driven computation mechanism and the replacement of energy-consuming weight multiplication with addition. However, to achieve high accuracy, it usually requires long spike trains to ensure accuracy, usually more than 1000 time steps. This offsets the computation efficiency brought by SNNs because a longer spike train means a larger number of operations and larger latency.

Persistent hiccup as one of the initial symptoms of leucine-rich glioma-inactivated-1 encephalitis: a case report.

Background: Anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis, an autoimmune disorder, is characterized by faciobrachial dystonic seizures, epilepsy, memory deficits and altered mental status while hiccup is not commonly found in patients.

Case Presentation: A 62-year-old male was presented with slurred speech, abnormal gait, faciobrachial dystonic seizures and impaired cognition. Besides, the hiccup was one of the initial symptoms.

EDCompress: Energy-Aware Model Compression for Dataflows.

Edge devices demand low energy consumption, cost, and small form factor. To efficiently deploy convolutional neural network (CNN) models on the edge device, energy-aware model compression becomes extremely important. However, existing work did not study this problem well because of the lack of considering the diversity of dataflow types in hardware architectures.

Radiographic imaging and tomography.

Radiographic imaging and tomography (RadIT) come in many types such as x-ray imaging and tomography (IT), proton IT, neutron IT, muon IT, and more. We identify five RadIT themes: physics, sources, detectors, methods, and data science, which are integral parts of image interpretation and 3D tomographic reconstruction. Traditionally, RadIT has been driven by medicine, non-destructive testing, material sciences, and security applications.

Simulating 50 keV X-ray Photon Detection in Silicon with a Down-Conversion Layer.

Simulation results are presented that explore an innovative, new design for X-ray detection in the 20-50 keV range that is an alternative to traditional direct and indirect detection methods. Typical indirect detection using a scintillator must trade-off between absorption efficiency and spatial resolution. With a high-Z layer that down-converts incident photons on top of a silicon detector, this design has increased absorption efficiency without sacrificing spatial resolution.

Billion-pixel x-ray camera (BiPC-X).

The continuing improvement in quantum efficiency (above 90% for single visible photons), reduction in noise (below 1 electron per pixel), and shrink in pixel pitch (less than 1 μm) enable billion-pixel x-ray cameras (BiPC-X) based on commercial complementary metal-oxide-semiconductor (CMOS) imaging sensors. We describe BiPC-X designs and prototype construction based on flexible tiling of commercial CMOS imaging sensors with millions of pixels. Device models are given for direct detection of low energy x rays (<10 keV) and indirect detection of higher energies using scintillators.

Time-lens photon Doppler velocimetry (TL-PDV).

We describe a time lens (TL) to expand the dynamic range of photon Doppler velocimetry (PDV) systems. The principle and preliminary design of a TL-PDV system are explained and shown to be feasible through simulations. In a PDV system, an interferometer is used for measuring frequency shifts due to the Doppler effect from the target motion.

Prevalence of diabetes and hypertension and their interaction effects on cardio-cerebrovascular diseases: a cross-sectional study.

Background: Hypertension and diabetes mellitus are two of the major risk factors for cardio-cerebrovascular diseases (CVDs). Although prior studies have confirmed that the coexistence of the two can markedly increase the risk of CVDs, few studies investigated whether potential interaction effects of hypertension and diabetes can result in greater cardio-cerebrovascular damage. We aimed to investigate the prevalence of hypertension and diabetes and whether they both affect synergistically the risk of CVDs.

Asynchronous and Load-Balanced Union-Find for Distributed and Parallel Scientific Data Visualization and Analysis.

We present a novel distributed union-find algorithm that features asynchronous parallelism and k-d tree based load balancing for scalable visualization and analysis of scientific data. Applications of union-find include level set extraction and critical point tracking, but distributed union-find can suffer from high synchronization costs and imbalanced workloads across parallel processes. In this study, we prove that global synchronizations in existing distributed union-find can be eliminated without changing final results, allowing overlapped communications and computations for scalable processing.

Neural network for 3D inertial confinement fusion shell reconstruction from single radiographs.

In inertial confinement fusion (ICF), x-ray radiography is a critical diagnostic for measuring implosion dynamics, which contain rich three-dimensional (3D) information. Traditional methods for reconstructing 3D volumes from 2D radiographs, such as filtered backprojection, require radiographs from at least two different angles or lines of sight (LOS). In ICF experiments, the space for diagnostics is limited, and cameras that can operate on fast timescales are expensive to implement, limiting the number of projections that can be acquired.

Two-photon X-ray ghost microscope.

This article presents a non-classical imaging mechanism that produces a diffraction-limited and magnified ghost image of the internal structure of an object through the measurement of intensity fluctuation correlation formed by two-photon interference. In principle, the lensless X-ray ghost imaging mechanism may achieve a spatial resolution determined by the wavelength and the angular diameter of the X-ray source, ∼λ/Δθ, with possible reduction caused by additional optics. In addition, it has the ability to image select "slices" deep within an object, which can be used for constructing 3D view of its internal structure.