Estimation of the number of single-photon emitters for multiple fluorophores with the same spectral signature.

Fluorescence microscopy is of vital importance for understanding biological function. However most fluorescence experiments are only qualitative inasmuch as the absolute number of fluorescent particles can often not be determined. Additionally, conventional approaches to measuring fluorescence intensity cannot distinguish between two or more fluorophores that are excited and emit in the same spectral window, as only the total intensity in a spectral window can be obtained. Here we show that, by using photon number resolving experiments, we are able to determine the number of emitters and their probability of emission for a number of different species, all with the same measured spectral signature. We illustrate our ideas by showing the determination of the number of emitters per species and the probability of photon collection from that species, for one, two, and three otherwise unresolvable fluorophores. The convolution Binomial model is presented to model the counted photons emitted by multiple species. And then the Expectation-Maximization (EM) algorithm is used to match the measured photon counts to the expected convolution Binomial distribution function. In applying the EM algorithm, to leverage the problem of being trapped in a sub-optimal solution, the moment method is introduced in finding the initial guess of the EM algorithm. Additionally, the associated Cram\'er-Rao lower bound is derived and compared with the simulation results.

Estimation of the number of single-photon emitters for multiple fluorophores with the same spectral signature.

Fluorescence microscopy is of vital importance for understanding biological function. However, most fluorescence experiments are only qualitative inasmuch as the absolute number of fluorescent particles can often not be determined. Additionally, conventional approaches to measuring fluorescence intensity cannot distinguish between two or more fluorophores that are excited and emit in the same spectral window, as only the total intensity in a spectral window can be obtained. Here we show that, by using photon number resolving experiments, we are able to determine the number of emitters and their probability of emission for a number of different species, all with the same measured spectral signature. We illustrate our ideas by showing the determination of the number of emitters per species and the probability of photon collection from that species, for one, two and three otherwise unresolvable fluorophores. The convolution binomial model is presented to represent the counted photons emitted by multiple species. Then, the expectation-maximization (EM) algorithm is used to match the measured photon counts to the expected convolution binomial distribution function. In applying the EM algorithm, to leverage the problem of being trapped in a sub-optimal solution, the moment method is introduced to yield an initial guess for the EM algorithm. Additionally, the associated Cramér-Rao lower bound is derived and compared with the simulation results.

RIOT: Recursive Inertial Odometry Transformer for Localisation from Low-Cost IMU Measurements.

Inertial localisation is an important technique as it enables ego-motion estimation in conditions where external observers are unavailable. However, low-cost inertial sensors are inherently corrupted by bias and noise, which lead to unbound errors, making straight integration for position intractable. Traditional mathematical approaches are reliant on prior system knowledge, geometric theories and are constrained by predefined dynamics. Recent advances in deep learning, which benefit from ever-increasing volumes of data and computational power, allow for data-driven solutions that offer more comprehensive understanding. Existing deep inertial odometry solutions rely on estimating the latent states, such as velocity, or are dependent on fixed-sensor positions and periodic motion patterns. In this work, we propose taking the traditional state estimation recursive methodology and applying it in the deep learning domain. Our approach, which incorporates the true position priors in the training process, is trained on inertial measurements and ground truth displacement data, allowing recursion and learning both motion characteristics and systemic error bias and drift. We present two end-to-end frameworks for pose invariant deep inertial odometry that utilises self-attention to capture both spatial features and long-range dependencies in inertial data. We evaluate our approaches against a custom 2-layer Gated Recurrent Unit, trained in the same manner on the same data, and tested each approach on a number of different users, devices and activities. Each network had a sequence length weighted relative trajectory error mean ≤0.4594 m, highlighting the effectiveness of our learning process used in the development of the models.

Photon extraction enhancement of praseodymium ions in gallium nitride nanopillars.

Lanthanoid-doped Gallium Nitride (GaN) integrated into nanophotonic technologies is a promising candidate for room-temperature quantum photon sources for quantum technology applications. We manufactured praseodymium (Pr)-doped GaN nanopillars of varying size, and showed significantly enhanced room-temperature photon extraction efficiency compared to unstructured Pr-doped GaN. Implanted Pr ions in GaN show two main emission peaks at 650.3 nm and 651.8 nm which are attributed to 3P0-3F2 transition in the 4f-shell. The maximum observed enhancement ratio was 23.5 for 200 nm diameter circular pillars, which can be divided into the emitted photon extraction enhancement by a factor of 4.5 and the photon collection enhancement by a factor of 5.2. The enhancement mechanism is explained by the eigenmode resonance inside the nanopillar. Our study provides a pathway for Lanthanoid-doped GaN nano/micro-scale photon emitters and quantum technology applications.

Magnetic-field-dependent stimulated emission from nitrogen-vacancy centers in diamond.

Negatively charged nitrogen-vacancy (NV) centers in diamond are promising magnetic field quantum sensors. Laser threshold magnetometry theory predicts improved NV center ensemble sensitivity via increased signal strength and magnetic field contrast. Here, we experimentally demonstrate laser threshold magnetometry. We use a macroscopic high-finesse laser cavity containing a highly NV-doped and low absorbing diamond gain medium that is pumped at 532 nm and resonantly seeded at 710 nm. This enables a 64% signal power amplification by stimulated emission. We test the magnetic field dependency of the amplification and thus demonstrate magnetic field-dependent stimulated emission from an NV center ensemble. This emission shows an ultrahigh contrast of 33% and a maximum output power in the milliwatt regime. The coherent readout of NV centers pave the way for novel cavity and laser applications of quantum defects and diamond NV magnetic field sensors with substantially improved sensitivity for the health, research, and mining sectors.

En route to nanoscopic quantum optical imaging: counting emitters with photon-number-resolving detectors.

The fundamental understanding of biological pathways requires minimally invasive nanoscopic optical resolution imaging. Many approaches to high-resolution imaging rely on localization of single emitters, such as fluorescent molecules or quantum dots. Additionally, the exact determination of the number of such emitters in an imaging volume is essential for a number of applications; however, in standard intensity-based microscopy it is not possible to determine the number of individual emitters within a diffraction limited spot without initial knowledge of system parameters. Here we explore how quantum measurements of the emitted photons using photon number resolving detectors can be used to address this challenging task. In the proposed new approach, the problem of counting emitters reduces to the task of determining differences between the emitted photon distribution and the Poisson limit. We show that quantum measurements of the number of photons emitted from an ensemble of emitters enable the determination of both the number of emitters and the probability of emission. This method can be applied for any type of single-photon emitters. The scaling laws of this new approach are presented by the Cramer-Rao Lower Bounds, and this technique has great potential in quantum optical imaging with nanoscopic resolution.

Einstein, von Frisch and the honeybee: a historical letter comes to light.

The work of the Nobel Laureate Karl von Frisch, the founder of this journal, was seminal in many ways. He established the honeybee as a key animal model for experimental behavioural studies on sensory perception, learning and memory, and first correctly interpreted its famous dance communication. Here, we report on a previously unknown letter by the Physicist and Nobel Laureate Albert Einstein that was written in October 1949. It briefly addresses the work of von Frisch and also queries how understanding animal perception and navigation may lead to innovations in physics. We discuss records proving that Einstein and von Frisch met in April 1949 when von Frisch visited the USA to present a lecture on bees at Princeton University. In the historical context of Einstein's theories and thought experiments, we discuss some more recent discoveries of animal sensory capabilities alien to us humans and potentially valuable for bio-inspired design improvements. We also address the orientation of animals like migratory birds mentioned by Einstein 70 years ago, which pushes the boundaries of our understanding nature, both its biology and physics.

Preferential coupling of diamond NV centres in step-index fibres.

Diamonds containing the negatively charged nitrogen-vacancy centre are a promising system for room-temperature magnetometry. The combination of nano- and micro-diamond particles with optical fibres provides an option for deploying nitrogen-vacancy magnetometers in harsh and challenging environments. Here we numerically explore the coupling efficiency from nitrogen-vacancy centres within a diamond doped at the core/clad interface across a range of commercially available fibre types so as to inform the design process for a diamond in fibre magnetometers. We determine coupling efficiencies from nitrogen-vacancy centres to the guided modes of a step-index fibre and predict the optically detected magnetic resonance (ODMR) generated by a ensemble of four nitrogen-vacancy centres in this hybrid fibre system. Our results show that the coupling efficiency is enhanced with a high refractive index difference between the fibre core and cladding and depends on the radial position of the nitrogen-vacancy centres in the fibre core. Our ODMR simulations show that due to the preferential coupling of the nitrogen-vacancy emission to the fibre guided modes, certain magnetometry features such as ODMR contrast can be enhanced and lead to improved sensitivity in such diamond-fibre systems, relative to conventional diamond only ensemble geometries.

Iridescence and hydrophobicity have no clear delineation that explains flower petal micro-surface.

Plant organs including flowers and leaves typically have a variety of different micro-structures present on the epidermal surface. These structures can produce measurable optical effects with viewing angle including shifts in peak reflectance and intensity; however, these different structures can also modulate hydrophobic properties of the surfaces. For some species optical effects have been proposed to act as signals to enhance pollination interactions, whilst the ability to efficiently shed water provides physiological advantages to plants in terms of gas exchange and reducing infections. Currently, little is known about epidermal surface structure of flowering plants in the Southern Hemisphere, and how micro-surface may be related with either hydrophobicity or visual signalling. We measured four Australian native species and two naturalised species using a combination of techniques including SEM imaging, spectral sampling with a goniometer and contact angle measurements. Spectral data were evaluated in relation to published psychophysics results for important pollinators and reveal that potential visual changes, where present, were unlikely to be perceived by relevant pollinators. Nevertheless, hydrophobicity also did not simply explain petal surfaces as similar structures could in some cases result in very different levels of water repellency.

Spontaneous quantity discrimination of artificial flowers by foraging honeybees.

Many animals need to process numerical and quantity information in order to survive. Spontaneous quantity discrimination allows differentiation between two or more quantities without reinforcement or prior training on any numerical task. It is useful for assessing food resources, aggressive interactions, predator avoidance and prey choice. Honeybees have previously demonstrated landmark counting, quantity matching, use of numerical rules, quantity discrimination and arithmetic, but have not been tested for spontaneous quantity discrimination. In bees, spontaneous quantity discrimination could be useful when assessing the quantity of flowers available in a patch and thus maximizing foraging efficiency. In the current study, we assessed the spontaneous quantity discrimination behaviour of honeybees. Bees were trained to associate a single yellow artificial flower with sucrose. Bees were then tested for their ability to discriminate between 13 different quantity comparisons of artificial flowers (numeric ratio range: 0.08-0.8). Bees significantly preferred the higher quantity only in comparisons where '1' was the lower quantity and where there was a sufficient magnitudinal distance between quantities (e.g. 1 versus 12, 1 versus 4, and 1 versus 3 but not 1 versus 2). Our results suggest a possible evolutionary benefit to choosing a foraging patch with a higher quantity of flowers when resources are scarce.

Beamed UV sonoluminescence by aspherical air bubble collapse near liquid-metal microparticles.

Irradiation with UV-C band ultraviolet light is one of the most commonly used ways of disinfecting water contaminated by pathogens such as bacteria and viruses. Sonoluminescence, the emission of light from acoustically-induced collapse of air bubbles in water, is an efficient means of generating UV-C light. However, because a spherical bubble collapsing in the bulk of water creates isotropic radiation, the generated UV-C light fluence is insufficient for disinfection. Here we show, based on detailed theoretical modelling and rigorous simulations, that it should be possible to create a UV light beam from aspherical air bubble collapse near a gallium-based liquid-metal microparticle. The beam is perpendicular to the metal surface and is caused by the interaction of sonoluminescence light with UV plasmon modes of the metal. We estimate that such beams can generate fluences exceeding 10 mJ/cm2, which is sufficient to irreversibly inactivate most common pathogens in water with the turbidity of more than 5 Nephelometric Turbidity Units.

3D-Printed Diamond-Titanium Composite: A Hybrid Material for Implant Engineering.

Diamond-based implant materials make up an emerging research area where the materials could be prepared to promote cellular functions, decrease bacteria attachment, and be suitable for potential in situ imaging. Up until now, diamond implants have been fabricated using coating technologies or embedding diamond nanoparticles in polymer matrices. Here we demonstrated a method of manufacturing diamond implants using laser cladding technology to 3D print a composite of diamond and fused titanium material. Using this method, we could prepare composite scaffolds of up to 50% diamond, which has never been achieved before. We next investigated the interfacial properties of these scaffolds for potential applications in implants. The addition of diamond to the biomaterial results in a 30% decrease in the water contact angle, making the scaffolds more hydrophilic and improving cellular adhesion and proliferation.

Modal interferometric refractive index sensing in microstructured exposed core fibres.

Optical fibre-based sensors measuring refractive index shift in bodily fluids and tissues are versatile and accurate probes of physiological processes. Here, we suggest a refractive index sensor based on a microstructured exposed-core fibre (ECF). By considering a high refractive index coating of the exposed core, our modelling demonstrates the splitting of the guided mode into a surface sensing mode and a mode that is isolated from the surface. With the isolated mode acting as a reference arm, this two-mode one-fibre solution provides for robust interferometric sensing with a sensitivity of up to 60, 000 rad/RIU-cm, which is suitable for sensing subtle physiological processes within hard-to-reach places inside living organisms, such as the spinal cord, ovarian tract and blood vessels.

Achieving arithmetic learning in honeybees and examining how individuals learn.

In recent years honeybees have demonstrated intriguing numerical capacities, leading to the recent discovery of their ability to perform simple arithmetic by learning to add or subtract 'one' using symbolic representations of operators. When training an insect with a miniature brain containing less than one million neurons to understand a conceptual rule, the procedure is of vital importance. We explain in detail the controls and process of designing an experiment to test for complex behaviors in a relatively simple brained animal. Furthermore, we will discuss the finding that individual honeybees do not demonstrate a consistent learning scenario when trained to perform the same tasks, rather they appear to acquire arithmetic rules through individual processes.

Surpassing the subitizing threshold: appetitive-aversive conditioning improves discrimination of numerosities in honeybees.

Animals including humans, fish and honeybees have demonstrated a quantity discrimination threshold at four objects, often known as subitizing elements. Discrimination between numerosities at or above the subitizing range is considered a complex capacity. In the current study, we trained and tested two groups of bees on their ability to differentiate between quantities (4 versus 5 through to 4 versus 8) when trained with different conditioning procedures. Bees trained with appetitive (reward) differential conditioning demonstrated no significant learning of this task, and limited discrimination above the subitizing range. In contrast, bees trained using appetitive-aversive (reward-aversion) differential conditioning demonstrated significant learning and subsequent discrimination of all tested comparisons from 4 versus 5 to 4 versus 8. Our results show conditioning procedure is vital to performance on numerically challenging tasks, and may inform future research on numerical abilities in other animals.

Sensitive and Multiplexed SERS Nanotags for the Detection of Cytokines Secreted by Lymphoma.

The sensitive and simultaneous detection of cytokines will provide new insights into the physiological process and disease pathways due to the complex nature of cytokine networks. However, the key challenge is the lack of probes that can simultaneously detect multiple cytokines in a single sample. In this contribution, we proposed an alternative approach for sensitive cytokine detection in a multiplex manner by the use of a new set of surface-enhanced Raman spectroscopy (SERS) nanotags. Typically, the newly designed SERS nanotags are composed of gold nanoparticles as the core, tuneable Raman molecules as the reporters, and a thin silver layer as the shell. As demonstrated through rigorous numerical simulations, enhanced Raman signal is achieved due to a strong localization of light in the 0.2 nm thin, optically deep-subwavelength region between the Au core and the Ag shell. Sensitive detection of cytokines is realized by forming a sandwich immunoassay. The detection limit is down to 4.5 pg mL-1 (S/N = 3). The specificity of the assay is proved as negligible signals were detected for the false targets. Furthermore, multiple cytokines are simultaneously detected in a single assay from the secretion of B-lymphocyte cell line (Raji) after concanavalin A (Con A) stimulation. The results indicate that our method holds a significant potential for sensitive and multiplexed detection of cytokines and offers the opportunity for future applications in clinical settings.

Honeybees prefer novel insect-pollinated flower shapes over bird-pollinated flower shapes.

Plant-pollinator interactions have a fundamental influence on flower evolution. Flower color signals are frequently tuned to the visual capabilities of important pollinators such as either bees or birds, but far less is known about whether flower shape influences the choices of pollinators. We tested European honeybee Apis mellifera preferences using novel achromatic (gray-scale) images of 12 insect-pollinated and 12 bird-pollinated native Australian flowers in Germany; thus, avoiding influences of color, odor, or prior experience. Independent bees were tested with a number of parameterized images specifically designed to assess preferences for size, shape, brightness, or the number of flower-like shapes present in an image. We show that honeybees have a preference for visiting images of insect-pollinated flowers and such a preference is most-likely mediated by holistic information rather than by individual image parameters. Our results indicate angiosperms have evolved flower shapes which influence the choice behavior of important pollinators, and thus suggest spatial achromatic flower properties are an important part of visual signaling for plant-pollinator interactions.

Engineering the Interface: Nanodiamond Coating on 3D-Printed Titanium Promotes Mammalian Cell Growth and Inhibits Staphylococcus aureus Colonization.

Additively manufactured selective laser melted titanium (SLM-Ti) opens the possibility of tailored medical implants for patients. Despite orthopedic implant advancements, significant problems remain with regard to suboptimal osseointegration at the interface between the implant and the surrounding tissue. Here, we show that applying a nanodiamond (ND) coating onto SLM-Ti scaffolds provides an improved surface for mammalian cell growth while inhibiting colonization of Staphylococcus aureus bacteria. Owing to the simplicity of our methodology, the approach is suitable for coating SLM-Ti geometries. The ND coating achieved 32 and 29% increases in cell density of human dermal fibroblasts and osteoblasts, respectively, after 3 days of incubation compared with the uncoated SLM-Ti substratum. This increase in cell density complements an 88% reduction in S. aureus detected on the ND-coated SLM-Ti substrata. This study paves a way to create facile antifouling SLM-Ti structures for biomedical implants.