Light Patterns Research Articles

Dynamic visual noise has limited influence on the habitat selection and behavioural activity of crustaceans and cephalopods

AbstractEnvironments contain various forms of noise that can interfere with the ability of animal sensory systems to perceive information. One ubiquitous type of visual noise in shallow aquatic habitats is caustic flicker (or caustics), consisting of dynamically moving light patterns caused by the refraction of light when passing through the water's rippling surface. While some teleost fish avoid environments with caustic noise (where their prey can be more difficult to detect), it remains untested whether caustics affect the habitat selection of invertebrates. In the present study, we ask whether three invertebrate species, the shore crab Carcinus maenas, the brown shrimp Crangon crangon, and the common cuttlefish Sepia officinalis, prefer or avoid associating with environments with caustic noise, and whether caustics affect their behavioural activity and habitat exploration. To do this, we exposed the three species in binary choice experiments to different simulated caustic noise levels varying in their temporal (speed) and spatial (definition) components. Neither of the three tested invertebrate species spent more or less time in environments with higher caustic noise levels. While we also found no evidence that caustics affected the behavioural activity and exploration of Ca. maenas and S. officinalis, the brown shrimp Cr. crangon reduced its activity with increasing spatial caustic noise. However, all obtained effect sizes in this study were small, suggesting that caustic noise only minimally affects invertebrate behaviour. Overall, our results show that, unlike in teleost fish, caustics have limited influence on the habitat selection, exploration, and activity of crustaceans and cephalopods.

Patterns of vehicle lights: Addressing complexities of camera-based vehicle light datasets and metrics

This paper explores the representation of vehicle lights in computer vision and its implications for various pattern recognition tasks in autonomous driving. Different representations for vehicle lights, including bounding boxes, center points, corner points, and segmentation masks, are discussed in terms of their strengths and weaknesses toward a variety of domain tasks, as well as associated data collection and annotation challenges. This leads to the introduction of the LISA Vehicle Lights Dataset, providing light annotations related to position, state, color, and signal, specifically designed for downstream applications in vehicle detection, intent and trajectory prediction, and safe path planning. A comparison of existing vehicle light datasets is provided, highlighting the unique features and limitations of each dataset. Because occlusions from vehicle pose and passing objects can limit camera observation, we introduce a group of Light Visibility neural networks, which take as input a detected vehicle image and return as output whether a corresponding vehicle light is present in the image. This is especially important for the evaluation of light localizations, states, and signals, as systems decisions should account for differences of lights being in unknown states due to occlusion versus model uncertainty. We show that our trained Light Visibility Models achieve over 90% accuracy on each of the four light classes. Our dataset and model are made available at https://cvrr.ucsd.edu/vehicle-lights-dataset.

Predicting the risk of hospital readmissions using a machine learning approach: a case study on patients undergoing skin procedures.

Even with modern advancements in medical care, one of the persistent challenges hospitals face is the frequent readmission of patients. These recurrent admissions not only escalate healthcare expenses but also amplify mental and emotional strain on patients. This research delved into two primary areas: unraveling the pivotal factors causing the readmissions, specifically targeting patients who underwent dermatological treatments, and determining the optimal machine learning algorithms that can foresee potential readmissions with higher accuracy. Among the multitude of algorithms tested, including logistic regression (LR), support vector machine (SVM), random forest (RF), Naïve Bayesian (NB), artificial neural network (ANN), xgboost (XG), and k-nearest neighbor (KNN), it was noted that two models-XG and RF-stood out in their prediction prowess. A closer inspection of the data brought to light certain patterns. For instance, male patients and those between the ages of 21 and 40 had a propensity to be readmitted more frequently. Moreover, the months of March and April witnessed a spike in these readmissions, with ~6% of the patients returning within just a month after their first admission. Upon further analysis, specific determinants such as the patient's age and the specific hospital where they were treated emerged as key indicators influencing the likelihood of their readmission.

Multi‑Beam Interference and Far‐Field Pattern of Guiding Light in Off‐Axis Unstable Resonator

Multi‑Beam Interference and Far‐Field Pattern of Guiding Light in Off‐Axis Unstable Resonator

Mathematical exploration of consciousness through topological data analysis for decoding neurobiological states

In this paper, we embark on a groundbreaking journey to understand one of the most profound mysteries of the human mind: consciousness. Our approach is unique because we use a branch of mathematics called Topological Data Analysis (TDA) to explore the complex workings of the brain. Imagine trying to understand the shape and connections of a vast network of roads without a map; TDA helps us create that map for the brain’s activity related to consciousness. At the heart of our study is the belief that the patterns of how brain regions connect and communicate hold the key to understanding consciousness. By applying TDA, we’re able to see these patterns in a new light, revealing the intricate landscape of brain activity in various states of consciousness, such as waking, sleeping, and dreaming. We meticulously collected and analyzed brain activity data using advanced neuroimaging techniques. Then, using TDA, we mapped out the topological structures—essentially, the shapes and connections within this data—that correspond to different conscious experiences. This mathematical lens allowed us to uncover hidden patterns and relationships within the brain’s activity, offering fresh insights into how consciousness emerges from the complex interplay of neural signals. Our findings not only deepen our understanding of consciousness but also demonstrate the power of mathematical approaches in unlocking the secrets of the human mind. This research paves the way for new explorations into consciousness and offers novel perspectives on how mathematics can help decipher the intricate workings of the brain.

Changes in visual evoked potentials during the menstrual cycle in young women

Background: The visual evoked potential (VEP) is a form of an electrical signal. VEP originates from the visual cortex which is located in Brodman areas 17 and 18 of the occipital lobe. VEP is generated in response to stimulation of the retina by light flashes or pattern stimuli. The advent of VEPs in the 1970s first allowed clinicians to assess neural conduction in the optic nerve. There are many factors that affect VEP such as age and gender; one among them is the hormonal factor. Ovarian and thyroid hormones are vital factors in the generation of olfactory, taste, visual, and auditory neuronal activity. The ovarian hormones progesterone and estrogen play a major role in the conduction of the optic nerve. Aims and Objectives: The aims and objectives of the study are to evaluate the influence of ovarian hormones in the VEPs. Materials and Methods: Among the 1st year medical students, 26 young females (18–20 years of age) were randomly selected. Informed consent was obtained from them and the institutional ethical committee approved the study. Students having regular menstrual periods for the past 6 months with normal visual acuity were included. Those with a history of polycystic ovarian disease, having irregular periods, under hormonal treatment were excluded from the study. Detailed history helps in identifying the proliferative and secretory phases of the menstrual cycle. The P100 wave latency of VEPs was recorded during these two different phases. Results: An unpaired t-test was used for analyzing the data. While comparing the proliferative and secretory phases, P100 wave latency was significantly reduced in the proliferative phase (101±3.6 vs. 97.9 ± 1.43 ms; P < 0.0001). Conclusion: The receptor sensitivity in the visual pathways to dopamine is increased by estrogen which in turn leads to a decrease in the time taken by the visual impulses to reach the visual cortex. Progesterone antagonizes estrogen activity in the central nervous system. Therefore, estrogen is responsible for the reduction in latency during the proliferative phase and progesterone is responsible for the prolonged VEP latency in the secretory phase. Thus, the excitability of the visual system is influenced by the ovarian hormones.

Pattern-illumination time-resolved phase microscopy and its applications for photocatalytic and photovoltaic materials.

Pattern-illumination time-resolved phase microscopy (PI-PM) is a technique used to study the microscopic charge carrier dynamics in photocatalytic and photovoltaic materials. The method involves illuminating a sample with a pump light pattern, which generates charge carriers and they decay subsequently due to trapping, recombination, and transfer processes. The distribution of photo-excited charge carriers is observed through refractive index changes using phase-contrast imaging. In the PI-PM method, the sensitivity of the refractive index change is enhanced by adjusting the focus position, the method takes advantage of photo-excited charge carriers to observe non-radiative processes, such as charge diffusion, trapping in defect/surface states, and interfacial charge transfer of photocatalytic and photovoltaic reactions. The quality of the image sequence is recovered using various informatics calculations. Categorizing and mapping different types of charge carriers based on their response profiles using clustering analysis provides spatial information on charge carrier types and the identification of local sites for efficient and inefficient photo-induced reactions, providing valuable information for the design and optimization of photocatalytic materials such as the cocatalyst effect.

First measurements of an imaging heavy ion beam probe at the ASDEX Upgrade tokamak.

The imaging heavy ion beam probe (i-HIBP) diagnostic has been successfully commissioned at ASDEX Upgrade. The i-HIBP injects a primary neutral beam into the plasma, where it is ionized, leading to a fan of secondary (charged) beams. These are deflected by the magnetic field of the tokamak and collected by a scintillator detector, generating a strike-line light pattern that encodes information on the density, electrostatic potential, and magnetic field of the plasma edge. The first measurements have been made, demonstrating the proof-of-principle of this diagnostic technique. A primary beam of 85/87Rb has been used with energies ranging between 60 and 72keV and extracted currents up to 1.5 mA. The first signals have been obtained in experiments covering a wide range of parameter spaces, with plasma currents (Ip) between 0.2 and 0.8 MA and on-axis toroidal magnetic field (Bt) between 1.9 and 2.7T. Low densities appear to be critical for the performance of the diagnostic, as signals are typically observed only when the line integrated density is below 2.0-3.0 × 1019m-2 in the central interferometer chord, depending on the plasma shape. The strike line moves as expected when Ip is ramped, indicating that current measurements are possible. Additionally, clear dynamics in the intensity of the strike line are often observed, which might be linked to changes in the edge profile structure. However, the signal-to-background ratio of the signals is hampered by stray light, and the image guide degradation is due to neutron irradiation. Finally, simulations have been carried out to investigate the sensitivity of the expected signals to plasma density and temperature. The results are in qualitative agreement with the experimental observations, suggesting that the diagnostic is almost insensitive to fluctuations in the temperature profile, while the signal level is highly determined by the density profile due to the beam attenuation.

Mesh-Based Double-Sided Freeform Lens Optimization

We present a mesh-based method for optimizing double-sided freeform lenses to control their caustic effects. Unlike traditional single-sided approaches, we optimize both sides of the lens simultaneously, using a bijective correspondence between the two sides to control light refraction paths. Our approach balances image fidelity, geometric compatibility, and physical constraints. Results demonstrate the method’s capability to accurately produce intricate light patterns, opening new possibilities in optical applications.

Upstream mobility and swarming of light activated micromotors.

Micromotors have been proposed for applications such as targeted drug delivery, thrombolysis, or sensing. However, single micrormotors are limited in the amount of payload they can deliver or force they can exert. Swarms of micromotors can overcome many of these challenges, however creating and controlling such swarms presents many challenges of its own. In particular, utilizing swarms in fluid flows is of significant importance for biomedical or lab-on-chip applications. Here, the upstream mobility and swarm formation of light driven micromotors in microchannel flows is demonstrated with maximum speeds around 0.1 mm s-1. Additionally, the light actuated microrobots operate in fairly low concentrations of hydrogen peroxide of approximately 1%. The micromotors form swarms at the boundary of the locally applied light pattern and the swarms can be moved by translating the light up or downstream.

Photoresist Fabrication for High-NA EUV Lithography: Material and Mechanism

Extreme ultraviolet (EUV) lithography is critical for the semiconductor industry nowadays. However, high-numerical aperture (NA) EUV systems face challenges in many areas, especially in photoresists. This paper reviews requirements and recent progress in EUV photoresists for high-NA EUV lithography. The key needs for photoresists include high resolution, low stochastic defects, minimal pattern collapse, and high sensitivity. Proposed solutions involve new photoresist materials and mechanisms, such as metal-containing photoresists, non-chemically amplified photoresists and tin-oxo cages photoresists. Basic fabrication and processing procedures are also discussed. Other than photoresists, the weak EUV light source also heavily restrains the development of photoresists. In the future, improvements in EUV light sources and patterning techniques will further help high-NA EUV photoresist development. In summary, the realization of high-NA EUV lithography system depends critically on the breakthrough of photoresists, while solutions are emerging to meet demanding requirements from various directions. Overall, these results shed light on guiding further exploration of next generation lithography.

Effect of Gap Width on the Distance between Bright Patterns in Yellow

This research aims to determine the effect of gap width on the distance between bright patterns in the yellow color experiment. This research was carried out in a virtual laboratory, with the method used is a quantitative method with an experimental method, namely the method used to determine the effect of the independent variable on the dependent variable. Data collection was taken during the practicum using the PhET website in the Wave Interference – Slits section, with yellow light which has a wavelength of around 670-690 nm. The distance between two slits is 1500 nm and three different slit widths are used, namely 500 nm, 600 nm, and 700 nm. This research shows that the smaller the value of the gap width, the greater the value of the dark light pattern. Where, the wider the gap, the denser the light-dark pattern on the screen, and the smaller the gap width, the more sparse the light-dark pattern on the screen. Keywords: Gap Width; PhET; Dark Light Pattern.

Improving Foundation Shade Recommendations using Skin Tone Recognition

As we concentrate on addressing the challenges in responsible beauty product recommendation, particularly when it involves comparing the product’s color with a person’s skin tone, similar as for foundation and robe p conditions. The features uprooted using the prints from illuminated terrain can be largely deceiving or indeed be inharmonious to be compared with the product attributes. Hence bad illumination condition can oppressively degrade quality of the recommendation. We introduce a machine learning frame for illumination assessment which classifies images into having moreover good or bad illumination condition. We also make an automatic stoner guidance tool which informs a stoner holding their camera if their illumination condition is good or bad. This way, the stoner is handed with rapid-fire feedback and can interactively control how the print is taken for their recommendation. Only a many studies are devoted to this problem, substantially due to the lack of dataset that's large, labeled, and different both in terms of skin tones and light patterns. Lack of similar dataset leads to neglecting skin tone diversity. Thus, we begin by constructing a different synthetic dataset that simulates colorful skin tones and light patterns in addition to a being facial image dataset. Next, we train a Convolutional Neural Network (CNN) for illumination assessment that outperforms the being results using the synthetic dataset. Eventually, we dissect how the work improves the shade recommendation for colorful foundation products.

A strontium-rich ultra-metal-poor star in the Atari disc component

ABSTRACT We report on the discovery of the first ultra-metal-poor (UMP) star 2MASS J20500194−6613298 (J2050−6613; [Fe/H] = −4.05) selected from the Gaia BP/RP spectral catalogue that belongs to the ancient Atari disc component. We obtained a high-resolution spectrum for the star with the MIKE spectrograph on the Magellan-Clay telescope. J2050−6613 displays a typical chemical abundance pattern for UMP stars, including carbon and zinc enhancements. In contrast, J2050−6613 shows extremely high [Sr/Fe] and [Sr/Ba] ratios compared to other stars in the [Fe/H] < −4.0 regime. J2050−6613 is most likely an early Population II star that formed from a gas cloud that was chemically enriched by a massive Population III hypernova (E > 1052 erg). Such a Population III core-collapse hypernova could simultaneously explain the origin of the abundance pattern of light and heavy elements of 2MASS J2050−6613 if a large amount of Sr of ∼10−5 M⊙ was produced, possibly by neutrino-driven (wind) ejecta. Therefore, the abundance pattern of 2MASS J2050−6613 places important constraints on Sr-producing nucleosynthesis sources operating in the Atari progenitor at the earliest times.

Sculpting optical fields into caustic patterns based on freeform optics

Manipulating flux transportation of optical fields holds great promise across various kinds of applications, encompassing laser micro-processing, optical trapping, microscopic imaging, and illumination engineering. In recent decades, freeform optics, lauded for its capacity to efficiently control the wavefronts of optical beams with high design freedom, has garnered significant attention as a potent tool for shaping light. Nevertheless, the predominant focus in current research has centered on the development of freeform optical elements (FOEs) tailored to project a designated two-dimensional flux density onto a specific target plane. This limitation confines the potential applications of freeform light shaping optics to a rather restricted domain. Moreover, the constraints imposed by geometric optics pose a further limitation on FOEs, particularly in their ability to sculpt coherent light, such as laser beams, as these are particularly susceptible to diffraction effects. Within the context of this study, we propose a design paradigm that harnesses freeform optics to craft light trajectories in three dimensions. This approach inherently gives rise to caustics, which are singularities within the realm of flux transfer in geometric optics. Crucially, our proposed method yields the capability to generate sharply defined light patterns, empirically giving better results for mitigating diffraction effects in contrast to previous design methodologies, which is observed by experiments. This design philosophy empowers FOEs to undertake new roles and functionalities by shaping caustics. To substantiate the potential of our proposal, we present a diverse array of design examples. These encompass scenarios ranging from the illumination of parallel planes to the sculpting of light propagation into three-dimensional curves, as well as the reshaping of beam intensities with an extended depth of field. We expect that the proposed work can broaden the scope of freeform optics, particularly within non-imaging applications, and propel freeform optical elements into hitherto unexplored territories.

Use of Field Concentration for Electroluminescent Devices

AbstractField concentration is often regarded as a problematic issue in soft electronics applications, especially when using curved electrodes, and in particular, those with sharp edges. However, field concentration can be turned into an advantage with appropriate device design. Herein, the applications of field concentration in hydrogel‐elastomer devices are explored. Three different types of electroluminescent hydrogel‐elastomer devices are fabricated using different types of electrodes and different light patterns. In addition, the effect of the field concentration can be extended into the bulk of the elastomer by preparing porous silicone elastomers and filling them with silicone oil. These devices are shown to be flexible and possess both good luminance and a long lifetime.

Photonics in Multimaterial Lateral Heterostructures Combining Group IV Chalcogenide van der Waals Semiconductors.

Lateral heterostructures combining two multilayer group IV chalcogenide van der Waals semiconductors have attracted interest for optoelectronics, twistronics, and valleytronics, owing to their structural anisotropy, bulk-like electronic properties, enhanced optical thickness, and vertical interfaces enabling in-plane charge manipulation/separation, perpendicular to the trajectory of incident light. Group IV monochalcogenides support propagating photonic waveguide modes, but their interference gives rise to complex light emission patterns throughout the visible/near-infrared range both in uniform flakes and single-interface lateral heterostructures. Here, this work demonstrates the judicious integration of pure and alloyed monochalcogenide crystals into multimaterial heterostructures with unique photonic properties, notably the ability to select photonic modes with targeted discrete energies through geometric factors rather than band engineering. SnS-GeS1-xSex-GeSe-GeS1-xSex heterostructures with a GeS1-xSex active layer sandwiched laterally between GeSe and SnS, semiconductors with similar optical constants but smaller bandgaps, were designed and realized via sequential vapor transport synthesis. Raman spectroscopy, electron microscopy/diffraction, and energy-dispersive X-ray spectroscopy confirm a high crystal quality of the laterally stitched components with sharp interfaces. Nanometer-scale cathodoluminescence spectroscopy provides evidence for a facile transfer of electron-hole pairs across the lateral interfaces and demonstrates the selection of photon emission at discrete energies in the laterally embedded active (GeS1- xSex) part of the heterostructure.

CFD and radiation field modeling of the NETmix milli-photocatalytic reactor: Evaluation of illumination systems composed of LEDs with distinct view angles

The coupling of ray tracing and computational fluid dynamics simulations was explored for the NETmix milli-photoreactor. Three LEDs plates composed of 15 inline LEDs were simulated and the LEDs-to-reactor distance varied. The radiation field obtained through ray tracing was incorporated into CFD simulations to elucidate the impact of LEDs light distribution patterns on the reactor performance. The employed LEDs emitted the same amount of power with the same light spectrum in all cases. The evaluated LEDs present a 48∘, 63∘ and 120∘ view angle. The impact of the distinct radiation fields on the photocatalytic oxidation of the n-decane over a thin TiO2 catalyst film was elucidated. Power absorption efficiency, homogeneity index, global illumination efficiency and the pollutant conversion were evaluated for each of the proposed illumination systems. The registered irradiance values varied from 154 W m−2 to 331 W m−2 with homogeneity indexes between 28.4% and 73.1%. Simulations have shown the dependency of the photocatalytic process on the homogeneity of the radiation field and how LED source selection is an important step in the modeling of photoreactors. The characteristics of the LEDs lamps had a significant impact on the pollutant degradation results.

OpenSVBRDF: A Database of Measured Spatially-Varying Reflectance

We present the first large-scale database of measured spatially-varying anisotropic reflectance, consisting of 1,000 high-quality near-planar SVBRDFs, spanning 9 material categories such as wood, fabric and metal. Each sample is captured in 15 minutes, and represented as a set of high-resolution texture maps that correspond to spatially-varying BRDF parameters and local frames. To build this database, we develop a novel integrated system for robust, high-quality and -efficiency reflectance acquisition and reconstruction. Our setup consists of 2 cameras and 16,384 LEDs. We train 64 lighting patterns for efficient acquisition, in conjunction with a network that predicts per-point reflectance in a neural representation from carefully aligned two-view measurements captured under the patterns. The intermediate results are further fine-tuned with respect to the photographs acquired under 63 effective linear lights, and finally fitted to a BRDF model. We report various statistics of the database, and demonstrate its value in the applications of material generation, classification as well as sampling. All related data, including future additions to the database, can be downloaded from https://opensvbrdf.github.io/.

Measurement of Three-Dimensional Back Shape of Normal Adults Using a Novel Three-Dimensional Imaging Mobile Surface Topography System (MSTS): An Intra- and Inter-Rater Reliability Study

Postural and spinal deformities are major contributing factors to musculoskeletal (MSK) disorders. Posture screening and assessment can help to identify early morphological deformities, thereby preventing progression and reducing or correcting them with effective treatments. The study evaluates both intra- and inter-repeatability of using a mobile structured light sensor with a structured light pattern for building an accurate 3D human model and its use in postural screening. 16 young males (age: 25 ± 5.6 years, height: 172 ± 5.3 cm, mass: 69 ± 8.6 kg) participated without any musculoskeletal pain or pre-existing leg or spinal abnormalities. An iPad-based 3D mobile scanning tool, Structure SensorTM (2018 version), was used to capture the participants’ back and whole-body shape. The collected data (3D model) were realigned and processed in the open-source software, Netfabb BasicTM (7.2 version). For each participant, five trained raters individually measured three trials of standing back and body posture on two separate occasions to calculate both intra- and inter-rater reliability. With the use of this software, nine postural variables and angular displacements were individually measured by the raters. The results indicated good to excellent intra-rater and good to moderate inter-rater reliability for measuring 78% (7 out of 9) of postural variables with an ICC ranging from 0.70 to 0.98. The remaining 22% of variables (2 out of 9; lateral pelvic tilt and right frontal knee angle) showed moderate to low inter- and intra-rater reliability, with ICCs ranging from 0.26 to 0.79.