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Achieving long-wavelength infrared (LWIR) cameras with high sensitivity and shorter exposure times faces challenges due to series reflections from high-refractive index lenses within compact optical systems. However, designing effective antireflective coatings to maximize light throughput in these systems is complicated by the limited range of transparent materials available for the LWIR. This scarcity narrows the degrees of freedom in design, complicating the optimization process for a system that aims to minimize the number of physical layers and address the inherent large refractive mismatch from high-index lenses. In this study, we use discrete-to-continuous optimization to design a subwavelength-thick antireflective multilayer coating on high-refractive index Si substrate for LWIR cameras, where the coating consists of few (e.g., five) alternating stacks of high- and low-refractive-index thin films (e.g., Ge-YF3, Ge-ZnS, or ZnS-YF3). Discrete optimization efficiently reveals the configuration of physical layers through binary optimization supported by a machine learning model. Continuous optimization identifies the optimal thickness of each coating layer using the conventional gradient method. As a result, considering the responsivity of a LWIR camera, the discrete-to-continuous strategy finds the optimal design of a 2.3-μm-thick antireflective coating on Si substrate consisting of five physical layers based on the Ge-YF3 high-low index pair, showing an average reflectance of 0.54 % within the wavelength range of 8–13 μm. Moreover, conventional thin-film deposition (e.g., electron-beam evaporator) techniques successfully realize the designed structure, and Fourier-transform infrared spectroscopy (FTIR) and thermography confirm the high performance of the antireflective function.

The mycolic acid layer of the Mycobacterium tuberculosis cell wall is essential for viability and virulence, and the enzymes responsible for its synthesis are targets for antimycobacterial drug development. Polyketide synthase 13 (Pks13) is a module encoding several enzymatic and transport functions that carries out the condensation of two different long-chain fatty acids to produce mycolic acids. We determined structures by cryogenic-electron microscopy of dimeric multi-enzyme Pks13 purified from mycobacteria under normal growth conditions, captured with native substrates. Structures define the ketosynthase (KS), linker and acyl transferase (AT) domains at 1.8 Å resolution and two alternative locations of the N-terminal acyl carrier protein. These structures suggest intermediate states on the pathway for substrate delivery to the KS domain. Other domains, visible at lower resolution, are flexible relative to the KS-AT core. The chemical structures of three bound endogenous long-chain fatty acid substrates were determined by electrospray ionization mass spectrometry.

Passive radiative cooling has emerged as a sustainable energy-saving solution, characterized by its energy-free operation and absence of carbon emissions. Conventional radiative coolers are designed with a skyward orientation, allowing for efficient heat dissipation to the cold heat sink. However, this design feature presents challenges when installed on vertical surfaces, as nearby objects obstruct heat release by blocking the cooler’s skyward view. Here, we introduce a directional radiative cooling glass (DRCG) designed to facilitate efficient heat dissipation through angular selective emission. The DRCG is constructed as a multilayer structure incorporating epsilon-near-zero materials, specifically Si3N4 and Al2O3, layered on an indium-tin-oxide thermal reflector. This innovative design restricts thermal emission to specific angular ranges, known as the Berreman mode. Additionally, the transparent layers enable a visible transmittance exceeding 84 %. Theoretical simulations validate the enhanced cooling performance of the DRCG, exhibiting a temperature reduction of over 1.5 °C compared with conventional glass in hot urban environments characterized by a nearby object temperature exceeding 60 °C and a sky view factor of 0.25. Furthermore, outdoor experiments demonstrate that employing the DRCG as a window enhances space-cooling performance by ∼1.5 °C. These findings underscore the potential of transparent energy-saving windows in mitigating the urban heat island effect.

Solar reflectance and thermal emissivity are critical benchmarks for evaluating the effectiveness of passive cooling strategies. The integration of three-dimensional (3D) printing techniques with passive cooling materials enables local thermal management of multifaceted objects, offering opportunities for unexplored energy-saving applications. For example, conformal printing of cooling materials can mitigate solar absorption caused by the top metal electrodes in solar cells, thereby improving their efficiency and lifetime. In this study, we report the synthesis of 3D printable hollow silica nanoparticles (HSNPs) designed to induce subambient cooling performance under daylight conditions. HSNPs with diameters of 400–700 nm and silica shell thicknesses of approximately 100 nm were synthesized using an in-situ sol–gel emulsion method. Subsequently, these HSNPs were formulated into printable pastes by carefully selecting the mixture concentration and molecular weight of polyvinylpyrrolidone (PVP). The PVP-linked HSNPs exhibited a solar (0.3–2.5 μm) reflectivity of 0.98 and a thermal (8–13 μm) emissivity of 0.93. In contrast to a single silica nanoparticle (NP), the scattering analysis of a single HSNP revealed a distinctive scattering distribution characterized by amplified backward scattering and suppressed forward scattering. In outdoor daytime experiments, the HSNP-printed sample led to the subambient cooling of a dielectric substrate, surpassing the cooling performance of reference materials such as silica NPs, silver pastes, and commercial white plastics and paints.

To date, various optimization algorithms have been used to design non-intuitive photonic structures with unconventional optical performance. Good training datasets facilitate the optimization process, particularly when an objective function has a non-convex shape containing multiple local optima in a continuous parametric space. Herein, we developed a discrete-to-continuous optimization algorithm and confirmed its validity by designing and fabricating deep-ultraviolet antireflective MgF2/LaF3 multilayers. For discrete optimization, a multilayer was encoded into a binary vector with multiple bits; a 10 nm thick MgF2 or LaF3 layer was assigned a binary digit of 0 or 1, respectively. Using the binary-based training datasets, a factorization machine formulated a surrogate function, which discovered the ground binary vector representing a near-optimal figure of merit. Then, the figure of merit was refined through continuous optimization (e.g., using an interior-point method) of the ground binary vector. MgF2/LaF3 multilayers with a variety of bit levels were created to attain a minimum average angular (0°–45°) reflectance at 193 nm. A MgF2/LaF3 multilayer optimized at ten bits (i.e., a total thickness of approximately 100 nm) yielded an average reflectance of 0.2%, which agreed well with the experimental results. Moreover, an integrated ray-wave optics simulation predicted that a single CaF2 plano-convex lens coated with the optimized multilayer could exhibit a transmittance of 99.7%. The developed optimization approach will be widely applicable to any photonic structures that can represent a binary vector with multiple bits, such as microwave metasurfaces, in addition to being useful for producing ideal optical multilayers.

Background Objectives Methods Results and Conclusions Comprehensive assessment of skills and performance are necessary to improve the quality of care in nursing education. Various factors pose challenges to accurate assessments, including high student–teacher ratio and observer bias.To establish an assessment system based on first‐person video of smart glasses and validate its usability and feasibility.We used two cameras (smart glasses for first‐person perspective and a web cam) to perform video analysis for skill and performance assessments. Usability tests were conducted using quantitative and qualitative questionnaires for the usefulness and acceptability of the current assessment system. Data from standardised checklists for three clinical nursing skills (intramuscular injection, endotracheal suction, and Levin tube feeding) were used to analyse the inter‐rater reliability in addition to Fleiss' Kappa coefficient analysis. A total of 22 participants (18 students and 4 reviewers) were recruited. They completed the study. Apart from physical discomfort component, the proposed smart glasses‐based first‐person video assessment system achieved good usability scores from both students and reviewers.Fleiss' Kappa values for individual items ranged from 0.450 to 0.808, with an overall average value of 0.592. Results of this study validated the potential of smart glasses‐based assessment system where a set of beneficial mechanisms may meaningfully support the formative learning process. However, issues regarding upgrading the device and need for guidelines for roles of raters and students still remain. [ABSTRACT FROM AUTHOR]

Precise surface reflectance control at specific deep‐ultraviolet (DUV) wavelengths across wide angles is crucial for semiconductor inspection and lithography tools. The inherent challenges in designing DUV antireflective multilayers stem from limited transparent materials and the resultant fabrication complexity owing to numerous interfaces. Here, wide‐angle antireflective multilayers finely tuned to 248 nm designed using an active learning scheme is presented. The active learning scheme employing factorization machines (FM) identifies the optimal configurations for binary‐material‐based multilayers (AlF3/LaF3, AlF3/MgF2, and AlF3/Al2O3) with varying index contrasts, achieving minimal figure‐of‐merit (i.e., average angular reflectance) values at predetermined total thicknesses. High‐index‐contrast AlF3/Al2O3 multilayers are fabricated via atomic layer deposition, thus enabling the conformal coating of high‐numerical‐aperture (NA) lenses with atomic precision. An optimized AlF3/Al2O3 tri‐layer with a total thickness of 180 nm results in an average (0°–45°) reflectance of 0.4% on a CaF2 planar substrate and 0.6% on a CaF2 convex lens (NA = 0.47), similar to the performance of an ideal single‐layer coating requiring a practically unavailable refractive index. Phasor analysis, which considers only first‐order reflections between adjacent layers, supports the benefits of high‐index‐contrast binary materials and the use of the FM‐based active learning scheme in antireflective multilayer design. [ABSTRACT FROM AUTHOR]

Achieving long-wavelength infrared (LWIR) cameras with high sensitivity and shorter exposure times faces challenges due to series reflections from high-refractive index lenses within compact optical systems. However, designing effective antireflective coatings to maximize light throughput in these systems is complicated by the limited range of transparent materials available for the LWIR. This scarcity narrows the degrees of freedom in design, complicating the optimization process for a system that aims to minimize the number of physical layers and address the inherent large refractive mismatch from high-index lenses. In this study, we use discrete-to-continuous optimization to design a subwavelength-thick antireflective multilayer coating on high-refractive index Si substrate for LWIR cameras, where the coating consists of few (e.g., five) alternating stacks of high- and low-refractive-index thin films (e.g., Ge-YF3, Ge-ZnS, or ZnS-YF3). Discrete optimization efficiently reveals the configuration of physical layers through binary optimization supported by a machine learning model. Continuous optimization identifies the optimal thickness of each coating layer using the conventional gradient method. As a result, considering the responsivity of a LWIR camera, the discrete-to-continuous strategy finds the optimal design of a 2.3-μm-thick antireflective coating on Si substrate consisting of five physical layers based on the Ge-YF3 high-low index pair, showing an average reflectance of 0.54 % within the wavelength range of 8–13 μm. Moreover, conventional thin-film deposition (e.g., electron-beam evaporator) techniques successfully realize the designed structure, and Fourier-transform infrared spectroscopy (FTIR) and thermography confirm the high performance of the antireflective function. [ABSTRACT FROM AUTHOR]

Traditionally, crystallographic analysis of macromolecules has depended on large, well-ordered crystals, which often require significant effort to obtain. Even sizable crystals sometimes suffer from pathologies that render them inappropriate for high-resolution structure determination. Here we show that fragmentation of large, imperfect crystals into microcrystals or nanocrystals can provide a simple path for high-resolution structure determination by the cryoEM method MicroED and potentially by serial femtosecond crystallography.

Pregnant women face an increased risk of intimate partner violence (IPV). In addition to the risk of violence faced by women, there is a dual concern for risk of harm to the fetus. Expanding knowledge on childbirth outcomes, other domains of children's development have been examined in recent literature. Yet, there is limited comprehensive knowledge in the area. This scoping review study, informed by ecobiodevelopmental theory, mapped evidence associating prenatal IPV exposure and children's development. We searched eight databases, including PubMed, CINAHL, and ERIC. Thirty-one empirical studies published in English that associated prenatal IPV exposure and children's development were eligible for our review. Included studies were published between 2006 and 2022, with 39% published in the most recent 5 years. Eighteen studies had sample sizes smaller than 500, and 21 were atheoretical; six failed to consider covariates. Reviewed studies showed adverse effects of prenatal IPV exposure on psychological, behavioral, physical health, and physiological outcomes, either directly or indirectly via mechanisms such as maternal behavioral health. Due to inconsistency in results and a lack of empirical evidence, however, social and cognitive outcomes were identified as needing further research to enhance our understanding of the global and domain-specific effects of prenatal IPV exposure. Prospective longitudinal studies, driven by theories of causal mechanisms, which adjust for empirically qualified confounders, will be critical to inform practice and policy to promote healthy development of prenatally IPV-exposed children. Incorporating strengths/asset-focused outcomes and examining contextual factors and sex/gender specific effects may advance the knowledge in this area. [ABSTRACT FROM AUTHOR]

A patterning method termed "RIPPLE" (reactive interface patterning promoted by lithographic electrochemistry) is applied to the fabrication of arrays of dielectric and metallic optical elements. This method uses cyclic voltammetry to impart patterns onto the working electrode of a standard three-electrode electrochemical setup. Using this technique and a template stripping process, periodic arrays of Ag circular Bragg gratings are patterned in a high-throughput fashion over large substrate areas. By varying the scan rate of the cyclically applied voltage ramps, the periodicity of the gratings can be tuned in situ over micrometer and submicrometer length scales. Characterization of the periodic arrays of periodic gratings identified point-like and annular scattering modes at different planes above the structured surface. Facile, reliable, and rapid patterning techniques like RIPPLE may enable the high-throughput and low-cost fabrication of photonic elements and metasurfaces for energy conversion and sensing applications.

BACKGROUND: The in-depth understanding of human anatomy is the foundation for safety in nursing practice. Augmented reality is an emerging technology that can be used for integrative learning in nursing education. OBJECTIVE: The study aimed to develop a human anatomy-based skill training system and pilot test its usability and feasibility. METHODS: Twenty-seven nursing students participated in 3D anatomy-based skill training for intramuscular injection and Levin tube feeding using HoloLens 2. Various user interfaces including pictures, videos, animation graphics, and annotation boxes assisted users with a comprehensive understanding of the step-by-step procedures for these techniques. A one-group pre-post test was conducted to observe changes in skill performance competency, usability, and learning satisfaction. RESULTS: After study participation, a statistically significant improvement in skill performance competency (p < 0.05) was observed. The usability results showed that students were satisfied with the usefulness of the program (9.55 ± 0.49) and scored highly for the intention to participate in other educational programs (9.62 ± 0.59). A high level of learning satisfaction was achieved (9.55 ± 0.49), with positive responses in fostering students' engagement and excitement in the application of cutting-edge technology. CONCLUSION: The 3D anatomy-based nursing skill training demonstrated good potential to improve learning outcomes and facilitate engagement in self-directed practice. This can be integrated into undergraduate nursing education as an assistant teaching tool, contributing to the combination of knowledge and practice. [ABSTRACT FROM AUTHOR]

Background: In a birth-cohort study, we followed offspring with prenatal cocaine exposure (PCE) to investigate longitudinal associations of PCE with self-reported behavioral adjustment from early adolescence to emerging adulthood (EA). Environmental pathways (family functioning, non-kinship care, maltreatment) were specified as potential mediators of PCE. Methods: Participants were 372 (190 PCE; 47% male), primarily Black, low socioeconomic status, enrolled at birth. Internalizing and externalizing behaviors were assessed using Youth Self-Report at ages 12 and 15 and Adult Self-Report at age 21. Extended random-intercept cross-lagged panel modeling was used to account for potential bidirectional relationships between internalizing and externalizing behaviors over time, examining potential mediators. Results: Adjusting for covariates, significant indirect effects were found for each mediator at different ages. For family functioning, these were both internalizing (β = 0.83, p = 0.04) and externalizing behaviors (β = 1.58, p = 0.02) at age 12 and externalizing behaviors at age 15 (β = 0.51, p = 0.03); for non-kinship care, externalizing behaviors at ages 12 (β = 0.63, p = 0.02) and 15 (β = 0.20, p = 0.03); and for maltreatment, both internalizing and externalizing behaviors at ages 15 (β = 0.64, p = 0.02 for internalizing; β = 0.50, p = 0.03 for externalizing) and 21 (β = 1.39, p = 0.01 for internalizing; β = 1.11, p = 0.01 for externalizing). Direct associations of PCE with internalizing and externalizing behaviors were not observed, nor cross-lagged relationships between internalizing and externalizing behaviors. Conclusions: Negative associations of PCE with behavioral adjustment persist into EA via environmental pathways, specifying intervention points to disrupt adverse pathways toward healthy development. [ABSTRACT FROM AUTHOR]

BackgroundSkill training in nursing education has been highly dependent on self-training because of Korea’s high student-faculty ratio. Students tend to have a passive attitude in self-practice, and it is hard to expect effective learning outcomes with traditional checklist-dependent self-practice. Smart glasses have a high potential to assist nursing students with timely information, and a hands-free device does not interrupt performance. ObjectiveThis study aimed to develop a smart glass–based nursing skill training program and evaluate its usability and feasibility for the implementation of self-practice. MethodsWe conducted a usability and feasibility study with 30 undergraduate nursing students during a 2-hour open lab for self-practice of core nursing skills, wearing smart glasses for visualized guidance. The usability test was conducted using a 16-item self-reporting questionnaire and 7 open-ended questions. Learning satisfaction was assessed using a 7-item questionnaire. The number of practice sessions was recorded, and perceived competency in core nursing skills was measured before and after the intervention. At the final evaluation, performance accuracy and time consumed for completion were recorded. ResultsSmart glass–assisted self-practice of nursing skills was perceived as helpful, convenient, and interesting. Participants reported improved recollection of sequences of skills, and perceived competency was significantly improved. Several issues were raised by participants regarding smart glasses, including small screen size, touch sensors, fogged lenses with masks, heaviness, and heat after a period of time. ConclusionsSmart glasses have the potential to assist self-practice, providing timely information at students’ own paces. Having both hands free from holding a device, participants reported the convenience of learning as they could practice and view the information simultaneously. Further revision correcting reported issues would improve the applicability of smart glasses in other areas of nursing education.