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Northern Spotted Owls (Strix occidentalis caurina) are of management and conservation concern in the US Pacific Northwest where populations have been monitored since the 1990s using mark-resight methods. Passive acoustic monitoring has the potential to support monitoring efforts; however, its use is currently primarily restricted to determining species presence rather than breeding status. Distinguishing female from male Northern Spotted Owl vocalizations could facilitate determination of pair status using passive acoustic methods, greatly enhancing inference derived from noninvasive monitoring data. In 2017, we deployed 150 autonomous recording units (ARUs) within 30 5-km2 hexagons overlapping recently occupied owl territories in Oregon and Washington, USA, where mark-resight methods were simultaneously occurring. We collected approximately 150,000 hours of recordings and detected 22,458 Northern Spotted Owl vocalizations at 76 ARUs. We summarized vocalizations by call type and found differences in the proportion of call types made by single, paired, and nesting owls. We used expert opinion to classify 2812 four-note location calls as female or male. We summarized inter-sex variation within 19 acoustic attributes of the four-note location call and its subcomponents, and developed a mixed logistic regression model to classify sex based on call-segment acoustic attributes. Males generally called at lower frequencies than females, with mean fundamental frequencies of 556 Hz and 666 Hz, respectively. Male four-note location calls were also longer than female calls, with signal median times of 1.99 s and 1.71 s, respectively. The middle-two-note and the full-call segment of the four-note location call were both useful for classifying sex of the calling owl. Our top-ranked models were able to predict 82–83% of our testing data consistent with expert classification as either male or female with 98–99% accuracy (17–18% of test set was classified as unknown). Our results suggest that acoustic characteristics of Northern Spotted Owl calls captured with ARUs can be used to identify whether sites have males and/or females present, and we suggest that further investigation into the full repertoire of Northern Spotted Owl call types is warranted. Strix occidentalis caurina es una especie de interés para la gestión y conservación en la región noroeste del Pacífico de los EEUU donde sus poblaciones han sido seguidas desde la década de 1990 mediante métodos de marcado y reavistamiento. El monitoreo acústico pasivo tiene el potencial de apoyar los esfuerzos de seguimiento; sin embargo, su uso está principalmente restringido a determinar la presencia de especies en lugar del estatus reproductivo. Distinguir las vocalizaciones entre hembras y machos de S. o. caurina utilizando métodos acústicos pasivos podría facilitar la determinación del estatus de las parejas reproductoras, mejorando ampliamente la inferencia derivada de los datos de seguimiento mediante métodos no invasivos. En 2017, colocamos 150 unidades de grabación autónomas (UGA) dentro de 30 hexágonos de 5 km2 cubriendo los territorios recientemente ocupados por estos búhos en Oregón y Washington, EEUU, donde simultáneamente se utilizaban métodos de marcado y reavistamiento. Colectamos aproximadamente 150,000 horas de grabaciones y detectamos 22,458 vocalizaciones de S. o. caurina en 76 UGAs. Resumimos las vocalizaciones por tipo de llamada y encontramos diferencias en la proporción de tipos de llamadas realizadas por búhos solteros, en parejas y anidando. Utilizamos la opinión de expertos para clasificar 2812 llamadas de ubicación emitidas por machos o por hembras. Resumimos la variación entre sexos considerando 19 atributos acústicos de la llamada de ubicación de cuatro notas y sus subcomponentes, y desarrollamos un modelo de regresión logística mixto para clasificar el sexo en función de los atributos acústicos de segmentos de la llamada. Los machos generalmente cantan a frecuencias más bajas que las hembras, con frecuencias fundamentales medias de 556 Hz y 666 Hz, respectivamente. Las llamadas de ubicación de cuatro notas emitidas por los machos también fueron más largas que las llamadas emitidas por las hembras, con tiempos medios de señal de 1.99 s y 1.71 s, respectivamente. La nota dos del medio y el segmento de llamada completo de la llamada de ubicación de cuatro notas fueron útiles para clasificar el sexo del búho que emite la llamada. Nuestros modelos mejor clasificados fueron capaces de predecir el 82–83% de nuestros datos de testeo de acuerdo con la clasificación de expertos como macho o hembra, con una precisión del 98–99% (17–18% del set de testeo se clasificó como desconocido). Nuestros resultados sugieren que las características acústicas de las llamadas de S. o. caurina registradas con UGAs pueden utilizarse para identificar la presencia de machos y/o hembras en estos sitios. Finalmente, sugerimos que es necesario continuar investigando el repertorio completo de los tipos de llamadas emitidas por S. o. caurina. [Traducción del equipo editorial] [ABSTRACT FROM AUTHOR]

A major challenge for lithium‐ion batteries based on nickel‐rich layered oxide cathodes is capacity fading. While chemo‐mechanical degradation and/or structural transformation are widely considered responsible for degradation, a comprehensive understanding of this process is still not complete. For the stable performance of these cathode materials, aluminium (Al) plays a crucial role, not only as a current collector but also as substitutional element for the transition metals in the cathodes and a protective oxide coating (as Al2O3). However, excess Al can be detrimental due to both its redox inactive nature in the cathode and the insulating nature of Al2O3. In this work, we report an analysis of the Al content in two different types of nickel‐rich manganese cobalt oxide cathode materials after battery cycling. Our results indicate a significant thickening of Al‐containing phases on the surface of the NMC811 electrode. Similar results are observed from commercial batteries (a mixture of NMC532 and LiMn2O4) that were analysed before use and at the end of life, where Al‐containing phases were found to increase significantly at surfaces and grain boundaries. Considering the detrimental effects of the excess Al in the nickel‐rich cathodes, our observation of increased Al content via battery cycling is believed to bring a new perspective to the ongoing discussions regarding the capacity fading phenomenon of nickel‐rich layered oxide materials as part of their complex degradation mechanisms. [ABSTRACT FROM AUTHOR]

Nickel-rich lithium nickel-manganese-cobalt oxide cathodes, in particular Li(Ni0.8Mn0.1Co0.1)O2 (NMC811), are currently being commercialized as next generation cathode materials, due to their increased capacities compared to current materials. Unfortunately, the higher nickel content has been shown to accelerate cell degradation and a better understanding is needed to maximize cell lifetimes. NMC811/graphite cells were tested under stressed conditions (elevated temperature and cell voltages) to accelerate degradation focusing on transition metal (TM) dissolution from the cathode. Increasing the cell temperature, upper cutoff voltage (UCV) and number of cycles all accelerated capacity fade and diffraction studies showed that under stressed conditions, additional degradation mechanisms beyond lithium loss to the SEI are present. Significant TM dissolution and subsequent deposition on the graphite anode is seen, particularly at stressed conditions. The concentration of TMs in the electrolyte remained invariant with cycling conditions, presumably reflecting the limited solubility of these ions and emphasizing the role that TM deposition on the anode plays in continuing to drive dissolution. Significant deposits of metals from the cell casings and current collectors were also detected at all cycling conditions, indicating that corrosion and metal leaching can be as important as TM dissolution from the active material in some cell formats. [ABSTRACT FROM AUTHOR]

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Passive acoustic monitoring is an emerging approach to wildlife monitoring that leverages recent improvements in automated recording units and other technologies. A central challenge of this approach is the task of locating and identifying target species vocalizations in large volumes of audio data. To address this issue, we developed an efficient data processing pipeline using a deep convolutional neural network (CNN) to automate the detection of owl vocalizations in spectrograms generated from unprocessed field recordings. While the project was initially focused on spotted and barred owls, we also trained the network to recognize northern saw‐whet owl, great horned owl, northern pygmy‐owl, and western screech‐owl. Although classification performance varies across species, initial results are promising. Recall, or the proportion of calls in the dataset that are detected and correctly identified, ranged from 63.1% for barred owl to 91.5% for spotted owl based on raw network output. Precision, the rate of true positives among apparent detections, ranged from 0.4% for spotted owl to 77.1% for northern saw‐whet owl based on raw output. In limited tests, the CNN performed as well as or better than human technicians at detecting owl calls. Our model output is suitable for developing species encounter histories for occupancy models and other analyses. We believe our approach is sufficiently general to support long‐term, large‐scale monitoring of a broad range of species beyond our target species list, including birds, mammals, and others. [ABSTRACT FROM AUTHOR]

Nest attendance behaviour in birds is a function of the careful balance between the risk of nest predation and the needs of the parents and nestlings. This attendance must be carefully regulated, as increased parental activity at the nest increases nest predation risk. We tested the long‐standing hypothesis that nest predation risk influences parental behaviour by evaluating the influence of local Marsh Wren Cistothorus palustris density on the off‐bout frequency of Yellow‐headed Blackbirds Xanthocephalus xanthocephalus. Marsh Wren density was negatively correlated with Yellow‐headed Blackbird off‐bout frequency during the morning (05:00–10:00 h) and evening (16:00–21:00 h), suggesting that Yellow‐headed Blackbirds alter their nest attendance behaviour in response to a perceived increased risk of nest predation. We suggest that Yellow‐headed Blackbirds are sensitive to nest predation risk and alter their behaviour accordingly to increase overall fitness, although future research is needed to evaluate the influence of Marsh Wren nest predation on the reproductive success of Yellow‐headed Blackbirds. [ABSTRACT FROM AUTHOR]

Keywords: aluminium coating; Li-ion batteries; layered oxides; NMC811; Ni-rich cathodes EN aluminium coating Li-ion batteries layered oxides NMC811 Ni-rich cathodes 1781 1781 1 12/07/21 20211201 NES 211201 B The Front Cover b demonstrates the impact of Al impurities on the nickel-rich NMC cathodes. Cover Picture: The Complex Role of Aluminium Contamination in Nickel-Rich Layered Oxide Cathodes for Lithium-Ion Batteries (Batteries & Supercaps 12/2021) Aluminium coating, Li-ion batteries, layered oxides, NMC811, Ni-rich cathodes. [Extracted from the article]

• We developed a deep neural network to identify sounds made by 14 animal species. • We built an efficient pipeline for processing large amounts of audio. • Output can be quickly reviewed to produce encounter histories for occupancy analyses. • Identification of multiple species calling simultaneously is less reliable. • We created a desktop app to make this tool accessible to field biologists. The use of passive acoustic monitoring in wildlife ecology has increased dramatically in recent years as researchers take advantage of improvements in autonomous recording units and analytical methods. These technologies have allowed researchers to collect large quantities of acoustic data which must then be processed to extract meaningful information, e.g. target species detections. A persistent issue in acoustic monitoring is the challenge of efficiently automating the detection of species of interest, and deep learning has emerged as a powerful approach to accomplish this task. Here we report on the development and application of a deep convolutional neural network for the automated detection of 14 forest-adapted birds and mammals by classifying spectrogram images generated from short audio clips. The neural network performed well for most species, with precision exceeding 90% and recall exceeding 50% at high score thresholds, indicating high power to detect these species when they were present and vocally active, combined with a low proportion of false positives. We describe a multi-step workflow that integrates this neural network to efficiently process large volumes of audio data with a combination of automated detection and human review. This workflow reduces the necessary human effort by > 99% compared to full manual review of the data. As an optional component of this workflow, we developed a graphical interface for the neural network that can be run through RStudio using the Shiny package, creating a portable and user-friendly way for field biologists and managers to efficiently process audio data and detect these target species close to the point of collection and with minimal delays using consumer-grade computers. [ABSTRACT FROM AUTHOR]

Background: Declines in biodiversity and ecosystem health due to climate change are raising urgent concerns. In response, large-scale multispecies monitoring programmes are being implemented that increasingly adopt sensor-based approaches such as acoustic recording. These approaches rely heavily on ecological data science. However, developing reliable algorithms for processing sensor-based data relies heavily on labelled datasets of sufficient quality and quantity. We present a dataset of 1,575 dawn chorus soundscape recordings, 141 being fully annotated (n = 32,994 annotations) with avian, mammalian and amphibian vocalisations. The remaining recordings were included to facilitate novel research applications. These recordings are paired with 48 site-level climatic, forest structure and topographic covariates. This dataset provides a valuable resource to researchers developing acoustic classification algorithms or studying biodiversity and wildlife behaviour and its relationship to environmental gradients. The dawn chorus recordings were collected as part of a long-term Northern Spotted Owl monitoring program; this demonstrates the complementary value of harnessing existing monitoring efforts to strengthen biodiversity sampling., New Information: This dataset of dawn chorus soundscape recordings is one of the few open-access acoustic datasets annotated with non-biotic and both interspecific (across species) and intraspecific (within species) bird, mammal and amphibian sonotypes and the first that is paired with climatic, forest structure and topographical covariates extracted at recorder locations. This makes it a valuable resource for researchers studying the dawn chorus and its relationship to the environment.

Aging and many illnesses and injuries impair skeletal muscle mass and function, but the molecular mechanisms are not well understood. To better understand the mechanisms, we generated and studied transgenic mice with skeletal muscle-specific expression of growth arrest and DNA damage inducible α (GADD45A), a signaling protein whose expression in skeletal muscle rises during aging and a wide range of illnesses and injuries. We found that GADD45A induced several cellular changes that are characteristic of skeletal muscle atrophy, including a reduction in skeletal muscle mitochondria and oxidative capacity, selective atrophy of glycolytic muscle fibers, and paradoxical expression of oxidative myosin heavy chains despite mitochondrial loss. These cellular changes were at least partly mediated by MAP kinase kinase kinase 4, a protein kinase that is directly activated by GADD45A. By inducing these changes, GADD45A decreased the mass of muscles that are enriched in glycolytic fibers, and it impaired strength, specific force, and endurance exercise capacity. Furthermore, as predicted by data from mouse models, we found that GADD45A expression in skeletal muscle was associated with muscle weakness in humans. Collectively, these findings identify GADD45A as a mediator of mitochondrial loss, atrophy, and weakness in mouse skeletal muscle and a potential target for muscle weakness in humans.

We present a structural and magnetic study of two batches of polycrystalline LiNi 0.8 Mn 0.1 Co 0.1 O 2 (commonly known as Li NMC 811), a Ni-rich Li ion battery cathode material, using elemental analysis, X-ray and neutron diffraction, magnetometry, and polarized neutron scattering measurements. We find that the samples, labeled S1 and S2, have the composition Li 1- x Ni 0.9+ x - y Mn y Co 0.1 O 2 , with x = 0.025(2), y = 0.120(2) for S1 and x = 0.002(2), y = 0.094(2) for S2, corresponding to different concentrations of magnetic ions and excess Ni 2+ in the Li + layers. Both samples show a peak in the zero-field-cooled (ZFC) dc susceptibility at 8.0(2) K, but the temperature at which the ZFC and FC (field-cooled) curves deviate is substantially different: 64(2) K for S1 and 122(2) K for S2. The ac susceptibility measurements show that the transition for S1 shifts with frequency whereas no such shift is observed for S2 within the resolution of our measurements. Our results demonstrate the sample dependence of magnetic properties in Li NMC 811, consistent with previous reports on the parent material LiNiO 2 . We further establish that a combination of experimental techniques is necessary to accurately determine the chemical composition of next-generation battery materials with multiple cations.

We demonstrate the realization of a two-dimensional chiral optical waveguide with an infinite translational symmetry that exhibits asymmetric wave propagation. The low-symmetry geometry of the cross-section that lacks any rotational and mirror symmetries shows in-principal directional asymmetric polarization rotation. We use general symmetry arguments to provide qualitative analysis of the waveguide's eigenstates and numerically corroborate this using finite element simulation. We show that despite the only perturbative break of time-reversal symmetry via small modal losses, the structure supports a non-degenerate pair of co-rotating elliptical modes. We fabricated meters long fiber with a spiral structure and studied its optical properties.

We demonstrate the preparation and transmission of the lowest loss azimuthally polarized TE₀₁₋ like mode in a photonic band gap (PBG) fiber. Using the nature of the mode and the properties of the band gap structure we construct a novel coupler that operates away from the band gap's center to enhance the differential losses and facilitate the radiative loss of hybrid fundamental fiber modes. Remarkably, even though the coupler is highly multimoded, a pure azimuthally polarized mode is generated after only 17 cm. Theoretical calculations verify the validity of this technique and accurately predict the coupling efficiency. The generation and single mode propagation of this unique azimuthally polarized, doughnut shaped mode in a large hollow-core fiber can find numerous applications including in optical microscopy, optical tweezers, and guiding particles along the fiber.

Hollow-core photonic bandgap fibers (PBG) offer the opportunity to suppress highly the optical absorption and nonlinearities of their constituent materials, which makes them viable candidates for transmitting high-peak power pulses. We report the fabrication and characterization of polymer-composite PBG fibers in a novel materials system, polycarbonate and arsenic sulfide glass. Propagation losses for the 60 microm-core fibers are less than 2dB/m, a 52x improvement over previous 1D-PBG fibers at this wavelength. Through preferential coupling the fiber is capable of operating with over 97% the fiber's power output in the fundamental (HE(11)) mode. The fiber transmitted pulses with peak powers of 11.4 MW before failure.