Intensity Variations Research Articles

Sub-daily scale variations and trends in southwest monsoon rainfall over the West coasts of India and Myanmar

The West Coast of India (WCI) and the West Coast of Myanmar (WCM) receive a good amount of monsoon rainfall due to the orographic lifting and moisture transport from the neighbouring sea. Here, diurnal variation in rainfall amount, frequency, intensity, and contribution during the summer monsoon period was studied using TRMM 3 hourly precipitation data. The analysis was carried out over lowland, midland and highland regions of both the coasts. The subregions exhibit a similar diurnal pattern even though the intensity and frequency of rainfall vary from region to region. Generally, bimodal variations with late afternoon and early morning peaks are found over lowland and midland regions of both WCI and WCM in rainfall frequency, amount and contribution. However, highland regions exhibit unimodal variation with a single late afternoon peak. Over WCI, lowland regions exhibit primary peak during early morning, whereas lowlands of WCM exhibit primary peak during afternoon hours. Rainfall intensity exhibits a different pattern compared to other parameters. Rainfall intensity increases from south to north over both the coasts. Among the subregions, maximum rainfall intensity is found over midlands and minimum over highlands. In general, more rainfall is observed over subregions of WCM than subregions of WCI. Most of the lowland and midland regions, exhibit a significant increasing trend in rainfall frequency and contribution at morning hours and a significant decreasing trend at afternoon hours. Rainfall frequency exhibit different periodicities during different time indicating interannual heterogeneity in rainfall. The diurnal pattern of summer monsoon rainfall over the Indian and Myanmar West coasts shows remarkable latitudinal and topographical variations.

Changes in social norms during the early stages of the COVID-19 pandemic across 43 countries

The emergence of COVID-19 dramatically changed social behavior across societies and contexts. Here we study whether social norms also changed. Specifically, we study this question for cultural tightness (the degree to which societies generally have strong norms), specific social norms (e.g. stealing, hand washing), and norms about enforcement, using survey data from 30,431 respondents in 43 countries recorded before and in the early stages following the emergence of COVID-19. Using variation in disease intensity, we shed light on the mechanisms predicting changes in social norm measures. We find evidence that, after the emergence of the COVID-19 pandemic, hand washing norms increased while tightness and punishing frequency slightly decreased but observe no evidence for a robust change in most other norms. Thus, at least in the short term, our findings suggest that cultures are largely stable to pandemic threats except in those norms, hand washing in this case, that are perceived to be directly relevant to dealing with the collective threat.

Probing cell metabolism using the two-photon excitation autofluorescence lifetime of tryptophan.

Compared to intensity detection, fluorescence lifetime has the advantage of being unaffected by variations in excitation intensity, fluorophore concentration, or attenuation due to biological absorption and scattering. In this Letter, to the best of our knowledge, we present the use of the two-photon excitation autofluorescence lifetime imaging of tryptophan (TRP) to probe cell metabolism for the first time. Tests of pure chemical samples showed that the fluorescence lifetime of TRP was highly sensitive to changes in molecular conformation and the environment. In in vitro cell experiments, we successfully utilized the fluorescence lifetime of TRP to distinguish tumor cells from healthy cells, track the therapeutic effect of the tumor immunotherapy drug 1-MT for HeLa cells, and monitor cells in response to carbonyl cyanide 3-chlorophenylhydrazone (CCCP)-induced cell apoptosis. These results reveal that the two-photon excitation autofluorescence lifetime of TRP could be a sensitive natural probe of cell metabolism in living cells.

Assessment of the Spatiotemporal Variability of Urban Heat Island Intensity in Colombo Metropolitan Area


 
 
 During the last few decades, the Colombo Metropolitan Area (CMA) has experienced rapid population growth and unplanned urbanization, resulting in the replacement of natural landcover with more impervious surfaces. The primary approach of current study was to determine the gradients of air temperature and assess the spatiotemporal variation of atmospheric urban heat island (AUHI) intensity in the CMA considering a range of rural sites extending in different radial directions from the urban center. A total of sixteen rural observation sites that extend from an urban center in four directions were selected within the CMA, with four sites 3.5 km apart from each other in any direction. The air temperatures at each site were measured using HOBO UX-100-003 temperature data loggers for an 8-day period from 21st to 28th, of February 2022. The normalized difference vegetation index (NDVI) and normalized difference building index (NDBI) were used to determine the influence of land use/land cover on air temperatures. The results revealed that air temperature had a strong positive correlation with NDBI. Thus, the current study suggests that the impervious surface/s is a significant predictor of air temperature over the study area. The higher air temperatures were observed at the urban center in relation to the selected suburban and rural observation sites. Hence, the current study confirms that AUHI exists within the selected study area over the CMA. It was found that AUHI tends to be present throughout the day in the CMA. However, it becomes strong between 12.00 A.M. and 6.00 A.M and mostly weakens in the late afternoon hours. Furthermore, this study found that the timing and magnitudes of AUHI vary from direction to direction across the study area depending on the site-specific characteristics of the rural observation sites. The current study emphasizes that site-specific land use/land cover characteristics can have a significant impact on the interpretation of UHI study results even within a single metropolitan area. Therefore, taking only one rural site might not be effective in determining the UHI intensity and a range of sites need to be considered (to select from) for in-depth analysis of UHI in any given area. The findings of the current study will provide firsthand knowledge for urban planners to identify future trends in UHI in the CMA and will promote further UHI research in this area.
 Keywords: Rural observation site, Atmospheric urban heat island, Normalized Difference Vegetation Index
 
 

Non‐Destructive Tomographic Nanoscale Imaging of Ferroelectric Domain Walls

AbstractExtraordinary physical properties arise at polar interfaces in oxide materials, including the emergence of 2D electron gases, sheet‐superconductivity, and multiferroicity. A special type of polar interface is ferroelectric domain walls, where electronic reconstruction phenomena can be driven by bound charges. Great progress has been achieved in the characterization of such domain walls and, over the last decade, their potential for next‐generation nanotechnology has become clear. Established tomography techniques, however, are either destructive or offer insufficient spatial resolution, creating a pressing demand for 3D imaging compatible with future fabrication processes. Here, non‐destructive tomographic imaging of ferroelectric domain walls is demonstrated using secondary electrons. Utilizing conventional scanning electron microscopy (SEM), the position, orientation, and charge state of hidden domain walls are reconstructed at distances up to several hundreds of nanometers away from the surface. A mathematical model is derived that links the SEM intensity variations at the surface to the local domain wall properties, enabling non‐destructive tomography with good noise tolerance on the timescale of seconds. The SEM‐based approach facilitates high‐throughput screening of materials with functional domain walls and domain‐wall‐based devices, which is essential for monitoring during the production of device architectures and quality control in real‐time.

Acoustic and Spectral Analysis of Adi Triphthongs

Adi, a zero-resource indigenous tribal language of Arunachal Pradesh, originated in Tibeto-Burman. According to the “UNESCO Atlas of the World's Languages in Danger of 2017” report, Adi is critically endangered. In this research, two new Adi triphthongs, /uai/ [uai] and /oai/ [ɔai], are proposed in the phoneme set of the Adi language. Adi has 51 phonemes, including 14 monophthongs (7 short and 7 long vowels), 19 diphthongs, two triphthongs, and 16 consonants. This research analysed Adi triphthongs’ spectral and acoustic properties, including intensity variation, long-term average spectrum (LTAS), and formant distribution. The mean of the first four formant frequencies of male and female Adi speakers is measured, which may be the identification of these two phones in the Adi speech recognition systems. Four different Adi words for each triphthong are recorded from 68 individual native Adi speakers (32 males and 36 females) in Arunachal Pradesh. This study may be helpful for phonetic modelling to build speech recognition applications for the Adi language.

Directionality of FIV3 ground-motion intensities during the 6 February 2023 Kahramanmaraş, Türkiye earthquake doublet

At present time, ground-motion prediction models neglect the directionality observed in horizontal components of earthquake ground motions, that is, the important changes in ground-motion intensity that occur with changes in azimuth. This study presents an investigation of the directionality of a recently proposed measure of ground-motion intensity during the 6 February 2023, Mw 7.8 Pazarcık and Mw 7.5 Elbistan earthquake doublet in the Kahramanmaraş region of Türkiye, which resulted in the collapse of more than 35,000 buildings and caused almost 60,000 fatalities. The studied intensity measure is referred to as FIV3, which has been shown to be better correlated with structural collapse than the spectral acceleration at the fundamental period of the structure. The improved intensity measure is period-dependent and is computed as the sum of the three largest incremental velocities with the same polarity obtained from the area under segments of a low-pass filtered ground acceleration time series. The following aspects are studied in this article: variation of FIV3 intensity with changes in the orientation; variation of FIV3 intensity with changes in the period of vibration; attenuation of FIV3 intensities with increasing distance; and spatial distribution of the orientation of maximum FIV3 intensity. This study is based on 231 pairs of records from the Mw 7.8 main event and 222 pairs of records from the Mw 7.5 event. Similarly to the directionality of spectral ordinates, it is found that the directionality of FIV3 intensity also increases with increasing period. Strong directionality occurred not only in the near field but up to distances as large as 400 km from the epicenter. The orientation of maximum FIV3 intensity is found to occur close to the transverse orientation, consistent with observations for the orientation of maximum spectral ordinates during strike-slip earthquakes.

The Brown Sugar Mediated Carbon Quantum Dots as a Novel Fluorescence Sensor for Sensitive Detection of Gentamicin and Its Application in Foods.

In this work, a novel fluorescence sensing strategy was proposed for the detection of gentamicin based on fluorescent carbon quantum dots (CQDs) and gold nanoparticles (AuNPs). Herein, the CQDs were green-synthesized for the first time via a one-step hydrothermal method utilizing brown sugar as the precursor. In the presence of citrate-stabilized AuNPs, the fluorescence of CQDs was quenched efficiently. Gentamicin, on the other hand, had a higher affinity for AuNPs and was able to compete with CQDs for a preferential binding to AuNPs, which ultimately led to the aggregation of AuNPs and freeing of CQDs in solution, causing the fluorescence recovery of CQDs. Based on the above phenomenon, the concentrations of gentamicin could be ascertained by detecting the variations in fluorescence intensity of CQDs. This sensing strategy exhibited excellent selectivity in various antibiotics. At the same time, the method displayed outstanding sensitivity for gentamicin, which was successfully applied to real samples detection.

A beta-Poisson model for infectious disease transmission.

Outbreaks of emerging and zoonotic infections represent a substantial threat to human health and well-being. These outbreaks tend to be characterised by highly stochastic transmission dynamics with intense variation in transmission potential between cases. The negative binomial distribution is commonly used as a model for transmission in the early stages of an epidemic as it has a natural interpretation as the convolution of a Poisson contact process and a gamma-distributed infectivity. In this study we expand upon the negative binomial model by introducing a beta-Poisson mixture model in which infectious individuals make contacts at the points of a Poisson process and then transmit infection along these contacts with a beta-distributed probability. We show that the negative binomial distribution is a limit case of this model, as is the zero-inflated Poisson distribution obtained by combining a Poisson-distributed contact process with an additional failure probability. We assess the beta-Poisson model's applicability by fitting it to secondary case distributions (the distribution of the number of subsequent cases generated by a single case) estimated from outbreaks covering a range of pathogens and geographical settings. We find that while the beta-Poisson mixture can achieve a closer to fit to data than the negative binomial distribution, it is consistently outperformed by the negative binomial in terms of Akaike Information Criterion, making it a suboptimal choice on parsimonious grounds. The beta-Poisson performs similarly to the negative binomial model in its ability to capture features of the secondary case distribution such as overdispersion, prevalence of superspreaders, and the probability of a case generating zero subsequent cases. Despite this possible shortcoming, the beta-Poisson distribution may still be of interest in the context of intervention modelling since its structure allows for the simulation of measures which change contact structures while leaving individual-level infectivity unchanged, and vice-versa.

Experimental Study on Runoff and Sediment Production of the Fully Weathered Granite Backfill Slope under Heavy Rain in Longling, Yunnan Province

Heavy or intermittent rainfall can cause slopes to become unstable and erode, resulting in significant damage, loss of life, and destruction of property. Targeted management solutions are based on an analysis of slopes’ flow generation and sediment production patterns during periods of rainfall. This study used a fully granite backfill slope as its research subject and examined the features of slope erosion during intermittent rainfall. We examined the processes of slope flow generation and soil erosion during intermittent rain through indoor artificially simulated rainfall experiments. Three intermittent rainfall events with a 220 mm/h intensity were designed during the experiment. Each rainfall event lasted for 60 min, with an interval of 60 min between the events. By analyzing multiple rainfall events, this study reveals the patterns of runoff and sediment yield on different slopes in response to variations in rainfall intensity and slope gradient. The runoff volume on other slope surfaces exhibits a similar pattern in reaction to changes in rainfall events. As the frequency of rainfall events increases, the surface runoff tends to be higher. Additionally, with variations in slope steepness, the runoff volume generally follows an increasing trend. Notably, the slope with a 20° incline shows the smallest runoff volume. The sediment yield on different slope surfaces gradually increases as the slope increases. In particular, on a 20° slope, the sediment yield experiences a substantial increase, indicating that the impact of the slope on the sediment yield becomes more pronounced. In different rainfall events, the morphology of the slope changes due to the influence of gravity and hydraulics, resulting in oscillations in both the average runoff rate and sediment yield. Furthermore, as the slope steepens, the amplitude of these oscillations increases. The process of slope erosion involves three stages: raindrop splash erosion, runoff erosion, and collapse damage. The sequence of slope damage locations is as follows: footslope, mid-slope, and hilltop. For the backfilled slope of completely weathered granite, the artificial slope can be controlled to around 20°. Erosion on the slope mainly occurs after the formation of gullies, and slope management should focus on preventing gully formation before it happens.

Natural genetic variation in GLK1-mediated photosynthetic acclimation in response to light

BackgroundGOLDEN-like (GLK) transcription factors are central regulators of chloroplast biogenesis in Arabidopsis and other species. Findings from Arabidopsis show that these factors also contribute to photosynthetic acclimation, e.g. to variation in light intensity, and are controlled by retrograde signals emanating from the chloroplast. However, the natural variation of GLK1-centered gene-regulatory networks in Arabidopsis is largely unexplored.ResultsBy evaluating the activities of GLK1 target genes and GLK1 itself in vegetative leaves of natural Arabidopsis accessions grown under standard conditions, we uncovered variation in the activity of GLK1 centered regulatory networks. This is linked with the ecogeographic origin of the accessions, and can be associated with a complex genetic variation across loci acting in different functional pathways, including photosynthesis, ROS and brassinosteroid pathways. Our results identify candidate upstream regulators that contribute to a basal level of GLK1 activity in rosette leaves, which can then impact the capacity to acclimate to different environmental conditions. Indeed, accessions with higher GLK1 activity, arising from habitats with a high monthly variation in solar radiation levels, may show lower levels of photoinhibition at higher light intensities.ConclusionsOur results provide evidence for natural variation in GLK1 regulatory activities in vegetative leaves. This variation is associated with ecogeographic origin and can contribute to acclimation to high light conditions.

Variation of Pain Intensity with Smoking in Knee Osteoarthritis in Males

Background: Knee osteoarthritis is a significant cause of disability, affecting daily living activities predominantly in females but also impacting males. Various factors contribute to its development, including smoking, yet data on its effect on the male population is sparse. Objective: To explore the relationship between smoking and pain intensity in males with moderate-stage knee osteoarthritis. Methods: A cross-sectional study was conducted over six months, enrolling 71 male participants aged 30 to 75 years with grade 2 knee osteoarthritis, diagnosed according to the Kellgren and Lawrence scale. Participants were categorized into smokers and non-smokers. Data on smoking habits and pain severity, assessed using the numeric pain rating scale, were collected through questionnaires. The association between smoking and pain intensity was analyzed using the Pearson Chi-square test, with a significance level set at P<0.05. Results: Out of 71 participants, 36 (50.7%) were smokers, and 35 (49.3%) were non-smokers. Severe pain was reported by 25 smokers, while 26 non-smokers experienced moderate pain. The analysis revealed a significant association between smoking and increased pain severity (P<0.05), with a direct correlation between the number of cigarettes smoked and pain intensity. Conclusion: The study identified a significant association between smoking and higher pain intensity in male patients with knee osteoarthritis. These findings suggest that smoking cessation should be a key component of osteoarthritis management strategies to alleviate pain and improve quality of life in affected individuals.

Distributed Acoustic Sensing for Crowd Motion and Firecracker Explosions in the Fireworks Show

Abstract Urban seismology has recently emerged as a vibrant scientific field, driven by the growing interest in seismic signals generated by major public events, sports gatherings, and transportation services. However, deploying dense traditional seismometers in economically active, densely populated urban areas with heavy traffic poses significant challenges. In this study, we conducted a field experiment utilizing distributed acoustic sensing (DAS) technology during a fireworks display in Guangzhou on 5 February 2023. About 572 m of optical fiber was turned into 286 seismic sensors and deployed on LingShan Island to monitor various vibration signals generated during the fireworks show. Our analysis revealed substantial correlations between crowd motions during different phases of the event and ambient noise features recorded by DAS. Moreover, the cross-correlation functions of the ambient noise with its dispersion characteristics pointed to near-field pedestrian activity as the primary noise source. Real-time heat maps of human crowd motions were reconstructed from DAS recording, offering significant insights into the variations of activity intensity across different locations. Discerning fireworks events on the DAS array is more effective than on a scattered seismometer array, because it is easier to ensure that the same event is picked for all the sites in the DAS dense linear configuration. The DAS data inspection allowed us to pick up a total of 549 firecracker explosions in comparison to the seismometer data that only allowed us to detect 116 firecracker events. The heights of fireworks were located by the grid-search method and predominantly distributed at 75–300 m, closely aligning with actual fireworks explosion locations. Our findings underscore that the DAS technology can monitor crowd motion and detect vibration signals in the air, bridging the gap between fundamental earth science research and human social activities.

Partitioning intensity inhomogeneity colour images via Saliency-based active contour

Partitioning or segmenting intensity inhomogeneity colour images is a challenging problem in computer vision and image shape analysis. Given an input image, the active contour model (ACM) which is formulated in variational framework is regularly used to partition objects in the image. A selective type of variational ACM approach is better than a global approach for segmenting specific target objects, which is useful for applications such as tumor segmentation or tissue classification in medical imaging. However, the existing selective ACMs yield unsatisfactory outcomes when performing the segmentation for colour (vector-valued) with intensity variations. Therefore, our new approach incorporates both local image fitting and saliency maps into a new variational selective ACM to tackle the problem. The euler-lagrange (EL) equations were presented to solve the proposed model. Thirty combinations of synthetic and medical images were tested. The visual observation and quantitative results show that the proposed model outshines the other existing models by average, with the accuracy of 2.23% more than the compared model and the Dice and Jaccard coefficients which were around 12.78% and 19.53% higher, respectively, than the compared model.

Spatially Uniform and Quantitative Surface-Enhanced Raman Scattering under Modal Ultrastrong Coupling Beyond Nanostructure Homogeneity Limits.

We developed a substrate that enables highly sensitive and spatially uniform surface-enhanced Raman scattering (SERS). This substrate comprises densely packed gold nanoparticles (d-AuNPs)/titanium dioxide/Au film (d-ATA). The d-ATA substrate demonstrates modal ultrastrong coupling between localized surface plasmon resonances (LSPRs) of AuNPs and Fabry-Pérot nanocavities. d-ATA exhibits a significant enhancement of the near-field intensity, resulting in a 78-fold increase in the SERS signal for crystal violet (CV) compared to that of d-AuNP/TiO2 substrates. Importantly, high sensitivity and a spatially uniform signal intensity can be obtained without precise control of the shape and arrangement of the nanoscale AuNPs, enabling quantitative SERS measurements. Additionally, SERS measurements of rhodamine 6G (R6G) on this substrate under ultralow adsorption conditions (0.6 R6G molecules/AuNP) show a spatial variation in the signal intensity within 3%. These findings suggest that the SERS signal under modal ultrastrong coupling originates from multiple plasmonic particles with quantum coherence.

Performance study of ray-based ocean acoustic tomography methods for estimating submesoscale variability in the upper ocean.

Ocean acoustic tomography (OAT) methods aim at estimating variations of sound speed profiles (SSP) based on acoustic measurements between multiple source-receiver pairs (e.g., eigenray travel times). This study investigates the estimation of range-dependent SSPs in the upper ocean over short ranges (<5 km) using the classical ray-based OAT formulation as well as iterative or adaptive OAT formulations (i.e., when the sources and receivers configuration can evolve across successive iterations of this inverse problem). A regional ocean circulation model for the DeSoto Canyon in the Gulf of Mexico is used to simulate three-dimensional sound speed variations spanning a month-long period, which exhibits significant submesoscale variability of variable intensity. OAT performance is investigated in this simulated environment in terms of (1) the selected source-receivers configuration and effective ray coverage, (2) the selected OAT estimator formulations, linearized forward model accuracy, and the parameterization of the expected SSP variability in terms of empirical orthogonal functions, and (3) the duration over which the OAT inversion is performed. Practical implications for the design of future OAT experiments for monitoring submesoscale variability in the upper ocean with moving autonomous platforms are discussed.

Individual factors and vection in younger and older adults: How sex, field dependence, personality, and visual attention do (or do not) affect illusory self-motion.

An important aspect to an immersive experience in Virtual Reality is vection, defined as the illusion of self-motion. Much of the literature to date has explored strategies to maximize vection through manipulations of the visual stimulus (e.g., increasing speed) or the experimental context (e.g., framing of the study instructions). However, the role of individual differences (e.g., age, biological sex) in vection susceptibility has received little attention. The objective of the current study was to investigate the influence of individual-difference factors on vection perception in younger and older adults. Forty-six younger adults (M age = 25.1) and 39 older adults (M age = 72.4) completed assessments of personality traits, field dependence, and visual attention prior to observing a moving visual stimulus aimed at inducing circular vection. Vection was measured using self-reports of onset latency, duration, and intensity. Results indicated that, in both age groups, females experienced longer-lasting vection compared to males. Additionally, the level of field dependence was related to vection intensity and duration in males but not in females. Variability in vection intensity was best explained by a mixture of biological, perceptual, cognitive, and personality variables. Taken together, these findings suggest that individual factors are important for understanding differences in vection susceptibility.

A multiregressed COA-SAM model for predicting seasonal streamflow variability: A case study over Murray river basin

&lt;p&gt;Streamflow of the Murray River (MR) was investigated from 1978 to 2017, using statistical analysis based on Indian Ocean modes of variability. During the cool season, June to August (JJA), observations and reanalysis products have been used to analyse the relation of streamflow of MR with Indian Ocean High (IOH) and Southern Annular Mode (SAM) over South Australia (SA). Recently, the river has suffered from severe drought, whereas drought drivers differ significantly in terms of interannual and decadal timescales. As a defining feature of atmospheric general circulation, the IOH is quantitatively simulated in all global climate models. Variations in the streamflow of MR have been linked to the variability of intensity and positions of Indian Ocean high pressure (IOHP) meridionally and the impact of SAM across the Indian Ocean. It is found that the correlation of streamflow with IOHP is (r = -0.41), SAM (r = -0.52) and shows the strongest correlation with Indian Ocean High Longitude (IOHLN), which is -0.56. Moreover, SAM explains only 27% of streamflow variability, while IOHP and IOHLN indices calculated by the Center of Action (COA) approach explain 39% of the variation. This paper examines the decline of the inflow rate of MR in SA by applying the COA approach, Mann-Kendall (MK) test and Pearson correlation. We further investigate the impact of significant predictors over the flow of MR. Inflow rate of the hydrology of MR is influenced by the period of time, which shows a decreasing trend with -1.976 by applying autocorrelation. Overall, monthly and annual streamflows have also investigated a significant decreasing trend. Cross-correlation is also used to verify the relationship between streamflow and significant predictors of MR.&lt;/p&gt;&#x0D;

Reliable Event Generation With Invertible Conditional Normalizing Flow.

Event streams provide a novel paradigm to describe visual scenes by capturing intensity variations above specific thresholds along with various types of noise. Existing event generation methods usually rely on one-way mappings using hand-crafted parameters and noise rates, which may not adequately suit diverse scenarios and event cameras. To address this limitation, we propose a novel approach to learn a bidirectional mapping between the feature space of event streams and their inherent parameters, enabling the generation of reliable event streams with enhanced generalization capabilities. We first randomly generate a vast number of parameters and synthesize massive event streams using an event simulator. Subsequently, an event-based normalizing flow network is proposed to learn the invertible mapping between the representation of a synthetic event stream and its parameters. The invertible mapping is implemented by incorporating an intensity-guided conditional affine simulation mechanism, facilitating better alignment between event features and parameter spaces. Additionally, we impose constraints on event sparsity, edge distribution, and noise distribution through novel event losses, further emphasizing event priors in the bidirectional mapping. Our framework surpasses state-of-the-art methods in video reconstruction, optical flow estimation, and parameter estimation tasks on synthetic and real-world datasets, exhibiting excellent generalization across diverse scenes and cameras.

Predicting the spatial distribution of wintering golden eagles to inform full annual cycle conservation in western North America.

Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species' habitat preferences vary among seasons, age-classes, geographic regions, or other factors. Conservation of golden eagles (Aquila chrysaetos) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated-winter-and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult "floaters", and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2% contribution), vegetation and landcover (27.9%), topography (14%), climate and weather (9.4%), and ecoregion (8.7%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10% quantile) occurred on private lands (55%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33%), but higher concentration of high-use habitat than expected for their area (1.5-1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.