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This paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. This makes it possible to use an electron microscope to image fiber samples corresponding to the sample size using microtomography. Molded samples and pellets of four polyamide-6 short-glass fiber-reinforced composites with mass fractions of 15%, 30%, and 50% were considered. The aspect ratio distribution measured by SEM for the investigated materials was 20.25 with a coefficient of variation of 5.1%. The fiber aspect ratio obtained based on mean field homogenization theory and the tensile curve approximation was underestimated at 13.698 with a coefficient of variation of 5.2%. The deviation between the micro- and macro-estimates can be represented as a mean effective aspect ratio of 68% with a coefficient of variation of 8.5%. The developed technology for preparing samples for SEM and automated image processing can be used to study other short-reinforced polymer composite materials. The obtained estimates can serve as a useful reference when calibrating other models of short-fiber-reinforced polymer materials.

Computer vision technology for the automatic recognition and geometric characterization of carbon and glass fibers in scanning electron microscopy images is proposed. The proposed pipeline, combining the SAM model and DeepLabV3+, provides the generalizability and accuracy of the foundational SAM model and the ability to quickly train on a small amount of data via the DeepLabV3+ model. The pipeline was trained several times more rapidly with lower requirements for computing resources than fine-tuning the SAM model, with comparable inference time. On the basis of the pipeline, an end-to-end technology for processing images of electron microscopic fibers was developed, the input of which is images with metadata and the output of which is statistics on the distribution of the geometric characteristics of the fibers. This innovation is of great practical importance for modeling the physical characteristics of materials. This paper proposes a few-shot training procedure for the DeepLabV3+/SAM pipeline, combining the training of the DeepLabV3+ model weights and the SAM model parameters. It allows effective training of the pipeline using only 37 real labeled images. The pipeline was then adapted to a new type of fiber and background using 15 additional real labeled images. This article also proposes a method for generating synthetic data for training neural network models, which improves the quality of segmentation by the IoU and PixAcc metrics from 0.943 and 0.949 to 0.953 and 0.959, i.e., by 1% on average. The developed pipeline significantly reduces the time required to evaluate fiber length in scanning electron microscope images.

This paper discusses an approach to estimating the parameters of the cohesive zone model (CZM) by mode II by extruding the bushing along the lug axis. This method of evaluation requires small samples, which is particularly relevant when investigating short fiber-reinforced polymers (SFRPs) with additively manufactured embedded elements. Adhesion is investigated on the example of 30% carbon fiber-reinforced polyamide-6 molded to Ti-6Al-4V (VT6) selective laser-melted (SLM) alloy bushing in cases of a roughness Ra = 2.66 μm (vibratory finishing), Ra = 8.79 μm (sandblasting), and Ra = 10.02 (directly from SLM). The values of the maximum equivalent tangential contact stress were in a range from 1.1 MPa to 9.5 MPa, while the critical fracture energy for tangential slip was estimated at 15 N/mm for all cases. Experimental validation of the obtained CZM mode II was carried out by evaluating the load-carrying capacity of the lugs with different bushings. In both the experiment and the calculation, greater bushing roughness provides greater lug load-bearing capacity. The ribbed bushings added significant strength in the experiments, which confirmed the importance of considering the tangential mode in the contact model. The presented models can be used for the preliminary evaluation of short fiber-reinforced polyamide-6 parts with titanium-embedded elements bearing capacity.

A fully developed turbulent flow in a concentric annulus, Re =10,000, ri/ro=0.5, with an inner rotating cylinder in the velocity range N=Uω/Ub=0÷4, is studied via a large-eddy simulation. Also, for comparison, simulations by steady-state, unstatiounary RANS k-ω SST (URANS), and Elliptic Blending Model (EBM) were made. The main focus of this study is on the effect of high rotation on the mean flow, turbulence statistics, and vortex structure. Distribution of the tangential velocity and the Reynolds stress tensor change their behaviour at N>0.5∼1. With rotation increases, the production of tangential fluctuation becomes dominant over axial ones and the position of turbulent kinetic energy maximum shifts towards the wall into the buffer zone. URANS and EBM approaches show good agreement with LES in mean flow, turbulent statistics, and integral parameters. The difference in pressure loss prediction between LES and URANS does not exceed 20%, but the average difference is about 11%. The EBM approach underestimates pressure losses up to 9% and on average not more than 5%. Vortex structures are described well by URANS.

Computer vision technology for the automatic recognition and geometric characterization of carbon and glass fibers in scanning electron microscopy images is proposed. The proposed pipeline, combining the SAM model and DeepLabV3+, provides the generalizability and accuracy of the foundational SAM model and the ability to quickly train on a small amount of data via the DeepLabV3+ model. The pipeline was trained several times more rapidly with lower requirements for computing resources than fine-tuning the SAM model, with comparable inference time. On the basis of the pipeline, an end-to-end technology for processing images of electron microscopic fibers was developed, the input of which is images with metadata and the output of which is statistics on the distribution of the geometric characteristics of the fibers. This innovation is of great practical importance for modeling the physical characteristics of materials. This paper proposes a few-shot training procedure for the DeepLabV3+/SAM pipeline, combining the training of the DeepLabV3+ model weights and the SAM model parameters. It allows effective training of the pipeline using only 37 real labeled images. The pipeline was then adapted to a new type of fiber and background using 15 additional real labeled images. This article also proposes a method for generating synthetic data for training neural network models, which improves the quality of segmentation by the IoU and PixAcc metrics from 0.943 and 0.949 to 0.953 and 0.959, i.e., by 1% on average. The developed pipeline significantly reduces the time required to evaluate fiber length in scanning electron microscope images. [ABSTRACT FROM AUTHOR]

This paper presents a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. The novelty of this work lies in an effective fiber length evaluation based on a comparative analysis of fiber aspect ratios using scanning electron microscopy (SEM) and the mean field homogenization approach. This makes it possible to use an electron microscope to image fiber samples corresponding to the sample size using microtomography. Molded samples and pellets of four polyamide-6 short-glass fiber-reinforced composites with mass fractions of 15%, 30%, and 50% were considered. The aspect ratio distribution measured by SEM for the investigated materials was 20.25 with a coefficient of variation of 5.1%. The fiber aspect ratio obtained based on mean field homogenization theory and the tensile curve approximation was underestimated at 13.698 with a coefficient of variation of 5.2%. The deviation between the micro- and macro-estimates can be represented as a mean effective aspect ratio of 68% with a coefficient of variation of 8.5%. The developed technology for preparing samples for SEM and automated image processing can be used to study other short-reinforced polymer composite materials. The obtained estimates can serve as a useful reference when calibrating other models of short-fiber-reinforced polymer materials. [ABSTRACT FROM AUTHOR]

This paper discusses an approach to estimating the parameters of the cohesive zone model (CZM) by mode II by extruding the bushing along the lug axis. This method of evaluation requires small samples, which is particularly relevant when investigating short fiber-reinforced polymers (SFRPs) with additively manufactured embedded elements. Adhesion is investigated on the example of 30% carbon fiber-reinforced polyamide-6 molded to Ti-6Al-4V (VT6) selective laser-melted (SLM) alloy bushing in cases of a roughness Ra = 2.66 μm (vibratory finishing), Ra = 8.79 μm (sandblasting), and Ra = 10.02 (directly from SLM). The values of the maximum equivalent tangential contact stress were in a range from 1.1 MPa to 9.5 MPa, while the critical fracture energy for tangential slip was estimated at 15 N/mm for all cases. Experimental validation of the obtained CZM mode II was carried out by evaluating the load-carrying capacity of the lugs with different bushings. In both the experiment and the calculation, greater bushing roughness provides greater lug load-bearing capacity. The ribbed bushings added significant strength in the experiments, which confirmed the importance of considering the tangential mode in the contact model. The presented models can be used for the preliminary evaluation of short fiber-reinforced polyamide-6 parts with titanium-embedded elements bearing capacity. [ABSTRACT FROM AUTHOR]

A fully developed turbulent flow in a concentric annulus, Re = 10,000 , r i / r o = 0.5 , with an inner rotating cylinder in the velocity range N = U ω / U b = 0 ÷ 4 , is studied via a large-eddy simulation. Also, for comparison, simulations by steady-state, unstatiounary RANS k- ω SST (URANS), and Elliptic Blending Model (EBM) were made. The main focus of this study is on the effect of high rotation on the mean flow, turbulence statistics, and vortex structure. Distribution of the tangential velocity and the Reynolds stress tensor change their behaviour at N > 0.5 ∼ 1 . With rotation increases, the production of tangential fluctuation becomes dominant over axial ones and the position of turbulent kinetic energy maximum shifts towards the wall into the buffer zone. URANS and EBM approaches show good agreement with LES in mean flow, turbulent statistics, and integral parameters. The difference in pressure loss prediction between LES and URANS does not exceed 20%, but the average difference is about 11%. The EBM approach underestimates pressure losses up to 9% and on average not more than 5%. Vortex structures are described well by URANS. [ABSTRACT FROM AUTHOR]

The loss of autocorrelations of tropical sea surface temperatures (SST) during late spring, also called the spring predictability barrier (SPB), is a factor that strongly limits the predictability of El Nino Southern Oscillation (ENSO), and especially the statistical SST‐based ENSO forecasts starting from the winter‐spring season. Recent studies show that Pacific atmospheric circulation anomalies in winter‐spring may have a long‐term impact on the summer tropical climate via the SST footprint. Here, we infer an index based on sea level pressure (SLP) data from February to March in a single area surrounding Hawaii, and show that this area is the most informative part of the large SLP pattern initiating the SST footprinting mechanism. We then construct a statistically optimal linear model of the Nino 3.4 index taking this atmospheric index as a forcing. We find that this forcing efficiently lowers the SPB and provides significant improvements of interseasonal Niño 3.4 forecasts. Plain Language Summary: Interseasonal forecasting of El Niño Southern Oscillation (ENSO) is in high demand due to the impacts of ENSO on regional climatic conditions around the world as well as the global climate. Improvements in the quality of climate data in recent decades have led to the active use of statistical ENSO models, which compete with physical models in predictive power. The main disadvantage of statistical forecasts is the pronounced seasonal growth of uncertainty when predicting the upcoming summer‐fall ENSO conditions from winter‐spring months; this phenomenon is called the spring predictability barrier (SPB). A number of recent works revealed that winter‐spring atmospheric anomalies can substantially impact the ENSO system through the SPB via a complex atmosphere‐ocean interaction mechanism. Here, we introduce a reliable ENSO predictor constructed from sea level pressure data relating to this mechanism and show that the predictor significantly improves the multimonth (up to 1 year) ENSO forecast by lowering the SPB in a statistical model of the key ENSO index. Key Points: A novel early El Nino Southern Oscillation (ENSO) predictor based on the February–March sea level pressure is introducedSignificant correlations of the predictor with the upcoming summer – next spring ENSO conditions are shownThe predictor significantly improves the interseasonal forecast skills of the statistical Nino 3.4 index model [ABSTRACT FROM AUTHOR]

Annual cycle events may be interlinked, influence following annual cycle stages, and may alter performance of individuals. Such links, called carry-over effects, can explain individual variation in timing or reproductive success in migratory species. Identifying the key links affecting fitness may reveal the mechanisms of species population dynamics but the current evidence for the strongest carry-over effects is equivocal. Here, we aim to assess the carry-over effects in great reed warblers Acrocephalus arundinaceus, a long-distance migratory songbird, using 103 full-annual tracks from three European and two Asian breeding populations. Our results showed strong positive relationships within autumn and spring migration periods and buffering capacity of the non-breeding period preventing events to carry over between these periods. Moreover, we found no profound relation between the non-breeding habitat quality or seasonality (quantified using stable isotopes and remote sensing data) and the timing of spring migration. The strongest carry-over effects occurred in individuals from the southern European breeding population compared to the northern and the central European populations. A moderate relationship between the habitat seasonality during moult and the spring migration timing indicates the importance of the complete moult. The overall weak carry-over effects of non-breeding habitat conditions found in this study contrast with previous results and imply between-species differences in these crucial relationships. Moreover, the population-specific carry-over effects highlight the importance of multi-population approach and advise caution in interpretation of results from single-population studies. Finally, the carry-over effect from the moulting period indicates the significance of a so-far neglected link in the species. Significance statement: Environmental conditions vary in space and time. Therefore, migratory species adjust the timing of migration in order to maximise their fitness. However, the links between annual cycle events in multiple populations and the consequences of environmental conditions outside the breeding range are scarcely known. In this study, we used tracking data of the great reed warbler, an insectivorous bird species breeding across western Eurasia and wintering in Africa, to study a complex system of links between annual events. We found that the strength of these links differed between geographically distinct populations but not between sexes. Moreover, harsh environmental conditions during moult delayed the timing of subsequent events. Our findings could help explain large-scale differences in population size changes observed in some species and highlight the importance of energetically demanding moult period for the life of migratory species. Finally, our results demonstrate the need for multi-population approach in studies on seasonal interactions. [ABSTRACT FROM AUTHOR]

The present paper is the second part of a two-part study on empirical modeling and prediction of climate variability. This paper deals with spatially distributed data, as opposed to the univariate data of Part I. The choice of a basis for effective data compression becomes of the essence. In many applications, it is the set of spatial empirical orthogonal functions that provides the uncorrelated time series of principal components (PCs) used in the learning set. In this paper, the basis of the learning set is obtained instead by applying multichannel singular-spectrum analysis to climatic time series and using the leading spatiotemporal PCs to construct a reduced stochastic model. The effectiveness of this approach is illustrated by predicting the behavior of the Jin-Neelin-Ghil (JNG) hybrid seasonally forced coupled ocean-atmosphere model of El Niño-Southern Oscillation. The JNG model produces spatially distributed and weakly nonstationary time series to which the model reduction and prediction methodology is applied. Critical transitions in the hybrid periodically forced coupled model are successfully predicted on time scales that are substantially longer than the duration of the learning sample. [ABSTRACT FROM AUTHOR]

Hybridization is observed frequently in birds, but often it is not known whether the hybrids are fertile and if backcrossing occurs. The breeding ranges of the great reed warbler (Acrocephalus arundinaceus) and the clamorous reed warbler (A. stentoreus) overlap in southern Kazakhstan and a previous study has documented hybridization in a sympatric population. In the present study, we first present a large set of novel microsatellite loci isolated and characterised in great reed warblers. Secondly, we evaluate whether hybridization in the sympatric breeding population has been followed by backcrossing and introgression. We isolated 181 unique microsatellite loci in great reed warblers. Of 41 loci evaluated, 40 amplified and 30 were polymorphic. Bayesian clustering analyses based on genotype data from 23 autosomal loci recognised two well-defined genetic clusters corresponding to the two species. Individuals clustered to a very high extent to either of these clusters (admixture proportions ⩾0.984) with the exception of four previously suggested arundinaceus-stentoreus hybrid birds that showed mixed ancestry (admixture proportions 0.495-0.619). Analyses of simulated hybrids and backcrossed individuals showed that the sampled birds do not correspond to first-fourth-generation backcrosses, and that fifth or higher generation backcrosses to a high extent resemble 'pure' birds at this set of markers. We conclude that these novel microsatellite loci provide a useful molecular resource for Acrocephalus warblers. The time to reach reproductive isolation is believed to be very long in birds, approximately 5 Myrs, and with an estimated divergence time of 2 Myrs between these warblers, some backcrossing and introgression could have been expected. However, there was no evidence for backcrossing and introgression suggesting that hybrids are either infertile or their progeny inviable. Very low levels of introgression cannot be excluded, which still may be an important factor as a source of new genetic variation. [ABSTRACT FROM AUTHOR]

We here report the finding of ten new specimens of the poorly known large-billed reed warbler Acrocephalus orinus. Preliminary identifications were made on the basis of bill, tarsus and claw measurements, and their specific identity was then confirmed by comparison of partial sequences of the cytochrome b gene with a large data set containing nearly all other species in the genus Acrocephalus, including the type specimen of A. orinus. Five of the new specimens were collected in summer in Afghanistan and Kazakhstan, indicating that the species probably breeds in Central Asia, and the data and moult of the others suggest that the species migrates along the Himalayas to winter in N India and SE Asia. The population structure suggests a stable or shrinking population. [ABSTRACT FROM AUTHOR]

I Avian Diseases i is an international journal dedicated to avian health published by the American Association of Avian Pathologists (AAAP). B Evaluation of Factors That Influence Dose Variability of Marek's Disease Vaccines. b B. López De Juan Abad, A. L. Cortes, M. Correa, and I. M. Gimeno B Transcriptional Analyses of Innate and Acquired Immune Patterning Elicited by Marek's Disease Virus Vaccine Strains: Turkey Herpesvirus (HVT), Marek's Disease Virus 2 (strain SB1), and Bivalent Vaccines (HVT/SB1 and HVT-LT/SB1). b Sabari Nath Neerukonda, Upendra K. Katneni, Nirajan Bhandari, and Mark S. Parcells. [Extracted from the article]

Currently, causes of the middle Pleistocene transition (MPT) – the onset of large-amplitude glacial variability with 100 kyr time scale instead of regular 41 kyr cycles before – are a challenging puzzle in Paleoclimatology. Here we show how a Bayesian data analysis based on machine learning approaches can help to reveal the main mechanisms underlying the Pleistocene variability, which most likely explain proxy records and can be used for testing existing theories. We construct a Bayesian data-driven model from benthic δ18O records (LR04 stack) accounting for the main factors which may potentially impact climate of the Pleistocene: internal climate dynamics, gradual trends, variations of insolation, and millennial variability. In contrast to some theories, we uncover that under long-term trends in climate, the strong glacial cycles have appeared due to internal nonlinear oscillations induced by millennial noise. We find that while the orbital Milankovitch forcing does not matter for the MPT onset, the obliquity oscillation phase-locks the climate cycles through the meridional gradient of insolation. [ABSTRACT FROM AUTHOR]