Miracle-dz/UniFAR-FTUs huggingface dataset:
Deriving Wheat Crop Productivity Indicators Using Sentinel-1 Time Series

High-frequency Earth observation (EO) data have been shown to be effective in identifying crops and monitoring their development. The purpose of this paper is to derive quantitative indicators of crop productivity using synthetic aperture radar (SAR). This study shows that the field-specific SAR time series can be used to characterise growth and maturation periods and to estimate the performance of cereals. Winter wheat fields on the Rothamsted Research farm in Harpenden (UK) were selected for the analysis during three cropping seasons (2017 to 2019). Average SAR backscatter from Sentinel-1 satellites was extracted for each field and temporal analysis was applied to the backscatter cross-polarisation ratio (VH/VV). The calculation of the different curve parameters during the growing period involves (i) fitting of two logistic curves to the dynamics of the SAR time series, which describe timing and intensity of growth and maturation, respectively; (ii) plotting the associated first and second derivative in order to assist the determination of key stages in the crop development; and (iii) exploring the correlation matrix for the derived indicators and their predictive power for yield. The results show that the day of the year of the maximum VH/VV value was negatively correlated with yield (r = −0.56), and the duration of “full” vegetation was positively correlated with yield (r = 0.61). Significant seasonal variation in the timing of peak vegetation (p = 0.042), the midpoint of growth (p = 0.037), the duration of the growing season (p = 0.039) and yield (p = 0.016) were observed and were consistent with observations of crop phenology. Further research is required to obtain a more detailed picture of the uncertainty of the presented novel methodology, as well as its validity across a wider range of agroecosystems.
Patterns of small mammal diversity in fragments of subtropical Interior Atlantic Forest in eastern Paraguay

The deforestation of eastern Paraguay is a relatively recent phenomenon, starting as early as the 1940s. Assuming that larger forest fragments retain mechanisms and patterns of biodiversity resembling the original forests, understanding these patterns is valuable for comparative, management, and conservation purposes. In this study, I document diversity patterns in four of the largest reserves of subtropical rainforest in eastern Paraguay as part of a 3-year field study. Forty grids, totaling 31,600 trap nights per reserve, resulted in 19 captured species. Spearman correlations were used to understand effects of distance to edge, and various diversity metrics and multivariate analyses were implemented to compare assemblages between remnants. Trapping revealed an increase in biodiversity toward forest edges. Medium-sized remnants showed the highest diversity (D) and evenness (J). Statistically significant differences were found between and among forest fragments. Given that biodiversity includes both richness and abundances, high biodiversity metrics are not the best indicator for ecosystem “health,” as population explosions closer to edges result in greater biodiversity. More edge, more biodiversity. Thus, more emphasis needs to be given to understanding the natural history of native fauna and common assemblage patterns when addressing conservation and management strategies.
Influence of jackrabbit density on coyote population change

May coyote (Canis 1utrans) population densities were estimated by three methods on a 700square-mile study area astride the Utah-Idaho state line during 1966 to 1970. Indices of coyote populations in the spring, summer, and fall of the same years, and in the winter of 1963 to 1966, collectively, provided trend information for the period 1963 to 1970. An estimate of the percentage of female coyotes breeding in 1969 was obtained from a February collection of 19 carcasses in a region surrounding the study area. Estimates of litter sizes and percentages of females breeding in the western third of Utah were obtained from records of the Division of Wildlife Services. Coyote food habits were studied from stomach contents of 186 animals collected in the winters of 1967-68, 196S69, and 1969-70; and from 111 scats collected year-round, 196S69. Coyotes in the study area from 196S70 may have numbered somewhere near 200 or more animals in the S years of study. The population declined from its highest index value in 1963 to one-seventh of that value in 1968, then increased substantially in 1969 and 1970. These changes appear to have been correlated with the density of black-tailed jackrabbits (Lepus califorricus ) the previous year. The causal mechanism may in part have been the effect of jackrabbit density ( jackrabbits comprised three-fourths or more of the coyote diet during the period of study) on the coyote reproductive rate, both in terms of litter size and percentage of females breeding. Although most of the observed coyote mortality was man-induced, it represented only a part of the total; hence, the pattern and causes of mortality remain largely unknown. Long-range coyote density appears to be partly a function of the size of the food base, with artificial control doubtlessly playing a part. In this region, where the biota is relatively simple, the jackrabbit constitutes a major part of the food base and therefore is a partial determinant of coyote density. The physiological or behavioral links, or both, are unknown at present. This paper summarizes part of the findings of a long-term study of coyote populations being conducted on a 700-square-mile study area in northwestern Utah and southcentral Idaho. Coyotes in this area have fluctuated markedly from 1963 to 1970, the period for which we have data. The purpose of this paper is to explore the circumstances of these changes and their possible interactions with population changes of black-tailed jackrabbits. The study was conducted in the eastern edge of the Great Basin where jackrabbits are a prominent herbivore, historically subject to marked population changes (Palmer 1897, Nelson
Polarized Trout Epithelial Cells Regulate Transepithelial Electrical Resistance, Gene Expression, and the Phosphoproteome in Response to Viral Infection

The burden of disease is a major challenge in aquaculture production. The fish gill characterized with a large surface area and short route to the bloodstream is a major environmental interface and a significant portal of entry for pathogens. To investigate gill responses to viral infection the salmonid gill cell line RTgill-W1 was stimulated with synthetic dsRNA and the salmonid alphavirus subtype 2 (SAV-2). Epithelial integrity in polarized cells can be measured as transepithelial electrical resistance (TEER) which is defined as the electrical resistance across a cell monolayer. TEER is a widely accepted quantitative measure of cellular integrity of a cell monolayer. TEER increased immediately after stimulation with the synthetic dsRNA, polyinosinic:polycytidylic acid (poly(I:C)). In parallel, tight junction and gene expression of innate immune activation markers was modulated in response to poly(I:C). The SAV-2 virus was found to replicate at a low level in RTgill-W1 cells where TEER was disturbed at an early stage of infection, however, gene expression related to tight junction regulation was not modulated. A strong poly(I:C)-driven antiviral response was observed including increases of Rig-like receptors (RLRs) and interferon stimulating genes (ISGs) mRNAs. At the level of signal transduction, poly(I:C) stimulation was accompanied by the phosphorylation of 671 proteins, of which 390 were activated solely in response to the presence of poly(I:C). According to motif analysis, kinases in this group included MAPKs, Ca2+/calmodulin-dependent kinase (CaMK) and cAMP-dependent protein kinase (PKA), all reported to be activated in response to viral infection in mammals. Results also highlighted an activation of the cytoskeletal organization that could be mediated by members of the integrin family. While further work is needed to validate these results, our data indicate that salmonid gill epithelia has the ability to mount a significant response to viral infection which might be important in disease progression. In vitro cell culture can facilitate both a deeper understanding of the anti-viral response in fish and open novel therapeutic avenues for fish health management in aquaculture.
Block and Lock HIV Cure Strategies to Control the Latent Reservoir

The HIV latent reservoir represents the major challenge to cure development. Residing in resting CD4+ T cells and myeloid cells at multiple locations in the body, including sanctuary sites such as the brain, the latent reservoir is not eliminated by ART and has the ability to reactivate virus replication to pre-therapy levels when ART is ceased. There are four broad areas of HIV cure research. The only successful cure strategy, thus far, is stem cell transplantation using naturally HIV resistant CCR5Δ32 stem cells. A second potential cure approach uses gene editing technology, such as zinc-finger nucleases and CRISPR/Cas9. Another two cure strategies aim to control the HIV reservoir, with polar opposite concepts; The “shock and kill” approach, which aims to “shock” or reactivate the latent virus and then “kill” infected cells via targeted immune responses. Lastly, the “block and lock” approach, which aims to enhance the latent virus state by “blocking” HIV transcription and “locking” the HIV promoter in a deep latent state via epigenetic modifications. “Shock and kill” approaches are a major focus of cure studies, however we predict that the increased specificity of “block and lock” approaches will be required for the successful development of a sustained HIV clinical remission in the absence of ART. This review focuses on the current research of novel “block and lock” approaches being explored to generate an HIV cure via induction of epigenetic silencing. We will also discuss potential future therapeutic delivery and the challenges associated with progressing “block and lock” cure approaches as these move toward clinical trials.
Subsurface Chlorophyll-a Maxima in the Southern Ocean

Our review of the literature has revealed Southern Ocean subsurface chlorophyll-a maxima (SCMs) to be an annually recurrent feature throughout the basin. Most of these SCMs are different to the “typical” SCMs observed in the tropics, which are maintained by the nutrient-light co-limitation of phytoplankton growth. Rather, we have found that SCMs are formed by other processes including diatom aggregation, sea-ice retreat, eddies, subduction events and photo-acclimation. At a local scale, these SCMs can facilitate increased downward carbon export, primary production and food availability for higher trophic levels. A large proportion of Southern Ocean SCMs appear to be sustained by aggregates of large diatoms that form under severe iron limitation in the seasonal mixed layer. The ability of large diatoms to regulate their buoyancy must play a role in the development of these SCMs as they appear to increase buoyancy at the SCM and thus avoid further sinking with the decline of the spring bloom or naturally iron fertilized blooms. These SCMs remain largely unobserved by satellites and it seems that ship-based sampling may not be able to fully capture their biomass. In the context of the Marine Ecosystem Assessment of the Southern Ocean it is important to consider that this phenomenon is missing in our current understanding of Southern Ocean ecology and future climate scenarios. The broader implications of SCMs for Southern Ocean ecology will only be revealed through basin-wide observations. This can only be achieved through an integrated observation system that is able to harness the detailed information encapsulated in ship-based sampling, with the increased observational capacity of fluorometers on autonomous platforms such as those in the biogeochemical Argo (BGC-Argo) and the Marine Mammals Exploring the Ocean Pole to pole (MEOP) programs. The main challenge toward achieving this is the uncertainties associated with translating fluorescence to chlorophyll-a concentrations. Until this translation is resolved, the reporting of subsurface fluorescence maxima (SFMs) in place of SCMs could still yield valuable insights with careful interpretation.
Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series

Differences in topographic structure, vegetation structure, and surface wetness exist between peatland classes, making active remote sensing techniques such as SAR and LiDAR promising for peatland mapping. As the timing of green-up, senescence, and hydrologic conditions vary differently in peatland classes, and in comparison with upland classes, full growing-season time series SAR imagery was expected to produce higher accuracy classification results than using only a few select SAR images. Both interferometric coherence, amplitude and difference in amplitude time series datasets were assessed, as it was hypothesized that these may be able to capture subtle changes in phenology and hydrology, which in turn differentiate classes throughout a growing season. Groups of variables were compared for their effectiveness in Random Forest classification for both Sentinel-1 and Radarsat-2. The Shapley value was used to determine the contribution of each group of variables in thirty scenarios, and Mean Decrease in Accuracy was compared to evaluate its ability to rank variables by relative importance. Despite being dual-pol, the results of classifications using Sentinel-1 coherence (12-day repeat) were significantly better than using fully polarimetric RADARSAT-2 coherence (24-day repeat), likely owing to the difference in baseline and specific acquisition dates of the data in this study. Overall, full growing season Sentinel-1 coherence time series produced higher accuracy results than fully polarimetric quad pol RADARSAT-2 coherence amplitude, difference in amplitude and polarimetric decomposition time series. Using a full growing season of time-series imagery in classification resulted in higher accuracy than using a few dates over a growing season. Using mean decrease in accuracy to rank and reduce variables resulted in a weaker classification than if the entire time series is used.
Selection for High Egg Testosterone and Immune Response of Young Japanese Quail under Mild Food Restriction

Maternal androgens link the mother and her progeny and can shape postnatal growth and development. However, the positive effects of prenatal androgens are likely to be balanced by negative impacts on other fitness related traits, such as immune defence, especially when animals are subjected to unfavourable environmental conditions (e.g. a food shortage). To examine these relationships, we investigated the effects of genetic selection on high (HET) and low (LET) egg testosterone content in Japanese quail on the immune system under mild food restriction. To test immune response, we examined: (1) skin swelling after subcutaneous phytohaemagglutinine injection; and (2) acute phase response in reaction to intraperitoneal lipopolysaccharide (LPS) administration. Food restriction decreased body mass in comparison with ad libitum fed animals, but food restriction did not diminish the positive influence of increased maternal testosterone (mT) on body growth. Furthermore, three hours after LPS injection, plasma corticosterone levels and heterophil/lymphocyte ratio were not affected by increased mT. In fact, cell mediated immunity was enhanced in the HET as compared to the LET line. Thus, our data indicate no trade-off between growth rate and immune response in young quail hatched from eggs with high mT, even under conditions of mild food deficiency.
Crop Mapping from Sentinel-1 Polarimetric Time-Series with a Deep Neural Network

Timely and accurate agricultural information is essential for food security assessment and agricultural management. Synthetic aperture radar (SAR) systems are increasingly available in crop mapping, as they provide all-weather imagery. In particular, the Sentinel-1 sensor provides dense time-series data, thus offering a unique opportunity for crop mapping. However, in most studies, the Sentinel-1 complex backscatter coefficient was used directly which limits the potential of the Sentinel-1 in crop mapping. Meanwhile, most of the existing methods may not be tailored for the task of crop classification in time-series polarimetric SAR data. To solve the above problem, we present a novel deep learning strategy in this research. To be specific, we collected Sentinel-1 time-series data in two study areas. The Sentinel-1 image covariance matrix is used as an input to maintain the integrity of polarimetric information. Then, a depthwise separable convolution recurrent neural network (DSCRNN) architecture is proposed to characterize crop types from multiple perspectives and achieve better classification results. The experimental results indicate that the proposed method achieves better accuracy in complex agricultural areas than other classical methods. Additionally, the variable importance provided by the random forest (RF) illustrated that the covariance vector has a far greater influence than the backscatter coefficient. Consequently, the strategy proposed in this research is effective and promising for crop mapping.
A Deep Learning Approach for Burned Area Segmentation with Sentinel-2 Data

Wildfires have major ecological, social and economic consequences. Information about the extent of burned areas is essential to assess these consequences and can be derived from remote sensing data. Over the last years, several methods have been developed to segment burned areas with satellite imagery. However, these methods mostly require extensive preprocessing, while deep learning techniques—which have successfully been applied to other segmentation tasks—have yet to be fully explored. In this work, we combine sensor-specific and methodological developments from the past few years and suggest an automatic processing chain, based on deep learning, for burned area segmentation using mono-temporal Sentinel-2 imagery. In particular, we created a new training and validation dataset, which is used to train a convolutional neural network based on a U-Net architecture. We performed several tests on the input data and reached optimal network performance using the spectral bands of the visual, near infrared and shortwave infrared domains. The final segmentation model achieved an overall accuracy of 0.98 and a kappa coefficient of 0.94.
Ionospheric S4 Scintillations from GNSS Radio Occultation (RO) at Slant Path

Ionospheric scintillation can significantly degrade the performance and the usability of space-based communication and navigation signals. Characterization and prediction of ionospheric scintillation can be made from the Global Navigation Satellite System (GNSS) radio occultation (RO) technique using the measurement from a deep slant path where the RO tangent height (ht) is far below the ionospheric sources. In this study, the L–band S4 from the RO measurements at ht = 30 km is used to infer the amplitude scintillation on the ground. The analysis of global RO data at ht = 30 km shows that sporadic–E (Es), equatorial plasma bubbles (EPBs), and equatorial spread–F (ESF) produce most of the significant S4 enhancements, although the polar S4 is generally weak. The enhanced S4 is a strong function of local time and magnetic dip angle. The Es–induced daytime S4 tends to have a negative correlation with the solar cycle at low latitudes but a positive correlation at high latitudes. The nighttime S4 is dominated by a strong semiannual variation at low latitudes.
Errata for "Cerebro: A Data System for Optimized Deep Learning Model Selection"

We discovered that there was an inconsistency in the communication cost formulation for the decentralized fine-grained training method in Table 2 of our paper [1]. We used Horovod as the archetype for decentralized fine-grained approaches, and its correct communication cost is higher than what we had reported. So, we amend the communication cost of decentralized fine-grained to [EQUATION]
Vertical distribution of transparent exopolymer particle (TEP) concentration in the oligotrophic western tropical North Pacific

Seawater samples were collected during May−June 2013 from 32 stations west of Guam (10° 30’ N−16° N, 140° 30’ E−144° E) at depths of 5−300 m to describe the vertical profile of transparent exopolymer particle (TEP) concentrations. TEP concentration varied from 18 to 69 μg gum xanthan equivalents per liter, which was a similar level to those observed in other open ocean areas, and the vertical profile of the TEP concentration had a subsurface maximum and minimum which was not associated with phytoplankton abundance. The TEP subsurface maximum occurred from the bottom of the mixed layer to the top of the subsurface chlorophyll maximum (SCM) where dissolved oxygen was supersaturated, indicating that the TEP maximum is produced based on active photosynthesis. The TEP subsurface minimum occurred from the bottom of the SCM to 200 m depth, and was characterized by negative preformed-nitrate water which is produced by decomposition of carbon-rich and nitrogen-poor dissolved organic matter. Additionally, water turbulence, which promotes abiotic TEP production, hardly occurred in the TEP subsurface minimum layer because stratification in this layer was most developed in the vertical profiles. Therefore, our results suggest that the low abiotic TEP production may have induced the TEP minimum. Hence, the TEP concentration in the oligotrophic ocean varied both with phytoplankton activities and also abiotic processes.
Mutualism between Grasses and Grazers: An Evolutionary Hypothesis

Grasses and grazers have evolved mutualism to an extent that one group would not have been possible without the other. The recent discovery (Dyer 1980) that saliva produced by grazers stimulates grass growth is interpreted as a mutualistic adaptation by which both grass and grazer benefit. Other such adaptations include a basal meristem which is out of reach of most grazers, high palatability of grass leaves and shoots and vegetative reproduction, all of which, we suggest, are responses to selection by grazers and which increase the fitness of individual grass plants. Grazers and grasses evolved together in the Miocene. Selection pressure from grazers has produced large, long-lived grasses which are completely adapted to grazing. Grasses do not "defend" themselves from grazers; rather they encourage them, possibly also regulating the level of consumption.