julilili42/papers huggingface dataset:
Tracking halogen recycling and volatile loss in kimberlite magmatism from Greenland: Evidence from combined F-Cl-Br and δ37Cl systematics
2021-01-10

Kimberlite magmatism occurs as a result of volatile fluxed melting of the convecting upper mantle underlying cratonic lithospheric mantle regions. During passage to the Earth's surface, proto-kimberlite magma can interact with, and assimilate, variably enriched cratonic mantle producing hybrid melts consisting of asthenospheric and cratonic mantle components including contributions from metasomatic domains. The halogen elements (F, Cl, Br, I) and chlorine isotope ratios (37Cl/35Cl) are increasingly used as tracers of recycled crustal materials within the Earth's mantle yet are only rarely reported in analyses of kimberlites. As a result, the origin and distribution of halogens in kimberlite magmas is poorly constrained. Here, we present novel, combined elemental (F, Cl, Br) and isotopic (δ37Cl) halogen data for 14 fresh kimberlite samples from the North Atlantic Craton (NAC) of West and South-West Greenland. The F composition of kimberlites from the NAC appears to be controlled by melting in the convecting upper mantle with minimal effect from interaction with metasomatized lithospheric mantle or volatile loss during or after emplacement. By contrast, Cl and Br in the studied samples have undergone significant devolatilization during kimberlite dyke emplacement and post-emplacement processes, whereby up to 99% of the original halogen budget was removed. Whilst all the studied kimberlites broadly follow the same geochemical pattern, there exists some regional variability in their halogen systematics. The northern NAC kimberlite samples from Majuagaa have mantle-like δ37Cl values of −0.2 to −0.5‰ [versus SMOC (standard mean ocean chloride)]. In contrast, kimberlite dykes from Nigerdlikasik and Pyramidefjeld near the southern craton margin display positive δ37Cl values of +0.4‰ to +1.3‰, in addition to a relative Cl and Br enrichment, which is consistent with the assimilation of recycled crust-derived halogens by the kimberlite magmas. The data support a scenario in which recycled halogens were sampled either from within an OIB-type reservoir in the convecting mantle or through interaction with subduction-modified lithospheric mantle reservoir during eruption. We prefer a scenario in which the ascending kimberlite magmas assimilated Cl-rich, metasomatized regions within cratonic mantle lithosphere.
Yolo+FPN: 2D and 3D Fused Object Detection With an RGB-D Camera
2021-01-10

In this paper we propose a new deep neural network system, called Yolo+FPN, which fuses both 2D and 3D object detection algorithms to achieve better real-time object detection results and faster inference speed, to be used on real robots. Finding an optimized fusion strategy to efficiently combine 3D object detection with 2D detection information is useful and challenging for both indoor and outdoor robots. In order to satisfy real-time requirements, a trade-off between accuracy and efficiency is needed. We not only have improved training and test accuracies and lower mean losses on the KITTI object detection benchmark comparing with our baseline method, but also achieve competitive average precision on 3D detection of all classes in three levels of difficulty comparing with other state-of-the-art methods. Also, we implemented Yolo+FPN system using an RGB-D camera, and compared the speed of object detection using different GPUs. For the real implementation of both indoor and outdoor scenes, we focus on person detection, which is the most challenging and important among the three classes.
Learning Parameter Distributions to Detect Concept Drift in Data Streams
2021-01-10

Data distributions in streaming environments are usually not stationary. In order to maintain a high predictive quality at all times, online learning models need to adapt to distributional changes, which are known as concept drift. The timely and robust identification of concept drift can be difficult, as we never have access to the true distribution of streaming data. In this work, we propose a novel framework for the detection of real concept drift, called ERICS. By treating the parameters of a predictive model as random variables, we show that concept drift corresponds to a change in the distribution of optimal parameters. To this end, we adopt common measures from information theory. The proposed framework is completely model-agnostic. By choosing an appropriate base model, ERICS is also capable to detect concept drift at the input level, which is a significant advantage over existing approaches. An evaluation on several synthetic and real-world data sets suggests that the proposed framework identifies concept drift more effectively and precisely than various existing works.
FourierNet: Compact Mask Representation for Instance Segmentation Using Differentiable Shape Decoders
2021-01-10

We present FourierNet, a single shot, anchor-free, fully convolutional instance segmentation method that predicts a shape vector. Consequently, this shape vector is converted into the masks' contour points using a fast numerical transform. Compared to previous methods, we introduce a new training technique, where we utilize a differentiable shape decoder, which manages the automatic weight balancing of the shape vector's coefficients. We used the Fourier series as a shape encoder because of its coefficient interpretability and fast implementation. FourierNet shows promising results compared to polygon representation methods, achieving 30.6 mAP on the MS COCO 2017 benchmark. At lower image resolutions, it runs at 26.6 FPS with 24.3 mAP. It reaches 23.3 mAP using just eight parameters to represent the mask (note that at least four parameters are needed for bounding box prediction only). Qualitative analysis shows that suppressing a reasonable proportion of higher frequencies of Fourier series, still generates meaningful masks. These results validate our understanding that lower frequency components hold higher information for the segmentation task, and therefore, we can achieve a compressed representation. Code is available at: github.com/cogsys-tuebingen/FourierNet.
Aggregating Dependent Gaussian Experts in Local Approximation
2021-01-10

Distributed Gaussian processes (DGPs) are prominent local approximation methods to scale Gaussian processes (GPs) to large datasets. Instead of a global estimation, they train local experts by dividing the training set into subsets, thus reducing the time complexity. This strategy is based on the conditional independence assumption, which basically means that there is a perfect diversity between the local experts. In practice, however, this assumption is often violated, and the aggregation of experts leads to sub-optimal and inconsistent solutions. In this paper, we propose a novel approach for aggregating the Gaussian experts by detecting strong violations of conditional independence. The dependency between experts is determined by using a Gaussian graphical model, which yields the precision matrix. The precision matrix encodes conditional dependencies between experts and is used to detect strongly dependent experts and construct an improved aggregation. Using both synthetic and real datasets, our experimental evaluations illustrate that our new method outperforms other state-of-the-art (SOTA) DGP approaches while being substantially more time-efficient than SOTA approaches, which build on independent experts.
Shape Consistent 2D Keypoint Estimation under Domain Shift
2021-01-10

Recent unsupervised domain adaptation methods based on deep architectures have shown remarkable performance not only in traditional classification tasks but also in more complex problems involving structured predictions (e.g. semantic segmentation, depth estimation). Following this trend, in this paper we present a novel deep adaptation framework for estimating keypoints under domain shift}, i.e. when the training (source) and the test (target) images significantly differ in terms of visual appearance. Our method seamlessly combines three different components: feature alignment, adversarial training and self-supervision. Specifically, our deep architecture leverages from domain-specific distribution alignment layers to perform target adaptation at the feature level. Furthermore, a novel loss is proposed which combines an adversarial term for ensuring aligned predictions in the output space and a geometric consistency term which guarantees coherent predictions between a target sample and its perturbed version. Our extensive experimental evaluation conducted on three publicly available benchmarks shows that our approach outperforms state-of-the-art domain adaptation methods in the 2D keypoint prediction task.
Patch-seq: Past, Present, and Future
2021-01-11

Single-cell transcriptomic approaches are revolutionizing neuroscience. Integrating this wealth of data with morphology and physiology, for the comprehensive study of neuronal biology, requires multiplexing gene expression data with complementary techniques. To meet this need, multiple groups in parallel have developed “Patch-seq,” a modification of whole-cell patch-clamp protocols that enables mRNA sequencing of cell contents after electrophysiological recordings from individual neurons and morphologic reconstruction of the same cells. In this review, we first outline the critical technical developments that enabled robust Patch-seq experimental efforts and analytical solutions to interpret the rich multimodal data generated. We then review recent applications of Patch-seq that address novel and long-standing questions in neuroscience. These include the following: (1) targeted study of specific neuronal populations based on their anatomic location, functional properties, lineage, or a combination of these factors; (2) the compilation and integration of multimodal cell type atlases; and (3) the investigation of the molecular basis of morphologic and functional diversity. Finally, we highlight potential opportunities for further technical development and lines of research that may benefit from implementing the Patch-seq technique. As a multimodal approach at the intersection of molecular neurobiology and physiology, Patch-seq is uniquely positioned to directly link gene expression to brain function.
A fungal member of the Arabidopsis thaliana phyllosphere antagonizes Albugo laibachii via a GH25 lysozyme
2021-01-11

Plants are not only challenged by pathogenic organisms but also colonized by commensal microbes. The network of interactions these microbes establish with their host and among each other is suggested to contribute to the immune responses of plants against pathogens. In wild Arabidopsis thaliana populations, the oomycete pathogen Albugo laibachii plays an influential role in structuring the leaf phyllosphere. We show that the epiphytic yeast Moesziomyces bullatus ex Albugo on Arabidopsis, a close relative of pathogenic smut fungi, is an antagonistic member of the A. thaliana phyllosphere, which reduces infection of A. thaliana by A. laibachii . Combination of transcriptomics, reverse genetics, and protein characterization identified a GH25 hydrolase with lysozyme activity as a major effector of this microbial antagonism. Our findings broaden the understanding of microbial interactions within the phyllosphere, provide insights into the evolution of epiphytic basidiomycete yeasts, and pave the way for novel biocontrol strategies.
Longitudinal Monitoring of Lactate in Hospitalized and Ambulatory COVID-19 Patients
2021-01-11

Hypoxemia is readily detectable by assessing SpO2 levels, and these are important in optimizing COVID-19 patient management. Hyperlactatemia is a marker of tissue hypoxia, particularly in patients with increased oxygen requirement and microvascular obstruction. We monitored peripheral venous lactate concentrations in hospitalized patients with moderate to severe COVID-19 (n = 18) and in mild ambulatory COVID-19 patients in home quarantine (n = 16). Whole blood lactate decreased significantly during the clinical course and recovery in hospitalized patients (P = 0.008). The blood lactate levels were significantly higher in hospitalized patients than ambulatory patients (day 1: hospitalized versus ambulatory patients P = 0.002; day 28: hospitalized versus ambulatory patients P = < 0.0001). Elevated lactate levels may be helpful in risk stratification, and serial monitoring of lactate may prove useful in the care of hospitalized COVID-19 patients.
Comparison of four 31P single‐voxel MRS sequences in the human brain at 9.4 T
2021-01-11

Purpose In this study, different single‐voxel localization sequences were implemented and systematically compared for the first time for phosphorous MRS ( 31 P‐MRS) in the human brain at 9.4 T. Methods Two multishot sequences, image‐selected in vivo spectroscopy (ISIS) and a conventional slice‐selective excitation combined with localization by adiabatic selective refocusing (semiLASER) variant of the spin‐echo full intensity–acquired localized spectroscopy (SPECIAL‐semiLASER), and two single‐shot sequences, semiLASER and stimulated echo acquisition mode (STEAM), were implemented and optimized for 31 P‐MRS in the human brain at 9.4 T. Pulses and coil setup were optimized, localization accuracy was tested in phantom experiments, and absolute SNR of the sequences was compared in vivo. The SNR per unit time (SNR/t) was derived and compared for all four sequences and verified experimentally for ISIS in two different voxel sizes (3 × 3 × 3 cm 3 , 5 × 5 × 5 cm 3 , 10‐minute measurement time). Metabolite signals obtained with ISIS were quantified. The possible spectral quality in vivo acquired in clinically feasible time (3:30 minutes, 3 × 3 × 3 cm 3 ) was explored for two different coil setups. Results All evaluated sequences performed with good localization accuracy in phantom experiments and provided well‐resolved spectra in vivo. However, ISIS has the lowest chemical shift displacement error, the best localization accuracy, the highest SNR/t for most metabolites, provides metabolite concentrations comparable to literature values, and is the only one of the sequences that allows for the detection of the whole 31 P spectrum, including β–adenosine triphosphate, with the used setup. The SNR/t of STEAM is comparable to the SNR/t of ISIS. The semiLASER and SPECIAL‐semiLASER sequences provide good results for metabolites with long T 2 . Conclusion At 9.4 T, high‐quality single‐voxel localized 31 P‐MRS can be performed in the human brain with different localization methods, each with inherent characteristics suitable for different research issues.
Genomic vulnerability and socio‐economic threats under climate change in an African rainforest bird
2021-01-11

Abstract Preserving biodiversity under rapidly changing climate conditions is challenging. One approach for estimating impacts and their magnitude is to model current relationships between genomic and environmental data and then to forecast those relationships under future climate scenarios. In this way, understanding future genomic and environmental relationships can help guide management decisions, such as where to establish new protected areas where populations might be buffered from high temperatures or major changes in rainfall. However, climate warming is only one of many anthropogenic threats one must consider in rapidly developing parts of the world. In Central Africa, deforestation, mining, and infrastructure development are accelerating population declines of rainforest species. Here we investigate multiple anthropogenic threats in a Central African rainforest songbird, the little greenbul ( Andropadus virens ). We examine current climate and genomic variation in order to explore the association between genome and environment under future climate conditions. Specifically, we estimate Genomic Vulnerability , defined as the mismatch between current and predicted future genomic variation based on genotype–environment relationships modeled across contemporary populations. We do so while considering other anthropogenic impacts. We find that coastal and central Cameroon populations will require the greatest shifts in adaptive genomic variation, because both climate and land use in these areas are predicted to change dramatically. In contrast, in the more northern forest–savanna ecotones, genomic shifts required to keep pace with climate will be more moderate, and other anthropogenic impacts are expected to be comparatively low in magnitude. While an analysis of diverse taxa will be necessary for making comprehensive conservation decisions, the species‐specific results presented illustrate how evolutionary genomics and other anthropogenic threats may be mapped and used to inform mitigation efforts. To this end, we present an integrated conceptual model demonstrating how the approach for a single species can be expanded to many taxonomically diverse species.
Structural Origin of the Optical Properties of Ag-Doped Fluorophosphate and Sulfophosphate Glasses
2021-01-11

Given the ubiquity of glass formulations that are functionalized with silver compounds, the electronic interaction between isolated silver cations and the glass network deserves more attention. Here, we report the structural origin of the optical properties that result from silver doping in fluorophosphate (PF) and sulfophosphate (PS) glasses. To achieve this, solid-state nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) are combined with optical spectroscopic analysis and physical property measurements. Comparing the <sup>31</sup>P NMR, <sup>27</sup>Al 1d NMR, and <sup>27</sup>Al multi-quantum magic-angle spinning NMR of doped glasses and glasses with large amounts of Ag<sup>+</sup> added, we deduce silver's bonding preference in these mixed-anion aluminophosphate glasses. We show that such understanding provides an explanation for the large Stokes shift observed for Ag<sup>+</sup> in PF and PS glasses, which is related to absorption by the ionic Ag<sup>+</sup>···<sup>-</sup>O-P species and transfer of the excitation energy within more covalently bonded Ag<sub>2</sub>O-like clusters. This is corroborated by DFT calculations, which show that the Ag<sup>+</sup>···<sup>-</sup>O-P and Ag<sup>+</sup>···<sup>-</sup>O-S bonds in corresponding crystals are mostly ionic. The introduction of more silver ions into the crystal structure results in more covalent bonding between Ag<sup>+</sup> and the phosphate matrix.
Climate warming changes synchrony of plants and pollinators
2021-01-11

Abstract Climate warming changes the phenology of many species. When interacting organisms respond differently, climate change may disrupt their interactions and affect the stability of ecosystems. Here, we used GBIF occurrence records to examine phenology trends in plants and their associated insect pollinators in Germany since the 1980s. We found strong phenological advances in plants, but differences in the extent of shifts among pollinator groups. The temporal trends in plant and insect phenologies were generally associated with interannual temperature variation, and thus likely driven by climate change. When examining the synchrony of species-level plant-pollinator interactions, their temporal trends differed among pollinator groups. Overall, plant-pollinator interactions become more synchronized, mainly since the phenology of plants responded more strongly to climate change than that of the pollinators. However, if the observed trends continue, many interactions may become more asynchronous again in the future. Our study suggests that climate change affects the phenologies of both plants and insects, and that it also influences the synchrony of plant-pollinator interactions.
Mapping scientised education in German-American transnational networks after 1945
2021-01-11

This article charts some of the historical paths that have helped bring forth, in late-modern societies, what I call scientised educational discourses and practices. Though the project of forming the ‘scientific man’ can be traced back to the nineteenth century, it is argued that the nature of the project changed once it became aligned with the Cold War sciences, especially cybernetics, computer science and psychology. How former military scientists and researchers from various disciplines generated algorithmic and computational ideas of the human mind that entered the fields of education, teaching and learning during the Cold War era is reconstructed. These ideas not only had a decisive role in shaping scientised subjects such as the lifelong learner, they also inspired the emergence of new scientific disciplines. One example is the field of empirically based educational research in West Germany, which – in its ‘scientised form – was not very well established in West Germany prior to the 1960s.
Late Pleistocene palaeoecology and phylogeography of woolly rhinoceroses
2021-01-11

Abstract The woolly rhinoceros ( Coelodonta antiquitatis ) was a cold-adapted herbivore, widely distributed from western Europe to north-east Siberia during the Late Pleistocene. Previous studies associate the extinction of the species ~14,000 years before present to climatic and vegetational changes, and suggest that later survival of populations in north-east Siberia may relate to the later persistence of open vegetation in that region. Here, we analyzed carbon ( δ 13 C) and nitrogen ( δ 15 N) stable isotopes and mitochondrial DNA sequences to elucidate the evolutionary ecology of the species. Our dataset comprised 286 woolly rhinoceros isotopic records, including 192 unpublished records, from across the species range, dating from &gt;58,600 14 C years to ~14,000 years before present. Crucially, we present the first 71 isotopic records available to date of the 15,000 years preceding woolly rhinoceros extinction. The data reveal ecological flexibility and geographical variation in woolly rhinoceros stable isotope compositions through time. In north-east Siberia, we detected δ 15 N stability through time. This could reflect long-term environmental stability, and might have enabled the later survival of the species in the region. To further investigate the palaeoecology of woolly rhinoceroses, we compared their isotopic compositions with that of other contemporary herbivores. This analysis suggests possible niche partitioning between woolly rhinoceros and both horse ( Equus spp. ) and woolly mammoth ( Mammuthus primigenius ), and isotopic similarities between woolly rhinoceros and both musk ox ( Ovibos moschatus ) and saiga ( Saiga tatarica ) at different points in time. To provide phylogeographical context to the isotopic data, we analyzed 61 published mitochondrial control region sequences. The data show a lack of geographic structuring; we found three haplogroups with overlapping distributions, all of which show a signal of expansion during the Last Glacial Maximum. Furthermore, our genetic findings support the notion that environmental stability in Siberia had an impact on the paleoecology of woolly rhinoceroses in the region. Our study highlights the utility of combining stable isotopic records with ancient DNA to advance our knowledge of the evolutionary ecology of past populations and extinct species.