### Recent Submissions

• #### Multiple wheat genomes reveal global variation in modern breeding

(Nature, Springer Science and Business Media LLC, 2020-11-25) [Article]
AbstractAdvances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome$^{1}$, and the lack of genome-assembly data for multiple wheat lines$^{2,3}$. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses$^{4,5}$. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm1$^{6}$, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.
• #### A Multilayer Nonlinear Elimination Preconditioned Inexact Newton Method for Steady-State Incompressible Flow Problems in Three Dimensions

(SIAM Journal on Scientific Computing, Society for Industrial & Applied Mathematics (SIAM), 2020-11-24) [Article]
We develop a multilayer nonlinear elimination preconditioned inexact Newton method for a nonlinear algebraic system of equations, and a target application is the three-dimensional steady-state incompressible Navier--Stokes equations at high Reynolds numbers. Nonlinear steadystate problems are often more difficult to solve than time-dependent problems because the Jacobian matrix is less diagonally dominant, and a good initial guess from the previous time step is not available. For such problems, Newton-like methods may suffer from slow convergence or stagnation even with globalization techniques such as line search. In this paper, we introduce a cascadic multilayer nonlinear elimination approach based on feedback from intermediate solutions to improve the convergence of Newton iteration. Numerical experiments show that the proposed algorithm is superior to the classical inexact Newton method and other single layer nonlinear elimination approaches in terms of the robustness and efficiency. Using the proposed nonlinear preconditioner with a highly parallel domain decomposition framework, we demonstrate that steady solutions of the Navier--Stokes equations with Reynolds numbers as large as 7,500 can be obtained for the lid-driven cavity flow problem in three dimensions without the use of any continuation methods.
• #### Source Apportionment and Elemental Composition of Atmospheric Total Suspended Particulates (TSP) Over the Red Sea Coast of Saudi Arabia

(Earth Systems and Environment, Springer Science and Business Media LLC, 2020-11-24) [Article]
AbstractThis work presents a comprehensive study on concentrations and elemental composition of total suspended atmospheric particulates for a semi-urban site on the Red Sea coast, and on-board a research vessel, which collected off-shore samples along the Red Sea. We conducted one of the most extended measurement campaigns of atmospheric particulates ever for the region, with continuous measurements over 27 months. The overall mean concentrations (± st. dev.) of TSP were 125 ± 197 µg m$^{−3}$ for the permanent semi-urban site, and 108 ± 193 µg m$^{−3}$ for the off-shore mobile site. The region is frequently severely impacted by both localised and widespread dust storms, which on occasion, can increase atmospheric particulate concentrations to levels above mg m$^{−3}$ (> 1000 µg m$^{−3}$). Median concentrations were not as variable between seasons, indicating a stable, permanent presence of atmospheric particulates independent of the time of year. The primary chemical elements contributing to particulate mass were Na, Ca, S, Al and Fe. We employed Positive Matrix Factorisation (EPA PMF v5.0.14) to identify different major sources of particulates, which were crustal, marine, fuel oil combustion/secondary sulphate and mixed anthropogenic. The crustal source was characterised by tracers Al, Fe, K, Mg and Sn, and was present to some extent in the other identified sources due to the permanent presence of dust particles in the atmosphere. The fuel oil combustion/secondary sulphate source was identifiable by the almost exclusive presence of S, and to a lesser extent V, emitted from oil combustion as primary emissions and also secondary sulphate formation following the release of S to the atmosphere. A mixed anthropogenic source was characterised by Zn, Ni, Cr, Cu and Pb, emitted from traffic, industry, power generation and water desalination. This study highlights that the natural sources of particulates in this desert region give rise to frequent episodes of extremely poor air quality, and this problem is compounded by significant emissions of anthropogenic pollution, which has an impact across the entire Red Sea basin. Further stringent measures should be adopted to improve air quality across the region and prevent long-term damage to the health of the local population and ecosystems.
• #### Energy Stability of Explicit Runge--Kutta Methods for Nonautonomous or Nonlinear Problems

(SIAM Journal on Numerical Analysis, Society for Industrial & Applied Mathematics (SIAM), 2020-11-24) [Article]
Many important initial value problems have the property that energy is nonincreasing in time. Energy stable methods, also referred to as strongly stable methods, guarantee the same property discretely. We investigate requirements for conditional energy stability of explicit Runge--Kutta methods for nonlinear or nonautonomous problems. We provide both necessary and sufficient conditions for energy stability over these classes of problems. Examples of conditionally energy stable schemes are constructed, and an example is given in which unconditional energy stability is obtained with an explicit scheme.
• #### Seismic Velocities Distribution in a 3D Mantle: Implications for InSight Measurements

(Wiley, 2020-11-24) [Preprint]
• #### Composition, uniqueness and connectivity across tropical coastal lagoon habitats in the Red Sea.

(BMC ecology, Springer Science and Business Media LLC, 2020-11-24) [Article]
BACKGROUND:Tropical habitats and their associated environmental characteristics play a critical role in shaping macroinvertebrate communities. Assessing patterns of diversity over space and time and investigating the factors that control and generate those patterns is critical for conservation efforts. However, these factors are still poorly understood in sub-tropical and tropical regions. The present study applied a combination of uni- and multivariate techniques to test whether patterns of biodiversity, composition, and structure of macrobenthic assemblages change across different lagoon habitats (two mangrove sites; two seagrass meadows with varying levels of vegetation cover; and an unvegetated subtidal area) and between seasons and years. RESULTS:In total, 4771 invertebrates were identified belonging to 272 operational taxonomic units (OTUs). We observed that macrobenthic lagoon assemblages are diverse, heterogeneous and that the most evident biological pattern was spatial rather than temporal. To investigate whether macrofaunal patterns within the lagoon habitats (mangrove, seagrass, unvegetated area) changed through the time, we analysed each habitat separately. The results showed high seasonal and inter-annual variability in the macrofaunal patterns. However, the seagrass beds that are characterized by variable vegetation cover, through time, showed comparatively higher stability (with the lowest values of inter-annual variability and a high number of resident taxa). These results support the theory that seagrass habitat complexity promotes diversity and density of macrobenthic assemblages. Despite the structural and functional importance of seagrass beds documented in this study, the results also highlighted the small-scale heterogeneity of tropical habitats that may serve as biodiversity repositories. CONCLUSIONS:Comprehensive approaches at the "seascape" level are required for improved ecosystem management and to maintain connectivity patterns amongst habitats. This is particularly true along the Saudi Arabian coast of the Red Sea, which is currently experiencing rapid coastal development. Also, considering the high temporal variability (seasonal and inter-annual) of tropical shallow-water habitats, monitoring and management plans must include temporal scales.
• #### Adversarial Generation of Continuous Images

(arXiv, 2020-11-24) [Preprint]
In most existing learning systems, images are typically viewed as 2D pixel arrays. However, in another paradigm gaining popularity, a 2D image is represented as an implicit neural representation (INR) -- an MLP that predicts an RGB pixel value given its (x,y) coordinate. In this paper, we propose two novel architectural techniques for building INR-based image decoders: factorized multiplicative modulation and multi-scale INRs, and use them to build a state-of-the-art continuous image GAN. Previous attempts to adapt INRs for image generation were limited to MNIST-like datasets and do not scale to complex real-world data. Our proposed architectural design improves the performance of continuous image generators by x6-40 times and reaches FID scores of 6.27 on LSUN bedroom 256x256 and 16.32 on FFHQ 1024x1024, greatly reducing the gap between continuous image GANs and pixel-based ones. To the best of our knowledge, these are the highest reported scores for an image generator, that consists entirely of fully-connected layers. Apart from that, we explore several exciting properties of INR-based decoders, like out-of-the-box superresolution, meaningful image-space interpolation, accelerated inference of low-resolution images, an ability to extrapolate outside of image boundaries and strong geometric prior. The source code is available at https://github.com/universome/inr-gan
• #### A single neuron subset governs a single coactive neuron circuit in Hydra vulgaris , representing a prototypic feature of neural evolution

(Cold Spring Harbor Laboratory, 2020-11-23) [Preprint]
The last common ancestor of Bilateria and Cnidaria is believed to be one of the first animals to develop a nervous system over 500 million years ago. Many of the genes involved in the neural function of the advanced nervous system in Bilateria are well conserved in Cnidaria. Thus, Cnidarian representative species, Hydra, is considered to be a living fossil and a good model organism for the study of the putative primitive nervous system in its last common ancestor. The diffuse nervous system of Hydra consists of several peptidergic neuron subsets. However, the specific functions of these subsets remain unclear. Using calcium imaging, here we show that the neuron subsets that express neuropeptide, Hym-176 function as motor neurons to evoke longitudinal contraction. We found that all neurons in a subset defined by the Hym-176 gene (Hym-176A) or its paralogs (Hym-176B) expression are excited simultaneously, which is then followed by longitudinal contraction. This indicates not only that these neuron subsets are motor neurons but also that a single molecularly defined neuron subset forms a single coactive motor circuit. This is in contrast with the Bilaterian nervous system, where a single molecularly defined neuron subset harbors multiple coactive circuits, showing a mixture of neurons firing with different timings. Furthermore, we found that the two motor circuits, one expressing Hym-176B in the body column and the other expressing Hym-176A in the foot, are coordinately regulated to exert region-specific contraction. Our results demonstrate that one neuron subset is likely to form a monofunctional circuit as a minimum functional unit to build a more complex behavior in Hydra. We propose that this simple feature (one subset, one circuit, one function) found in Hydra is a fundamental trait of the primitive nervous system.
• #### Eddy-induced transport and kinetic energy budget in the Arabian Sea

(Geophysical Research Letters, American Geophysical Union (AGU), 2020-11-23) [Article]
This study investigates the vertical eddy structure, eddy-induced transport, and eddy kinetic energy (EKE) budget in the Arabian Sea (AS) using an eddy-resolving reanalysis product. The EKE intensifies during summer in the western AS. Anticyclonic eddies (AEs) and cyclonic eddies (CEs) present warm-fresh and cold-salty cores, respectively, with interleaved salinity structures. The eddy-induced swirl transport is larger in the western AS and tends to compensate for heat transport by the mean flow. Zonal drift transport by AEs and CEs offset each other, and meridional transport is generally weaker. Eddies also produce notable upward heat flux during summer in the western AS, where ageostrophic circulations are induced to maintain a turbulent thermal wind balance. Plausible mechanisms for EKE production are governed by baroclinic and barotropic instabilities, which are enhanced in summer in the western basin, where signals are quantitatively one order larger than the turbulent wind inputs.
• #### TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks

(arXiv, 2020-11-23) [Preprint]
Understanding videos is challenging in computer vision. In particular, the large memory footprint of an untrimmed video makes most tasks infeasible to train end-to-end without dropping part of the input data. To cope with the memory limitation of commodity GPUs, current video localization models encode videos in an offline fashion. Even though these encoders are learned, they are typically trained for action classification tasks at the frame- or clip-level. Since it is difficult to finetune these encoders for other video tasks, they might be sub-optimal for temporal localization tasks. In this work, we propose a novel, supervised pretraining paradigm for clip-level video representation that does not only train to classify activities, but also considers background clips and global video information to gain temporal sensitivity. Extensive experiments show that features extracted by clip-level encoders trained with our novel pretraining task are more discriminative for several temporal localization tasks. Specifically, we show that using our newly trained features with state-of-the-art methods significantly improves performance on three tasks: Temporal Action Localization (+1.72% in average mAP on ActivityNet and +4.4% in mAP@0.5 on THUMOS14), Action Proposal Generation (+1.94% in AUC on ActivityNet), and Dense Video Captioning (+0.31% in average METEOR on ActivityNet Captions). We believe video feature encoding is an important building block for many video algorithms, and extracting meaningful features should be of paramount importance in the effort to build more accurate models.
• #### Host-association as major driver of microbiome structure and composition in Red Sea seagrass ecosystems

(Environmental Microbiology, Wiley, 2020-11-22) [Article]
The role of the microbiome in sustaining seagrasses has recently been highlighted. However, our understanding of the seagrass microbiome lacks behind that of other organisms. Here, we analyze the endophytic and total bacterial communities of leaves, rhizomes, and roots of six Red Sea seagrass species and their sediments. The structure of seagrass bacterial communities revealed that the 1% most abundant OTUs accounted for 87.9 and 74.8 % of the total numbers of reads in sediment and plant tissue samples, respectively. We found taxonomically distinct bacterial communities in vegetated and bare sediments. Yet, our results suggest that lifestyle (i.e. free-living or host-association) is the main driver of bacterial community composition. Seagrass bacterial communities were tissue- and species-specific and differed from those of surrounding sediments. We identified OTUs belonging to genera related to N and S cycles in roots, and members of Actinobacteria, Bacteroidetes, and Firmicutes phyla as particularly enriched in root endosphere. The finding of highly similar OTUs in well-defined sub-clusters by network analysis suggests the co-occurrence of highly connected key members within Red Sea seagrass bacterial communities. These results provide key information towards the understanding of the role of microorganisms in seagrass ecosystem functioning framed under the seagrass holobiont concept.
• #### Boundary-sensitive Pre-training for Temporal Localization in Videos

(arXiv, 2020-11-21) [Preprint]
Many video analysis tasks require temporal localization thus detection of content changes. However, most existing models developed for these tasks are pre-trained on general video action classification tasks. This is because large scale annotation of temporal boundaries in untrimmed videos is expensive. Therefore no suitable datasets exist for temporal boundary-sensitive pre-training. In this paper for the first time, we investigate model pre-training for temporal localization by introducing a novel boundary-sensitive pretext (BSP) task. Instead of relying on costly manual annotations of temporal boundaries, we propose to synthesize temporal boundaries in existing video action classification datasets. With the synthesized boundaries, BSP can be simply conducted via classifying the boundary types. This enables the learning of video representations that are much more transferable to downstream temporal localization tasks. Extensive experiments show that the proposed BSP is superior and complementary to the existing action classification based pre-training counterpart, and achieves new state-of-the-art performance on several temporal localization tasks.
• #### Compositional Fluctuations Locked by Athermal Transformation Yielding High Thermoelectric Performance in GeTe.

(Advanced materials (Deerfield Beach, Fla.), Wiley, 2020-11-20) [Article]
Phase transition in thermoelectric (TE) material is a double-edged sword-it is undesired for device operation in applications, but the fluctuations near an electronic instability are favorable. Here, Sb doping is used to elicit a spontaneous composition fluctuation showing uphill diffusion in GeTe that is otherwise suspended by diffusionless athermal cubic-to-rhombohedral phase transition at around 700 K. The interplay between these two phase transitions yields exquisite composition fluctuations and a coexistence of cubic and rhombohedral phases in favor of exceptional figures-of-merit zT. Specifically, alloying GeTe by Sb2 Te3 significantly suppresses the thermal conductivity while retaining eligible carrier concentration over a wide composition range, resulting in high zT values of >2.6. These results not only attest to the efficacy of using phase transition in manipulating the microstructures of GeTe-based materials but also open up a new thermodynamic route to develop higher performance TE materials in general.
• #### Advances in statistical modeling of spatial extremes

(WIREs Computational Statistics, Wiley, 2020-11-20) [Article]
The classical modeling of spatial extremes relies on asymptotic models (i.e., max-stable or r-Pareto processes) for block maxima or peaks over high thresholds, respectively. However, at finite levels, empirical evidence often suggests that such asymptotic models are too rigidly constrained, and that they do not adequately capture the frequent situation where more severe events tend to be spatially more localized. In other words, these asymptotic models have a strong tail dependence that persists at increasingly high levels, while data usually suggest that it should weaken instead. Another well-known limitation of classical spatial extremes models is that they are either computationally prohibitive to fit in high dimensions, or they need to be fitted using less efficient techniques. In this review paper, we describe recent progress in the modeling and inference for spatial extremes, focusing on new models that have more flexible tail structures that can bridge asymptotic dependence classes, and that are more easily amenable to likelihood-based inference for large datasets. In particular, we discuss various types of random scale constructions, as well as the conditional spatial extremes model, which have recently been getting increasing attention within the statistics of extremes community. We illustrate some of these new spatial models on two different environmental applications.
• #### Advances in the Design of Heterogeneous Catalysts and Thermocatalytic Processes for CO2 Utilization

(ACS Catalysis, American Chemical Society (ACS), 2020-11-20) [Article]
Utilization of CO2 as feedstock to produce fine chemicals and renewable fuels is a highly promising field, which presents unique challenges in its implementation at scale. Heterogeneous catalysis with its simple operation and industrial compatibility can be an effective means of achieving this challenging task. This review summarizes the current developments in heterogeneous thermal catalysis for the production of carbon monoxide, alcohols, and hydrocarbons from CO2. A detailed discussion is provided regarding structure−activity correlations between the catalyst surface and intermediate species which can aid in the rational design of future generation catalysts. Effects of active metal components, catalyst supports, and promoters are discussed in each section, which will guide researchers to synthesize new catalysts with improved selectivity and stability. Additionally, a brief overview regarding process design considerations has been provided. Future research directions are proposed with special emphasis on the application scope of new catalytic materials and possible approaches to increase catalyst performance.
• #### MXenes for Rechargeable Batteries Beyond the Lithium-Ion

(Advanced Materials, Wiley, 2020-11-20) [Article]
Research on next-generation battery technologies (beyond Li-ion batteries, or LIBs) has been accelerating over the past few years. A key challenge for these emerging batteries has been the lack of suitable electrode materials, which severely limits their further developments. MXenes, a new class of 2D transition metal carbides, carbonitrides, and nitrides, are proposed as electrode materials for these emerging batteries due to several desirable attributes. These attributes include large and tunable interlayer spaces, excellent hydrophilicity, extraordinary conductivity, compositional diversity, and abundant surface chemistries, making MXenes promising not only as electrode materials but also as other components in the cells of emerging batteries. Herein, an overview and assessment of the utilization of MXenes in rechargeable batteries beyond LIBs, including alkali-ion (e.g., Na+ , K+ ) storage, multivalent-ion (e.g., Mg2+ , Zn2+ , and Al3+ ) storage, and metal batteries are presented. In particular, the synthetic strategies and properties of MXenes that enable MXenes to play various roles as electrodes, metal anode protective layers, sulfur hosts, separator modification layers, and conductive additives in these emerging batteries are discussed. Moreover, a perspective on promising future research directions on MXenes and MXene-based materials, ranging from material design and processing, fundamental understanding of the reaction mechanisms, to device performance optimization strategies is provided.
• #### A new approach for quantifying epigenetic landscapes.

(The Journal of biological chemistry, American Society for Biochemistry & Molecular Biology (ASBMB), 2020-11-20) [Article]
ChIP-Seq is a widespread experimental method for determining the global enrichment of chromatin modifications and genome-associated factors. Whereas it is straightforward to compare the relative genomic distribution of these epigenetic features, researchers have also made efforts to compare their signal strength using external references for normalization. New work now suggests that these "spike-ins" could lead to inaccurate conclusions due to intrinsic issues of the methodology and instead calls for new criteria of experimental reporting that may permit internal standardization when certain parameters are fulfilled.
• #### High-speed filtered Rayleigh scattering thermometry in premixed flames through narrow channels

(Combustion and Flame, Elsevier BV, 2020-11-20) [Article]
High-speed filtered Rayleigh scattering at 10 kHz repetition rate for time-resolved temperature measurements in premixed flames propagating in mm-high channels is demonstrated for the first time. The instrument relies on a pulse burst laser with a 200 ns temporal width, and a CCD camera operated in subframe burst gate mode to achieve high signal to noise ratio despite the limited optical access. A 10-inch-long iodine cell acts as a molecular filter and the laser, which is seeded using an external cavity diode laser and operated in a temporally stretched mode, is wavelength-tuned to the peak of a strong iodine absorption line. A CCD camera, operated in the sub-frame burst gating mode with the help of an external slit configuration, is used as the detector to achieve improved camera noise performance. Filtered Rayleigh scattering temperature measurements in premixed flat flames stabilized over a McKenna burner indicate an instrument precision of 3%. Temperature measurements in the products region are within 3% of measurements obtained with conventional Rayleigh scattering. The system's capabilities are demonstrated through time-resolved temperature measurements in a premixed methane-air flame propagating in a 1.5 mm-high rectangular channel designed to study flame quenching in flame arrestors. Surface scattering from the optical windows and the channel surfaces is successfully suppressed and time-resolved temperature profiles are obtained for both quenching and no-quenching events.
• #### Counterintuitive Wetting Transitions in Doubly Reentrant Cavities as a Function of Surface Make‐Up, Hydrostatic Pressure, and Cavity Aspect Ratio

(Advanced Materials Interfaces, Wiley, 2020-11-20) [Article]
Surfaces that entrap air underwater serve numerous practical applications, such as mitigating cavitation erosion and reducing frictional drag. These surfaces typically rely on perfluorinated coatings. However, the non-biodegradability and fragility of the coatings limit practical applications. Thus, coating-free, sustainable, and robust approaches are desirable. Recently, a microtexture comprising doubly reentrant cavities (DRCs) has been demonstrated to entrap air on immersion in wetting liquids. While this is a promising approach, insights into the effects of surface chemistry, hydrostatic pressure, and cavity dimensions on wetting transitions in DRCs remain unavailable. In response, Cassie-to-Wenzel transitions into circular DRCs submerged in water are investigated and compared with those in cylindrical “simple” cavities (SCs). It is found that at low hydrostatic pressures (≈50 Pa), DRCs with hydrophilic (θo ≈ 40°) and hydrophobic (θo ≈ 112°) make-ups fill within 105 and 107 s, respectively, while SCs with hydrophilic make-up fill within <10−2 s. Under elevated hydrostatic pressure (P ≤ 90 kPa), counterintuitively, DRCs with hydrophobic make-up fill dramatically faster than the commensurate SCs. This comprehensive report should provide a rational framework for harnessing microtexturing and surface chemistry toward coating-free liquid repellency.
• #### Monolayer Graphene Transfer onto Hydrophilic Substrates: A New Protocol Using Electrostatic Charging

(Membranes, MDPI AG, 2020-11-20) [Article]
In the present work, we developed a novel method for transferring monolayer graphene onto four different commercial hydrophilic micro/ultra-filtration substrates. The developed method used electrostatic charging to maintain the contact between the graphene and the target substrate intact during the etching step through the wet transfer process. Several measurement/analysis techniques were used in order to evaluate the properties of the surfaces and to assess the quality of the transferred graphene. The techniques included water contact angle (CA), atomic force microscopy (AFM), and field emission scanning electron microscopy (FESEM). Potassium chloride (KCl) ions were used for the transport study through the developed graphene-based membranes. The results revealed that 70% rejection of KCI ions was recorded for the graphene/polyvinylidene difluoride (PVDF1) membrane, followed by 67% rejection for the graphene/polyethersulfone (PES) membrane, and 65% rejection for graphene/PVDF3 membrane. It was revealed that the smoothest substrate was the most effective in rejecting the ions. Although defects such as tears and cracks within the graphene layer were still evolving in this new transfer method, however, the use of Nylon 6,6 interfacial polymerization allowed sealing the tears and cracks within the graphene monolayer. This enhanced the KCl ions rejection of up to 85% through the defect-sealed graphene/polymer composite membranes.