Recent Submissions

  • Composite nanofiltration membrane comprising one-dimensional erdite, two-dimensional reduced graphene oxide, and silkworm pupae binder

    Balaji, K.R.; Hardian, Rifan; Dileep Kumar, V.G.; Viswanatha, R.; Kumar, Suneel; Kumar, Surender; Singh, Archana; Santosh, Mysore Sridhar; Szekely, Gyorgy (Materials Today Chemistry, Elsevier, 2021-10-23) [Article]
    Composite nanofiltration membranes offer advantages because of synergetic effects among the constituent materials’ properties. However, the sustainability of both the membrane fabrication and the raw materials has been a drawback of this energy-efficient separation technology. We report the facile fabrication of a nanocomposite membrane composed of a two-dimensional (2D) material of reduced graphene oxide (rGO) combined with a one-dimensional (1D) material of a ternary metal-based chalcogenide (NaFeS2 or NFS), using silkworm pupae protein as a natural binder. All the source materials can be derived from either nature or waste, ensuring the sustainability of the membrane and its production method. The structural characteristics of the synthesized membranes were analyzed, and the morphology of the composite membranes was studied thoroughly. Thermogravimetric analysis, differential scanning calorimetry, and nanoindentation characterizations indicated that the composite membranes were mechanically and thermally stable. The water and acetone fluxes; salt, dye, and pollutant rejections; and long-term membrane performance were evaluated using a cross-flow filtration system. Solute rejection was observed to increase (up to 98%, 94%, 95%, and 78% for Rhodamine B, 2,4-dichlorophenol, MgCl2, and NaCl, respectively) with increasing concentration of the nanomaterials in the membrane. The fine-tuning of the molecular weight cut-off from 794 to 600 g mol–1 was achieved by varying the concentration of the nanomaterials from 1 to 3 mg mL–1 . Our research findings demonstrate the synergetic effects of combining 1D and 2D materials using silkworm pupae binder. The composite membrane was stable in different classes of organic solvents, including hydrocarbons, alcohols, esters, ethers, polar aprotic solvents, halogenated solvents, and ketones. This first use of natural pupae binder in constructing membrane materials paves the way toward the development of more sustainable membranes.
  • Deep characterization of paired chromatin and transcriptomes in four immune cell types from multiple sclerosis patients

    Fernandes, Sunjay Jude; Ericsson, Matilda; Khademi, Mohsen; Jagodic, Maja; Olsson, Tomas; Gomez-Cabrero, David; Kockum, Ingrid; Tegner, Jesper (Epigenomics, Future Medicine Ltd, 2021-10-22) [Article]
    Background: The putative involvement of chromatin states in multiple sclerosis (MS) is thus far unclear. Here we determined the association of chromatin-accessibility with concurrent genetic, epigenetic and transcriptional events. Material & methods: We generated paired assay for transposase-accessible chromatin sequencing and RNA-seq profiles from sorted blood immune CD4$^{+}$ and CD8$^{+}$ T cells, CD14$^{+}$ monocytes and CD19$^{+}$ B cells from healthy controls (HCs) and MS patients. Results: We identified differentially accessible regions between MS and HCs, primarily in CD4$^{+}$ and CD19$^{+}$. CD4$^{+}$ regions were enriched for MS-associated single nucleotide polymorphisms and differentially methylated loci. In the vicinity of differentially accessible regions of CD4$^{+}$ cells, 42 differentially expressed genes were identified. The top two dysregulated genes identified in this multilayer analysis were CCDC114 and SERTAD1. Conclusion: These findings provide new insight into the primary role of CD4$^{+}$ and CD19$^{+}$ cells in MS.
  • Optical diagnostics and multi-point pressure sensing on the knocking combustion with multiple spark ignition

    Shi, Hao; Tang, Qinglong; Uddeen, Kalim; Magnotti, Gaetano; Turner, James W. G. (Combustion and Flame, Elsevier BV, 2021-10-22) [Article]
    Engine knock is an abnormal combustion phenomenon that limits the thermal efficiency and service life of spark-ignition engines. A better understanding of the knock mechanisms and characteristics is beneficial to knock alleviation and engine efficiency improvement. In this study, a metal liner with four evenly-spaced spark plugs in the periphery of the combustion chamber is designed to initiate knock from different positions. Four spark strategies are applied to the single-cylinder optical research engine and six pressure sensors are utilized to analyze the local pressure oscillations in the cylinder. The knocking combustion is investigated by simultaneous 72 kHz high-speed imaging and 6-point pressure sensing. The experimental results indicate that using multiple spark-ignition could promote knock intensity, advance the start of auto-ignition and introduce more acoustic resonance modes. The center pressure sensor is more sensitive to the first radial resonant mode (0, 1) of the knock pressure oscillation, while the side sensors are more sensitive to the first and second circumferential resonant modes (1, 0) and (2, 0). The knock onset judged by natural flame photography is earlier than that by pressure analysis because the auto-ignition event happens first and induces the subsequent pressure fluctuation. Natural flame luminosity analysis demonstrates that the initial auto-ignition sites only cause weak pressure oscillations, and the instantaneous combustion of the remaining end-gas increases the heat release rate significantly and gives rise to more violent pressure oscillations. Statistically, the maximum amplitude of pressure oscillation follows an exponential relationship with the peak mean flame luminosity. The end-gas resides in the gaps among the flame fronts generated by different spark strategies while the first auto-ignition sites are not evenly distributed in the end-gas zone. This fact gives insights into the local temperature non-uniformity of the end gas zone that affects the spatial distributions of the initial auto-ignition sites in the cylinder.
  • Etch-free additive lithographic fabrication methods for reflective and transmissive micro-optics

    Fu, Qiang; Amata, Hadi; Heidrich, Wolfgang (Optics Express, The Optical Society, 2021-10-22) [Article]
    With the widespread application of micro-optics in a large range of areas, versatile high quality fabrication methods for diffractive optical elements (DOEs) have always been desired by both the research community and by industry. Traditionally, multi-level DOEs are fabricated by a repetitive combination of photolithography and reactive-ion etching (RIE). The optical phase accuracy and micro-surface quality are severely affected by various etching artifacts, e.g., RIE lag, aspect ratio dependent etching rates, and etching artifacts in the RIE steps. Here we propose an alternative way to fabricate DOEs by additively growing multi-level microstructures onto the substrate. Depth accuracy, surface roughness, uniformity and smoothness are easily controlled to high accuracy by a combination of deposition and lift-off, rather than etching. Uniform depths can be realized for both micrometer and millimeter scale features that are simultaneously present in the designs. The grown media can either be used directly as a reflective DOE, or as a master stamp for nanoimprinting refractive designs. We demonstrate the effectiveness of the fabrication methods with representative reflective and transmissive DOEs for imaging and display applications.
  • Optimal Interfacial Band Bending Achieved by Fine Energy Level Tuning in Mixed-Halide Perovskite Solar Cells

    Daboczi, Matyas; Ratnasingham, Sinclair R.; Mohan, Lokeshwari; Pu, Chenfeng; Hamilton, Iain; Chin, Yi-Chun; McLachlan, Martyn A.; Kim, Ji Seon (ACS Energy Letters, American Chemical Society (ACS), 2021-10-21) [Article]
    Most highly efficient perovskite solar cells employ mixed iodide–bromide photoactive layers; however, understanding the beneficial effect of the low (5–15 mol %) bromide content is incomplete. Here, a series of MAPb(I1–xBrx)3 perovskite layers are investigated to understand the origin of the high peak power conversion efficiency (19.2%) observed at small bromide content (0.10 ≤ x ≤ 0.125). For the x = 0.125 perovskite, 200 meV shallower energy levels are revealed, accompanied by a reduced density of trap states and stable tetragonal mixed-halide phase with compressed unit cell. In contrast, the higher bromide content samples (x > 0.125) show deeper energy levels, cubic perovskite crystal structure, and signs of halide segregation. Surface photovoltage measurements unveil an undesirable band bending at the hole transport layer/perovskite interface for MAPbI3 and x > 0.125 mixed-halide layers, which is eliminated for the x = 0.125 perovskite because of its shallower Fermi level, enabling enhanced device performance.
  • Soliton-based single-point pulse wave velocity model: A quantum mechanical approach

    Piliouras, Evangelos; Laleg-Kirati, Taous-Meriem (Biomedical Signal Processing and Control, Elsevier BV, 2021-10-20) [Article]
    Cardiovascular diseases (CVDs) are one of the strongest contributors to mortality rates worldwide. To assess the severity of a clinical situation, various indices of CVD risk have been established, one of them being the arterial stiffness. Arterial stiffness is the quantification of the arterial elasticity. There exist several methodologies to assess the level of arterial stiffness where their non-invasiveness is a matter of great importance. The pulse wave velocity (PWV) is used as an indicator of the arterial stiffness and satisfies the non-invasiveness requirement. Specifically, the carotid-femoral PWV-based method is considered one of the most trustworthy methodology in quantifying the arterial stiffness. This paper proposes a new model for the PWV along with insights on a real scenario implementation. The model utilizes Semi-classical signal analysis (SCSA) as the main signal processing framework to analyze the blood pressure waveform. The proposed model is suggested to be used as an add-on to existing methodologies, bringing the feature of single-point measurement, once a calibration phase has preceded. The use of such a model can eliminate the pulse propagation time-delay, one of the dominant sources of PWV error. Additionally, the single-point measurement paves the way of prolonged PWV monitoring that can reveal new clinical features of the PWV. The model was validated both in a theoretical and data basis, validating its predicted hyperbolic PWV behavior with respect to the SCSA parameters.
  • NERO: a biomedical named-entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding

    Wang, Kanix; Stevens, Robert; Alachram, Halima; Li, Yu; Soldatova, Larisa; King, Ross; Ananiadou, Sophia; Schoene, Annika M.; Li, Maolin; Christopoulou, Fenia; Ambite, José Luis; Matthew, Joel; Garg, Sahil; Hermjakob, Ulf; Marcu, Daniel; Sheng, Emily; Beißbarth, Tim; Wingender, Edgar; Galstyan, Aram; Gao, Xin; Chambers, Brendan; Pan, Weidi; Khomtchouk, Bohdan B.; Evans, James A.; Rzhetsky, Andrey (npj Systems Biology and Applications, Springer Science and Business Media LLC, 2021-10-20) [Article]
    Machine reading (MR) is essential for unlocking valuable knowledge contained in millions of existing biomedical documents. Over the last two decades1,2, the most dramatic advances in MR have followed in the wake of critical corpus development3. Large, well-annotated corpora have been associated with punctuated advances in MR methodology and automated knowledge extraction systems in the same way that ImageNet4 was fundamental for developing machine vision techniques. This study contributes six components to an advanced, named entity analysis tool for biomedicine: (a) a new, Named Entity Recognition Ontology (NERO) developed specifically for describing textual entities in biomedical texts, which accounts for diverse levels of ambiguity, bridging the scientific sublanguages of molecular biology, genetics, biochemistry, and medicine; (b) detailed guidelines for human experts annotating hundreds of named entity classes; (c) pictographs for all named entities, to simplify the burden of annotation for curators; (d) an original, annotated corpus comprising 35,865 sentences, which encapsulate 190,679 named entities and 43,438 events connecting two or more entities; (e) validated, off-the-shelf, named entity recognition (NER) automated extraction, and; (f) embedding models that demonstrate the promise of biomedical associations embedded within this corpus.
  • Sustainable and Inexpensive Polydimethylsiloxane Sponges for Daytime Radiative Cooling

    Zhou, Lyu; Rada, Jacob; Zhang, Huafan; Song, Haomin; Mirniaharikandi, Seyededriss; Ooi, Boon S.; Gan, Qiaoqiang (Advanced Science, Wiley, 2021-10-20) [Article]
    Radiative cooling is an emerging cooling technology that can passively release heat to the environment. To obtain a subambient cooling effect during the daytime, chemically engineered structural materials are widely explored to simultaneously reject sunlight and preserve strong thermal emission. However, many previously reported fabrication processes involve hazardous chemicals, which can hinder a material's ability to be mass produced. In order to eliminate the hazardous chemicals used in the fabrication of previous works, this article reports a white polydimethylsiloxane (PDMS) sponge fabricated by a sustainable process using microsugar templates. By substituting the chemicals for sugar, the manufacturing procedure produces zero toxic waste and can also be endlessly recycled via methods widely used in the sugar industry. The obtained porous PDMS exhibits strong visible scattering and thermal emission, resulting in an efficient temperature reduction of 4.6 °C and cooling power of 43 W m−2 under direct solar irradiation. In addition, due to the air-filled voids within the PDMS sponge, its thermal conductivity remains low at 0.06 W (m K)−1. This unique combination of radiative cooling and thermal insulation properties can efficiently suppress the heat exchange with the solar-heated rooftop or the environment, representing a promising future for new energy-efficient building envelope material.
  • Unusual design strategy of stable and soluble high-molecular-weight copper(I) arylacetylide polymer

    Zheng, Bian; Chen, Yu; Guangshan, Zhu; Kang, Chuanqing; Gao, Lianxun; Zhao, Zhiqiang; Jiang, Li; Zhai, Yongchang; Cui, Fengchao; Tian, Yuyang; Tian, Hongkun; Jia, Jiangtao; Eddaoudi, Mohamed (Chemical Communications, Royal Society of Chemistry (RSC), 2021-10-20) [Article]
    Stable and soluble high-molecular-weight copper(I) arylacetylide polymers were obtained by unusual means. Long enough side chain, electron-withdrawing ester groups and chloroform solvent in polymerization can together relate to the solubility...
  • A Modified HSIFT Descriptor for Medical Image Classification of Anatomy Objects

    Khan, Sumeer Ahmad; Gulzar, Yonis; Turaev, Sherzod; Peng, Young Suet (Symmetry, MDPI AG, 2021-10-20) [Article]
    Modeling low level features to high level semantics in medical imaging is an important aspect in filtering anatomy objects. Bag of Visual Words (BOVW) representations have been proven effective to model these low level features to mid level representations. Convolutional neural nets are learning systems that can automatically extract high-quality representations from raw images. However, their deployment in the medical field is still a bit challenging due to the lack of training data. In this paper, learned features that are obtained by training convolutional neural networks are compared with our proposed hand-crafted HSIFT features. The HSIFT feature is a symmetric fusion of a Harris corner detector and the Scale Invariance Transform process (SIFT) with BOVW representation. The SIFT process is enhanced as well as the classification technique by adopting bagging with a surrogate split method. Quantitative evaluation shows that our proposed hand-crafted HSIFT feature outperforms the learned features from convolutional neural networks in discriminating anatomy image classes.
  • Cryo-EM structure of human Pol κ bound to DNA and mono-ubiquitylated PCNA

    Lancey, Claudia; Tehseen, Muhammad; Bakshi, Souvika; Percival, Matthew; Takahashi, Masateru; Sobhy, Mohamed Abdelmaboud; Raducanu, Vlad-Stefan; Blair, Kerry; Muskett, Frederick W.; Ragan, Timothy J.; Crehuet, Ramon; Hamdan, Samir; De Biasio, Alfredo (Nature Communications, Springer Science and Business Media LLC, 2021-10-19) [Article]
    AbstractY-family DNA polymerase κ (Pol κ) can replicate damaged DNA templates to rescue stalled replication forks. Access of Pol κ to DNA damage sites is facilitated by its interaction with the processivity clamp PCNA and is regulated by PCNA mono-ubiquitylation. Here, we present cryo-EM reconstructions of human Pol κ bound to DNA, an incoming nucleotide, and wild type or mono-ubiquitylated PCNA (Ub-PCNA). In both reconstructions, the internal PIP-box adjacent to the Pol κ Polymerase-Associated Domain (PAD) docks the catalytic core to one PCNA protomer in an angled orientation, bending the DNA exiting the Pol κ active site through PCNA, while Pol κ C-terminal domain containing two Ubiquitin Binding Zinc Fingers (UBZs) is invisible, in agreement with disorder predictions. The ubiquitin moieties are partly flexible and extend radially away from PCNA, with the ubiquitin at the Pol κ-bound protomer appearing more rigid. Activity assays suggest that, when the internal PIP-box interaction is lost, Pol κ is retained on DNA by a secondary interaction between the UBZs and the ubiquitins flexibly conjugated to PCNA. Our data provide a structural basis for the recruitment of a Y-family TLS polymerase to sites of DNA damage.
  • Cell-to-Cell Communication During Plant-Pathogen Interaction

    Tabassum, Naheed; Blilou, Ikram (Molecular Plant-Microbe Interactions®, Scientific Societies, 2021-10-19) [Article]
    Recognition of pathogen activates cellular signaling such as ROS, MAPK, Ca2+ signaling which ultimately fine-tunes the cell to cell communication. These further coordinates with the hormone signaling to execute the defense response at local and systemic level. Interestingly, phytopathogens have also evolved to manipulate the cellular and hormonal signaling and/or exploit hosts cell to cell connection in multiple ways at multiple levels. Overall, the triumph over the pathogen depends on prime decisions and actions-how the plant maintain, regulate and eventually break the intercellular communication through apoplastic and symplastic routes. Here, we review how intercellular communication in plants is mediated, manipulated and maneuvered during plant-pathogen interaction. Key words: Cell to cell communication, plant defense, plasmodesmata, phytohormones
  • Rayleigh Wave Dispersion Spectrum Inversion Across Scales

    Zhang, Zhendong; Saygin, Erdinc; He, Leiyu; Alkhalifah, Tariq Ali (Surveys in Geophysics, Springer Science and Business Media LLC, 2021-10-19) [Article]
    Traditional approaches of using dispersion curves for S-wave velocity reconstruction have limitations, principally, the 1D-layered model assumption and the automatic/manual picking of dispersion curves. At the same time, conventional full-waveform inversion (FWI) can easily converge to a non-global minimum when applied directly to complicated surface waves. Alternatively, the recently introduced wave equation dispersion spectrum inversion method can avoid these limitations, by applying the adjoint state method on the dispersion spectra of the observed and predicted data and utilizing the local similarity objective function to depress cycle skipping. We apply the wave equation dispersion spectrum inversion to three real datasets of different scales: tens of meters scale active-source data for estimating shallow targets, tens of kilometers scale ambient noise data for reservoir characterization and a continental-scale seismic array data for imaging the crust and uppermost mantle. We use these three open datasets from exploration to crustal scale seismology to demonstrate the effectiveness of the inversion method. The dispersion spectrum inversion method adapts well to the different-scale data without any special tuning. The main benefits of the proposed method over traditional methods are that (1) it can handle lateral variations; (2) it avoids direct picking dispersion curves; (3) it utilizes both the fundamental and higher modes of Rayleigh waves, and (4) the inversion can be solved using gradient-based local optimizations. Compared to the conventional 1D inversion, the dispersion spectrum inversion requires more computational cost since it requires solving the 2D/3D elastic wave equation in each iteration. A good match between the observed and predicted dispersion spectra also leads to a reasonably good match between the observed and predicted waveforms, though the inversion does not aim to match the waveforms.
  • LineFS: Efficient SmartNIC Offload of a Distributed File System with Pipeline Parallelism

    Kim, Jongyul; Jang, Insu; Reda, Waleed; Im, Jaeseong; Canini, Marco; Kostić, Dejan; Kwon, Youngjin; Peter, Simon; Witchel, Emmett (ACM, 2021-10-19) [Conference Paper]
    In multi-tenant systems, the CPU overhead of distributed file systems (DFSes) is increasingly a burden to application performance. CPU and memory interference cause degraded and unstable application and storage performance, in particular for operation latency. Recent client-local DFSes for persistent memory (PM) accelerate this trend. DFS offload to SmartNICs is a promising solution to these problems, but it is challenging to fit the complex demands of a DFS onto simple SmartNIC processors located across PCIe. We present LineFS, a SmartNIC-offloaded, high-performance DFS with support for client-local PM. To fully leverage the SmartNIC architecture, we decompose DFS operations into execution stages that can be offloaded to a parallel datapath execution pipeline on the SmartNIC. LineFS offloads CPU-intensive DFS tasks, like replication, compression, data publication, index and consistency management to a Smart-NIC. We implement LineFS on the Mellanox BlueField Smart-NIC and compare it to Assise, a state-of-the-art PM DFS. LineFS improves latency in LevelDB up to 80% and throughput in Filebench up to 79%, while providing extended DFS availability during host system failures.
  • Ammonia and ammonia/hydrogen blends oxidation in a jet-stirred reactor: Experimental and numerical study

    Osipova, Ksenia N.; Zhang, Xiaoyuan; Sarathy, Mani; Korobeinichev, Oleg P.; Shmakov, Andrey G. (Fuel, Elsevier BV, 2021-10-18) [Article]
    One of the most important problems of modern energy industry is the transition to carbon free fuels, which can mitigate the negative environmental effects. This paper presents experimental data on ammonia and ammonia/hydrogen blends oxidation in an isothermal jet-stirred reactor over the temperature of range 800–1300 K. Experiments were performed under atmospheric pressure, residence time of 1 s, various equivalence ratios, and with argon dilution at ≈0.99. It was revealed that hydrogen addition shifts the onset temperature of ammonia oxidation by about 250 K towards the lower region. A detailed chemical kinetic model which showed the best predictive capability was used to understand the effect of hydrogen addition on ammonia reactivity. It was shown that hydrogen presence results into higher concentrations of H, O and OH radicals. Moreover, these radicals start to form at lower temperatures when hydrogen is present. However, the change of the equivalence ratio has only slight effect on the temperature range of ammonia conversion.
  • Detailed investigation of the mixing field and stability of natural gas and propane in highly turbulent planar flames

    Elbaz, Ayman M.; Mansour, Mohy S.; Akoush, Bassem M.; Juddoo, Mrinal; Khedr, Alaa M.; Al-Bulqini, Hazem M.; Zayed, Mohamed F.; Ahmed, Mahmoud M.A.; Roberts, William L.; Masri, Assaad R. (Fuel, Elsevier BV, 2021-10-18) [Article]
    In most practical combustion devices, the actual combustion process occurs within different mixture inhomogeneity levels. Investigating the mixture fraction field upstream of the reaction zones of these flames is an essential step toward understanding their structure, stability, and emission formation. In this study, the mixture fraction fields were measured for turbulent non-reacting inhomogeneous mixtures immediately downstream from the slot burner exit, using Rayleigh scattering imaging. The slot burner had two concentric slots. The inner air slot can be recessed at distances upstream from the exit of the outer fuel slot, allowing various degrees of mixture inhomogeneity. Mixture fraction field statistics and the two-dimensional gradient were utilized to characterize the impact of the air-to-fuel velocity ratio, global equivalence ratio, fuel composition, Reynolds number, and the premixing length on the mixture mixing field, and thus flame stability. These impacts were evaluated by tracking the normalized mean mixture fraction and mixture fraction fluctuation transition across the regime diagram for partially premixed flames. The results showed that the air-to-fuel velocity ratio was the critical parameter affecting the mixture fraction field for the short premixing length. Stability results showed that the level of mixture inhomogeneity mainly influenced the flame stability. High flame stability is achieved if a large portion of the inhomogeneous mixture fraction is within the fuel flammability limits.
  • Comparative Transcriptome Analysis of Wheat Lines in the Field Reveals Multiple Essential Biochemical Pathways Suppressed by Obligate Pathogens.

    Poretti, Manuel; Sotiropoulos, Alexandros G; Graf, Johannes; Jung, Esther; Bourras, Salim; Krattinger, Simon G.; Wicker, Thomas (Frontiers in plant science, Frontiers Media SA, 2021-10-18) [Article]
    Mildew and rust are the most devastating cereal pathogens, and in wheat they can cause up to 50% yield loss every year. Wheat lines containing resistance genes are used to effectively control fungal diseases, but the molecular mechanisms underlying the interaction between wheat and its fungal pathogens are poorly understood. Here, we used RNA sequencing (RNA-Seq) to compare the transcriptomic landscape of susceptible and resistant wheat lines to identify genes and pathways that are targeted by obligate biotrophic fungal pathogens. The five lines differed in the expression of thousands of genes under infection as well as control conditions. Generally, mixed infection with powdery mildew and leaf rust resulted in downregulation of numerous genes in susceptible lines. Interestingly, transcriptomic comparison between the nearly isogenic lines Thatcher and Thatcher-Lr34 identified 753 genes that are uniquely downregulated in the susceptible line upon infection. Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, revealed the suppression of six major biochemical pathways, namely nuclear transport, alternative splicing, DNA damage response, ubiquitin-mediated proteolysis, phosphoinositol signaling, and photosynthesis. We conclude that powdery mildew and leaf rust evade the wheat defense system by suppression of programmed cell death (PCD) and responses to cellular damage. Considering the broad range of the induced changes, we propose that the pathogen targets "master regulators" at critical steps in the respective pathways. Identification of these wheat genes targeted by the pathogen could inspire new directions for future wheat breeding.
  • Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion

    Weissmann, Simon; Chada, Neil Kumar; Schillings, Claudia; Tong, Xin T. (arXiv, 2021-10-18) [Preprint]
    Ensemble Kalman inversion (EKI) is a derivative-free optimizer aimed at solving inverse problems, taking motivation from the celebrated ensemble Kalman filter. The purpose of this article is to consider the introduction of adaptive Tikhonov strategies for EKI. This work builds upon Tikhonov EKI (TEKI) which was proposed for a fixed regularization constant. By adaptively learning the regularization parameter, this procedure is known to improve the recovery of the underlying unknown. For the analysis, we consider a continuous-time setting where we extend known results such as well-posdeness and convergence of various loss functions, but with the addition of noisy observations. Furthermore, we allow a time-varying noise and regularization covariance in our presented convergence result which mimic adaptive regularization schemes. In turn we present three adaptive regularization schemes, which are highlighted from both the deterministic and Bayesian approaches for inverse problems, which include bilevel optimization, the MAP formulation and covariance learning. We numerically test these schemes and the theory on linear and nonlinear partial differential equations, where they outperform the non-adaptive TEKI and EKI.
  • Terahertz emission mediated by ultrafast time-varying metasurfaces

    Tunesi, J.; Peters, L.; Gongora, J. S. Totero; Olivieri, L.; Fratalocchi, Andrea; Pasquazi, A.; Peccianti, M. (Physical Review Research, American Physical Society (APS), 2021-10-18) [Article]
    Systems with ultrafast time-varying dielectric properties represent an emerging physical framework. We demonstrate here the observation of subcycle dynamics interacting directly with an electromagnetic source comprised of morphologically constrained photoexcited carriers in a surface nanostructure. A transition to a metallic metasurface state occurs on time scales faster than the terahertz-field period, inducing large nonlinear ultrafast phase shifts in the terahertz emission and exposing an interesting physical setting.
  • Machine Learning Enabled Traveltime Inversion Based on the Horizontal Source Location Perturbation

    Yildirim, Isa Eren; Alkhalifah, Tariq Ali; Yildirim, Ertugrul Umut (GEOPHYSICS, Society of Exploration Geophysicists, 2021-10-17) [Article]
    Gradient based traveltime tomography, which aims to minimize the difference between modeled and observed first arrival times, is a highly non-linear optimization problem. Stabilization of this inverse problem often requires employing regularization. While regularization helps avoid local minima solutions, it might cause low resolution tomograms because of its inherent smoothing property. On the other hand, although conventional ray-based tomography can be robust in terms of the uniqueness of the solution, it suffers from the limitations inherent in ray tracing, which limits its use in complex media. To mitigate the aforementioned drawbacks of gradient and ray-based tomography, we approach the problem in a completely novel way leveraging data-driven inversion techniques based on training deep convolutional neural networks (DCNN). Since DCNN often face challenges in detecting high level features from the relatively smooth traveltime data, we use this type of network to map horizontal changes in observed first arrival traveltimes caused by a source shift to lateral velocity variations. The relationship between them is explained by a linearized eikonal equation. Construction of the velocity models from this predicted lateral variation requires information from, for example, a vertical well-log in the area. This vertical profile is then used to build a tomogram from the output of the network. Both synthetic and field data results verify that the suggested approach estimates the velocity models reliably. Because of the limited depth penetration of first arrival traveltimes, the method is particularly favorable for near-surface applications.

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