Actinobacillus utilizes a binding protein?dependent ABC transporter to acquire the active form of vi
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Pan, Chuxi↗
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KEBLM: Knowledge-Enhanced Biomedical Language Models
Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing structured knowledge bases that are readily available for many domains, especially scientific domains. As a result, these PLMs may not achieve satisfactory performance on knowledge-intensive tasks such as biomedical NLP. Comprehending a complex biomedical document without domain-specific knowledge is challenging, even for humans. Inspired by this observation, we propose a general framework for incorporating various types of domain knowledge from multiple sources into biomedical PLMs. We encode domain knowledge using lightweight adapter modules, bottleneck feed-forward networks that are inserted into different locations of a backbone PLM. For each knowledge source of interest, we pretrain an adapter module to capture the knowledge in a self-supervised way. We design a wide range of self-supervised objectives to accommodate diverse types of knowledge, ranging from entity relations to description sentences. Once a set of pretrained adapters is available, we employ fusion layers to combine the knowledge encoded within these adapters for downstream tasks. Each fusion layer is a parameterized mixer of the available trained adapters that can identify and activate the most useful adapters for a given input. Our method diverges from prior work by including a knowledge consolidation phase, during which we teach the fusion layers to effectively combine knowledge from both the original PLM and newly-acquired external knowledge using a large collection of unannotated texts. After the consolidation phase, the complete knowledge-enhanced model can be fine-tuned for any downstream task of interest to achieve optimal performance. Extensive experiments on many biomedical NLP datasets show that our proposed framework consistently improves the performance of the underlying PLMs on various downstream tasks such as natural language inference, question answering, and entity linking. These results demonstrate the benefits of using multiple sources of external knowledge to enhance PLMs and the effectiveness of the framework for incorporating knowledge into PLMs. Finally, while primarily focused on the biomedical domain in this work, our framework is highly adaptable and can be easily applied to other domains, such as the bioenergy sector.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
Identification and evolution of active sites in isomorphously substituted Fe-ZSM-5 catalysts for methane dehydroaromatization (MDA)
Methane dehydroaromatization (MDA) enables the catalytic conversion of methane into aromatics, mainly benzene, along with hydrogen, in a single-step process under non-oxidative conditions. In this study, we prepared a series of isomorphously substituted Fe-ZSM-5 catalysts with exclusively isolated or low-oligomerized sites up to 3.2% Fe weight loading by adding ethylenediaminetetraacetic acid (EDTA) to the crystallization gel. These catalysts exhibit no induction/activation period and a significantly higher maximum product yield compared to Fe/ZSM-5 catalysts prepared by the incipient wetness impregnation method and containing extensively aggregated FeOx. This investigation focuses on the evolution of Fe sites during the post-synthetic treatments. Most importantly, we demonstrate the quantitative relation between Fe site isolation and catalytic activity, proving that isolated or low-oligomerized Fe species at the exchange sites formed during post-synthetic retreatment are the active sites for methane activation.
02 PETROLEUM↗
Studies of Slc30a10 Deficiency in Mice Reveal That Intestinal Iron Transporters Dmt1 and Ferroportin Transport Manganese
Not provided.
Gastroenterology & Hepatology↗
Fast multiscale Gaussian beam methods for wave equations in bounded convex domains
Motivated by fast multiscale Gaussian wavepacket transforms and multiscale Gaussian beam methods which were originally designed for pure initial-value problems of wave equations, we develop fast multiscale Gaussian beam methods for initial boundary value problems of wave equations in bounded convex domains in the high frequency regime. To compute the wave propagation in bounded convex domains, we have to take into account reflecting multiscale Gaussian beams, which are accomplished by enforcing reflecting boundary conditions during beam propagation and carrying out suitable reflecting beam summation. To propagate multiscale beams efficiently, we prove that the ratio of the squared magnitude of beam amplitude and the beam width is roughly conserved, and accordingly we propose an effective indicator to identify significant beams. We also prove that the resulting multiscale Gaussian beam methods converge asymptotically. Numerical examples demonstrate the accuracy and efficiency of the method.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Characterization of high-quality kerfless epitaxial silicon for solar cells: Defect sources and impact on minority-carrier lifetime
We investigate the types and origins of structural defects in thin (<100 μm) kerfless epitaxial single crystal silicon grown on top of reorganized porous silicon layers. Although the structural defect density is low (has average defect density < 10 4 cm -2 ), localized areas with a defect density > 10 5 cm -2 are observed. Cross-sectional and systematic plan-view defect etching and microscopy reveals that the majority of stacking faults and dislocations originate at the interface between the porous silicon layer and the epitaxial wafer. Localised dislocation clusters are observed in regions of collapsed/deformed porous silicon and at decorated stacking faults. In localized regions of high extended defect density, increased minority-carrier recombination activity is observed. Evidence for impurity segregation to the extended defects (internal gettering), which is known to exacerbate carrier recombination is demonstrated. In conclusion, the impact of the defects on material performance and substrate re-use is also discussed.
14 SOLAR ENERGY↗
Bimetallic NiCo boride nanoparticles confined in a MXene network enable efficient ambient ammonia electrosynthesis
Ambient electrocatalytic nitrogen fixation is an emerging technology for green ammonia synthesis, but the absence of optimized, stable and performant catalysts can render its practical application challenging. Herein, bimetallic NiCo boride nanoparticles confined in MXene are shown to accomplish high-performance nitrogen reduction electrolysis. Taking advantage of the synergistic effect in specific compositions with unique electronic d and p orbits and typical architecture of rich nanosized particles embedded in the interconnected conductive network, the synthesized MXene@NiCoB composite demonstrates extensive improvements in nitrogen molecule chemisorption, active area exposure and charge transport. As a result, optimal NH 3 yield rate of 38.7 μg h -1 mgcat. -1 and Faradaic efficiency of 6.92% are acquired in 0.1 M Na 2 SO 4 electrolyte. Moreover, the great catalytic performance can be almost entirely maintained in the cases of repeatedly-cycled and long-term electrolysis. Theoretical investigations reveal that the nitrogen reduction reaction on MXene@NiCoB catalyst proceeds according to the distal pathway, with a distinctly-reduced energy barrier relative to the Co 2 B counterpart. In conclusion, this work may inspire a new route towards the rational catalyst design for the nitrogen reduction reaction.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Engineering uranyl-chelating peptides from NikR for electrochemical peptide-based sensing applications
We have, for the first time, designed three uranyl-chelating peptides by modeling after the uranyl binding pocket found in a mutated Ni(II)-dependent transcriptional repressor (NikR). All three thiolated and methylene blue (MB)-modified peptides, NikR-5, NikR-11, and NikR-15, contain the five core amino acids responsible for target recognition, but the two longer peptides have either one or two additional glycine residues in between the five amino acids. These three peptide probes were then used in the fabrication of electrochemical peptide-based (E-PB) uranyl ion (U(VI)) sensors, with the goal of elucidating the effects of the added glycine residues and probe flexibility on target recognition. The sensing mechanism is similar to other “signal-off” E-PB sensors, in which binding of the target rigidifies the probe, resulting in a decrease in the redox signal from the tethered MB label. Although all three sensors responded to U(VI), the NikR-15 sensor's behavior was irreproducible and thus precluded from the rest of the study. The NikR-11 sensor showed the largest response to U(VI), whereas the NikR-5 sensor showed higher specificity for U(VI). The limit of detection was 50 nM for both sensors, which is well below the U.S. Environmental Protection Agency maximum contaminant level for uranium. Both sensors were further tested and proven functional in a 50% synthetic aquifer sample. Overall, the NikR-11 sensor, fabricated with the 11-amino acid probe, is deemed the optimal design. Incorporating glycine residues is a strategic way to lengthen the peptide slightly to improve target binding. This simple yet versatile approach to recreating binding pockets on electrode surfaces can potentially be employed in the design of other E-PB and surface-based metal ion sensors.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Effect of medium permeability anisotropy on the morphological evolution of two non-uniformities in a geochemical dissolution system
The morphological evolutions of chemical dissolution fronts have attracted increasing interest in the field of the geological sciences and in industrial applications. Extensive research based on numerical simulations has been conducted to understand how various mechanisms and processes influence the morphological evolution of chemical dissolution fronts within geological media. Most researchers in previous studies have assumed the medium permeability to be isotropic for developing numerical models, despite isotropic geological media being uncommon in the real world. This study investigates the effect of medium permeability anisotropy on the morphological evolutions of two non-uniformities with higher permeability in a geochemical dissolution system. A series of numerical simulations are performed to evaluate the effect of medium permeability anisotropy on the morphological evolution of a chemical dissolution front. The simulation results indicate that the patterns of the dissolution reaction front are substantially affected by medium permeability anisotropy. An increase in the permeability anisotropy ratio, which is defined as the ratio of the permeability in the transverse direction to that in the longitudinal direction, enhances the dominance of the flow-focusing effect over the stabilizing or merging effect induced by diffusion/dispersion mechanism. Therefore, an increase in the permeability anisotropy ratio can increase the fingering length of the dissolution front or cause the dissolution front to have a more unstable pattern. By contrast, a reduction in the permeability anisotropy ratio will weaken the flow-focusing effect, thereby reducing the fingering length of the dissolution front or changing the front morphology such that it has a more stable status. The effect of the permeability anisotropy ratio on the morphological evolution tends to decrease when the Zhao number (negative dimensionless upstream pressure gradient) of the system increases. The consideration of medium permeability anisotropy in the geochemical dissolution model renders the simulation of the morphological evolutions of dissolution reaction fronts more realistic.
58 GEOSCIENCES↗