Prediction and Identification of Potential Immunodominant Epitopes in Glycoproteins B, C, E, G, and I of Herpes Simplex Virus Type 2

Twenty B candidate epitopes of glycoproteins B (gB2), C (gC2), E (gE2), G (gG2), and I (gI2) of herpes simplex virus type 2 (HSV-2) were predicted using DNAstar, Biosun, and Antheprot methods combined with the polynomial method. Subsequently, the biological functions of the peptides were tested via experiments in vitro. Among the 20 epitope peptides, 17 could react with the antisera to the corresponding parent proteins in the EIA tests. In particular, five peptides, namely, gB2466–473 (EQDRKPRN), gC2216–223 (GRTDRPSA), gE2483–491 (DPPERPDSP), gG2572–579 (EPPDDDDS), and gI2286-295 (CRRRYRRPRG) had strong reaction with the antisera. All conjugates of the five peptides with the carrier protein BSA could stimulate mice into producing antibodies. The antisera to these peptides reacted strongly with the corresponding parent glycoproteins during the Western Blot tests, and the peptides reacted strongly with the antibodies against the parent glycoproteins during the EIA tests. The antisera against the five peptides could neutralize HSV-2 infection in vitro, which has not been reported until now. These results suggest that the immunodominant epitopes screened using software algorithms may be used for virus diagnosis and vaccine design against HSV-2

Coalbed methane accumulation, in-situ stress, and permeability of coal reservoirs in a complex structural region (Fukang area) of the southern Junggar Basin, China

The enrichment of coalbed methane (CBM), in-situ stress field, and permeability are three key factors that are decisive to effective CBM exploration. The southern Junggar Basin is the third large CBM basin in China but is also known for the occurrence of complex geological structures. In this study, we take the Fukang area of the southern Junggar Basin as an example, coalbed methane accumulation and permeability, and their geological controls were analyzed based on the determination of geological structures, in-situ stress, gas content, permeability, hydrology and coal properties. The results indicate that gas contents of the Fukang coal reservoirs are controlled by structural framework and burial depth, and high-to-ultra-high thickness of coals has a slightly positive effect on gas contents. Perennial water flow (e.g., the Baiyanghe River) favors gas accumulation by forming a hydraulic stagnant zone in deep reservoirs, but can also draw down gas contents by persistent transportation of dissolved gases to ground surfaces. Widely developed burnt rocks and sufficient groundwater recharge make microbial gases an important gas source in addition to thermogenic gases. The in-situ stress field of the Fukang area (700–1,500 m) is dominated by a normal stress regime, characterized by vertical stress > maximum horizontal stress > minor horizontal stress. Stress ratios, including lateral stress coefficient, natural stress ratios, and horizontal principal stress ratio are all included in the stress envelopes of China. Permeability in the Fukang area is prominently partitioned into two distinct groups, one group of low permeability (0.001–0.350 mD) and the other group of high permeability (0.988–16.640 mD). The low group of permeability is significantly formulated by depth-dependent stress variations, and the high group of permeability is controlled by the relatively high structural curvatures in the core parts of synclines and the distance to the syncline core. Meanwhile, coal deformation and varying dip angles intensify the heterogeneity and anisotropy of permeability in the Fukang area. These findings will promote the CBM recovery process in China and improve our understanding of the interaction between geological conditions and reservoir parameters and in complex structural regions

ADEPT: Automatic Differentiable DEsign of Photonic Tensor Cores

Photonic tensor cores (PTCs) are essential building blocks for optical artificial intelligence (AI) accelerators based on programmable photonic integrated circuits. PTCs can achieve ultra-fast and efficient tensor operations for neural network (NN) acceleration. Current PTC designs are either manually constructed or based on matrix decomposition theory, which lacks the adaptability to meet various hardware constraints and device specifications. To our best knowledge, automatic PTC design methodology is still unexplored. It will be promising to move beyond the manual design paradigm and "nurture" photonic neurocomputing with AI and design automation. Therefore, in this work, for the first time, we propose a fully differentiable framework, dubbed ADEPT, that can efficiently search PTC designs adaptive to various circuit footprint constraints and foundry PDKs. Extensive experiments show superior flexibility and effectiveness of the proposed ADEPT framework to explore a large PTC design space. On various NN models and benchmarks, our searched PTC topology outperforms prior manually-designed structures with competitive matrix representability, 2-30x higher footprint compactness, and better noise robustness, demonstrating a new paradigm in photonic neural chip design. The code of ADEPT is available at https://github.com/JeremieMelo/ADEPT using the https://github.com/JeremieMelo/pytorch-onn (TorchONN) library.Comment: Accepted to ACM/IEEE Design Automation Conference (DAC), 202

Post-Layout Simulation Driven Analog Circuit Sizing

Post-layout simulation provides accurate guidance for analog circuit design, but post-layout performance is hard to be directly optimized at early design stages. Prior work on analog circuit sizing often utilizes pre-layout simulation results as the optimization objective. In this work, we propose a post-layout-simulation-driven (post-simulation-driven for short) analog circuit sizing framework that directly optimizes the post-layout simulation performance. The framework integrates automated layout generation into the optimization loop of transistor sizing and leverages a coupled Bayesian optimization algorithm to search for the best post-simulation performance. Experimental results demonstrate that our framework can achieve over 20% better post-layout performance in competitive time than manual design and the method that only considers pre-layout optimization

Disconnection-mediated Twin/Twin-junction migration in FCC metals

We present the results of novel, time-resolved, in situ HRTEM observations, molecular dynamics (MD) simulations, and disconnection theory that elucidate the mechanism by which the motion of grain boundaries (GBs) in polycrystalline materials are coupled through disconnection motion/reactions at/adjacent to GB triple junctions (TJs). We focus on TJs composed of a pair of coherent twin boundaries (CTBs) and a Σ9 GB in copper. As for all GBs, disconnection theory implies that multiple modes/local mechanisms for CTB migration are possible and that the mode selection is affected by the nature of the driving force for migration. While we observe (HRTEM and MD) CTB migration through the motion of pure steps driven by chemical potential jump, other experimental observations (and our simulations) show that stress-driven CTB migration occurs through the motion of disconnections with a non-zero Burgers vector; these are pure-step and twinning-partial CTB migration mechanisms. Our experimental observations and simulations demonstrate that the motion of a GB drags its delimiting TJ and may force the motion of the other GBs meeting at the TJ. Our experiments and simulations focus on two types of TJs composed of a pair of CTBs and a Σ9 GB; a 107° TJ readily migrates while a 70° TJ is immobile (experiment, simulation) in agreement with our disconnection theory even though the intrinsic mobilities of the constituent GBs do not depend on TJ-type. We also demonstrate that disconnections may be formed at TJs (chemical potential jump/stress driven) and at GB/free surface junctions (stress-driven)

High‐Performance Doped Silver Films: Overcoming Fundamental Material Limits for Nanophotonic Applications

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137336/1/adma201605177-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137336/2/adma201605177_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137336/3/adma201605177.pd

Highly active and stable stepped Cu surface for enhanced electrochemical CO₂ reduction to C₂H₄

Electrochemical CO₂ reduction to value-added chemical feedstocks is of considerable interest for renewable energy storage and renewable source generation while mitigating CO₂ emissions from human activity. Copper represents an effective catalyst in reducing CO₂ to hydrocarbons or oxygenates, but it is often plagued by a low product selectivity and limited long-term stability. Here we report that copper nanowires with rich surface steps exhibit a remarkably high Faradaic efficiency for C₂H₄ that can be maintained for over 200 hours. Computational studies reveal that these steps are thermodynamically favoured compared with Cu(100) surface under the operating conditions and the stepped surface favours C₂ products by suppressing the C₁ pathway and hydrogen production

Highly active and stable stepped Cu surface for enhanced electrochemical CO₂ reduction to C₂H₄

Electrochemical CO₂ reduction to value-added chemical feedstocks is of considerable interest for renewable energy storage and renewable source generation while mitigating CO₂ emissions from human activity. Copper represents an effective catalyst in reducing CO₂ to hydrocarbons or oxygenates, but it is often plagued by a low product selectivity and limited long-term stability. Here we report that copper nanowires with rich surface steps exhibit a remarkably high Faradaic efficiency for C₂H₄ that can be maintained for over 200 hours. Computational studies reveal that these steps are thermodynamically favoured compared with Cu(100) surface under the operating conditions and the stepped surface favours C₂ products by suppressing the C₁ pathway and hydrogen production