A high temperature pressure sensor based on magnetic coupling and silicon wafer bonding

In this thesis, the design and fabrication of a bulk micromachined and wafer bonded pressure sensor for high temperature applications is described. The device design is based on the magnetic coupling principle as described by the Biot-Savart law. By combining the mechanical properties of single crystal silicon with magnetic coupling, the designed sensor can be operated up to 600°C. The key components within the sensor are two inductive coils, a silicon diaphragm and a hermetic vacuum cavity. The modeling based on a nine-turn single level coil device and a 300 μm x 300 diaphragm indicates an output rms voltage range of 70 mV with an input current of 100 mA and frequency of 200 MHz at pressures ranging from 0 kPa to 300 kPa for a sensitivity of 11 μV/mA.MHzkPa at 300°C. The output voltage doubles to 150 mV at 600 °C for the same pressure range. Experiments on 6-turn single-level aluminum foil coils showed a linear decrease in output with the reduction in coil dimensions as the Young\u27s modulus decreases. Experiments indicate that double-level or multi-level coils give substantially larger output. The sensor fabrication plan combines standard IC processing, anistropic etch of silicon and silicon wafer bonding. A KOH solution is used to etch the silicon and define the diaphragm. The diaphragm is formed by a boron diffusion technique. The diaphragm thickness is controlled by the diffusion depth and etch-stop technology. The silicon wafer bonding uses sputtered Pyrex as an intermediate adhesive layer. Pyrex has good thermal expansion of coefficient with that of silicon. This would ensure a good thermal match between the silicon and glass together with a good thermal stability at high temperatures

Effects of Nonaerated Circulation Water Velocity on Nutrient Release from Aquaculture Pond Sediments

Sustaining good water quality in aquaculture ponds is vital. Without an aerator, the dissolved oxygen in ponds comes primarily from mass transfer at the water-ambient atmosphere interface. As sediment can seriously affect water quality, this study used indoor experiments to examine the nutrient (nitrogen and phosphorus) release mechanisms and fluxes from sediment in aquaculture ponds with moving water but no aeration. The results showed that the ammonia nitrogen (NH3-N) concentration in the overlying water was inversely proportional to flow velocity and that a higher flow velocity tended to result in a lower concentration in the overlying water, a steeper vertical gradient of concentration within the bed sediments, and a faster release rate from the sediments. The sediment disturbed by flowing water released more nitrate nitrogen (NO3-N) and nitrite nitrogen (NO2-N) into the overlying water and NO2-N could become oxidized into NO3-N. In still water, NO3-N was released gradually and some anaerobic NO3-N was nitrified into NO2-N. Phosphorus release from the sediments was controlled by the adsorption-desorption balance, with the phosphorus concentration in the overlying water dropping gradually to a steady value from its initial maximum. The relationship between NH3-N release flux and flow rate is described by a cubic function

Domains Necessary for G␣ 12 Binding and Stimulation of Protein Phosphatase-2A (PP2A): Is G␣ 12 a Novel Regulatory Subunit of PP2A?

ABSTRACT Many cellular signaling pathways share regulation by protein phosphatase-2A (PP2A), a widely expressed serine/threonine phosphatase, and the heterotrimeric G protein G␣ 12 . PP2A activity is altered in carcinogenesis and in some neurodegenerative diseases. We have identified binding of G␣ 12 with the A␣ subunit of PP2A, a trimeric enzyme composed of A (scaffolding), B (regulatory), and C (catalytic) subunits and demonstrated that G␣ 12 stimulated phosphatase activity (J Biol Chem 279: [54983][54984][54985][54986] 2004). We now show in substrate-velocity analysis using purified PP2A that V max was stimulated 3-to 4-fold by glutathione transferase (GST)-G␣ 12 with little effect on K m values. To identify the binding domains mediating the A␣-G␣ 12 interaction, an extensive mutational analysis was performed. Well-characterized mutations of A␣ were expressed in vitro and tested for binding to GST-G␣ 12 in pull-down assays. G␣ 12 binds to A␣ along repeats 7 to 10, and PP2A B subunits are not necessary for binding. To identify where A␣ binds to G␣ 12 , a series of 61 G␣ 12 mutants were engineered to contain the sequence Asn-Ala-Ala-Ile-Arg-Ser (NAAIRS) in place of 6 consecutive amino acids. Mutant G␣ 12 proteins were individually expressed in human embryonic kidney cells and analyzed for interaction with GST or GST-A␣ in pull-down assays. The A␣ binding sites were localized to regions near the N and C termini of G␣ 12 . The expression of constitutively activated G␣ 12 (QL␣ 12 ) in Madin Darby canine kidney cells stimulated PP2A activity as determined by decreased phosphorylation of tyrosine 307 on the catalytic subunit. Based on crystal structures of G␣ 12 and PP2A A␣, a model describing the binding surfaces and potential mechanisms of G␣ 12 -mediated PP2A activation is presented

STREET: A Multi-Task Structured Reasoning and Explanation Benchmark

We introduce STREET, a unified multi-task and multi-domain natural language reasoning and explanation benchmark. Unlike most existing question-answering (QA) datasets, we expect models to not only answer questions, but also produce step-by-step structured explanations describing how premises in the question are used to produce intermediate conclusions that can prove the correctness of a certain answer. We perform extensive evaluation with popular language models such as few-shot prompting GPT-3 and fine-tuned T5. We find that these models still lag behind human performance when producing such structured reasoning steps. We believe this work will provide a way for the community to better train and test systems on multi-step reasoning and explanations in natural language.Comment: Published in ICLR 202

Prenatal Exposure to Polycyclic Aromatic Hydrocarbons, Benzo[a]pyrene–DNA Adducts, and Genomic DNA Methylation in Cord Blood

Background: Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic environmental pollutants generated during incomplete combustion. After exposure and during metabolism, PAHs can form reactive epoxides that can covalently bind to DNA. These PAH–DNA adducts are established markers of cancer risk. PAH exposure has been associated with epigenetic alterations, including genomic cytosine methylation. Both global hypomethylation and hypermethylation of specific genes have been associated with cancer and other diseases in humans. Experimental evidence suggests that PAH–DNA adduct formation may preferentially target methylated genomic regions. Early embryonic development may be a particularly susceptible period for PAH exposure, resulting in both increased PAH–DNA adducts and altered DNA methylation

Vomiting and wasting disease associated with hemagglutinating encephalomyelitis viruses infection in piglets in jilin, china

One coronavirus strain was isolated from brain tissues of ten piglets with evident clinical manifestations of vomiting, diarrhea and dyskinesia in Jilin province in China. Antigenic and genomic characterizations of the virus (isolate PHEV-JLsp09) were based on multiplex PCR and negative staining electron microscopy and sequence analysis of the Hemagglutinin-esterase (HE) gene. These piglets were diagnosed with Porcine hemagglutinating encephalomyelitis virus (PHEV)

miR-K12-7-5p Encoded by Kaposi's Sarcoma-Associated Herpesvirus Stabilizes the Latent State by Targeting Viral ORF50/RTA

Seventeen miRNAs encoded by Kaposi's sarcoma-associated herpesvirus (KSHV) have been identified and their functions have begun to be characterized. Among these miRNAs, we report here that miR-K12-7 directly targets the replication and transcription activator (RTA) encoded by open reading frame 50. We found that miR-K12-7 targeted the RTA 3′ untranslated region (RTA3′UTR) in a seed sequence-dependent manner. miR-K12-7-5p derived from miR-K12-7 mediates the inhibition of RTA expression, and the mutation of the seed match site totally abrogated the inhibitory effect of miR-K12-7 on RTA3′UTR. The inhibition of RTA expression by miR-K12-7 was further confirmed in the latently KSHV-infected 293/Bac36 cell line through transient transfection of miR-K12-7 expression plasmid or specific inhibitor of miR-K12-7-5p, respectively. The transient transfection of miR-K12-7 into 293/Bac36 cells reduced RTA expression and the expression of the downstream early genes regulated by RTA, and also the production of progeny virus was significantly reduced after treatment with chemical inducers. Our study revealed that another miRNA, miR-K12-7-5p, targets the viral immediate early gene RTA and that this miRNA contributes to the maintenance of viral latency

Infrared and Visible Image Fusion with Hybrid Image Filtering

Image fusion is an important technique aiming to generate a composite image from multiple images of the same scene. Infrared and visible images can provide the same scene information from different aspects, which is useful for target recognition. But the existing fusion methods cannot well preserve the thermal radiation and appearance information simultaneously. Thus, we propose an infrared and visible image fusion method by hybrid image filtering. We represent the fusion problem with a divide and conquer strategy. A Gaussian filter is used to decompose the source images into base layers and detail layers. An improved co-occurrence filter fuses the detail layers for preserving the thermal radiation of the source images. A guided filter fuses the base layers for retaining the background appearance information of the source images. Superposition of the fused base layer and fused detail layer generates the final fusion image. Subjective visual and objective quantitative evaluations comparing with other fusion algorithms demonstrate the better performance of the proposed method

MTQA: Text-Based Multitype Question and Answer Reading Comprehension Model

Text-based multitype question answering is one of the research hotspots in the field of reading comprehension models. Multitype reading comprehension models have the characteristics of shorter time to propose, complex components of relevant corpus, and greater difficulty in model construction. There are relatively few research works in this field. Therefore, it is urgent to improve the model performance. In this paper, a text-based multitype question and answer reading comprehension model (MTQA) is proposed. The model is based on a multilayer transformer encoding and decoding structure. In the decoding structure, the headers of the answer type prediction decoding, fragment decoding, arithmetic decoding, counting decoding, and negation are added for the characteristics of multiple types of corpora. Meanwhile, high-performance ELECTRA checkpoints are employed, and secondary pretraining based on these checkpoints and an absolute loss function are designed to improve the model performance. The experimental results show that the performance of the proposed model on the DROP and QUOREF corpora is better than the best results of the current existing models, which proves that the proposed MTQA model has high feature extraction and relatively strong generalization capabilities

Influence of Structural Parameters on Mechanical Properties of Triply Periodic Minimal Surface Structure

Titanium alloy is widely used in aerospace and other fields due to its low density, high specific strength, corrosion resistance, and other advantages. With the development of selective laser melting additive manufacturing technology, it is possible to manufacture triply periodic minimal surface porous structures. The effects of structural parameters on the mechanical properties of a Ti-6Al-4V Diamond (D)-type triply periodic minimal surface structure are studied. According to the characteristics of porous structures, the Gibson Ashby fitting formulas of D structures are modified using the concept of equivalent cross-sectional areas. The influence of cell size and surface thickness on the compressive modulus and strength of a D structure is discussed. Prediction formulas of the mechanical properties based on cell size and surface thickness are established by combining the relative density with the structural parameters. On this basis, the density optimization method is applied to the lightweight design of a rocket-related assembly based on D structure filling. The design results verify the feasibility of a lightweight design based on triply periodic minimal surface structure filling