Improving mobility of silicon metal-oxide-semiconductor devices for quantum dots by high vacuum activation annealing

To improve mobility of fabricated silicon metal-oxide-semiconductor (MOS) quantum devices, forming gas annealing is a common method used to mitigate the effects of disorder at the Si/SiO2 interface. However, the importance of activation annealing is usually ignored. Here, we show that a high vacuum environment for implantation activation is beneficial for improving mobility compared to nitrogen atmosphere. Low-temperature transport measurements of Hall bars show that peak mobility can be improved by a factor of two, reaching 1.5 m^2/(Vs) using high vacuum annealing during implantation activation. Moreover, the charge stability diagram of a single quantum dot is mapped, with no visible disturbance caused by disorder, suggesting possibility of fabricating high-quality quantum dots on commercial wafers. Our results may provide valuable insights into device optimization in silicon-based quantum computing.Comment: 13 pages, 4 figure

Synteny analysis in Rosids with a walnut physical map reveals slow genome evolution in long-lived woody perennials.

BackgroundMutations often accompany DNA replication. Since there may be fewer cell cycles per year in the germlines of long-lived than short-lived angiosperms, the genomes of long-lived angiosperms may be diverging more slowly than those of short-lived angiosperms. Here we test this hypothesis.ResultsWe first constructed a genetic map for walnut, a woody perennial. All linkage groups were short, and recombination rates were greatly reduced in the centromeric regions. We then used the genetic map to construct a walnut bacterial artificial chromosome (BAC) clone-based physical map, which contained 15,203 exonic BAC-end sequences, and quantified with it synteny between the walnut genome and genomes of three long-lived woody perennials, Vitis vinifera, Populus trichocarpa, and Malus domestica, and three short-lived herbs, Cucumis sativus, Medicago truncatula, and Fragaria vesca. Each measure of synteny we used showed that the genomes of woody perennials were less diverged from the walnut genome than those of herbs. We also estimated the nucleotide substitution rate at silent codon positions in the walnut lineage. It was one-fifth and one-sixth of published nucleotide substitution rates in the Medicago and Arabidopsis lineages, respectively. We uncovered a whole-genome duplication in the walnut lineage, dated it to the neighborhood of the Cretaceous-Tertiary boundary, and allocated the 16 walnut chromosomes into eight homoeologous pairs. We pointed out that during polyploidy-dysploidy cycles, the dominant tendency is to reduce the chromosome number.ConclusionSlow rates of nucleotide substitution are accompanied by slow rates of synteny erosion during genome divergence in woody perennials

Modified Technique of Pancreaticogastrostomy for Soft Pancreas with Two Continuous Hemstitch Sutures: A Single-Center Prospective Study

Postoperative pancreatic fistula (POPF) remains a persistent problem after pancreaticoduodenectomy (PD), especially in the presence of a soft, nonfibrotic pancreas. To reduce the risk of POPF, pancreaticogastrostomy (PG) is an optional reconstruction technique for surgeons after PD. This study presents a new technique of PG for a soft, nonfibrotic pancreas with double-binding continuous hemstitch sutures and evaluates its safety and reliability. From January 2011 to June 2012, 92 cases of patients with periampullary malignancy with a soft pancreas underwent this technique. A modified technique of PG was performed with two continuous hemstitch sutures placed in the mucosal and seromuscular layers of the posterior gastric wall, respectively. Then the morbidity and mortality was calculated. This technique was applied in 92 patients after PD all with soft pancreas. The median time for the anastomosis was 12 min (range, 8–24). Operative mortality was zero, and morbidity was 16.3 % (n = 15), including hemorrhage (n = 2), biliary fistula (n = 2), pulmonary infection (n = 1), delayed gastric emptying (DGE; n = 5, 5.4 %), abdominal abscess (n = 3, one caused by PF), and POPF (n = 2, 2.2 %). Two patients developed a pancreatic fistula (one type A and one type B) classified according to the International Study Group on Pancreatic Fistula. The described technique is a simple and safe reconstruction procedure after PD, especially for patients with a soft and fragile pancreas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11605-013-2183-8) contains supplementary material, which is available to authorized users

MoWE: Mixture of Weather Experts for Multiple Adverse Weather Removal

Currently, most adverse weather removal tasks are handled independently, such as deraining, desnowing, and dehazing. However, in autonomous driving scenarios, the type, intensity, and mixing degree of the weather are unknown, so the separated task setting cannot deal with these complex conditions well. Besides, the vision applications in autonomous driving often aim at high-level tasks, but existing weather removal methods neglect the connection between performance on perceptual tasks and signal fidelity. To this end, in upstream task, we propose a novel \textbf{Mixture of Weather Experts(MoWE)} Transformer framework to handle complex weather removal in a perception-aware fashion. We design a \textbf{Weather-aware Router} to make the experts targeted more relevant to weather types while without the need for weather type labels during inference. To handle diverse weather conditions, we propose \textbf{Multi-scale Experts} to fuse information among neighbor tokens. In downstream task, we propose a \textbf{Label-free Perception-aware Metric} to measure whether the outputs of image processing models are suitable for high level perception tasks without the demand for semantic labels. We collect a syntactic dataset \textbf{MAW-Sim} towards autonomous driving scenarios to benchmark the multiple weather removal performance of existing methods. Our MoWE achieves SOTA performance in upstream task on the proposed dataset and two public datasets, i.e. All-Weather and Rain/Fog-Cityscapes, and also have better perceptual results in downstream segmentation task compared to other methods. Our codes and datasets will be released after acceptance

High freezing rate improves flavor fidelity effect of hand grab mutton after short-term frozen storage

Taking the eutectic point as the final freezing temperature, the differences of flavor substances of in hand grab mutton (HGM) frozen at three rates of 0. 26 cm/h (−18°C), 0.56 cm/h (−40°C) and 2.00 cm/h (−80°C) were determined and analyzed. The results showed that the flavor of HGM decreased significantly after freezing. With the increase of freezing rate, the contents of aldehydes, alcohols, ketones, acids, esters, others, free amino acids and 5′-nucleotides were higher, and the content of specific substances was also generally increased. All samples from unfrozen and frozen HGM could be divided into four groups using an electronic nose based on different flavor characteristics. Seven common key aroma components were determined by relative odor activity value (ROAV), including hexanal, heptanal, octanal, nonanal, (E)-oct-2-enal, (2E,4E)-deca-2,4-dienal and oct-1-en-3-ol. The higher the freezing rate, the greater the ROAVs. Taste activity values calculated by all taste substances were far <1, and the direct contribution of the substances to the taste of HGM was not significant. The equivalent umami concentration of HGM frozen at −80°C was the highest. These findings indicated that higher freezing rate was more conducive to the retention of flavor substances in HGM, and the flavor fidelity effect of freezing at −80°C was particularly remarkable

In-depth analysis of music structure as a self-organized network

Words in a natural language not only transmit information but also evolve with the development of civilization and human migration. The same is true for music. To understand the complex structure behind the music, we introduced an algorithm called the Essential Element Network (EEN) to encode the audio into text. The network is obtained by calculating the correlations between scales, time, and volume. Optimizing EEN to generate Zipfs law for the frequency and rank of the clustering coefficient enables us to generate and regard the semantic relationships as words. We map these encoded words into the scale-temporal space, which helps us organize systematically the syntax in the deep structure of music. Our algorithm provides precise descriptions of the complex network behind the music, as opposed to the black-box nature of other deep learning approaches. As a result, the experience and properties accumulated through these processes can offer not only a new approach to the applications of Natural Language Processing (NLP) but also an easier and more objective way to analyze the evolution and development of music.Comment: 5 page