WTC2005-64026 A MOLECULAR DYNAMICS STUDY ON THE STATIC AND DYNAMIC PROPERTIES OF LUBRICANT PFPE IN HARD DISK DRIVER

ABSTRACT The static and dynamic properties of lubricant PFPE are important for the service durability and reliability of the computer head-disk device. Thus molecular dynamic simulations based on a coarse-grained, bead-spring model are adopted to study those properties. On the one hand, we investigate the static properties and infer the structure of both nonpolar and polar PFPE films. For a nonpolar PFPE film, there is a layering structure in the surface layer. And for a polar PFPE film, besides layering structure, there is a bi-polymer structure in the bulk layer. On the other hand, we investigate the dynamic properties and find that for nonpolar PFPE film, a precursor film around one atomic diameter thickness develops according to layering structure; while for polar PFPE film, besides a precursor film, a much steeper and slower spreading shape appears according to bi-polymer structure

Long-term effects of restoration on the links between above-and belowground biodiversity in degraded Horqin sandy grassland, Northern China

Long-term ecological restoration plays an important role in the sustainable development of degraded grassland ecosystem. In this study, the levels of species diversity, genetic diversity and soil microbial diversity in restored grassland were measured by vegetation survey, DNA barcoding and soil microbial high-throughput sequencing technology, so as to explore the relationship between above- and belowground biodiversity and its driving factors in Horqin sandy grassland. In this study, the results found that herb are dominated in restoration grassland types. Plant species richness (SR) from post-non-grazing restoration plot (NGR) communities was significantly higher than other restoration communities (10 ± 1.1, p = 0.004). Genetic diversity indices of dominant plant species in chloroplast DNA (cpDNA), were remarkable greater than nuclear DNA (nrDNA) in each recovering sandy grassland plots (amplitude of difference was 44.8%–70.5% in allelic richness (AR), 81.9%–128.1% in expected heterozygosity (HE)). The soil bacterial and fungal richness from natural mobile dune grassland (NM) communities was notably lower than that from recovering grassland types (1641.9 ± 100.4, p < 0.001; 533 ± 16.6, p < 0.001). In this study, heterogeneous levels of genetic variability among different recovering sandy grassland types were detected. Correlation analyses revealed that there were positive correlations between species diversity and genetic diversity (SR & AR: r = 0.56, R2 = 0.31, p < 0.001; SR & HE: r = 0.33, R2 = 0.11, p = 0.045) and a negative correlation between soil microbial diversity and genetic diversity (r = -0.44, R2 = 0.19, p = 0.005). The final structural equation model explained 38% of the variance in SR, 57% in AR, 52% in soil microbial diversity (SD), 49% in aboveground biomass (AGB), 87% in soil organic carbon (SOC), 47% in soil alkali-hydrolyzable nitrogen (SAN) and 69% in soil available phosphorus (SOP). Long-term ecological restoration had significant direct positive effects on AGB, SOC, SAN, SOP, AR, SR and SD. There was a negative correlation between above- and belowground biodiversity and biological and abiotic factors. The results of this study have clarified the above- and underground biodiversity levels of sandy grassland and the relationship with driving factors under long-term ecological restoration measures, and will provide effective support for the management and sustainable development of sandy grassland

137Caesium, 40Potassium and potassium in raw and deep-oil stir-fried mushroom meals from Yunnan in China

A number of wild, edible mushroom species (Baorangia bicolor, Boletus calopus, Boletus obsclereumbrinus, Butyriboletus roseoflavus, Rubroboletus sinicus, Rugiboletus extremiorientalis and Xerocomus sp.) were collected in 2017, from Yunnan (Yuxi prefecture) in SW China. Samples of raw and stir-fried pools of these specimens were analysed for radioisotopes 137Cs (caesium) and 40 K (potassium), and for total K concentrations. On a whole (wet) weight (ww) basis, 137Cs activity ranged from <0.10 to 0.75 Bq kg−1 for raw, and from 0.5 to 4.4 Bq kg-1 in stir-fried mushrooms. Radiopotassium (40K) activity ranged from 57 to 96 Bq kg−1 ww for raw, and 170 to 370 Bq kg−1 ww for stir-fried mushrooms, while the corresponding concentration ranges for total K were 2100–3400 mg kg−1 ww (mean: 2800 ± 3900 mg kg−1 ww), and 6000–13000 mg kg−1 ww) mean: 8700 ± 2100 mg kg−1 ww), respectively. This data indicates that mushrooms from this region show negligible 137Cs contamination with evidently higher activity levels of 40K. The deep oil stir-frying process results in enrichment in the resulting meals for all three determinants. 100 g meal portions showed 137Cs activity in the range <0.08 to 0.44 Bq 100 g−1 ww (mean 0.15 ± 0.12 Bq 100 g−1 ww), and 40K activity from 16 to 37 Bq 100 g−1 ww (mean 24 ± 6 Bq 100 g−1 ww). The consequent exposure from 40K contained in a single 100 g serving and weekly (100 g x7) servings was equivalent to radiation doses in the range of 0.099 to 0.23 µSv and 0.68–1.6 µSv per capita (means 0.15 ± 0.04 and 1.1 ± 0.3 µSv). This is equivalent to doses in the range of 0.0017 to 0.0038 µSv kg-1 bm day-1 and 0.011 to 0.027 µSv kg-1 bm week-1 respectively (mean values of 0.0025 ± 0.006 µSv kg-1 bm day-1and 0.018 ± 0.004 µSv kg-1 bm week-1). Analogically to the annual 137Cs radiation exposure resulting from high rates of annual consumption (20–24 kg per capita), the estimated annual dose of radiation from 40K would range from 0.34 up to 0.92 µSv kg-1 bm (mean 0.60 µSv kg-1 bm). Thus in practice, high annual consumption rates of wild, stir-fried mushrooms as seen in Yunnan, would result in negligible internal doses from decay of artificial 137Cs, relative to that from natural 40K. The 100 g servings also contained between 590–1300 mg K making this local food one of the top dietary sources of nutritionally important potassium for local consumers

Reference Ranges and Association of Age and Lifestyle Characteristics with Testosterone, Sex Hormone Binding Globulin, and Luteinizing Hormone among 1166 Western Chinese Men

Decreased total testosterone (TT) is the recommended metric to identify age-related hypogonadism. However, average TT and the extent to which it varies by age, can vary substantially among different populations. Population-specific reference ranges are needed to understand normal versus abnormal TT levels. Therefore, the goal for this study was to describe androgen concentrations and their correlates among Western Chinese men. We completed a population-based, cross-sectional study including 227 young adults (YA) (20–39 years) and 939 older adults (OA) (40–89 years). We measured TT, sex-hormone binding globulin (SHBG), luteinizing hormone (LH), testosterone secreting index (TSI), and calculated free testosterone (cFT). Reference ranges for this population were determined using average YA concentrations. Multivariable regression models were used to predict hormone concentrations adjusting for age, waist-to-height ratio (WHR), marital status, education, occupation, smoking, alcohol, blood glucose, and blood pressure. Among OA, 3.8% had low TT, 15.2% had low cFT, 26.3% had low TSI, 21.6% had high SHBG, and 6.1% had high LH. Average cFT was significantly lower in OA (0.30 nmol/L; standard deviation (SD): 0.09) versus YA (0.37; SD: 0.11) but TT was not different in OA (16.82 nmol/L; SD: 4.80) versus YA (16.88; SD: 5.29). In adjusted models increasing age was significantly associated with increased SHBG or LH, and decreased cFT or TSI; however, TT was not significantly associated with age (β = 0.02 nmol/L; 95% confidence interval (CI): -0.01, 0.04). Higher WHR was associated with significantly decreased TT, SHBG, TSI, and LH. The only variable significantly related to cFT was age (β = -0.0033; 95% CI:-0.0037, -0.0028); suggesting that cFT measurements would not be confounded by other lifestyle factors. In conclusion, cFT, but not TT, varies with age in this population, suggesting cFT may be a better potential marker for age-related androgen deficiency than TT among Western Chinese men

Twist Promotes Tumor Metastasis in Basal-Like Breast Cancer by Transcriptionally Upregulating ROR1

Rationale: Twist is a key transcription factor for induction of epithelial-mesenchymal transition (EMT), which promotes cell migration, invasion, and cancer metastasis, confers cancer cells with stem cell-like characteristics, and provides therapeutic resistance. However, the functional roles and targeted genes of Twist in EMT and cancer progression remain elusive. Methods: The potential targeted genes of Twist were identified from the global transcriptomes of T47D/Twist cells by microarray analysis. EMT phenotype was detected by western blotting and immunofluorescence of marker proteins. The dual-luciferase reporter and chromatin immunoprecipitation assays were employed to observe the direct transcriptional induction of ROR1 by Twist. A lung metastasis model was used to study the pro-metastatic role of Twist and ROR1 by injecting MDA-MB-231 cells into tail vein of nude mice. Bio-informatics analysis was utilized to measure the metastasis-free survival of breast cancer patients. Results: Twist protein was proved to directly activate the transcription of ROR1 gene, a receptor of Wnt5a in non-canonical WNT signaling pathway. Silencing of ROR1 inhibited EMT process, cell migration, invasion, and cancer metastasis of basal-like breast cancer (BLBC) cells. Knockdown of ROR1 also ameliorated the pro-metastatic effect of Twist. Furthermore, analyses of clinical specimens indicated that high expression of both ROR1 and Twist tightly correlates with poor metastasis-free survival of breast cancer patients. Conclusion: ROR1 is a targeted gene of Twist. Twist/ROR1 signaling is critical for invasion and metastasis of BLBC cells

Dynamical trust and reputation computation model for B2C E-Commerce

Trust is one of the most important factors that influence the successful application of network service environments, such as e-commerce, wireless sensor networks, and online social networks. Computation models associated with trust and reputation have been paid special attention in both computer societies and service science in recent years. In this paper, a dynamical computation model of reputation for B2C e-commerce is proposed. Firstly, conceptions associated with trust and reputation are introduced, and the mathematical formula of trust for B2C e-commerce is given. Then a dynamical computation model of reputation is further proposed based on the conception of trust and the relationship between trust and reputation. In the proposed model, classical varying processes of reputation of B2C e-commerce are discussed. Furthermore, the iterative trust and reputation computation models are formulated via a set of difference equations based on the closed-loop feedback mechanism. Finally, a group of numerical simulation experiments are performed to illustrate the proposed model of trust and reputation. Experimental results show that the proposed model is effective in simulating the dynamical processes of trust and reputation for B2C e-commerce

Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia

Assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation strategies. Sang et al. assemble a reference genome for Populus koreana and combine population genomics and modelling to predict spatiotemporal responses to climate change.Rapid global climate change is posing a substantial threat to biodiversity. The assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation and mitigation strategies. Here we generate a chromosome-scale genome assembly and re-sequence genomes of 230 individuals collected from 24 populations for Populus koreana, a pioneer and keystone tree species in temperate forests of East Asia. We integrate population genomics and environmental variables to reveal a set of climate-associated single-nucleotide polymorphisms, insertion/deletions and structural variations, especially numerous adaptive non-coding variants distributed across the genome. We incorporate these variants into an environmental modeling scheme to predict a highly spatiotemporal shift of this species in response to future climate change. We further identify the most vulnerable populations that need conservation priority and many candidate genes and variants that may be useful for forest tree breeding with special aims. Our findings highlight the importance of integrating genomic and environmental data to predict adaptive capacity of a key forest to rapid climate change in the future

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a million hours of audio. We find that the combination of pre-training, self-training and scaling up model size greatly increases data efficiency, even for extremely large tasks with tens of thousands of hours of labeled data. In particular, on an ASR task with 34k hours of labeled data, by fine-tuning an 8 billion parameter pre-trained Conformer model we can match state-of-the-art (SoTA) performance with only 3% of the training data and significantly improve SoTA with the full training set. We also report on the universal benefits gained from using big pre-trained and self-trained models for a large set of downstream tasks that cover a wide range of speech domains and span multiple orders of magnitudes of dataset sizes, including obtaining SoTA performance on many public benchmarks. In addition, we utilize the learned representation of pre-trained networks to achieve SoTA results on non-ASR tasks.Comment: 14 pages, 7 figures, 13 tables; v2: minor corrections, reference baselines and bibliography updated; v3: corrections based on reviewer feedback, bibliography update