Categorisation of Tinnitus Severity for the Mandarin Tinnitus Questionnaire

Background: The Tinnitus Questionnaire is commonly used to evaluate the psychological impact of tinnitus and has been translated into Mandarin. The original English version of the Tinnitus Questionnaire was translated into Mandarin (MTQ). The MTQ included not the same items compared with original version. Thus, MTQ should have its own severity categorization. Aims/objectives: The objective of this research was to develop a method to categorize tinnitus patients by clinical severity using scores from the Mandarin Tinnitus Questionnaire (MTQ). Material and Methods: A total of 192 participants with primary complaint of tinnitus were enrolled. Cross-tabulation was used to compare two categorization approaches of tinnitus severity. With the first approach, categories were assigned based purely on quartiles of MTQ scores. In the second approach, severity was determined based on Ordinal logistic regression. The two approaches were verified by comparing the consistency with clinical judgement. Results: Categorization based on quartiles showed low consistency with clinical assessment(kappa=0.33), while categorization based on ordinal logistic regression showed good consistency with clinical assessment(kappa = 0.86).Regression-based MTQ score cut-offs were 47 for severe tinnitus. Conclusions and significance: Tinnitus severity can be categorized accurately using ordinal logistic regression analysis of MTQ scores

Zc(3900)Z_c(3900) as a DDˉ∗D\bar{D}^* molecule from the pole counting rule

A comprehensive study on the nature of the $Z_c(3900)$ resonant structure is carried out in this work. By constructing the pertinent effective Lagrangians and considering the important final-state-interaction effects, we first give a unified description to all the relevant experimental data available, including the $J/\psi\pi$ and $\pi\pi$ invariant mass distributions from the $e^+e^-\to J/\psi\pi\pi$ process, the $h_c\pi$ distribution from $e^+e^-\to h_c\pi\pi$ and also the $D\bar D^{*}$ spectrum in the $e^+e^-\to D\bar D^{*}\pi$ process. After fitting the unknown parameters to the previous data, we search the pole in the complex energy plane and find only one pole in the nearby energy region in different Riemann sheets. Therefore we conclude that $Z_c(3900)$ is of $D\bar D^*$ molecular nature, according to the pole counting rule method~[Nucl.~Phys.~A543, 632 (1992); Phys.~Rev.~D 35,~1633 (1987)]. We emphasize that the conclusion based upon the pole counting method is not trivial, since both the $D\bar D^{*}$ contact interactions and the explicit $Z_c$ exchanges are introduced in our analyses and they lead to the same conclusion.Comment: 21 pages, 9 figures. To match the published version in PRD. Additional discussion on the spectral density function is include

Variations of China's emission estimates:Response to uncertainties in energy statistics

The accuracy of China's energy statistics is of great concern because it contributes greatly to the uncertainties in estimates of global emissions. This study attempts to improve the understanding of uncertainties in China's energy statistics and evaluate their impacts on China's emissions during the period of 1990-2013. We employed the Multi-resolution Emission Inventory for China (MEIC) model to calculate China's emissions based on different official data sets of energy statistics using the same emission factors. We found that the apparent uncertainties (maximum discrepancy) in China's energy consumption increased from 2004 to 2012, reaching a maximum of 646Mtce (million tons of coal equivalent) in 2011 and that coal dominated these uncertainties. The discrepancies between the national and provincial energy statistics were reduced after the three economic censuses conducted during this period, and converging uncertainties were found in 2013. The emissions calculated from the provincial energy statistics are generally higher than those calculated from the national energy statistics, and the apparent uncertainty ratio (the ratio of the maximum discrepancy to the mean value) owing to energy uncertainties in 2012 took values of 30.0, 16.4, 7.7, 9.2 and 15.6%, for SO2, NOx, VOC, PM2.5 and CO2 emissions, respectively. SO2 emissions are most sensitive to energy uncertainties because of the high contributions from industrial coal combustion. The calculated emission trends are also greatly affected by energy uncertainties - from 1996 to 2012, CO2 and NOx emissions, respectively, increased by 191 and 197% according to the provincial energy statistics but by only 145 and 139% as determined from the original national energy statistics. The energy-induced emission uncertainties for some species such as SO2 and NOx are comparable to total uncertainties of emissions as estimated by previous studies, indicating variations in energy consumption could be an important source of China's emission uncertainties

Fast Nearest Neighbor Machine Translation

Though nearest neighbor Machine Translation ($k$NN-MT) \citep{khandelwal2020nearest} has proved to introduce significant performance boosts over standard neural MT systems, it is prohibitively slow since it uses the entire reference corpus as the datastore for the nearest neighbor search. This means each step for each beam in the beam search has to search over the entire reference corpus. $k$NN-MT is thus two-orders slower than vanilla MT models, making it hard to be applied to real-world applications, especially online services. In this work, we propose Fast $k$NN-MT to address this issue. Fast $k$NN-MT constructs a significantly smaller datastore for the nearest neighbor search: for each word in a source sentence, Fast $k$NN-MT first selects its nearest token-level neighbors, which is limited to tokens that are the same as the query token. Then at each decoding step, in contrast to using the entire corpus as the datastore, the search space is limited to target tokens corresponding to the previously selected reference source tokens. This strategy avoids search through the whole datastore for nearest neighbors and drastically improves decoding efficiency. Without loss of performance, Fast $k$NN-MT is two-orders faster than $k$NN-MT, and is only two times slower than the standard NMT model. Fast $k$NN-MT enables the practical use of $k$NN-MT systems in real-world MT applications. The code is available at \url{https://github.com/ShannonAI/fast-knn-nmt}Comment: To appear at ACL 2022 Finding

Generating Giant and Tunable Nonlinearity in a Macroscopic Mechanical Resonator from Chemical Bonding Force

Nonlinearity in macroscopic mechanical system plays a crucial role in a wide variety of applications, including signal transduction and processing, synchronization, and building logical devices. However, it is difficult to generate nonlinearity due to the fact that macroscopic mechanical systems follow the Hooke's law and response linearly to external force, unless strong drive is used. Here we propose and experimentally realize a record-high nonlinear response in macroscopic mechanical system by exploring the anharmonicity in deforming a single chemical bond. We then demonstrate the tunability of nonlinear response by precisely controlling the chemical bonding interaction, and realize a cubic elastic constant of \mathversion{bold}$2 \times 10^{18}~{\rm N}/{\rm m^3}$, many orders of magnitude larger in strength than reported previously. This enables us to observe vibrational bistate transitions of the resonator driven by the weak Brownian thermal noise at 6~K. This method can be flexibly applied to a variety of mechanical systems to improve nonlinear responses, and can be used, with further improvements, to explore macroscopic quantum mechanics

Comparative transcriptome analysis on the synthesis pathway of honey bee (Apis mellifera) mandibular gland secretions

Secretions from mandibular glands (MGs) have important caste-specific functions that are associated with the social evolution of honey bees. To gain insights into the molecular architecture underlying these caste differences, we compared the gene expression patterns of MGs from queens, queenright workers (WQRs) and queenless workers (WQLs) using high-throughput RNA-sequencing technology. In total, we identified 46 candidate genes associated with caste-specific biosynthesis of fatty acid pheromones in the MG, including members of cytochrome P450 (CYP450) family and genes involved in fatty acid β-oxidation and ω-oxidation. For further identification of the CYP450s genes involved in the biosynthesis of MG secretions, we analyzed by means of qPCR, the expression levels of six of the CYP450 genes most abundantly expressed in the transcriptome analysis across different castes, ages, tasks and tissues. Our analysis revealed that CYP6AS8 and CYP6AS11, the most abundantly expressed CYP450 genes in worker and queen MGs, respectively, are selectively expressed in the MGs of workers and queens compared to other tissues. These results suggest that these genes might be responsible for the critical bifurcated hydroxylation process in the biosynthesis pathway. Our study contributes to the description of the molecular basis for the biosynthesis of fatty acid-derived pheromones in the MGs.The National Natural Science Foundation of China (No. 31101773), the Science and Technology Department of Zhejiang Province, China (F.H., 2016C02054-11) and the earmarked funds for Modern Agroindustry Technology Research System (No. CARS-45).http://www.nature.com/scientificreportsam2017Zoology and Entomolog

Association between bile acid metabolism and bone mineral density in postmenopausal women

OBJECTIVES: Previous studies have not shown any correlation between bile acid metabolism and bone mineral density (BMD) in women with postmenopausal osteoporosis. Thus, the current study evaluated the association between bile acid levels as well as BMD and bone turnover marker levels in this group of women. METHODS: This single-center cross-sectional study included 150 postmenopausal Chinese women. According to BMD, the participants were divided into three groups: osteoporosis group, osteopenia group, and healthy control group. Serum bile acid, fibroblast growth factor 19 (FGF19), and bone turnover biomarker levels were assessed. Moreover, the concentrations of parathyroid hormone, 25-hydroxy vitamin D [25(OH)D], procollagen type I N-peptide (P1NP), and beta-CrossLaps of type I collagen containing cross-linked C-terminal telopeptide (bCTX) were evaluated. The BMD of the lumbar spine and proximal femur were examined via dual-energy X-ray absorptiometry. RESULTS: The serum total bile acid levels in the osteoporosis and osteopenia groups (5.28±1.56 and 5.31±1.56 umol/L, respectively) were significantly lower than that in the healthy control group (6.33±2.04 umol/L; p=0.002 and 0.018, respectively). Serum bile acid level was positively associated with the BMD of the lumbar spine, femoral neck, and total hip. However, it negatively correlated with b-CTX concentration. Moreover, no correlation was observed between bile acid and P1NP levels, and the levels of the other biomarkers that were measured did not differ between the groups. CONCLUSION: Serum bile acid was positively correlated with BMD and negatively correlated with bone turnover biomarkers reflecting bone absorption in postmenopausal women. Thus, bile acid may play an important role in bone metabolism