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Understanding the association between sleep traits and tinnitus could help prevent and provide appropriate interventions against tinnitus. Therefore, this study aimed to assess the relationship between different sleep patterns and tinnitus.A cross-sectional analysis using baseline data (2006-2010, n = 168,064) by logistic regressions was conducted to evaluate the association between sleep traits (including the overall health sleep score and five sleep behaviors) and the occurrence (yes/no), frequency (constant/transient), and severity (upsetting/not upsetting) of tinnitus. Further, a prospective analysis of participants without tinnitus at baseline (n = 9581) was performed, who had been followed-up for 7 years (2012-2019), to assess the association between new-onset tinnitus and sleep characteristics. Moreover, a subgroup analysis was also carried out to estimate the differences in sex by dividing the participants into male and female groups. A sensitivity analysis was also conducted by excluding ear-related diseases to avoid their confounding effects on tinnitus (n = 102,159).In the cross-sectional analysis, participants with "current tinnitus" (OR: 1.13, 95% CI: 1.04-1.22, p = 0.004) had a higher risk of having a poor overall healthy sleep score and unhealthy sleep behaviors such as short sleep durations (OR: 1.09, 95% CI: 1.04-1.14, p0.001), late chronotypes (OR: 1.09, 95% CI: 1.05-1.13, p0.001), and sleeplessness (OR: 1.16, 95% CI: 1.11-1.22, p0.001) than those participants who "did not have current tinnitus." However, this trend was not obvious between "constant tinnitus" and "transient tinnitus." When considering the severity of tinnitus, the risk of "upsetting tinnitus" was obviously higher if participants had lower overall healthy sleep scores (OR: 1.31, 95% CI: 1.13-1.53, p0.001). Additionally, short sleep duration (OR: 1.22, 95% CI: 1.12-1.33, p0.001), late chronotypes (OR: 1.13, 95% CI: 1.04-1.22, p = 0.003), and sleeplessness (OR: 1.43, 95% CI: 1.29-1.59, p0.001) showed positive correlations with "upsetting tinnitus." In the prospective analysis, sleeplessness presented a consistently significant association with "upsetting tinnitus" (RR: 2.28, p = 0.001). Consistent results were observed in the sex subgroup analysis, where a much more pronounced trend was identified in females compared with the males. The results of the sensitivity analysis were consistent with those of the cross-sectional and prospective analyses.Different types of sleep disturbance may be associated with the occurrence and severity of tinnitus; therefore, precise interventions for different types of sleep disturbance, particularly sleeplessness, may help in the prevention and treatment of tinnitus.

BACKGROUND: It remains unclear if patients with allergic rhinitis (AR) and/or asthma are susceptible to corona virus disease 2019 (COVID-19) infection, severity, and mortality. OBJECTIVE: To investigate the role of AR and/or asthma in COVID-19 infection, severity, and mortality, and assess whether long-term AR and/or asthma medications affected the outcomes of COVID-19. METHODS: Demographic and clinical data of 70,557 adult participants completed SARS-CoV-2 testing between March 16 and December 31, 2020, in the UK Biobank were analyzed. The rates of COVID-19 infection, hospitalization, and mortality in relation to pre-existing AR and/or asthma were assessed based on adjusted generalized linear models. We further analyzed the impact of long-term AR and/or asthma medications on the risk of COVID-19 hospitalization and mortality. RESULTS: Patients with AR of all ages had lower positive rates of SARS-CoV-2 tests (relative risk [RR]: 0.75, 95% confidence interval [CI]: 0.69-0.81, P < .001), with lower susceptibility in males (RR: 0.74, 95% CI: 0.65-0.85, P < .001) than females (RR: 0.8, 95% CI: 0.72-0.9, P < .001). However, similar effects of asthma against COVID-19 hospitalization were only major in participants aged

Sweater pattern design plays a crucial role in practical production, determining whether the finished products can meet the requirements of customers. In addition, pattern-designing is also a vital...

Accurate prognostic prediction for head and neck cancer (HNC) is important for the improvement of clinical management. We aimed to compare the prognostic value of various machine learning techniques (MLTs) and statistical Cox regression model for different types of HNC.Clinical data of HNC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 1974 to 2016. The prediction performance of five ML models, including random forest (RF), gradient boosting decision tree (GBDT), support vector machine (SVM), neural network (NN) and deep learning (DL), were compared with the statistical Cox regression model by estimating the concordance index (C-index), integrated Brier score (IBS), time-dependent receiver operating characteristic (ROC) curve and the area under the curve (AUC).Our results showed that the RF model outperformed all other models in prognostic prediction for all tumor sites of HNC, particularly for major salivary gland cancer (MSGC, C-index: 88.730 ± 0.8700, IBS: 7.680 ± 0.4800), oral cavity cancer (OCC, C-index: 84.250 ± 0.6700, IBS: 11.480 ± 0.3300) and oropharyngeal cancer (OPC, C-index: 82.510 ± 0.5400, IBS: 10.120 ± 0.1400). Meanwhile, we analyzed the importance of each clinical variable in the RF model, in which age and tumor size presented the strongest positive prognostic effects. Additionally, similar results can be observed in the internal (6The RF model is a promising prognostic prediction tool for HNC patients, regardless of the anatomic subsites.

Heavy metals can be enriched in living organisms and seriously endanger human health and the ecological environment, which has evolved into a significant global environmental problem. Based on summarizing the spatial distribution of heavy metals in the environment, this review introduces heavy metal detection technologies such as inductively coupled plasma mass spectrometry/atomic emission spectrometry, atomic absorption spectrometry, atomic fluorescence spectrometry, and laser-induced breakdown spectrometry. It summarizes their respective advantages, characteristics, and applicability. Besides, atmospheric pressure discharge plasma as a potential heavy metal detection technology is also introduced and discussed in this review. The current research mainly focuses on improving the analytical performance and optimizing the practical application. Furthermore, this review not only summarizes the advantages of atmospheric pressure discharge plasma in the field of element analysis but also summarizes the principal scientific and technical problems to be solved urgently.

To realize three-dimensional (3-D) simulation of weft-knitted fabrics, this paper proposes a 3-D loop modeling method which includes yarn texture and rapid deformation of fabric. The deformation of the fabric is achieved using a simplified particle system. In this study, the shape of the loop is controlled by using 10 control points, and the coordinates of the loop type control points are calculated in combination with the actual loop shape and a quadratic Bezier curve equation. To realize the deformation of the loop, the relationship between the control points and the particle system is established. The 3-D surface model of the yarn is constructed based on a local frame of the loop path. In addition, the yarn simulation is achieved by texture mapping. The simulation of fancy weft-knitted fabric is realized by the joint programming of Visual Studio and OpenGL. The results show that the simplified particle model can accurately achieve the deformation of the fabric with high efficiency. The geometric model properly represents the loop shape and exhibits the yarn texture.

Rapidly progressive glomerulonephritis (RPGN), characterized by rapid kidney dysfunction caused by aggressive glomerulonephritis, is usually associated with crescentic glomerulonephritis (CrGN). In the present study, the data from patients with CrGN were retrospectively analyzed at a tertiary medical center in China with the aim of investigating the clinicopathological features and the association of the type of CrGN with the prognosis. The renal biopsies of 49 patients diagnosed with CrGN were obtained between December 2011 and July 2016. Of the 49 patients, 11 patients (22.45%) had type I CrGN, 19 (38.78%) had type II CrGN and 19 (38.78%) had type III CrGN. The majority of CrGN patients exhibited multiple-system involvement and 28 patients (57.14%) had kidney enlargement. Proportions of patients with acute kidney injury (AKI), acute kidney diseases without AKI, and chronic kidney disease were 28.57, 46.94 and 24.49%, respectively. Among the 3 types of CrGN, patients with type I CrGN tended to have a higher proportion of AKI with more cellular crescent formation, and higher serum creatinine and retinol binding protein. Circulating anti-GBM antibodies were present in all type I CrGN patients and anti-neutrophilic cytoplasmic autoantibodies were detected in 84.21% of patients with type III CrGN. Type III CrGN patients had a superior kidney survival, whereas type I CrGN patients had the worst kidney prognosis (P

Glaciers are susceptible indicators of climate change and crucial parts of the world’s water cycle. In the context of global warming, we took the Urumqi Glacier No.1 (UG1) as an example, which is situated at the source of the Urumqi River on the northern slope of the Tianshan Mountains, Xinjiang, combined with the climate data of Daxigou Meteorological Station from 1980 to 2020, and the change of glacier mass balance and its response to extreme climate are discussed. The results suggest that the glacier mass balance of UG1 showed a downward trend over the studied 41-year period, and the mass loss increased. The cumulative glacier mass balance value was −19,776 mm w.e., and the average annual value was −482 mm w.e.a−1. The Mann-Kendall trend test showed that the change point occurred around 1994, and the mass balance of UG1 became more negative after 1994. In the same period, the changing mass balance trend of UG1 was not the same in different seasons. The inter-annual variation of summer mass balance was drastic, showing a marked downward trend; the inter-annual change of winter mass balance was small, showing a slight uptrend. The changing of extreme climate indices where UG1 is located showed that only TX90p and TX10p changed observably from 1980 to 2020, and the extreme precipitation indices changed evidently and had been on the rise. The changing trend of extreme climate indices indicated that the temperature was rising, the warming was significant, and the precipitation was increasing. During 1980–2020, the glacier mass balance was substantially correlated with the extreme temperature indices (TX90p, TXx) but not with the extreme precipitation indices. Analyzing on a seasonal scale, the summer mass balance was memorably correlated with the extreme temperature indices (TX90p, TX10p, TXx), and the correlation coefficient between winter mass balance and the extreme precipitation index R95p and winter precipitation was in the range 0.36~0.40 (p < 0.05). According to the correlation between glacier mass balance and extreme climate indices, the summer mass balance was mainly affected by temperature, and the winter mass balance was affected primarily by precipitation.

To realize 3D garment simulation online and show the wearing effect of different body types, a method for rapid parametric human modeling is proposed in this article. The parameterization consists of two phases. In the first phase, the characteristic parameters of the sample model are extracted according to the different types of feature information. In the second phase, the deformation is realized by combining the axial deformation method and the radial weight. Thus, according to contrasts between the input measurement and the sample sizes, parametric human modeling is realized by deformation of the sample model. In the deformation stage, the axis curve is simplified to the straight-line segment in the axis deformation method, reducing the calculation. Comparative analysis and the results of experiments demonstrate that the better performance can be achieved at a higher speed, and this method realizes real-time parametric human modeling.

Purpose The whole garment technology offers a solution for the production efficiency by directly knitting a seamless tubular garment. Due to its complexity, high requirements and few references, the technology has not been widely applied in mass production. Therefore, the purpose of this paper is to show garment technology’s detailed design method, the technique calculation process and its merits compared than common technology. Design/methodology/approach This paper first analyzes the knitting principle of the four-bed computerized flat knitting machine from its configuration. After that, the design method is putted forward as well as the technique calculation process. To reveal the advantages of the whole garment technology, this paper builds a comprehensive evaluation system by comparing the knitting time, labor cost and the yarn consumption. Findings With the evaluation system, the whole garment technology is proved to be more productive, cost-saving and less materials-consuming. Moreover, this advantage stands more out when the machine gage is higher. Research limitations/implications Due to limited research time and references, this paper only presents the whole garment technology for knitting common and traditional styles. More complicated and fashioned garments can be studied in the future research. Practical implications The design method and technology presented in this paper can be used as a reference for both the designers in the manufacture industry and the scholars for academic research works. Originality/value This paper has presented the whole garment technology and a specific method for technique calculation with consideration of garment structures. It also builds a evaluation system to show the advantages in terms of knitting efficiency, labor cost and yarn consumption.

Nonalcoholic fatty liver disease (NAFLD) commonly occurs in patients with type 2 diabetes mellitus (T2DM). Osteopontin (OPN) is a multifunctional protein with pleiotropic physiological functions. This study aimed to investigate the interrelation between circulating OPN and NAFLD in T2DM patients. Overall, 249 subjects were classified into 4 groups: 53 patients with NAFLD and T2DM; 57 with newly diagnosed T2DM; 59 with NAFLD; and 80 healthy age- and sex-matched controls. Serum OPN was measured by ELISA. The OPN distribution in the pooled data was divided into quartiles; significant trends across increasing quartiles were estimated by the Cochran-Armitage trend test. Compared with the controls, circulating OPN concentrations were significantly elevated in NAFLD patients and T2DM patients with or without NAFLD. Serum OPN levels were higher in the overweight/obese group than that in the lean group. Circulating OPN levels were positively correlated with CRP, age, BMI, SBP, DBP, HbA1c, UA, TGs, WBCs, neutrophils, FBG, and HOMA-IR and negatively correlated with ADP, albumin and HDL. Age, albumin, HbA1c, HDL and hsCRP were independently related to circulating OPN. The relative risks for NAFLD, T2DM and T2DM with NAFLD increased significantly along with increasing OPN quartiles based on the Cochran-Armitage trend test. OPN is an optimal predictor in the diagnosis of T2DM with NAFLD and T2DM and may contribute to the aggravation of the metabolic state.