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The support point layout of the machine tool has an important influence on the working performance of the machine tool, when the material, manufacturing process and internal structure of machine bed are determined. In order to ensure that the precision machine tool has good leveling performance, stability and anti-interference, this paper presents an optimized design method of three-point support for T-shape bed of precision horizontal machining center. This article first establishes the statics model of the T-shape bed and analyzes grillage beam model used to characterize the main static deformation trend of the bed based on the singular function method. After verifying the rationality of the model through simulation, the optimized three-point support position can be obtained. Then this paper measured the deformation of the upper surface of a simple bed due to gravity. The deviation between the experimental results and the simulation results is less than 20%, which verifies the reliability of the simulation and theoretical results. Based on the ISIGHT multi-disciplinary optimization platform, this paper completes the multi-objective optimization of the support point layout of the bed, and the optimization results prove the accuracy of the theoretical model. This paper takes the bed of M800H precision horizontal machining center as an example to illustrate the application process of the proposed method. Finally, this paper compares the optimization effect of the static characteristics of the bed and the whole machine. The maximum deformation of the bed has reduced by 27.1%. In the whole machine status, the deformation of the spindle end has reduced by 50.8%, and the maximum deformation of the workpiece end have reduced by 50.0%.

By applying the locally optimal rotation method to deal with the lowest eigenvalue of a Hessian matrix, we have efficiently incorporated the hyperdynamics method into the ab initio scheme. In the present method, we only need to calculate the first derivative of the potential and several more force calls in each molecular dynamics (MD) step, which makes hyperdynamics simulation applicable in ab initio MD simulations. With this implementation, we are able to simulate defect diffusion in silicon with boost factors up to 105. We utilized both direct MD and the hyperdynamics method to investigate diffusion of lithium atoms and silicon vacancies in silicon. We identified the complex diffusion process. The obtained diffusion coefficients of Li atoms and Si vacancies are in good agreement with the direct MD results.

Being a critical factor affecting the motion accuracy of precision machine tools, structural thermal elongation of precision ball screw unit is generally caused by the comprehensive influence from heat generations of screw-nut pair / bearings and time-varying ambient temperature. To resist 2 thermal disturbances above to guarantee precisely the original length of screw shaft, an active coolant control strategy is proposed in this paper. This strategy is based on an empirical model: For the slender and long tubular structure of screw shaft, the screw shaft temperature is approximately equal to its recirculating coolant temperature. The reason is that the intensive forced coolant convection is capable of eliminating screw shaft temperature rises caused by friction heat generations and ambient air convections. Based on this premise, screw coolant temperature can be consistently controlled by an active strategy, further to correct the thermal elongation of screw shaft. It can be experimentally verified that the thermal variations of machine positioning accuracy caused by the active coolant control strategy are not more than 10µm, which are lower than traditional strategy. Besides, based on detected structural temperatures of precision ball screw unit, the empirical model above is further proved to be reliable by FE simulation method.

Introduction Comparisons between brand and biosimilar basal insulin in hospitalized patients are lacking. We aimed to compare the efficacy and safety of brand insulin glargine vs. biosimilar insulin glargine in non-critical hospitalized patients with type 2 diabetes mellitus (T2DM). Methods This retrospective study was conducted using the electronic medical records of 194,006 patients at the Qingdao Endocrine and Diabetes Hospital between January 2006 and December 2017. A total of 476 patients diagnosed with T2DM, hospitalized, and treated with subcutaneous insulin glargine were included. After propensity score matching (1:3), patients who received biosimilar insulin glargine (Basalin) (n = 34) were compared to a matched group of patients who received brand insulin glargine (Lantus) (n = 101). Outcome measures were changes in fasting blood glucose (FBG), the incidence of hypoglycemia, and insulin dose. Results Compared to patients who received Basalin, patients who received Lantus achieved more reduction in FBG during insulin treatment (− 1.24 mmol/L vs. − 2.20 mmol/L; p = 0.04) and had a lower mean FBG at the end of treatment (8.20 mmol/L vs. 7.26 mmol/L; p = 0.12). Patients in Basalin and Lantus groups had a comparable mean daily dose of basal insulin at initiation (0.19 vs. 0.18 IU/kg; p = 0.30) and end of treatment (0.21 vs. 0.21 IU/kg; p = 0.99), and a similar duration of basal insulin treatment (16.4 vs. 15.3 days; p = 0.74). Hypoglycemia was infrequent in both Basalin and Lantus treatment (one vs. four patients, respectively; p = 1.00) and no severe hypoglycemic events were reported. Conclusion In a non-critical hospital setting, subcutaneous treatment with Lantus brought significant FBG improvement without increased hypoglycemic risk.

This paper studies the spectral estimation problem of estimating the locations of a fixed number of point sources given multiple snapshots of Fourier measurements collected by a uniform array of sensors. We prove novel stability bounds for MUSIC and ESPRIT as a function of the noise standard deviation, number of snapshots, source amplitudes, and support. Our most general result is a perturbation bound of the signal space in terms of the minimum singular value of Fourier matrices. When the point sources are located in several separated clumps, we provide an explicit upper bound of the noise-space correlation perturbation error in MUSIC and the support error in ESPRIT in terms of a Super-Resolution Factor (SRF). The upper bound for ESPRIT is then compared with a new Cram\'er-Rao lower bound for the clumps model. As a result, we show that ESPRIT is comparable to that of the optimal unbiased estimator(s) in terms of the dependence on noise, number of snapshots and SRF. As a byproduct of our analysis, we discover several fundamental differences between the single-snapshot and multi-snapshot problems. Our theory is validated by numerical experiments., Comment: 16 pages

Previous studies on Data Augmentation (DA) mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data. To address this dilemma, we propose a Diversity-Enhanced and Constraints-Relaxed Augmentation (DECRA) that has two essential components on top of a transformer-based backbone model, including a \(\mathbf {k}\)-\(\varvec{\beta }\) augmentation and a masked language model loss. Extensive experiments demonstrate that our DECRA outperforms state-of-the-art approaches by 3.8% in the overall score.

We examine the possibility of using a reinforcement learning (RL) algorithm to solve large-scale eigenvalue problems in which the desired the eigenvector can be approximated by a sparse vector with at most $k$ nonzero elements, where $k$ is relatively small compare to the dimension of the matrix to be partially diagonalized. This type of problem arises in applications in which the desired eigenvector exhibits localization properties and in large-scale eigenvalue computations in which the amount of computational resource is limited. When the positions of these nonzero elements can be determined, we can obtain the $k$-sparse approximation to the original problem by computing eigenvalues of a $k\times k$ submatrix extracted from $k$ rows and columns of the original matrix. We review a previously developed greedy algorithm for incrementally probing the positions of the nonzero elements in a $k$-sparse approximate eigenvector and show that the greedy algorithm can be improved by using an RL method to refine the selection of $k$ rows and columns of the original matrix. We describe how to represent states, actions, rewards and policies in an RL algorithm designed to solve the $k$-sparse eigenvalue problem and demonstrate the effectiveness of the RL algorithm on two examples originating from quantum many-body physics., 29 pages, 10 figures, 3 table

Stock Trend Prediction(STP) has drawn wide attention from various fields, especially Artificial Intelligence. Most previous studies are single-scale oriented which results in information loss from a multi-scale perspective. In fact, multi-scale behavior is vital for making intelligent investment decisions. A mature investor will thoroughly investigate the state of a stock market at various time scales. To automatically learn the multi-scale information in stock data, we propose a Multi-scale Two-way Deep Neural Network. It learns multi-scale patterns from two types of scale-information, wavelet-based and downsampling-based, by eXtreme Gradient Boosting and Recurrent Convolutional Neural Network, respectively. After combining the learned patterns from the two-way, our model achieves state-of-the-art performance on FI-2010 and CSI-2016, where the latter is our published long-range stock dataset to help future studies for STP task. Extensive experimental results on the two datasets indicate that multi-scale information can significantly improve the STP performance and our model is superior in capturing such information.

We consider the problem of resolving $ r$ point sources from $n$ samples at the low end of the spectrum when point spread functions (PSFs) are not known. Assuming that the spectrum samples of the PSFs lie in low dimensional subspace (let $s$ denote the dimension), this problem can be reformulated as a matrix recovery problem, followed by location estimation. By exploiting the low rank structure of the vectorized Hankel matrix associated with the target matrix, a convex approach called Vectorized Hankel Lift is proposed for the matrix recovery. It is shown that $n\gtrsim rs\log^4 n$ samples are sufficient for Vectorized Hankel Lift to achieve the exact recovery. For the location retrieval from the matrix, applying the single snapshot MUSIC method within the vectorized Hankel lift framework corresponds to the spatial smoothing technique proposed to improve the performance of the MMV MUSIC for the direction-of-arrival (DOA) estimation.

A novel orthogonalization-free method together with two specific algorithms are proposed to solve extreme eigenvalue problems. On top of gradient-based algorithms, the proposed algorithms modify the multi-column gradient such that earlier columns are decoupled from later ones. Global convergence to eigenvectors instead of eigenspace is guaranteed almost surely. Locally, algorithms converge linearly with convergence rate depending on eigengaps. Momentum acceleration, exact linesearch, and column locking are incorporated to further accelerate both algorithms and reduce their computational costs. We demonstrate the efficiency of both algorithms on several random matrices with different spectrum distribution and matrices from computational chemistry.

Introduction We explored the impact of a temporary tobacco-free public policy for the 2008 Summer Olympics on the smoking prevalence and secondhand smoke exposure among the population of a co-hosting city, Qingdao, China. Methods The Qingdao Diabetes Survey was analyzed for 2006 (n = 4599) and 2009 (n = 4680), which are survey years before and after the tobacco-free Olympics public policy period (July 2007 to January 2009). We analyzed the differences in self-reported smoking prevalence and exposure to secondhand smoke at home and/or workplace, and compared odds of smoking by survey year and of exposure to secondhand smoke among nonsmokers. Results From 2006 to 2009, the male smoking prevalence declined from 51.4% (95% confidence interval [CI] = 49.0% to 53.9%) to 42.6% (95% CI = 40.2% to 45.1%), and the proportion of lighter smokers decreased more. Among nonsmokers, the secondhand smoke exposure rate declined from 62.2% (95% CI = 60.5% to 63.9%) to 56.8% (95% CI = 55.1% to 58.6%). Regression analyses show 34% lower odds of men smoking after Olympics (OR = 0.66, 95% CI = 0.57% to 0.77%). Rural residents and individuals who are not retired were more likely to smoke. Female nonsmokers report 17% less exposure to secondhand smoke after Olympics (OR = 0.83, 95% CI = 0.70% to 0.98%). Urban nonsmokers were more likely to be exposed than their rural counterparts. Conclusions Smoking prevalence among men and secondhand smoke exposure among women significantly decreased in Qingdao, China, after the tobacco-free Olympics public policy period. As only the proportion of lighter smokers decreased, this may help explain why urban nonsmokers reported increased exposure. Unintended increased secondhand smoke exposure and cessation support need to be addressed in large-scale policy campaigns. Implications Hosting the Olympic Games can help to initiate large-scale tobacco-free public policies for hosting cities. Although previous studies have demonstrated reduction in nonsmoker exposure to secondhand smoke, the impact on the hosting city’s smoking prevalence or exposure rates is unclear. After the Olympic Games in Qingdao, China, smoking prevalence among men significantly decreased, mostly due to light smokers. Secondhand smoke exposure at home and/or workplace significantly decreased among female nonsmokers. Urban nonsmokers had an unintended consequence of increased secondhand smoke exposure after the tobacco-free Olympic policy period. Concurrent promotion of cessation support for heavier smokers may be needed.

Geometric accuracy is crucially important for machine tools. Identification of geometric errors, especially position-dependent geometric errors, is still a challenging issue. This paper presents a systematic and fast approach to identify the geometric error components of a precision machine tool using double ball bar (DBB). The approach can be implemented in three steps: (1) polynomial based error modeling that relates the DBB radius error directly to the geometric error parameters of machine tool; (2) spatial measurement trajectory planning with a single installation of DBB in order to avoid producing extra setup errors; (3) error identification with regularization method that can solve the ill-posed identification problem effectively. Simulations and experiments show the accuracy and effectiveness of the proposed identification approach. The results of the DBB test show that, utilizing the proposed identification method, the roundness errors of the three circular paths in xy-, yz- and xz-plane are reduced from 27.3 μm, 20.7 μm and 24.1 μm to 9.2 μm, 12.3 μm and 7.8 μm, respectively, with error compensation.

For the precision machining activity, the accuracy of motorized spindle unit can generally be influenced by ambient heat convection and spindle heat generations. This paper develops an active coolant strategy for spindle thermal balance control, to dissipate accurately disturbing heat transfers above. Analytical relationship among spindle internal heat generation, external heat convection and coolant heat dissipation is established. This modeling illustrates that spindle thermal errors can be actively corrected by the real time monitoring – decision making – eliminating method onto spindle structural temperature. Then this active coolant strategy is realized by a developing application of differentiated multi-loops bath recirculation system. Consequently, based on a workshop with about 3.5 °C ambient temperature time variance, advantages of the active coolant strategy are experimentally verified: Compared with previous strategy, the proposed strategy is more advantageous in aspects of spindle structural heat exchange and thermal error corrections.

Angular contact ball bearings have been widely utilized in machine tool spindles and bearing preload has a great influence on the performance of the spindle. The variable preload control technology, including variable pressure preload and variable position preload, is the key technology for intelligent spindle. In order to implement variable pressure/position preload control, the control method and control performance of the variable pressure/position preload spindle-bearing system by using piezoelectric actuators under close-loop control are systematically studied in this paper. A test rig of variable pressure/position spindle-bearing system is developed, and the piezoelectric actuators are adopted to realized preload or axial clearance close-loop control automatically. Both variable pressure preload and variable position preload can be realized on the test rig. The mechanical model of the variable pressure/position preload spindle-bearing system by using piezoelectric actuators is established. Then stiffness model considering the external axial load in static state, and axial displacement as well as operational preload model in rotational state of the spindle-bearing system with piezoelectric actuators in variable pressure preload and variable position preload are proposed and simulated. The design method of the preload mechanism by using piezoelectric actuators is presented. PI controller is employed to regulate the preload or axial clearance of the spindle-bearing system in real-time. A series of experiments are implemented to verify the validity of the variable preload control method and the superiority of the variable pressure/position preload control performance by using piezoelectric actuators. The results show that the variable pressure/position preload spindle-bearing system by using piezoelectric actuators shows excellent performance in controlling preload or axial clearance. The static and dynamic characteristics as well as the operational behaviors of the spindle-bearing system under variable position preload and variable pressure preload are verified by experiments. It is illustrated that the stiffness and the first order natural frequency will be changed with the change of preload methods and preload values. The operational behaviors vary greatly with the preload method, initial preload (negative axial clearance) and rotational speed. The variable preload control method plays a great important role on the performance of spindle-bearing system. Furthermore, this paper provides a foundation for the future research of preloading intelligent control technology as well as investigating the thermal-mechanical-dynamic characteristic of high speed spindle-bearing system.

The surface catalyzing action of hematite ( α -Fe2O3) in reduction of hexavalent chromium (Cr(VI)) by citric acid was studied. The results revealed that Cr(VI) could be reduced to Cr(III) by citrate in the presence of 1% (m/v) hematite in the darkness at pH range of 2.0–6.3. The reaction completed within a week to totally reduce 10 mg L − 1 of Cr(VI) by 20 mM citrate in the presence of 1% hematite at pH 4.2, well fitted with zero-order kinetic model ( R 2 > 0 . 99 ). Though ferric ions (Fe(III)) dissolved from hematite surface could also stimulate the Cr(VI) reduction by citrate, hematite surface played a much more important role in this process. The Fe atoms of hematite surface could transport electrons from citrate to Cr(VI) through Fe(III)-Fe(II) cycling, which was proposed as the underlying mechanism of reduction of Cr(VI) by citrate in the presence of iron oxides under certain environmental conditions. Our results suggest that Fe redox cycling may be driven Cr(VI) reduction in the soil/water with the coexist of low molecular organic matters, which could be a sustainable remediation strategy for chromate contamination.

Biclustering (co-clustering, two-mode clustering), as one of the classical unsupervised learning methods, has been applied in many different fields in recent years. Different types of biclustering methods have been developed such as probabilistic methods, two-way clustering methods, variance minimization methods, and so on. However, few regression-based methods have been proposed to the best of our knowledge. Such methods have been applied in traditional clustering, which can improve both the computational efficiency and the clustering accuracy. In this paper, we present a penalized regression-based method for localizing the biclusters (PRbiclust). By imposing Truncated LASSO Penalty (TLP) and group TLP terms to penalize the column vectors and the row vectors in the regression model, the structure of biclusters in the data matrix is recovered. The model is formulated as an optimization problem with nonconvex penalties, and a computationally efficient algorithm is proposed to solve it. Convergence of the algorithm is proved. To extract the biclusters from the recovered data matrix, we propose a graph-based localization method. An evaluation criterion is also proposed to measure the efficiency of bicluster localization when noise entries exist. We apply the proposed method to both simulated datasets with different setups and a real dataset. Experiments show that this method can well capture the bicluster structure, and performs better than the existing works.

Background: Data describing epidemiology, clinical outcomes and treatment patterns, of hospitalised patients with pneumonia in China are limited. We aimed to describe such information among adult pneumonia patients in southern and northern China. Methods: We retrospectively reviewed electronic medical records of pneumonia patients aged ≥18 years, hospitalized between 2008 and 2013 at Guangdong Provincial Hospital of Chinese Medicine (n=3,636), southern China, and between 2010 and 2014 at Peking University People’s Hospital, Beijing (n=1,689), northern China, in order to collect data on patient demographics, microbiology, clinical outcomes and treatment and resistance patterns. Results: The mean (SD) age of patients was 60.0 (21.4) and 64.4 (18.4) years in Guangdong and Beijing, respectively. Mean length of hospital stay was 12.1 and 20.8 days, and overall mortality was 2.9% and 8.0%, respectively. Gram-negative bacilli were most frequently isolated, predominantly Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa. Infection with these bacteria was associated with unfavourable clinical outcomes, and the antibiotic resistance among these bacteria increased between 2008–2010 and 2011–2013 in both regions of China. The treatment and choice of antibiotics slightly varied between the two regions based on the susceptible pathogens identified among their populations. Conclusions: Of the pathogens identified, Staphylococcus aureus infection (particularly the methicillin-resistant S. aureus ) was associated with poor clinical outcomes; however antibiotic resistance among S. aureus generally decreased during the study data collection periods. Also, disease severity was greater in Beijing as compared with Guangdong, and this may be associated with higher microbiological diagnosis rate and higher frequency of initial antibiotic modification among Beijing populations.

CuMgFe layered double hydroxide (CuMgFe-LDH) was successfully synthesized and characterized as an efficient catalyst of persulfate (PS) for the degradation of ethylbenzene. Under the conditions of 0.2gL-1 CuMgFe-LDH and 4.0mmolL-1 persulfate at pH 7.6, the degradation efficiency of 0.08mmolL-1 ethylbenzene was 93.7% with TOC removal efficiency of 65.2% in 24h, and the concentration of Cu leached into the solution was as low as 0.095mgL-1 after the reaction. The reuse of CuMgFe-LDH showed that the catalyst was highly stable after 5 recycles. Electron Spin Resonance (ESR) test and free radical quenching experiment indicated that SO4- and OH radicals were the dominant species accounted for the degradation of ethylbenzene in the CuMgFe-LDH/persulfate system. Catalytic mechanism of the formation of a complex of Cu(II)O3SOOSO32- and the subsequent redox cycle of Cu(II)/Cu(III) accounted for the generation of radicals was proposed.

To overcome the imbalance between spindle heat generation and dissipation caused by existed spindle cooling strategies, this paper develops a power matching based cooling strategy for motorized spindle unit. Firstly, heat generation, conduction and dissipation are considered for the modeling of spindle structural heat exchange. This modeling methodology conveys that an operating motorized spindle unit will have satisfactory thermal behaviors only if the supply dissipation powers from recirculation coolants are dynamically and respectively equal to their corresponding heat generation powers (mainly from spindle bearings and motor). Based on this principle, the power matching between spindle heat generations and dissipations is realized by the real-time power estimations of spindle heat sources and the modified constant supply cooling powers strategy. It can be ultimately verified by experiments that the power matching based dissipation strategy is more advantageous than existed spindle cooling strategies in dissipation of spindle heat generations and decrease of thermal errors.

Nonalcoholic fatty liver disease (NAFLD) is independently associated with cardiovascular disease and chronic kidney disease. Among patients with type 2 diabetes (T2DM), the relationship between NAFLD and diabetic macrovascular and microvascular complications is unclear. The study population consisted of 2504 patients (M/F: 1520/984, mean age 60.8 ± 10.4 years) with T2DM who have been hospitalized between 2007 and 2011. All subjects had data on anthropometric parameters, total cholesterol (TC), low-density lipoprotein cholesterol, HbA1C, creatinine (Scr), tumor necrosis factor- α (TNF-α), and 24h urine albumin exerting rate (24hUAER). Doppler ultrasound examination was used to diagnose fatty liver and to measure carotid artery intima-media thickness (IMT). Carotid artery intimal thickening was diagnosed as IMT≧1mm. Diabetic nephropathy (DN) was diagnosed if 24hUAER≧30mg/24h. NAFLD accounted for 57.4% of all patients. After adjusting for age, gender, disease duration, systolic blood pressure (SBP), waist and other factors, patients with NAFLD had increased carotid artery IMT (1.11 ± 0.25 vs. 0.87 ±0.18 mm, P Disclosure L. Zhang: None. N. Wang: None. J. Wang: None. X. Yin: None. Y. Yang: None. W. Gao: None. Y. Dong: None.

The current study aims to determine the secular trend of prevalence of type 2 diabetes and prediabetes and risk factors for diabetes from 2002 to 2009. We conducted 3 population-based surveys for diabetes in individuals aged 35-74 years in Qingdao in 2002, 2006 and 2009, respectively, with random-sampling approach. The sample size was 1792, 4549 and 4310 in 2002, 2006 and 2009, respectively. We performed a questionnaire-based survey to collect general information. All participants underwent standardized 2-h 75-g oral glucose tolerance tests (OGTTs). The 1999 WHO diagnostic criteria for diabetes and prediabetes was applied. Age-standardized prevalence of diabetes was calculated. Multiple non-conditional logistic regression were applied to analyze the risk factors for diabetes, taking diabetes as the dependent variable. In 2002, the age-standardized prevalence of diabetes was 12.32%, the corresponding prevalence was 16.57% and 18.01%, respectively, in 2006 and 2009. The prevalence of diabetes increased from 2002 to 2009 (p Disclosure L. Zhang: None. W. Gao: None. N. Wang: None. J. Wang: None. X. Yin: None. Y. Zhu: None. Y. Dong: None.

The study aimed to investigate the effect of 7-point or 5-point glucose monitoring on medical costs, glycemic control and the incidence of hypoglycemia in hospitalized patients with type 2 diabetes (T2DM). A total of 4002 patients with T2DM (1490 male and 2512 female cases) with complete medical records were included between 2012 and 2017. The average age was 61.5 years and the mean disease duration 8.68 years. According to the frequency of daily monitoring of blood glucose during hospitalization, patients were divided into 2 subgroups of 5-point group and 7-point group. Patients in 5-point group received fasting blood glucose (FBG), 2h blood glucose (2hBG) after breakfast, 2hBG after lunch, 2hBG after dinner and bedtime blood glucose tests. Patients in 7-point group received additional tests of pre-lunch glucose and pre-dinner blood glucose. Blood glucose monitoring was performed using Johnson & Johnson SureStep blood glucose meter. Comparison of two groups includes duration of in-hospital stay, medical costs, glycemic control and the incidence of hypoglycemia. Patients in 7-point glucose monitoring group had significantly shorter hospital stay (14.4 vs. 16.6 days, P0.05). At discharge, both fasting and 2-h glucose decreased significantly compared with baseline levels in either 5-point or 7-point group. In 7-point group, FPG decreased by 2.41mmol/L and 2hPG by 3.9mmol/L. In the 5-point group, the corresponding figures were 2.07mmol/L and 3.6mmol/L, respectively. The incidence of hypoglycemia were 24.2% in 7-point group and 33.1% in 5-point group (P Disclosure L. Zhang: None. Y. Gu: None. Y. Yang: None. N. Wang: None. W. Gao: None. J. Wang: None. X. Yin: None. Y. Dong: None.

Temperature variations in the machine tool structural components may lead to relative pose variations between the tool tip and the workpiece. Different thermal layouts may lead to various temperature distributions and generate various thermal deformations. Thermal symmetric design is often used to complete thermal balancing of machine tools. Studies on theoretical methods to guide the layout design of the heat sources (HS) and cooling sources (CS) in machine tools are insufficient. To address this problem, a novel analytical approach for characterising the equivalent cuboid thermal response of machine tool structural components is presented in this paper. The proposed analytical modelling method can realise analytical temperature field modelling with Green's function, calculating the equivalent thermal moment with Reissner's theory, and matching the thermal power-deformation mapping coefficient (TPDMC) using the finite element method (FEM). The explicit and correlative formulation between the thermal power of the HSs and CSs and the guideway thermal deviations is deduced. Furthermore, the layout principles of the CSs are presented according to the maximum efficiency of the thermal moment and the characterisation matching of the TPDMC curves. Afterwards, power matching of the CS is obtained with the aid of the minimum deformation principles of the key positions. Simulated and experimental results illustrated that the proposed method can be used to rapidly and accurately analyse the temperature and thermal deformation responses of the machine tool, as well as to provide a thermal balancing strategy according to specific thermal conditions. The analytical approach proposed in this paper is a general method suitable for the thermal balancing design of machine tools, and it is of great value for improving the thermally induced accuracy stability of machine tools.

Objective: To study the clinical characteristics related to metabolic disorders and complications in type 2 diabetes mellitus patients hospitalized in the Qingdao Endocrine and Diabetes Hospital from 2006 to 2012 in Qingdao, China. Patient population and methods: Data from 14,289 (51% males) type 2 diabetes mellitus patients hospitalized between 2006 and 2012 were collected and analysed. Information on patients’ demographic, anthropometric, laboratory and disease histories were extracted from electronic medical records. Results: The mean age of the patients was 60.5 years, with median diabetes duration of 9.0 years. Mean haemoglobin A1c was 8.4%, where Conclusion: Inadequate control of hyperglycaemia, poor metabolic profiles and diabetic complications were common challenges for long-term diabetes management in Chinese patients with type 2 diabetes mellitus.

The incidence of all cancers in China is generally higher in urban areas; however, the mortality risk for affected patients is considerably higher in rural areas. We present a subanalysis investigating the differences in patient and disease characteristics, treatment patterns, and outcomes between rural and urban patients who were diagnosed with breast cancer at West China Hospital between 2005-2009. Baseline patient and disease characteristics were recorded, and patients were followed up for a minimum of 3 years, or until death. For this subanalysis, patients were stratified by their residential status (rural or urban). Of the 2252 patients in the cohort, 76.3% were from urban areas and 22.1% were from rural areas. Significant differences were observed in the prevalence of luminal A and human epidermal growth factor receptor 2-positive breast cancers among rural and urban patients. Estrogen receptor (ER)-positive patients were less likely to receive anti-ER therapy if they were from rural areas compared with urban areas; the use of aromatase inhibitors was also significantly lower for rural patients than urban patients. Univariate, multivariate, and Kaplan-Meier analyses all demonstrated that overall survival and progression-free survival were significantly lower for rural patients than urban patients.

A reduced graphene oxide (rGO) supported magnetite nanoparticle (nFe 3 O 4 ) composite (nFe 3 O 4 /rGO) was synthesized and shown for the first time to be an efficient persulfate activator to generate SO 4 − for trichloroethylene (TCE) degradation. The degradation efficiency of TCE (0.15 mmol L −1 ) was 98.6% within 5 min in the presence of 6.94 g L −1 nFe 3 O 4 /rGO with an optimum mass ratio of 1:4 and persulfate concentration of 3.0 mmol L −1 . By dispersing nFe 3 O 4 on the rGO surface, nanoparticle agglomeration was prevented and the aggregation of the rGO sheets was disrupted. Both the redox effect coupled in nFe 3 O 4 and the electron transfer by functional groups containing oxygen on the surface of rGO enhanced the SO 4 − generation. Given the identified free radical species and the characterization of the nFe 3 O 4 /rGO, a persulfate activation mechanism by nFe 3 O 4 /rGO for the degradation of TCE was interpreted.

This paper presents an efficient algorithmic implementation of the iterative minimization formulation (IMF) for fast local search of transition state on potential energy surface. The IMF is a second order iterative scheme providing a general and rigorous description for the eigenvector-following (min-mode following) methodology. We offer a unified interpretation in numerics via the IMF for existing eigenvector-following methods, such as the gentlest ascent dynamics, the dimer method and many other variants. We then propose our new algorithm based on the IMF. The main feature of our algorithm is that the translation step is replaced by solving an optimization subproblem associated with an auxiliary objective function which is constructed from the min-mode information. We show that using an efficient scheme for the inexact solver and enforcing an adaptive stopping criterion for this subproblem, the overall computational cost will be effectively reduced and a super-linear rate between the accuracy and the computational cost can be achieved. A series of numerical tests demonstrate the significant improvement in the computational efficiency for the new algorithm.

Pipe route design plays a prominent role in ship design. Due to the complex configuration in layout space with numerous pipelines, diverse design constraints, and obstacles, it is a complicated and time-consuming process to obtain the optimal route of ship pipes. In this article, an optimized design method for branch pipe routing is proposed to improve design efficiency and to reduce human errors. By simplifying equipment and ship hull models and dividing workspace into three-dimensional grid cells, the mathematic model of layout space is constructed. Based on the proposed concept of pipe grading method, the optimization model of pipe routing is established. Then an optimization procedure is presented to deal with pipe route planning problem by combining maze algorithm (MA), nondominated sorting genetic algorithm II (NSGA-II), and cooperative coevolutionary nondominated sorting genetic algorithm II (CCNSGA-II). To improve the performance in genetic algorithm procedure, a fixed-length encoding method is presented based on improved maze algorithm and adaptive region strategy. Fuzzy set theory is employed to extract the best compromise pipeline from Pareto optimal solutions. Simulation test of branch pipe and design optimization of a fuel piping system were carried out to illustrate the design optimization procedure in detail and to verify the feasibility and effectiveness of the proposed methodology.

Textual information embedded in the medical image contains rich structured information about the medical condition of a patient. This paper aims at extracting structured textual information from semi-structured medical images. Given the recognized text spans of an image preprocessed by optical character recognition (OCR), due to the spatial discontinuity of texts spans as well as potential errors brought by OCR, the structured information extraction becomes more challenging. In this paper, we propose a domain-specific language, called ODL, which allows users to describe the value and layout of text data contained in the images. Based on the value and spatial constraints described in ODL, the ODL parser associates values found in the image with the data structure in the ODL description, while conforming to the aforementioned constraints. We conduct experiments on a dataset consisting of real medical images, our ODL parser consistently outperforms existing approaches in terms of extraction accuracy, which shows the better tolerance of incorrectly recognized texts, and positional variances between images. This accuracy can be further improved by learning from a few manual corrections.

Geometric errors of machine tools are one of the main contributors for machining inaccuracies. A multi-step error measurement and compensation method is proposed in this paper to investigate the effects of different geometric errors on volumetric errors. The kinematic error chain is built using multi-body system theory (MBS) and homogenous transformation matrices first. Then, the original geometric errors without any compensations are measured and the deviations of tool tip caused by different geometric errors are calculated. Furthermore, various compensation strategies considering diverse geometric errors effects are carried out in the machine tool to validate the predicted volumetric errors. The multi axis calibrator, which can detect six errors of a translational axis in one measurement, is used to measure the variations of 18 errors of translational axes and volumetric diagonal errors of a three axes machine tool. Besides, the squareness errors were measured by a ball-bar. The pragmatic effects of positioning, straightness, angular and squareness errors on volumetric errors are derived from comparisons between various compensation results. Results reveal that linear errors effect the whole volumetric positioning errors while the angular errors mainly effect the volumetric positioning errors of the region far from reference coordinate point.

A high catalytic system using Cu layered double hydrotalcite (Cu(II)-Mg(II)-Fe(III)LDHs) and hydrogen peroxide (H2O2) was developed for the degradation of ethylbenzene. It was identified that the degradation efficiency of ethylbenzene (0.08 mmol L−1) and TOC removal were 96.1% and 39.7% respectively in the presence of 0.1 g L−1 Cu(II)-Mg(II)-Fe(III)LDHs with (Cu2+ + Mg2+)/Fe3+ molar ratio of 5.0 and 0.16 mmol L−1 H2O2 in 6.0 h. Based on ESR and XPS data, hydroxyl radicals (•OH) were the predominant free radical specials generated from the catalytic decomposition of H2O2 for the degradation of ethylbenzene. The redox of Cu(II)/Cu(III) on the layered Cu(II)-Mg(II)-Fe(III)LDHs surface active sites accounted for the formation of •OH radicals and the cycle of Cu(II) in the Cu(II)-Mg(II)-Fe(III)LDHs/H2O2 system were proposed.

Motorized spindle unit is the core component of a precision CNC machine tool. Its thermal errors perform generally serious disturbance onto the accuracy and accuracy stability of precision machining. Traditionally, the effectiveness of the compensation method for spindle thermal errors is restricted by machine freedom degrees. For this problem, this paper presents an active, differentiated, and intelligent control method onto spindle thermal behaviors, to realize comprehensive and accurate suppressions onto spindle thermal errors. Firstly, the mechanism of spindle heat generation/dissipation-structural temperature-thermal deformation error is analyzed. This modeling conveys that the constantly least spindle thermal errors can be realized by differentiated and active controls onto its structural thermal behaviors. Based on this principle, besides, the active control method is developed by a combination of extreme learning machine (ELM) and genetic algorithm (GA). The aim is to realize the general applicability of this active and intelligent control algorithm, for the spindle time-varying thermal behaviors. Consequently, the contrasting experiments clarify that the proposed active and intelligent control method can suppress accurately and synchronously all kinds of spindle thermal errors. It is significantly beneficial for the improvements of the accuracy and accuracy stability of motorized spindle units.

Volumetric accuracy is susceptible to thermal gradient caused by internal heat source (IHS) and external heat source (EHS). A temperature-structure multi-step calculation method is presented to investigate the influences of EHSs on volumetric thermal errors of precision machine tools. The temperature and structure of the machine tool are simulated first, and then, the volumetric thermal errors are calculated using multi-body theory method. Simulations are completed to study the effects of different EHSs on a machine tool, and series of validating experiments are carried out to verify the modeling method. The test results in specific position and working condition revealed that EHSs contribute 53, 21, and 68% of thermal deviations in X, Y, and Z directions individually. It is illustrated that the EHS is an important factor affecting the volumetric accuracy of precision machine tools. The methods provided in this paper are valuable for machine tool designers to evaluate the EHS effects on volumetric thermal errors during designing process; furthermore, some insulating measures are suggested to improve the accuracy and accuracy stability of precision machine tools by reducing the EHS influences.

We introduce efficient approaches to construct high order finite difference discretizations for solving partial differential equations, based on a composite grid hierarchy. We introduce a modification of the traditional point clustering algorithm, obtained by adding restrictive parameters that control the minimal patch length and the size of the buffer zone. As a result, a reduction in the number of interfacial cells is observed. Based on a reasonable geometric grid setting, we discuss a general approach for the construction of stencils in a composite grid environment. The straightforward approach leads to an ill-posed problem. In our approach we regularize this problem, and transform it into solving a symmetric system of linear of equations. Finally, a stencil repository has been designed to further reduce computational overhead. The effectiveness of the discretizations is illustrated by numerical experiments on second order elliptic differential equations.

To develop a visual and reliable weld quality assessment method for resistant spot welding, the electrode displacement signal was measured and analyzed. Some statistical features closely related to the weld quality were extracted. The multi-dimensional extracted features from the signal were sketched as Chernoff face which characterizes the welding quality through the different facial expressions. The weld quality was summarized as four levels, namely poor, good, excellent and expulsion, and each level corresponded to one kind of facial expression. By visual judgment, good or bad welds were identified accurately and rapidly even though the weld was made under abnormal welding conditions. In particular, the visual characteristic makes the diagnostic procedure for welding quality easily understood and interpreted.

We discuss the inexact two-grid methods for solving eigenvalue problems, including both partial differential and integral equations. Instead of solving the linear system exactly in both traditional two-grid and accelerated two-grid method, we point out that it is enough to apply an inexact solver to the fine grid problems, which will cut down the computational cost. Different stopping criteria for both methods are developed for keeping the optimality of the resulting solution. Numerical examples are provided to verify our theoretical analyses.

The motion track of belt spindle is important for the radial error of belt spindle. An analytical modeling method for the motion track of belt spindle under the combined effects of bending moment-torque-thermal deformation is proposed in this paper. Three running phases of belt spindle have been analyzed and modeled: the start-up phase with leaping change due to the change in force and bending moment, the accelerating phase with axis deflection, and the constant speed phase with axis regression because of the combined effects of bending moment-torque-thermal deformation. The simulation and test were completed on the belt spindle of SKVM850 machine tool, which illustrates the variation law of the radial error of belt spindle during the whole running phases.

Inverse design is a promising approach in the realm of material science for finding structures with desired property. We developed a new package with novel algorithm for inverse design named as IM2ODE (inverse design of Materials by Multi-Objective Differential Evolution). The target properties of concern include the optical and electronic-structure properties of semiconductors, hardness of crystals, etc. IM2ODE can easily predict the atomic configurations with desired properties for three dimensional structure, interface and cluster, even complex defect in solid. Tests have been run on multiple systems and it has been proved that IM2ODE is highly efficient and reliable, which can be applied widely.

Traditional bath recirculation cooler for precision machine tools always has the uniform and open-loop cooling strategy onto different heat generating parts. This causes redundant generated heat being transferred into the machine structure, and results in unsatisfactory thermal errors of precision machine tools. For the solution of this problem, this paper presents the differentiated multi-loops bath recirculation system. The developed system can accomplish differentiated and close-loop cooling strategies onto machine heat generating parts during its operation. Specially, in order to illustrate the advantages of this system, constant supply cooling powers strategy is presented with its applications onto a certain type of built-in motorized spindle. Consequently, advantages of the proposed strategy based on the differentiated multi-loops bath recirculation system are verified experimentally in the environment within consistent temperature (TR = 20 ± 0.3°C). Compared with room temperature tracing strategy based on the traditional bath recirculation cooler, the constant supply cooling powers strategy is verified to be advantageous in spindle temperature stabilization and thermal errors decrease.\ud

This paper proposes and analyzes an iterative minimization formulation for searching index-1 saddle points of an energy function. We give a general and rigorous description of eigenvector-following...

Branch pipe routing problem can be formulated as finding the Rectilinear Steiner Minimal Trees with Obstacles (RSMTO) (Liu & Wang 2012). For the RSMTO problem, one of the important tasks is to construct a reasonable layout space model.

Fruit, vegetable, seafood, and dairy intake may reduce the risk of type 2 diabetes, but this relationship is unclear. We aimed to examine the associations between fruit, vegetable, seafood, and dairy intake and type 2 diabetes prevalence in a Chinese population.A total of 4,343 individuals aged 35-74 years participated in a population-based cross-sectional study in Qingdao, China. The frequency and quantity of fruit, vegetable, seafood, and dairy intake were determined using a standard food frequency questionnaire. Diabetes was classified according to the WHO/IDF 2006 criteria. Logistic regression analysis was employed to estimate odds ratio (OR) for type 2 diabetes in relation to fruit, vegetable, seafood, and dairy intake in a multivariable model.The multivariate-adjusted ORs (95% confidence interval) for the presence of type 2 diabetes were 0.68 (0.46-0.98), 0.50 (0.37-0.68), and 0.91 (0.66-1.25), respectively, for the highest versus the lowest groups regarding total fruit and vegetable, fruit or vegetable intake in women. The ORs for type 2 diabetes prevalence regarding the quantity of fruit and vegetable, fruit, and yogurt intake were 0.88 (0.78-0.99), 0.71 (0.61-0.82), and 0.56 (0.32-0.98) in women, but not in men. Seafood consumption was inversely associated with diabetes risk in men, but not in women; the corresponding figures were 0.58 (0.35-0.96) and 0.92 (0.63-1.36), respectively.Fruit, vegetable, and yogurt intake in women and seafood intake in men were inversely associated with type 2 diabetes prevalence in this Chinese population. These findings require confirmation in a prospective study.

Composite of nanoscale Zero Valent Iron (nZVI) loaded on Biochar (BC) was prepared and characterized as hydrogen peroxide (H2O2) activator for the degradation of trichloroethylene (TCE). nZVI is homogeneously loaded on lamellarly structured BC surfaces to form nZVI/BC with specific surface area (SBET) of 184.91 m2 g−1, which can efficiently activate H2O2 to achieve TCE degradation efficiency of 98.9% with TOC removal of 78.2% within 30 min under the conditions of 0.10 mmol L−1 TCE, 1.13 g L−1 nZVI/BC and 1.50 mmol L−1 H2O2. Test results from the Electron Spin Resonance (ESR) measurement and coumarin based fluorescent probe technology indicated that ∙OH radicals were the dominant species responsible for the degradation of TCE within the nZVI/BC-H2O2 system. Activation mechanism of the redox action of Fe2+/Fe3+ generated under both aerobic and anaerobic conditions from nZVI and single electron transfer process from BC surface bound C–OH to H2O2 promoted decomposition of H2O2 into ∙OH radicals was proposed.

Aims To estimate the long-term cost-effectiveness of exenatide twice daily vs insulin glargine once daily as add-on therapy to oral antidiabetic agents (OADs) for Chinese patients with type 2 diabetes (T2DM). Methods The Cardiff Diabetes Model was used to simulate disease progression and estimate the long-term effects of exenatide twice daily vs insulin glargine once daily. Patient profiles and treatment effects required for the model were obtained from literature reviews (English and Chinese databases) and from a meta-analysis of 8 randomized controlled trials comparing exenatide twice daily with insulin glargine once daily add-on to OADs for T2DM in China. Medical expenditure data were collected from 639 patients with T2DM (aged ≥18 years) with and without complications incurred between January 1, 2014 and December 31, 2015 from claims databases in Shandong, China. Costs (2014 Chinese Yuan [¥]) and benefits were estimated, from the payers’ perspective, over 40 years at a discount rate of 3%. A series of sensitivity analyses were performed. Results Patients on exenatide twice daily + OAD had a lower predicted incidence of most cardiovascular and hypoglycaemic events and lower total costs compared with those on insulin glargine once daily + OAD. A greater number of quality-adjusted life years (QALYs; 1.94) at a cost saving of ¥117 706 gained was associated with exenatide twice daily vs insulin glargine once daily. (i.e. cost saving of ¥60 764/QALY) per patient. Conclusions In Chinese patients with T2DM inadequately controlled by OADs, exenatide twice daily is a cost-effective add-on therapy alternative to insulin glargine once daily, and may address the problem of an excess of medical needs resulting from weight gain and hypoglycaemia in T2DM treatment.

Dynamic stiffness and damping of the headstock, which is a critical component of precision horizontal machining center, are two main factors that influence machining accuracy and surface finish quality. Constrained Layer Damping (CLD) structure is proved to be effective in raising damping capacity for the thin plate and shell structures. In this paper, one kind of high damping material is utilized on the headstock to improve damping capacity. The dynamic characteristic of the hybrid headstock is investigated analytically and experimentally. The results demonstrate that the resonant response amplitudes of the headstock with damping material can decrease significantly compared to original cast structure. To obtain the optimal configuration of damping material, a topology optimization method based on the Evolutionary Structural Optimization (ESO) is implemented. Modal Strain Energy (MSE) method is employed to analyze the damping and to derive the sensitivity of the modal loss factor. The optimization results indicate that the added weight of damping material decreases by 50%; meanwhile the first two orders of modal loss factor decrease by less than 23.5% compared to the original structure.

This paper presents a general and systematic approach for geometric error modeling of machine tools due to the geometric errors arising from manufacturing and assembly. The approach can be implemented in three steps: (1) development of a linear map between the pose error twist and source errors within machine tool kinematic chains using homogeneous transformation matrix method; (2) formulation of a linear map between the pose error twist and the error intensities of a machine tool; (3) combination of these two models for error separation. The merit of this approach lies in that it enables the source errors affecting the compensatable and uncompensatable pose accuracy of the machine tool to be explicitly separated, thereby providing designers and/or field engineers with an informative guideline for the accuracy improvement by suitable measures, i.e. component tolerancing in design, manufacturing and assembly processes, and error compensation. Two typical multi-axis machine tools are taken as examples to illustrate the generality and effectiveness of this approach.

To examine and compare health-related quality of life (HRQoL) in people with previously known diabetes, new screen-detected asymptomatic diabetes and people without diabetes. HRQoL of 4,613 individuals who participated in a population-based cross-sectional diabetes survey in Qingdao, China, in 2009, was assessed using the 15D instrument. A Tobit regression model to estimate the effects of diabetes on HRQoL separate from effects of other health determinants was constructed. Among the surveyed population, 220 (4.8 %) individuals had previously known diabetes and 531 (11.5 %) individuals had new screen-detected diabetes, defined by fasting plasma glucose ≥7.0 mmol/l and/or 2-h plasma glucose ≥11.1 mmol/l. The age-, gender-, and BMI-adjusted mean 15D score of people without diabetes, with new screen-detected diabetes, and previously known diabetes was 0.975, 0.975, and 0.964, respectively, for urban and 0.971, 0.972, and 0.960, respectively, for rural participants. HRQoL overall and on all the dimensions (p

To improve the efficiency of acquiring monitored features and present a reliable quality assessment method for resistance spot welding, a novel method for converting the electrode displacement signal into binary image is proposed. The probabilistic neural network is adopted to provide a probabilistic viewpoint and a deterministic classification result of weld quality when the image characteristic of displacement signal is selected as monitored features. Test results of the classifier demonstrate that it is feasible and reliable to utilise binary image of the displacement signal to evaluate weld quality. The method reserves weld quality information as much as possible and it avoids complex algorithm for extracting and selecting monitored features. At the same time, when there are small samples, the classifier can identify good or bad weld rapidly and accurately even though the weld is from abnormal welding process, such as expulsion, current shunting and small edge distance condition.