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Brain functional connectivity (FC) networks derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely applied to automated identification of brain disorders, such as Alzheimer's disease (AD) and attention deficit hyperactivity disorder (ADHD). To generate compact representations of FC networks, various thresholding strategies have been developed to analyze brain FC networks. However, existing studies usually employ predefined thresholds or percentages of connections to threshold FC networks, thus ignoring the diversity of temporal correlation (particularly strong associations) among brain regions in same/different subject groups. Also, it is usually challenging to decide the optimal threshold or connection percentage in practice. To this end, in this paper, we propose a distribution-guided network thresholding (DNT) method for functional connectivity analysis in brain disorder identification with rs-fMRI. Specifically, for each functional connectivity of a pair of brain regions, we proposed to compute its specific threshold based on the distribution of connection strength (i.e., temporal correlation) between subject groups (e.g., patients and normal controls). The proposed DNT can adaptively yield FC-specific threshold for each connection in brain networks, thus preserving the diversity of temporal correlation among brain regions. Experiment results on both ADNI and ADHD-200 datasets demonstrate the effectiveness of our proposed DNT method in fMRI-based identification of AD and ADHD.

Introduction In this study, we performed a consecutive macropathologic analysis to assess microscopic extension (ME) in high-grade glioma (HGG) to determine appropriate clinical target volume (CTV) margins for radiotherapy. Materials and methods The study included HGG patients with tumors located in non-functional areas, and supratotal resection was performed. The ME distance from the edge of the tumor to the microscopic tumor cells surrounding brain tissue was measured. Associations between the extent of ME and clinicopathological characteristics were evaluated by multivariate linear regression (MVLR) analysis. An ME predictive model was developed based on the MVLR model. Results Between June 2017 and July 2019, 652 pathologic slides obtained from 30 HGG patients were analyzed. The mean ME distance was 1.70 cm (range, 0.63 to 2.87 cm). The MVLR analysis identified that pathologic grade, subventricular zone (SVZ) contact and O6-methylguanine-DNA methyltransferase (MGMT) methylation, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status were independent variables predicting ME (all P ME = 0.672 + 0.513XGrade + 0.380XSVZ + 0.439XMGMT + 0.320XIDH + 0.333X1p/19q. The R-square value of goodness of fit was 0.780. The receiver operating characteristic curve proved that the area under the curve was 0.964 (P Conclusion ME was heterogeneously distributed across different grades of gliomas according to the tumor location and molecular marker status, which indicated that CTV delineation should be individualized. The model could predict the ME of HGG, which may help clinicians determine the CTV for individual patients. Trial registration The trial was registered with Chinese Clinical Trial Registry (ChiCTR2100046106). Registered 4 May 2021-Retrospectively registered.

The axial spacing measurement between optical elements is of great significance to the positioning and adjustment of precision optical systems. Aiming at the problems of complex dispersive objective lens structure and small dispersion range in the existing dispersion confocal measurement system, a method for measuring the axial spacing of optical elements based on the method of polarization diffraction dispersion confocal was proposed. The axial dimension of a traditional refractive confocal lens with a few hundred millimeters and the complex alignment requirements were simplified to a single-chip lens with a few millimeters, which simplified the system structure. The results of lens spacing and thickness measurement experiments show that the spacing measurement error is 10 μm.

Integrated zoom and image stabilization system based on deformable mirrors (DMs) has advantages of miniaturization, rapid response and low energy consumption. Integrating the two capabilities on one DM-based imaging system poses considerable challenges. First, limited DM stroke will result in limited changeable aberration correction value for zoom and image stabilization. Second, the DM-based off-axis imaging system suffers a simple relative movement between optical axis and objects caused by carrier vibration may result in complicated optical system aberrations. To address these challenges, a reasonable assignment of the changeable aberration correction value for zoom and image stabilization is needed. Image stabilization and aberration correction in DM-based off-axis imaging system, should be considered when translation or rotation occurs. To troubleshoot the assignment issues of the correcting aberrations, we propose a graded optimization method which comprises two steps. To troubleshoot the image stabilization and aberration correction issues, we introduce vectorial ray tracing method and image point freezing principle to transform the aberration correction problem into an optimization problem of image coordinates. With the proposed method, we construct practical integrated freeform surfaces of DMs for a space camera with three mirrors. The sagittal heights of designed DM surface profiles are limited within their available stroke.

As one of the important research areas of cognitive diagnosis assessment, cognitive diagnostic computerized adaptive testing (CD-CAT) has received much attention in recent years. Measurement accuracy is the major theme in CD-CAT, and both the item selection method and the attribute coverage have a crucial effect on measurement accuracy. A new attribute coverage index, the ratio of test length to the number of attributes (RTA), is introduced in the current study. RTA is appropriate when the item pool comprises many items that measure multiple attributes where it can both produce acceptable measurement accuracy and balance the attribute coverage. With simulations, the new index is compared to the original item selection method (ORI) and the attribute balance index (ABI), which have been proposed in previous studies. The results show that (1) the RTA method produces comparable measurement accuracy to the ORI method under most item selection methods; (2) the RTA method produces higher measurement accuracy than the ABI method for most item selection methods, with the exception of the mutual information item selection method; (3) the RTA method prefers items that measure multiple attributes, compared to the ORI and ABI methods, while the ABI prefers items that measure a single attribute; and (4) the RTA method performs better than the ORI method with respect to attribute coverage, while it performs worse than the ABI with long tests.

Although classification accuracy is a critical issue in cognitive diagnostic computerized adaptive testing, attention has increasingly shifted to item exposure control to ensure test security. In this study, we developed the binary restrictive threshold (BRT) method to balance measurement accuracy and item exposure. In addition, a simulation study was conducted to evaluate its performance. The results indicated that the BRT method performed better than the restrictive progressive (RP) and stratified dynamic binary searching (SDBS) approaches but worse than the restrictive threshold (RT) method in terms of classification accuracy. With respect to item exposure control, the BRT method exhibited noticeably stronger performance compared with the RT method, even though its performance was not as high as that of the RP and SDBS methods.

Bayesian networks (BNs) can be employed to cognitive diagnostic assessment (CDA). Most of the existing researches on the BNs for CDA utilized the MCMC algorithm to estimate parameters of BNs. When EM algorithm and gradient descending (GD) learning method were adopted to estimate the parameters of BNs, some challenges may emerge in educational assessment due to the monotonic constraints (greater skill should lead to better item performance) cannot be satisfied in the above two method. This paper proposed to train the BN first based on the ideal response pattern data contained in every CDA and continue to estimate the parameters of BN based on the EM or the GD algorithm regarding the parameters based on the IRP training method as informative priors to satisfy the monotonic constraints. Both the simulation study and realistic data analysis demonstrated the validity and feasibility of the new method. The BN based on the new parameter estimating method exhibits promising statistical classification performance and even outperforms the G-DINA method in some conditions.

The efficacy of crizotinib for anaplastic lymphoma kinase (ALK)-rearranged non-small-cell lung cancer (NSCLC) patients with brain metastasis is controversial. Real-world research data are needed as further evidence. We conducted a multicenter, retrospective study to explore how crizotinib affects the control of brain metastasis and the survival outcomes among Chinese patients. We reviewed the medical records of unselected ALK-rearranged NSCLC patients treated with crizotinib at five hospitals in China from January 1, 2013 to November 30, 2017. Patients developing brain metastasis either before or during crizotinib treatment were included. Survival outcomes were analyzed by the Kaplan–Meier method, and prognostic factors were analyzed by multivariate Cox regression. A total of 174 patients were included in the analysis; 95 of these patients had baseline brain metastasis, while 79 patients developed brain metastasis during crizotinib treatment. Among patients with baseline brain metastasis, the median intracranial time to progression was 19.3 months (95% confidence interval [CI] 12.5–26.2) and the median overall survival (OS) was 53.4 months (95% CI not reached). A total of 135 patients experienced intracranial progression, and 94 of these patients continued crizotinib beyond progressive disease (CBPD). There was no significant difference in the median OS between patients with CBPD and without CBPD (48.3 months vs 53.4 months; p = 0.296). ALK-rearranged advanced NSCLC patients with baseline brain metastasis can still achieve OS benefits from crizotinib treatment. However, patients with intracranial progression may not obtain a long-term survival benefit from continuation of CBPD.

Background Crizotinib is associated with a favorable survival benefit in patients with ALK‐positive non‐small cell lung cancer (NSCLC); however, a subset of patients harboring ALK rearrangement shows a poor response. Methods We collected the clinical features and survival outcomes of 28 primary‐resistant responders (PRR) with progression‐free survival (PFS) of < 3 months on crizotinib and compared these with 78 long‐term responders (LTR) that achieved > 24 months PFS (control). Results Primary resistance was observed in 6.5% of the patients. The median PFS of the PRR and LTR groups was 1.2 months (95% confidence interval [CI] 0.70–1.73) and 47.0 months (95% CI 34.39–59.64), respectively. A better Eastern Cooperative Oncology Group performance status score was significantly associated with longer PFS (odds ratio 0.06, 95% CI 0.01–0.33; P = 0.001). The median overall survival (OS) of the PRR group was 8.4 months (95% CI 3.47–13.42) and crizotinib as first‐line treatment was an independent predictive factor for survival outcome (P = 0.005). Patients administered ALK‐tyrosine kinase inhibitors after crizotinib progression had significantly longer survival than the PRR group treated with best supportive care (P = 0.007), but no significant difference was found between ALK‐tyrosine kinase inhibitor treatment and single chemotherapy (P = 0.944). Conclusion Patients with primary resistance to crizotinib displayed unfavorable survival outcomes and the underlying mechanism cannot be identified in clinical features. Nevertheless, next‐generation ALK inhibitors and chemotherapy after crizotinib progression could confer a therapeutic and survival benefit in this population.

Purpose: To summarize the framework and development procedure of the China National Assessment of Education Quality - Physical Education & Health in 2015 (CNAEQ-PEH 2015), an authoritative and evid...

Abstract. Random response is a very common aberrant response behavior in personality tests and may negatively affect the reliability, validity, or other analytical aspects of psychological assessment. Typically, researchers use a single person-fit index to identify random responses. This study recommends a three-step person-fit analysis procedure. Unlike the typical single person-fit methods, the three-step procedure identifies both global misfit and local misfit individuals using different person-fit indices. This procedure was able to identify more local misfit individuals than single-index method, and a graphical method was used to visualize those particular items in which random response behaviors appear. This method may be useful to researchers in that it will provide them with more information about response behaviors, allowing better evaluation of scale administration and development of more plausible explanations. Real data were used in this study instead of simulation data. In order to create real random responses, an experimental test administration was designed. Four different random response samples were produced using this experimental system.

Objective Crizotinib has demonstrated promising efficacy in patients with anaplastic lymphoma kinase (ALK)-positive non-small-cell lung cancer (NSCLC) in clinical trials. We conducted this retrospective multicenter study to assess the outcomes of crizotinib therapy in, to our knowledge, a large sample cohort of patients with ALK-positive advanced NSCLC. Methods We reviewed the medical records of 484 unselected ALK-positive NSCLC patients treated with crizotinib at 5 cancer centers in China from January 2013 to November 2017. Clinical data were collected from the initiation of crizotinib therapy to Response Evaluation Criteria in Solid Tumors (RECIST)-defined progressive disease (PD). Results A total of 428 eligible ALK-positive NSCLC patients were enrolled, 273 (63.8%) of whom received crizotinib as first-line treatment. The median progression-free survival (PFS) and overall survival (OS) from the initiation of crizotinib treatment were 14.4 [95% confidence interval (95% CI), 12.4−16.4] months and 53.4 (95% CI, 33.7−73.1) months, respectively. In subgroup analyses, patients who received crizotinib as first-line treatment showed a higher disease control rate (DCR) and a longer median OS compared with second-/later-line crizotinib treatment (94.8% and OS not reachedvs. 89.0% and 40.5 months, respectively). For 261 patients with RECIST-defined PD, multivariate Cox analysis revealed that in patients who received first-line crizotinib therapy, continued crizotinib beyond progressive disease (CBPD) and next-generation ALK inhibitors after crizotinib failure were associated with improved survival. Conclusions This study has demonstrated the clinically meaningful benefit of crizotinib treatment in a large cohort of Chinese ALK-positive NSCLC patients. CBPD and next-generation ALK inhibitor treatment may provide improved survival after RECIST-defined progression on crizotinib.

Ceritinib shows efficacy in ALK+ NSCLC patients with BM. However, the disease will inevitably progress over time due to acquired resistance. We now report a case with BM from advanced lung adenocarcinoma with ALK mutations who exhibited a surprising and long-term response to treatment of ceritinib combined with bevacizumab.

A simultaneous phase-shifting interferometer with a monitored spatial light modulator (SLM) flexible reference mirror is proposed to balance the flexibility and accuracy of aspheric-surface in-process measurements. In this method, polarization simultaneous phase-shifting camera systems are applied to reduce the influence of environmental vibrations on the in-process measurements. An SLM reference mirror is employed to improve the flexibility of in-process measurements. A device is integrated to monitor the SLM surface in order to improve measurement accuracy caused by the spatial phase nonuniformity and modulation instability of the SLM. Thus, the SLM surface is monitored and the aspheric surface is measured simultaneously in only one interferometer, which presents the advantages of a compact structure and simple calibration. A flat acrylic mirror with an unknown surface figure error is measured by the proposed interferometer. Cross tests demonstrate the feasibility of this interferometer.

Smart home technologies are assisting elderly people to live independently and actively. Recently, the smart home healthcare market advances all over the world due to the increasing demand for connected health monitoring equipment. As a consequence, the interoperability problems of personal health standards/ecosystem and smart home protocols/ standards are rising. In the scope of this paper, a concept that supports the cooperation of the PCHA ecosystem and the ECHONET Lite protocol via a Data Distribution Platform is proposed and implemented.

Introduction: One of the most difficult steps of radiotherapy is to determine the clinical target volume (CTV) based on microscopic extension (ME). In this study, we performed a consecutive macropathologic analysis to assess ME in high-grade glioma (HGG) to determine appropriate CTV margins for radiotherapy.Material and methods: The study included 30 HGG patients with tumors located in non-functional areas, and supra total resection was performed. The ME distance from the edge of the tumor to the microscopic tumor cells surrounding brain tissue was measured. Associations between the extent of ME and clinicopathological characteristics were evaluated by multivariate linear regression (MVLR) analysis. An ME predictive model was developed based on the MVLR model. Meanwhile, in order to validate the feasibility and safety of this model, we prospectively recruited another 30 HGG patients in a 1:1 ratio to receive guideline-based radiotherapy (RT) or model-based RT. The overall response rate (ORR) was evaluated during a follow-up of 14 months.Results: Between June 2017 and July 2019, 652 pathologic slides were analyzed. The mean ME distance was 1.70cm (range, 0.63 to 2.87cm). The MVLR analysis identified that pathologic grade, subventricular zone (SVZ) contact and O6-methylguanine-DNA methyltransferase (MGMT) methylation, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status were independent variables predicting ME (all P < 0.05). A multivariable prediction model was developed as follows: YME = 0.672 + 0.513XGrade + 0.380XSVZ + 0.439XMGMT + 0.320XIDH + 0.333X1p/19q. The R-square value of goodness of fit was 0.780. In our validation cohort, after a mean follow-up of 7.65months, patients in the model RT group had a higher ORR than those in the guideline RT group (66.7% vs. 20%, P = 0.01).Conclusion: ME was heterogeneously distributed across different grades of gliomas according to the tumor location and molecular marker status, which indicated that CTV delineation should be individualized. The model could predict the ME of HGG, which may help clinicians determine the CTV for individual patients.

In recent years, Siamese trackers have been extensively studied because of their high accuracy and speed. However, when the target is occluded by other objects, the result will be greatly drifted, which affects the quality of the tracking results. This study based on the RGB-D data proposes an object tracking method integrating a target occlusion estimation module and a target location correction module, called Siamese-Occlusion-Correction (SiamOC). When a target is occluded, these modules can help the Siamese tracker correct the target location. In this paper, experiments demonstrate that the method which is the real-time tracker has achieved competitive results on the CDTB dataset.

Currently, intelligent security systems are widely deployed in indoor buildings to ensure the safety of people in shopping malls, banks, train stations, and other indoor buildings. Multi-Object Tracking (MOT), as an important component of intelligent security systems, has received much attention from many researchers in recent years. However, existing multi-objective tracking algorithms still suffer from trajectory drift and interruption problems in crowded scenes, which cannot provide valuable data for managers. In order to solve the above problems, this paper proposes a Multi-Object Tracking algorithm for RGB-D images based on Asymmetric Dual Siamese networks (ADSiamMOT-RGBD). This algorithm combines appearance information from RGB images and target contour information from depth images. Furthermore, the attention module is applied to repress the redundant information in the combined features to overcome the trajectory drift problem. We also propose a trajectory analysis module, which analyzes whether the head movement trajectory is correct in combination with time-context information. It reduces the number of human error trajectories. The experimental results show that the proposed method in this paper has better tracking quality on the MICC, EPFL, and UMdatasets than the previous work.

How to effectively evaluate students’ essays based on a series of relatively objective writing criteria has always been a topic of discussion. With the development of automatic essay scoring, a key question is whether the writing quality can be evaluated systematically based on the scoring rubric. To address this issue, we used an innovative set of graph-based features to predict the quality of Chinese middle school students’ essays. These features are divided into four sub-dimensions: basic characteristics, main idea, essay content, and essay development. The results show that graph-based features were significantly better at predicting human essay scores than the baseline features. This indicates that graph-based features can be used to reliably and systematically evaluate the quality of an essay based on the scoring rubric, and it can be used as an alternative tool to replace or supplement human evaluation.

Following the popularization of the connected device and home appliance, the market of smart home service is changing to an open mode from the mode that all develop by device makers. It will produce many of service developers to acquire data from device makers, and develop services and provide to end-users. But device makers do not have a uniform data description model and a uniform interface. Furthermore, the number of data will be billions, lead to discover the useful data by people is difficult. Therefore, in this research, we proposed a system that can use the data catalog to get data from heterogeneous architecture device clouds, provide by machine-readable interface and human-readable interface. And the system has a data auto-select mechanism to solve the problem that people difficult to discover useful data efficiently from billions of data. And validate the proposed system is effective.

Background The A type of carotid-cavernous fistulas (CCF-A) is characterized by direct communication between the internal carotid artery (ICA) with a very low incidence. But it severely endangers the health and even the life of patients, not only causes insufferable symptoms but also can induce fatal epistaxis, intracranial hemorrhages or even death. So, this disease needs therapy as early as possible. The ideal treatment for CCF-A is to exclude the fistula from circulation, preserving the carotid flow. Interventional therapy has become the chief method for CCF-A especially in recent years, but the prerequisite, that the microwire or and microcatheter in ICA can be navigated across the orificium fistulae and into distal ICA, is necessary. Otherwise it is difficult to reserve the communication of seriously injured ICA and the orificium fistulae could simultaneously be reliably closed. The authors used a series of new and novel CCF with good result. Methods The authors experienced a patient of TCCF-A, whose ICA was seriously injured and customary method failed in the first treatment because the microwire and microcatheter could not cross the segment of orificium fistulae. Then, the authors applied military (outflanking techniques, aerial refueling, and retrograde navigation) to manage this case. Results Finally, the CCF-A was completely cured and the parent artery was perfect preserved without any complication. Conclusions For patients of TCCF-A with severe ICA injury, these strategies may be very important for some patients whose affected ICA cannot tolerant to be blocked.

We propose a new method that balances attribute coverage for short-length cognitive diagnostic computerized adaptive testing (CD-CAT). The new method uses the attribute discrimination index (ADI-based method) instead of the number of items that measure each attribute [modified global discrimination index (MGDI)-based method] to balance the attribute coverage. Therefore, the information that each attribute provides can be captured. The purpose of the simulation study was to evaluate the performance of the new method, and the results showed the following: (a) Compared with uncontrolled attribute-balance coverage method, the new method produced a higher mastery pattern correct classification rate (PCCR) and attribute correct classification rate (ACCR) with both the posterior-weighted Kullback-Leibler (PWKL) and the modified PWKL (MPWKL) item selection method. (b) Equalization of ACCR (E-ACCR) based on the ADI-based method leads to better results, followed by the MGDI-based method. The uncontrolled method leads to the worst results regardless of item selection methods. (c) Both the ADI-based and MGDI-based methods produced acceptable examinee qualification rates, regardless of item selection methods, although they were relatively low for the uncontrolled condition.

The CAPTRA-Lung study (NCT03334864) is a prospective observational study that will capture real-world data of patients with advanced or metastatic non-small cell lung cancer (NSCLC) across China. The study aims to complement the results from current therapeutic regimens to improve the standard of diagnosis and treatment, evaluate the effectiveness and safety of systemic therapy, and determine the factors influencing the outcomes and responses to treatment. From January 2018 to December 2023, eligible patients with advanced or metastatic NSCLC who are receiving treatment and participating in follow-up at 16 institutions in China, will be enrolled. The demographic, clinical, laboratory, and treatment characteristics and responses to treatment will be recorded in a case report form and transcribed into an electronic data capture system. Overall survival, progression-free survival, overall response rate, and incidence of adverse events will be calculated from the time of initial enrolment until progression evaluated by physicians, last contact, date of death, or analysis cutoff date, respectively. Based on the disease characteristics and treatment strategies, four sub-cohorts will also be established. This study cohort could serve as a pool of patients with advanced or metastatic NSCLC to support further research.

Renewable energy has developed rapidly in recent years. For tackling the issues of intermittency, volatility and uncertainty of renewable energy, the electrochemical energy storage is attracting more and more attentions. How to select the optimal one among electrochemical energy storage technologies is an important topic. In this paper, a new hybrid model is proposed for the selection of the optimal electrochemical energy storage, which the Bayesian BWM is used to determine the criteria weights and the TOPSIS method is employed to rank the comprehensive performance of different electrochemical energy storage technologies. Meanwhile, eight criteria from economic, social, environmental and technological pillars are selected. Taking four kinds of electrochemical energy storage technologies as examples, the empirical result shows the Li-ion battery should be selected as the optimal electrochemical energy storage technology for renewable energy-based power generation stations compared with lead-acid battery, Nas battery and NiMH battery. The proposed method for the optimal selection of electrochemical energy storage is valid and practical, which can provide effective reference for decision-makers.

Amphihevir, a benzofuran derivative, is the first reported hepatitis C virus (HCV) nonstructural protein 4B (NS4B) inhibitor that has advanced to clinical trials (currently in phase Ib trial [CTR20170632]). Here, we report the results of a preclinical study of its potency, toxicity, selectivity, drug metabolism and pharmacokinetics (DMPK), and safety profiles. Amphihevir displayed good antiviral activities against genotype 1a (50% effective concentration [EC(50)] of 0.34 nM) and genotype 1b (EC(50) of 1.97 nM) replicons and no cytotoxicity in 12 cell lines derived from animals and humans. Amphihevir was found to be inactive against other viruses, human kinases, and G protein-coupled receptors (GPCRs), which implies its good selectivity. A 9-day long-term treatment of genotype 1b replicons with amphihevir resulted in a 3.8 Log(10) decline of the hepatitis C viral RNA at a concentration of 25× EC(90). Drug resistance screening showed that mutations occurred at H94, F98, and V105 of NS4B, which mediated the resistance to amphihevir. This result suggests that NS4B is the main target of amphihevir. There was no cross-resistance between amphihevir and NS5A, NS3/4A, and NS5B inhibitors, suggesting that amphihevir in combination with other anti-hepatitis C virus drugs could be used to treat hepatitis C, as proven by studies of amphihevir and other hepatitis C virus inhibitors. Pharmacokinetic studies demonstrated that amphihevir has good oral bioavailability and appropriate half-life (t(1/2)) in rats and dogs, thereby supporting its use once per day. Finally, amphihevir showed good safety profiles in rats and dogs. The results shed light on the use of amphihevir as a potential treatment option for chronic hepatitis C patients.

BACKGROUND The aim of this study is to explore the application of magnetic resonance imaging (MRI) and computed tomography (CT) image indexing in the assessment of cerebral injury of hypoxic-ischemic encephalopathy (HIE) neonate. METHODS The clinical data of 100 HIE children, who were admitted to the Department of Radiology, Xuzhou Children's Hospital, Jiangsu, from June 2013 to June 2014, were statistically analyzed. RESULTS Among the imaging data of 100 HIE children, the detection rate and false negative rate were 91.4% and 8.6%, respectively. The MRI detection rate was 100%. There was significant correlation between clinical indexing and CT indexing and MRI indexing (coefficient of contingency 0.731 and 0.723, P

The wheel-rail contact relationship in turnout is more complicated than that in regular track, which will increase the dynamic wheel-rail interaction. The slide plate, being important component of turnout, is prone to produce fatigue damage under the cyclic action of wheel-rail contact force. In this paper, an investigation and analysis has been done on the fatigue damage of welded slide plate, tongue depressor fracture and weld separation. The structural optimization schemes are proposed for various failure modes. The fatigue performance of slide plate for two schemes is evaluated and compared by simulation. The strength performance of slide plate for two schemes is compared by laboratory test. In simulation, two models were established to analyse the wheel-rail dynamic interaction of vehicle-track system and stress characteristics of slide plate, respectively. The fatigue life of the slide plate for two schemes were evaluated and compared, based on the fatigue damage theories. During the test, the ultimate strength of tongue depressor and bond strength between the slide platform and the base plate for two schemes, were tested and compared. The simulation and test results showed that the fatigue and strength performance of slide plate have increased reasonably after optimization. It can provide reference for design of slide plate.

The description of deformable mirror (DM) surface, which is usually a complex freeform surface, affects the measurement speed and accuracy in a real-time interferometric measurement system with a DM as the dynamic compensator. We propose an accurate and fast description method with automatically configurable Gaussian radial basis function. The distribution and shape factors of GRBFs are related to the complexity of the surface with sufficient flexibility to improve the accuracy, and the fitting results are automatically obtained using a traversal optimization algorithm, which can improve the fitting speed by reducing the number of time-consuming calculations. The feasibility is verified by numerical and practical experiment.

The wheel-rail dynamic resonance (W-RDR) under multi wheelset-rail nonlinear interactions in the mid-high frequency range is still unclear regarding wheelset flexibility, wave transmissions and reflections (W-TF) among each wheel-rail interaction. To clearly elucidate W-RDR and its induced modes, a double vehicle-track coupled dynamic model of multiple flexible wheelset-rail interactions is established. The validity of the model in the mid-high frequency range is verified by comparing the simulated axlebox acceleration with the measured data. Then, the W-RDR (vertical force, friction power) is calculated and analyzed. Furthermore, the W-RDR under the single/ double/ multiple wheelset-rail interactions is compared and the rail bending modes between bogie wheels are proposed. The influence of wheelset flexibility and W-TF among each wheel-rail interaction on W-RDR are clarified. Finally, the initiation mechanism of rail corrugation is revealed based on corrugation growth rate. The results show that the wheelset flexibility has limited influence on vertical force resonances but significant contribution to friction power resonances. The W-TF between bogie wheels produce three rail local bending modes. The W-TF between wheels of adjacent bogies further intensify response peaks but do not generate new resonances. The W-RDR is mainly caused by the P2 resonance mode, the rail bending modes between bogie wheels and the wheelset bending modes. The rail 3rd-order bending, pinned-pinned resonance between bogie wheels and the wheelset 2nd antisymmetric bending resonance are key factors in corrugation initiation. Moreover, the wheel-rail resonance at the bogie leading wheelset is more prone to produce corrugation than that at the rear wheelset.

Eleated expression of NIMA-related kinase 2 (NEK2) was frequently observed in a variety of malignant cancers, and it appears to be involved in the initiation, maintenance, progression, metastasis of cancer and is positively associated with poor prognosis. We sought to investigate NEK2 expression and its predictive roles in malignant gliomas, and study the correlation of NEK2 protein expression with proliferation, clinical parameters, overall survival and some other parameters. We investigate NEK2 protein expression in 99 samples of malignant gliomas, including 35 WHO grade II, 22 grade III, and 42 grade IV gliomas, by immunohistochemistry and western blot (n = 50). We then made correlative analysis of protein overexpression using the Kaplan-Meier method, Log rank test, and Cox proportional-hazards model analysis. NEK2 protein was overexpressed in malignant gliomas, but not in normal brain tissues. Overexpression of NEK2 correlated with malignancy, proliferation and adverse overall survival in gliomas. Moreover, chemotherapy, resection extent and WHO grade also correlate with overall survival in gliomas. However, within WHO grade II glioma subgroup, NEK2 overexpression showed no impact on overall survival. The present study firstly reveals that NEK2 protein is widely overexpressed in gliomas. NEK2 overexpression correlates significantly with malignancy (WHO grades), proliferation (Ki-67) and prognosis in malignant gliomas. NEK2 is a potential gene therapy target and prognostic indicator.

We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we developed 24 test items addressing the attributes of exothermic and endothermic reactions, chemical bonds and heat quantity change, reaction heat and enthalpy, thermochemical equations, and Hess’s law. The test was administered to a sample base of 694 senior high school students taught in 3 schools across 2 cities. Results based on the Rule Space Model analysis indicated that (1) the test items developed by the Rule Space Model were of high psychometric quality for good analysis of difficulties, discriminations, reliabilities, and validities; (2) the Rule Space Model analysis classified the students into seven different attribute mastery patterns; and (3) the initial hypothesized learning progression was modified by the attribute mastery patterns and the learning paths to be more precise and detailed.

Hyperglycemia was proved to cause neuron death in both animal experiments and poor outcome of hemorrhage patients, but the predictive ability of admission blood glucose level for early hematoma growth in patients with intracranial hemorrhage (ICH) is still controversial. Spot sign is a well-established imaging predictor for early hematoma growth, implying active microvascular bleeding. Here, we aim to assess associations between admission serum glucose and early hematoma expansion in ICH patients, as well as spot sign. We retrospectively reviewed all the patients with ICH from January 2017 to March 2018 in West China Hospital, Sichuan University. Admission blood glucose, clinical variables, radiological characteristics, and laboratorial parameters were obtained from medical record. According to computed tomography (CT) and computed tomography angiography (CTA) scan results, hematoma expansion and spot sign were identified by 2 experienced neuroradiologists. Multivariate logistic regression analyses were employed to adjust the associations of hematoma expansion and spot sign with other clinical parameters. Around 42 patients exhibited early hematoma expansions and 26 exhibited spot signs over 138 enrolled patients. The average level of admission blood glucose was 7.55 mmol/L. Multivariate logistic regression analyses revealed that Glasgow Coma Scale (GCS) score on admission, hematoma volume, spot sign, and hyperglycemia were associated with hematoma expansion, whereas admission serum glucose and hematoma size were only associated with spot sign, respectively. Admission blood glucose level is correlated with hematoma growth and incidence of spot sign. These results indicated that hyperglycemia probably plays a critical role in the pathological process of the active bleeding. Further studies should be drawn urgently to understand the potential molecular mechanism of systemic hyperglycemia in affecting prognosis of patients with ICH.

Nivolumab prolonged disease control in a patient with advanced squamous lung cancer that was refractory to multiple treatments. The rapid eradication of cancer after the administration of nivolumab caused hemoptysis and repeated infection. Six months after immunotherapy, mediastinal lymph node metastasis developed and afatinib effectively relieved dysphonia associated with nerve paralysis.

In this work, Shi-Jie Wei and Tao Xin contributed equally to this work. This annotation for the contribution was omitted in the original publication of this paper [1]. It can be confirmed in the previous arXiv version [2]. Hence, The sentence “Shi-Jie Wei and Tao Xin contributed equally to this work.” should be added.

The performance of the limited-information statistic M2 for diagnostic classification models (DCMs) is under-investigated in the current literature. Specifically, the investigations of M2 for specific DCMs rather than general modeling frameworks are needed. This article aims to demonstrate the usefulness of M2 in hierarchical diagnostic classification models (HDCMs). The performance of M2 in evaluating the fit of HDCMs was investigated in the presence of four types of attribute hierarchies. Two simulation studies were conducted to examine Type I error rates and statistical power of M2 under different simulation conditions, respectively. The findings suggest acceptable Type I error rates control of M2 as well as high statistical power under the conditions of a Q-matrix misspecification and the DINA model misspecification. The data of Examination for the Certificate of Proficiency in English (ECPE) were used to empirically illustrate the suitability of M2 in practice.

The poor prognosis in non-small-cell lung cancer has driven the development of novel targeted therapies. Vascular endothelial growth factor is the most potent force in mediating tumor angiogenesis, and many angiogenesis inhibitors have been developed for oncology treatment. We performed a study to characterize the efficacy, safety and tumor suppression of three lung cancer related anti-angiogenic drugs (bevacizumab, endostar and apatinib) using transgenic zebrafish embryo and human lung cancer xenotransplantation model. All three drugs demonstrated remarkable angiogenesis and tumor inhibition effect in the zebrafish model, within the nonlethal dose range. Endostar and bevacizumab showed competitive anti-tumor efficacy. The anti-tumor performance of apatinib was hamstrung by its elevated toxicity at 35 °C. The addition of pemetrexed to anti-angiogenesis therapy had no obvious additional benefit in tumors.

Infrared electrochromic device is a kind of device whose infrared emissivity can change reversibly under electric field excitation. This kind of device has important applications in the fields of adaptive infrared camouflage and intelligent thermal control, and has become a research frontier and hot spot in the field of infrared radiation control. In this paper, the working principle, research status and progress of infrared electrochromic devices based on metal oxides, conductive polymers, graphene and metals are summarized, and the development trend of infrared electrochromic device is analyzed.

The wheel high-order polygonal wear leads to strong vibration/ noise and deterioration of railway systems, whose distribution is closely related to the seasonality and wheelset position. To elucidate its initiation mechanism and distribution rule, a multi-vehicle-track coupled dynamic model considering the wheel-rail variable friction characteristics was established and the OOR growth rate used to evaluate the degree of polygonal wear initiation was proposed. The wheel-rail resonance and OOR growth rate was simulated, and compared with the results under the single/ double/ multiple wheelset-rail interactions. We find that the rail bending modes between wheels of bogie are the key to induce friction power resonance and polygonal wear initiation, in which the rail 3rd-order bending resonance between wheels of bogie is the root cause of the high-order polygonal wear. The rail bending resonance between wheels of adjacent bogies accelerates the further growth of polygonal wear. Furthermore, by analyzing the influence of wheel-rail friction coefficient, fastener stiffness, and curve track on the polygonal wear, the distribution rule related to the seasonality and wheelset position was explained. The polygonal wear is more frequent and severe in summer than in other seasons, mainly due to frequent rainfalls, followed by high temperatures. The 1st /4th wheelset is prone to form the polygonal wear, which is due to the vehicle reciprocates on the railway line containing curves and the rail bending resonance between wheels of adjacent bogies. The research is expected to provide guidance for the prevention and service of polygonal wear.

The quality of track geometry is an important aspect in railway engineering, as it reflects any deviations and thus the actual condition of a track. Monitoring and prediction of a relevant geometry quality parameter provides an opportunity for effective maintenance, thus creating the advantages of extending the life of the asset, reducing maintenance costs and minimizing possession time requirements. Effective maintenance practice requires a good understanding of the behaviour of track structures over time and also prediction of its condition using only a few inputs. This paper presents a grey-system-theory-based model for predicting track irregularity. Three variants of the grey model are presented and their performances are compared with simple linear and exponential models. Regression models and the grey-system-theory-based models are used to obtain the standard deviation of the longitudinal level from a series of geometry inspection data. The overall performances of the models are evaluated in terms of the regression and prediction accuracies, and it is shown that a Fourier series modification of the grey model has the best performance and the minimum error. The contribution of this paper is the creation of a prediction model for track geometry quality, which is essential for planning and scheduling of preventive geometry maintenance.

The aim of this paper is to study the optimization of the rail profile for heavy haul railways. A numerical model is developed, where the rail profile is parameterized as a generalized function for a series of independent variables. A well-designed formula, which characterizes the conformance between wheel and rail profiles around contact point for all possible wheel–rail contact situations, is considered as the objective function. During the construction of the objective function, a wheel–rail contact geometry algorithm is implemented to detect contact point positions quickly. Linear and nonlinear constraints are introduced in order to meet some necessary conditions. Then, the optimization of rail profile can be transformed into a typical mathematical nonlinear optimization problem with single objective, multivariables, and multiconstraints. In order to solve this problem effectively and efficiently, the sequential quadratic programming algorithm combined with Lagrange function, quasi-Newton method is employed. At each major iteration, a quasi-Newton approximation is made of the Hessian matrix of the Lagrangian function using BFGS updating method. This is then used to generate a quadratic programming subproblem whose solution is for forming the search direction for the iteration of independent variables. Finally, the R75 rail profile, prevalently used in China’s heavy haul railways, is optimized using the developed model to better match the LM wheel profile. A modified rail profile is put forward and compared with the original rail profile systematically in wheel–rail contact geometry relationship, vehicle–track dynamic behaviors, and wear developments. A vehicle–track coupling dynamics model and a wheel–rail wear prediction model are respectively established to conduct the comparative study. According to the calculation results, the optimized rail profile is proved to have superior performances and, thus, can be considered a better choice to match LM wheel for China’s heavy haul railways, which is of practical value for the design and preventive grinding of heavy haul rails. In addition, this application example validates the rationality of the developed numerical optimization model. It can also be used for the optimization of other rail profiles.

The occurrence of high-speed railway wheel-rail defects is closely related to the vibration characteristics of the track structures, which can be affected by service conditions. Theoretical models are the main measures to study this problem. However, due to the modeling simplification and initial parameters used in current track modeling methods, it is difficult to accurately simulate the vibration characteristics of in-serving track structures. To supplement this shortcoming, by conducting a series of research works, including: (1) a modal test on a ballastless track; (2) the sensitivity analysis of the modal parameters of the ballastless track; (3) designing and carrying out of three model updating schemes based on the measured modal parameters, this paper obtained a model that is highly consistent with the vibration characteristics of the actual track structure. The research work can provide a reliable reference for modal testing, vibration analysis and model updating of ballastless track structures.

Rubber mats are widely used as a common vibration reduction material in urban rail transit and high-speed railway, due to its excellent technical characteristics. At the transition zones between different types of slab tracks, a moving wheel experiences a rapid change in elevation. Severe vibration and deterioration of track structures may occur because of the sudden change in the vertical track stiffness. This paper focuses on applying rubber mats to solve the transition problem by changing stiffness gradually. A self-compiling program was used for establishing the vehicle-track coupled dynamic analysis model. Dynamic responses of vehicle-track system without transition scheme are simulated to demonstrate the necessity of designing a track transition. One 5-slab-transition scheme is proposed and optimized according to the simulation results. The smoothness of the transition zone is significantly improved with the proposed design.

Background: Parkinson's disease (PD) is one of the foremost neurological disorders which is differentiated next to the progressive dopamine (DA) loss, especially in the area of substantia nigra pars compacta (SNpc). Aberrant neuroinflammation, as well as excessive reactive oxygen species (ROS) generation, have exposed to stimulate neuronal defeat in the gradual developing PD. The current study investigated whether fucoxanthin could attenuate the pathophysiology seen in an 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-mediated PD model. Materials and Methods: C57BL/6 mice received 30 mg/kg of MPTP (i.p.) every day for 5 consecutive days to establish PD, subsequently everyday treatment with fucoxanthin intended for 7 days. Intraperitoneal injection of MPTP, resulted in impaired motor functions, dopaminergic neuronal loss, decreased DA, Tyrosine hydroxylase (TH) levels, and microglial activation-mediated neuroinflammation. Results: Fucoxanthin administration ameliorated α-synuclein abnormal accumulation and motor impairment in MPTP-induced chronic PD mouse model. Our observed findings revealed that fucoxanthin administration reverses the MPTP-mediated decline of DA neuron, TH along with microglial activation predominantly in the SNpc region. The Western blot analysis exposed that fucoxanthin suppressed the expression patterns of proinflammatory cytokines following MPTP administration. Conclusion: In conclusion, Fucoxanthin exerts neuroprotective potential in opposition to MPTP-mediated PD mice through repressing α-synuclein expression, oxidative stress and gliosis, recommended that fucoxanthin might perform as a beneficial remedy toward PD amelioration.

We present an electrically tunable terahertz (THz) spatial phase shifter (SPS) based on liquid crystal (LC). An integrated structure was proposed, consisting of two LC layers (with horizontal and vertical grating electrode respectively) and a 45° linear polarization plate in the middle. The performance of this device provides actively controllable spatial phase modulation capabilities, which has many potential applications. Moreover, one application as adaptive THz lens was also implemented. The initial measurement results show good focusing capacity and adjustable focal length.

AIM Patients with advanced nonsquamous nonsmall cell lung cancer (NSCLC) who experienced progression with two or more lines chemotherapy have no treatment options that clearly confer a survival benefit. As a novel vascular endothelial growth factor receptor-2 tyrosine kinase inhibitor, apatinib has a certain antitumor effect for various solid tumors. The present study evaluated the efficacy and safety of apatinib in advanced nonsquamous NSCLC as salvage treatment in Chinese real-world practice. METHODS Twenty-eight patients were enrolled in this observational study from October 2015 to May 2017. Progression-free survival (PFS) and overall survival (OS) were graphed by Kaplan-Meier curve and intergroup comparisons were carried out by log-rank test. Objective response rate (ORR), disease control rate (DCR) and adverse effects (AEs) were also evaluated. RESULTS Seven patients obtained partial response, and 18 obtained stable disease, representing an ORR of 26% and a DCR of 93%. Median PFS and OS were 3 (95% confidence interval [CI] 2.6-3.4) and 7.4 (95% CI 1.3-13.5) months, respectively. The efficacy analysis showed that Eastern Cooperative Oncology Group (ECOG) performance status 0-1 was correlated with prolonged OS and PFS (P

As the cost of software development rises, software reuse has been overly successful in controlling the time and expenses to date. However, it is difficult to catch the essential of reusing management. In fact, there are a lot of factors and approaches must be considered in software reuse process, so it is important to strengthen key point management in software reusing. In order to manage software reusing process effectively, this paper provides a framework of software reusing engineering management. The framework shows us how to choose types of reuse process and what to do in reuse process management. This paper will discuss four types of software reusing, and show how to analyze reusing feasibility. Then, different types will be related to different reusing management processes and key points. Besides, this paper will also illustrate a case study. The case indicates that the framework could take advantage of reusing factors and approaches together, and give reasonable processes in each type of software reusing engineering management. In addition, key point management plays a crucial role in software reusing. As a summary, the advantages of this framework and the future research will be discussed.

As of today, no one can tell when a universal quantum computer with thousands of logical quantum bits (qubits) will be built. At present, most quantum computer prototypes involve less than ten individually controllable qubits, and only exist in laboratories for the sake of either the great costs of devices or professional maintenance requirements. Moreover, scientists believe that quantum computers will never replace our daily, every-minute use of classical computers, but would rather serve as a substantial addition to the classical ones when tackling some particular problems. Due to the above two reasons, cloud-based quantum computing is anticipated to be the most useful and reachable form for public users to experience with the power of quantum. As initial attempts, IBM Q has launched influential cloud services on a superconducting quantum processor in 2016, but no other platforms has followed up yet. Here, we report our new cloud quantum computing service -- NMRCloudQ (http://nmrcloudq.com/zh-hans/), where nuclear magnetic resonance, one of the pioneer platforms with mature techniques in experimental quantum computing, plays as the role of implementing computing tasks. Our service provides a comprehensive software environment preconfigured with a list of quantum information processing packages, and aims to be freely accessible to either amateurs that look forward to keeping pace with this quantum era or professionals that are interested in carrying out real quantum computing experiments in person. In our current version, four qubits are already usable with in average 1.26% single-qubit gate error rate and 1.77% two-qubit controlled-NOT gate error rate via randomized benchmaking tests. Improved control precisions as well as a new seven-qubit processor are also in preparation and will be available later., Comment: NMRCloudQ at http://nmrcloudq.com:8000/zh-hans/. Interface is Chinese; English available soon