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Objectives –Mismatch negativity (MMN) has been demonstrated as a potential biomarker for pre-attentive processing and prognosis in patients with psychosis. However, previous studies mainly evaluated the reliability of MMN across only two repeated sessions, which is inadequate to draw a convincing conclusion. The current study aimed to assess multi-session test-retest reliability in duration-related MMN (dMMN) and frequency-related MMN (fMMN). Methods –We recorded four repeated sessions of electroencephalography (EEG) from 16 healthy participants in an oddball task. MMNs were extracted and their reliability was evaluated by intra-class coefficient (ICC). We also analyzed the correlation between fMMN and dMMN. Results –Both dMMN and fMMN amplitudes exhibited good test-retest reliability, and fMMN had better reliability (average ICC = 0.7279) than dMMN (average ICC = 0.6974). Moreover, dMMN and fMMN showed more than moderate linear correlation in amplitudes (r = 0.598, CI: [0.100, 0.857]). Conclusion –Both the duration- and frequency-related MMN amplitudes were highly reliable across four-session experiments. These results provide further evidence for the potential utility of MMNs as biomarkers in research into brain function, and prognosis in psychotic illness.

This study is aimed at carrying out investigations on a domestic gas field, located in Yanchang, China, with a view to optimize the natural gas purification process. The main objectives of this work are (i) to reduce the natural gas purification system’s energy consumption and (ii) improve the existing purification levels. Process simulations were carried out using Aspen Plus™ software, and a comprehensive technical and economic analysis was carried out. The single-factor sensitivity analysis method was used to determine the parameters of absorption, such as the reflux ratio and number of stages. The heat transfer process was analyzed using the energy-saving method of the energy system, and a modified process was recommended. The optimization results show that the recommended system has better purification performance, the comprehensive energy consumption is effectively reduced, and the energy efficiency is improved by 9%.

For tilting pad bearing of large unit, it is not easy to identify stiffness and damping coefficients in full-size unit test. Because of many limiting factors in large unit test, the stiffness and damping test methods are not fully applicable to large units, which can be easily implemented in laboratory. The nonexcitation methods are proposed in this paper to identify the stiffness and damping coefficients of tilting pad bearing in the critical speed range of large unit, including direct method and iterative method. Firstly, the rotor speed and vibration during the whole period are obtained. The vibration data of the first-order critical speed range in the startup stage are selected, and the stiffness and damping coefficients of tilting pad bearing are identified through the two methods. The results show that the stiffness and damping coefficients identified through the direct method are generally less than the theoretical values. The identification error of stiffness coefficient is within ±9%, and the identification accuracy of stiffness coefficient is significantly higher than that of damping coefficient. The damping coefficient identified by the iterative method agrees well with the theoretical value, and the identification error is about −3%. In conclusion, the stiffness and damping coefficients of tilting pad bearing in the range of first-order critical speed can be obtained by combining the two identification methods. These identification results are relatively reliable and can basically meet the analysis requirements of important vibration problems of bearing-rotor system.

Air gap discharge voltage is the key parameter to determine the minimum approach distance for live working. In this study, a mathematical–physical model for predicting 50% discharge voltage of the transmission line air gaps considering the effect of live line worker is developed based on the continuous leader inception criterion. Also, the tower structure coefficient S T is proposed to represent the influence of various tower structures and S T is calculated by finite element method. Finally, the switching impulse discharge tests of the equipotential worker-tower structure gaps are carried out on 750 kV transmission lines to verify the proposed model. The research results show that the errors between the calculation and experimental data are within ±4.03% which demonstrates the feasibility of discharge voltage prediction for complicated live working gaps. This model offers a possible way to determine the safety air gap distance for live working by analytical and numerical calculation rather than costly and time-consuming experiments.

Accurate prediction of software energy consumption is of great significance for the sustainable development of the environment. In order to overcome the limitations of a single prediction method and further improve the prediction accuracy, a combined prediction energy model of adaboost algorithm and RBF (radial basis function) neural network at software architecture level is proposed. Firstly, three kinds of energy prediction models are established by polynomial regression, support vector machine and neural network respectively. Secondly, the RBF neural network is used to nonlinear combine the predicted values of the above three models. Finally, RBF integrated by adaboost algorithm is used as high-precision prediction of energy consumption. Experimental results show that the prediction accuracy of the combined prediction model is higher than that of the single model.

A kind of distributed hybrid thrust bearing with tilting pad is proposed in this paper, and the influence of thrust plate tilt on bearing performance is analyzed. The film thickness equation is constructed, considering the machining error and installation error synthetically which are the main causes of thrust plate tilt. Substituting the film thickness equation to the classical calculation equation of thrust bearing, the time-varying stiffness of the bearing is obtained. The influence of tilt angle of thrust plate on time-varying stiffness of the bearing is analyzed through the case bearing, and the bearing performance is controlled by change pivot position of tilting pad which is represented by preload coefficient. The results show that the thrust plate tilt causes the fluctuation of the bearing stiffness during the rotation period, and this fluctuation is exacerbated as the increasing of the tilt angle. The bearing stiffness increases and the tilt angle range of the thrust plate decreases accordingly, because that the increasing of the preload coefficient of tilting pad makes the bearing unilateral gap decrease. However, the large preload coefficient exacerbates the adverse effect of thrust plate tilt on the bearing, so the preload coefficient of the tilting pad needs to be adjusted reasonably. The research in this paper can provide a theoretical reference for the optimization of the tilt angle of the thrust plate and provide data support for the engineering application of distributed hybrid thrust bearing with tilting pad.

Traditional collaborative filtering recommendation is one of the most commonly used algorithms in current recommendation systems, and it is also the mainstream algorithm used in the e-commerce industry. The basic principle of collaborative filtering is that users with similar interests will have similar interest bias in the future. However, the traditional collaborative filtering algorithm faces some of the following problems in the e-commerce industry: (1) lacking of confidence based on user interest bias similarity; (2) without consideration of the time factor; (3) no correlation between behaviors. Therefore, the collaborative filtering model based on user interest probability (PUCF) proposed in this paper to solves the above problems. Firstly, Wilson confidence interval is used to solve the problem of confidence, the behavioral time decay factor is obtained through the normalized time. And then considering the problem of conversion between behaviors. Besides the algorithm assigns different calculation weights to the existence of progressive behavior relationships, and to a certain extent considers the influence of the internal connections between behaviors on user interest. Through looking for the optimal parameters and making comparative experiments, it shows that the effect of collaborative filtering model based on user interest probability (PUCF) proposed in this paper is better than other collaborative filtering methods.

Helicopters are widely used due to their excellent low-altitude flight characteristics and convenient take-off and landing advantages. However, the complex environment in low altitude has always been a high-risk scenario where helicopter accidents frequently occur. Lidar has become a key sensor for future helicopters to improve their survivability due to their three-dimensional sensing capabilities, full-time detection, and high accuracy. This article first introduces the laser radar-based helicopter-assisted navigation augmented reality processing framework, and then discusses the laser radar point cloud data processing method in detail. Finally, the point cloud data and the image are superimposed and fused to achieve the effect of augmented reality. The verification in the simulation environment shows that the augmented reality effect brought by the superposition and fusion of the processed point cloud data and the image can effectively improve the pilot's environmental perception ability.

High-frequency transformers with small size and light weight have been widely concerned by researchers at home and abroad. The oil-paper insulation of high frequency transformers is affected by the high frequency pulse produced by power electronic device, which is more prone to discharge fault and insulation failure. To study the effect of high frequency pulse voltage on the discharge characteristics of oil-paper insulation, a needle plate electrode model was used to carry out the discharge experiment of different layers of oil-paper insulation samples at 1–20 kHz bipolar high frequency square wave voltage produced by high frequency power supply. The partial discharge and breakdown characteristics of oil-paper insulation under high frequency square wave pulse voltage were studied. The results show that the discharge quantity of oilpaper insulation increases greatly with high frequency pulse voltage compared with AC voltage. There is no discharge phenomenon in the process of discharge development, which is significantly different from that under AC voltage. The intensity of discharge increases under high frequency pulse voltage and its increasement accelerates the deterioration of oil-paper insulation.

Fiberglass reinforced plastic (FRP) hot sticks are the most common tool used in live working on 10-kV overhead power lines. However, the flashover voltage of hot sticks significantly decreases with increase in altitude. Until now, test data for live working in areas where the altitude exceeds 3000 m have not been available. In this paper, an experimental study on the flashover performance of the FRP hot sticks was carried out in different high-altitude areas. Power frequency discharge tests were performed in Yambajan (4300 m), Lhasa (3600 m), Nyingchi (2900 m), and Wuhan (28 m), respectively. The flashover characteristics in different areas were obtained and analyzed, and a voltage correction method was proposed. Based on these test results, the minimum approach distance of hot stick in high-altitude conditions was determined, and the safety margin was verified. The test results show that for altitudes between 2500 and 4500 m, the hot stick flashover voltage decreases by 7.725% with every 1000 m of altitude increase, and the minimum approach distance of hot stick is 0.6 m (without end fitting) and 0.9 m (with end fitting), and the safety margin is 3.

We demonstrate a new, to the best of our knowledge, dimensional “horizontal optimization” scheme, which can improve the high-speed characteristics of a PIN photodetector by designing the incident optical field distribution. First, coaxially incident faculae with the same peak and same power are studied and simulated, revealing that the bandwidth of the photodetector illuminated by uniform light is higher than that of the device illuminated by nonuniform light. Next, an annular optical field is designed incident to the photodetector, and the bandwidth is further improved. For a PIN photodetector, by carefully optimizing the incident optical field distribution, the photodetector bandwidth under an annular optical field can be increased significantly compared with that under conventional coaxial illumination.

Under the background of big data, the financial information of enterprises is increasing rapidly, and the relationship between financial data is intricate. In order to enhance competitiveness, enterprises should build a big data financial sharing system according to their own conditions to ensure that the financial management of enterprise groups is more standardized, High-efficiency, optimized allocation and scientific use of capital resources, and reduce the financial risk of the enterprise. For example, in a company, there were 7 risks in the financial system in 2013. Since the introduction of the financial shared service center cloud platform in 2015, the number of risks has not been less than 3 in three consecutive years, which has significantly reduced the risks in the financial system. This fully shows that the establishment of the cloud platform of the financial shared service center can bring more economic benefits to enterprises and promote the improvement of enterprise competitiveness.

Background Lymph node ratio (LNR) has been suggested to be an effective prognostic tool for stratifying non-small cell lung cancer (NSCLC) cases. In this study, we sought to determine cancer-specific survival (CCS) of NSCLC cases from the SEER registry and used the X-tile method to optimize CCS-based LNR cut-off points for prognostic stratification of node-positive NSCLC. Methods CSS and other clinicopathologic variables were retrieved from the SEER registry. Kaplan-Meier methods were used to calculate CSS. The optimal cut-off points for LNR classification were determined by the X-tile approach. Multivariate Cox regression analysis was performed to identify independent risks of CSS. Results Totally 11,341 lung cancer patients were included. Their median CSS was 22 months (range 0,143). The median LNR was 0.22 (Q1,Q3: 0.11, 0.50). X-tile analysis showed that the optimal LNR cut-off points were 0.28 and 0.81, dividing the cohort into low (LNR1 ≤ 0.28; n = 6580, 58%), middle (0.28 n = 3025, 26.7%), and high (LNR3 > 0.81; n = 1736, 15.3%) subsets. Kaplan-Meier analysis showed that patients with a low LNR had a significantly higher CCS versus patients with middle or high LNR (P P P Conclusions LNR is an independent prognostic factor of node-positive NSCLC and its optimal cut-off values established using the robust x-tile method effectively define subpopulations of node-positive NSCLC cases, which is important in guiding selection of treatment strategies clinically.

High quality is one of the most objectives in rice breeding. Introduction and evaluation of the quality of rice germplasm resources is of great significance for selecting high-quality rice parents and breeding high-quality rice varieties. In this study, 28 rice germplasm resources were introduced from Africa and Brazil, and their quality was evaluated in Wuhan, Hubei Province. The results showed that the processing and appearance quality of these germplasm resources were excellent, but the cooking and eating quality were poor. Finally, 13 varieties with high quality were screened out. The correlation analysis of different quality traits showed that the correlation among processing quality, appearance quality, cooking and eating quality was low. The genotypes of GS3 , Wx and Alk were identified. It was found that both GS3 and Wx contained two genotypes, and Alk contained three genotypes. The phenotypes showed significantly difference between different genotypes for both Wx and ALK . Our results will give valuable germplasm resources, gene resources and marker resources for breeding high quality rice varieties.

This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. We have fabricated arrays of 60-nm-size magnetic Fe nanodots over a 1-cm2 -size area using nanoporous alumina membranes as shadow masks. The size and size distribution of the nanodots correlate very well with that of the membrane pores. By placing an antiferromagnetic FeF2 layer underneath the Fe nanodots, an exchange anisotropy can be introduced into the Fe/FeF2 system. We have observed an increase in the magnetic hysteresis loop squareness in biased nanodots, suggesting that exchange bias may be used as a tunable source of anisotropy to stabilize the magnetization in such nanodots.

Aiming at the monitoring system for the distributed nitrogen generator devices, a remote distributed monitoring system for mine nitrogen generator devices based on the edge gateway is designed. Three parts are involved in the monitoring system, they are local devices, cloud server and monitoring side. Local devices are typical industrial control system with PLC controller and network communicator to realize remote monitoring. More than common remote monitoring system, an edge gateway is added near the local controller, helping handle data, store data and compress data, communicating with cloud server for remote monitoring. The cloud server communicates with the nitrogen generator devices with MQTT protocol. The monitoring side is programmed using JQuery and Echarts to build Web interface. Two tests were conducted to confirm the time-delay and control reliability of the remote monitoring system, it showed that time delay was less than 400ms with no packet loss and success control rate is more than 99.9%.

Success in supply chain implementation depends on the way of dealing with market changes and customer needs. Agility is a concept that has been introduced in recent years to improve the supply chain. On the other hand, paying attention to environmental problems is another issue, and chains are trying to increase their popularity by focusing on this issue. Considering the importance of this issue, designing a multiobjective closed-loop supply chain network has been discussed in this research. The main contribution of this research is the integration of green and agility concepts in supply chain design. In this regard, a mathematical model is presented with economic, environmental, and agility objectives. First, the mathematical model is solved using the Epsilon constraint method, and then, the multiobjective weed algorithm is proposed to solve the model. The results of comparisons between the two methods show that the multiobjective weed algorithm has performed well in terms of various metrics of NPS, SNS, and Max Spread. In terms of the solving time, the average solving time of this algorithm was about 0.1% of the solving time of the Epsilon constraint method. Moreover, all cases show the superiority of the multiobjective weed algorithm over the Epsilon constraint method in solving the proposed mathematical model.

Intelligent logistics refers to the realization of system perception, comprehensive analysis, and timely processing in all aspects of logistics transportation, warehousing, packaging, loading and unloading, circulation processing, distribution, and information services based on information technologies such as the Internet of Things, VR, and artificial intelligence, And the function of self-adjustment. The realization of intelligent logistics can greatly reduce the transportation costs of various related industries, improve transportation efficiency, and enhance corporate profitability. In this paper, the application of intelligent logistics system in Jiangxi railway freight has greatly improved the efficiency of transportation, warehousing, packaging, handling, circulation processing, distribution, and information services.

Background: Approximately 4-20% patients with degenerative lumbar diseases showed persistent pain after lumbar fusion surgery that may develop into failed back surgery syndrome (FBSS), and this persistent pain may be related to the postoperative increased release of inflammatory mediators. Minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) can obviously reduce the intraoperative soft tissue trauma. The aim of this study is to investigate the persistent pain in the patients with degenerative lumbar diseases undergoing MIS-TLIF compared with conventional‑invasive TLIF. Material and methods: This study retrospectively included 146 patients (MIS-TLIF vs. conventional‑invasive TLIF: 56 vs. 90), and the incidence of persistent pain were evaluated. Furthermore, inflammation related markers in both blood and drainage fluid samples, including white blood cell (WBC) count, C-reactive protein (CRP), creatine kinase (CK), interleukin-6 (IL-6) and IL-1β, were tested before and after operation. Results: Significantly larger number of patients undergoing conventional‑invasive TLIF showed postoperative persistent pain compared to those undergoing MIS-TLIF (4/56, 7.1% vs. 20/90, 22.2%; P < 0.05). In both treatment groups, the patients with postoperative persistent pain showed increased IL-6 and IL-1β in drainage fluid, as well as increased IL-6 in blood samples (P < 0.05), and there is significant correlation between the inflammation markers in drainage fluid and the extent of postoperative persistent pain in patients with postoperative persistent pain (P < 0.05). Conclusions: Local inflammatory substance accumulation may be potential cause for postoperative persistent pain, and MIS-TLIF may reduce this inflammatory accumulation at the surgical site and subsequently reduce the risk of persistent pain.

When residents participate in demand response, the randomness of residents' electricity consumption behavior can not be ignored in formulating demand response strategy. In this paper, according to the randomness of residential electricity consumption, the demand response control strategy for residential flexible load in China's new urban area is studied by making full use of the detailed residential electricity data available from the power grid. The daily demand response optimization dispatching model for residential flexible load equipment is established for load aggregator. Then the optimal scheduling model is solved.

At present, the research of power system demand response mainly tends to the research of ‘peak shaving and valley filling’, that is, under the premise that some loads on the user side are interruptible or transferable loads, the grid can mobilize the enthusiasm of users directly or indirectly through effective economic or technical means to achieve peak shaving and valley filling. The power grid guides the users to use electricity orderly by means of electric charge compensation, differential electricity price, time of use price and other incentive measures, that is, the power market can reduce the peak valley difference of power grid, reduce the loss of power grid and load impact, and ensure the reliable operation of the power grid. In this paper, according to the research status of demand response, combined with the requirements of the demand response system, the multi user demand response resource address pool is studied and designed. Based on the resource address pool, the rapid query under the demand response demand can be realized.

Processing satellite signals can deceive receiver time. For GPS time receivers, this paper proposes two time spoofing methods, one is based on delay control, and the other is based on clock frequency control. By analyzing the principle of satellite timing, the receiver's time-related parameters and time spoofing principle are deduced and the delay control model and the clock control model are constructed respectively. Finally, the effectiveness of the two control methods is verified through design simulation experiments, of which results present that the time-delay control method can linearly skew the receiver time and the clock control method makes the receiver time shift at a certain speed.

With the integration of electric vehicle (EV), distributed energy storage and temperature control load into the new generation power system, new challenges and opportunities are presented for power grid dispatching. Large and medium-sized users mainly rely on the operation mode of load aggregators as intermediaries to participate in demand response. Aiming at the demand response allocation problem of aggregators in this mode, and according to the response characteristics of various flexible loads, a scheduling method for flexible load aggregators to participate in power grid is proposed. We proposed a dispatching method aim at flexible load aggregator participating in power grid. Firstly, we have established different flexible load model. Secondly, the demand response strategy under the flexible incentive for personalized customization of user requirements has been studied. Finally, through the analysis of simulation examples, the effectiveness and feasibility of the method of flexible load aggregators participating in power system dispatching operation planning are verified.

Defect detection methods based on machine learning extremely accelerate the transmission lines routine inspection process. In this paper, we propose an automatic defect detection method based on improved YOLOv3. Random feature pyramid (RFP) structure is introduced for the highly discriminative feature map construction. Focal loss function, which focus on differentiating between easy and hard examples, is employed to deal with the class imbalance problem. Experimental results demonstrate that the proposed approach obtains competitive performance compared with state-of-the-art deep learning object detection methods.

In order to solve the problems of tracking accuracy and servo performance degradation caused by the lagging measurement information and amplitude mismatch of the heterogenous sensor in the photoelectric pod system, a high-precision comprehensive processing method based on multisource sensor measurement information is proposed in this paper according to the typical control loop of the photoelectric tracking system. Firstly, based on the optimal estimation theory, the output miss distance of the tracker is pre estimated to solve the problem of insufficient estimation of target position accuracy and high speed noise. Then, in view of the information mismatch between the angle sensor and the angular velocity sensor, the nonlinear tracking differentiator is used to get the angular velocity of the angle sensor and make a difference with the measured value of the angular velocity sensor. Finally, the amplitude and delay of the measurement information are adjusted adaptively according to the size of the root mean square of the difference value until the difference value is minimized. The algorithm was applied to the stable tracking experiment of a certain type of pod, and the results showed that the tracking accuracy increased from $92\ \mu \text{rad}$ to $54\ \mu \text{rad}$ , which significantly improved the tracking accuracy of the system and proved the effectiveness of the algorithm. The method proposed in this paper can be quickly applied to other photoelectric systems, and has reference significance[1].

The target position accuracy of the two aircraft intersection position system depends heavily on the position and attitude measurement accuracy of the platform. For this reason, this paper proposes the INS/ CNS integrated navigation method based on the stable platform of star seeking for the intersection measurement environment of airborne photoelectric platform, which is used to obtain the attitude and position reference of UAV platform accurately and in real time, finally improve the target position accuracy of the intersection measurement of two UAVs[3].

For high-end CNC machine tools, the stiffness of the spindle system is one of the most important performance indicators. In this paper, the hydrostatic motorized spindle system of a grinding machine is taken as the research object, and a two-degree-of-freedom stiffness model of the spindle system considering rotor swing is proposed. The stiffness of the spindle system under different excitation frequencies is analyzed, and the contributions of the stiffness of two bearings to the stiffness of the spindle system are evaluated. The vibration test on the spindle system is implemented through the hammering method. The vibration responses of the spindle system are obtained, and the stiffness of the spindle system is identified. The results show that the test results of the stiffness of the spindle system are in good agreement with the theoretical calculation, with an average error of about 14.21%. The research in this paper can provide theoretical and data support for bearing design and stiffness evaluation of a hydrostatic spindle system.

The liquid phase maldistribution factor has been investigated in trickle bed reactor, and the results are compared with the previous measurement data from literature by using the Electrical Resistance Tomography. The simulation results are in agreement with the experimental results to some degree. The flow rates and particle sizes have been simulated with the method of multiphase flow. There are two different particles with average diameters of 3.4 mm and 5.3 mm. The flow rate has been studied ranging from 100 ml/min to 1100 ml/min. It has been found that the changes of the particles and liquid flow rates have a significant impact on the distribution of the liquid volume fraction. The internal liquid holdup is more serious, and the wall-flow phenomenon is more obvious in a bigger flow rate. The prediction of the liquid volume fraction distribution is a key research technique. Regression predictions have also been researched on the section near outlet, which can predict the internal flow state of the trickle bed under the condition of high temperature and high pressure. The average liquid volume fraction is linear with flow rates. The maldistribution factor is the index correlation with the flow rates. The results and main conclusions can be used to predict the distributions and get the properties in a trickle bed reactor.

In this paper, the research work of image recognition is carried out in the face of the detection of illegal intrusion objects in power transmission lines. By analyzing the current intelligent monitoring and real-time prediction related technologies, Based on the image data of binocular camera, the method of identifying illegal foreign objects is mainly studied under the condition of constructing line space equation. The research on identification method proposes the use of continuous inter-frame difference method and background difference method to detect foreign object recognition, which can effectively overcome the problem of missed detection of static foreign objects, shadow misdetection and inability to locate foreign objects in the foreign object detection algorithm based on image difference. And using the point cloud to calculate the spatial distance, it can accurately obtain the distance from the invading foreign object to the line. And the feasibility of the verification method on site.

A synchronous-traveling carrier photodetector (STC-PD) with a thick absorption region and large diameter is presented and investigated for 100 Gbps PAM4 applications. In the STC structure, a suitable electric field is introduced to synchronize the traveling of electrons and holes, which achieves high bandwidth while maintaining large responsivity. The characteristics of STC-PD, including electric field distribution, energy band diagram, responsivity, junction capacitance, and frequency response, have been studied carefully.

We propose a method to correct the error induced by the obscurations of Ritchey-Chretien (R-C) collimators, when measuring modulation transfer function (MTF) of high-resolution space cameras by the ISO 12,233 slanted-edge method. The obscurations of an R-C collimator include the secondary mirror (SM) and its supporting bars. Mathematical models are derived to simulate possible obscurations by virtual surfaces of Zemax, with which we get the correction function (CF) of the obscuration induced error (OIE). Simulated results manifest that the proposed method can correct the OIE. Furthermore, an experiment setup is established with the same system parameters of the previous Zemax modeled system. The experiment results verify the effectiveness of the proposed method again. Our method can guarantee the precision of the ISO 12,233 slanted-edge method when an R-C collimator is chosen.

Materials sandwiches of aluminium/titanium are widely used in structural aerospace, especially in the surface coating and skeletons of aircrafts. Due to their inhomogeneous behavior and poor machinability, drilling aluminium/titanium sandwich in one-shot operation has brought great challenges to the modern manufacturing community. In this paper, a series of experiments were conducted to understand and characterize the process of drilling aluminium/titanium sandwich. Experimental results have shown that the serrated chip is not common in drilling. Only the outer edge of the spiral chip has saw teeth because of the variable cutting speed along the cutting edge. In addition, a better understanding of the phase transformation on surface and subsurface of drilled hole has been provided. Two kinds of phase transformations on the surface of drilled hole have been observed: one is the allotropic transformation from α to β phase and the other is that from β to minor phases α′ (hexagonal martensites). All these are mainly due to the interaction of mechanical force and high temperature.

Background Chinese herbal medicine has been used to treat hypertension in China and East Asia since centuries. In this study, we conduct an overview of systematic reviews of Chinese herbal medicine in the treatment of primary hypertension to 1) summarize the conclusions of these reviews, 2) evaluate the methodological quality of these reviews, and 3) rate the confidence in the effect on each outcome. Methods We comprehensively searched six databases to retrieve systematic reviews of Chinese herbal medicine for primary hypertension from inception to December 31, 2015. We used AMSTAR to evaluate the methodological quality of included reviews, and we classified the quality of evidence for each outcome in included reviews using the GRADE approach. Results A total of 12 systematic reviews with 31 outcomes were included, among which 11 systematic reviews focus on the therapeutic effect of Chinese herbal medicine combined with conventional medicine or simple Chinese herbal medicine versus simple conventional medicine. Among the 11 items of AMSTAR, the lowest quality was “providing a priori design” item, none review conformed to this item, the next was “stating the conflict of interest” item, only three reviews conformed to this item. Five reviews scored less than seven in AMSTAR, which means that the overall methodological quality was fairly poor. For GRADE, of the 31 outcomes, the quality of evidence was high in none (0 %), moderate in three (10 %), low in 19 (61 %), and very low in nine (29 %). Of the five downgrading factors, risk of bias (100 %) was the most common downgrading factor in the included reviews, followed by imprecision (42 %), inconsistency (39 %), publication bias (39 %), and indirectness (0 %). Conclusions The methodological quality of systematic reviews about Chinese herbal medicine for primary hypertension is fairly poor, and the quality of evidence level is low. Physicians should be cautious when applying the interventions in these reviews for primary hypertension patients in clinical practice. Electronic supplementary material The online version of this article (doi:10.1186/s13643-016-0353-y) contains supplementary material, which is available to authorized users.

Prostate cancer is a heterogenous disease that has a varied range from indolent to highly aggressiveness. The routinely used biomarker, Prostate Specific Antigen (PSA), is controversial due to over-diagnosis. A new approach is urgently needed to discriminate the indolent and lethal prostate cancer. We report the measurements of patient urine using surface-enhancement Raman scattering (SERS) as a potential means of differentiating aggressive and indolent prostate cancer types. To this end, urine samples from twenty prostate cancer patients with known clinical outcome are investigated in this study, with ten in each of the two groups: aggressive and indolent. SERS measurements, ten for each sample, are carried out in blind without revealing any clinical details to the investigators. Principal component analysis (PCA) and linear discriminant analysis (LDA) are used to statistically analyze the large number of Raman spectra to identify and classify the specific Raman features potentially associated with aggressive and indolent prostate cancer types. The experimental classifications are compared with the clinical outcome of the prostate cancer patients to demonstration the potential of SERS as an alternative method for patient screening and decision-making for the optimal treatment strategy.