Anomalous normal-state gap in an electron-doped cuprate.

In the underdoped n-type cuprate Nd2-xCexCuO4, long-range antiferromagnetic order reconstructs the Fermi surface, resulting in a putative antiferromagnetic metal with small Fermi pockets. Using angle-resolved photoemission spectroscopy, we observe an anomalous energy gap, an order of magnitude smaller than the antiferromagnetic gap, in a wide portion of the underdoped regime and smoothly connecting to the superconducting gap at optimal doping. After considering all the known ordering tendencies in tandem with the phase diagram, we hypothesize that the normal-state gap in the underdoped n-type cuprates originates from Cooper pairing. The high temperature scale of the normal-state gap raises the prospect of engineering higher transition temperatures in the n-type cuprates comparable to those of the p-type cuprates.

Differentiated roles of Lifshitz transition on thermodynamics and superconductivity in La2-xSrxCuO4.

The effect of Lifshitz transition on thermodynamics and superconductivity in hole-doped cuprates has been heavily debated but remains an open question. In particular, an observed peak of electronic specific heat is proposed to originate from fluctuations of a putative quantum critical point p* (e.g., the termination of pseudogap at zero temperature), which is close to but distinguishable from the Lifshitz transition in overdoped La-based cuprates where the Fermi surface transforms from hole-like to electron-like. Here we report an in situ angle-resolved photoemission spectroscopy study of three-dimensional Fermi surfaces in La2-xSrxCuO4 thin films (x = 0.06 to 0.35). With accurate kz dispersion quantification, the said Lifshitz transition is determined to happen within a finite range around x = 0.21. Normal state electronic specific heat, calculated from spectroscopy-derived band parameters, reveals a doping-dependent profile with a maximum at x = 0.21 that agrees with previous thermodynamic microcalorimetry measurements. The account of the specific heat maximum by underlying band structures excludes the need for additionally dominant contribution from the quantum fluctuations at p*. A d-wave superconducting gap smoothly across the Lifshitz transition demonstrates the insensitivity of superconductivity to the dramatic density of states enhancement.

Multi-variable classification model for valve internal leakage based on acoustic emission time-frequency domain characteristics and random forest.

To use acoustic-emission technology to detect leaks inside valves, the necessary first step is to model the valve-internal-leakage acoustic-emission signal (VILAES) mathematically. A multi-variable classification model that relates the VILAES characteristics and the leakage rate under varying pressure is built by combining time-frequency domain characteristics and the random-forest method. A Butterworth bandpass filter is used to preprocess the VILAES from a liquid medium, and the best frequency band for filtering is determined as being 140 kHz-180 kHz. Then, (i) the standard deviation, (ii) root mean square, (iii) wavelet packet entropy, (iv) peak standard-deviation probability density, and (v) spectrum area are calculated as the VILAES characteristics, and six parameters-the pressure and the five VILAES characteristics-are used as the inputs for the random-forest classification model. Analysis shows that the five VILAES characteristics increase with an increase in the leakage rate. The multi-variable classification model is established by random forest to determine whether the valve leakage is small, medium, or large. The random forest uses many decision trees to predict the final result. For the same experimental data, the accuracy and operating time of the multi-variable classification model are compared with those of a support-vector-machine classification method for the bandpass and wavelet packet filtering preprocessing methods. The results show that the modeling method based on the combination of time-frequency characteristics and random forest has shorter operating time and higher accuracy.

Signal processing method based on connection fitting of echo peak point with a large slope for ultrasonic gas flow meter.

Ultrasonic gas flow meters are especially suitable for measurement in pipelines with large diameters. However, on the one hand, it is difficult to find a stable feature point to calculate the duration of propagation of the ultrasonic signal, through which we can obtain the real-time flow rate of the gas, and on the other hand, the computation incurred by signal processing methods to this end is burdensome and affects the real-time performance of the flow meter. To solve these problems, this study examines the characteristics of the stability of the echo signal and patterns of variation in the echo contour at different flow rates of gas. We found that peak points of the middle part of the rising segment of the echo signal were relatively stable, and the slope of the envelope of this part was always relatively large but constant, which indicates that peak points in this part were approximately distributed along a straight line. This finding is used to develop a signal processing method based on the connection fitting of the echo peak point with a large slope. This method is easy to implement, incurs a small amount of calculation, and has strong anti-interference ability. Moreover, it can guide research on signal processing methods and the stability of the echo signal. The proposed method was implemented on a dual-core hardware system, and the results of calibration show that it can attain 1.0-level accuracy over a measurable range of 30 m3/h-1100 m3/h.

Metallic surface states in a correlated d-electron topological Kondo insulator candidate FeSb2.

The resistance of a conventional insulator diverges as temperature approaches zero. The peculiar low-temperature resistivity saturation in the 4f Kondo insulator (KI) SmB6 has spurred proposals of a correlation-driven topological Kondo insulator (TKI) with exotic ground states. However, the scarcity of model TKI material families leaves difficulties in disentangling key ingredients from irrelevant details. Here we use angle-resolved photoemission spectroscopy (ARPES) to study FeSb2, a correlated d-electron KI candidate that also exhibits a low-temperature resistivity saturation. On the (010) surface, we find a rich assemblage of metallic states with two-dimensional dispersion. Measurements of the bulk band structure reveal band renormalization, a large temperature-dependent band shift, and flat spectral features along certain high-symmetry directions, providing spectroscopic evidence for strong correlations. Our observations suggest that exotic insulating states resembling those in SmB6 and YbB12 may also exist in systems with d instead of f electrons.

Incoherent strange metal sharply bounded by a critical doping in Bi2212.

In normal metals, macroscopic properties are understood using the concept of quasiparticles. In the cuprate high-temperature superconductors, the metallic state above the highest transition temperature is anomalous and is known as the "strange metal." We studied this state using angle-resolved photoemission spectroscopy. With increasing doping across a temperature-independent critical value p c ~ 0.19, we observed that near the Brillouin zone boundary, the strange metal, characterized by an incoherent spectral function, abruptly reconstructs into a more conventional metal with quasiparticles. Above the temperature of superconducting fluctuations, we found that the pseudogap also discontinuously collapses at the very same value of p c These observations suggest that the incoherent strange metal is a distinct state and a prerequisite for the pseudogap; such findings are incompatible with existing pseudogap quantum critical point scenarios.

Peak-to-peak standard deviation based bubble detection method in sodium flow with electromagnetic vortex flowmeter.

The steam generator (SG) is a heat exchange device between a sodium coolant and water in sodium-cooled fast reactors. Its transfer tubes are prone to leakage to result in sodium-water reaction, which will affect the operational safety of the entire nuclear reactor. To this end, a signal processing method is studied to detect the SG leakage using an electromagnetic vortex flowmeter (EVFM). Water flow is firstly used to replace liquid sodium for conducting the hydraulic experiments, and the output signal of the sensor of the EVFM (abbreviated as EVFM sensor output signal) is collected under different gas injection volumes. The characteristics of the signal are analyzed in the time domain, and the collected signals are modeled. A signal processing method of bubble detection in liquid sodium is proposed based on the peak-to-peak standard deviation, which is realized in real time on the hardware system based on a digital signal processor. The gas injection experiments in liquid sodium are conducted to verify the effectiveness of the signal processing method and system developed in this paper. The minimum amount leakage of water can be detected as 0.1 g/s.

Fermi surface reconstruction in electron-doped cuprates without antiferromagnetic long-range order.

Fermi surface (FS) topology is a fundamental property of metals and superconductors. In electron-doped cuprate Nd2-x Ce x CuO4 (NCCO), an unexpected FS reconstruction has been observed in optimal- and overdoped regime (x = 0.15-0.17) by quantum oscillation measurements (QOM). This is all the more puzzling because neutron scattering suggests that the antiferromagnetic (AFM) long-range order, which is believed to reconstruct the FS, vanishes before x = 0.14. To reconcile the conflict, a widely discussed external magnetic-field-induced AFM long-range order in QOM explains the FS reconstruction as an extrinsic property. Here, we report angle-resolved photoemission (ARPES) evidence of FS reconstruction in optimal- and overdoped NCCO. The observed FSs are in quantitative agreement with QOM, suggesting an intrinsic FS reconstruction without field. This reconstructed FS, despite its importance as a basis to understand electron-doped cuprates, cannot be explained under the traditional scheme. Furthermore, the energy gap of the reconstruction decreases rapidly near x = 0.17 like an order parameter, echoing the quantum critical doping in transport. The totality of the data points to a mysterious order between x = 0.14 and 0.17, whose appearance favors the FS reconstruction and disappearance defines the quantum critical doping. A recent topological proposal provides an ansatz for its origin.

Echo signal envelope fitting based signal processing methods for ultrasonic gas flow-meter.

The echo signal of the ultrasonic gas flow-meter is difficult to locate, and the computation of signal processing methods proposed by others is extensive which affects the meter's real-time performance. Aiming at solving these problems the echo signal envelopes under different flow rates are analyzed. And three kinds of signal processing methods based on echo signal envelope fitting are proposed. The shape of the echo signal remains the "approximate spindle shape" as the flow rate increases, and the envelope gradient of the middle parts of the upper envelope's rising section and the lower envelope's falling section remains the same at different flow rates, so the mathematical models of the two sections are established to obtain the envelope gradient curves of the two sections. With the envelope gradient curves, the ranges of envelope and peak points that linearly distributed are obtained. The least squares fitting is performed on those peak points to obtain two feature straight lines for respectively representing the upper envelope's rising section and the lower envelope's falling section. According to the spatial characteristics of the feature straight lines, the points on the feature straight lines are selected as the feature points for quickly locating the echo signal. According to the offline verification and comparison, the best one of three kinds of signal processing methods is selected, and realized on the hardware system of the two-channel ultrasonic gas flow-meter. The transmitter of two-channel ultrasonic gas flow-meter is developed based on FPGA & DSP dual core structure. It utilizes the parallel processing capacity and logic control ability of FPGA to realize the controlling of the high-speed ADC & DAC and the storage of the data. At the same time, it adopts the high-speed computing capacity of DSP to implement the digital signal processing method. The gas flow calibration experiments were carried out in a national accredited testing agency to verify the effectiveness of the signal processing methods and system. The experimental results show that the improved signal processing method based on echo signal upper and lower envelope fitting can quickly and accurately locate the echo signal. And the measurable range of the ultrasonic gas flow meter based on this signal processing method is broadened to 10 m3/h to 1,300 m3/h, and the turndown ratio is broadened to 1:130.

The Impact of Cervical Spinal Cord Contusion on the Laryngeal Resistance in the Rat.

The present study was designed to investigate laryngeal function responses to chemoreceptor activation after unilateral high-cervical spinal cord contusion in rats. Adult male Sprague-Dawley rats received laminectomy or unilateral contusion at the C2 spinal cord. Both respiratory airflow and subglottal pressure were measured in spontaneously breathing rats at three days, two weeks, or six weeks after spinal surgery. Laryngeal closure responses were evoked via intrajugular capsaicin (1.5 µg/kg) administration and hypoxia (12.5% O2, 3 min) to activate bronchopulmonary C-fibers and chemoreceptors, respectively. High cervical contusion resulted in long-term reductions in tidal volume without changes in laryngeal resistance at baseline. Alternatively, capsaicin-induced increased subglottal pressure was significantly attenuated in contused rats at three days post-injury. Contused rats regained the ability to increase laryngeal resistance after capsaicin treatment at two and six weeks post-injury, whereas this recovered response remained weaker than uninjured animals. Notably, hypoxia-induced laryngeal closure was not altered during the acute injured stage, but instead was blunted at six weeks post-injury. These data suggest that cervical spinal cord injury not only influences the breathing pattern, but it also impacts upper airway function through modulation of laryngeal resistance. An attenuated laryngeal closure response may negatively impact the ability to prevent irritant inhalation and maintenance of the functional residual capacity. This may contribute to the provocation of pulmonary disease after cervical spinal cord injury.

Geographic distribution of echinococcosis in Tibetan region of Sichuan Province, China.

BACKGROUND: Echinococcosis is a parasitic zoonosis caused by Echinococcus larvae parasitism causing high mortality. The Tibetan Region of Sichuan Province is a high prevalence area for echinococcosis in China. Understanding the geographic distribution pattern is necessary for precise control and prevention. In this study, a spatial analysis was conducted to explore the town-level epidemiology of echinococcosis in the Sichuan Tibetan Region and to provide guidance for formulating regional prevention and control strategies. METHODS: The study was based on reported echinococcosis cases by the end of 2017, and each case was geo-coded at the town level. Spatial empirical Bayes smoothing and global spatial autocorrelation were used to detect the spatial distribution pattern. Spatial scan statistics were applied to examine local clusters. RESULTS: The spatial distribution of echinococcosis in the Sichuan Tibetan Region was mapped at the town level in terms of the crude prevalence rate, excess hazard and spatial smoothed prevalence rate. The spatial distribution of echinococcosis was non-random and clustered with the significant global spatial autocorrelation (I = 0.7301, P = 0.001). Additionally, five significant spatial clusters were detected through the spatial scan statistic. CONCLUSIONS: There was evidence for the existence of significant echinococcosis clusters in the Tibetan Region of Sichuan Province, China. The results of this study may assist local health departments with developing better prevention strategies and prompt more efficient public health interventions.

Transient process based electromagnetic flow measurement methods and implementation.

The ordinary electromagnetic flowmeter (EMF) utilizes the steady-state period of the excitation current for measuring the flow rate in order to ensure zero stability and measurement accuracy. In this paper, the transient process of EMF is studied to measure the flow rate so as to realize applications requiring ultra-low power consumption, for example, water meters. For this reason, the dynamic excitation current and signal voltage of the transient process are analyzed, and three kinds of transient measurement methods are proposed to determine the relationship between the processing results of the signal voltage and flow rates. They are the voltage-current ratio method, voltage-current differential method, and differential interference compensation method. In order to verify these measurement methods, a DSP (Digital Signal Processor) that is the same processing chip as the current ordinary electromagnetic flow transmitter is selected to design a hardware system of the transmitter, and the excitation current and signal voltage of the transient process are acquired. Analysis of experimental data shows that there is a good linear relationship between the processing results of the signal voltage and flow rates. The software of the electromagnetic flow transmitter based on DSP is developed, and the transient measurement methods are realized in real time so as to perform the water flow calibration experiments and power consumption tests. The experimental results show that the measurement accuracy is 0.5% which is the same as the ordinary EMF. Comparisons of power consumption show that the excitation power consumption of EMF based on the transient measurement principle is 1/1200 of that of the ordinary EMF.

Error analysis and new dual-cosine window for estimating the sensor frequency response function from the step response data.

Aiming at reducing the estimation error of the sensor frequency response function (FRF) estimated by the commonly used window-based spectral estimation method, the error models of interpolation and transient errors are derived in the form of non-parameter models. Accordingly, window effects on the errors are analyzed and reveal that the commonly used hanning window leads to smaller interpolation error which can also be significantly eliminated by the cubic spline interpolation method when estimating the FRF from the step response data, and window with smaller front-end value can restrain more transient error. Thus, a new dual-cosine window with its non-zero discrete Fourier transform bins at -3, -1, 0, 1, and 3 is constructed for FRF estimation. Compared with the hanning window, the new dual-cosine window has the equivalent interpolation error suppression capability and better transient error suppression capability when estimating the FRF from the step response; specifically, it reduces the asymptotic property of the transient error from O(N-2) of the hanning window method to O(N-4) while only increases the uncertainty slightly (about 0.4 dB). Then, one direction of a wind tunnel strain gauge balance which is a high order, small damping, and non-minimum phase system is employed as the example for verifying the new dual-cosine window-based spectral estimation method. The model simulation result shows that the new dual-cosine window method is better than the hanning window method for FRF estimation, and compared with the Gans method and LPM method, it has the advantages of simple computation, less time consumption, and short data requirement; the actual data calculation result of the balance FRF is consistent to the simulation result. Thus, the new dual-cosine window is effective and practical for FRF estimation.

Energy transfer model and its applications of ultrasonic gas flow-meter under static and dynamic flow rates.

Most of the ultrasonic gas flow-meters measure the gas flow rate by calculating the ultrasonic transmission time difference between the downstream and upstream. Ultrasonic energy attenuation occurs in the processes of the ultrasonic generation, conversion, transmission, and reception. Additionally, at the same time, the gas flow will also affect the ultrasonic propagation during the measurement, which results in the ultrasonic energy attenuation and the offset of ultrasonic propagation path. Thus, the ultrasonic energy received by the transducer is weaker. When the gas flow rate increases, this effect becomes more apparent. It leads to the measurement accuracy reduced, and the measurement range narrowed. An energy transfer model, where the ultrasonic gas flow-meter under without/with the gas flow, is established by adopting the statistical analysis and curve fitting based on a large amount of experimental data. The static sub model without the gas flow expresses the energy conversion efficiency of ultrasonic gas transducers, and the dynamic sub model with the gas flow reflects the energy attenuation pattern following the flow rate variations. The mathematical model can be used to determine the minimum energy of the excitation signal for meeting the requirement of specific measurement range, and predict the maximum measurable flow rate in the case of fixed energy of excitation signal. Based on the above studies, a method to enhance the excitation signal energy is proposed under the output power of the transmitting circuit being a finite value so as to extend the measurement rage of ultrasonic gas flow-meter.

Analysis on Serum Trace Element Levels of Echinococciasis Patients in Garze Tibetan Autonomous Prefecture in Sichuan, China, 2011.

In Garze Tibetan autonomous prefecture in Sichuan province, China, 41 echinococciasis patients who had received surgical treatment were recruited in the study, and 82 health persons who had lived in Garze for at least 10 years were selected as controls. The serum levels of Zn, Se and Cu of the cases and controls were detected. The results showed that most echinococciasis cases were distributed in Shiqu county (17.1%, 7/41), and only 1 case was distributed in Yajiang county (2.4%). The male to female ratio of the cases was 1:1.56. The echinococciasis patients were mainly aged 30-39 years (36.59%, 15/41). And, the cases aged 20-49 years accounted for 68.29% (28/41). Compared with health controls, the serum levels of Zn and Se of the cases significantly declined. However, the serum level of Cu of the cases had no significantly change. It was confirmed that the serum levels of Zn and Se were interrelated with the prevalence of echinococciasis.

Development of Coriolis mass flowmeter with digital drive and signal processing technology.

Coriolis mass flowmeter (CMF) often suffers from two-phase flowrate which may cause flowtube stalling. To solve this problem, a digital drive method and a digital signal processing method of CMF is studied and implemented in this paper. A positive-negative step signal is used to initiate the flowtube oscillation without knowing the natural frequency of the flowtube. A digital zero-crossing detection method based on Lagrange interpolation is adopted to calculate the frequency and phase difference of the sensor output signals in order to synthesize the digital drive signal. The digital drive approach is implemented by a multiplying digital to analog converter (MDAC) and a direct digital synthesizer (DDS). A digital Coriolis mass flow transmitter is developed with a digital signal processor (DSP) to control the digital drive, and realize the signal processing. Water flow calibrations and gas-liquid two-phase flowrate experiments are conducted to examine the performance of the transmitter. The experimental results show that the transmitter shortens the start-up time and can maintain the oscillation of flowtube in two-phase flowrate condition.

Frequency-domain correction of sensor dynamic error for step response.

To obtain accurate results in dynamic measurements it is required that the sensors should have good dynamic performance. In practice, sensors have non-ideal dynamic characteristics due to their small damp ratios and low natural frequencies. In this case some dynamic error correction methods can be adopted for dealing with the sensor responses to eliminate the effect of their dynamic characteristics. The frequency-domain correction of sensor dynamic error is a common method. Using the existing calculation method, however, the correct frequency-domain correction function (FCF) cannot be obtained according to the step response calibration experimental data. This is because of the leakage error and invalid FCF value caused by the cycle extension of the finite length step input-output intercepting data. In order to solve these problems the data splicing preprocessing and FCF interpolation are put forward, and the FCF calculation steps as well as sensor dynamic error correction procedure by the calculated FCF are presented in this paper. The proposed solution is applied to the dynamic error correction of the bar-shaped wind tunnel strain gauge balance so as to verify its effectiveness. The dynamic error correction results show that the adjust time of the balance step response is shortened to 10 ms (shorter than 1/30 before correction) after frequency-domain correction, and the overshoot is fallen within 5% (less than 1/10 before correction) as well. The dynamic measurement accuracy of the balance is improved significantly.

[Survey on a new case of visceral leishmaniasis in Shanxi Province].

A new case of visceral leishmaniasis (kala-azar) was reported by Changzhi CDC of Shanxi Province in September 2011. The case was investigated clinically and epidemiologically. The patient was a two-year-old boy who lived in Huangnian Town of Changzhi County in Shanxi Province. Clinical examination showed hepatosplenomegaly, consistent decrease of blood cells and Leishman-Donovan body in the bone marrow smear. The rK39 immune diagnosis test showed strongly positive. The case was diagnosed as kala-azar. After one course treatment of sodium stibogluconate, the patient's condition improved markedly. There were no cases of kala-azar in this region historically. Blood samples of 17 individuals and 5 domestic animals including 3 dogs were all negative in the rK39 immunodiagnostic test. It is speculated that the potential risk of kala-azar transmission exists in this region.

Note: anti-strong-disturbance signal processing method of vortex flowmeter with two sensors.

Some digital signal processing methods have been used to deal with the output signal of vortex flowmeter for extracting the flow rate frequency from the noisy output of vortex flow rate sensor and achieving the measurement of small flow rate. In applications, however, the power of noise is larger than that of flow rate sometimes. These strong disturbances are caused by pipe vibration mostly. Under this condition the previous digital signal processing methods will be unavailable. Therefore, an anti-strong-disturbance solution is studied for the vortex flowmeter with two sensors in this Note. In this solution, two piezoelectric sensors are installed in the vortex probe. One is called the flow rate sensor for measuring both the flow rate and vibration noise, and the other is called the vibration sensor for detecting the vibration noise and sensing the flow rate signal weakly at the same time. An anti-strong-disturbance signal processing method combining the frequency-domain substation algorithm with the frequency-variance calculation algorithm is proposed to identify the flow rate frequency. When the peak number of amplitude spectrum of the flow rate sensor is different from that of the vibration sensor, the frequency-domain subtraction algorithm will be adopted; when the peak number of amplitude spectrum of the flow rate sensor is the same as that of the vibration sensor, the frequency-variance calculation algorithm will be employed. The whole algorithm is implemented in real time by an ultralow power micro control unit (MCU) to meet requirements of process instrumentation. The experimental results show that this method can obtain the flow rate frequency correctly even if the power of the pipe vibration noise is larger than that of the vortex flow rate signal.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor.

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at tau=0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.