Water vapor estimation based on 1-year data of E-band millimeter wave link in North China

Abstract. The amount of water vapor in the atmosphere is very small, but its content varies greatly in different humidity areas. The change in water vapor will affect the transmission of microwave link signals, and most of the water vapor is concentrated in the lower layer, so the water vapor density can be measured by the change in the near-ground microwave link transmission signal. This study collected 1-year data of the E-band millimeter wave link in Hebei, China, and used a model based on the International Telecommunication Union Radiocommunication Sector (ITU-R) to estimate the water vapor density. An improved method of extracting the water-vapor-induced attenuation value is also introduced. It has a higher time resolution, and the estimation error is lower than the previous method. In addition, this paper conducts the seasonal analysis of water vapor inversion for the first time. The monthly and seasonal evaluation index results show a high correlation between the retrieved water vapor density and the actual water vapor density value measured by the local weather station. The correlation value for the whole year is up to 0.95, the root mean square error is as low as 0.35 g m−3, and the average relative error is as low as 5.00 %. Compared with European Center for Medium-Range Weather Forecast (ECMWF) reanalysis, the correlation of the daily water vapor density estimation of the link has increased by 0.17, the root mean square error has been reduced by 3.14 g m−3, and the mean relative error has been reduced by 34.00 %. This research shows that millimeter wave backhaul link provides high-precision data for the measurement of water vapor density and has a positive effect on future weather forecast research. </jats:p

Research on Rainfall Monitoring Based on E-Band Millimeter Wave Link in East China

Accurate rainfall observation data with high temporal and spatial resolution are essential for national disaster prevention and mitigation as well as climate response decisions. This paper introduces a field experiment using an E-band millimeter-wave link to obtain rainfall rate information in Nanjing city, which is situated in the east of China. The link is 3 km long and operates at 71 and 81 GHz. We first distinguish between the wet and the dry periods, and then determine the classification threshold for calculating attenuation baseline in real time. We correct the influence of the wet antenna attenuation and finally calculate the rainfall rate through the power law relationship between the rainfall rate and the rain-induced attenuation. The experimental results show that the correlation between the rainfall rate retrieved from the 71 GHz link and the rainfall rate measured by the raindrop spectrometer is up to 0.9. The correlation at 81 GHz is up to 0.91. The mean relative errors are all below 5%. By comparing with the rainfall rate measured by the laser raindrop spectrometer set up at the experimental site, we verified the reliability and accuracy of monitoring rainfall using the E-band millimeter-wave link.</jats:p

Characterization of the complete mitochondrial genome of Arma custos (Hemiptera: Pentatomidae)

The Arma custos is an important natural enemy of agricultural and forest pests. The complete mitochondrial genome (mitogenome) of A. custos was determined in the present paper. This mitogenome is 15,629 bp in size and comprises of 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes, and a control region. All protein-coding genes are initiate with ATN, except ND2, COX1, ATP8 and ND1 use TTA or TTG as the start codon, and terminate with TAA with the exception of COX2 and ND5 which use a single T residue as the stop codon. All tRNAs, ranging from 63 to 72 bp, have the cloverleaf structure except tRNASer(AGN). The monophyly of the subfamily Asopinae is highly supported by the phylogenetic tree and A. custos is recovered as sister to the remaining Asopinae species

Novel FEM-Based Wavelet Bases and Their Contextualized Applications to Bearing Fault Diagnosis

Feature extraction herein refers to using an appropriate wavelet basis to filter vibration signals with the aim to reveal fault transient characteristics, which underlies bearing fault diagnosis. Wavelet transform has developed into a well-established signal processing approach with wide applications in bearing fault diagnosis. Nevertheless, a suitable wavelet basis is essential for wavelet transform to perform its best. So far, numerous wavelet bases are available for bearing diagnosis, most of which, however, have a waveform analogous to that of impulse responses of a single-degree-of-freedom system. In fact, bearings are of multi-degree-of-freedom and not totally rigid. Furthermore, a specific wavelet basis is definitely unable to accommodate all bearing vibrations, given that fault characteristics vary with bearings&rsquo; operating conditions and fault types. As such, a simulated wavelet-driven personalized scheme is proposed to improve bearing fault diagnosis for contextualized engineering practical applications. For a specific bearing of interest, personalized finite element models (FEM) with various faults are constructed and corresponding fault-induced responses are then obtained. Afterward, FEM-based wavelet bases are formulated and specified by its discrete values from such responses. Taking NU306 bearing with inner or outer defect for example, FEM-based wavelet basis is applied to the corresponding experimental signals by means of wavelet filtering. The comparisons with adaptive Morlet and impulse wavelet demonstrate that the personalized FEM-based wavelet basis match very well with the fault-induced transients present in experimental bearing vibrations and thus have a promising superiority and expandability

The latent time from surfacing to the onset of symptoms and the number of cases with different severities in 5,278 DCI cases.

*<p>Kendall correlation analysis showed a weak negative correlation between the severity and the latent time (τ = −0.3604, <i>P</i><0.0001).</p

Measurement of strain in Al-Cu interconnect lines with x-ray microdiffraction

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