4-Meth­oxy­anilinium hexa­fluoro­phosphate monohydrate

In the structure of the title compound, C7H10NO+·PF6 −·H2O, the protonated 4-meth­oxy­anilinium cations and hexa­fluoro­phosphate anions are bridged by the water mol­ecule via N—H⋯O and O—H⋯F hydrogen bonds. The resulting zigzag chains extend along the c axis. In addition, C—H⋯π inter­actions are observed in the crystal packing

4-Bromo­anilinium hexa­fluoro­phosphate monohydrate

In the title compound, C6H7BrN+·PF6 −·H2O, N—H⋯F, N—H⋯O and O—H⋯F hydrogen-bonding inter­actions stabilize the crystal structure and give rise to to chains running parallel to the c axis. In the anion, four of the F atoms are disordered over two sets of sites of equal occupancy

Body Mass Index of Male Youths Aged 18-20 Years of the Han Nationality Living in Different Regions of China

The study was conducted to assess the nutritional status and levels of body mass index (BMI, kg/m2) and to evaluate the geographical distribution of male youths of the Han nationality in China. In total, 60,773 male youths, aged 18-20 years, of the Han nationality, were categorized into underweight, normal-weight, overweight, and obesity according to the international adult BMI cut-offs. Different levels of nutritional status and BMI of male youths of the Han nationality were compared among different areas. The mean BMI for the whole country was 20.6 in urban areas and 20.0 in rural areas. BMI increased from 20.1 among 18-year old youths to 20.5 among 20-year old youths. The prevalence of underweight among the male youths was 21.6%, while the prevalence of overweight and obesity were 4.6% and 0.6% respectively. For urban youths, the prevalence of underweight, overweight, and obesity were 21.0%, 6.8%, and 1.1% respectively, while these were, respectively, 21.9%, 3.3%, and 0.3% for rural youths. The nutritional status of the male youths in North-China was at the highest level (21.1) among the six areas, and the prevalence of underweight, overweight, and obesity were 14.3%, 9.1%, and 1.4% respectively. The highest prevalence of underweight was 29.8% in the North-West region, and the lowest prevalence of overweight was 2.2% in the South-Middle region, while the lowest prevalence of obesity was 0.2% in the South-West region. The nutritional status of the male youths was significantly different among different areas. Underweight was still prevalent in all male youth groups. Nonetheless, overweight was more prevalent among urban youths than among rural youths and was more prevalent in the North region than in the South region

A Design of Focal-plane Compensation of Aviation Imaging Equipment Based on MS5534C

AbstractThis paper proposes an auto-compensation method for defocusing distance caused by temperature and pressure in aviation imaging equipment. As the host computer, the TMS320F2812 is the core controller and the digital pressure sensor MS5534C from Intersema Company is used as slave computer. The controller acquires the output of the temperature and the pressure from the sensor through MCBSP interface. By the change of temperature and pressure which results in defocusing distance, the software is adopted to compensate the defocusing distance and thereby keeps the stabilization of focal plane in aviation imaging equipment. The design proposal and the software flow is shown in the paper, furthermore the new system has simple interface, small size and real-time function. With many flight tests, the defocusing distance after the compensation of temperature and pressure is far less than the half focal depth of the optical system and it is fully satisfied with the requirements of imaging

Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loop

Telephone transcription data can be very noisy due to speech recognition errors, disfluencies, etc. Not only that annotating such data is very challenging for the annotators, but also such data may have lots of annotation errors even after the annotation job is completed, resulting in a very poor model performance. In this paper, we present an active learning framework that leverages human in the loop learning to identify data samples from the annotated dataset for re-annotation that are more likely to contain annotation errors. In this way, we largely reduce the need for data re-annotation for the whole dataset. We conduct extensive experiments with our proposed approach for Named Entity Recognition and observe that by re-annotating only about 6% training instances out of the whole dataset, the F1 score for a certain entity type can be significantly improved by about 25%.Comment: The final version of this paper will be published in the Proceedings of the DaSH Workshop @ EMNLP 2022. This paper is accepted for presentation in both DaSH@EMNLP 2022 and HiLL@NIPS 202

A multidimensional and multiscale model for pressure analysis in a reservoir-pipe-valve system

Reservoir-pipe-valve (RPV) systems are widely used in many industrial processes. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operations such as rapid valve opening or closing. To investigate the pressure response, with particular interest in the pressure fluctuations in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled as a zero-dimensional virtual point, the pipe is modeled as a one-dimensional system using the MOC, and the valve is modeled using a threedimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve is obtained. The results show that the proposed model is in good agreement when compared with a high fidelity CFD model used to represent both large-scale and small-scale spaces. As expected, the proposed model is significantly more computationally efficient than the CFD model. This demonstrates the feasibility of analyzing complex RPV systems within an affordable computational time

The fabrication of an eccentric three-core fiber and its application as a twist sensor

The fabrication and application for twist sensing of an eccentric three-core fiber were demonstrated. The fiber was made by stack-and-draw technique, in which silica rods and core canes were put in a tube and drawn on a fiber drawing tower. Three cores formed a Mach-Zehnder interferometer, where the lights transmitted in the three cores interfered with each other, resulted in the formation of envelopes on spectrum. Because two of the cores were off axis, phase differences among the cores varied with twist due to different stretches on each core, which caused shift of the spectral envelopes of the interference signal. Wide range twist measurement can be realized with relatively high sensitivity by tracking lower dips of the envelopes. Experimental results revealed that the dips shift quadratically with twist angle, which means that the sensitivity increases with twist. The compensation of temperature influence was also implemented by inscribing a Bragg grating on one of the cores with femtosecond laser. Because the fiber can be mass-produced, it is suitable for twist sensing in practical application for its low cost