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ObjectiveAiming at the problem of the narrow dynamic range of current optical fiber displacement sensors, a balloon-like long-period fiber grating (LPFG) displacement sensor with a simple structure and easy preparation method is designed. MethodsBased on simulation and optimization by RSOFT software, the measurement range is determined by the balloon-like optical fiber under different curvatures. A multimode fiber balloon-like LPFG (MMF-BLPFG) formed by periodically embedding multimode fiber (MMF) into single-mode fiber (SMF) provides a reference peak for measuring the displacement. Using a precise continuous cutting device as the experimental basis, test samples consistent with the simulation results are prepared for testing. ResultsThe maximum displacement measurement range of 36 mm is achieved by measuring the drift of two resonance peaks. ConclusionsThe proposed sensor has good application potential in large-scale measurement scenarios such as the stability measurement and continuous monitoring of the underwater drainage space piping systems of ships.

Liquid hydrogen is one of the high-quality energy carriers, but a large leak of liquid hydrogen can pose significant safety risks. Understanding its diffusion law after accidental leakage is an important issue for the safe utilization of hydrogen energy. In this paper, a series of open-space large-volume liquid hydrogen release experiments are performed to observe the evolution of visible clouds during the release, and an array of hydrogen concentration sensors is set up to monitor the fluctuation in hydrogen concentration at different locations. Based on the experimental conditions, the diffusion of hydrogen clouds in the atmosphere under different release hole diameters and different ground materials is compared. The results show that with the release of liquid hydrogen, the white visible cloud formed by air condensation or solidification is generated rapidly and spread widely, and the visible cloud is most obvious near the ground. With the termination of liquid hydrogen release, solid air is deposited on the ground, and the visible clouds gradually shrink from the far field to the release source. Hydrogen concentration fluctuations in the far field in the case of the cobblestone ground are more dependent on spontaneous diffusion by the hydrogen concentration gradient. In addition, compared with the concrete ground, the cobblestone ground has greater resistance to liquid hydrogen extension; the diffusion of hydrogen clouds to the far field lags. The rapid increase stage of hydrogen concentration at N8 in Test 7 lags about 3 s behind N12 in Test 6, N3 lags about 7.5 s behind N1, and N16 lags about 8.25 s behind N14. The near-source space is prone to high-concentration hydrogen clouds. The duration of the high-concentration hydrogen cloud at N12 is about 15 s, which is twice as long as the duration at N8, increasing the safety risk of the near-source space.

Background: 22q11.2 deletion syndrome (22q11.2DS) is a disorder caused when a small part of chromosome 22 is missing. Diagnosis is currently established by the identification of a heterozygous deletion at chromosome 22q11.2 through chromosomal microarray analysis or other genomic analyses. However, more accurate identification of the breakpoint contributes to a clearer understanding of the 22q11.2 deletion syndrome.Methods: In this study, we present a feasible nanopore sequencing method of 22q11.2 deletion. This DNA enrichment method—region-specific amplification (RSA)—is able to analyze the 22q11.2 deletion by specific amplification of an approximately 1-Mb region where the breakpoint might exist. RSA introduces universal primers into the target region DNA by a Y-shaped adaptor ligation and a single primer extension. The enriched products, completed by amplification with universal primers, are then processed by standard ONT ligation sequencing protocols.Results: RSA is able to deliver adequate coverage (>98%) and comparable long reads (average length >1 Kb) throughout the 22q11.2 region. The long nanopore sequencing reads, derived from three umbilical cord blood samples, have facilitated the identification of the breakpoint of the 22q11.2 deletion, as well as by Sanger sequencing.Conclusion: The Oxford Nanopore MinION sequencer can use RSA to sequence the target region 22q11.2; this method could also be used for other hard-to-sequence parts of the genome.

Gesture recognition is widely used in the field of sensing.There are three kinds of gesture recognition methods based on computer vision,depth sensor and motion sensor.The recognition based on motion sensor has the advantages of less input data,high speed,and direct acquisition of hand 3D information,which has gradually become a research hotspot.Traditional gesture recognition based on motion sensor can be considered as a pattern recognition problem essentially and its accuracy depends heavily on feature data sets extracted from prior experience.Different from traditional pattern recognition methods,deep learning can greatly reduce the workload of artificial heuristic feature extraction.To solve the problem of traditional pattern recognition,this paper proposes a real-time multi-dimensional features recognition method based on Long Short-Term Memory(LSTM)and the performance of the method is verified by sufficient experiment.The method defines a gesture library consisting of five basic gestures and seven complex gestures at first.Based on the kinematic features of hand posture,the angle features and displacement features are extracted and then the frequency domain features of sensor data are extracted by short-time Fourier transform(SFTF).Then,three features are inputted into deep neural network LSTM for training,so the collected gestures are classified and recognized.At the same time,in order to verify the effectiveness of the proposed method,the gesture data of six volunteers are collected as the experimental data set by self-designed hand-held experience stick.The experimental results show that the accuracy of the recognition method proposed in this paper achieves 94.38% for basic and complex gestures,and the recognition accuracy is improved by nearly 2% compared with the traditional support vector machine,K-nearest neighbor method and fully connected neural network.

Temperature exerts a profound influence on the fidelity of photosensors, making the attainment of reliable temperature compensation a formidable task within engineering realms. This research delves into the intricacies of photosensors used in high-precision accelerometers, proposing an innovative, high-precision, adaptive, closed-loop compensation mechanism. Our design stands in stark contrast to traditional open-loop models, demonstrating superior performance by achieving a remarkable reduction in compensation error—nearly 98%. This advancement in consistency and precision marks a significant leap forward for the application of high-precision photosensors in engineering contexts. [ABSTRACT FROM AUTHOR]

The effective detection and tracking of low, small and slow targets is a current hot issue in the radar field. The paper is a sequel to radar weak target detection based on RFT and AMF fusion focus, and concentrates on the tracking of typical UAVs by pulse Doppler radar. The implementations of tracking algorithm mainly include: first, the preprocessing of the plots centroid processing and the multi-frame acceleration estimation has been applied. Then the labeled multi-Bernoulli (LMB) smoother is used for the multi-target tracking. Finally, the final trajectories of targets are output after trajectory continuity judgment and effective trajectory extraction. The LMB smoother can output the smoothed trajectories of targets, therefore, improving the estimation accuracy of distance and velocity. Trajectory continuity judgment and effective track extraction can effectively overcome the problems of breaking trajectory caused by velocity jitter and false trajectory caused by velocity ambiguity. The comprehensive score rate to process multiple test data is 96.67%, which verifies the effectiveness and robustness of the proposed tracking algorithm.

Oxidative stress and inflammation are important and critical mediators in the development and progression of chronic kidney disease (CKD) and its complications. Shenkang injection (SKI) has been widely used to treat patients with CKD. Although the anti-oxidative and anti-inflammatory activity was involved in SKI against CKD, its bioactive components and underlying mechanism remain enigmatic. A rat model of adenine-induced chronic renal failure (CRF) is associated with, and largely driven by, oxidative stress and inflammation. Hence, we identified the anti-oxidative and anti-inflammatory components of SKI and further revealed their underlying mechanism in the adenine-induced CRF rats. Compared with control rats, the levels of creatinine, urea, uric acid, total cholesterol, triglyceride, and low-density lipoprotein cholesterol in serum were significantly increased in the adenine-induced CRF rats. However, treatment with SKI and its three anthraquinones including chrysophanol, emodin, and rhein could reverse these aberrant changes. They could significantly inhibit pro-fibrotic protein expressions including collagen I, α-SMA, fibronectin, and vimentin in the kidney tissues of the adenine-induced CRF rats. Of note, SKI and rhein showed the stronger inhibitory effect on these pro-fibrotic protein expressions than chrysophanol and emodin. Furthermore, they could improve dysregulation of IƙB/NF-ƙB and Keap1/Nrf2 signaling pathways. Chrysophanol and emodin showed the stronger inhibitory effect on the NF-κB p65 protein expression than SKI and rhein. Rhein showed the strongest inhibitory effect on p65 downstream target gene products including NAD(P)H oxidase subunits (p47phox, p67phox, and gp91phox) and COX-2, MCP-1, iNOS, and 12-LO in the kidney tissues. However, SKI and rhein showed the stronger inhibitory effect on the significantly downregulated anti-inflammatory and anti-oxidative protein expression nuclear Nrf2 and its target gene products including HO-1, catalase, GCLC, and NQO1 in the Keap1/Nrf2 signaling pathway than chrysophanol and emodin. This study first demonstrated that SKI and its major components protected against renal fibrosis by inhibiting oxidative stress and inflammation via simultaneous targeting IƙB/NF-ƙB and Keap1/Nrf2 signaling pathways, which illuminated the potential molecular mechanism of anti-oxidative and anti-inflammatory effects of SKI.

Abstract Background Application of chromosomal microarray analysis (CMA) to investigate the genetic characteristics of fetal growth restriction (FGR) without ultrasonic structural anomalies at 18–32 weeks. Methods This study includes singleton fetuses with the estimated fetal weight (EFW) using the formula of Hadlock C below the 10th percentile for gestational age. FGRs without structural anomalies were selected, and the ones at high risk of noninvasive prenatal testing for trisomy 13, 18 and 21 would be excluded. The cases were divided into two groups: early-onset group (

To recycle the returned alloy effectively, effects of returns proportion on alloy composition, microstructure and compression properties of superalloy GH4169 were studied by means of scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and thermal-mechanical simulator. The results show that returns addition has no significant effect on the main alloy elements content and the principle precipitates, but increases the volume fraction of Al2O3 inclusions, resulting in the increase of oxygen level of GH4169 alloy. Returns addition does not change the elastic and plastic deformation process at room temperature or at 1,150 °C, but high returns proportion GH4169 alloy shows improved compression strength and yield strength. The alloy with 100% returns shows a maximum compression strength 1,153.45 MPa at room temperature, while the alloy with 80% returns has a maximum value 69.3 MPa at 1,150 °C. Returns addition increases fluctuation range and reduces the stability of yield strength and compression strength of GH4169 alloy at room temperature. It is noted that the volume fraction and the size of Al2O3, and the fraction of Laves phase reach their maximum values in the GH4169 alloy with 60% returns, which exhibits maximum yield strength of 516.65 MPa at room temperature and 62.17 MPa at 1,150 °C.