A non-dispersive infrared sensor for real-time detection of cyanogen chloride

Cyanogen chloride, as a systemic toxic agent, can cause death rapidly. In this paper, a non-dispersive infrared sensor was designed for the infrared  absorption detection of cyanogen chloride at 800 cm−1. The roughness of the internal coating material was analyzed by experiments, and the gold-  plated gas chamber was selected. The light path propagation of different cross-section gas chambers was simulated, and the circular section gas  chamber was selected to increase the infrared detector signal. The effect of flow rate on voltage was studied. The standard curve between voltage and  concentration was obtained under the optimal condition of 0.4 L min−1. The maximum response time was 19 s, and RSD was less than 2%. The  interference experiment results showed that common gases entering the gas chamber do not cause interference. The non-dispersive infrared sensor for  cyanogen chloride has good stability and detects cyanogen chloride in real-time

Manipulating refractive index, homogeneity and spectroscopy of Yb3+^{3+}-doped silica-core glass towards high-power large mode area photonic crystal fiber lasers

Output power scaling of single mode large mode area (LMA) photonic crystal fiber (PCF) amplifiers urgently requires the low refractive index of Yb³⁺-doped silica glasses whilst maintaining high optical homogeneity. In this paper, we report on a promising alternative Yb³⁺/Al³⁺/F¯/P⁵⁺-co-doped silica core-glass (YAFP), which is prepared by modified sol-gel method developed by our group and highly suitable for fabricating high power LMA PCF amplifiers. By controlling the doping combinations of Al³⁺/F¯/P⁵⁺ in Yb³⁺- doped silica glass,it not only ensures low refractive index (RI) but also maintains the excellent optical homogeneity and spectroscopic properties of Yb³⁺. The spectroscopic properties of Yb³⁺ ions have not deteriorated by the co-doping of F¯ and P⁵⁺ in YAFP glass compared with that of Yb³⁺/Al³⁺ co-doped silica glass. A large-size (⌀5 mm × 90 mm) YAFP silica-core glass rod with low average RI difference of 2.6 × 10¯⁴ (with respect to pure silica glass), and low radial and axial RI fluctuations of ~2 × 10¯⁴, was prepared. A LMA PCF with 50 μm core diameter was obtained by stack-capillary-draw techniques using YAFP core glass. Its core NA is 0.027. An average amplified power of 97 W peaking at 1030 nm and light-light efficiency of 54% are achieved from a 6.5 m long PCF in the pulse amplification laser experiment. Meanwhile, quasi-single-mode transmission is obtained with laser beam quality factor M² of 1.4

Muon beamtest results of high-density glass scintillator tiles

To achieve the physics goal of precisely measure the Higgs, Z, W bosons and the top quark, future electron-positron colliders require that their detector system has excellent jet energy resolution. One feasible technical option is the high granular calorimetery based on the particle flow algorithm (PFA). A new high-granularity hadronic calorimeter with glass scintillator tiles (GSHCAL) has been proposed, which focus on the significant improvement of hadronic energy resolution with a notable increase of the energy sampling fraction by using high-density glass scintillator tiles. The minimum ionizing particle (MIP) response of a glass scintillator tile is crucial to the hadronic calorimeter, so a dedicated beamtest setup was developed for testing the first batch of large-size glass scintillators. The maximum MIP response of the first batch of glass scintillator tiles can reach up to 107 p.e./MIP, which essentially meets the design requirements of the CEPC GSHCAL. An optical simulation model of a single glass scintillator tile has been established, and the simulation results are consistent with the beamtest results

Multi-Level Cycle-Consistent Adversarial Networks with Attention Mechanism for Face Sketch-Photo Synthesis

The synthesis between face sketches and face photos has important application values in law enforcement and digital entertainment. In cases of a lack of paired sketch-photo data, this paper proposes an unsupervised model to solve the problems of missing key facial details and a lack of realism in the synthesized images of existing methods. The model is built on the CycleGAN architecture. To retain more semantic information in the target domain, a multi-scale feature extraction module is inserted before the generator. In addition, the convolutional block attention module is introduced into the generator to enhance the ability of the model to extract important feature information. Via CBAM, the model improves the quality of the converted image and reduces the artifacts caused by image background interference. Next, in order to preserve more identity information in the generated photo, this paper constructs the multi-level cycle consistency loss function. Qualitative experiments on CUFS and CUFSF public datasets show that the facial details and edge structures synthesized by our model are clearer and more realistic. Meanwhile the performance indexes of structural similarity and peak signal-to-noise ratio in quantitative experiments are also significantly improved compared with other methods

Understanding the Professional Practice of Teachers of Chinese as an Additional Language through the Lens of Teacher Agency

Teacher agency plays a key role in sustaining the professional practice of language teachers, including teachers of Chinese as an additional language (CAL), to ensure sustainable multilingualism in universities. This paper reports on an exploratory study that examined five CAL teachers’ experiences of using teaching materials in a leading Belarussian university. Drawing on theorization about teacher agency, the analysis of the participants’ experiences helped to reveal the manifestations of teacher agency in their engagement with teaching materials in their teaching, which emerged from interactions between individual aspirations and contextual conditions. In particular, the findings highlight that three factors, namely teachers’ beliefs, teacher identity, and relationships within their community, play significant roles in mediating the participants’ exercise of agency in using teaching materials. The findings not only contribute to the conceptualization of teacher agency, but suggest that pedagogical content knowledge (PCK) and materials development of CAL teachers should be emphasized in supporting effective teaching, so that they can achieve sustainable professional practice to ensure sustainable multilingualism in universities

Understanding the Professional Practice of Teachers of Chinese as an Additional Language through the Lens of Teacher Agency

Teacher agency plays a key role in sustaining the professional practice of language teachers, including teachers of Chinese as an additional language (CAL), to ensure sustainable multilingualism in universities. This paper reports on an exploratory study that examined five CAL teachers’ experiences of using teaching materials in a leading Belarussian university. Drawing on theorization about teacher agency, the analysis of the participants’ experiences helped to reveal the manifestations of teacher agency in their engagement with teaching materials in their teaching, which emerged from interactions between individual aspirations and contextual conditions. In particular, the findings highlight that three factors, namely teachers’ beliefs, teacher identity, and relationships within their community, play significant roles in mediating the participants’ exercise of agency in using teaching materials. The findings not only contribute to the conceptualization of teacher agency, but suggest that pedagogical content knowledge (PCK) and materials development of CAL teachers should be emphasized in supporting effective teaching, so that they can achieve sustainable professional practice to ensure sustainable multilingualism in universities.</jats:p

Joint Cross-Consistency Learning and Multi-Feature Fusion for Person Re-Identification

To solve the problem of inadequate feature extraction by the model due to factors such as occlusion and illumination in person re-identification tasks, this paper proposed a model with a joint cross-consistency learning and multi-feature fusion person re-identification. The attention mechanism and the mixed pooling module were first embedded in the residual network so that the model adaptively focuses on the more valid information in the person images. Secondly, the dataset was randomly divided into two categories according to the camera perspective, and a feature classifier was trained for the two types of datasets respectively. Then, two classifiers with specific knowledge were used to guide the model to extract features unrelated to the camera perspective for the two types of datasets so that the obtained image features were endowed with domain invariance by the model, and the differences in the perspective, attitude, background, and other related information of different images were alleviated. Then, the multi-level features were fused through the feature pyramid to concern the more critical information of the image. Finally, a combination of Cosine Softmax loss, triplet loss, and cluster center loss was proposed to train the model to address the differences of multiple losses in the optimization space. The first accuracy of the proposed model reached 95.9% and 89.7% on the datasets Market-1501 and DukeMTMC-reID, respectively. The results indicated that the proposed model has good feature extraction capability