Microfiber-based polarization beam splitter and its application for passively mode-locked all-fiber laser

Nonlinear polarization evolution based on polarization beam splitter (PBS) is a classical technique for passive mode-locking of fiber lasers. Different from commonly used bulky PBS, in this paper all-fiber PBSs composed of two parallel coupled microfibers have been proposed and fabricated under the condition of appropriate microfiber diameter and coupling length. Using our fabricated microfiber PBSs, passively mode-locked all-fiber lasers have also been demonstrated. The results indicate that the microfiber-based PBS has advantages of simple fabrication, compact size, and most importantly, variable polarization extinction ratio and operation bandwidth. The all-fiber mode-locked lasers with the microfiber PBSs generating stable pulses at both 1.0 μm and 1.5 μm wavelength bands have comparable performance with their counterparts based on bulky PBSs. It may be a step towards true all-fiber mode-locked laser and other all-fiber systems

InAlN/GaN MOSHEMTs with high drain current of 2.3 A/mm high on/off ratio of 1012 and low SS of 64 mV/dec enabled by atomic-layer-epitaxial MgCaO as gate dielectric

Summary form only given. Recently, GaN-based high-electron-mobility-transistor (HEMT) has demonstrated its promise in high frequency, high power and low noise electronic devices. The lattice matched InAlN/GaN HEMT structure provides a higher 2D electron density than AlGaN/GaN due to a larger bandgap offset and minimized short-channel-effects due to its thinner barrier. However, because of its several-nm thin barrier, those devices usually suffer from high gate leakage and interface trap issues, the device off-state performance is degraded and thereby the off-state breakdown voltage is decreased. Therefore, finding a good method to reduce the gate leakage and interface trap density is of great importance to improve the device off-state performance. In this study, we use atomic layer epitaxial MgCaO as gate dielectric to fabricate sub-100nm InAlN/GaN MOSHEMTs with significantly improved maximum drain current, current on/off ratio and low subthreshold swing.Chemistry and Chemical Biolog

Epitaxial Growth of MgxCa1–xO on GaN by Atomic Layer Deposition

We demonstrate for the first time that a singlecrystalline epitaxial MgxCa1−xO film can be deposited on gallium nitride (GaN) by atomic layer deposition (ALD). By adjusting the ratio between the amounts of Mg and Ca in the film, a lattice matched MgxCa1−xO/GaN(0001) interface can be achieved with low interfacial defect density. High-resolution X-ray diffraction (XRD) shows that the lattice parameter of this ternary oxide nearly obeys Vegard’s law. An atomically sharp interface from cross-sectional transmission electron microscopy (TEM) confirmed the high quality of the epitaxy.High-temperature capacitance−voltage characterization showed that the film with composition Mg0.25Ca0.75O has the lowest interfacial defect density. With this optimal oxide composition, a Mg0.25Ca0.75O/AlGaN/GaN metal−oxide −semiconductor high-electron-mobility (MOS-HEMT) device was fabricated. An ultrahigh on/off ratio of 1012 and a near ideal SS of 62 mV/dec were achieved with this device.Chemistry and Chemical Biolog

Modelling the Mimic Defence Technology for Multimedia Cloud Servers

A current research trend is to combine multimedia data with artificial intelligence and process them on cloud servers. In this context, ensuring the security of multimedia cloud servers is critical, and the cyber mimic defence (CMD) technology is a promising approach to this end. CMD, which is an innovative active defence technology developed in China, can be applied in many scenarios. However, although the mathematical model is a key component of CMD, a universally acceptable mathematical model for theoretical CMD has not been established yet. In this work, the attack problems and modelling difficulties were extensively examined, and a comprehensive modelling theory and concepts were clarified. By decoupling the model from the input and output of the specific system scene, the modelling difficulties were effectively avoided, and the mathematical expression of the CMD mechanism was enhanced. Furthermore, the process characteristics of the attack behaviour were identified by using a specific mathematical mapping method. Finally, based on the decomposition problem of large prime factors and convolution operations, an intuitive and exclusive CMD mathematical model was proposed. The proposed model could clearly express the CMD mechanism and transform the problems of attack and defence in the CMD domain into corresponding mathematical problems. These aspects were considered to qualitatively assess the CMD security, and it was noted that a high level of security can be realized. Furthermore, the overhead of CMD was analyzed. Moreover, the proposed model can be directly programmed

Domain Adversarial Network for Cross-Domain Emotion Recognition in Conversation

Emotion Recognition in Conversation (ERC) aims to recognize the emotion for each utterance in a conversation automatically. Due to the difficulty of collecting and labeling, this task lacks the dataset corpora available on a large scale. This increases the difficulty of finishing the supervised training required by large-scale neural networks. Introducing the large-scale generative conversational dataset can assist with modeling dialogue. However, the spatial distribution of feature vectors in the source and target domains is inconsistent after introducing the external dataset. To alleviate the problem, we propose a Domain Adversarial Network for Cross-Domain Emotion Recognition in Conversation (DAN-CDERC) model, consisting of domain adversarial and emotion recognition models. The domain adversarial model consists of the encoders, a generator and a domain discriminator. First, the encoders and generator learn contextual features from a large-scale source dataset. The discriminator performs domain adaptation by discriminating the domain to make the feature space of the source and target domain consistent, so as to obtain domain invariant features. Then DAN-CDERC transfers the learned domain invariant dialogue context knowledge from the domain adversarial model to the emotion recognition model to assist in modeling the dialogue context. Due to the use of a domain adversarial network, DAN-CDERC obtains dialogue-level contextual information that is domain invariant, thereby reducing the negative impact of inconsistency in domain space. Empirical studies illustrate that the proposed model outperforms the baseline models on three benchmark emotion recognition datasets

Mimic Encryption Box for Network Multimedia Data Security

With the rapid development of the Internet, the security of network multimedia data has attracted increasingly more attention. The moving target defense (MTD) and cyber mimic defense (CMD) approaches provide a new way to solve this problem. To enhance the security of network multimedia data, this paper proposes a mimic encryption box for network multimedia data security. The mimic encryption box can directly access the network where the multimedia device is located, automatically complete the negotiation, provide safe and convenient encryption services, and effectively prevent network attacks. According to the principles of dynamization, diversification, and randomization, the mimic encryption box uses a reconfigurable encryption algorithm to encrypt network data and uses IP address hopping, port number hopping, protocol camouflage, and network channel change to increase the attack threshold. Second, the mimic encryption box has a built-in pseudorandom number generator and key management system, which can generate an initial random key and update the key with the hash value of the data packet to achieve “one packet, one key.” Finally, through the cooperation of the ARM and the FPGA, an access control list can be used to filter illegal data and monitor the working status of the system in real time. If an abnormality is found, the feedback reconstruction mechanism is used to “clean” the FPGA to make it work normally again. The experimental results and analysis show that the mimic encryption box designed in this paper has high network encryption performance and can effectively prevent data leakage. At the same time, it provides a mimic security defense mechanism at multiple levels, which can effectively resist a variety of network attacks and has high security

Comparative Genomic Characterization of Actinobacillus pleuropneumoniae▿ †

The Gram-negative bacterium Actinobacillus pleuropneumoniae is the etiologic agent of porcine contagious pleuropneumoniae, a lethal respiratory infectious disease causing great economic losses in the swine industry worldwide. In order to better interpret the genetic background of serotypic diversity, nine genomes of A. pleuropneumoniae reference strains of serovars 1, 2, 4, 6, 9, 10, 11, 12, and 13 were sequenced by using rapid high-throughput approach. Based on 12 genomes of corresponding serovar reference strains including three publicly available complete genomes (serovars 3, 5b, and 7) of this bacterium, we performed a comprehensive analysis of comparative genomics and first reported a global genomic characterization for this pathogen. Clustering of 26,012 predicted protein-coding genes showed that the pan genome of A. pleuropneumoniae consists of 3,303 gene clusters, which contain 1,709 core genome genes, 822 distributed genes, and 772 strain-specific genes. The genome components involved in the biogenesis of capsular polysaccharide and lipopolysaccharide O antigen relative to serovar diversity were compared, and their genetic diversity was depicted. Our findings shed more light on genomic features associated with serovar diversity of A. pleuropneumoniae and provide broader insight into both pathogenesis research and clinical/epidemiological application against the severe disease caused by this swine pathogen