Superconducting properties of novel BiSe2_{2}-based layered LaO1−x_{1-x}Fx_{x}BiSe2_{2} single crystals

F-doped LaOBiSe$_{2}$ superconducting single crystals with typical size of 2$\times$4$\times$0.2 mm$^{3}$ are successfully grown by flux method and the superconducting properties are studied. Both the superconducting transition temperature and the shielding volume fraction are effectively improved with fluorine doping. The LaO$_{0.48}$F$_{0.52}$BiSe$_{1.93}$ sample exhibits zero-resistivity at 3.7 K, which is higher than that of the LaO$_{0.5}$F$_{0.5}$BiSe$_{2}$ polycrystalline sample (2.4K). Bulk superconductivity is confirmed by a clear specific-heat jump at the associated temperature. The samples exhibit strong anisotropy and the anisotropy parameter is about 30, as estimated by the upper critical field and effective mass modelComment: 5 pages, 5 figures, 2 tables, accepted for publication in Europhysics Lette

Optimal Vibration Control for Half-Car Suspension on In-Vehicle Networks in Delta Domain

The paper explores the optimal vibration control design problem for a half-car suspension working on in-vehicle networks in delta domain. First, the original suspension system with ECU-actuator delay and sensor-ECU delay is modeled. By using delta operators, the original system is transformed into an associated sampled-data system with time delays in delta domain. After model transformation, the sampled-data system equation is reduced to one without actuator delays and convenient to calculate the states with nonintegral time delay. Therefore, the sampled-data optimal vibration control law can be easily obtained deriving from a Riccati equation and a Stein equation of delta domain. The feedforward control term and the control memory terms designed in the control law ensure the compensation for the effects produced by disturbance and actuator delay, respectively. Moreover, an observer is constructed to implement the physical realizability of the feedforward term and solve the immeasurability problem of some state variables. A half-car suspension model with delays is applied to simulate the responses through the designed controller. Simulation results illustrate the effectiveness of the proposed controller and the simplicity of the designing approach

Identifying enablers and barriers to the implementation of the green infrastructure for urban flood management: a comparative analysis of the UK and China

Climate change and urbanization are increasing the urban flood risk, which can cause adverse on socio-economic and environmental impacts. Green Infrastructure (GI) can reduce stormwater runoff and offer multiple benefits that have been initiated in the United Kingdom (UK) and China, namely Sustainable Urban Drainage Systems (SUDS) and Sponge Cities Program (SCP) respectively. Currently, the implementation of GI is restricted to small spatial (site specific) scale and facing several constraints such as financial investment and governance, that limited its fuller functions and potential. This study aims to identify the barriers and enablers for the adoption of GI by investigating SUDS and SCP in the UK and China, through twelve in-depth semi-structured interviews with stakeholders. Our results found that multiple benefits of the SUDS and SCP were identified, as the main enablers in both countries with reducing the stormwater runoff and alleviating peak discharge in the drainage system, also contributing to social well-being and climate adaptations. Some barriers found the current practices are facing challenges from financial, biophysical and socio-political circumstances in both cases. We conclude that it is beneficial to learn the comparative findings and experiences from both countries, which contributes to stakeholders for improving current GI practices, in prior to achieve more sustainable long-term deliverables

Context-aware Coherent Speaking Style Prediction with Hierarchical Transformers for Audiobook Speech Synthesis

Recent advances in text-to-speech have significantly improved the expressiveness of synthesized speech. However, it is still challenging to generate speech with contextually appropriate and coherent speaking style for multi-sentence text in audiobooks. In this paper, we propose a context-aware coherent speaking style prediction method for audiobook speech synthesis. To predict the style embedding of the current utterance, a hierarchical transformer-based context-aware style predictor with a mixture attention mask is designed, considering both text-side context information and speech-side style information of previous speeches. Based on this, we can generate long-form speech with coherent style and prosody sentence by sentence. Objective and subjective evaluations on a Mandarin audiobook dataset demonstrate that our proposed model can generate speech with more expressive and coherent speaking style than baselines, for both single-sentence and multi-sentence test.Comment: Accepted by ICASSP 202

Neutrino Masses, Lepton Flavor Mixing and Leptogenesis in the Minimal Seesaw Model

We present a review of neutrino phenomenology in the minimal seesaw model (MSM), an economical and intriguing extension of the Standard Model with only two heavy right-handed Majorana neutrinos. Given current neutrino oscillation data, the MSM can predict the neutrino mass spectrum and constrain the effective masses of the tritium beta decay and the neutrinoless double-beta decay. We outline five distinct schemes to parameterize the neutrino Yukawa-coupling matrix of the MSM. The lepton flavor mixing and baryogenesis via leptogenesis are investigated in some detail by taking account of possible texture zeros of the Dirac neutrino mass matrix. We derive an upper bound on the CP-violating asymmetry in the decay of the lighter right-handed Majorana neutrino. The effects of the renormalization-group evolution on the neutrino mixing parameters are analyzed, and the correlation between the CP-violating phenomena at low and high energies is highlighted. We show that the observed matter-antimatter asymmetry of the Universe can naturally be interpreted through the resonant leptogenesis mechanism at the TeV scale. The lepton-flavor-violating rare decays, such as $\mu \to e + \gamma$, are also discussed in the supersymmetric extension of the MSM.Comment: 50 pages, 22 EPS figures, macro file ws-ijmpe.cls included, accepted for publication in Int. J. Mod. Phys.

A comprehensive immunoreceptor phosphotyrosine-based signaling network revealed by reciprocal protein-peptide array screening

Cells of the immune system communicate with their environment through immunoreceptors. These receptors often harbor intracellular tyrosine residues, which, when phosphorylated upon receptor activation, serve as docking sites to recruit downstream signaling proteins containing the Src Homology 2 (SH2) domain. A systematic investigation of interactions between the SH2 domain and the immunoreceptor tyrosine-based regulatory motifs (ITRM), including inhibitory (ITIM), activating (ITAM), or switching (ITSM) motifs, is critical for understanding cellular signal transduction and immune function. Using the B cell inhibitory receptor CD22 as an example, we developed an approach that combines reciprocal or bidirectional phosphopeptide and SH2 domain array screens with in-solution binding assays to identify a comprehensive SH2-CD22 interaction network. Extending this approach to 194 human ITRM sequences and 78 SH2 domains led to the identification of a high-confidence immunoreceptor interactome containing 1137 binary interactions. Besides recapitulating many previously reported interactions, our study uncovered numerous novel interactions. The resulting ITRM-SH2 interactome not only helped to fill many gaps in the immune signaling network, it also allowed us to associate different SH2 domains to distinct immune functions. Detailed analysis of the NK cell ITRM-mediated interactions led to the identification of a network nucleated by the Vav3 and Fyn SH2 domains. We showed further that these SH2 domains have distinct functions in cytotoxicity. The bidirectional protein-peptide array approach described herein may be applied to the numerous other peptide-binding modules to identify potential protein-protein interactions in a systematic and reliable manner

Towards Spontaneous Style Modeling with Semi-supervised Pre-training for Conversational Text-to-Speech Synthesis

The spontaneous behavior that often occurs in conversations makes speech more human-like compared to reading-style. However, synthesizing spontaneous-style speech is challenging due to the lack of high-quality spontaneous datasets and the high cost of labeling spontaneous behavior. In this paper, we propose a semi-supervised pre-training method to increase the amount of spontaneous-style speech and spontaneous behavioral labels. In the process of semi-supervised learning, both text and speech information are considered for detecting spontaneous behaviors labels in speech. Moreover, a linguistic-aware encoder is used to model the relationship between each sentence in the conversation. Experimental results indicate that our proposed method achieves superior expressive speech synthesis performance with the ability to model spontaneous behavior in spontaneous-style speech and predict reasonable spontaneous behavior from text.Comment: Accepted by INTERSPEECH 202