Rabies, as one of the most threatening zoonoses in world, causes a fatal central nervous system (CNS) disease. So far, vaccination with rabies vaccines has been effective measure to prevent and control this At present, inactivated are widely used humans domestic animals. However, humoral immune responses induced by relatively low multiple shots required achieve protective immunity. Supplementation an adjuvant is practical way improve immunogenicity vaccines. In study, we found that...

For a class of high-order nonlinear multi-agent systems with input hysteresis, an adaptive consensus output-feedback quantized control scheme full state constraints is investigated. The major properties the proposed are: 1) According to different hysteresis characteristics each agent in system, quantization inverse compensator designed eliminate influence on system while ensuring that signal maintains desired value. 2) A barrier Lyapunov function introduced for first time hysteretic system....

Training speaker-discriminative and robust speaker verification systems without labels is still challenging worthwhile to explore. In this study, we propose an effective self-supervised learning framework a novel regularization strategy facilitate representation learning. Different from contrastive learning-based methods, the proposed (SSReg) focuses exclusively on similarity between latent representations of positive data pairs. We also explore effectiveness alternative online augmentation...

The safety of autonomous driving systems, particularly self-driving vehicles, remains paramount concern. These systems exhibit affine nonlinear dynamics and face the challenge executing predefined control tasks while adhering to state input constraints mitigate risks. However, achieving within framework constraints, such as collision avoidance maintaining system states secure boundaries, presents challenges due limited options. In this study, we introduce a novel approach address concerns by...

Chimeric antigen receptor (CAR) T cell therapy has emerged as a pioneering cancer treatment, achieving unprecedented success in treating certain hematological malignancies such lymphomas and leukemias. However, more patients receive CAR-T therapies, treatment-associated secondary primary are increasingly being reported partly due to unexpected CAR transgene insertion, raising serious safety concerns. To address this issue, we describe here nonviral, non-integrating approach generate...

Automatic speech recognition (ASR) systems often make unrecoverable errors due to subsystem pruning (acoustic, language and pronunciation models); for example words acoustics using short-term context, prior rescoring with long-term context based on linguistics. In this work we model ASR as a phrase-based noisy transformation channel propose an error correction system that can learn from the aggregate of all independent modules constituting attempt invert those. The proposed exploit neural...

Behavioral annotation using signal processing and machine learning is highly dependent on training data manual annotations of behavioral labels. Previous studies have shown that speech information encodes significant be used in a variety automated behavior recognition tasks. However, extracting from still difficult task due to the sparseness coupled with complex, high-dimensionality speech, complex multiple streams it encodes. In this work we exploit slow varying properties human behavior....

Abstract Bordetella bronchiseptica ( Bb ) is recognized as a leading cause of respiratory diseases in dogs and cats. However, epidemiological data on cats China are still limited, there no commercially available vaccine. Live vaccines containing that widely used abroad generally effective but can establish latency potentially reactivate to illness some immunodeficient vaccinated recipients, raising safety concerns. In this study, 34 canine-derived two feline-derived strains were isolated...

The primary characteristic of robust speaker representations is that they are invariant to factors variability not related identity. Disentanglement one the techniques used improve robustness both intrinsic acquired during speech production (e.g., emotion, lexical content) and extrinsic signal capture channel, noise). in neural can be achieved either a supervised fashion with annotations nuisance (factors identity) or an unsupervised without labels removed. In case it important understand...

Vaccination is the most efficient method to prevent rabies. TLR4, a well-known immune sensor, plays critical role in initiating innate response.

In this work we analyze the importance of lexical and acoustic modalities in behavioral expression perception. We demonstrate that relates to amount therapy, hence communication training, a person received. It also exhibits some relationship gender. proceed provide an analysis on couple therapy data by splitting into clusters based gender or stage therapy. Our demonstrates significant difference between optimal modality weights per cluster stage. Given finding propose use communication-skill...

Training speaker-discriminative and robust speaker verification systems without labels is still challenging worthwhile to explore. In this study, we propose an effective self-supervised learning framework a novel regularization strategy facilitate representation learning. Different from contrastive learning-based methods, the proposed (SSReg) focuses exclusively on similarity between latent representations of positive data pairs. We also explore effectiveness alternative online augmentation...

Observational studies are based on accurate assessment of human state. A behavior recognition system that models interlocutors' state in real-time can significantly aid the mental health domain. However, from speech remains a challenging task since it is difficult to find generalizable and representative features because noisy high-dimensional data, especially when data limited annotated coarsely subjectively. Deep Neural Networks (DNN) have shown promise wide range machine learning tasks,...

End-to-end (E2E) spoken language understanding (SLU) is constrained by the cost of collecting speech-semantics pairs, especially when label domains change. Hence, we explore \textit{zero-shot} E2E SLU, which learns SLU without instead using only speech-text and text-semantics pairs. Previous work achieved zero-shot pseudolabeling all transcripts with a natural (NLU) model learned on corpora. However, this method requires to match, often mismatch due separate collections. Furthermore, entire...

Safety-critical control has received extensive attention in mobile robotic systems such as unmanned surface vehicles (USVs), whose main objective is to make the vessels accomplish their desired tasks while avoiding unsafe areas, also known obstacle avoidance control. In this paper, for a class of underactuated USV with collision requirements, neural quantized tracking algorithm based on barrier functions (CBFs) developed, which implemented by backstepping technique and can guarantee...

The safety of autonomous driving systems, particularly self-driving vehicles, remains paramount concern. These systems exhibit affine nonlinear dynamics and face the challenge executing predefined control tasks while adhering to state input constraints mitigate risks. However, achieving within framework constraints, such as collision avoidance maintaining system states secure boundaries, presents challenges due limited options. In this study, we introduce a novel approach address concerns by...