Investigating the features of risky driving behaviors on expressway diverge area based on conflict and modeling analysis.

Driving behaviors are important cause of expressway crash. In this study, method based on modified time-to-collision (MTTC) to identify risky driving behaviors on an expressway diverge area is proposed, thus investigating the impact of velocity and acceleration features of risky driving behavior. Firstly, MTTC is applied to judge whether the behavior is risky. Then, the relationships between velocity, acceleration and different driving behavior on the expressway diverge area were fit by binary logistic regression models (BLR) with L2 regularization and random forests (RF) models, and the models were interpreted by feature importance plots and partial dependency plots. The results show that the AUC metric of 4 RF models for 4 types of driving behaviors, namely, left lane change, right lane change, acceleration and deceleration, are 0.932, 0.845, 0.846 and 0.860 separately. The interpretation of models demonstrates that velocity and absolute value of acceleration greatly affect the risk of the driving behaviors. Different driving behaviors with a certain acceleration have a range of safety speed range. The range will get narrower with the growth of maximum absolute value of acceleration rate, and will be nearly non-exist when the acceleration is over 5 m/s2. In conclusion, this study provided a methodology to measure the risk of driving behaviors and establish a model to recognize of risky driving behaviors. The results can lay the foundation for making countermeasures to prevent risky driving behaviors by managing the vehicle speed.

One-Step Rapid and Sensitive ASFV p30 Antibody Detection via Nanoplasmonic Biosensors.

African swine fever (ASF) is one of the most serious transnational swine diseases in the world. The case fatality rate of susceptible pigs is up to 100%. Currently, no commercial vaccine is available, so the prevention and control of ASF mainly relies on early diagnosis and culling of infected pigs. As the ASF virus continues to evolve, develop, and diversify, nucleic acid testing becomes less efficient. Here, we developed a method for the rapid and direct optical measurement of African swine fever virus (ASFV) antibody in vitro. This one-step procedure requires nearly no sample preparation and involves p30 protein-specific label-free integration into standard 96-well plates. Using a nanoplasmonic biosensor with extraordinary optical transmission (EOT) effect, one-step sample addition, ASFV antibody was detected within 20 min. The positive antibody showed a satisfactory sensitivity and linear relationship in the dilution ratio of 1:100-1:16000. It was used for the detection of clinical serum samples with a coincidence rate of 96.6%. The measurement results can be automatically analyzed and displayed on a conventional microplate meter computer and connected device. Our detection method can be widely applied in point-of-care testing (POCT) of ASFV antibody in pig farms. IMPORTANCE African swine fever (ASF) is a serious transnational disease caused by the African swine fever virus (ASFV), which is highly contagious in wild boars and domestic pigs. There is currently no available vaccine for ASF; therefore, development efforts are a key priority as ASFV continues to evolve and diversify. The ASF antibody rapid detection platform comprising the nanoplasmonic biosensor with extraordinary optical transmission effect can greatly reduce the detection time and improve detection flux while maintaining detection sensitivity and specificity. The one-step sample addition can effectively avoid cross contamination of samples in the detection process. The detection method provides a solution for the rapid and accurate real-time monitoring of ASF in pig farms.

YWHAG inhibits influenza a virus replication by suppressing the release of viral M2 protein.

Influenza A virus (IAV) poses a serious threat to human life and property. The IAV matrix protein 2 (M2) is significant in viral budding. Increasing studies have proven the important roles of host factors in IAV replication. In this study, immunoprecipitation combined with mass spectrometry revealed that the host protein tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein gamma (YWHAG), which belongs to the 14-3-3 protein scaffold family, interacts with M2. Their interactions were further confirmed by co-immunoprecipitation (Co-IP), immunofluorescence, and confocal microscopy of virus-infected HeLa cells. Moreover, we constructed YWHAG-KO and YWHAG-overexpressing cells and found that YWHAG knockout significantly increased viral production, whereas its overexpression reduced the titer of virus progeny. Therefore, YWHAG is a negative regulatory factor during IAV infection. Further, YWHAG knockout or overexpression had no effect on the binding, entry, or viral RNA replication in the early stages of the virus life cycle. On the contrary, it impaired the release of virions at the plasma membrane as determined using transmission electron microscopy and suppressed the M2-mediated budding of the influenza virus. Importantly, the H158F mutation of YWHAG was found to affect interaction with M2 and its budding. Collectively, our work demonstrates that YWHAG is a novel cellular regulator that targets and mediates the interaction and release of M2.

Multimodal interaction enhanced representation learning for video emotion recognition.

Video emotion recognition aims to infer human emotional states from the audio, visual, and text modalities. Previous approaches are centered around designing sophisticated fusion mechanisms, but usually ignore the fact that text contains global semantic information, while speech and face video show more fine-grained temporal dynamics of emotion. From the perspective of cognitive sciences, the process of emotion expression, either through facial expression or speech, is implicitly regulated by high-level semantics. Inspired by this fact, we propose a multimodal interaction enhanced representation learning framework for emotion recognition from face video, where a semantic enhancement module is first designed to guide the audio/visual encoder using the semantic information from text, then the multimodal bottleneck Transformer is adopted to further reinforce the audio and visual representations by modeling the cross-modal dynamic interactions between the two feature sequences. Experimental results on two benchmark emotion databases indicate the superiority of our proposed method. With the semantic enhanced audio and visual features, it outperforms the state-of-the-art models which fuse the features or decisions from the audio, visual and text modalities.

Development of a Dual ELISA for the Detection of CD2v-Unexpressed Lower-Virulence Mutational ASFV.

African swine fever virus (ASFV) is an important viral pathogen infecting pigs worldwide throughout the pig industry. CD2v (an outer-membrane glycosylated protein of ASFV)-unexpressed lower-virulence mutants have appeared in China and other countries in recent years. Using OIE-recommended quantitative PCR and ELISA methods, people can accurately judge whether pigs are infected with wild-type ASFV. However, the strategy has failed to distinguish ΔCD2v lower-virulence mutants and wild-type ASFV infection. Here, we expressed and purified the CD2v and p30 proteins via CHO cells and successfully established a dual enzyme-linked immunosorbent assay (ELISA), which can be used to differentiate pigs infected with wild-type ASFV or with CD2v-unexpressed lower-virulence mutants. The dual ELISA showed excellent specificity without cross-reactions with antibodies of PRRSV, CSFV, JEV, PRV, or PPV. The dual ELISA could detect ASFV-infected positive serum samples up to dilutions of 5120 times, possessing high sensitivity. Therefore, the application of this dual ELISA approach can play an important role in ASFV epidemiology study and fill the gaps in differential diagnosis.

3-Indoleacetonitrile Is Highly Effective in Treating Influenza A Virus Infection In Vitro and In Vivo.

Influenza A viruses are serious zoonotic pathogens that continuously cause pandemics in several animal hosts, including birds, pigs, and humans. Indole derivatives containing an indole core framework have been extensively studied and developed to prevent and/or treat viral infection. This study evaluated the anti-influenza activity of several indole derivatives, including 3-indoleacetonitrile, indole-3-carboxaldehyde, 3-carboxyindole, and gramine, in A549 and MDCK cells. Among these compounds, 3-indoleacetonitrile exerts profound antiviral activity against a broad spectrum of influenza A viruses, as tested in A549 cells. Importantly, in a mouse model, 3-indoleacetonitrile with a non-toxic concentration of 20 mg/kg effectively reduced the mortality and weight loss, diminished lung virus titers, and alleviated lung lesions of mice lethally challenged with A/duck/Hubei/WH18/2015 H5N6 and A/Puerto Rico/8/1934 H1N1 influenza A viruses. The antiviral properties enable the potential use of 3-indoleacetonitrile for the treatment of IAV infection.

A chiral sensor for recognition of varied amines based on 19F NMR signals of newly designed rhodium complexes.

A novel chiral octahedral rhodium complex containing fluorine has been developed to be an excellent chiral sensor for a variety of amines including diamines, monoamines, amino alcohols and amino acids, showing well distinguishable 19F NMR signals and an accurate measurement of enantiomeric determination.