Interpretable and Flexible Target-Conditioned Neural Planners For Autonomous Vehicles

Learning-based approaches to autonomous vehicle planners have the potential to scale to many complicated real-world driving scenarios by leveraging huge amounts of driver demonstrations. However, prior work only learns to estimate a single planning trajectory, while there may be multiple acceptable plans in real-world scenarios. To solve the problem, we propose an interpretable neural planner to regress a heatmap, which effectively represents multiple potential goals in the bird's-eye view of an autonomous vehicle. The planner employs an adaptive Gaussian kernel and relaxed hourglass loss to better capture the uncertainty of planning problems. We also use a negative Gaussian kernel to add supervision to the heatmap regression, enabling the model to learn collision avoidance effectively. Our systematic evaluation on the Lyft Open Dataset across a diverse range of real-world driving scenarios shows that our model achieves a safer and more flexible driving performance than prior works

Safety-Critical Scenario Generation Via Reinforcement Learning Based Editing

Generating safety-critical scenarios is essential for testing and verifying the safety of autonomous vehicles. Traditional optimization techniques suffer from the curse of dimensionality and limit the search space to fixed parameter spaces. To address these challenges, we propose a deep reinforcement learning approach that generates scenarios by sequential editing, such as adding new agents or modifying the trajectories of the existing agents. Our framework employs a reward function consisting of both risk and plausibility objectives. The plausibility objective leverages generative models, such as a variational autoencoder, to learn the likelihood of the generated parameters from the training datasets; It penalizes the generation of unlikely scenarios. Our approach overcomes the dimensionality challenge and explores a wide range of safety-critical scenarios. Our evaluation demonstrates that the proposed method generates safety-critical scenarios of higher quality compared with previous approaches

Probing Product Description Generation via Posterior Distillation

In product description generation (PDG), the user-cared aspect is critical for the recommendation system, which can not only improve user's experiences but also obtain more clicks. High-quality customer reviews can be considered as an ideal source to mine user-cared aspects. However, in reality, a large number of new products (known as long-tailed commodities) cannot gather sufficient amount of customer reviews, which brings a big challenge in the product description generation task. Existing works tend to generate the product description solely based on item information, i.e., product attributes or title words, which leads to tedious contents and cannot attract customers effectively. To tackle this problem, we propose an adaptive posterior network based on Transformer architecture that can utilize user-cared information from customer reviews. Specifically, we first extend the self-attentive Transformer encoder to encode product titles and attributes. Then, we apply an adaptive posterior distillation module to utilize useful review information, which integrates user-cared aspects to the generation process. Finally, we apply a Transformer-based decoding phase with copy mechanism to automatically generate the product description. Besides, we also collect a large-scare Chinese product description dataset to support our work and further research in this field. Experimental results show that our model is superior to traditional generative models in both automatic indicators and human evaluation

Recent strategies for constructing efficient interfacial solar evaporation systems

Interfacial solar evaporation (ISE) is a promising technology to relieve worldwide freshwater shortages owing to its high energy conversion efficiency and environmentally sustainable potential. So far, many innovative materials and evaporators have been proposed and applied in ISE to enable highly controllable and efficient solar-to-thermal energy conversion. With rational design, solar evaporators can achieve excellent energy management for lowering energy loss, harvesting extra energy, and efficiently utilizing energy in the system to improve freshwater production. Beyond that, a strategy of reducing water vaporization enthalpy by introducing molecular engineering for water-state regulation has also been demonstrated as an effective approach to boost ISE. Based on these, this article discusses the energy nexus in two-dimensional (2D) and three-dimensional (3D) evaporators separately and reviews the strategies for design and fabrication of highly efficient ISE systems. The summarized work offers significant perspectives for guiding the future design of ISE systems with efficient energy management, which pave pathways for practical applications

Survivin is a prognostic marker and therapeutic target for extranodal, nasal-type natural killer/T cell lymphoma.

Background: The relationship between survivin and extranodal, nasal-type natural killer/T cell lymphoma (ENKTCL) was unclearly established yet. We here studied the potential prognostic roles of survivin and its implication as a target in ENKTCL therapy. Methods: ENKTCL patients\u27 peripheral blood were collected and tested by ELISA. ENKTCL cell lines were cultured with or without survivin inhibitor and tested by MTT and Flow cytometry. According to the gene expression profiles from the ArrayExpress Archive under E-TABM-702, survivin co-regulated cluster was established by Coupled Two-way Clustering Algorithm. Results: Seventeen point six percent of total 17 ENKTCL patients were serum survivin-positive. These patients had poorer outcome than that of negative cases (P Conclusions: We concluded that survivin was a potential prognostic marker and a critical regulatory molecule in the pathological process of ENKTCL. It would be a promising target in drugs discovery for ENKTCL therapy

The Double Burdens of Mental Health Among AIDS Patients With Fully Successful Immune Restoration: A Cross-Sectional Study of Anxiety and Depression in China

Background: Anxiety and depression continue to be significant comorbidities for people with HIV infection. We investigated the prevalence of and factors associated with anxiety and depression among adult HIV-infected patients across China.Methods: In this cross-sectional study, we described clinical and psychosocial variables related to depression and anxiety in 4103 HIV-infected persons. Doctors assessed anxiety and depression by asking patients whether they had experienced anxiety or depression in the prior month. Patients also self-administered the Hospital Anxiety and Depression (HAD) scale; those with score ≥8 on HAD-A/D were considered to be at high risk of anxiety or depression.Results: Associations between socio-demographic, psychosocial, and ART-related clinical factors and risk of depression or anxiety were investigated using multivariable logistic regression. Among patients assessed between 9/2014 and 11/2015, 27.4% had symptoms of anxiety, 32.9% had symptoms of depression, and 19.0% had both. Recentness of HIV diagnoses (P = 0.046) was associated with elevated odds of anxiety. Older age (P = 0.004), higher educational attainment (P < 0.001), employment (P = 0.001), support from family / friends (P < 0.001), and sleep disturbance (P < 0.001), and number of ART regimen switches (P = 0.046) were associated with risk of depression, while neither sex nor transmission route showed any associations. There were no significant associations with HIV-specific clinical factors including current CD4+ T cell count and current viral load.Conclusions: Prevalence of symptoms of anxiety and depression is high in this cohort of treatment-experienced HIV patients. Psychological and social-demographic factors, rather than HIV disease status, were associated with risk of depression and anxiety. This finding highlights the need to deliver interventions to address the mental health issues affecting HIV-infected persons with fully successful immune restoration across China