Auto-Encoding Scene Graphs for Image Captioning

We propose Scene Graph Auto-Encoder (SGAE) that incorporates the language inductive bias into the encoder-decoder image captioning framework for more human-like captions. Intuitively, we humans use the inductive bias to compose collocations and contextual inference in discourse. For example, when we see the relation `person on bike', it is natural to replace `on' with `ride' and infer `person riding bike on a road' even the `road' is not evident. Therefore, exploiting such bias as a language prior is expected to help the conventional encoder-decoder models less likely overfit to the dataset bias and focus on reasoning. Specifically, we use the scene graph --- a directed graph ($\mathcal{G}$) where an object node is connected by adjective nodes and relationship nodes --- to represent the complex structural layout of both image ($\mathcal{I}$) and sentence ($\mathcal{S}$). In the textual domain, we use SGAE to learn a dictionary ($\mathcal{D}$) that helps to reconstruct sentences in the $\mathcal{S}\rightarrow \mathcal{G} \rightarrow \mathcal{D} \rightarrow \mathcal{S}$ pipeline, where $\mathcal{D}$ encodes the desired language prior; in the vision-language domain, we use the shared $\mathcal{D}$ to guide the encoder-decoder in the $\mathcal{I}\rightarrow \mathcal{G}\rightarrow \mathcal{D} \rightarrow \mathcal{S}$ pipeline. Thanks to the scene graph representation and shared dictionary, the inductive bias is transferred across domains in principle. We validate the effectiveness of SGAE on the challenging MS-COCO image captioning benchmark, e.g., our SGAE-based single-model achieves a new state-of-the-art $127.8$ CIDEr-D on the Karpathy split, and a competitive $125.5$ CIDEr-D (c40) on the official server even compared to other ensemble models

Aquaporin-3 Attenuates Oxidative Stress-Induced Nucleus Pulposus Cell Apoptosis Through Regulating the P38 MAPK Pathway

Background/Aims: Previous studies have shown that oxidative damage is a main contributor to disc nucleus pulposus (NP) cell apoptosis. Aquaporin-3 (AQP-3) facilitates reactive oxygen species (ROS) scavenging and thus alleviates oxidative injury in other cells. This study aims to investigate the role and mechanism of AQP-3 in regulating NP cell apoptosis under oxidative damage. Methods: Rat NP cells were treated with H2O2 for 48 hours, while control NP cells were free of H2O2. Recombinant AQP-3 lentiviral vectors were used to investigate the effect of enhanced AQP-3 expression levels in NP cells. NP cell apoptosis was assessed by flow cytometry, caspase-3 activity, gene expression of apoptosis-related molecules (Bax, Bcl-2 and caspase-3), and protein expression of cellular apoptosis markers (cleaved PARP and cleaved caspase-3). Additionally, intracellular ROS content and activity of the p38 MAPK pathway were evaluated. Results: Compared with the control NP cells, oxidative damage in the treatment cells significantly increased cell apoptosis ratios and caspase-3 activity, upregulated gene expression of Bax and caspase-3, downregulated gene expression of Bcl-2, and increased protein expression of cleaved PARP and cleaved caspase-3, as well as increased intracellular ROS content and activity of the p38 MAPK pathway. However, AQP-3 overexpression partly alleviated cell apoptosis, decreased intracellular ROS content, and inhibited the p38 MAPK pathway in NP cells under oxidative damage. Conclusion: Oxidative damage can significantly downregulate AQP-3 expression. Enhancing AQP-3 expression in NP cells partly attenuates cellular apoptosis through regulating the p38 MAPK pathway under oxidative damage

Radiomics model based on intratumoral and peritumoral features for predicting major pathological response in non-small cell lung cancer receiving neoadjuvant immunochemotherapy

ObjectiveTo establish a radiomics model based on intratumoral and peritumoral features extracted from pre-treatment CT to predict the major pathological response (MPR) in patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant immunochemotherapy.MethodsA total of 148 NSCLC patients who underwent neoadjuvant immunochemotherapy from two centers (SRRSH and ZCH) were retrospectively included. The SRRSH dataset (n=105) was used as the training and internal validation cohort. Radiomics features of intratumoral (T) and peritumoral regions (P1 = 0-5mm, P2 = 5-10mm, and P3 = 10-15mm) were extracted from pre-treatment CT. Intra- and inter- class correlation coefficients and least absolute shrinkage and selection operator were used to feature selection. Four single ROI models mentioned above and a combined radiomics (CR: T+P1+P2+P3) model were established by using machine learning algorithms. Clinical factors were selected to construct the combined radiomics-clinical (CRC) model, which was validated in the external center ZCH (n=43). The performance of the models was assessed by DeLong test, calibration curve and decision curve analysis.ResultsHistopathological type was the only independent clinical risk factor. The model CR with eight selected radiomics features demonstrated a good predictive performance in the internal validation (AUC=0.810) and significantly improved than the model T (AUC=0.810 vs 0.619, p<0.05). The model CRC yielded the best predictive capability (AUC=0.814) and obtained satisfactory performance in the independent external test set (AUC=0.768, 95% CI: 0.62-0.91).ConclusionWe established a CRC model that incorporates intratumoral and peritumoral features and histopathological type, providing an effective approach for selecting NSCLC patients suitable for neoadjuvant immunochemotherapy

DS-KCF: a real-time tracker for RGB-D data

© 2016 The Author(s) We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF tracker that is able to exploit depth information to handle scale changes, occlusions, and shape changes. Despite the computational demands of the extra functionalities, we still achieve real-time performance rates of 35–43 fps in MATLAB and 187 fps in our C++ implementation. Our proposed method includes fast depth-based target object segmentation that enables, (1) efficient scale change handling within the KCF core functionality in the Fourier domain, (2) the detection of occlusions by temporal analysis of the target’s depth distribution, and (3) the estimation of a target’s change of shape through the temporal evolution of its segmented silhouette allows. Finally, we provide an in-depth analysis of the factors affecting the throughput and precision of our proposed tracker and perform extensive comparative analysis. Both the MATLAB and C++ versions of our software are available in the public domain

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Terahertz Broadband Absorber Based on a Combined Circular Disc Structure

To solve the problem of complex structure and narrow absorption band of most of today′s terahertz absorbers, this paper proposes and utilizes the finite element (COMSOL) method to numerically simulate a broadband absorber based on a straightforward periodic structure consisting of a disk and concentric ring. The final results show that our designed absorber has an absorption rate of over 99% in the broadband range of 9.06 THz to 9.8 THz and an average of over 97.7% in the ultra-broadband range of 8.62 THz to 10 THz. The reason for the high absorption is explained by the depiction of the electric field on the absorber surface at different frequencies. In addition, the materials for the top pattern of the absorber are replaced by Cu, Ag, or Al, and the absorber still achieves perfect absorption with different metal materials. Due to the perfect symmetry of the absorber structure, the absorber is very polarization-insensitive. The overall design is simple, easy to process and production. Therefore, our research will offer great potential for applications in areas such as terahertz electromagnetic stealth, sensing, and thermal imaging