Boosting Multi-Modal E-commerce Attribute Value Extraction via Unified Learning Scheme and Dynamic Range Minimization

With the prosperity of e-commerce industry, various modalities, e.g., vision and language, are utilized to describe product items. It is an enormous challenge to understand such diversified data, especially via extracting the attribute-value pairs in text sequences with the aid of helpful image regions. Although a series of previous works have been dedicated to this task, there remain seldomly investigated obstacles that hinder further improvements: 1) Parameters from up-stream single-modal pretraining are inadequately applied, without proper jointly fine-tuning in a down-stream multi-modal task. 2) To select descriptive parts of images, a simple late fusion is widely applied, regardless of priori knowledge that language-related information should be encoded into a common linguistic embedding space by stronger encoders. 3) Due to diversity across products, their attribute sets tend to vary greatly, but current approaches predict with an unnecessary maximal range and lead to more potential false positives. To address these issues, we propose in this paper a novel approach to boost multi-modal e-commerce attribute value extraction via unified learning scheme and dynamic range minimization: 1) Firstly, a unified scheme is designed to jointly train a multi-modal task with pretrained single-modal parameters. 2) Secondly, a text-guided information range minimization method is proposed to adaptively encode descriptive parts of each modality into an identical space with a powerful pretrained linguistic model. 3) Moreover, a prototype-guided attribute range minimization method is proposed to first determine the proper attribute set of the current product, and then select prototypes to guide the prediction of the chosen attributes. Experiments on the popular multi-modal e-commerce benchmarks show that our approach achieves superior performance over the other state-of-the-art techniques

ASSIST: Interactive Scene Nodes for Scalable and Realistic Indoor Simulation

We present ASSIST, an object-wise neural radiance field as a panoptic representation for compositional and realistic simulation. Central to our approach is a novel scene node data structure that stores the information of each object in a unified fashion, allowing online interaction in both intra- and cross-scene settings. By incorporating a differentiable neural network along with the associated bounding box and semantic features, the proposed structure guarantees user-friendly interaction on independent objects to scale up novel view simulation. Objects in the scene can be queried, added, duplicated, deleted, transformed, or swapped simply through mouse/keyboard controls or language instructions. Experiments demonstrate the efficacy of the proposed method, where scaled realistic simulation can be achieved through interactive editing and compositional rendering, with color images, depth images, and panoptic segmentation masks generated in a 3D consistent manner

NASICON-type air-stable and all-climate cathode for sodium-ion batteries with low cost and high-power density

The development of low-cost and long-lasting all-climate cathode materials for the sodium ion battery has been one of the key issues for the success of large-scale energy storage. One option is the utilization of earth-abundant elements such as iron. Here, we synthesize a NASICON-type tuneable Na4Fe3(PO4)2(P2O7)/C nanocomposite which shows both excellent rate performance and outstanding cycling stability over more than 4400 cycles. Its air stability and all-climate properties are investigated, and its potential as the sodium host in full cells has been studied. A remarkably low volume change of 4.0% is observed. Its high sodium diffusion coefficient has been measured and analysed via first-principles calculations, and its three-dimensional sodium ion diffusion pathways are identified. Our results indicate that this low-cost and environmentally friendly Na4Fe3(PO4)2(P2O7)/C nanocomposite could be a competitive candidate material for sodium ion batteries

Prevalence of Vitamin D Inadequacy Among Chinese Postmenopausal Women: A Nationwide, Multicenter, Cross-Sectional Study

Purpose: We aimed to investigate the status of serum 25-hydroxyvitamin D [25(OH)D] among Chinese postmenopausal women in a multicenter cross-sectional study.Methods: Non-institutionalized postmenopausal women aged ≥55 years were recruited from urban and rural areas in 7 geographically different regions in China. Subject enrollment was executed during the summer and the winter. Vitamin D insufficiency and deficiency were defined as 25(OH)D < 30 and< 20 ng/ml, and was measured by liquid chromatography-tandem mass spectrometry. Women were referred to a dual-energy x-ray absorptiometry (DXA) if they had a medium-to-high fracture risk suggested by Osteoporosis Self-Assessment Tool for Asians (OSTA).Results: Among all subjects, 91.2% (1,535/1,684, 95%CI: 89.7, 92.5) had vitamin D insufficiency and 61.3% had vitamin D deficiency (1,033/1,684, 95%CI: 59.0, 63.7). The prevalence of vitamin D deficiency was significantly higher in urban dwellers (64.9 vs. 57.7% in rural, P = 0.002) and in winter-enrolled subjects (84.7 vs. 41.3% in summer, P < 0.0001). The prevalence of vitamin D inadequacy did not increase in trend by latitude and was numerically lower in women who had high fracture risk and osteoporosis. A non-curvilinear change of intact parathyroid hormone (iPTH) levels was observed at 25(OH)D >16.78 ng/mL.Conclusions: The prevalence of vitamin D inadequacy was remarkable among Chinese postmenopausal women and independent of fracture risk assessed by OSTA or osteoporosis suggested by DXA. Winter season, urban residence, however not latitude, were significantly associated with a higher likelihood of vitamin D deficiency. Optimal vitamin D status for iPTH and bone-related outcomes merits further investigation in this population

Pre-anesthetic use of butorphanol for the prevention of emergence agitation in thoracic surgery: A multicenter, randomized controlled trial

BackgroundEmergence agitation (EA) is common in patients after general anesthesia (GA) and is associated with poor outcomes. Patients with thoracic surgery have a higher incidence of EA compared with other surgery. This study aimed to investigate the impact of pre-anesthetic butorphanol infusion on the incidence of EA in patients undergoing thoracic surgery with GA.Materials and methodsThis prospective randomized controlled trial (RCT) was conducted in 20 tertiary hospitals in China. A total of 668 patients undergoing elective video-assisted thoracoscopic lobectomy/segmentectomy for lung cancer were assessed for eligibility, and 620 patients were enrolled. In total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. Patients in the intervention group received butorphanol 0.02 mg/kg 15 min before induction of anesthesia. Patients in the control group received volume-matched normal saline in the same schedule. The primary outcome was the incidence of EA after 5 min of extubation, and EA was evaluated using the Riker Sedation-Agitation Scale (RSAS). The incidence of EA was determined by the chi-square test, with a significance of P < 0.05.ResultsIn total, 296 patients who received butorphanol and 306 control patients were included in the intention-to-treat analysis. The incidence of EA 5 min after extubation was lower with butorphanol treatment: 9.8% (29 of 296) vs. 24.5% (75 of 306) in the control group (P = 0.0001). Patients who received butorphanol had a lower incidence of drug-related complications (including injecting propofol pain and coughing with sufentanil): 112 of 296 vs. 199 of 306 in the control group (P = 0.001) and 3 of 296 vs. 35 of 306 in the control group (P = 0.0001).ConclusionThe pre-anesthetic administration of butorphanol reduced the incidence of EA after thoracic surgery under GA.Clinical trial registration[http://www.chictr.org.cn/showproj.aspx?proj=42684], identifier [ChiCTR1900025705]

Interference Confocal Microscope Integrated with Spatial Phase Shifter

We present an interference confocal microscope (ICM) with a new single-body four-step simultaneous phase-shifter device designed to obtain high immunity to vibration. The proposed ICM combines the respective advantages of simultaneous phase shifting interferometry and bipolar differential confocal microscopy to obtain high axis resolution, large dynamic range, and reduce the sensitivity to vibration and reflectance disturbance seamlessly. A compact single body spatial phase shifter is added to capture four phase-shifted interference signals simultaneously without time delay and construct a stable and space-saving simplified interference confocal microscope system. The test result can be obtained by combining the interference phase response and the bipolar property of differential confocal microscopy without phase unwrapping. Experiments prove that the proposed microscope is capable of providing stable measurements with 1 nm of axial depth resolution for either low- or high-numerical aperture objective lenses

Interference Confocal Microscope Integrated with Spatial Phase Shifter

We present an interference confocal microscope (ICM) with a new single-body four-step simultaneous phase-shifter device designed to obtain high immunity to vibration. The proposed ICM combines the respective advantages of simultaneous phase shifting interferometry and bipolar differential confocal microscopy to obtain high axis resolution, large dynamic range, and reduce the sensitivity to vibration and reflectance disturbance seamlessly. A compact single body spatial phase shifter is added to capture four phase-shifted interference signals simultaneously without time delay and construct a stable and space-saving simplified interference confocal microscope system. The test result can be obtained by combining the interference phase response and the bipolar property of differential confocal microscopy without phase unwrapping. Experiments prove that the proposed microscope is capable of providing stable measurements with 1 nm of axial depth resolution for either low- or high-numerical aperture objective lenses

Dehydroabietic Acid Derivative QC2 Induces Oncosis in Hepatocellular Carcinoma Cells

Aim. Rosin, the traditional Chinese medicine, is reported to be able to inhibit skin cancer cell lines. In this report, we investigate the inhibitory effect against HCC cells of QC2, the derivative of rosin’s main components dehydroabietic acid. Methods. MTT assay was used to determine the cytotoxicity of QC2. Morphological changes were observed by time-lapse microscopy and transmission electron microscopy and the cytoskeleton changes were observed by laser-scanning confocal microscopy. Cytomembrane integrity and organelles damage were confirmed by detection of the reactive oxygen (ROS), lactate dehydrogenase (LDH), and mitochondrial membrane potential (Δψm). The underlying mechanism was manifested by Western blotting. The oncotic cell death was further confirmed by detection of oncosis related protein calpain. Results. Swelling cell type and destroyed cytoskeleton were observed in QC2-treated HCC cells. Organelle damage was visualized by transmission electron microscopy. The detection of ROS accumulation, increased LDH release, and decreased ATP and Δψm confirmed the cell death. The oncotic related protein calpain was found to increase time-dependently in QC2-treated HCC cells, while its inhibitor PD150606 attenuated the cytotoxicity. Conclusions. Dehydroabietic acid derivative QC2 activated oncosis related protein calpain to induce the damage of cytomembrane and organelles which finally lead to oncosis in HCC cells

Ship Detection from Ocean SAR Image Based on Local Contrast Variance Weighted Information Entropy

Ship detection from synthetic aperture radar (SAR) images is one of the crucial issues in maritime surveillance. However, due to the varying ocean waves and the strong echo of the sea surface, it is very difficult to detect ships from heterogeneous and strong clutter backgrounds. In this paper, an innovative ship detection method is proposed to effectively distinguish the vessels from complex backgrounds from a SAR image. First, the input SAR image is pre-screened by the maximally-stable extremal region (MSER) method, which can obtain the ship candidate regions with low computational complexity. Then, the proposed local contrast variance weighted information entropy (LCVWIE) is adopted to evaluate the complexity of those candidate regions and the dissimilarity between the candidate regions with their neighborhoods. Finally, the LCVWIE values of the candidate regions are compared with an adaptive threshold to obtain the final detection result. Experimental results based on measured ocean SAR images have shown that the proposed method can obtain stable detection performance both in strong clutter and heterogeneous backgrounds. Meanwhile, it has a low computational complexity compared with some existing detection methods