Ultrafast Video Attention Prediction with Coupled Knowledge Distillation

Large convolutional neural network models have recently demonstrated impressive performance on video attention prediction. Conventionally, these models are with intensive computation and large memory. To address these issues, we design an extremely light-weight network with ultrafast speed, named UVA-Net. The network is constructed based on depth-wise convolutions and takes low-resolution images as input. However, this straight-forward acceleration method will decrease performance dramatically. To this end, we propose a coupled knowledge distillation strategy to augment and train the network effectively. With this strategy, the model can further automatically discover and emphasize implicit useful cues contained in the data. Both spatial and temporal knowledge learned by the high-resolution complex teacher networks also can be distilled and transferred into the proposed low-resolution light-weight spatiotemporal network. Experimental results show that the performance of our model is comparable to ten state-of-the-art models in video attention prediction, while it costs only 0.68 MB memory footprint, runs about 10,106 FPS on GPU and 404 FPS on CPU, which is 206 times faster than previous models

3D Printing of Auxetic Shape-Memory Metamaterial Towards Designable Buckling

Poisson’s ratios of shape-memory auxetic metamaterial was experimentally investigated. Based on the generalized Maxwell model and finite-element method, the buckling behaviors and their main influence factors were studied. The analytical results and experimental ones showed a good agreement. Thermomechanical properties of the printed metamaterials govern the temperature and strain rate-dependent buckling, and a controllable transition from the negative to positive Poisson’s ratio in the metamaterials can be achieved. Based on the shape memory effect, the buckled state and the Poisson’s ratio of the metamaterials can be tuned by programmed thermomechanical processes. This study provides a simple and efficient way to generate morphing structures using the designable buckling effect

Transfer-free, lithography-free and fast growth of patterned CVD graphene directly on insulators by using sacrificial metal catalyst

Chemical vapor deposited graphene suffers from two problems: transfer from metal catalysts to insulators, and photoresist induced degradation during patterning. Both result in macroscopic and microscopic damages such as holes, tears, doping, and contamination, translated into property and yield dropping. We attempt to solve the problems simultaneously. A nickel thin film is evaporated on SiO2 as a sacrificial catalyst, on which surface graphene is grown. A polymer (PMMA) support is spin-coated on the graphene. During the Ni wet etching process, the etchant can permeate the polymer, making the etching efficient. The PMMA/graphene layer is fixed on the substrate by controlling the surface morphology of Ni film during the graphene growth. After etching, the graphene naturally adheres to the insulating substrate. By using this method, transfer-free, lithography-free and fast growth of graphene realized. The whole experiment has good repeatability and controllability. Compared with graphene transfer between substrates, here, no mechanical manipulation is required, leading to minimal damage. Due to the presence of Ni, the graphene quality is intrinsically better than catalyst-free growth. The Ni thickness and growth temperature are controlled to limit the number of layers of graphene. The technology can be extended to grow other two-dimensional materials with other catalysts

Genome-wide identification and comprehensive analysis of tubby-like protein gene family in multiple crops

IntroductionThe highly conserved tubby-like proteins (TLPs) play key roles in animal neuronal development and plant growth. The abiotic stress tolerance function of TLPs has been widely explored in plants, however, little is known about comparative studies of TLPs within crops.MethodsBioinformatic identification, phylogenetic analysis, Cis-element analysis, expression analysis, Cis-element analysis, expression analysis and so on were explored to analysis the TLP gene family of multiple crops.ResultsIn this study, a comprehensive analysis of TLP genes were carried out in seven crops to explore whether similar function of TLPs in rice could be achieved in other crops. We identified 20, 9, 14, 11, 12, 35, 14 and 13 TLP genes in Glycine max, Hordeum vulgare, Sorghum bicolor, Arabidopsis thaliana, Oryza sativa Japonica, Triticum aestivum, Setaria italic and Zea mays, respectively. All of them were divided into two groups and ten orthogroups (Ors) based on amino acids. A majority of TLP genes had two domains, tubby-like domain and F-box domain, while members of Or5 only had tubby-like domain. In addition, Or5 had more exons and shorter DNA sequences, showing that characteristics of different Ors reflected the differentiated function and feature of TLP genes in evolutionary process, and Or5 was the most different from the other Ors. Besides, we recognized 25 cis-elements in the promoter of TLP genes and explored multiple new regulation pathway of TLPs including light and hormone response. The bioinformatic and transcriptomic analysis implied the stresses induced expression and possible functional redundancy of TLP genes. We detected the expression level of 6 OsTLP genes at 1 to 6 days after seed germination in rice, and the most obvious changes in these days were appeared in OsTLP10 and OsTLP12.DiscussionCombined yeast two-hybrid system and pull down assay, we suggested that the TLP genes of Or1 may have similar function during seed germination in different species. In general, the results of comprehensive analysis of TLP gene family in multiple species provide valuable evolutionary and functional information of TLP gene family which are useful for further application and study of TLP genes

Influence of body composition assessment with bioelectrical impedance vector analysis in cancer patients undergoing surgery

BackgroundMalnutrition is common in patients undergoing surgery for cancers and is a risk factor for postoperative outcomes. Body composition provides information for precise nutrition intervention in perioperative period for improving patients’ postoperative outcomes.ObjectionThe aim was to determine changes in parameters of body composition and nutritional status of cancer patients during perioperative period.MethodsA total of 92 patients diagnosed with cancer were divided into gastrointestinal and non-gastrointestinal cancer group according to different cancer types. The patients body composition assessed by bioelectrical impedance vector analysis (BIVA) on the day before surgery, postoperative day 1 and 1 day before discharge. The changes between two groups were compared and the correlation between body composition and preoperative serum nutritional indexes was analyzed.ResultsThe nutritional status of all patients become worse after surgery, and phase angle (PA) continued to decrease in the perioperative period. Fat-free mass (FFM), fat-free mass index (FFMI), skeletal muscle mass (SMM), extracellular water (ECW), total body water (TBW), hydration, and body cell mass (BCM) rise slightly and then fall in the postoperative period in patients with gastrointestinal cancer, and had a sustained increase in non-gastrointestinal patients, respectively (P<0.05). Postoperative body composition changes in patients with gastrointestinal cancer are related to preoperative albumin, pre-albumin, hemoglobin, and C-reactive protein (P<0.05), whereas postoperative body composition changes in patients with non-gastrointestinal cancer are related to age (P<0.05).ConclusionsSignificant changes in body composition both in patients with gastrointestinal cancer and non-gastrointestinal cancer during perioperative period are observed. Changes in body composition for the cancer patients who undergoing surgery are related to age and preoperative serum nutrition index