ViT-Calibrator: Decision Stream Calibration for Vision Transformer

A surge of interest has emerged in utilizing Transformers in diverse vision tasks owing to its formidable performance. However, existing approaches primarily focus on optimizing internal model architecture designs that often entail significant trial and error with high burdens. In this work, we propose a new paradigm dubbed Decision Stream Calibration that boosts the performance of general Vision Transformers. To achieve this, we shed light on the information propagation mechanism in the learning procedure by exploring the correlation between different tokens and the relevance coefficient of multiple dimensions. Upon further analysis, it was discovered that 1) the final decision is associated with tokens of foreground targets, while token features of foreground target will be transmitted into the next layer as much as possible, and the useless token features of background area will be eliminated gradually in the forward propagation. 2) Each category is solely associated with specific sparse dimensions in the tokens. Based on the discoveries mentioned above, we designed a two-stage calibration scheme, namely ViT-Calibrator, including token propagation calibration stage and dimension propagation calibration stage. Extensive experiments on commonly used datasets show that the proposed approach can achieve promising results. The source codes are given in the supplements.Comment: 14pages, 12 figure

Assessing spatial heterogeneous response of ecosystem service relationships to land use intensification

Sustainable land use should balance the competing needs for development and protection. Land-use intensification facilitates material benefits from ecosystem, while potentially undermining the capacity of regulate the life-support environment and thus altering trade-offs between ecosystem services (ES). However, there remains a limited understanding of how land-use intensity (LUI) affects the spatial heterogeneity of ES relationships. To address this issue, we first propose an ES synergies (ESS) index, to clarify site-specific ES relationships, based on a combination of the production possibility frontier (PPF) and the technique for order preference by similarity to the ideal solution (TOPSIS). Then, we assess the nonlinear impacts of LUI on ESS, using the generalized additive models (GAMs). A case study was conducted in the Three Gorges region of central China, due to the dilemma between intensive development for poverty alleviation and water-soil retention for ecological protection. The results showed that an increase in LUI caused different rates of decline in ESS. Land-use intensification increased resource inputs and anthropogenic disturbances within entire land parcels, thus disrupting the synergistic relationships between several ES. Specifically, the synergies between water retention and carbon sequestration or biodiversity conservation decreased by more than three times as much as those between water retention and food production. Excessive LUI will reduce the provision of carbon sequestration and biodiversity conservation compared to that of food production for the same level of water retention. However, moderate LUI can promote the synergistic provision of multiple services. For example, an LUI threshold of 2.5, which maximized the synergies of water-soil retention with other ES, showed the optimal balance of diverse ecological benefits at the highest level of intensity. Our study is expected to extend existing knowledge on the spatial heterogeneity of ES relationships by considering site-specific land use, and to mitigate the costs of land management due to ES trade-offs

The effects of post-weld aging and cryogenic treatment on self-fusion welded austenitic stainless steel

The effects of post-weld aging and cryogenic treatment on self-fusion welded austenitic stainless steel thick plates were investigated in the present work. The results showed that fusion zone microstructure consisted of austenite matrix and vermicular ferrite. Aging treatment promoted the decomposition of δ-ferrite into σ-ferrites as well as the precipitation of carbides. Isothermal martensitic transformation in the Tungsten Inert Gas Welding (TIG) specimen was induced by cryogenic treatment, and stacking faults were increased. The fusion zone microstructure of Electron Beam Welding (EBW) and Laser Welding (LW) was finer than that of TIG, with acicular ferrite distributed in the austenite matrix. A large number of twins were generated in the austenite matrix after LW. Cryogenic treatment produced a large number of sub-grains in LW specimens, which was due to the entanglement and accumulation of dislocations in the vicinity of ferrite. Post-weld aging and cryogenic treatment have no influence on the strength of weldments with different welding methods while cryogenic treatment could improve the impact toughness of EBW and LW weldments by the extent of 7.4% and 8.8%, respectively. The aging treatment reduced the impact toughness by 49%, 33% and 15.5%, as well as the uniform elongation by 44%, 39% and 17% for TIG, EBW and LW, respectively. Aging treatment reduced the surface residual stress of TIG weldment by 58.8% in Y direction and 61.2% in X direction. Cryogenic treatment at could also release the surface residual stress of TIG weldment by 36.8% in X direction and 16.3% in Y direction

Comparison of Conductor-Temperature Calculations Based on Different Radial-Position-Temperature Detections for High-Voltage Power Cable

In this paper, the calculation of the conductor temperature is related to the temperature sensor position in high-voltage power cables and four thermal circuits—based on the temperatures of insulation shield, the center of waterproof compound, the aluminum sheath, and the jacket surface are established to calculate the conductor temperature. To examine the effectiveness of conductor temperature calculations, simulation models based on flow characteristics of the air gap between the waterproof compound and the aluminum are built up, and thermocouples are placed at the four radial positions in a 110 kV cross-linked polyethylene (XLPE) insulated power cable to measure the temperatures of four positions. In measurements, six cases of current heating test under three laying environments, such as duct, water, and backfilled soil were carried out. Both errors of the conductor temperature calculation and the simulation based on the temperature of insulation shield were significantly smaller than others under all laying environments. It is the uncertainty of the thermal resistivity, together with the difference of the initial temperature of each radial position by the solar radiation, which led to the above results. The thermal capacitance of the air has little impact on errors. The thermal resistance of the air gap is the largest error source. Compromising the temperature-estimation accuracy and the insulation-damage risk, the waterproof compound is the recommended sensor position to improve the accuracy of conductor-temperature calculation. When the thermal resistances were calculated correctly, the aluminum sheath is also the recommended sensor position besides the waterproof compound

Comparison Knowledge Translation for Generalizable Image Classification

Deep learning has recently achieved remarkable performance in image classification tasks, which depends heavily on massive annotation. However, the classification mechanism of existing deep learning models seems to contrast to humans' recognition mechanism. With only a glance at an image of the object even unknown type, humans can quickly and precisely find other same category objects from massive images, which benefits from daily recognition of various objects. In this paper, we attempt to build a generalizable framework that emulates the humans' recognition mechanism in the image classification task, hoping to improve the classification performance on unseen categories with the support of annotations of other categories. Specifically, we investigate a new task termed Comparison Knowledge Translation (CKT). Given a set of fully labeled categories, CKT aims to translate the comparison knowledge learned from the labeled categories to a set of novel categories. To this end, we put forward a Comparison Classification Translation Network (CCT-Net), which comprises a comparison classifier and a matching discriminator. The comparison classifier is devised to classify whether two images belong to the same category or not, while the matching discriminator works together in an adversarial manner to ensure whether classified results match the truth. Exhaustive experiments show that CCT-Net achieves surprising generalization ability on unseen categories and SOTA performance on target categories.Comment: Accepted by IJCAI 2022; Adding Supplementary Material

Ultrasound-assisted nitrogen and boron codoping of graphene oxide for efficient oxygen reduction reaction

Development of naturally abundant, low cost, and energy-efficient electrocatalysts for the oxygen reduction reaction (ORR) is essential for commercialization of fuel cells. In this work, we report simple ultrasonication assisted synthesis of nitrogen and boron dual-doped graphene oxide (NB/GO) and demonstrate its application as an effective ORR catalyst realizing predominantly 4e– reduction of O2 to OH– in 0.1 M KOH. Enhanced ORR electrocatalysis of the dual B and N codoped GO as opposed to GO singly doped with B or N arises from the synergistic interaction of the boron and nitrogen species. The content and configuration of both N and B dopants can be readily tailored by controlling the ultrasonic conditions, thereby permitting tuning of the ORR activity. Furthermore, the developed NB/GO metal-free catalyst exhibited very promising long-term durability and resistance to methanol poisoning compared to the state-of the art Pt/C catalyst

http://purl.access.gpo.gov/GPO/LPS108982 (accessed

Developing aptamer probes for acute myelogenous leukemia detection and surface protein biomarker discover