AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets

This paper studies the Binary Neural Networks (BNNs) in which weights and activations are both binarized into 1-bit values, thus greatly reducing the memory usage and computational complexity. Since the modern deep neural networks are of sophisticated design with complex architecture for the accuracy reason, the diversity on distributions of weights and activations is very high. Therefore, the conventional sign function cannot be well used for effectively binarizing full-precision values in BNNs. To this end, we present a simple yet effective approach called AdaBin to adaptively obtain the optimal binary sets $\{b_1, b_2\}$ ($b_1, b_2\in \mathbb{R}$) of weights and activations for each layer instead of a fixed set (\textit{i.e.}, $\{-1, +1\}$). In this way, the proposed method can better fit different distributions and increase the representation ability of binarized features. In practice, we use the center position and distance of 1-bit values to define a new binary quantization function. For the weights, we propose an equalization method to align the symmetrical center of binary distribution to real-valued distribution, and minimize the Kullback-Leibler divergence of them. Meanwhile, we introduce a gradient-based optimization method to get these two parameters for activations, which are jointly trained in an end-to-end manner. Experimental results on benchmark models and datasets demonstrate that the proposed AdaBin is able to achieve state-of-the-art performance. For instance, we obtain a 66.4% Top-1 accuracy on the ImageNet using ResNet-18 architecture, and a 69.4 mAP on PASCAL VOC using SSD300. The PyTorch code is available at \url{https://github.com/huawei-noah/Efficient-Computing/tree/master/BinaryNetworks/AdaBin} and the MindSpore code is available at \url{https://gitee.com/mindspore/models/tree/master/research/cv/AdaBin}.Comment: ECCV 202

Analysis of the Invasion of Acetes into the Water Intake of the Daya Bay Nuclear Power Base

The invasions of marine organisms into the intake of nuclear power plants threaten the normal operation of such plants. Most published numerical models assumed that marine organisms passively follow the current, but such models neglected their biological swimming ability. In this work, adopting a hydrodynamic mathematical model to replicate the flow around the Daya Bay nuclear power base, the invasion characteristics of Acetes were explored by considering the behavior of biological movement. A concept of biological residual current was introduced to describe biological movements that were dominated by both tidal current and biological swimming ability. The biological residual currents near the nuclear power plant were obtained for cases with different nocturnal migration periods (12 h, 13 h, 14 h, 15 h, and 16 h). Using the Lagrangian particle-tracking method, the primary invasion paths of Acetes were obtained, as well as the travel time of Acetes to the intake, based on the biological residual current along monitoring points. The results showed that the invading time for Acetes reaching the water intake of the nuclear power base was significantly decreased when biological migration behavior was considered. When the nocturnal active period was over 13 h, it took only 10 days for Acetes to enter the western waters of Daya Bay from the southwest of Da Lajia Island and then continue migrating to the water intake in the nuclear power base. When the nocturnal active period was less than 13 h, it took more than 20 days for Acetes to travel the same distance. The present work provides a new methodology for the simulation and prediction of the migration of marine organisms

Analysis of the Invasion of Acetes into the Water Intake of the Daya Bay Nuclear Power Base

The invasions of marine organisms into the intake of nuclear power plants threaten the normal operation of such plants. Most published numerical models assumed that marine organisms passively follow the current, but such models neglected their biological swimming ability. In this work, adopting a hydrodynamic mathematical model to replicate the flow around the Daya Bay nuclear power base, the invasion characteristics of Acetes were explored by considering the behavior of biological movement. A concept of biological residual current was introduced to describe biological movements that were dominated by both tidal current and biological swimming ability. The biological residual currents near the nuclear power plant were obtained for cases with different nocturnal migration periods (12 h, 13 h, 14 h, 15 h, and 16 h). Using the Lagrangian particle-tracking method, the primary invasion paths of Acetes were obtained, as well as the travel time of Acetes to the intake, based on the biological residual current along monitoring points. The results showed that the invading time for Acetes reaching the water intake of the nuclear power base was significantly decreased when biological migration behavior was considered. When the nocturnal active period was over 13 h, it took only 10 days for Acetes to enter the western waters of Daya Bay from the southwest of Da Lajia Island and then continue migrating to the water intake in the nuclear power base. When the nocturnal active period was less than 13 h, it took more than 20 days for Acetes to travel the same distance. The present work provides a new methodology for the simulation and prediction of the migration of marine organisms

The Nitrogen Removal Performance and Functional Bacteria in Heterotrophic Denitrification and Mixotrophic Denitrification Process

The heterotrophic and autotrophic synergistic denitrification (HAD) system can effectively remove sulfide, nitrate, and organic carbon pollutants from municipal wastewater. However, the effect of sulfide on the functional bacteria in the denitrification system is still unclear. To better understand the mechanism of sulfide affected on bacteria in the system, the up-flow anaerobic sludge blanket (UASB) reactor was operated continuously under heterotrophic (no sulfide added) and mixotrophic conditions (with increased sulfide contents) for 120 days. The contents of protein (PN) in extracellular polymeric substances (EPS) were significantly increased with the addition of sulfide, which enhanced the flocculation of sludge and was beneficial to the formation of high-density microorganism communities. The dominant bacteria showed large differences under different nutrient conditions. The abundances of Thauera increased from 4.13% to over 12.94%, and that of Dechloromonas and Thiobacillus were 2.61–3.01% and 1.04–2.66% respectively after added sulfide. And the efficient performance of the system in mixotrophic conditions was accomplished with the interaction of heterotrophic sulfide-oxidizing, nitrate-reducing bacteria (Thauera, Dechloromonas), autotrophic sulfide-oxidizing, nitrate-reducing bacteria (Thiobacillus) and heterotrophic nitrate-reducing bacteria (Rubrivivax, Acidovorax, Simplicispira, Alicycliphilus). Moreover, the abundances of Nar G, Nap A, Nir S, Nor B, and Nos Z were significantly enhanced in mixotrophic conditions, indicating that the nitrogen metabolism potential of the system was also improved after added sulfide. These results elucidated the reasons for the enhanced denitrifying capacity of the system by adding S2− from the microbiological point of view and provided a theoretical basis for the establishment of an efficient denitrification system

Magnetic soft micromachines made of linked microactuator networks

Soft untethered micromachines with overall sizes less than 100 μm enable diverse programmed shape transformations and functions for future biomedical and organ-on-a-chip applications. However, fabrication of such machines has been hampered by the lack of control of microactuator's programmability. To address such challenge, we use two-photon polymerization to selectively link Janus microparticle-based magnetic microactuators by three-dimensional (3D) printing of soft or rigid polymer microstructures or links. Sequentially, we position each microactuator at a desired location by surface rolling and rotation to a desired position and orientation by applying magnetic field-based torques, and then 3D printing soft or rigid links to connect with other temporarily fixed microactuators. The linked 2D microactuator networks exhibit programmed 2D and 3D shape transformations, and untethered limbless and limbed micromachine prototypes exhibit various robotic gaits for surface locomotion. The fabrication strategy presented here can enable soft micromachine designs and applications at the cellular scales.ISSN:2375-254

Phase transition behaviours near the triple point for Pb-free (1 − x)Ba(Zr

The reason for the large electromechanical response in Pb-free piezoceramic Ba(Zr0.2Ti0.8)O3-(Ba0.7Ca0.3)TiO3 (BZT-BCT) still remains controversial, and a central issue is whether or not the multi-phase-coexisting point (triple point) in the phase diagram is a thermodynamic tricritical point. In this letter, we study the phase transition behaviour for the ferro-para transitions of BZT-BCT specimens in the vicinity of a triple point. Our results show that latent heat and thermal hysteresis approach zero, while the permittivity peak value is maximized close to the triple-point composition, which suggests that the triple point exhibits nearly tricritical transition behaviours in the BZT-BCT system. Further, the TEM result shows that the domain width is minimized with composition approaching the triple point, which indicates a reduction of the domain wall energy possibly relevant to the tricriticality of the triple point. A sixth-order Landau energy modeling shows that the triple tricritical point provides a free-energy state of near-vanishing polarization anisotropy and thus enhances the piezoelectric response for such a material system

Canine Fibroblast Growth Factor 21 Ameliorates Hyperglycemia Associated with Inhibiting Hepatic Gluconeogenesis and Improving Pancreatic Beta-Cell Survival in Diabetic Mice and Dogs

<div><p>Diabetes mellitus is a common endocrinopathy in dog. Fibroblast growth factor 21 (FGF-21) is a secreted protein, which is involved in glucose homeostasis. We speculate that the recombinant canine FGF-21 (cFGF-21) has the potential to become a powerful therapeutics to treat canine diabetes. The cFGF-21 gene was cloned and expressed in <i>E</i>. <i>coli</i> Rosetta (DE3). After purification, a cFGF-21 protein with the purity exceeding 95% was obtained. Mouse 3T3-L1 adipocytes and type 1 diabetic mice/dogs induced by STZ were used to examine the biological activity of cFGF-21 <i>in vitro</i> and <i>in vivo</i>, respectively. Results showed that cFGF-21 stimulated glucose uptake in adipocytes significantly in a dose-dependent manner, and reduced plasma glucose significantly in diabetic mice/dogs. After treatment with cFGF-21, the serum insulin level, glycosylated hemoglobin (HbA1c) level and the expressions of the hepatic gluconeogenesis genes (glucose-6-phosphatase, G6Pase and phosphoenolpyruvate carboxykinase, PCK) of the diabetic mice/dogs were attenuated significantly. In the mouse experiment, we also found that the phosphorylation of signal transducer and activator of transcription 3 (STAT3) and the expression of suppressor of cytokine signaling 3 (SOCS3) were up-regulated significantly in the livers after treatment. Histopathological and immunohistochemical results showed that treatment with cFGF-21 promoted recovery of pancreatic islets from STZ-induced apoptosis. Besides, we also found that treatment with cFGF-21 protected liver against STZ or hyperglycemia induced damage and the mechanism of this action associated with inhibiting oxidative stress. In conclusion, cFGF-21 represents a promising candidate for canine diabetes therapeutics. The mechanism of cFGF-21 ameliorates hyperglycemia associated with inhibiting hepatic gluconeogenesis by regulation of STAT3 signal pathway and improving pancreatic beta-cell survival.</p></div