We studied the movable singularities of solutions of autonomous non-algebraic first-order ordinary differential equations in the form of y′=I(y(t)) and y′=I1(y(t))+I2(y(t))+⋯+In(y(t)), aiming to ...prove that all movable singularities of all complex solutions of these equations are at most algebraic branch points. This study explores the use of the constructing triangle method to analyze complex solutions of autonomous non-algebraic first-order ordinary differential equations. For complex solutions in the form of y=w+iv, we treat the constructing triangle method as a way to construct a right-angled triangle in the complex plane, with the lengths of the adjacent sides being w and v. We use the definitions of the trigonometric functions sin and cos (the ratio of the adjacent side to the hypotenuse) to represent the trigonometric functions of complex solutions y=w+iv. Since the movable singularities of the inverse functions of trigonometric functions are easy to analyze, the properties of the movable singularities of the complex solutions are then easy to deal with.
FlowNet3D: Learning Scene Flow in 3D Point Clouds Liu, Xingyu; Qi, Charles R.; Guibas, Leonidas J.
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
06/2019
Conference Proceeding
Open access
Many applications in robotics and human-computer interaction can benefit from understanding 3D motion of points in a dynamic environment, widely noted as scene flow. While most previous methods focus ...on stereo and RGB-D images as input, few try to estimate scene flow directly from point clouds. In this work, we propose a novel deep neural network named FlowNet3D that learns scene flow from point clouds in an end-to-end fashion. Our network simultaneously learns deep hierarchical features of point clouds and flow embeddings that represent point motions, supported by two newly proposed learning layers for point sets. We evaluate the network on both challenging synthetic data from FlyingThings3D and real Lidar scans from KITTI. Trained on synthetic data only, our network successfully generalizes to real scans, outperforming various baselines and showing competitive results to the prior art. We also demonstrate two applications of our scene flow output (scan registration and motion segmentation) to show its potential wide use cases.
Compared to the numerous studies on the public’s seismic preparedness, few studies have focused on actual behavioral responses to earthquakes. According to an investigation of immediate public ...behavioral responses to an earthquake in the Beijing–Tianjin–Hebei region of China, this study found that the public’s response behaviors included two main patterns of self-protection and milling. It reveals that the adoption of a behavioral pattern is the result of a complex interaction of cultural and psychological factors related to fatalism and emotional response. Specifically, fatalism reduces the possibility of an individual engaging in self-protective activities. However, fear motivates a positive response. The findings in this study suggest that earthquake resilience can be enhanced through both cultural pathways and cognitive processes. These findings shed new light on earthquake behavioral science and aid policymakers in developing strategies for disaster education and emergency training, especially for people who hold fatalistic beliefs about disaster risk reduction.
State-of-the-art deep neural networks (DNNs) have hundreds of millions of connections and are both computationally and memory intensive, making them difficult to deploy on embedded systems with ...limited hardware resources and power budgets. While custom hardware helps the computation, fetching weights from DRAM is two orders of magnitude more expensive than ALU operations, and dominates the required power. Previously proposed 'Deep Compression' makes it possible to fit large DNNs (AlexNet and VGGNet) fully in on-chip SRAM. This compression is achieved by pruning the redundant connections and having multiple connections share the same weight. We propose an energy efficient inference engine (EIE) that performs inference on this compressed network model and accelerates the resulting sparse matrix-vector multiplication with weight sharing. Going from DRAM to SRAM gives EIE 120x energy saving, Exploiting sparsity saves 10x, Weight sharing gives 8x, Skipping zero activations from ReLU saves another 3x. Evaluated on nine DNN benchmarks, EIE is 189x and 13x faster when compared to CPU and GPU implementations of the same DNN without compression. EIE has a processing power of 102 GOPS working directly on a compressed network, corresponding to 3 TOPS on an uncompressed network, and processes FC layers of AlexNet at 1.88x104 frames/sec with a power dissipation of only 600mW. It is 24,000x and 3,400x more energy efficient than a CPU and GPU respectively. Compared with DaDianNao, EIE has 2.9x, 19x and 3x better throughput, energy efficiency and area efficiency.
Abstract Stem cells display sensitivity to substrate presentation of topographical cues via changes in cell morphology. These biomechanical responses may be transmitted to the nucleus through ...cytoskeletal-linked signaling pathways. Here we investigate the influence of aligned substratum topography on the cell morphology and subsequently, the neuronal differentiation capabilities of adult neural stem cells (ANSCs). ANSCs that were cultured on aligned fibers elongated along the major fiber axis. Upon induction of differentiation with retinoic acid, a higher fraction of cells on aligned fibers exhibited markers of neuronal differentiation as compared with cells on random fiber or unpatterned surfaces. This effect was in part due to substrate selectivity, whereby aligned fiber substrates were less receptive to the attachment and continued survival of oligodendrocytes than random fiber or unpatterned substrates. Substrate-induced elongation alone was also effective in upregulating canonical Wnt signaling in ANSCs, which was further potentiated by retinoic acid treatment. These findings suggest a mechanism by which morphological control of stem cells operates in concert with biochemical cues for cell fate determination.
Reasonable design of electrode materials is the key to solving the low energy density of the supercapacitors. Transition metal oxide Co3O4 material is commonly used in the field of supercapacitors, ...but the poor cycle stability limits its practical application. Herein, we report 0.3Mn-Co3O4 nanostructures grown on nickel foam by a facile one-step hydrothermal approach. The morphology of the samples can be regulated by the introduction of different amounts of Mn ions. The specific capacitance reaches 525.5 C/g at 1 A/g. The performance of 0.3Mn-Co3O4 material is significantly improved due to its excellent stability and conductivity, which makes it a suitable electrode material for supercapacitors. A flexible asymmetric device is also fabricated using the sample as the cathode. The assembled capacitor still possesses a desirable cycle stability after charging and discharging of 10,000 times, and its capacitance retention rate can reach 83.71%.
This study sought to purify and identify antioxidant peptides from sheep (Ovis aries) plasma protein hydrolysates and assess their protective impacts on H2O2‐induced Caco‐2 cells. The purification ...process involved reversed high‐performance liquid chromatography, anion‐exchange chromatography, and Sephadex G‐25. Three peptides, namely Trp‐Glu‐Glu‐Pro‐Ala‐Met (WEEPAM), Ser‐Leu‐His‐Phe‐Met‐Glu (SLHFME), and His‐Cys‐Thr‐Thr‐Phe‐Met‐Ile, with molecular weights of 761.84, 762.87, and 852.03 Da, respectively, were identified by liquid chromatography with tandem mass spectrometry. Among the three antioxidant peptides, superoxide radical (O2−) radical scavenging capacity of WEEPAM and SLHFME was not significantly different from glutathione (GSH) (p > 0.05), while their 1,1‐diphenyl‐2‐picrylhydrazyl radical scavenging capacity was greater than GSH (p < 0.05). WEEPAM revealed increased antioxidant activity after pepsin and trypsin hydrolysis under an in vitro digestion model. In addition, WEEPAM inhibited oxidative damage in Caco‐2 cells by significantly reducing reactive oxygen species accumulation, early apoptosis, malondialdehyde formation, and increasing intracellular superoxide dismutase, glutathione peroxidase, and catalase activities.
Microorganisms play a fundamental role in biogeochemical cycling and are highly sensitive to environmental factors, including the physiochemical properties of the soils and the concentrations of ...heavy metals/metalloids. In this study, high-throughput sequencing of the 16S rRNA gene was used to study the microbial communities of farmland soils in farmland in the vicinity of a lead–zinc smelter. Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, and Gemmatimonadetes were the predominant phyla in the sites of interest.
Sphingomonas
,
Gemmatimonas
,
Lysobacter
,
Flavisolibacter
, and
Chitinophaga
were heavy metal-/metalloid-tolerant microbial groups with potential for bioremediation of the heavy metal/metalloid contaminated soils. However, the bacterial diversity was different for the different sites. The contents of heavy metal/metalloid species and the soil properties were studied to evaluate the effect on the soil bacterial communities. The Mantel test revealed that soil pH, total cadmium (T-Cd), and available arsenic played a vital role in determining the structure of the microbial communities. Further, we analyzed statistically the heavy metals/metalloids and the soil properties, and the results revealed that the microbial richness and diversity were regulated mainly by the soil properties, which correlated positively with organic matter and available nitrogen, while available phosphorus and available potassium were negatively correlated. The functional annotation of the prokaryotic taxa (FAPROTAX) method was used to predict the function of the microbial communities. Chemoheterotrophy and airborne chemoheterotrophy of the main microbial community functions were inhibited by soil pH and the heavy metals/metalloids, except in the case of available lead. Mantel tests revealed that T-Cd and available zinc were the dominant factors affecting the functions of the microbial communities. Overall, the research indicated that in contaminated soils, the presence of multiple heavy metals/metalloids, and the soil properties synergistically shaped the structure and function of the microbial communities.
In the adult bone marrow, osteoblasts and adipocytes share a common precursor called mesenchymal stem cells (MSCs). The plasticity between the two lineages has been confirmed over the past decades, ...and has important implications in the etiology of bone diseases such as osteoporosis, which involves an imbalance between osteoblasts and adipocytes. The commitment and differentiation of bone marrow (BM) MSCs is tightly controlled by the local environment that maintains a balance between osteoblast lineage and adipocyte. However, pathological conditions linked to osteoporosis can change the BM microenvironment and shift the MSC fate to favor adipocytes over osteoblasts, and consequently decrease bone mass with marrow fat accumulation. This review discusses the changes that occur in the BM microenvironment under pathological conditions, and how these changes affect MSC fate. We suggest that manipulating local environments could have therapeutic implications to avoid bone loss in diseases like osteoporosis.
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