End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation

Multivariate time series forecasting with hierarchical structure is pervasive in real-world applications, demanding not only predicting each level of the hierarchy, but also reconciling all forecasts to ensure coherency, i.e., the forecasts should satisfy the hierarchical aggregation constraints. Moreover, the disparities of statistical characteristics between levels can be huge, worsened by non-Gaussian distributions and non-linear correlations. To this extent, we propose a novel end-to-end hierarchical time series forecasting model, based on conditioned normalizing flow-based autoregressive transformer reconciliation, to represent complex data distribution while simultaneously reconciling the forecasts to ensure coherency. Unlike other state-of-the-art methods, we achieve the forecasting and reconciliation simultaneously without requiring any explicit post-processing step. In addition, by harnessing the power of deep model, we do not rely on any assumption such as unbiased estimates or Gaussian distribution. Our evaluation experiments are conducted on four real-world hierarchical datasets from different industrial domains (three public ones and a dataset from the application servers of Alipay's data center) and the preliminary results demonstrate efficacy of our proposed method

SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies

Multivariate time series forecasting with hierarchical structure is widely used in real-world applications, e.g., sales predictions for the geographical hierarchy formed by cities, states, and countries. The hierarchical time series (HTS) forecasting includes two sub-tasks, i.e., forecasting and reconciliation. In the previous works, hierarchical information is only integrated in the reconciliation step to maintain coherency, but not in forecasting step for accuracy improvement. In this paper, we propose two novel tree-based feature integration mechanisms, i.e., top-down convolution and bottom-up attention to leverage the information of the hierarchical structure to improve the forecasting performance. Moreover, unlike most previous reconciliation methods which either rely on strong assumptions or focus on coherent constraints only,we utilize deep neural optimization networks, which not only achieve coherency without any assumptions, but also allow more flexible and realistic constraints to achieve task-based targets, e.g., lower under-estimation penalty and meaningful decision-making loss to facilitate the subsequent downstream tasks. Experiments on real-world datasets demonstrate that our tree-based feature integration mechanism achieves superior performances on hierarchical forecasting tasks compared to the state-of-the-art methods, and our neural optimization networks can be applied to real-world tasks effectively without any additional effort under coherence and task-based constraint

Biocompatible Single-Crystal Selenium Nanobelt Based Nanodevice as a Temperature-Tunable Photosensor

Selenium materials are widely used in photoelectrical devices, owing to their unique semiconductive properties. Single-crystal selenium nanobelts with large specific surface area, fine photoconductivity, and biocompatibility provide potential applications in biomedical nanodevices, such as implantable artificial retina and rapid photon detector/stimulator for optogenetics. Here, we present a selenium nanobelt based nanodevice, which is fabricated with single Se nanobelt. This device shows a rapid photo response, different sensitivities to visible light of variable wave length, and temperature-tunable property. The biocompatibility of the Se nanobelts was proved by MTT test using two cell lines. Our investigation introduced a photosensor that will be important for multiple potential applications in human visual system, photocells in energy or MEMS, and temperature-tunable photoelectrical device for optogenetics research

High Proportion of 22q13 Deletions and SHANK3 Mutations in Chinese Patients with Intellectual Disability

Intellectual disability (ID) is a heterogeneous disorder caused by chromosomal abnormalities, monogenic factors and environmental factors. 22q13 deletion syndrome is a genetic disorder characterized by severe ID. Although the frequency of 22q13 deletions in ID is unclear, it is believed to be largely underestimated. To address this issue, we used Affymetrix Human SNP 6.0 array to detect the 22q13 deletions in 234 Chinese unexplained ID patients and 103 controls. After the Quality Control (QC) test of raw data, 22q13 deletions were found in four out of 230 cases (1.7%), while absent in parents of the cases and 101 controls. A review of genome-wide microarray studies in ID was performed and the frequency of 22q13 deletions from the literatures was 0.24%, much lower than our report. The overlapping region shared by all 4 cases encompasses the gene SHANK3. A heterozygous de novo nonsense mutation Y1015X of SHANK3 was identified in one ID patient. Cortical neurons were prepared from embryonic mice and were transfected with a control plasmid, shank3 wild-type (WT) or mutant plasmids. Overexpression of the Y1015 mutant in neurons significantly affected neurite outgrowth compared with shank3 WT. These findings suggest that 22q13 deletions may be a more frequent cause for Chinese ID patients than previously thought, and the SHANK3 gene is involved in the neurite development

Cofilin-1 is involved in regulation of actin reorganization during influenza A virus assembly and budding

Influenza A virus (IAV) assembly and budding on host cell surface plasma membrane requires actin cytoskeleton reorganization. The underlying molecular mechanism involving actin reorganization remains unclarified. In this study, we found that the natural antiviral compound petagalloyl glucose (PGG) inhibits F-actin reorganization in the host cell membrane during the late stage of IAV infection, which are associated with the suppression of total cofilin-1 level and its phosphorylation. Knock-down of cofilin-1 reduces viral yields. These findings provide the first evidence that cofilin-1 plays an important role in regulating actin reorganization during IAV assembly and budding

Study on Spatial Geometric Similarity Based on Conformal Geometric Algebra

The study of spatial geometric similarity plays a significant role in spatial data retrieval. Many researchers have examined spatial geometric similarity, which is useful for spatial analysis and data retrieval. However, the majority of them focused on objects of the same type. Methods to support the spatial geometric similarity computation for different types of objects are rare, a systematic theory index has not been developed yet, and there has not been a comprehensive computational model of spatial geometric similarity. In this study, we conducted an analysis of the spatial geometric similarity computation based on conformal geometric algebra (CGA), which has certain advantages in the quantitative computation of the measurement information of spatial objects and the qualitative judgment of the topological relations of spatial objects. First, we developed a unified expression model for spatial geometric scenes, integrating shapes of objects and spatial relations between them. Then, we established a model for the spatial geometric similarity computation under various geographical circumstances to provide a novel approach for spatial geometric similarity research. Finally, the computation model was verified through a case study. The study of spatial geometric similarity sheds light on spatial data retrieval, which has scientific significance and practical value

House Age, Price and Rent: Implications from Land-Structure Decomposition

Big cities often witness land price outgrowing structure price. For such cities this paper derives two predictions regarding the dynamics between house prices, rent and structure age. First, older houses have a higher price growth rate than younger ones, even after controlling for location and other attributes; second, the age depreciation of house price, defined as the decline of house price with respect to house age, is slower than the similarly-defined age depreciation of rent. These hypotheses are supported by the micro-data on housing market in Beijing. These two inferences have implications for both real estate valuation and house price index construction. Keywords: Land price, Structure price, House prices, Rent, DepreciationNational Natural Science Foundation (China) (71625004)National Natural Science Foundation (China) (71273154)National Natural Science Foundation (China) (71322307)National Natural Science Foundation (China) (71533004)China. Ministry of Science and Technology. National Key Technologies R&D Program (2016YFC0502804

A Circular-Arc-Type Magnetic Coupler with Strong Misalignment Tolerance for AUV Wireless Charging System

The wireless charging system (WCS) is widely employed to solve the problem of underwater charging of autonomous underwater vehicles (AUVs). However, the AUV is prone to misalignment caused by the tidal currents, which directly leads to fluctuations in transmission efficiency and output power. For this reason, a circular-arc-type (CA-type) magnetic coupler with strong misalignment tolerance was proposed in this article. Compared with the ring-type magnetic coupler, the proposed magnetic coupler had better magnetic field convergence and lower weight. Further, the effect of dimensional parameters on the CA-type magnetic coupler performance was analyzed by ANSYS Maxwell, with which the parameters of the magnetic coupler were optimized, and its coupling coefficient could finally reach 0.671. To analyze the influence of misalignment on the CA-type magnetic coupler, EE-type and UI-type magnetic cores are compared. Within the same range of rotation misalignment [−10°, 10°] and axial misalignment [−30, 30 mm], the CA-type magnetic core has stronger misalignment adaptability, and it can achieve a stable output power of 575 W and DC-DC efficiency of 92.51% when rotational misalignment occurs. A WCS experimental prototype is built based on one of the magnetic couplers and its experimental results verify the correctness of the theoretical analysis and simulation results

Comparison and Optimization of a Magnetic Lead Screw Applied in Wave Energy Conversions

In order to improve the power density of the wave power generation system, a magnetic lead screw (MLS) is introduced in this paper as a speed-increasing device in a wave energy converter (WEC), which converts low-speed linear wave motion to high-speed rotational motion. Then, several types of MLSs with different topologies, which were optimized, are described. Finite element analysis (FEA) was used to investigate and evaluate their electromagnetic performances, such as the thrust force, torque, air gap magnetic density, etc. The optimized MLS prototype was manufactured, and the measurements verify the FEA results. Finally, a magnetic lead screw hybrid generator (MLSHG) for application to the WEC is proposed. This MLS significantly improved the power density under different wave conditions. When the moving speed v = 0.15 m/s, the output power of the MLSHG and outer-PM linear tubular generator were 923 W and 87 W, respectively, when the load resistance was 5 Ω. The output power of the MLSHG was more than 10 times compared to that of the outer-PM linear tubular generator in a fair comparison. Here, it is shown that the power density and output power of were MLSHG increased greatly

Detent Force Reduction in Linear Interior Permanent Magnet Generator for Direct-Drive Wave Power Conversion

The permanent magnet linear generator is widely applied in the direct-drive wave energy converter (DD-WEC) because of its high power density. In this paper, a novel tubular permanent magnet linear generator, which consists of multilayer and interior permanent magnets (MI-TLPMGs), is presented for DD-WEC, which improves the output power and back electromotive force (back EMF) through the flux concentrating effect. However, MI-TLPMGs with multilayer embedded permanent magnets have severe problems regarding force ripples and detent force, which affect the DD-WEC’s dynamics. Therefore, a DD-WEC system with MI-TLPMGs is proposed, and the effect of the detent force on the dynamic performance of the DD-WEC is analyzed theoretically. Then, the L-type auxiliary teeth and magnetic barriers, which are optimized by the Taguchi method, are introduced to minimize the detent force of the MI-TLPMGs. After optimization using the Taguchi method, the amplitude of the detent force is reduced from the initial 21.7 N to 5.2 N, which means it has weakened by nearly 76.1%. Finally, a prototype has been manufactured and measured in the wave tank to verify the optimization results