Search

crucial for transportation management. However, traditional spatial-temporal deep learning models grapple with addressing the sparse and long-tail characteristics in high-resolution O-D matrices and quantifying prediction uncertainty. This dilemma arises from the numerous zeros and over-dispersed demand patterns within these matrices, which challenge the Gaussian assumption inherent to deterministic deep learning models. To address these challenges, we propose a novel approach: the Spatial-Temporal Tweedie Graph Neural Network (STTD). The STTD introduces the Tweedie distribution as a compelling alternative to the traditional 'zero-inflated' model and leverages spatial and temporal embeddings to parameterize travel demand distributions. Our evaluations using real-world datasets highlight STTD's superiority in providing accurate predictions and precise confidence intervals, particularly in high-resolution scenarios., Comment: In submission to CIKM 2023

Additional file 1:Supplementary Fig. 1. Flow chart of data analysis in this study. Supplementary Table 1. Parameters of two risk equations used in this study for men and women. Supplementary Table 2. Comparison of research objects between man and woman. Supplementary Table 3.1. Screening variable subsets based on Cox regression in man. Supplementary Table 3.2. Screening variable subsets based on Lasso-Cox regression in man. Supplementary Table 3.3. Screening variable subsets based on RSF in man. Supplementary Table 3.4. Screening variable subsets based on Cox regression in woman. Supplementary Table 3.5. Screening variable subsets based on Lasso-Cox regression in woman. Supplementary Table 3.6. Screening variable subsets based on RSF in woman. Supplementary Table 4. C statistic of different models on training and test sets.

Based on digital coaxial holography image technology, a laser coaxial digital holographic tool setting device is built. The tool hologram was obtained by using the same laser and different power irradiation. The sharpest reconstruction image was obtained by using the focusing evaluation function of wavelet transform and piecewise-progressive search algorithm. Then, the improved self-snake filter was used to process the image, and the tool contour was extracted by using the Sobel operator. At the maximum threshold corresponding to the clear tool profile can be obtained, the tool profile under different laser power was compared. Finally the most suitable laser power for digital holographic tool setting device was obtained.

Objectives This study intended to investigate the dynamics of anti-spike (S) IgG and IgM antibodies in COVID-19 patients. Methods Anti-S IgG/IgM was determined by a semi-quantitative fluorescence immunoassay in the plasma of COVID-19 patients at the manifestation and rehabilitation stages. The immunoreactivity to full-length S proteins, C-terminal domain (CTD), and N-terminal domain (NTD) of S1 fragments were determined by an ELISA assay. Clinical properties at admission and discharge were collected simultaneously. Results The positive rates of anti-S IgG/IgM in COVID-19 patients were elevated after rehabilitation compared to the in-patients. Anti-S IgG and IgM were not apparent until day 14 and day ten, respectively, according to Simple Moving Average analysis with five days’ slide window deduction. More than 90% of the rehabilitation patients exhibited IgG and IgM responses targeting CTD-S1 fragments. Decreased total peripheral lymphocytes, CD4+ and CD8+ T cell counts were seen in COVID-19 patients at admission and recovered after the rehabilitation. Conclusions Anti-S IgG and IgM do not appear at the onset with the decrease in T cells, making early serological screening less significant. However, the presence of high IgG and IgM to S1-CTD in the recovered patients highlights humoral responses after SARS-CoV-2 infection, which might be associated with efficient immune protection in COVID-19 patients.

Ti6A14V alloy is widely used in military, biological and chemical fields. Therefore, the research on the surface integrity of Ti6A14V milling is highly concerned at home and abroad. In this paper, the influence of cutting parameters on surface integrity of Ti6A14V is studied, which provides experimental data reference for surface integrity control. The conclusions show that the cutting surface roughness, cutting force and surface residual stress decrease with the increase of spindle speed, and increase with the increase of feed rate and cutting depth. With increased of spindle speed, the milling temperature first decreases and then increases. With increased of feed rate and milling depth, the milling temperature gradually increased.

To explore the effect of miR-199a-5p and AKT signal pathway on cognitive function and neuronal cells in rats with ischemic stroke. Sprague-Dawley rats were divided into 6 groups: Normal group (normal rats), Sham group (rats received sham operation), Model group (MCAO rats), miR-199a-5p inhibitor group (model rats treated with miR-199a-5p inhibitor), IGF-1 group (model rats treated with AKT signaling pathway activator), miR-199a-5p inhibitor + IGF-1 group (model rats treated by miR-199a-5p inhibitor and AKT signaling pathway activator). Rat behavior and cerebral infarction area were observed. TUNEL fluorescence staining was used to detect neuronal apoptosis in hippocampal CA1 region of rats. The dual luciferase reporter assay validated the targeting relationship between miR-199a-5p and AKT. qRT-PCR and WB were used to detect the expression level of miR-199a-5p, (p)-AKT and (p)-mTOR, apoptosis-related proteins Bax and Bcl-2. Compared with the normal group, the expression of miR-199a-5p was increased in the Model group, and the expression levels of AKT, mTOR, p-AKT, and p-mTOR were decreased (all P < 0.05); the cognitive function of the rats in the Model group was thereby significantly lower (P < 0.05). miR-199a-5p was targeted to inhibit AKT. Compared with the Model group, miR-199a-5p inhibition combined with IGF-1 showed more significant effects on improving cognitive function and protecting neuronal cells of rats. In conclusion, silencing miR-199a-5p can effectively improve cognitive function in ischemic stroke rats and decrease neuronal apoptosis in hippocampus by activating the AKT signaling pathway.

Aiming at the various shortcomings of existing tool setting methods, this paper proposes a coaxial holographic tool setting method for tiny tools. Based on the research and analysis of the principle of holographic imaging and the key issues of holographic images, a set of holographic tool setting detection device for micro milling tool was built, and the micro milling tool measurement was carried out on the five-axis machining center using standard tools. experiment. Experimental results show that the tool setting device can efficiently perform tool setting detection of micro-milling tool. Compared with the measurement results of the high-precision external presetting instrument, the relative error of the contact tool setting instrument is 0.033%, and the relative error of the holographic tool setting prototype is 0.007%, which is more effective in realizing the tool setting of tiny tools. Detection. This result verifies the feasibility of the coaxial holographic tool setting method for micro tool, that is, holographic measurement can be used for high-precision tool setting of micro milling tool.

According to the characteristics of micro parts microscopic detection image, including the image texture is similar, the edge information is too little and the gray distribution Range is limited, based on the basic principles of algorithm, analyzes the traditional sharpness evaluation function. Aiming at the defect that the traditional sharpness evaluation function cannot have both high sensitivity and noise immunity, an algorithm based on local variance information entropy is proposed. The method uses the local variance to weight the self-information of each gray level, on the one hand, it makes up for the lack of spatial information of information entropy and avoids misjudgement of sharpness; on the other hand, it can increase the weights of clear region pixels when they participate in the calculation of information, while reducing the weights of background and noise region pixels, thereby improve the function sensitivity. The experimental results show that compared with the traditional sharpness evaluation function, the local variance information entropy function not only has high sensitivity, but also has better noise immunity and is suitable for actual auto-focusing systems.

In the process of ultra-precision machining, the tool-setting accuracy of the micro-milling tool is limited by the tool diameter. The accuracy of tool setting decreases with the decrease of tool diameter, which becomes an important factor for restricting the accuracy of ultra-precision machining. Based on the imaging principle of digital in-line holography, an efficient and non-contacted method for tool setting was proposed for improving the accuracy of tool setting. Aiming at the imaging problem of micro-milling tool, the evaluation function based on wavelet transform was introduced in the process of progressive search, so the optimal reconstructed image was accurately obtained through the autofocusing algorithm. Then the zero-order term and the conjugate image were eliminated via the self-snake diffusion. The tool contour was extracted by Sobel operator, and tool diameter was measured using different methods. Measurement results proved that holographic imaging can meet the requirements of in-position dynamic measurement for micro-milling tools, and also provided an important basis for the accuracy of tool setting.

In this paper, the milling experiments of the 7075 Aluminum alloy thin wall specimens are carried out. In the dry cutting under the experimental conditions, the hard alloy cutter the use of the 7075 Aluminum alloy milling can get better quality of the thin-walled specimens, machining, cutting and cutting edge burr and the source, the chip adhesion phenomenon, in the selection of cutting speed for variable conditions, with the increase of cutting speed, milling of thin-walled specimen deformation gradually becomes smaller the thin, the specimen surface residual stress gradually increase, in the selection of feed speed conditions within the range of variables, with the increase of feed speed, the 7075 Aluminum alloy milling of thin-walled specimens. The deformation degree increased, thin specimen surface residual stress decreases gradually, in the selection of cutting depth conditions the range of variables, with the increase of cutting depth, the 7075 Aluminum alloy test milling of thin-walled parts is the greater the degree of deformation, thin-walled specimen surface residual stress was gradually decreased, residual stress the hour gradually thin plate specimens deformation amount is small, the milling of thin-walled specimens after deformation is inevitable.

The high prevalence of metabolic syndrome (MetS) and cardiovascular diseases (CVD) is observed among Kazakhs in Xinjiang. Because MetS may significantly predict the occurrence of CVD, the inclusion of CVD-related indicators in metabolic network may improve the predictive ability for a CVD-risk model for Kazakhs in Xinjiang.The study included 2,644 subjects who were followed for 5 years or longer. CVD cases were identified via medical records of the local hospitals from April 2016 to August 2017. Factor analysis was performed in 706 subjects (267 men and 439 women) with MetS to extract CVD-related potential factors from 18 biomarkers tested in a routine health check-up, served as a synthetic predictor (SP). We evaluated the predictive ability of the CVD-risk model using age and SP, logistic regression discrimination for internal validation (n = 384; men = 164, women = 220) and external validation (n = 219; men = 89, women = 130), calculated the probability of CVD for each participant, and receiver operating characteristic curves.According to the diagnostic criteria of JIS, the prevalence of MetS in Kazakh was 30.9%. Seven potential factors with a similar pattern were obtained from men and women and comprised the CVD predictors. When predicting CVD in the internal validation, the area under the curve (AUC) were 0.857 (95%CI 0.807-0.898) for men and 0.852 (95%CI 0.809-0.889) for women, respectively. In the external validation, the AUC to predict CVD were 0.914 (95%CI 0.832-0.963) for men and 0.848 (95%CI 0.774-0.905) for women. It is suggested that SP might serve as a useful tool in identifying CVD with in Kazakhs, especially for Kazakhs men.Among 7 potential factors were extracted from 18 biomarkrs in Kazakhs with MetS, and SP may be used for CVD risk assessment.

The titanium dioxide nanoparticles with high purity and specific surface area were synthesized through an alkali-solution and acid-isolation method with titanium slag as raw material. As a catalyst support of V2O5-WO3-MoO3/TiO2 selective catalytic reduction catalyst, the high specific surface area TiO2 nanoparticles can improve the low temperature activity of the catalyst and enhance its resistance to sulfur poisoning.

A carbon nanosheet is a new type of two-dimensional material that is fabricated by the electron-induced crosslinking of aromatic self-assembled monolayers. A novel bulge test in an atomic force microscope has been used to study the mechanical properties of carbon nanosheets. The elastic behavior was investigated by analyzing the pressure-deflection relationship in the bulge test. Young’s moduli of carbon nanosheets as a function of irradiation electron doses can be determined. With an electron dose above 50 mC/cm2, BPT nanosheets exhibit a stable Young’s modulus ranging from 6 GPa to 8 GPa and NBPT nanosheets ranging from 8 GPa to 10 GPa. CBPS nanosheets have a similar mechanical stiffness which appears to increase slightly at higher electron doses. The residual stresses that have been introduced into carbon nanosheets through the crosslinking and the transferring process are in the range of 40 to 100 MPa. In addition to the adhesion and corrugation of a carbon nanosheet on a SiO2 substrate, the adhesion between an AFM tip and a freestanding nanosheet was also estimated and analyzed. The viscoelasticity of carbon nanosheets was investigated with hysteresis, creep and stress relaxation being observed. We were able to probe the creep deformation with a strain rate above 1 percent and the resultant creep rates range from 10-6 s-1 to 6×10-6 s-1 with a dependence on stress levels. Recovery after creep unloading has also been demonstrated. The ultimate tensile strength of carbon nanosheets was also determined by performing bulge tests. BPT and NBPT nanosheets have tensile strength ranging from 400 MPa to 700 MPa. We fabricated multilayer carbon nanosheets and the average Young’s modulus is demonstrated to be very similar to that of the single layer carbon nanosheet. Overlapping reduces the possibility of a rupture of a monolayer because of defects. Therefore it improves the mechanical stability and enhances the yield of suspended multilayer nanosheets in even larger sizes. The structural transformation of carbon nanosheets upon annealing has been studied by various analytical techniques. From a mechanical point of view, annealing leads to a systematic increase of Young’s moduli with rising temperature, up to 48 GPa at ~1000 K. Finally, polymer brushes grafted on biphenyl-based nanosheets provided a new class of material termed as "polymer carpet". Both bulge test and nanoindentation were used to characterize the mechanical properties of polymer carpets. The polystyrene carpets experience a decrease in stiffness with decreases of thickness smaller than 20 nm. The polystyrene brush component has a Young’s modulus of ~1.3 GPa for the thinnest polystyrene carpet. With a thicknesses over 30 nm, Young’s moduli range from 3 GPa to 4 GPa.

2D Materials 7(2), 022001 (2020). doi:10.1088/2053-1583/ab1e0a, Published by IOP Publ., Bristol