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The present work focuses on the state‐of‐charge (SOC) estimation of a lithium‐ion battery in terms of a second‐order extended Kalman filter (EKF). First, an equivalent circuit model is introduced to describe the performance of lithium‐ion batteries. The model parameters are then identified through hybrid pulse power characterization experiments conducted over a wide range of temperatures (−10 to 55°C). A two‐dimensional mathematical relationship is established with respect to the SOC and temperature based on a dual‐fifth polynomial expression. The main effects and sensitivities of the SOC and temperature on the parameters are analysed according to the principle of variance analysis and partial derivatives. An estimation algorithm is developed, which combines the two‐dimensional parameter model and second‐order EKF. Finally, the proposed approach is validated compared to other estimation schemes through discharge experiments under extreme temperatures and dynamic loading profiles, which yields experimental results that estimate the SOC with an absolute error of less than 4.5% under harsh conditions. This not only demonstrates that it can characterize dependency of the model parameters on the operating conditions and address the uncertainty of model parameters, but also verifies the advantage of present method at low temperatures especially at sub‐zero temperatures.

The inconsistency of lithium-ion cells degrades battery performance, lifetime and even safety. The complexity of the cell reaction mechanism causes an irregular asymmetrical distribution of various cell parameters, such as capacity and internal resistance, among others. In this study, the Newman electrochemical model was used to simulate the 1C discharge curves of 100 LiMn2O4 pouch cells with parameter variations typically produced in manufacturing processes, and the three-parameter Weibull probability model was used to analyze the dispersion and symmetry of the resulting discharge voltage distributions. The results showed that the dispersion of the voltage distribution was related to the rate of decrease in the discharge voltage, and the symmetry was related to the change in the rate of voltage decrease. The effect of the cells’ capacity dominated the voltage distribution thermodynamically during discharge, and the phase transformation process significantly skewed the voltage distribution. The effects of the ohmic drop and polarization voltage on the voltage distribution were primarily kinetic. The presence of current returned the right-skewed voltage distribution caused by phase transformation to a more symmetrical distribution. Thus, the Weibull parameters elucidated the electrochemical behavior during the discharge process, and this method can guide the prediction and control of cell inconsistency, as well as detection and control strategies for cell management systems.

In electric vehicles (EVs), owing to the necessity of large amounts of energy and power, lithium-ion batteries need to be used in series and parallel configurations. However, the performance of the battery pack is lower than that of any single cell within the pack because of the inconsistency among the packed cells. Herein, the inconsistent voltages of unpacked cells due to varying capacities during discharge are analyzed to provide mechanical reason for inconsistency of battery pack. In terms of dispersion and symmetry, the statistical characteristics of voltage distribution are described using Weibull parameters and is investigated using a numerical analysis of the characteristic voltage curve. The numerical analysis results agree well with the experimental and statistical ones, which confirms that voltage inconsistency originating from manufacturing processes is primarily related with capacity inconsistency and the features of the voltage curves. Furthermore, this numerical approach can provide not only significant theoretical insight into the formation and evaluation of voltage inconsistency; but also practical guidance for controlling the quality of cell production and state estimation for the battery pack due to its low computational cost.

Most pedestrian trajectory prediction methods rely on a huge amount of trajectories annotation, which is time-consuming and expensive. Moreover, a well-trained model may not effectively generalize to a new scenario captured by another camera. Therefore, it is desirable to adapt the model trained on an annotated source domain to the target domain. To achieve domain adaptation for trajectory prediction, we propose a Cross-domain Trajectory Prediction Network (CTP-Net). In this framework, encoders are used in both domains to encode the observed trajectories, then their features are aligned by a cross-domain feature discriminator. Further, considering the consistency between the observed and the predicted trajectories, a target domain offset discriminator is utilized to adversarially regularize the future trajectory predictions to be in line with the observed trajectories. Extensive experiments demonstrate the effectiveness of our method on domain adaptation for pedestrian trajectory prediction., Work is accepted by CICAI(CAAI International Conference on Artificial Intelligence), 12 pages

Additional file 2: Table S1. Relative risk (RR) and 95% confidence intervals (95% CI) for low and high temperatures associated with daily AS outpatient over different lag days in Hefei, China, from January 2014 to December 2019. Table S2. Relative risk (RR) and 95% confidence intervals (95% CI) for low and high relative humidity associated with daily AS outpatient visits over different lag days in Hefei, China, from January 2014 to December 2019.

Additional file 1: Fig. S1. Data selection process. Fig. S2. Effects for cold weather (1st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 7 dfs per year was used to control the seasonal patterns and long term trends. Fig. S3. Effects for cold weather (1st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 9 dfs per year was used to control the seasonal patterns and long term trends. Fig. S4. Effects for cold weather (1st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 4 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S5. Effects for cold weather (1st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 5 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S6. Effects for hot weather (99st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 7 dfs per year was used to control the seasonal patterns and long term trends. Fig. S7. Effects for hot weather (99st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 9 dfs per year was used to control the seasonal patterns and long term trends. Fig. S8. Effects for hot weather (99st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 4 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S9. Effects for hot weather (99st percentiles of temperature) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 5 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S10. Effects for dry weather (1st percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 7 dfs per year was used to control the seasonal patterns and long term trends. Fig. S11. Effects for dry weather (1st percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 9 dfs per year was used to control the seasonal patterns and long term trends. Fig. S12. Effects for dry weather (1st percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 4 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S13. Effects for dry weather (1st percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 5 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S14. Effects for damp weather (99th percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 7 dfs per year was used to control the seasonal patterns and long term trends. Fig. S15. Effects for damp weather (99th percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 3 dfs was used to control environmental factors, 9 dfs per year was used to control the seasonal patterns and long term trends. Fig. S16. Effects for damp weather (99th percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 4 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends. Fig. S17. Effects for damp weather (99th percentiles of relative humidity) on daily outpatient visits for AS at lag 0–7 day; A nature cubic spline with 5 dfs was used to control environmental factors, 8 dfs per year was used to control the seasonal patterns and long term trends.

This study evaluated the screening of Sudan dyes in salty egg using liquid chromatography/time-of-flight mass spectrometry (LC–TOF-MS). With this technology, accurate mass measurements were made to generate elemental compositions of ions and to provide complementary structural information. This approach is useful for the elucidation of organic pollutants at trace levels in complex food extracts and in the present study salty egg samples were analyzed for the presence of Sudan IV. TOF accurate mass elemental composition data of Sudan IV were found to be crucial for structural elucidation which was applied to the investigation of nine salty egg samples.

In this work, a new multiresidue methodology using liquid chromatography‐time‐of‐flight‐mass spectrometry (LC‐TOF‐MS) for the quantitative analysis of pesticide residues has been developed. The accurate mass was obtained in different levels (from 0.02 to 0.10 mg · kg−1) and accuracy errors was lower than 3 ppm, which is well within the accepted limits for target confirmation. Linearity of response ranged from 0.01 mg · kg−1 to 1 mg · kg−1. The average recoveries of nine urea herbicides in spiked soybean ranged from 70.16% to 114.41%, and the relative standard deviations (RSD) were between 2.22% and 11.12%. Limits of detection (LOD) were between 0.00003 and 0.009 mg · kg−1. The results indicated that the method developed was easier, faster, and more sensitive. It also demonstrated that this method could meet the requirements for simultaneous determination of urea herbicides in soybean. This study provides valuable evidence for that LC‐TOF‐MS method has the potential in screening multi‐residue pest...

Multi-growth approaches including pulsed atomic layer epitaxy and high temperature continuous growth were used to deposit AlN layers on sapphire. The results show that the crystal quality can be significantly improved by the this technique.

Wide-bandgap perovskite solar cells (PSCs) are attracting increasing attention because they play an irreplaceable role in tandem solar cells. Nevertheless, wide-bandgap PSCs suffer large open-circuit voltage (V-OC) loss and instability due to photoinduced halide segregation, significantly limiting their application. Herein, a bile salt (sodium glycochenodeoxycholate, GCDC, a natural product), is used to construct an ultrathin self-assembled ionic insulating layer firmly coating the perovskite film, which suppresses halide phase separation, reduces V-OC loss, and improves device stability. As a result, 1.68 eV wide-bandgap devices with an inverted structure deliver a V-OC of 1.20 V with an efficiency of 20.38%. The unencapsulated GCDC-treated devices are considerably more stable than the control devices, retaining 92% of their initial efficiency after 1392 h storage under ambient conditions and retaining 93% after heating at 65 degrees C for 1128 h in an N-2 atmosphere. This strategy of mitigating ion migration via anchoring a nonconductive layer provides a simple approach to achieving efficient and stable wide-bandgap PSCs.