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Objective When mining travel characteristics from urban rail transit travel trajectory data, passenger travel activity patterns are found closely related to the stations near their residence and workplace. This is reflected in their travel trajectories by fixed boarding/alighting routes and concentrated entry/exit stations. Meanwhile, passenger travel trajectories associated with residence and workplace exhibit certain fluctuations, and the travel data strongly related to workplace-residence often differ significantly from other travel data. To accurately extract passenger travel trajectory characteristics, it is essential to clarify the residence-workplace relationship within urban rail transit passenger travel data. Method A mechanism for mining travel characteristics and classifying passengers based on residence-workplace relationship is proposed. The preliminary workplace-residence judgments are formed by identifying the hotspots of passenger trajectory activities related to residence, workplace and social activity locations. Then, the spatio-temporal patterns strongly associated with workplace-residence are explored. A K-means clustering algorithm extracted on the basis of passenger travel trajectory characteristic values is used to cluster passengers according to their residence-workplace judgment, resulting in a passenger classification method that precisely matches the passenger travel characteristics. Result & Conclusion Simulation validation results indicate that passengers with clearly defined residence-workplace relationship exhibit four distinct travel patterns of two-point, two-point-two-line, three-point, and multi-point. These travel pattern classification results make up a crucial technical foundation for constructing detailed passenger profiles and developing intelligent security check strategies.

Human activities have increased the input of nitrogen (N) to forest ecosystems and have greatly affected litter decomposition and the soil environment. But differences in forests with different nitrogen deposition backgrounds. To better understand the response of litter decomposition and soil environment of N-limited forest to nitrogen deposition. We established an in situ experiment to simulate the effects of N deposition on soil and litter ecosystem processes in a Picea schrenkiana forest in the Tianshan Mountains, China. This study included four N treatments: control (no N addition), low N addition (LN: 5 kg N ha-1 a-1), medium N addition (MN: 10 kg N ha-1 a-1) and high N addition (HN: 20 kg N ha-1 a-1). Our results showed that N addition had a significant effect on litter decomposition and the soil environment. Litter mass loss in the LN treatment and in the MN treatment was significantly higher than that in the control treatment. In contrast, the amount of litter lost in the HN treatment was significantly lower than the other treatments. N application inhibited the degradation of lignin but promoted the breakdown of cellulose. The carbon (C), N, and phosphorus (P) contents of litter did not differ significantly among the treatments, but LN promoted the release of C and P. Our results also showed that soil pH decreased with increasing nitrogen application rates, while soil enzyme activity showed the opposite trend. In addition, the results of redundancy analysis (RDA) and correlation analyses showed that the soil environment was closely related to litter decomposition. Soil enzymes had a positive effect on litter decomposition rates, and N addition amplified these correlations. Our study confirmed that N application had effects on litter decomposition and the soil environment in a N-limited P. schrenkiana forest. LN had a strong positive effect on litter decomposition and the soil environment, while HN was significantly negative. Therefore, increased N deposition may have a negative effect on material cycling of similar forest ecosystems in the near future.

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Abstract There is considerable potential for integrating transarterial chemoembolization (TACE), programmed death-(ligand)1 (PD-[L]1) inhibitors, and molecular targeted treatments (MTT) in hepatocellular carcinoma (HCC). It is necessary to investigate the therapeutic efficacy and safety of TACE combined with PD-(L)1 inhibitors and MTT in real-world situations. In this nationwide, retrospective, cohort study, 826 HCC patients receiving either TACE plus PD-(L)1 blockades and MTT (combination group, n = 376) or TACE monotherapy (monotherapy group, n = 450) were included from January 2018 to May 2021. The primary endpoint was progression-free survival (PFS) according to modified RECIST. The secondary outcomes included overall survival (OS), objective response rate (ORR), and safety. We performed propensity score matching approaches to reduce bias between two groups. After matching, 228 pairs were included with a predominantly advanced disease population. Median PFS in combination group was 9.5 months (95% confidence interval [CI], 8.4–11.0) versus 8.0 months (95% CI, 6.6–9.5) (adjusted hazard ratio [HR], 0.70, P = 0.002). OS and ORR were also significantly higher in combination group (median OS, 19.2 [16.1–27.3] vs. 15.7 months [13.0–20.2]; adjusted HR, 0.63, P = 0.001; ORR, 60.1% vs. 32.0%; P