Learning-Initialized Trajectory Planning in Unknown Environments

Autonomous flight in unknown environments requires precise planning for both the spatial and temporal profiles of trajectories, which generally involves nonconvex optimization, leading to high time costs and susceptibility to local optima. To address these limitations, we introduce the Learning-Initialized Trajectory Planner (LIT-Planner), a novel approach that guides optimization using a Neural Network (NN) Planner to provide initial values. We first leverage the spatial-temporal optimization with batch sampling to generate training cases, aiming to capture multimodality in trajectories. Based on these data, the NN-Planner maps visual and inertial observations to trajectory parameters for handling unknown environments. The network outputs are then optimized to enhance both reliability and explainability, ensuring robust performance. Furthermore, we propose a framework that supports robust online replanning with tolerance to planning latency. Comprehensive simulations validate the LIT-Planner's time efficiency without compromising trajectory quality compared to optimization-based methods. Real-world experiments further demonstrate its practical suitability for autonomous drone navigation

Indirect influence in social networks as an induced percolation phenomenon

Significance Increasing empirical evidence in diverse social and ecological systems has shown that indirect interactions play a pivotal role in shaping systems’ dynamical behavior. Our empirical study on collaboration networks of scientists further reveals that an indirect effect can dominate over direct influence in behavioral spreading. However, almost all models in existence focus on direct interactions, and the general impact of indirect interactions has not been studied. We propose a new percolation process, termed induced percolation, to characterize indirect interactions and find that indirect interactions raise a plethora of new phenomena, including the wide range of possible phase transitions. Such an indirect mechanism leads to very different spreading outcomes from that of direct influences

The Effect of the Major-Grain-Producing-Areas Oriented Policy on Crop Production: Evidence from China

As a powerful actor in the global food system, China experienced a significant drop in crop production from 1998 to 2003, which posed a substantial threat to national food security and led to the establishment of 13 major grain-producing areas (MGPA). Although some qualitative research has found that the MGPA policy plays an important role in ensuring the national food security, quantitative evidence on the effect of the MGPA policy and its potential mechanism remains scarce. Based on China’s interprovincial panel data from 1998 to 2018, this study used a difference-in-differences (DD) estimation strategy to analyze the treatment effect of the MGPA policy by taking the assignment of 13 MGPA as a quasi-experiment. The results showed that the enforcement of the MGPA policy significantly increased crop production, especially in terms of grain, rice and wheat yields. The average grain yields were raised by 27.5%. The results of the event study analysis showed that the treatment effects were sustainable in the following years of the policy implementation. This study also explored alternative causal channels and found that the MGPA policy raised crop yields mainly by expanding planting areas, improving the level of mechanization and increasing transfer payments. These findings demonstrate the effectiveness of the MGPA policy in increasing crop production in a developing country setting, which could enlighten policymakers in some less well-developed countries on boosting crop production and maintaining food security

Technical Efficiency of Maize Production and Its Influencing Factors in the World’s Largest Groundwater Drop Funnel Area, China

Improving the efficiency of maize production is of great significance for global food security and the effective supply of agricultural products. Based on the survey data of 381 rural households, this study uses a stochastic frontier analysis to estimate the efficiency value and empirically analyze the factors affecting the technology efficiency of maize production in the Hengshui area of the North China Plain. First, higher costs were found to be related to extensive production methods of fertilization, pesticide application, and irrigation. Second, the results showed that there was an inverted U-shaped relationship between the irrigation cost and maize output. Specifically, when the irrigation cost was about 938 yuan/hectare, the maize output per unit area was optimal. Third, there was also an inverted U-shaped relationship between the fertilizer cost and maize output, and the loss of technical efficiency of maize output was minimal when the fertilizer cost is 2547 yuan/hectare. In addition, the findings of the inefficiency influencing factor model suggested that temperature and humidity were all positively associated with the non-efficiency of maize production. These findings can provide empirical support for improving the efficiency of maize production in North China or arid and semi-arid regions around the world

RESEARCH ON EMBEDDED SMART BEARING STRUCTURE ANALYSIS AND VIBRATION MONITORING SYSTEM DESIGN (MT)

Embedded smart bearing is a kind of structural unit with the characteristics of self sensing, self diagnosis, self-adaptive and self-regulation, which is one of the development directions of high-end bearing at home and abroad. Based on Ioannides-Harris theory, the load distribution of rolling bearing is analyzed. Combined with the finite element simulation model, the influence of outer ring grooving on bearing reliability is analyzed, and the radial grooving structure of outer ring of rolling bearing is determined. According to the theoretical analysis and numerical simulation, the embedded bearing vibration monitoring system is designed by combining the vibration sensor with the bearing body. By using the bearing life testing machine, the bearing life test is carried out and the vibration signals of smart bearings with different structures are collected. The experimental results show that the amplitude of vibration signal of smart bearing is higher than that of traditional bearing pedestal monitoring method, and it can effectively monitor the running state of the bearing; compared with the structure of axial grooving, the service life of the proposed smart bearing is similar to that of the ordinary bearing, which provides a new method for the condition monitoring and fault diagnosis of the rolling bearing

Physiologically‐based pharmacokinetic pharmacodynamic parent‐metabolite model of edoxaban to predict drug–drug‐disease interactions: M4 contribution

Abstract This study aimed to develop a physiologically‐based pharmacokinetic pharmacodynamic (PBPK/PD) parent‐metabolite model of edoxaban, an oral anticoagulant with a narrow therapeutic index, and to predict pharmacokinetic (PK)/PD profiles and potential drug–drug‐disease interactions (DDDIs) in patients with renal impairment. A whole‐body PBPK model with a linear additive PD model of edoxaban and its active metabolite M4 was developed and validated in SimCYP for healthy adults with or without interacting drugs. The model was extrapolated to situations including renal impairment and drug‐drug interactions (DDIs). Observed PK and PD data in adults were compared with predicted data. The effect of several model parameters on the PK/PD response of edoxaban and M4 was investigated in sensitivity analysis. The PBPK/PD model successfully predicted PK profiles of edoxaban and M4 as well as anticoagulation PD responses with or without the influence of interacting drugs. For patients with renal impairment, the PBPK model successfully predicted the fold change in each impairment group. Inhibitory DDI and renal impairment had a synergistic effect on the increased exposure of edoxaban and M4, and their downstream anticoagulation PD effect. Sensitivity analysis and DDDI simulation show that renal clearance, intestinal P‐glycoprotein activity, and hepatic OATP1B1 activity are the major factors affecting edoxaban‐M4 PK profiles and PD responses. Anticoagulation effect induced by M4 cannot be ignored when OATP1B1 is inhibited or downregulated. Our study provides a reasonable approach to adjust the dose of edoxaban in several complicated scenarios especially when M4 cannot be ignored due to decreased OATP1B1 activity

Effects of Different Land-Use Systems on Soil Aggregates: A Case Study of the Loess Plateau (Northern China)

Soil aggregate stability is an important indicator for controlling soil losses and can improve soil quality, particularly in an area such as the Loess Plateau. The objective of this study was to estimate the differences in soil aggregates across six different land-use systems (grassland, apple orchard, abandoned apple orchard, cropland maize, cropland wheat, and shrub-grassland). For this purpose, dry and wet sieving techniques were employed to assess aggregate content and aggregate stability. Higher percentages of water stable aggregates were observed in the abandoned apple orchard and shrub-grassland at 63% and 61%, respectively. The maximum dry aggregate stability (%) was recorded at 78% and 77% in both wheat cropland and common apple orchard, and the abandoned apple orchard was only 74%. Both mean weight diameters and geometric mean diameters of aggregate were recorded as higher in grassland, shrub-grassland, and the abandoned apple orchard, than the other land uses. The formation of soil aggregates and their stability were positively correlated with soil organic carbon content and root biomass of different plant communities. Higher amounts of soil organic carbon content were noted in the abandoned apple orchard, common apple orchard, and natural grassland at the 0–20 cm soil layer. The results of the correlation coefficient showed a positive significant correlation between the mean weight diameter, geometric diameter, root biomass, and soil organic carbon content. Conclusively, the type of land use affected the soil aggregation and distribution of size fractions; the small fractions of the aggregates formed large fractions by combining with fresh organic matter, and increased soil organic carbon concentrations were closely linked with the formation of macro-aggregates. Thus, converting slope farmland to forestland and grassland could improve water-stable aggregate and reduce soil disturbances in areas (like the Loess Plateau) with the highest erosion risk

Whole-Genome Analysis Reveals That Bacteriophages Promote Environmental Adaptation of <i>Staphylococcus aureus</i> via Gene Exchange, Acquisition, and Loss

The study of bacteriophages is experiencing a resurgence owing to their antibacterial efficacy, lack of side effects, and low production cost. Nonetheless, the interactions between Staphylococcus aureus bacteriophages and their hosts remain unexplored. In this study, whole-genome sequences of 188 S. aureus bacteriophages—20 Podoviridae, 56 Herelleviridae, and 112 Siphoviridae—were obtained from the National Center for Biotechnology Information (NCBI, USA) genome database. A phylogenetic tree was constructed to estimate their genetic relatedness using single-nucleotide polymorphism analysis. Comparative analysis was performed to investigate the structural diversity and ortholog groups in the subdividing clusters. Mosaic structures and gene content were compared in relation to phylogeny. Phylogenetic analysis revealed that the bacteriophages could be distinguished into three lineages (I–III), including nine subdividing clusters and seven singletons. The subdividing clusters shared similar mosaic structures and core ortholog clusters, including the genes involved in bacteriophage morphogenesis and DNA packaging. Notably, several functional modules of bacteriophages 187 and 2368A shared more than 95% nucleotide sequence identity with prophages in the S. aureus strain RJ1267 and the Staphylococcus pseudintermedius strain SP_11306_4, whereas other modules exhibited little nucleotide sequence similarity. Moreover, the cluster phages shared similar types of holins, lysins, and DNA packaging genes and harbored diverse genes associated with DNA replication and virulence. The data suggested that the genetic diversity of S. aureus bacteriophages was likely due to gene replacement, acquisition, and loss among staphylococcal phages, which may have crossed species barriers. Moreover, frequent module exchanges likely occurred exclusively among the subdividing cluster phages. We hypothesize that during evolution, the S. aureus phages enhanced their DNA replication in host cells and the adaptive environment of their host