Multiple shoot induction and rooting of Paeonia lactiflora ‘Da Fu Gui’

Underground buds of herbaceous peony (Paeonia lactiflora Pall.) ‘Da Fu Gui’ were micropropagated in vitro. The basic processes including culture initiation, shoot induction, axillary shoot proliferation and rooting were established. The best initial medium of ‘Da Fu Gui’ was half-strength MS (Murashige and Skoog) medium (double-strength Ca2+) supplemented with 0.5 mg l-1 6-benzylaminopurine (BA) plus 0.5 mg l-1 gibberellic acid (GA3). The best medium for axillary shoot induction was half-strength MS medium (double-strength Ca2+) supplemented with 1.0 mg l-1 BA plus 0.5 mg l-1 kinetin (Kin), while 0.5 mg l-1 BA + 0.3 mg l-1 Kin was best for shoot proliferation. Shoot height at the time of inoculation had a great effect on proliferation and growth of ‘Da Fu Gui’. Putrescine (Put) (0.5 to 5.0 mg l-1) prevented rooting of ‘Da Fu Gui’ but it favored the development of roots. Highest rooting percentage was observed on half-strength MS medium (double-strength Ca2+) supplemented with 1 mg l-1 indole-3-butyric acid (IBA).Key words: Herbaceous peony, underground buds, axillary shoots, micropropagation

Climate change : strategies for mitigation and adaptation

The sustainability of life on Earth is under increasing threat due to humaninduced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change

OsMre11 Is Required for Mitosis during Rice Growth and Development

Meiotic recombination 11 (Mre11) is a relatively conserved nuclease in various species. Mre11 plays important roles in meiosis and DNA damage repair in yeast, humans and Arabidopsis, but little research has been done on mitotic DNA replication and repair in rice. Here, it was found that Mre11 was an extensively expressed gene among the various tissues and organs of rice, and loss-of-function of Mre11 resulted in severe defects of vegetative and reproductive growth, including dwarf plants, abnormally developed male and female gametes, and completely abortive seeds. The decreased number of cells in the apical meristem and the appearance of chromosomal fragments and bridges during the mitotic cell cycle in rice mre11 mutant roots revealed an essential role of OsMre11. Further research showed that DNA replication was suppressed, and a large number of DNA strand breaks occurred during the mitotic cell cycle of rice mre11 mutants. The expression of OsMre11 was up-regulated with the treatment of hydroxyurea and methyl methanesulfonate. Moreover, OsMre11 could form a complex with OsRad50 and OsNbs1, and they might function together in non-homologous end joining and homologous recombination repair pathways. These results indicated that OsMre11 plays vital roles in DNA replication and damage repair of the mitotic cell cycle, which ensure the development and fertility of rice by maintaining genome stability

Traffic Accident Severity Prediction Based on Random Forest

The prediction of traffic accident severity is essential for traffic safety management and control. To achieve high prediction accuracy and model interpretability, we propose a hybrid model that integrates random forest (RF) and Bayesian optimization (BO). In the proposed model, BO-RF, RF is adopted as a basic predictive model and BO is used to tune the parameters of RF. Experimental results show that BO-RF achieves higher accuracy than conventional algorithms. Moreover, BO-RF provides interpretable results by relative importance and a partial dependence plot. We can identify important influential factors for traffic accident severity by relative importance. Further, we can investigate how the influential factors affect traffic accident severity by the partial dependence plot. These results provide insights to mitigate the severity of traffic accident consequences and contribute to the sustainable development of transportation

Thirty years of research on driving behavior active intervention: A bibliometric overview

To better understand the research focus and development direction in the field of driving behavior active intervention, thereby laying a scientific foundation for further research, we used the combination of topic words and keywords to retrieve relevant articles from the Core Collection Database of Web of Science (WOS). A total of 578 articles published from 1992 to 2022 were finally obtained. Firstly, the time distribution characteristics, country distribution, institution distribution and main source journal distribution of published articles were explored. Then, by using the CiteSpace and VOSviewer software, cited reference co-citation analysis, keyword co-occurrence analysis and burst detection analysis were carried out respectively to visually explore the knowledge base, research topic, research frontier and development trend of this field. The results indicate that the USA, Australia and China are the three most active countries in the studies of driving behavior active intervention. Accidental Analysis & Prevention, Transportation Research Part F: Traffic Psychology and Behavior, and Journal of Safety Research are widely selected journals for publications related to this field. The research frontiers in the field of driving behavior active intervention focus on: “traffic safety and crashes analysis, as well as enforcement intervention”, “driving risk and education for young drivers”, “information provision and driving behavior”, “workload and situation awareness for automated driving”. It is worth noting that in recent years, “warning system”, “time”, “work load” have become research hotspots in this field. To sum up, by a bibliometric overview of research on driving behavior active intervention over the past thirty years, this paper clarifies the development skeleton of this research field, determines its hot topics and research progress, and provides a reference for the follow-up exploratory scientific research in this field

Site-Specific Unmodeled Error Mitigation for GNSS Positioning in Urban Environments Using a Real-Time Adaptive Weighting Model

In Global Navigation Satellite System (GNSS) positioning, observation precisions are frequently impacted by the site-specific unmodeled errors, especially for the code observations that are widely used by smart phones and vehicles in urban environments. The site-specific unmodeled errors mainly refer to the multipath and other space loss caused by the signal propagation (e.g., non-line-of-sight reception). As usual, the observation precisions are estimated by the weighting function in a stochastic model. Only once the realistic weighting function is applied can we obtain the precise positioning results. Unfortunately, the existing weighting schemes do not fully take these site-specific unmodeled effects into account. Specifically, the traditional weighting models indirectly and partly reflect, or even simply ignore, these unmodeled effects. In this paper, we propose a real-time adaptive weighting model to mitigate the site-specific unmodeled errors of code observations. This unmodeled-error-weighted model takes full advantages of satellite elevation angle and carrier-to-noise power density ratio (C/N0). In detail, elevation is taken as a fundamental part of the proposed model, then C/N0 is applied to estimate the precision of site-specific unmodeled errors. The principle of the second part is that the measured C/N0 will deviate from the nominal values when the signal distortions are severe. Specifically, the template functions of C/N0 and its precision, which can estimate the nominal values, are applied to adaptively adjust the precision of site-specific unmodeled errors. The proposed method is tested in single-point positioning (SPP) and code real-time differenced (RTD) positioning by static and kinematic datasets. Results indicate that the adaptive model is superior to the equal-weight, elevation and C/N0 models. Compared with these traditional approaches, the accuracy of SPP and RTD solutions are improved by 35.1% and 17.6% on average in the dense high-rise building group, as well as 11.4% and 11.9% on average in the urban-forested area. This demonstrates the benefit to code-based positioning brought by a real-time adaptive weighting model as it can mitigate the impacts of site-specific unmodeled errors and improve the positioning accuracy