Developing an interdisciplinary and cross‐sectoral community of practice in the domain of forests and livelihoods

Although significant resources are being spent researching and fostering the relationship between forests and livelihoods to promote mutually beneficial outcomes, critical gaps in understanding persist. A core reason for such gaps is that researchers, practitioners, and policy makers lack the structured space to interact and collaborate, which is essential for effective, interdisciplinary research, practice, and evaluation. Thus, scientific findings, policy recommendations, and measured outcomes have not always been synthesized into deep, systemic understanding; learning from practice and implementation does not easily find its way into scientific analyses, and science often fails to influence policy. Communities of practice (CofPs) are dynamic sociocultural systems that bring people together to share and create knowledge around a common topic of interest. They offer participants a space and structure within which to develop new, systemic approaches to multidimensional problems on a common theme. Uniquely informed by a systems‐thinking perspective and drawing from the scientific and gray literatures and in‐depth interviews with representatives of established CofPs in the natural resource management and development domain, we argue that a well‐designed and adequately funded CofP can facilitate interdisciplinary and cross‐sectoral relationships and knowledge exchange. Well‐designed CofPs integrate a set of core features and processes to enhance individual, collective, and domain outcomes; they set out an initial but evolving purpose, encourage diverse leadership, and promote collective‐identity development. Funding facilitates effective communication strategies (e.g., in person meetings). We urge our colleagues across sectors and disciplines to take advantage of CofPs to advance the domain of forests and livelihoods.     

基于EMD-MFOA-ELM的瓦斯涌出量时变序列预测研究

为准确分析工作面绝对瓦斯涌出量的非平稳特征,实现瓦斯涌出量的准确预测,基于经验模态分解(EMD)、修正的果蝇优化算法(MFOA)和极限学习机(ELM)基本原理,构建瓦斯涌出量的EMD-MFOA-ELM多尺度时变预测模型。通过EMD将瓦斯涌出量时变序列进行深层次分解,获得多尺度本征模态函数(IMF);采用MFOA-ELM对各IMF时变序列建立动态预测模型,等权叠加各预测值,得到模型最终预测结果。以晋煤某矿瓦斯涌出量监测时序样本为例进行研究分析,结果表明:EMD能充分挖掘出监测数据隐含信息,有效降低数据复杂度;该模型预测相对误差为0.024 3%~0.651 0%,平均值仅为0.252 6%,预测精度和泛化能力高于未经EMD分解模型,能很好地适用于非平稳时变序列预测。     

辅助矿山救护队的建设工作应该加强

在现代煤矿里，灾害和事故仍然是不可避免的。采取减小组织内成员的自由度来强化专业救灾机构的整体功能固然重要，但非专业化的辅助矿山救护队的建设工作更应加强。因为他们亲临现场，熟悉灾情，又处于救灾的黄金时间里。因此，对是否酿成灾害和灾害中损失的控制问题，辅助矿山救护队有更多的优势。     

Song ranging by the dusky antbird,Cercomacra tyrannina: ranging without song learning

In a population of dusky antbirds (Cercomacra tyrannina), less aggressive responses to distance-degraded playbacks than to undegraded playbacks of pair duets show that this tropical suboscine passerine uses sound degradation to range distance from singing conspecifics. This is the first example of song-ranging in a species that does not learn songs, supporting the hypothesis that ranging preceded the song learning that occurs in more recently evolved passerine birds (oscines). Both sexes sing and are able to use song degradation to range distance from singers when their sex-specific song is played back. Received: 27 May 1994/Accepted after revision: 24 March 1996     

A new synergetic paradigm in environmental numerical modeling: Hybrid models combining deterministic and machine learning components

A new type of environmental numerical models, hybrid environmental numerical models (HEMs) based on combining deterministic modeling and machine learning components, is introduced and formulated. Conceptual and practical possibilities of developing HEM, as an optimal synergetic combination of the traditional deterministic/first principles modeling (like that used for solving PDEs on the sphere representing model dynamics of global climate models) and machine learning components (like accurate and fast neural network emulations of model physics or chemistry processes), are discussed. Examples of developed HEMs (hybrid climate models and a hybrid wind–wave ocean model) illustrate the feasibility and efficiency of the new approach for modeling extremely complex multidimensional systems.     

Propagation of olfactory information within the honeybee hive

Transfer of information about food source characteristics within insect societies is essential to colony-foraging success. The food odor communicated within honeybee hives has been shown to be important for food source exploitation. When successful foragers return to the nest and transfer the collected nectar to hive mates through mouth-to-mouth contacts (trophallaxis), potential recruits receiving these samples learn the food odor by associative learning. The food then becomes rapidly distributed among colony members, which is mainly a consequence of the numerous trophallaxes between hive-mates of all ages during food processing. We tested whether the distribution of food among hive mates causes a propagation of olfactory information within the hive. Using the proboscis extension response paradigm, we show that large proportions of bees of the age groups representing the main worker castes, 4 to 9-day-old bees (nurse-aged bees), 12 to 16-day-old bees (food processor-aged bees), and actual foragers (about 17+ day old bees) associatively learn the food odor in the course of processing food that has been collected by only a few foragers. Results further suggest that the information is shared more or less equally between bees of the three age groups. This shows that olfactory information about the flower species exploited by foragers is distributed within the entire colony and is acquired by bees of all age groups, which may influence many behaviors inside and outside the hive.     

应对大型油罐特大火灾的研究——LASTFIRE项目组简介

简要介绍了LASTFIRE项目组的成立背景、组织结构、研究领域、研究目的、研究思路、研究进展等内容,总结了该项目组近几年的研究成果,指出我国的相关企业或研究机构应积极参与这种国际研究组织,实现研究国外资源共享,共同提高大型储罐的安全技术和管理水平。     

Cycle Aware: Piloting a module for novice drivers

Introduction: In low-cycling countries, motor-vehicle traffic and driver behavior are well known barriers to the uptake of bicycles, particularly for utility cycling. Lack of separation between cyclists and faster-moving traffic is one key issue, while attitudes of drivers toward and/or harassment of cyclists is another. Cyclist-related driver education has been recommended as a means to improve driver-cyclist interactions. Methods: The driver licensing process provides an opportunity for such education. The Cycle Aware module was developed to test and enhance novice drivers’ knowledge of interacting safely with cyclists. It was piloted across three Australian jurisdictions targeting both novice and experienced drivers. Participants were asked to complete the Cycle Aware module and an accompanying survey. A total of 134 novice and 97 experienced drivers completed the survey with 42 novice and 50 experienced drivers going on to complete the module. Results: Both groups of drivers scored equally well in the module but the very youngest and very oldest participants were more likely to have some incorrect responses. We did not find any relationship between correct module scores and attitudes toward cyclists. Survey results showed both novice and experienced drivers had somewhat positive attitudes toward cyclists. The two cohorts differed on several attitude questions. Sixty percent (60%) of novices compared to 30% of experienced drivers reported feeling concerned when sharing the road with cyclists, and novices were less likely to agree that cyclists had a right to use the roads. Conclusions and practical applications: The analysis suggests novices need to be better equipped to share roads confidently with cyclists and to recognize cyclists as legitimate traffic participants.     

Learning for social-ecological change: a qualitative review of outcomes across empirical literature in natural resource management

Learning is considered as a promising mechanism to cope with rapid environmental change. The implications of learning for natural resource management (NRM) have not been explored in-depth and the evidence on the topic is scattered across multiple sources. We provide a qualitative review of types of learning outcomes and consider their manifestations in NRM across selected empirical literature. We conducted a systematic search of the peer-reviewed literature (N = 1,223) and a qualitative meta-synthesis of included articles, with an explicit focus on learning outcomes and NRM changes (N = 53). Besides social learning, we found several learning concepts used, including policy and transformative learning, and multiple links between learning and NRM reported. We observe that the development of skills, together with a system approach involving multi-level capacities, is decisive for implications of learning for NRM. Future reviews could systematically compare how primary research applies different learning concepts and discusses links between learning and NRM changes.     

地铁沿线老旧房屋结构安全预警模型

为研究城市地铁沿线老旧房屋普遍存在结构安全问题,基于机器学习模型,选取房屋年份、楼层、面积等11个属性构建预警指标体系,采用SMOTE过采样、独热编码等方法解决样本离散化、不均衡的问题;利用KNN、Bayes、Logistic、SVM 4种机器学习模型对房屋结构安全数据学习并测试,综合应用Accuracy、F1、AP、...