Temporal competition between differentiation programs determines cell fate choice

Multipotent differentiation, where cells adopt one of several possible fates, occurs in diverse systems ranging from bacteria to mammals. This decision‐making process is driven by multiple differentiation programs that operate simultaneously in the cell. How these programs interact to govern cell fate choice is poorly understood. To investigate this issue, we simultaneously measured activities of the competing sporulation and competence programs in single Bacillus subtilis cells. This approach revealed that these competing differentiation programs progress independently without cross‐regulation before the decision point. Cells seem to arrive at a fate choice through differences in the relative timing between the two programs. To test this proposed dynamic mechanism, we altered the relative timing by engineering artificial cross‐regulation between the sporulation and competence circuits. Results suggest a simple model that does not require a checkpoint or intricate cross‐regulation before cellular decision‐making. Rather, cell fate choice appears to be the outcome of a ‘molecular race’ between differentiation programs that compete in time, providing a simple dynamic mechanism for decision‐making.     

城市绿地供需的差异与联系研究进展

作为连接城市绿地与居民需求的重要概念,绿地供需是城市绿地研究和规划决策的重要内容。识别城市绿地供给与需求的区别和关联,有助于城市绿地合理配置、人类福祉提升和城市的可持续发展。本文梳理2016—2020年城市绿地供需研究的主要议题和研究模式,探讨不同议题的差异与联系,并对未来城市绿地供需关系研究提出建议。综述发现,多数研究从供给或需求一方面开展研究,较少将城市供给与需求研究结合一起分析。供给方面主要关注绿地时空分布特征与生态系统服务供给,需求方面侧重于研究居民对绿地的主观偏好与行为。绿地供给、需求的研究对象、研究尺度与研究指标存在较大差异,是二者难以建立联系的主要因素。今后的研究应注重绿地供需匹配的情况。基于主观偏好/客观指标的绿地供需整合研究,是城市绿地供需关系研究的重要方向。     

Analysis of “nontraditional” relationships under assortative mating

The set of conditions on the genetical and developmental mechanisms of quantitative characters as well as on selection and mating system presented in (Gimelfarb, 1981) is expanded, thus enabling one to obtain the genotypic covariances between relatives for a larger variety of relationships. It is also demonstrated that the frequency of a relationship in a population under assortative mating may in general be different from the frequency of this relationship in the population under random mating. A subpopulation of relatives is not necessarily a representative sample of the whole population with respect to the quantitative character distribution. However, for any relationship which is a combination of descendant-ancestor, full sib, Type 1 and Nth uncle-niece relationships, its frequency in a population under assortative mating is the same as in the population under random mating, and the subpopulation of such relatives is a representative sample of the whole population.Paper No. 6620 of the Journal Series of the North Carolina Agricultural Research Service, Raleigh, North Carolina. This investigation was supported in part by NIH Research Grant No. GM 11546 from the National Institute of General Medical Sciences     

酵母三杂交系统的应用研究进展

1996年,酵母三杂交技术被研究应用于筛选RNA结合蛋白.本介绍了酵母三杂交系统的原理、应用、前景和存在的不足及局限,并分析其原因,总结了在过去8年中利用此方法所取得的成就.在酵母双杂交基础上发展起来的酵母三杂交系统,其应用范围已扩大到蛋白质-蛋白质、蛋白质-RNA、蛋白质-小分子药物间的相互作用等更加广泛的研究领域.     

基于不同决策树的面向对象林区遥感影像分类比较

面向地理对象影像分析技术(GEOBIA)是影像分辨率越来越高的背景下的产物.如何提高高分辨率影像分类精度和分类效率是影像处理的重要议题之一.本研究对QuickBird影像多尺度分割后的对象进行分类,分析了C5.0、C4.5、CART决策树算法在林区面向对象分类中的效率,并与kNN算法的分类精度进行比较.利用eCognition软件对遥感影像进行多尺度分割,分析得到最佳尺度为90和40.在90尺度下分离出植被和非植被后,在40尺度下提取不同类别植被的光谱、纹理、形状等共21个特征,并利用C5.0、C4.5、CART决策树算法分别对其进行知识挖掘,自动建立分类规则.最后利用建立的分类规则分别对植被区域进行分类,并比较分析其精度.结果表明: 基于决策树的分类精度均高于传统的kNN法.其中,C5.0方法的精度最高,其总体分类精度为90.0%,Kappa系数0.87.决策树算法能有效提高林区树种分类精度,且C5.0决策树的Boosting算法对该分类效果具有最明显的提升.     

A compound decision approach to covariance matrix estimation

Covariance matrix estimation is a fundamental statistical task in many applications, but the sample covariance matrix is suboptimal when the sample size is comparable to or less than the number of features. Such high-dimensional settings are common in modern genomics, where covariance matrix estimation is frequently employed as a method for inferring gene networks. To achieve estimation accuracy in these settings, existing methods typically either assume that the population covariance matrix has some particular structure, for example, sparsity, or apply shrinkage to better estimate the population eigenvalues. In this paper, we study a new approach to estimating high-dimensional covariance matrices. We first frame covariance matrix estimation as a compound decision problem. This motivates defining a class of decision rules and using a nonparametric empirical Bayes g-modeling approach to estimate the optimal rule in the class. Simulation results and gene network inference in an RNA-seq experiment in mouse show that our approach is comparable to or can outperform a number of state-of-the-art proposals.     

Egg laying rather than host quality or host feeding experience drives habitat estimation in the parasitic wasp Nasonia vitripennis

In variable environments, sampling information on habitat quality is essential for making adaptive foraging decisions. In insect parasitoids, females foraging for hosts have repeatedly been shown to employ behavioral strategies that are in line with predictions from optimal foraging models. Yet, which cues exactly are employed to sample information on habitat quality has rarely been investigated. Using the gregarious parasitoid Nasonia vitripennis (Walker; Hymenoptera: Pteromalidae), we provided females with different cues about hosts to elucidate, which of them would change a wasp's posterior behavior suggesting a change in information status. We employed posterior clutch size decisions on a host as proxy for a female's estimation of habitat quality. Taking into account changes in physiological state of the foraging parasitoid, we tested whether different host qualities encountered previously change the subsequent clutch size decision in females. Additionally, we investigated whether other kinds of positive experiences—such as ample time to investigate hosts, host feeding, or egg laying—would increase a wasp's estimated value of habitat quality. Contrary to our expectations, quality differences in previously encountered hosts did not affect clutch size decisions. However, we found that prior egg laying experience changes posterior egg allocation to a host, indicating a change in female information status. Host feeding and the time available for host inspection, though correlated with egg laying experience, did not seem to contribute to this change in information status.     

Comprehensive criteria for biodiversity evaluation in conservation planning

In this paper we present the results of a multi-criteria decision analysis used to identify a comprehensive set of criteria for assigning biodiversity value to sites for conservation planning. For effective conservation management, biodiversity value needs to be a composite of biotic and abiotic factors. However, in the reserve design literature, conservation value is assigned with a limited set of metrics usually based on comprehensiveness, representativeness and persistence which may be insufficient at fully capturing biodiversity value. A group of conservation specialists in California, USA, used a multi-criteria decision making framework to elucidate and weight criteria for scoring biodiversity value at sites. A formal model for consensus and negotiation was applied to aggregate individuals’ criteria weights across all group members. The group identified ecological condition, followed by biotic composition as the most important contributors to site conservation value. Long- and short-term threats causing fragmentation and degradation are also important criteria to consider. Key criteria are identified for which further data collection would serve the greatest purpose in prioritizing sites and the role of prioritization criteria in the larger context of systematic conservation planning is discussed. With the recognition that biodiversity value plays an important role in conservation decisions, the criteria presented here represents a comprehensive suite of factors to consider when assigning biodiversity value to sites for conservation planning. These can serve as an encompassing list which other groups can customize for the purpose of biodiversity evaluation for alternative conservation planning contexts.     

神经网络与人事决策研究的新范式

随着多特征决策研究的深入,传统方法已经不能回答更加细致的问题。细察精确预测的理论、建立模型与数据的形式关系成为更有希望的研究方向。神经网络模型设计用来模拟许多并行的认知和神经行为,具有样例学习和迁移适应能力．在解释和预测方面具有传统方法所不具备的潜力。神经网络能够同时表征线性补偿和非补偿规则,其应用已经渗透到许多学科领域。网络范式对于人事研究和应用也有价值,有研究表明神经网络可以用于人力资源管理的一般领域,成为人事决策研究的新范式。     

Research Implications of Science-Informed,Value-Based Decision Making

In ‘Hard’ science, scientists correctly operate as the ‘guardians of certainty,’ using hypothesis testing formulations and value judgements about error rates and time discounting that make classical inferential methods appropriate. But these methods can neither generate most of the inputs needed by decision makers in their time frame, nor generate them in a form that allows them to be integrated into the decision in an analytically coherent and transparent way. The need for transparent accountability in public decision making under uncertainty and value conflict means the analytical coherence provided by the stochastic Bayesian decision analytic approach, drawing on the outputs of Bayesian science, is needed. If scientific researchers are to play the rôle they should be playing in informing value-based decision making, they need to see themselves also as ‘guardians of uncertainty,’ ensuring that the best possible current posterior distributions on relevant parameters are made available for decision making, irrespective of the state of the certainty-seeking research. The paper distinguishes the actors employing different technologies in terms of the focus of the technology (knowledge, values, choice); the ‘home base’ mode of their activity on the cognitive continuum of varying analysis-to-intuition ratios; and the underlying value judgements of the activity (especially error loss functions and time discount rates). Those who propose any principle of decision making other than the banal ‘Best Principle,’ including the ‘Precautionary Principle,’ are properly interpreted as advocates seeking to have their own value judgements and preferences regarding mode location apply. The task for accountable decision makers, and their supporting technologists, is to determine the best course of action under the universal conditions of uncertainty and value difference/conflict.     

Experiments with humans indicate that decision accuracy drives the evolution of niche width

One theory to explain the high incidence of niche specialization in many animals is that it reduces attentional load during resource-seeking behaviour and thus leads to more accurate resource selection. A recent neural network model refined the predictions of this theory, indicating that a cognitive advantage in specialists is likely to occur under realistic ecological conditions, namely when 'mistakes' (i.e. selection of non-host resources) contribute moderately but positively to fitness. Here, we present a formal empirical test of the predictions of this model. Using a human-computer interactive, we demonstrate that the central prediction of the model is supported: specialist humans are more accurate decision-makers than generalists when their mistakes are rewarded, but not when mistakes are punished. The idea that increased decision accuracy drives the evolution of niche width in animals has been supported in almost all empirical systems in which it has been investigated. Theoretical work supports the idea, and now the predictions of a key theoretical model have been demonstrated in a real biological information-processing system. Considering these interlocking pieces of evidence, we argue that specialization through increased decision accuracy may contribute significantly, along with other mechanisms, to promote niche specialization in animals.     

甘南高寒湿地草地放牧系统管理的AHP决策分析及生态恢复对策

以甘南玛曲县的高寒湿地为研究对象,系统探讨了湿地植被退化及土地沙漠化的主要动因及其时空变化特征。采用多层次的AHP(Analytic Hierarchy Process)决策模型,对导致湿地植被退化的主要因素及诸种恢复措施综合效果进行了管理决策分析。结果表明：引发湿地植被退化的诸因素中,长期超载放牧和鼠害、虫害是其主要因素,其权重分别为0．4995和0．2684;在湿地恢复的诸管理措施中,围栏轮牧和建植人工草地或半人工草地的综合效果显著,其组合权重分别为0．2584和0．2009。基于上述分析,提出了湿地生态恢复与可持续利用的主要管理对策。     

Decision errors in evaluating tipping points for ecosystem resilience

When an ecosystem reaches tipping points for selected indicators, resilience to further changes in external drivers can decrease, regime shifts can occur that diminish the capacity of the ecosystem to provide ecosystem services, and the ecosystem is more vulnerable to collapse. Evaluating tipping points for resilience using crisp decision rules can result in decision errors about whether or not resilience has been compromised. The source and nature of those errors are described and a fuzzy decision rule is proposed for evaluating resilience. Decision errors are evaluated for four cases. Cases 1 through 3 (or case 4) derive conditions for evaluating decision errors when there is a single (or multiple) indicator(s). The primary sources of decision errors for the four cases are discrepancies between measured (or established) and true values of the indicators (or tipping points) and using a crisp decision rule to reach conclusions about whether or not resilience has been compromised. A fuzzy decision rule, based on fuzzy TOPSIS, is proposed that evaluates the extent to which an ecosystem is resilient. Although crisp decision rules provide unambiguous conclusions about resilience, those conclusions can be faulty, particularly when measured indicators and established tipping points deviate substantially from their true values. In contrast, the conclusions from the fuzzy decision rule are less susceptible to the decision errors and, hence, faulty decisions.     

Decision Analysis: A Method for Taking Uncertainties into Account in Risk-Based Decision Making

The assessment of human and ecological risks and associated risk-management decisions are characterized by only partial knowledge of the relevant systems. Typically, large variability and measurement errors in data create challenges for estimating risks and identifying appropriate management strategies. The formal quantitative method of decision analysis can help deal with these challenges because it takes uncertainties into account explicitly and quantitatively. In recent years, research in several areas of natural resource management has demonstrated that decision analysis can identify policies that are appropriate in the presence of uncertainties. More importantly, the resulting optimal decision is often different from the one that would have been chosen had the uncertainties not been taken into account quantitatively. However, challenges still exist to effective implementation of decision analysis.     

The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy

Groups of organisms, from bacteria to fish schools to human societies, depend on their ability to make accurate decisions in an uncertain world. Most models of collective decision-making assume that groups reach a consensus during a decision-making bout, often through simple majority rule. In many natural and sociological systems, however, groups may fail to reach consensus, resulting in stalemates. Here, we build on opinion dynamics and collective wisdom models to examine how stalemates may affect the wisdom of crowds. For simple environments, where individuals have access to independent sources of information, we find that stalemates improve collective accuracy by selectively filtering out incorrect decisions (an effect we call stalemate filtering). In complex environments, where individuals have access to both shared and independent information, this effect is even more pronounced, restoring the wisdom of crowds in regions of parameter space where large groups perform poorly when making decisions using majority rule. We identify network properties that tune the system between consensus and accuracy, providing mechanisms by which animals, or evolution, could dynamically adjust the collective decision-making process in response to the reward structure of the possible outcomes. Overall, these results highlight the adaptive potential of stalemate filtering for improving the decision-making abilities of group-living animals.     

Incorporating social preferences into the ecological limits of hydrologic alteration (ELOHA): a case study in the Yampa‐White River basin,Colorado

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