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Resilience has been described in many ways and in this paper is considered as the ability of an organization or wider food supply chain to not just 'bounce back' to a steady state, but to 'bounce forward' or 'bounce without breaking' to a new sense of becoming that is continually reshaped by the evolving environment. This keynote-positioned conceptual paper reflects aspects of resilience that will be considered during the conference. Resilience as a concept can be framed in the context of food supply chains in terms of the triad of natural systems resilience, organizational resilience, and personal resilience. The main focus of this paper is on organizational resilience and developing the capacity to buffer shocks and to adapt to changing supply chain drivers and demands as the world in which the organization operates becomes more uncertain. One infrastructural approach to improving adaptive capacity, as a result resilience, is the integration of digital technologies and smart systems into food supply chains, what is often described as Industry 4.0. [ABSTRACT FROM AUTHOR]

In the last two decades resilience has emerged as a promising concept that can help societies and more generally social‐ecological systems become less vulnerable to shocks and stressors. As such it has been adopted by a large number of disciplines—from psychology, physics, and ecology to disaster risk reduction, climate change adaption, and humanitarian and food security interventions. However, although numerous definitions or measures of resilience have been proposed, those were mainly discipline centered and, as such, failed to provide an adequate overarching framework. This paper explores the question of the formalization and measurement of resilience, with the objective to develop a generic metric that applies across the disciplines and to the different interpretations of resilience. Building on the definitions found in the literature, a continuum of five categories of resilience responses is identified: (i) resistance, (ii) coping strategies, (iii) adaptation, (iv) adaptive preference, and (v) transformation. Those categories are then reframed into a generic metric, using viability analysis—a mathematical formalism which builds on dynamic systems and control theory. Theoretical and empirical analyses are then conducted, looking in particular at how inertia and costs associated with the types of responses influence the level of resilience. To illustrate this new metric, we draw on two models widely discussed in the resilience literature: the exploitation of renewable resources and the case of lake eutrophication. Both theoretical and numerical analyses demonstrate the relevance of the typology as a generic framework for resilience but also highlight transformation as a particular case of resilience response. [ABSTRACT FROM AUTHOR]

Air pollution is one of the major problems of the modern world. The popularization and powerful functions of smartphone applications enable people to participate in urban sensing to better know about the air problems surrounding them. Data sampling is one of the most important problems that affect the sensing performance. In this paper, we propose an Adaptive Sampling Scheme for Urban Air Quality (AS-air) through participatory sensing. Firstly, we propose to find the pattern rules of air quality according to the historical data contributed by participants based on Apriori algorithm. Based on it, we predict the on-line air quality and use it to accelerate the learning process to choose and adapt the sampling parameter based on Q-learning. The evaluation results show that AS-air provides an energy-efficient sampling strategy, which is adaptive toward the varied outside air environment with good sampling efficiency. [ABSTRACT FROM AUTHOR]

The distribution of cultural variants in a population is shaped by both neutral evolutionary dynamics and by selection pressures. The temporal dynamics of social network connectivity, that is, the order in which individuals in a population interact with each other, has been largely unexplored. In this paper, we investigate how, in a fully connected social network, connectivity dynamics, alone and in interaction with different cognitive biases, affect the evolution of cultural variants. Using agent‐based computer simulations, we manipulate population connectivity dynamics (early, mid, and late full‐population connectivity); content bias, or a preference for high‐quality variants; coordination bias, or whether agents tend to use self‐produced variants (egocentric bias), or to switch to variants observed in others (allocentric bias); and memory size, or the number of items that agents can store in their memory. We show that connectivity dynamics affect the time‐course of variant spread, with lower connectivity slowing down convergence of the population onto a single cultural variant. We also show that, compared to a neutral evolutionary model, content bias accelerates convergence and amplifies the effects of connectivity dynamics, while larger memory size and coordination bias, especially egocentric bias, slow down convergence. Furthermore, connectivity dynamics affect the frequency of high‐quality variants (adaptiveness), with late connectivity populations showing bursts of rapid change in adaptiveness followed by periods of relatively slower change, and early connectivity populations following a single‐peak evolutionary dynamic. We evaluate our simulations against existing data collected from previous experiments and show how our model reproduces the empirical patterns of convergence. [ABSTRACT FROM AUTHOR]

This paper aims to develop a load forecasting method for short-term load forecasting, based on an adaptive two-stage hybrid network with self-organized map (SOM) and support vector machine (SVM). In the first stage, a SOM network is applied to cluster the input data set into several subsets in an unsupervised manner. Then, groups of 24 SVMs for the next day's load profile are used to fit the training data of each subset in the second stage in a supervised way. The proposed structure is robust with different data types and can deal well with the nonstationarity of load series. In particular, our method has the ability to adapt to different models automatically for the regular days and anomalous days at the same time. With the trained network, we can straight-forwardly predict the next-day hourly electricity load. To confirm the effectiveness, the proposed model has been trained and tested on the data of the historical energy load from New York Independent System Operator. [ABSTRACT FROM AUTHOR]

The condition-based approach is one of the sophisticated methods used to overcome several impossibility results in the distributed consensus problem (e.g., impossibility of fault tolerance in asynchronous consensus or time complexity lower bounds in synchronous consensus). It introduces conditions on input vectors to specify subsets of all possible input vectors to consensus algorithms and condition-based algorithms can circumvent the impossibility if actual input vectors satisfy a particular condition. In this paper, we present a new condition-based paradigm for synchronous consensus. We introduce the new concept of adaptation on the time complexity of condition-based algorithms and present the adaptive condition-based approach to synchronous consensus. In our approach, all possible input vectors are classified into hierarchical conditions according to their difficulty called the legality level. The execution time of adaptive condition-based algorithms depends on the legality level of input vectors. We propose two adaptive condition-based algorithms for synchronous consensus. The first algorithm requires that the majority of processes be correct, and terminates within min{f + 2, t + 1} - l rounds if l < f, where f and I are the actual and the maximum numbers of faults, respectively, and 1 is the legality level of the input vector. Moreover, the algorithm terminates in one round if I ≥ t and f = 0 and terminates within two rounds if I ≥ f holds. Compared with previous algorithms, this algorithm achieves the best time complexity. The second algorithm can tolerate any number of faults, and terminates within max{3, min{f + 3, t + 2} - I} rounds if I < f holds, terminates in one round if I ≥ t. and f = 0, and terminates within three rounds if I ≥ f holds. [ABSTRACT FROM AUTHOR]

Computational trust and reputation models are key elements in the design of open multi-agent systems. They offer means of evaluating and reducing risks of cooperation in the presence of uncertainty. However, the models proposed in the literature do not consider the costs they introduce and how they are affected by environmental aspects. In this paper, a cognitive meta-model for adaptive trust and reputation in open multi-agent systems is presented. It acts as a complement to a non-adaptive model by allowing the agent to reason about it and react to changes in the environment. We demonstrate how the meta-model can be applied to existent models proposed in the literature, by adjusting the model's parameters. Finally, we propose evaluation criteria to drive meta-level reasoning considering the costs involved when employing trust and reputation models in dynamic environments. [ABSTRACT FROM AUTHOR]

While quality-adaptable applications are gaining increased popularity on embedded systems (especially multimedia applications), efficient scheduling techniques are necessary to explore this feature to achieve the optimal quality output. In addition to conventional real-time requirements, emerging challenges such as leakage power and multiprocessors further complicate the formulation and solution of adaptive application scheduling problems. In this paper, we propose a dynamic adaptive application scheduling scheme that efficiently distributes the runtime slack to achieve maximized execution quality under timing and dynamic/leakage energy constraints. Our proposed methods are threefold: First, for each task in the slack receiver group, a heuristic guided-search algorithm is proposed to select the optimal processor frequency to maximize the application execution quality. Second, we present an efficient slack receiver selection methodology aiming at identifying optimal slack receivers for quality maximization. Third, our framework is further extended to consider constraints brought by interprocessor communications, where we study the effects of slack inaccuracies introduced by transmission variations, and propose a local scaling approach to compensate the induced quality loss. Experimental results on synthesized tasks and a JPEG2000 codec show that the guided-search algorithm, aided by slack receiver selection, effectively outperforms contemporary approaches with at most 88 percent more quality improvement, whereas the local scaling contributes as large as 16.9 percent on top of the guided-search results. [ABSTRACT FROM AUTHOR]

Collaboration between biologists and roboticists can facilitate the creation of new behavioral algorithms by roboticists and help biologists by exposing the underlying mechanisms that allow the algorithms to function (for a review see Webb, 2000). This paper makes a direct comparison between robot annular puck sorting using real robots (Wilson, Melhuish, Sendova-Franks & Scholes, 2004) and brood sorting in the ant Leptothorax albipennis (Franks & Sendova-Franks, 1992). We compared the ants’ and robots’ structures in terms of radial displacement, shape, compactness, completeness and separation. This showed the effectiveness and limitations of using metrics developed for robots to quantify structures built by ants and helped relate common aspects of the structures to possible common aspects of the underlying algorithms. The ant behavioral rule set is still under investigation and a better understanding of the structure it creates has proved a very useful tool to examine aspects of the algorithm. We draw the conclusions that firstly, the size of the area available for sorting affects the robot algorithm and ant algorithm in opposite ways, secondly, the metrics have proved very useful in aiding discrimination between the robot and ant structures and thirdly, application of the metrics to the ant structure has offered biologists new ideas and a better understanding of the structure and how it is built. [ABSTRACT FROM PUBLISHER]

An indirect adaptive control approach is developed in this paper for robots with unknown nonlinear dynamics using neural networks (NNs). A key property of the proposed approach is that the actual joint angle values in the control law are replaced by the desired joint angles, angle velocities and accelerators, and the bound on the NN reconstruction errors is assumed to be unknown. Main theoretical results for designing such a neuro-controller are given, and the control performance of the proposed controller is verified with simulation studies. [ABSTRACT FROM AUTHOR]

Climate change exacerbates the challenges that water management nowadays has to deal with. This highlights the need for a legal framework that promotes adaptation by addressing the ecological value of water and the risks of flooding and drought. This paper analyzes to what extent the European legal framework meets this need. This is evaluated by analyzing to what extent the Water Framework Directive, the Floods Directive and the Water Scarcity and Drought Strategy build resilience. Resilience is an important concept in the adaptation to climate change discourse. It refers to the capacity of a social-ecological system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity and feedbacks. This paper uses five criteria to measure this: (1) the flexibility of rules and (2) the adaptiveness of such rules (3) openness, public participation and access to the courts (4) multilevel governance at the bioregional scale and (5) effectiveness. The European legal framework partly meets these criteria. It offers a river basin approach and both the setting of goals and objectives and their achievement is a multilevel, cyclical process, which includes public participation. However, the achievement of the goals is not easily enforceable and coordination within international river basins is legally weak. This detracts from the expected effectiveness of the EU legal framework in promoting adaptation by protecting the aquatic ecosystem and reducing flood and drought risks.

In adaptivity, the interface of the device automatically adjusts and assists the user. The adaptive user interfaces can adapt their activities by monitoring user status, the state of the system, and the current situation according to the adaptation strategy. Usually, the intensity of adaptation is measured in effectiveness, efficiency, and satisfaction to analyze the smartphone's adaptive features. The adaptive features of light-emitting diode (LED) notifications, voice commands, face recognition, screen rotation, kid mode, drive mode, night mode, Swift Keyboard, s-health, gesture recognition, and fingerprint are selected for both iOS and Android platforms. Task completion within a specific time frame is used to measure effectiveness and efficiency, while satisfaction is calculated using the after-scenario questionnaire (ASQ). A total of 550 users are involved in the experimentation. The usability evaluation is measured for smartphone features. The effectiveness of adaptive features contains higher adaptivity in face recognition (87%) and voice command (85%). Furthermore, the satisfaction level is greater for adaptive features than non-adaptive features. This study indicates that adaptive features can only be used after a thorough examination of the user's context. Furthermore, the usability evaluation shows that there is a dire need for adaptive smartphone features to provide ease and satisfaction to the user. [ABSTRACT FROM AUTHOR]

The rise of automation in many systems; and technology ubiquity in general, present some complex operational environments that require highly collaborative Complex Adaptive Systems of Systems (CASoS) solutions. This paper describes the need to engineer CASoS and explores how they may be applied to address complex problems. This effort builds on a developing body of knowledge in complex systems and focuses on understanding characteristics and measures of CASoS with an ultimate goal on developing engineered CASoS. The implications of deeper CASoS understanding hold potential for more effective future responses to naturally-occurring and adversarial CASoS. Thus, there stands much to gain in increasing this body of knowledge. [ABSTRACT FROM AUTHOR]

Adaptive comanagement (ACM) is often suggested as a way of handling the modern challenges of environmental governance, which include uncertainty and complexity. ACM is a novel combination of the learning dimension of adaptive management and the linkage dimension of comanagement. As has been suggested, there is a need for more insight on enabling policy environments for ACM success and failure. Picking up on this agenda we provide a case study of the world famous Venice lagoon in Italy. We address the following questions: first, to what extent are four institutional prescriptions typically associated with ACM currently practiced in the Venice system? Second, to what extent is learning taking place in the Venice system? Third, how is learning related to the implementation or nonimplementation of the prescriptions of ACM in the Venice system? Our analysis is based on interviews with stakeholders, participatory observation, and archive data. This paper demonstrates that the prescriptions of ACM are hardly followed in the Venice lagoon, but some levels of cognitive learning do take place, albeit very much within established management paradigms. Normative and relational learning are much rarer and when they do occur, they seem to have a relatively opportunistic reason. We propose that in particular the low levels of collaboration, because the governance system was deliberately set up in a hierarchical and mono-centric way, and the limited possibilities for stakeholder participation are implicated in this finding because they cause low levels of social capital and an incapacity to handle disagreements and uncertainty very well. [ABSTRACT FROM AUTHOR]

In this paper we ask whether the two-factor theory of delusions is compatible with two claims, that delusions are pathological and that delusions are adaptive. We concentrate on two recent and influential models of the two-factor theory: the one proposed by Max Coltheart, Peter Menzies and John Sutton (2010) and the one developed by Ryan McKay (2012). The models converge on the nature of Factor 1 but diverge about the nature of Factor 2. The differences between the two models are reflected in different accounts of the pathological and adaptive nature of delusions. We will explore such differences, considering naturalist and normativist accounts of the pathological and focusing on judgements of adaptiveness that are informed by the shear-pin hypothesis (McKay and Dennett 2009). After reaching our conclusions about the two models, we draw more general implications for the status of delusions within two-factor theories. Are there good grounds to claim that delusions are pathological? Are delusions ever adaptive? Can delusions be at the same time pathological and adaptive?

Abstract Time synchronization of clocks in the sensor nodes for wireless sensor networks (WSNs) is a fundamental technology for most mission-critical applications. Most of past research in time synchronization for WSNs, however, has only focused on achieving some of the goals at a time, such as accuracy, energy consumption, completion time, etc., making these solutions less capable of adapting to different application requirements. In this paper, we propose a new time synchronization algorithm named MBATS (mobile beacon-based adaptive time synchronization) in which a mobile beacon is employed to move or fly over the sensor deployment area to complete time synchronization. Moreover, MBATS is designed so that the number of sensor nodes that are synchronized by one instance of time synchronization from the mobile beacon could vary dynamically to meet application requirements on accuracy, completion time and energy consumption, making the proposed MBATS algorithm highly adaptable to different application requirements. In addition to showing the advantage of the proposed MBATS algorithm on the adaptability of time synchronization as well as on some of the main metrics of synchronization over comparable schemes for WSNs, we also present the results of our study on comparing the performance of letting the mobile beacon traverse along a designing path versus follow a random path. Such a study is important since it would allow us to learn the performance gains that we can expect to achieve with extra control effort spent on designing the path over the effortless random path strategy. Such study could provide us with some clues on how to choose a suitable time synchronization strategy to better meet application requirements, which may not necessarily be the designed path strategy due to the tradeoff between cost and performance gains.

Objective: Psychological distress is common in cancer patients during the diagnostic phase. Research demonstrated that anxiety, depression and defense mechanisms may influence physical and psychological well-being in patients with malignant tumors. The present retrospective study investigated the associations between clinical and psychological characteristics of cancer patients waiting for the diagnosis, focusing on metastatic cancer (MC) and breast cancer (BC). Methods: Patients with a new diagnosis of cancer referring to a Clinical Oncology Unit in Central Italy were interviewed during the 2017 for psychological assessment. Double-blind information about anxiety, depression, sleep disorders, defense style, and cancer diagnosis were available for the 567 patients included in this study. T-test, chi-squared and regression analyses were performed to detect associations between psychological variables and the presence of metastasis (MC) in the whole sample and in the subgroup of breast cancer (BC) patients. Results: Female gender and younger age were associated with anxiety, depression, and maladaptive defense style. A significant positive relationship was found between presence of metastasis and symptoms of anxiety. Depression resulted significantly more frequent in BC, while there was a trend close to statistical significance in MC. Immature defense style was widely used by BC women, with a score close to statistical significance. Conclusions: This retrospective study provided empirical evidence of the relationship between psychological functioning and clinical characteristics of cancer. In line with previous research, our findings confirmed the peculiar psychological functioning of BC patients. Further investigations are needed to understand how the diagnosis of cancer may influence the individual psychological functioning and vice versa. [ABSTRACT FROM AUTHOR]

Due to the prevalence of smartphones and various wearable devices, the collection of rich personal data that can be used for human activity recognition, user modeling, and personalized services has become feasible. Because of its popularity and high accessibility, the smartphone has not only become an effective terminal in personal data collection, but also a gateway connecting wearable devices and gathering various types of personal data from these wearables. In most current applications, such wearables operate to collect data according to a fixed schedule, often preset manually by a user. The main problems in the data collection arising from such fixed scheduling are weak adaptiveness to wearables' state changes, a high level of redundancy in collected data, and possible mismatches in the dynamic precision requirements of data capture. Therefore, we propose a context-aware scheduler, that is able to dynamically adjust a data collection schedule based on contingent situations in the condition of wearables, system resource availability, and user behavior. This paper is focused on context data detection and data collection scheduling in a smartphone-based client-server system. The smartphone functions as not only a gateway gathering data from multiple wearables, but also a terminal for the performance of a context-aware scheduler. A context-aware engine is implemented to handle different contextual information. The data quality and system performance have been evaluated and verified in practical experimental tests.

The availability of information and variety of online purchase options are increasing for consumers shopping for complex products (e.g., cars, real estate). This situation, and consumers' resulting sense of informedness, has led many to suggest that the need for business-to-consumer (B2C) salespeople is diminishing. Yet, despite these claims, many purchases—especially those associated with high prices and, therefore, high consumer involvement—still require consumers to interact with salespeople. This interaction, between consumers (at varying levels of informedness) and B2C salespeople, is the focus of the current study. Merging theories of consumer informedness and adaptive interpersonal influence, we suggest that the interaction between salesperson influence attempts and consumer informedness plays an important role in purchase decisions. To study this notion, Study 1 matches automobile shoppers' survey responses with objective purchase data from 480 sales interactions. Study 2 is a scenario-based experiment that investigates informedness and influence in a financial services setting. The findings of both studies suggest that understanding a consumer's informedness, and adapting the proper influence approach to it, is critical if salespeople are to influence modern consumers' purchase decisions and, thus, avoid irrelevancy. [ABSTRACT FROM AUTHOR]

While extensively studied in the 1990s, research on the electrical and electronics (E&E) industry in Singapore and the proximate areas of Indonesia has dwindled. Focusing on the E&E sector in the island of Batam (Riau Islands Province, Indonesia), we examine the industry's recent evolution, in particular its 'robustness'-its durability and capacity to adapt to adverse events. As to the explanatory factors accounting for its robustness, we evaluate the role of agency as opposed to conventional approaches that focus on structure. Our findings show that, in Batam, the E&E industry's robustness has started to suffer. While there is evidence that structural factors are at work, we argue that agency in the form of institutionally-embedded perspectives and behaviour of actors at the sub-national level also plays a role. Because the promotion of economic diversification through investment in new sectors is easier and more lucrative than upgrading and deepening of firm capabilities in existing sectors, agents privilege the former at the cost of the latter. At the end of the day, regional resilience is undermined, rather than reinforced as evinced by the recent atrophy of Batam's E&E industry. [ABSTRACT FROM AUTHOR]

Background: The current analysis of transposon elements (TE) in Drosophila melanogaster at Evolution Canyon, (EC), Israel, is based on data and analysis done by our collaborators (Drs. J. Gonzalez, J. Martinez and W. Makalowski, this issue). They estimated the frequencies of 28 TEs (transposon elements) in fruit flies (D. melanogaster) from the ecologically tropic, hot, and dry south-facing slope (SFS) or "African" slope (AS) of EC and compared it with the TE frequencies on the temperate-cool and humid north-facing slope (NFS) or "European" slope (ES), separated, on average, by 250 m. The flies were sampled from two stations on each slope. We received their results, including the frequencies of each TE on each slope, and the probabilities of the statistical analyses (G-tests) of each TE separately. We continued the analysis of the inter-slope differences of the frequencies of the TEs, and based our different conclusions on that analysis and on the difference between micro (=EC) and macro (2000 km.) comparisons [Gonzalez et al. 2015 doi:10.1186/s13062-015-0075-4]. Results: Our collaborators based all their conclusions on the non-significant results of each of the individual tests of the 28 TEs. We analysed also the distribution of the TE differences between the slopes, based on their results. Thirteen TEs were more frequent on the SFS, 11 were more frequent on the NFS, and four had equal frequencies. Because of the equalizing effect of the ongoing migration, only small and temporary differences between the slopes (0 - 0.06) were regarded by us as random fluctuations (drift). Three TEs were intermediate (0.08-0.09) and await additional research. The 11 TEs with large frequency differences (0.12 - 0.22) were regarded by us as putative adaptive TEs, because the equalizing power of ongoing migration will eliminate random large differences. Five of them were higher on the SFS and six were higher on the NFS. Gaps in the distribution of the differences distinguished between the large and small differences. The large gap among the 11 TEs favored on the NFS was significant and supports our rejection of drift as the only explanation of the distribution of the slope differences. The gaps in the distribution of the differences separated the putative TEs with strong enough selection from those TEs that couldn't overrule the migration. The results are compared and contrasted with the directional effect of the frequencies of the same TEs in the study of global climatic comparisons across thousands of kilometers. From the 11 putative adaptive TEs in the local "Evolution Canyon," six differentiate in the same direction as in the continental comparisons and four in the opposite direction. One TE, FBti0019144, differentiated in EC in the same direction as in Australia and in the opposite direction to that of North America. Conclusions: We presume that the major divergent evolutionary driving force at the local EC microsite is natural selection overruling gene flow. Therefore, after we rejected drift as an explanation of all the large slope differences, we regarded them as putatively adaptive. In order to substantiate the individual TE adaptation, we need to increase the sample sizes and reveal the significant adaptive TEs. The comparison of local and global studies show only partial similarity in the adaptation of the TEs, because of the dryness of the ecologically tropical climate in EC, in contrast to the wet tropical climate in the global compared climates. Moreover, adaptation of a TE may be expressed only in part of the time and specific localities. [ABSTRACT FROM AUTHOR]

The cognitive deterioration associated with aging is accompanied by structural alterations and loss of functionality of the frontostriatal dopamine system. The question arises how such deleterious cognitive effects could be countered. Brain training, currently highly popular among young and old alike, promises that users will improve on certain neurocognitive skills, and this has indeed been confirmed in a number of studies. Based on these results, it seems reasonable to expect beneficial effects of brain training in the elderly as well. A selective review of the existing literature suggests, however, that the results are neither robust nor consistent, and that transfer and sustained effects thus far appear limited. Based on this review, we argue for a series of elements that hold potential for progress in successful types of brain training: (1) including flexibility and novelty as features of the training, (2) focusing on a number of promising, yet largely unexplored domains, such as decision-making and memory strategy training, and (3) tailoring the training adaptively to the level and progress of the individual. We also emphasize the need for covariance-based MRI methods in linking structural and functional changes in the aging brain to individual differences in neurocognitive efficiency and trainability in order to further uncover the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Since the genetic code first was determined, many have claimed that it is organized adaptively, so as to assign similar codons to similar amino acids. This claim has proved difficult to establish due to the absence of relevant comparative data on alternative primordial codes and of objective measures of amino acid exchangeability. Here we use a recently developed measure of exchangeability to evaluate a null hypothesis and two alternative hypotheses about the adaptiveness of the genetic code. The null hypothesis that there is no tendency for exchangeable amino acids to be assigned to similar codons can be excluded here as expected from earlier work. The first alternative hypothesis is that any such correlation between codon distance and amino acid distance is due to incremental mechanisms of code evolution, and not to adaptation to reduce deleterious effects of future mutations. More specifically, new codon assignments that occur by ambiguity reduction or by codon capture will tend to give rise to correlations, whether due to the condition of amino acid ambiguity, or to the condition of similarity between a new tRNA synthetase (or tRNA) and its parent. The second alternative hypothesis, the adaptive hypothesis, then may be defined as an excess relative to what may be expected given the incremental nature of evolution, reflecting true adaptation for robustness rather than an incidental effect. The results reported here indicate that most of the nonrandomness in the amino acids to codon assignments can be explained by incremental code evolution, with a small residue of orderliness that may reflect code adaptation. [ABSTRACT FROM AUTHOR]

Adaptive comanagement (ACM) is often suggested as a way of handling the modern challenges of environmental governance, which include uncertainty and complexity. ACM is a novel combination of the learning dimension of adaptive management and the linkage dimension of comanagement. As has been suggested, there is a need for more insight on enabling policy environments for ACM success and failure. Picking up on this agenda we provide a case study of the world famous Venice lagoon in Italy. We address the following questions: first, to what extent are four institutional prescriptions typically associated with ACM currently practiced in the Venice system? Second, to what extent is learning taking place in the Venice system? Third, how is learning related to the implementation or nonimplementation of the prescriptions of ACM in the Venice system? Our analysis is based on interviews with stakeholders, participatory observation, and archive data. This paper demonstrates that the prescriptions of ACM are hardly followed in the Venice lagoon, but some levels of cognitive learning do take place, albeit very much within established management paradigms. Normative and relational learning are much rarer and when they do occur, they seem to have a relatively opportunistic reason. We propose that in particular the low levels of collaboration, because the governance system was deliberately set up in a hierarchical and mono-centric way, and the limited possibilities for stakeholder participation are implicated in this finding because they cause low levels of social capital and an incapacity to handle disagreements and uncertainty very well.

Denmark, Germany, and Finland are countries that have emerged as technology leaders in key renewable energy fields—wind energy, solar power, and bioenergy. In this article, we dig into the policy trajectories of these countries and concentrate particularly on a phenomenon that is common for them all—the long-term commitment to promoting particular renewable energy (RE) technologies. Analyzing commitment, its causes and its consequences, can be considered important, as earlier findings show that long-term, consistent policy signals are a key for policy success. In this article, we point out that this 'sticking' to a RE technology has emerged and manifested in multiple ways in the case countries. Examples include relying on existing cultural capacities when navigating energy policy direction, strategically promoting scaling of technology markets to root new energy practices in society and developing energy policies as an extension of existing socio-technical structures. In order to understand these dynamics in more depth, we utilize literature on policy robustness and resilience. While all the case countries, Denmark, Germany, and Finland, have generated robust RE policy goals, Finland has failed to foster resilience simultaneously. We conclude that analysing stickiness of policy elements can be fruitful when seeking to understand and design transformative policies. Further, it can be taken as a complementary analytical perspective in the policy mix studies. [ABSTRACT FROM AUTHOR]

Despite rising attention to pathways thinking in multiple domains such as climate adaptation, energy supply planning, and flood risk management, their spatial translation is so far understudied. We set out to study how spatial design based on pathways thinking can help develop more adaptive and sustainable landscapes. Using landscape analysis, field research, and research-through-designing in a case study on climate resilience in Boston (USA), we argue for better understanding of the spatial and design consequences of pathways in general. Our results indicate that pathways can be spatially translated, demanding landscape-informed choices when sequencing different policy actions. We found that spatial designing makes the landscape consequences of pathways transparent and enables policy-makers to replace the input of policy actions with spatial interventions, select pathways according to different underlying design strategies, use the mapped pathways to initiate an iterative research-through-designing process to test and inform different designs, and spatially visualize the pathways and possible sequences of actions. We conclude that policy-makers should be cognizant about the spatial implications of pathways and offer directions to enrich applications of pathways thinking for achieving adaptive and sustainable landscapes. [ABSTRACT FROM AUTHOR]

Adaptiveness of sex ratio control by the solitary parasitoid wasp Itoplectis naranyae (Hymenoptera: Ichneumonidae) in response to host size was studied, by examining whether differential effects of host size on the fitness of resulting wasps are to be found between males andfemales. The offspring sex ratio (male ratio) decreased with increasing host size. Larger hosts yielded larger wasps. Male larvae were less efficient in consuming larger hosts than female larvae. No significant interaction in development time was found between parasitoid sexand host size. Larger female wasps lived longer than smaller females, while longevity of male wasps did not increase with increasing waspsize. Smaller males were able to mate either with small or with large females, while larger males failed to mate with small females. Larger female wasps had a greater number of ovarioles and mature eggs at any one time than smaller females, although the number of eggs produced per host-feeding was not influenced by female wasps. Thus, the differential effect of host size on the fitness of males and females exists in I. naranyae. The basic assumption of the host-size model was therefore satisfied, demonstrating that sex ratio control by I. naranyae in response to host size is adaptive. [ABSTRACT FROM AUTHOR]