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Distribution centers (DCs) are an important part of the modern logistics system. The selection of a location for a DC is significant for saving costs and reducing externalities caused by distribution. In this paper, we propose a new hybrid method based on the analytic hierarchy process (AHP) and 2-tuple hybrid ordered weighted averaging (THOWA) to select the location of a DC in a megacity. First, we propose a new set of evaluation criteria integrating economic, political, social and ecological information based on the characteristics of Chinese megacities. Second, subjective criteria weights are calculated by AHP combining the evaluation of logistics experts. Third, experts from academia, enterprise and government assess the performance of alternatives. In addition, the overall evaluation values are aggregated by an improved THOWA operator to rank the alternatives. Finally, we conduct a sensitivity analysis to investigate the influence of criteria weights on the decision-making process. The proposed method is novel and addresses the uncertainty under limited quantitative information, which has the advantages of avoiding information loss and distortion problems in the integrating process and operating linguistic evaluation information effectively. The proposed method can be practically applied by municipal planning departments in deciding on the location of new DCs. A numerical application of the proposed method is provided. [ABSTRACT FROM AUTHOR]

Tourist satisfaction has always been a crucial research issue in the tourism economy. This paper utilizes the Spatial Durbin Model (SDM) to analyze the impact of urban tourism satisfaction on urban macroeconomics from a macro perspective, using quarterly data on tourist satisfaction in 35 large and medium-sized cities along with major urban macroeconomic variables. This study is quite distinct from previous research that focused on constructing a tourist satisfaction index and analyzing the influence factors of tourism satisfaction from the perspective of the micro-level internal composition of tourism. The empirical results show: Firstly, in respect of the impact of urban tourists' satisfaction on the GDP income of cities, the SDM and the SDM with a lagged first-order dependent variable (SDM_dlag) show that the short-term and long-term indirect effects of log-tourist satisfaction are significantly positive, indicating that city satisfaction has a significant positive spatial spillover effect on GDP growth in other cities; Secondly, in respect of the influence of urban tourist satisfaction on the cost of urban life in the SDM, the long-term direct and indirect effects of logarithmic satisfaction are significantly positive, implying, in the long run, that tourist satisfaction has a positive intraregional spillover effect and spatial spillover effect on urban living costs; Finally, the SDM_dlag for the regression of urban tourist satisfaction on the cost of urban daily life shows that the short-run direct and indirect effects of city tourist satisfaction are significantly negative, indicating that tourist satisfaction has intra-regional and spatial spillover effects, and its rise will reduce the cost of living expenses in local and other cities in the short term. Overall, we have further elucidated the role of different levels of urban tourist satisfaction in city macroeconomics from the spatial dimension, thereby enriching the existing research on tourist satisfaction to some certain extent. [ABSTRACT FROM AUTHOR]

Drug response prediction is a critical step for personalized treatment of cancer patients and ultimately leads to precision medicine. A lot of machine-learning based methods have been proposed to predict drug response from different types of genomic data. However, currently available methods could only give a “point” prediction of drug response value but fail to provide the reliability and distribution of the prediction, which are of equal interest in clinical practice. In this paper, we proposed a method based on quantile regression forest and applied it to the CCLE dataset. Through the out-of-bag validation, our method achieved much higher prediction accuracy of drug response than other available tools. The assessment of prediction reliability by prediction intervals and its significance in personalized medicine were illustrated by several examples. Functional analysis of selected drug response associated genes showed that the proposed method achieves more biologically plausible results. [ABSTRACT FROM AUTHOR]

Small-holding farmers in the developing world suffer from sub-optimal crop yields because they lack a soil diagnostic system that is affordable, usable, and actionable. This paper details the fabrication and characterization of an integrated point-of-use soil-testing system, comprised of disposable ion-selective electrode strips and a handheld electrochemical reader. Together, the strips and reader transduce soil ion concentrations into to an alphanumeric output that can be communicated via text message to a central service provider offering immediate, customized fertilizer advisory. The solid-state ion-selective electrode (SS-ISE) strips employ a two-electrode design with screen-printable carbon nanotube ink serving as the electrical contacts for the working and reference electrodes. The working electrode comprises a plasticizer-free butyl acrylate ion-selective membrane (ISM), doped with an ion-selective ionophore and lipophilic salt. Meanwhile, the reference electrode includes a screen-printed silver-silver chloride ink and a polyvinyl-butyral membrane, which is doped with sodium chloride for stable reference potentials. As a proof of concept, potassium-selective electrodes are studied, given potassium’s essential role in plant growth and reproduction. The ISE-based system is reproducibly manufactured to yield a Nernstian response with a sub-micromolar detection limit (pK+ of 5.18 ± 0.08) and near-Nernstian sensitivity (61 mV/decade) in the presence of a 0.02 M strontium chloride extraction solution. Analysis of soil samples using the printed electrodes and reader yielded a correlation coefficient of 푅2 = 0.89 with respect to values measured via inductively coupled plasma atomic emission spectroscopy (ICP-AES). The reliable performance of this system is encouraging toward its deployment for soil nutrient management in resource-limited environments. [ABSTRACT FROM AUTHOR]

Background: Digital spaces, and in particular social networking sites, are becoming increasingly present and influential in the functioning of our democracies. In this paper, we propose an integrated methodology for the data collection, the reconstruction, the analysis and the visualization of the development of a country’s political landscape from Twitter data. Method: The proposed method relies solely on the interactions between Twitter accounts and is independent of the characteristics of the shared contents such as the language of the tweets. We validate our methodology on a case study on the 2017 French presidential election (60 million Twitter exchanges between more than 2.4 million users) via two independent methods: the comparison between our automated political categorization and a human categorization based on the evaluation of a sample of 5000 profiles descriptions; the correspondence between the reconfigurations detected in the reconstructed political landscape and key political events reported in the media. This latter validation demonstrated the ability of our approach to accurately reflect the reconfigurations at play in the off-line political scene. Results: We built on this reconstruction to give insights into the opinion dynamics and the reconfigurations of political communities at play during a presidential election. First, we propose a quantitative description and analysis of the political engagement of members of political communities. Second, we analyze the impact of political communities on information diffusion and in particular on their role in the fake news phenomena. We measure a differential echo chamber effect on the different types of political news (fake news, debunks, standard news) caused by the community structure and emphasize the importance of addressing the meso-structures of political networks in understanding the fake news phenomena. Conclusions: Giving access to an intermediate level, between sociological surveys in the field and large statistical studies (such as those conducted by national or international organizations) we demonstrate that social networks data make it possible to qualify and quantify the activity of political communities in a multi-polar political environment; as well as their temporal evolution and reconfiguration, their structure, their alliance strategies and their semantic particularities during a presidential campaign through the analysis of their digital traces. We conclude this paper with a comment on the political and ethical implications of the use of social networks data in politics. We stress the importance of developing social macroscopes that will enable citizens to better understand how they collectively make society and propose as example the “Politoscope”, a macroscope that delivers some of our results in an interactive way. [ABSTRACT FROM AUTHOR]

Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diversity of snowball samples. In this study, we performed the first quantitative, medium-N analysis of snowball sampling to identify pathways to sample diversity, analysing 211 reach-outs conducted via snowball sampling, resulting in 81 interviews; these interviews were administered between April and August 2015 for a research project on anti-dam movements in Southeast Asia. Based upon this analysis, we were able to refine and enhance the previous recommendations (e.g., showcasing novel evidence on the value of multiple seeds or face-to-face interviews). This paper may thus be of particular interest to scholars employing or intending to employ snowball sampling. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the five-species Jungle game in the framework of evolutionary game theory. We address the coexistence and biodiversity of the system using mean-field theory and Monte Carlo simulations. Then, we find that the inhibition from the bottom-level species to the top-level species can be critical factors that affect biodiversity, no matter how it is distributed, whether homogeneously well mixed or structured. We also find that predators’ different preferences for food affect species’ coexistence. [ABSTRACT FROM AUTHOR]

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. [ABSTRACT FROM AUTHOR]

Demographic data are important to wildlife managers to gauge population health, to allow populations to be utilised sustainably, and to inform conservation efforts. We analysed published demographic data on the world’s wildfowl to examine taxonomic and geographic biases in study, and to identify gaps in knowledge. Wildfowl (order: Anseriformes) are a comparatively well studied bird group which includes 169 species of duck, goose and swan. In all, 1,586 wildfowl research papers published between 1911 and 2010 were found using Web of Knowledge (WoK) and Google Scholar. Over half of the research output involved just 15 species from seven genera. Research output was strongly biased towards ‘high income’ countries, common wildfowl species, and measures of productivity, rather than survival and movement patterns. There were significantly fewer demographic data for the world’s 31 threatened wildfowl species than for non-threatened species. Since 1994, the volume of demographic work on threatened species has increased more than for non-threatened species, but still makes up only 2.7% of total research output. As an aid to research prioritisation, a metric was created to reflect demographic knowledge gaps for each species related to research output for the species, its threat status, and availability of potentially useful surrogate data from congeneric species. According to the metric, the 25 highest priority species include thirteen threatened taxa and nine species each from Asia and South America, and six from Africa. [ABSTRACT FROM AUTHOR]

This paper proposes a road network growing model with the consideration of population distribution and central business district (CBD) attraction. In the model, the relative neighborhood graph (RNG) is introduced as the connection mechanism to capture the characteristics of road network topology. The simulation experiment is set up to illustrate the effects of population distribution and CBD attraction on the characteristics of road network. Moreover, several topological attributes of road network is evaluated by using coverage, circuitness, treeness and total length in the experiment. Finally, the suggested model is verified in the simulation of China and Beijing Highway networks. [ABSTRACT FROM AUTHOR]

Distance sampling is a technique for estimating the abundance of animals or other objects in a region, allowing for imperfect detection. This paper evaluates the statistical efficiency of the method when its assumptions are met, both theoretically and by simulation. The theoretical component of the paper is a derivation of the asymptotic variance penalty for the distance sampling estimator arising from uncertainty about the unknown detection parameters. This asymptotic penalty factor is tabulated for several detection functions. It is typically at least 2 but can be much higher, particularly for steeply declining detection rates. The asymptotic result relies on a model which makes the strong assumption that objects are uniformly distributed across the region. The simulation study relaxes this assumption by incorporating over-dispersion when generating object locations. Distance sampling and strip transect estimators are calculated for simulated data, for a variety of overdispersion factors, detection functions, sample sizes and strip widths. The simulation results confirm the theoretical asymptotic penalty in the non-overdispersed case. For a more realistic overdispersion factor of 2, distance sampling estimation outperforms strip transect estimation when a half-normal distance function is correctly assumed, confirming previous literature. When the hazard rate model is correctly assumed, strip transect estimators have lower mean squared error than the usual distance sampling estimator when the strip width is close enough to its optimal value (± 75% when there are 100 detections; ± 50% when there are 200 detections). Whether the ecologist can set the strip width sufficiently accurately will depend on the circumstances of each particular study. [ABSTRACT FROM AUTHOR]

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. [ABSTRACT FROM AUTHOR]

Structural patterns in collaboration networks are essential for understanding how new ideas, research practices, innovation or cooperation circulate and develop within academic communities and between and within university departments. In our research, we explore and investigate the structure of the collaboration network formed by the academics working full-time within all the 17 sociology departments across Romania. We show that the collaboration network is sparse and fragmented, and that it constitutes an environment that does not promote the circulation of new ideas and innovation within the field. Although recent years have witnessed an increase in the productivity of Romanian sociologists, there is still ample room for improvement in terms of the interaction infrastructure that ought to link individuals together so that they could maximize their potentials. We also fail to discern evidence in favor of the Matthew effect governing the growth of the network, which suggests scientific success and productivity are not rewarded. Instead, the structural properties of the collaboration network are partly those of a core-periphery network, where the spread of innovation and change can be explained by structural equivalence rather than by interpersonal influence models. We also provide support for the idea that, within the observed network, collaboration is the product of homophily rather than prestige effects. Further research on the subject based on data from other countries in the region is needed to place our results in a comparative framework, in particular to discern whether the behavior of the Romanian sociologist community is unique or rather common. [ABSTRACT FROM AUTHOR]

Listroscelidinae (Orthoptera: Tettigoniidae) are insectivorous Pantropical katydids whose taxonomy presents a long history of controversy, with several genera incertae sedis. This work focused on species occurring in the Brazilian Atlantic Forest, one of the world's most threatened biomes. We examined material deposited in scientific collections and visited 15 conservation units from Rio de Janeiro to southern Bahia between November 2011 and January 2012, catching 104 specimens from 10 conservation units. Based on morphological and molecular data we redefined Listroscelidini, adding a new tribe, new genus and eight new species to the subfamily. Using morphological analysis, we redescribed and added new geographic records for six species, synonymized two species and built a provisional identification key for the Atlantic Forest Listroscelidinae. Molecular results suggest two new species and a new genus to be described, possibly by the fission of the genus Hamayulus. We also proposed a 500 bp region in the final portion of the COI to be used as a molecular barcode. Our data suggest that the Atlantic Forest Listroscelidinae are seriously endangered, because they occur in highly preserved forest remnants, show high rates of endemism and have a narrow geographic distribution. Based on our results, we suggest future collection efforts must take into account the molecular barcode data to accelerate species recognition. [ABSTRACT FROM AUTHOR]

This paper examines how to maximize contribution in public good dilemmas by arranging people into homogeneous or heterogeneous subgroups. Past studies on the effect of homogeneity of efficacy have exclusively manipulated group composition in their experimental designs, which might have imposed a limit on ecological validity because group membership may not be easily changed in reality. In this study, we maintained the same group composition but varied the subgroup composition. We developed a public good dilemmas paradigm in which participants were assigned to one of the four conditions (high- vs. low-efficacy; homogeneous vs. heterogeneous subgroup) to produce their endowments and then to decide how much to contribute. We found that individuals in homogeneous and heterogeneous subgroups produced a similar amount and proportion of contribution, which was due to the two mediating effects that counteracted each other, namely (a) perceived efficacy relative to subgroup and (b) expectation of contribution of other subgroup members. This paper demonstrates both the pros and cons of arranging people into homogeneous and heterogeneous subgroups of efficacy. [ABSTRACT FROM AUTHOR]

Accurate reporting and forecasting of PM2.5 concentration are important for improving public health. In this paper, we propose a partial differential equation (PDE) model, specially, a linear diffusive equation, to describe the spatial-temporal characteristics of PM2.5 in order to make short-term prediction. We analyze the temporal and spatial patterns of a real dataset from China’s National Environmental Monitoring and validate the PDE-based model in terms of predicting the PM2.5 concentration of the next day by the former days’ history data. Our experiment results show that the PDE model is able to characterize and predict the process of PM2.5 transport. For example, for 300 continuous days of 2016, the average prediction accuracy of the PDE model over all city-regions is 93% or 83% based on different accuracy definitions. To our knowledge, this is the first attempt to use PDE-based model to study PM2.5 prediction in both temporal and spatial dimensions. [ABSTRACT FROM AUTHOR]

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

This paper presents the study of the fungi remains preserved in the waterlogged deposits of the Neolithic site of La Draga. These resources had the potential of being used as food and medicine, but also as tinder. Fire was without a doubt one of the most important resources for past people. It was used for lighting, heating, processing food and other materials, cooking and protection, and also possessed social and ritual significance. Hearths are one of the most common features at archaeological sites, but very often little attention is paid to the question of how these fires were lit, and they are seldom reflected in the archaeological record. In order to produce fire by percussion, an intermediate material is required between the sparks and the fuel. Fruiting bodies of fungi are a potential form of tinder, but are less inclined to be well-preserved than other materials. This paper presents the fungal fruiting bodies found at the Neolithic site of La Draga and discusses the meaning of their presence within the archaeological context of the site and European Prehistory. [ABSTRACT FROM AUTHOR]

Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks. [ABSTRACT FROM AUTHOR]

Background: There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species’ responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Objectives: Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. Data sources and study eligibility criteria: We systematically reviewed SDM studies published from 2003–2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. Synthesis methods and limitations: We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. Results: There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. Conclusions: We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis. [ABSTRACT FROM AUTHOR]

The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to “photograph” the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distance trip supplement for public transportations and private vehicles. A unique value of the bike flow data generated by these BSSs is to understand the human mobility in a short-distance trip. This understanding of the population on short-distance trip is lacking, limiting our capacity in management and operation of BSSs. Many existing operations research and management methods for BSS impose assumptions that emphasize statistical simplicity and homogeneity. Therefore, a deep understanding of the statistical patterns embedded in the bike flow data is an urgent and overriding issue to inform decision-makings for a variety of problems including traffic prediction, station placement, bike reallocation, and anomaly detection. In this paper, we aim to conduct a comprehensive analysis of the bike flow data using two large datasets collected in Chicago and Hangzhou over months. Our analysis reveals intrinsic structures of the bike flow data and regularities in both spatial and temporal scales such as a community structure and a taxonomy of the eigen-bike-flows. [ABSTRACT FROM AUTHOR]

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test. [ABSTRACT FROM AUTHOR]

Audio recordings of the environment are an increasingly important technique to monitor biodiversity and ecosystem function. While the acquisition of long-duration recordings is becoming easier and cheaper, the analysis and interpretation of that audio remains a significant research area. The issue addressed in this paper is the automated reduction of environmental audio data to facilitate ecological investigations. We describe a method that first reduces environmental audio to vectors of acoustic indices, which are then clustered. This can reduce the audio data by six to eight orders of magnitude yet retain useful ecological information. We describe techniques to visualise sequences of cluster occurrence (using for example, diel plots, rose plots) that assist interpretation of environmental audio. Colour coding acoustic clusters allows months and years of audio data to be visualised in a single image. These techniques are useful in identifying and indexing the contents of long-duration audio recordings. They could also play an important role in monitoring long-term changes in species abundance brought about by habitat degradation and/or restoration. [ABSTRACT FROM AUTHOR]

In a previous paper we showed that the yeast Pichia pastoris X-33 grown in parboiled rice effluent supplemented with glycerol byproduct from the biodiesel industry improved the quality of the effluent. In this paper we show the validation of this yeast (PPE) as probiotic for broilers. Its effect on feed efficiency and immunomodulation was compared with the same yeast grown in yeast peptone dextrose medium (PPY), with Saccharomyces boulardii (SBY) and with the controls fed unsupplemented feed (CON). One-day-old female chicks were vaccinated against infectious bursal disease (IBD) and the titers of anti-IBD antibodies were measured by ELISA. PPE group had the highest mean titres on days 14 and 28 (p<0,05), and at 28 days, 64% of the animals showed seroconvertion. The PPE group also showed the best weight gains at 42 days of age, that, on days 7, 14 and 21 were 19%, 15%, and 8.7% higher, respectively, than the control group. The best feed conversion, 8.2% higher than the control group, was obtained by PPY at 42 days. Histopathological studies did not detect any undesirable effects in the supplemented animals. We concluded that Pichia pastoris X-33 when grown in effluents of the rice parboiling industry supplemented with glycerol byproduct from the biodiesel has probiotic properties for poultry. [ABSTRACT FROM AUTHOR]

The selection of seismic attributes is a key process in reservoir prediction because the prediction accuracy relies on the reliability and credibility of the seismic attributes. However, effective selection method for useful seismic attributes is still a challenge. This paper presents a novel selection method of seismic attributes for reservoir prediction based on the gray relational degree (GRD) and support vector machine (SVM). The proposed method has a two-hierarchical structure. In the first hierarchy, the primary selection of seismic attributes is achieved by calculating the GRD between seismic attributes and reservoir parameters, and the GRD between the seismic attributes. The principle of the primary selection is that these seismic attributes with higher GRD to the reservoir parameters will have smaller GRD between themselves as compared to those with lower GRD to the reservoir parameters. Then the SVM is employed in the second hierarchy to perform an interactive error verification using training samples for the purpose of determining the final seismic attributes. A real-world case study was conducted to evaluate the proposed GRD-SVM method. Reliable seismic attributes were selected to predict the coalbed methane (CBM) content in southern Qinshui basin, China. In the analysis, the instantaneous amplitude, instantaneous bandwidth, instantaneous frequency, and minimum negative curvature were selected, and the predicted CBM content was fundamentally consistent with the measured CBM content. This real-world case study demonstrates that the proposed method is able to effectively select seismic attributes, and improve the prediction accuracy. Thus, the proposed GRD-SVM method can be used for the selection of seismic attributes in practice. [ABSTRACT FROM AUTHOR]

Due to the heavy exploitation of holothurians over the last few decades, it is necessary to implement fishing regulations aimed at reversing this situation. Holothurians require specific regulations that take into account their biology and ecology. Their behavior to group and form patches as a strategy for feeding, defense and reproduction, makes them vulnerable to overfishing. The higher the population density, the higher the catchability coefficient, and because they are sedentary organisms, the catchability does not change significantly until the density is very low. Hence, the stock assessment of holothurians can be improved by analyzing their spatial distribution. This paper proposes a stock assessment technique that considers the spatial distribution pattern of the sea cucumber Isostichopus badionotus from Yucatan, Mexico. A bioeconomic spatial model was developed to explain the interactions between fishing effort allocation, quasi-profits and the population in the short term. Because of the high price of the species and the low production costs, artisanal fishers preferred to maximize short-term quasi-profits, rather than the long-term benefits they could gain with low fishing mortality rates. [ABSTRACT FROM AUTHOR]

Land tenure and tenure security are among the most important factors determining the viability and success of Reducing Emissions from Deforestation and Forest Degradation (REDD+) initiatives. The premise of the present paper is that territorial conflicts lead to forest loss and compromise the successful implementation of REDD+. Within this context, the main objectives of this paper are to (i) document, relying on participatory methods, the extent to which land conflicts drive deforestation and (ii) reflect on the legal context of REDD+ examining if, from an Indigenous perspective, it offers tools to resolve such conflicts. We used the Upper Bayano Watershed in eastern Panama as a case study of complex land tenure dynamics, and their effects on forest conservation in the context of REDD+. Combining a range of participatory methods including participatory mapping and forest carbon stock assessment, we estimated the consequences of land invasions on forest carbon stocks. Our analysis shows that invasions of Indigenous territories amounted to 27.6% of the total deforestation for the period of 2001–2014. The situation is of paramount concern in the Embera territory of Majé where 95.4% of total deforestation was caused by colonist invaders. Using and validating the maps made freely available by the Global Forest Change initiative of the University of Maryland, we then developed a reference level for the watershed and carried out a back of the envelop estimation of likely REDD+ revenue, showing its potential to bring much needed income to Indigenous communities striving to protect their forest estate. Our analysis of current legislation in Panama highlights confusion and important legal voids and emphasizes the strong links between land tenure, carbon ownership, and territorial invasions. The options and shortcoming of implementing REDD+ in Indigenous territories is discussed in the conclusion taking our legal review into account. [ABSTRACT FROM AUTHOR]

“The Belt and Road” initiative has been expected to facilitate interactions among numerous city centers. This initiative would generate a number of centers, both economic and political, which would facilitate greater interaction. To explore how information flows are merged and the specific opportunities that may be offered, Chinese cities along “the Belt and Road” are selected for a case study. Furthermore, urban networks in cyberspace have been characterized by their infrastructure orientation, which implies that there is a relative dearth of studies focusing on the investigation of urban hierarchies by capturing information flows between Chinese cities along “the Belt and Road”. This paper employs Baidu, the main web search engine in China, to examine urban hierarchies. The results show that urban networks become more balanced, shifting from a polycentric to a homogenized pattern. Furthermore, cities in networks tend to have both a hierarchical system and a spatial concentration primarily in regions such as Beijing-Tianjin-Hebei, Yangtze River Delta and the Pearl River Delta region. Urban hierarchy based on web search activity does not follow the existing hierarchical system based on geospatial and economic development in all cases. Moreover, urban networks, under the framework of “the Belt and Road”, show several significant corridors and more opportunities for more cities, particularly western cities. Furthermore, factors that may influence web search activity are explored. The results show that web search activity is significantly influenced by the economic gap, geographical proximity and administrative rank of the city. [ABSTRACT FROM AUTHOR]

The automatic generation of test cases oriented paths in an effective manner is a challenging problem for structural testing of software. The use of search-based optimization methods, such as genetic algorithms (GAs), has been proposed to handle this problem. This paper proposes an improved adaptive genetic algorithm (IAGA) for test cases generation by maintaining population diversity. It uses adaptive crossover rate and mutation rate in dynamic adjustment according to the differences between individual similarity and fitness values, which enhances the exploitation of searching global optimum. This novel approach is experimented and tested on a benchmark and six industrial programs. The experimental results confirm that the proposed method is efficient in generating test cases for path coverage. [ABSTRACT FROM AUTHOR]

Background: Enhancing water provision services is a common target in forest restoration projects worldwide due to growing concerns over freshwater scarcity. However, whether or not forest cover expansion or restoration can improve water provision services is still unclear and highly disputed. Purpose: The goal of this review is to provide a balanced and impartial assessment of the impacts of forest restoration and forest cover expansion on water yields as informed by the scientific literature. Potential sources of bias on the results of papers published are also examined. Data sources: English, Spanish and Portuguese peer-review articles in Agricola, CAB Abstracts, ISI Web of Science, JSTOR, Google Scholar, and SciELO. Databases were searched through 2015. Search terms: Intervention terms included forest restoration, regeneration/regrowth, forest second-growth, forestation/afforestation, and forestry. Target terms included water yield/quantity, streamflow, discharge, channel runoff, and annual flow. Study selection and eligibility criteria: Articles were pre-selected based on key words in the title, abstract or text. Eligible articles addressed relevant interventions and targets and included quantitative information. Results: Most studies reported decreases in water yields following the intervention, while other hydrological benefits have been observed. However, relatively few studies focused specifically on forest restoration, especially with native species, and/or on projects done at large spatial or temporal scales. Information is especially limited for the humid tropics and subtropics. Conclusions and implications of key findings: While most studies reported a decrease in water yields, meta-analyses from a sub-set of studies suggest the potential influence of temporal and/or spatial scales on the outcomes of forest cover expansion or restoration projects. Given the many other benefits of forest restoration, improving our understanding of when and why forest restoration can lead to recovery of water yields is crucial to help improve positive outcomes and prevent unintended consequences. Our study identifies the critical types of studies and associated measurements needed. [ABSTRACT FROM AUTHOR]

Modern cities are engines of production, innovation, and growth. However, urbanization also increases both local and global pollution from household consumption and firms’ production. Do emissions change proportionately to city size or does pollution tend to outpace or lag urbanization? Do emissions scale differently with population versus economic growth or are emissions, population, and economic growth inextricably linked? How are the scaling relationships between emissions, population, and economic growth affected by environmental regulation? This paper examines the link between urbanization, economic growth and pollution using data from Metropolitan Statistical Areas (MSAs) in the United States between 1999 and 2011. We find that the emissions of local air pollution in these MSAs scale according to a ¾ power law with both population size and gross domestic product (GDP). However, the monetary damages from these local emissions scale linearly with both population and GDP. Counties that have previously been out of attainment with the local air quality standards set by the Clean Air Act show an entirely different relationship: local emissions scale according to the square root of population, while the monetary damages from local air pollution follow a 2/3rds power law with population. Counties out of attainment are subject to more stringent emission controls; we argue based on this that enforcement of the Clean Air Act induces sublinear scaling between emissions, damages, and city size. In contrast, we find that metropolitan GDP scales super-linearly with population in all MSAs regardless of attainment status. Summarizing, our findings suggest that environmental policy limits the adverse effects of urbanization without interfering with the productivity benefits that manifest in cities. [ABSTRACT FROM AUTHOR]

This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees. [ABSTRACT FROM AUTHOR]

Organizations are increasingly using sustainability reports to inform their stakeholders and the public about their sustainability practices. We apply topic modelling to 9,514 sustainability reports published between 1999 and 2015 in order to identify common topics and, thus, the most common practices described in these reports. In particular, we identify forty-two topics that reflect sustainability and focus on the coverage and trends of economic, environmental, and social sustainability topics. Among the first to analyse such a large amount of data on organizations’ sustainability reporting, the paper serves as an example of how to apply natural language processing as a strategy of inquiry in sustainability research. The paper also derives from the data analysis ten propositions for future research and practice that are of immediate value for organizations and researchers. [ABSTRACT FROM AUTHOR]

Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when using a signal processing technique to analyze them. In this paper, we present an experimental study of the characteristics of nine of the most frequently-used DNR. The objective of this paper is to evaluate the behavior of each representation when used to measure the similarity of a given pair of DNA sequences. [ABSTRACT FROM AUTHOR]

This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. [ABSTRACT FROM AUTHOR]

The World Health Organization (WHO) recognizes point-of-use water treatment (PoUWT) technologies as effective means to improve water quality. This paper investigates long-term performance and social acceptance of a novel PoUWT technology, a silver-infused ceramic tablet, in Limpopo Province, South Africa. When placed in a water storage container, the silver-embedded ceramic tablet releases silver ions into water, thereby disinfecting microbial pathogens and leaving the water safe for human consumption. As a result of its simplicity and efficiency, the silver-embedded ceramic tablet can serve as a stand-alone PoUWT method and as a secondary PoUWT to improve exisitng PoUWT methods, such as ceramic water filters. In this paper, three PoUWT interventions were conducted to evaluate the silver-embedded ceramic tablet: (1) the silver-embedded ceramic tablet as a stand-alone PoUWT method, (2) ceramic water filters stand-alone, and (3) a filter-tablet combination. The filter-tablet combination evaluates the silver-embedded ceramic tablet as a secondary PoUWT method when placed in the lower reservoir of the ceramic water filter system to provide residual disinfection post-filtration. Samples were collected from 79 households over one year and analyzed for turbidity, total silver levels and coliform bacteria. Results show that the silver-embedded ceramic tablet effectively reduced total coliform bacteria (TC) and E. coli when used as a stand-alone PoUWT method and when used in combination with ceramic water filters. The silver-embedded ceramic tablet’s performance as a stand-alone PoUWT method was comparable to current inexpensive, single-use PoUWT methods, demonstrating 100% and 75% median reduction in E. coli and TC, respectively, after two months of use. Overall, the the filter-tablet combination performed the best of the three interventions, providing a 100% average percent reduction in E. coli over one year. User surveys were also conducted and indicated that the silver-embedded ceramic tablet was simple to use and culturally appropriate. Also, silver levels in all treated water samples remained below 20 μg/L, significantly lower than the drinking water standard of 100 μg/L, making it safe for consumption. Long-term data demonstrates that the silver-embedded ceramic tablet has beneficial effects even after one year of use. This study demonstrates that the silver-embedded ceramic tablet can effectively improve water quality when used alone, or with ceramic water filters, to reduce rates of recontamination. Therefore, the tablet has the potential to provide a low-cost means to purify water in resource-limited settings. [ABSTRACT FROM AUTHOR]

While basic access to clean water is critical, another important issue is the affordability of water access for people around the globe. Prior international work has highlighted that a large proportion of consumers could not afford water if priced at full cost recovery levels. Given growing concern about affordability issues due to rising water rates, and a comparative lack of work on affordability in the developed world, as compared to the developing world, more work is needed in developed countries to understand the extent of this issue in terms of the number of households and persons impacted. To address this need, this paper assesses potential affordability issues for households in the United States using the U.S. EPA’s 4.5% affordability criteria for combined water and wastewater services. Analytical results from this paper highlight high-risk and at-risk households for water poverty or unaffordable water services. Many of these households are clustered in pockets of water poverty within counties, which is a concern for individual utility providers servicing a large proportion of customers with a financial inability to pay for water services. Results also highlight that while water rates remain comparatively affordable for many U.S. households, this trend will not continue in the future. If water rates rise at projected amounts over the next five years, conservative projections estimate that the percentage of U.S. households who will find water bills unaffordable could triple from 11.9% to 35.6%. This is a concern due to the cascading economic impacts associated with widespread affordability issues; these issues mean that utility providers could have fewer customers over which to spread the large fixed costs of water service. Unaffordable water bills also impact customers for whom water services are affordable via higher water rates to recover the costs of services that go unpaid by lower income households. [ABSTRACT FROM AUTHOR]

Selecting appropriate environmental variables is a key step in ecology. Terrain attributes (e.g. slope, rugosity) are routinely used as abiotic surrogates of species distribution and to produce habitat maps that can be used in decision-making for conservation or management. Selecting appropriate terrain attributes for ecological studies may be a challenging process that can lead users to select a subjective, potentially sub-optimal combination of attributes for their applications. The objective of this paper is to assess the impacts of subjectively selecting terrain attributes for ecological applications by comparing the performance of different combinations of terrain attributes in the production of habitat maps and species distribution models. Seven different selections of terrain attributes, alone or in combination with other environmental variables, were used to map benthic habitats of German Bank (off Nova Scotia, Canada). 29 maps of potential habitats based on unsupervised classifications of biophysical characteristics of German Bank were produced, and 29 species distribution models of sea scallops were generated using MaxEnt. The performances of the 58 maps were quantified and compared to evaluate the effectiveness of the various combinations of environmental variables. One of the combinations of terrain attributes–recommended in a related study and that includes a measure of relative position, slope, two measures of orientation, topographic mean and a measure of rugosity–yielded better results than the other selections for both methodologies, confirming that they together best describe terrain properties. Important differences in performance (up to 47% in accuracy measurement) and spatial outputs (up to 58% in spatial distribution of habitats) highlighted the importance of carefully selecting variables for ecological applications. This paper demonstrates that making a subjective choice of variables may reduce map accuracy and produce maps that do not adequately represent habitats and species distributions, thus having important implications when these maps are used for decision-making. [ABSTRACT FROM AUTHOR]

This paper presents an experimental characterization of millimeter-wave (mm-wave) channels in the 6.5 GHz, 10.5 GHz, 15 GHz, 19 GHz, 28 GHz and 38 GHz frequency bands in an indoor corridor environment. More than 4,000 power delay profiles were measured across the bands using an omnidirectional transmitter antenna and a highly directional horn receiver antenna for both co- and cross-polarized antenna configurations. This paper develops a new path-loss model to account for the frequency attenuation with distance, which we term the frequency attenuation (FA) path-loss model and introduce a frequency-dependent attenuation factor. The large-scale path loss was characterized based on both new and well-known path-loss models. A general and less complex method is also proposed to estimate the cross-polarization discrimination (XPD) factor of close-in reference distance with the XPD (CIX) and ABG with the XPD (ABGX) path-loss models to avoid the computational complexity of minimum mean square error (MMSE) approach. Moreover, small-scale parameters such as root mean square (RMS) delay spread, mean excess (MN-EX) delay, dispersion factors and maximum excess (MAX-EX) delay parameters were used to characterize the multipath channel dispersion. Multiple statistical distributions for RMS delay spread were also investigated. The results show that our proposed models are simpler and more physically-based than other well-known models. The path-loss exponents for all studied models are smaller than that of the free-space model by values in the range of 0.1 to 1.4 for all measured frequencies. The RMS delay spread values varied between 0.2 ns and 13.8 ns, and the dispersion factor values were less than 1 for all measured frequencies. The exponential and Weibull probability distribution models best fit the RMS delay spread empirical distribution for all of the measured frequencies in all scenarios. [ABSTRACT FROM AUTHOR]

Although studies have increasingly linked air pollution to specific health outcomes, less well understood is how public perceptions of air quality respond to changing pollutant levels. The growing availability of air pollution measurements and the proliferation of social media provide an opportunity to gauge public discussion of air quality conditions. In this paper, we consider particulate matter (PM) measurements from four Chinese megacities (Beijing, Shanghai, Guangzhou, and Chengdu) together with 112 million posts on Weibo (a popular Chinese microblogging system) from corresponding days in 2011–2013 to identify terms whose frequency was most correlated with PM levels. These correlations are used to construct an Air Discussion Index (ADI) for estimating daily PM based on the content of Weibo posts. In Beijing, the Chinese city with the most PM as measured by U.S. Embassy monitor stations, we found a strong correlation (R = 0.88) between the ADI and measured PM. In other Chinese cities with lower pollution levels, the correlation was weaker. Nonetheless, our results show that social media may be a useful proxy measurement for pollution, particularly when traditional measurement stations are unavailable, censored or misreported. [ABSTRACT FROM AUTHOR]

In nature, protozoa play a major role in controlling bacterial populations. This paper proposes a microfluidic device for the study of protozoa behaviors change due to their chemotactic response in the presence of bacterial cells. A three-channel microfluidic device was designed using a nitrocellulose membrane into which channels were cut using a laser cutter. The membrane was sandwiched between two glass slides; a Euglena suspension was then allowed to flow through the central channel. The two side channels were filled with either, 0.1% peptone as a negative control, or a Listeria suspension respectively. The membrane design prevented direct interaction but allowed Euglena cells to detect Listeria cells as secretions diffused through the nitrocellulose membrane. A significant number of Euglena cells migrated toward the chambers near the bacterial cells, indicating a positive chemotactic response of Euglena toward chemical cues released from Listeria cells. Filtrates collected from Listeria suspension with a series of molecular weight cutoffs (3k, 10k and 100k) were examined in Euglena chemotaxis tests. Euglena cells were attracted to all filtrates collected from the membrane filtration with different molecular weight cutoffs, suggesting small molecules from Listeria might be the chemical cues to attract protozoa. Headspace volatile organic compounds (VOC) released from Listeria were collected, spiked to 0.1% peptone and tested as the chemotactic effectors. It was discovered that the Euglena cells responded quickly to Listeria VOCs including decanal, 3,5- dimethylbenzaldehyde, ethyl acetate, indicating bacterial VOCs were used by Euglena to track the location of bacteria. [ABSTRACT FROM AUTHOR]

The quandong or native peach (Santalum acuminatum R.Br.) has been recognised as an important and tasty food resource among Aboriginal Australians in arid and semi-arid areas of southern Australia. It is valued for its fruit that is consumed raw or dried, and for its kernel, which is eaten raw or ground into paste for medicinal and skin care purposes. This paper reports on a study of ground stone implements within the Murray Darling Basin that has identified quandong stones as a distinct type of implement made specifically for the efficient cracking of quandong nuts. Data are presented on 1,327 ground stone implements from collections in 12 different locations in the Murray-Darling Basin (MDB), an area almost completely devoid of stone sources. Given the paucity of stone, multi-purpose use of implements is widely documented. Although it was common to find pits present in mortars and other ground stone tools demonstrating multiple functions, including use as anvils, a class of single purpose stones with multiple pits and distinctive form was identified. Most of these were found in areas known for groves of quandong and four were analysed for use-wear and residues along with two other ground stone items from the MDB. The results support their identification as specialised anvil stones for cracking quandong nuts. [ABSTRACT FROM AUTHOR]

The gut microbial community structure of adult Thrips tabaci collected from 10 different agro-climatically diverse locations of India was characterized by using the Illumina MiSeq platform to amplify the V3 region of the 16S rRNA gene of bacteria present in the sampled insects. Analyses were performed to study the bacterial communities associated with Thrips tabaci in India. The complete bacterial metagenome of T. tabaci was comprised of 1662 OTUs of which 62.25% belong to known and 37.7% of unidentified/unknown bacteria. These OTUs constituted 21 bacterial phyla of 276 identified genera. Phylum Proteobacteria was predominant, followed by Actinobacteria, Firmicutes, Bacteroidetes and Cyanobacteria. Additionally, the occurrence of the reproductive endosymbiont, Wolbachia was detected at two locations (0.56%) of the total known OTUs. There is high variation in diversity and species richness among the different locations. Alpha-diversity metrics indicated the higher gut bacterial diversity at Bangalore and lowest at Rahuri whereas higher bacterial species richness at T. tabaci samples from Imphal and lowest at Jhalawar. Beta diversity analyses comparing bacterial communities between the samples showed distinct differences in bacterial community composition of T. tabaci samples from different locations. This paper also constitutes the first record of detailed bacterial communities associated with T. tabaci. The location-wise variation in microbial metagenome profile of T. tabaci suggests that bacterial diversity might be governed by its population genetic structure, environment and habitat. [ABSTRACT FROM AUTHOR]

Differential Evolution (DE) is powerful for global optimization problems. Among DE algorithms, JADE and its variants, whose mutation strategy is DE/current-to-pbest/1 with optional archive, have good performance. A significant feature of the above mutation strategy is that one individual for difference operation comes from the union of the optional external archive and the population. In existing DE algorithms based on the mutation strategy—JADE and its variants, individuals eliminated from the population are send to the archive. In this paper, we propose a scheme for managing the optional external archive. According to our scheme, two subpopulations are maintained in the population. Each of them regards the other as the archive. In experiments, our scheme is applied in JADE and two of its variants—SHADE and L-SHADE. Experimental results show that our scheme can enhance JADE and its variants. Moreover, it can be seen that L-SHADE with our scheme performs significantly better than four DE algorithms, CoBiDE, MPEDE, EDEV, and MLCCDE. [ABSTRACT FROM AUTHOR]

Our food security depends on finding a sustainable alternative to rock phosphate for fertilizer production. Furthermore, over 2 billion people worldwide are currently affected by micronutrient deficiencies, and crop concentrations of essential minerals are declining. This paper examines whether a novel multi-element fertilizer, Thallo®, can produce crop yields comparable to conventional rock phosphate derived fertilizers, and have an additional benefit of increasing essential mineral concentrations. Thallo®, produced from abattoir and recycled industrial by-products, was tested against conventional mineral fertilizers in a pot trial with wheat and grass. In soil, yields were comparable between the fertilizer types, but, in a low-nutrient substrate, Thallo® showed a yield benefit. Elemental concentrations in the plant material typically reflected the relative concentrations in the fertilizer, and Thallo® fertilized plants contained significantly more of some essential elements, such as selenium and zinc. Furthermore, concentrations of the toxic element cadmium were significantly lower in Thallo® fertilized crops. Among the fertilizers, manganese concentrations were greatest in the Thallo®, but within the fertilized plants, they were greatest under the mineral fertilizer, showing the complexity of assessing whether nutrients will be taken up by crops. In summary, fertilizers from livestock waste have the potential to improve wheat and grass concentrations of essential elements while maintaining yields. [ABSTRACT FROM AUTHOR]

With green development becoming a global movement, environmental tax has been adopted by many governments to promote green development. This study analyzes the impact of environmental tax on green development by using a four-dimension dynamical system. The establishment of the system is based on the complex and dynamic interactions among economic development, pollution emissions, resources consumption, and environmental tax, where roles of environmental tax are reflected by the linear parameters. A theoretic analysis shows the complexity of the behavior of the system. Mainly, the existence of chaos is inferred by Lyapunov exponent spectrum and bifurcation diagram, then verified by the presence of a chaotic attractor. An empirical study of the green development dynamical system in China demonstrates the particular evolution paths of economic growth, pollution intensity, and resource intensity under different environmental tax parameters. Results indicate a robust beneficial role of environmental tax on green development. Furthermore, when an environmental tax is imposed, a firm government control, an active consumer awareness, an advanced technology level can stimulate economic growth, decrease pollution intensity, and control the resource intensity. But the government control has a stronger effect. This study provides a viable and promising approach to analyze the role of imposing an environmental tax on green development and may have potential application in other areas and countries. [ABSTRACT FROM AUTHOR]

Living vegetation volume (LVV), one of the most difficult tree parameters to calculate, is among the most important factors that indicates the biological characteristics and ecological functions of the crown. Obtaining precise LVV estimates is, however, challenging task because the irregularities of many crown shapes are difficult to capture using standard forestry field equipment. Terrestrial light detection and ranging (T-LiDAR) can be used to record the three-dimensional structures of trees. The primary branches of Larix olgensis and Quercus mongolica in the Qingyuan Experimental Station of Forest Ecology at the Chinese Academy of Sciences (CAS) were taken as the research objects. A new rapid LVV estimation method called the filling method was proposed in this paper based on a T-LiDAR point cloud. In the proposed method, the branch point clouds are divided into leaf points and wood points. We used RiSCAN PRO 1.64 to manually separate the leaf points and wood points under careful visual inspection, and calculated that leaf points and wood points accounted for 91% and 9% of the number of the point clouds of branches. Then, the equation LVV = V1N (where N is the number of leaf points, and V1 is cube size) is used to calculate LVV. When the laser transmission frequency is 300,000 points/second and the point cloud is diluted to 30% using the octree method, the point cloud can be replaced by a cube (V1) of 6.11 cm3 to fill the branch space. The results showed that good performance for this approach, the measuring accuracy for L. olgensis and Q. mongolica at the levels of α = 0.05 and α = 0.01, respectively (94.35%, 90.01% and 91.99%, 85.63%, respectively). The results suggest that the proposed method can be conveniently used to calculate the LVV of coniferous and broad-leaf species under specific scanning settings. This work is explorative because hypotheses or a theoretical framework have not been previously defined. Rather, we would like to contribute to the formation of hypotheses as a background for further studies. [ABSTRACT FROM AUTHOR]

This paper estimates the price changes in global bluefin tuna (BFT) markets in response to shifts in regional and global landings to evaluate the conservation and economic incentives from changes in the Total Allowable Catch (TAC) managed by all three Regional Fisheries Management Organizations. A fisherman’s income, and thus the financial incentive to accept management measures controlling catch levels, depends in part on how responsive price is to overall catch. Individual fisherman, with their own best interest in mind, used to wish to increase their individual landings and create an incentive to ask to increase the TAC for the industry, without realizing the possible revenue loss due to the resulting falling prices. To protect the value of all stakeholders’ property rights, a consensus to avoid abruptly raising the TAC, without first considering the potential loss due to market response, is needed. Alternatively, if revenue increases with lower TAC, a positive economic incentive for conservation is created if price increasing proportionately more than the lower supply, with harvest profits boosted by lower costs of production. To capture the complexity of substituting across various sources of supply and product form, a general synthetic inverse demand system is estimated to identify the impact of overall landings on BFT prices. This system estimates price flexibilities of both fresh and frozen longline-caught sashimi-grade tunas (Pacific, Atlantic and southern bluefins, and bigeye) at the Tokyo Center Market in Japan, including the Tsukiji Market, the world’s largest fish auction market that served as the single global price leader for BFT. The resulting estimation shows that own-quantity price flexibilities of every type of fresh and frozen BFTs are less than unity and inflexible in their own consumption. This creates poor individual producer incentives for fishermen to reduce wild or farmed BFT supply, as there is a chance to increase their own revenue, under the unlikely condition that the total supply is fixed. However, by observing the rapid increases in the TAC of Eastern Atlantic bluefin tuna (EABFT) in the coming years, suppliers may not be better off as price will drop proportionally faster and total revenue if the estimated scale flexibility is greater than one. Based on the estimated scale flexibility of frozen BFT, which is slightly less than unity, the frozen subsector of EABFT suppliers is the only winner under the supply increases. Suppliers of frozen BFT in other regions, fresh BFT (in the Atlantic and elsewhere), and southern BFT and bigeye tuna will all be harmed through lower revenue by the supply increases. Additionally, while total revenue might stay the same for frozen BFT suppliers, fishermen will potentially receive lower profits due to higher operating costs associated with increased landings when the supply of EABFT increases. Given the number of sectors that ultimately lose financially in the short term and given the ecological (and production) risks accompanying an abrupt increase in fishing pressure in the long term, the global economic losses resulting from an increase in the allowable catch of Atlantic bluefin tuna will outweigh any potential increases to revenue. [ABSTRACT FROM AUTHOR]

Regulating ecosystem services provided by urban forests are of great importance for the quality of life among city dwellers. To reach a maximum contribution to well-being in cities, the urban regulating ecosystem services (URES) must match with the demands in terms of space and time. If we understand the matches or mismatches between the current urban dwellers’ desired quality conditions (demand) and the supply of URES by urban forests (UF) in the cities, this will facilitate integrating the concepts of ecosystem services in urban planning and management, but such an assessment has suffered from major knowledge limitations. Since it is complex and problematic to identify the direct demands for URES and the spatiotemporal patterns therein, improving the demand indicators can help to determine the actual requirements. In this paper, a methodological approach based on indicators is presented and demonstrated for two important URES: air quality improvement and global climate change mitigation provided by urban trees and shrubs. Four air quality standards and greenhouse gas reduction targets were used and compared to supplies of the URES in Tabriz, Iran. Our results show that the mean contribution of the URES supply to air quality standards and greenhouse gas reduction targets is modest. Hence, in Tabriz, there is a strong mismatch between demand and supply. Mismatches at the city scale will have to be reduced by both a reduction in pollutant emissions and an increased provisioning of URES supply through urban greenery. The presented assessment approach and the results for Tabriz make it explicit how different the demands and supplies of the two studied URES are, and we expect similar mismatches in many other cities. Therefore, our approach, relatively simple but still realistic and easy-to-apply, can raise awareness about, and the utility of, the ecosystem services concepts for urban planning and policymaking. [ABSTRACT FROM AUTHOR]

Cells and organisms have developed homeostatic mechanisms which protect them against a changing environment. How growth and homeostasis interact is still not well understood, but of increasing interest to the molecular and synthetic biology community to recognize and design control circuits which can oppose the diluting effects of cell growth. In this paper we describe the performance of selected negative feedback controllers in response to different applied growth laws and time dependent outflow perturbations of a controlled variable. The approach taken here is based on deterministic mass action kinetics assuming that cell content is instantaneously mixed. All controllers behave ideal in the sense that they for step-wise perturbations in volume and a controlled compound A are able to drive A precisely back to the controllers’ theoretical set-points. The applied growth kinetics reflect experimentally observed growth laws, which range from surface to volume ratio growth to linear and exponential growth. Our results show that the kinetic implementation of integral control and the structure of the negative feedback loop are two properties which affect controller performance. Best performance is observed for controllers based on derepression kinetics and controllers with an autocatalytic implementation of integral control. Both are able to defend exponential growth and perturbations, although the autocatalytic controller shows an offset from its theoretical set-point. Controllers with activating signaling using zero-order or bimolecular (antithetic) kinetics for integral control behave very similar but less well. Their performance can be improved by implementing negative feedback structures having repression/derepression steps or by increasing controller aggressiveness. Our results provide a guide what type of feedback structures and integral control kinetics are suitable to oppose the dilution effects by different growth laws and time dependent perturbations on a deterministic level. [ABSTRACT FROM AUTHOR]