A spatially-resolved material flow model: of the Lisbon metropolitan area

Urban systems are the locus of consumption and engines of economic growth in a globalized world. Major cities offer then the most striking examples of the environmental and energy problems that accompany intense urbanization: as cities grow the flow of energy and materials increase and pose serious problems to global sustainability. It is therefore critical to understand the interactions between the socio-economic urban development and environmental pressures, and to develop models that may explain these interactions. Early efforts led to conceptual models of cities as urban ecosystems. Ecologists have described the city as a heterotrophic ecosystem highly dependent on large inputs of energy and materials and a vast capacity to absorb emissions and waste [1,3]. Wolman was the first to apply an urban metabolism approach to quantify the flows of energy and materials into and out of a hypothetical American city with a population of one million. Systems ecologists provided formal equations to describe the energy balance and the cycling of materials . Although these efforts have never been translated into operational simulation models, they have laid out the basis for urban-ecological research. A critical challenge in this context is how to balance service levels, asset management (at times with a growing maintenance backlog), and resource efficiency with respect to materials, energy and cost. In this paper the outline of a spatially resolved model of urban systems is described.Peer Reviewe

Indigenous knowledge related to climate variability and change: insights from droughts in semi-arid areas of former Makueni District, Kenya

This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961-2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists' decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and chang

The Public Repository of Xenografts enables discovery and randomized phase II-like trials in mice

More than 90% of drugs with preclinical activity fail in human trials, largely due to insufficient efficacy. We hypothesized that adequately powered trials of patient-derived xenografts (PDX) in mice could efficiently define therapeutic activity across heterogeneous tumors. To address this hypothesis, we established a large, publicly available repository of well-characterized leukemia and lymphoma PDXs that undergo orthotopic engraftment, called the Public Repository of Xenografts (PRoXe). PRoXe includes all de-identified information relevant to the primary specimens and the PDXs derived from them. Using this repository, we demonstrate that large studies of acute leukemia PDXs that mimic human randomized clinical trials can characterize drug efficacy and generate transcriptional, functional, and proteomic biomarkers in both treatment-naive and relapsed/refractory disease

ABSTRACT SMART LEGEND – SMART ATLAS!

Atlases are moving quickly towards multimedia, three-dimensional visualization and interactive techniques. Digital atlas maps benefit from nearly free navigation, sophisticated visualization techniques and analytical functionality. Zooming and panning, coloring, and interactive queries are standard features nowadays. But one of the most important features of every map – the legend – still lacks appropriate functionality and even good graphic design. Reviewing traditional and digital map legends, seven functional components can be extracted: visualization, navigation, analysis, dimensionality, thematic issues, general information, and layout. These seven legend components should be considered in the design process of every interactive legend. But we can go even a step further, by imagining and realizing smart functionality for the legend. In our new „smart legend “ approach, the legend is defined as a central control unit of the map. We can distinguish two main feature categories of a „smart legend“; Self-acting adaptations of the legend that aim at a preferably optimal depiction of the map elements, and the range of user interaction features provided. 1 THE LEGEND, A CLASSIC MAP FEATURE Traditional legends in paper maps and atlases Map legends are traditionally appointed to explain the content of a map. According to the Kansas Association of Mappers (2005), the legend is defined as „An explanation of the symbols, codes, names given to variables and othe

More is not always better: Temporal neural signatures of object-driven versus scene-driven human scene categorization

Scene categorization is an impressively rapid process (Potter et al., 2014). Examining the question which type of visual information is crucial for scene categorization to operate efficiently in the early stages of perception has sparked an ongoing debate among cognitive psychologists. Explanatory propositions have emphasized the importance of either object-centered (e.g., De Graef et al. 1990) or scene-centered (e.g., Greene & Oliva, 2009) processing routes with many also acknowledging integrative dual pathways to scene recognition (e.g., MacEvoy & Epstein, 2011). While there is ample evidence for the importance of both local and global scene information, recent work by our research group (Wiesmann & Võ, 2022; Wiesmann & Võ, 2023a; Wiesmann & Võ, 2023b) has suggested that object information is generally more useful to observers for rapid scene categorization, especially if these objects exhibit high specificity to a given scene category and demonstrate frequent occurrence within scenes belonging to that particular category. With increasing stimulus onset asynchrony and decreasing object diagnosticity, utility of global scene information is thought to increase. In this experiment, we now intend to use electroencephalography (EEG) to investigate the temporal dynamics and neural signatures of local and global scene information in the scene categorization process

Indigenous knowledge related to climate variability and change: insights from droughts in semi-arid areas of former Makueni District, Kenya

This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961–2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists’ decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and change

X-Ray tomography-based microstructure representation in the Snow Microwave Radiative Transfer model

The modular Snow Microwave Radiative Transfer (SMRT) model simulates microwave scattering behavior in snow via different selectable theories and snow microstructure representations, which is well suited to intercomparisons analyses. Here, five microstructure models were parameterized from X-ray tomography and thin-section images of snow samples and evaluated with SMRT. Three field experiments provided observations of scattering and absorption coefficients, brightness temperature, and/or backscatter with the increasing complexity of snowpack. These took place in Sodankylä, Finland, and Weissfluhjoch, Switzerland. Simulations of scattering and absorption coefficients agreed well with observations, with higher errors for snow with predominantly vertical structures. For simulation of brightness temperature, difficulty in retrieving stickiness with the Sticky Hard Sphere microstructure model resulted in relatively poor performance for two experiments, but good agreement for the third. Exponential microstructure gave generally good results, near to the best performing models for two field experiments. The Independent Sphere model gave intermediate results. New Teubner–Strey and Gaussian Random Field models demonstrated the advantages of SMRT over microwave models with restricted microstructural geometry. Relative model performance is assessed by the quality of the microstructure model fit to microcomputed tomography (CT) data and further improvements may be possible with different fitting techniques. Careful consideration of simulation stratigraphy is required in this new era of high resolution microstructure measurement as layers thinner than the wavelength introduce artificial scattering boundaries not seen by the instrument

Lung perfusion imaging in small animals using 4D micro-CT at heartbeat temporal resolution

Purpose: Quantitative in vivo imaging of lung perfusion in rodents can provide critical information for preclinical studies. However, the combined challenges of high temporal and spatial resolution have made routine quantitative perfusion imaging difficult in small animals. The purpose of this work is to demonstrate 4D micro-CT for perfusion imaging in rodents at heartbeat temporal resolution and isotropic spatial resolution