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This paper explains the first insights into the ongoing development of a CityGML based Food Water Energy Application Domain Extension (FWE ADE). Cities are undergoing rapid expansion throughout the globe. As a result, they face a common challenge to provide food, water and energy (FWE) supplies under healthy and economically productive conditions. Consequently, new tools and techniques must be developed to support decision-makers, such as governments, public or private infrastructure providers, investors and city developers, to understand, quantify and visualise multiple interdependent impacts for the sustainable supply of the FWE resources. However, a common practice amongst these stakeholders is to work in their data silos, which frequently results in a lack of data integration and communication between domain specific simulation tools belonging to different infrastructure departments. As a result, insights related to critical indicators showing inter-dependency amongst different urban infrastructure are missed and hence, not included in the cities’ redevelopment action plan. This paper documents the first ongoing attempt by an international group of domain experts from food, water, energy, urban design and geoinformatics to harmonise the data silos of food, water and energy domain for the case study regions of the County of Ludwigsburg in Germany, the city of Vienna in Austria and the neighbourhood of Gowanus in New York, the United States of America.

Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model–data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model–data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model–data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries.

Students who are Black or Hispanic have long been disproportionately represented in K-12 gifted and talented services. However, there are schools that have diverged from this trend by identifying atypically high numbers of Black and Hispanic students. In this conceptual replication of Peters and Johnson, we present predictors of whether a school offers gifted services (i.e., access) and representation indices for Black and Hispanic students (i.e., equity) within schools that enroll 10 or more Black or Hispanic students. Our results show that state policy mandates for gifted education are predictive of higher levels of access to and equity within gifted services for these schools. The average achievement and socioeconomic status of the district were positive predictors of access and equity while the district proportion eligible for special education services was a negative predictor of both. Finally, we end with a description of how the top 5% most-equitable schools in the country look different from their peers.

Citizen participation, co-creation – a joint development of professionals and citizens – initiatives for urban planning processes have increased significantly during the last few years. This development has been strongly supported by the evolution of Information and Communication Technologies (ICT). E.g., it has never been easier to get information through your mobile devices wherever and whenever you want it. Public open spatial data is available in many cities around the world and web-based applications use this data to provide tools and services for many different topics such as traffic information, or the communication of health-related information (e.g. ozone, particulate matter or pollen loads). This paper presents typical problems of such web-applications in terms of application design and implementation and usability evaluation via describing three case study applications which have been developed recently. It tries to answer the question: How can this kind of geo-services be developed and used by scientists to enable public participation within data gathering and urban planning processes? All three applications have the common goal to provide interactive geo-visualization and analysis features which are tailored to support users in their urban planning processes. The innovation of those applications lies in their flexibility regarding the topics they can tackle and their capability to perform interactive analyses triggered by the user. The applications have been built with a strong focus on exploring the available data (e.g. Open Government Data – OGD). Two of the applications have been implemented using the R-Shiny framework, the third application, the smarticipate platform, has been developed using ReactJS for the front-end, running a MongoDB in the background which is fed via a micro-service framework. In the latter application, the users can configure topics, i.e. the platform enables the user to create new services for different planning issues.

Abstract We compared the effect of cholesterol at different concentration on the phase behaviour of DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) multilamellar vesicles. We used pressure perturbation differential scanning calorimetry (PPC) that studies a system on the whole by giving access to relevant thermodynamic quantities, and elastic incoherent neutron scattering (EINS) that probes local motions of a system at the atomic level by allowing extraction of dynamical parameters. PPC revealed that the volume expansion coefficient of DMPC and DMPC/Cholesterol samples with 13 and 25 mol% cholesterol is a linear function of the heat capacity measured by differential scanning calorimetry. Neutron backscattering spectroscopy showed that the mean square displacements of H atoms do exhibit an increase with temperature and a decrease under increasing pressure. Cholesterol added at concentrations of 25 and 50 mol% led to suppression of the main phase transition. Taking advantage of these results, the present study aims (i) to show that calorimetry and EINS using the Bicout and Zaccai model equally permit to get access to thermodynamic quantities characterizing pure DMPC and DMPC/cholesterol mixtures, thus directly confirming the theoretical method, and (ii) to validate our approach as function of temperature and of pressure, as both are equally important and complementary thermodynamic variables.

This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account. The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine. While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper. The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements.

Finding all the "gifted" students who would benefit from a gifted and talented service is a perpetual concern. In this article, we focus on how to effectively implement multiple criteria in identification. First, we provide some broad background before introducing three different ways to combine multiple data points (AND, OR, and MEAN) when identifying students for gifted services. Next, we discuss how effective use of combining multiple criteria--including using two-phase identification systems--contributes to schools saving time and money while also better identifying students. To do this, we use newly introduced criteria for evaluating gifted and talented identification systems. Finally, we provide several keys for success that can help schools accomplish their identification goals effectively.

Universal screening is one of the most-common topics and well-accepted best practices within the field of gifted and talented education. There appears to be little disagreement that universally screening all students as part of a gifted and talented identification process results in fewer missed students. But surprisingly, there is little guidance on what makes for a quality universal screener--the tool that decides who needs further consideration. In this paper, we provide guidance that can help schools select the universal screener that helps them correctly identify as many students as possible at the lowest possible cost.

Rasmussen's encephalitis is a rare syndrome characterized by intractable seizures, often associated with epilepsia partialis continua and symptoms of progressive hemispheric dysfunction. Seizures are usually the hallmark of presentation, but antiepileptic drug treatment fails in most patients and is ineffective against epilepsia partialis continua, which often requires surgical intervention. Co-occurrence of focal cortical dysplasia has only rarely been described and may have implications regarding pathophysiology and management. We describe a rare case of dual pathology of Rasmussen's encephalitis presenting as a focal cortical dysplasia (FCD) and discuss the literature on this topic.

A change detection algorithm is applied on a three year time series of ASAR Wide Swath images in VV polarization over Calabria, Italy, in order to derive information on temporal soil moisture dynamics. The algorithm, adapted from an algorithm originally developed for ERS scatterometer, was validated using a simple hydrological model incorporating meteorological and pedological data. Strong positive correlations between modelled soil moisture and ASAR soil moisture were observed over arable land, while the correlation became much weaker over more vegetated areas. In a second phase, an attempt was made to incorporate seasonality in the different model parameters. It was observed that seasonally changing surface properties mainly affected the multitemporal incidence angle normalization. When applying a seasonal angular normalization, correlation coefficients between modelled soil moisture and retrieved soil moisture increased overall. Attempts to account for seasonality in the other model parameters did not result in an improved performance.

Failures of glacial lake dams can cause outburst floods and represents a serious hazard. The potential danger of outburst floods depends on various factors like the lake's area and volume, glacier change, morphometry of the glacier and its surrounding moraines and valley, and glacier velocity. Remote sensing offers an efficient tool for displacement calculations and risk assessment of the identification of potentially dangerous glacial lakes (PDGLs) and is especially helpful for remote mountainous areas. Not all important parameters can, however, be obtained using spaceborne imagery. Additional interpretation by an expert is required. ASTER data has a suitable accuracy to calculate surface velocity. Ikonos data offers more detail but requires more effort for rectification. All investigated debris-covered glacier tongues show areas with no or very slow movement rates. From 1962 to 2003 the number and area of glacial lakes increased, dominated by the occurrence and almost linear areal expansion of the moraine-dammed lakes, like the Imja Lake. Although the Imja Lake will probably still grow in the near future, the risk of an outburst flood (GLOF) is considered not higher than for other glacial lakes in the area. Potentially dangerous lakes and areas of lake development are identified. There is a high probability of further lake development at Khumbu Glacier, but a low one at Lhotse Glacier.

Vegetation patterns arise from the interplay between intraspecific and interspecific biotic interactions and from different abiotic constraints and interacting driving forces and distributions. In this study, we constructed an ensemble learning model that, based on spatially distributed environmental variables, could model vegetation patterns at the local scale. The study site was an alluvial floodplain with marked hydrologic gradients on which different vegetation types developed. The model was evaluated on accuracy, and could be concluded to perform well. However, model accuracy was remarkably lower for boundary areas between two distinct vegetation types. Subsequent application of the model on a spatially independent data set showed a poor performance that could be linked with the niche concept to conclude that an empirical distribution model, which has been constructed on local observations, is incapable to be applied beyond these boundaries.

Fluctuations in wetland hydrology create an interplay between aerobic and anaerobic conditions, controlling vegetation composition and microbial community structure and activity in wetland soils. In this study, we investigated the vegetation composition and microbial community structural and functional changes along a wetland hydrological gradient. Two different vegetation communities were distinguished along the hydrological gradient; Caricetum gracilis at the wet depression and Arrhenatheretum elatioris at the drier upper site. Microbial community structural changes were studied by a combined in situ 13CO2 pulse labeling and phospholipid fatty acid (PLFA) based stable isotope probing approach, which identifies the microbial groups actively involved in assimilation of newly photosynthesized, root-derived C in the rhizosphere soils. Gram negative bacterial communities were relatively more abundant in the surface soils of the drier upper site than in the surface soils of the wetter lower site, while the lower site and the deeper soil layers were relatively more inhabited by gram positive bacterial communities. Despite their large abundance, the metabolically active proportion of gram positive bacterial and actinomycetes communities was much smaller at both sites, compared to that of the gram negative bacterial and fungal communities. This suggests much slower assimilation of root-derived C by gram positive and actinomycetes communities than by gram negative bacteria and fungi at both sites. Ground water depth showed a significant effect on the relative abundance of several microbial communities. Relative abundance of gram negative bacteria significantly decreased with increasing ground water depth while the relative abundance of gram positive bacteria and actinomycetes at the surface layer increased with increasing ground water depth.

ENGLISH ABSTRACT: Special circumstances and considerations for the implementation of Computer Integrated Manufacturing principles in small and medium size factories are identified and discussed. An approach for esthablishing such programs is suggested and illustrated with a number of examples.AFRIKAANSE OPSOMMING: Spesiale omstandighede en oorwegings vir die implementering van Rekenaargeintegreerde Vervaardigingsbeginsels in klein en mediumgrootte fabrieke word geidentifiseer en bespreek. 'n Benadering vir die daarstelling van sodanige programme word voorgestel en geillustreer met behulp van verskeie voorbeelde.

There is increasing evidence that proteasomes have a biological role in the extracellular alveolar space, but inflammation could change their composition. We tested whether immunoproteasome protein-containing subpopulations are present in the alveolar space of patients with lung inflammation evoking the acute respiratory distress syndrome (ARDS). Bronchoalveolar lavage (BAL) supernatants and cell pellet lysate from ARDS patients (n=28) and healthy subjects (n=10) were analyzed for the presence of immunoproteasome proteins (LMP2 and LMP7) and proteasome subtypes by western blot, chromatographic purification, and 2D-dimensional gelelectrophoresis. In all ARDS patients but not in healthy subjects LMP7 and LMP2 were observed in BAL supernatants. Proteasomes purified from pooled ARDS BAL supernatant showed an altered enzyme activity ratio. Chromatography revealed a distinct pattern with 7 proteasome subtype peaks in BAL supernatant of ARDS patients that differed from healthy subjects. Total proteasome concentration in BAL supernatant was increased in ARDS (971 ng/mL ± 1116 versus 59±25; P