Overview on bio-based building material made with plant aggregate

Global warming, energy savings, and life cycle analysis issues are factors that have contributed to the rapid expansion of plant-based materials for buildings, which can be qualified as environmental-friendly, sustainable and efficient multifunctional materials. This review presents an overview on the several possibilities developed worldwide about the use of plant aggregate to design bio-based building materials. The use of crushed vegetal aggregates such as hemp (shiv), flax, coconut shells and other plants associated to mineral binder represents the most popular solution adopted in the beginning of this revolution in building materials. Vegetal aggregates are generally highly porous with a low apparent density and a complex architecture marked by a multi-scale porosity. These geometrical characteristics result in a high capacity to absorb sounds and have hygro-thermal transfer ability. This is one of the essential characteristics which differ of vegetal concrete compared to the tradition mineral-based concretes. In addition, the high flexibility of the aggregates leads to a non-fragile elasto-plastic behavior and a high deformability under stress, lack of fracturing and marked ductility with absorbance of the strains ever after having reached the maximum mechanical strength. Due to the sensitivity to moisture, the assessment of the durability of vegetal concrete constitutes one of the next scientific challenging of bio-based building materials.

National climate policies across Europe and their impacts on cities strategies

Globally, efforts are underway to reduce anthropogenic greenhouse gas emissions and to adapt to climate change impacts at the local level. However, there is a poor understanding of the relationship between city strategies on climate change mitigation and adaptation and the relevant policies at national and European level. This paper describes a comparative study and evaluation of cross-national policy. It reports the findings of studying the climate change strategies or plans from 200 European cities from Austria, Belgium, Estonia, Finland, France, Germany, Ireland, Italy, Netherlands, Spain and the United Kingdom. The study highlights the shared responsibility of global, European, national, regional and city policies. An interpretation and illustration of the influences from international and national networks and policy makers in stimulating the development of local strategies and actions is proposed. It was found that there is no archetypical way of planning for climate change, and multiple interests and motivations are inevitable. Our research warrants the need for a multi-scale approach to climate policy in the future, mainly ensuring sufficient capacity and resource to enable local authorities to plan and respond to their specific climate change agenda for maximising the management potentials for translating environmental challenges into opportunities.

The microphysics of collisionless shock waves

Collisionless shocks, that is shocks mediated by electromagnetic processes, are customary in space physics and in astrophysics. They are to be found in a great variety of objects and environments: magnetospheric and heliospheric shocks, supernova remnants, pulsar winds and their nebulæ, active galactic nuclei, gamma-ray bursts and clusters of galaxies shock waves. Collisionless shock microphysics enters at different stages of shock formation, shock dynamics and particle energization and/or acceleration. It turns out that the shock phenomenon is a multi-scale non-linear problem in time and space. It is complexified by the impact due to high-energy cosmic rays in astrophysical environments. This review adresses the physics of shock formation, shock dynamics and particle acceleration based on a close examination of available multi-wavelength or in situ observations, analytical and numerical developments. A particular emphasis is made on the different instabilities triggered during the shock formation and in association with particle acceleration processes with regards to the properties of the background upstream medium. It appears that among the most important parameters the background magnetic field through the magnetization and its obliquity is the dominant one. The shock velocity that can reach relativistic speeds has also a strong impact over the development of the micro-instabilities and the fate of particle acceleration. Recent developments of laboratory shock experiments has started to bring some new insights in the physics of space plasma and astrophysical shock waves. A special section is dedicated to new laser plasma experiments probing shock physics.

Stuck in the middle with you: The role of bridging organisations in urban regeneration

The literature on the governance of social-ecological systems increasingly recognizes a key role of bridging organisations (BOs) in transition processes towards sustainability. BOs can be defined as facilitators who allow for interorganisational collaboration. Our paper provides a more nuanced understanding of specific BO activities and their contributions towards urban sustainability. Our analysis is based on applying three complementary methodological angles (drawing on geolocalised data, interviews and action research) to 20 years of urban renovation investments in the city-region of Brussels. We distinguish between multi-scale, multi-actor and multi-dimensional tensions in urban renovation programmes and link these tensions to bridging challenges for BOs. Results suggest that the corresponding three types of bridging roles form a trilemma rather than a trilogy: the BOs in study have mediated one tension by de facto exacerbating another. Lessons from action research suggest that a wider use of temporality and shared language to communicate about urban renovation projects could attenuate the bridging trilemma.

Hierarchical Reconstruction Method for Solving Ill-posed Linear Inverse Problems

We present a detailed analysis of the application of a multi-scale Hierarchical Reconstruction method for solving a family of ill-posed linear inverse problems. When the observations on the unknown quantity of interest and the observation operators are known, these inverse problems are concerned with the recovery of the unknown from its observations. Although the observation operators we consider are linear, they are inevitably ill-posed in various ways. We recall in this context the classical Tikhonov regularization method with a stabilizing function which targets the specific ill-posedness from the observation operators and preserves desired features of the unknown. Having studied the mechanism of the Tikhonov regularization, we propose a multi-scale generalization to the Tikhonov regularization method, so-called the Hierarchical Reconstruction (HR) method. First introduction of the HR method can be traced back to the Hierarchical Decomposition method in Image Processing. The HR method successively extracts information from the previous hierarchical residual to the current hierarchical term at a finer hierarchical scale. As the sum of all the hierarchical terms, the hierarchical sum from the HR method provides an reasonable approximate solution to the unknown, when the observation matrix satisfies certain conditions with specific stabilizing functions. When compared to the Tikhonov regularization method on solving the same inverse problems, the HR method is shown to be able to decrease the total number of iterations, reduce the approximation error, and offer self control of the approximation distance between the hierarchical sum and the unknown, thanks to using a ladder of finitely many hierarchical scales. We report numerical experiments supporting our claims on these advantages the HR method has over the Tikhonov regularization method.

Provenance does matter: Links between winter trophic segregation and the migratory origins of European robins

Amongst migratory species, it is common to find individuals from different populations or geographical origins sharing staging or wintering areas. Given their differing life histories, ecological theory would predict that the different groups of individuals should exhibit some level of niche segregation. This has rarely been investigated because of the difficulty in assigning migrating individuals to breeding areas. Here, we start by documenting a broad geographical gradient of hydrogen isotopes (δ (2)H) in robin Erithacus rubecula feathers across Europe. We then use δ (2)H, as well as wing-tip shape, as surrogates for broad migratory origin of birds wintering in Iberia, to investigate the ecological segregation of populations. Wintering robins of different sexes, ages and body sizes are known to segregate between habitats in Iberia. This has been attributed to the despotic exclusion of inferior competitors from the best patches by dominant individuals. We find no segregation between habitats in relation to δ (2)H in feathers, or to wing-tip shape, which suggests that no major asymmetries in competitive ability exist between migrant robins of different origins. Trophic level (inferred from nitrogen isotopes in blood) correlated both with δ (2)H in feathers and with wing-tip shape, showing that individuals from different geographic origins display a degree of ecological segregation in shared winter quarters. Isotopic mixing models indicate that wintering birds originating from more northerly populations consume more invertebrates. Our multi-scale study suggests that trophic-niche segregation may result from specializations (arising in the population-specific breeding areas) that are transported by the migrants into the shared wintering grounds.

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

OBSERVATIONS AND EMISSIONS OF ENERGY-ASSOCIATED OZONE PRECURSORS IN THE MID-ATLANTIC UNITED STATES

Surface ozone is formed in the presence of NOx (NO + NO2) and volatile organic compounds (VOCs) and is hazardous to human health. A better understanding of these precursors is needed for developing effective policies to improve air quality. To evaluate the year-to-year changes in source contributions to total VOCs, Positive Matrix Factorization (PMF) was used to perform source apportionment using available hourly observations from June through August at a Photochemical Assessment Monitoring Station (PAMS) in Essex, MD for each year from 2007-2015. Results suggest that while gasoline and vehicle exhaust emissions have fallen, the contribution of natural gas sources to total VOCs has risen. To investigate this increasing natural gas influence, ethane measurements from PAMS sites in Essex, MD and Washington, D.C. were examined. Following a period of decline, daytime ethane concentrations have increased significantly after 2009. This trend appears to be linked with the rapid shale gas production in upwind, neighboring states, especially Pennsylvania and West Virginia. Back-trajectory analyses similarly show that ethane concentrations at these monitors were significantly greater if air parcels had passed through counties containing a high density of unconventional natural gas wells. In addition to VOC emissions, the compressors and engines involved with hydraulic fracturing operations also emit NOx and particulate matter (PM). The Community Multi-scale Air Quality (CMAQ) Model was used to simulate air quality for the Eastern U.S. in 2020, including emissions from shale gas operations in the Appalachian Basin. Predicted concentrations of ozone and PM show the largest decreases when these natural gas resources are hypothetically used to convert coal-fired power plants, despite the increased emissions from hydraulic fracturing operations expanded into all possible shale regions in the Appalachian Basin. While not as clean as burning natural gas, emissions of NOx from coal-fired power plants can be reduced by utilizing post-combustion controls. However, even though capital investment has already been made, these controls are not always operated at optimal rates. CMAQ simulations for the Eastern U.S. in 2018 show ozone concentrations decrease by ~5 ppb when controls on coal-fired power plants limit NOx emissions to historically best rates.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Theoretical investigation of intra- and inter-cellular spatiotemporal calcium patterns in microcirculation

Microcirculatory vessels are lined by endothelial cells (ECs) which are surrounded by a single or multiple layer of smooth muscle cells (SMCs). Spontaneous and agonist induced spatiotemporal calcium (Ca2+) events are generated in ECs and SMCs, and regulated by complex bi-directional signaling between the two layers which ultimately determines the vessel tone. The contractile state of microcirculatory vessels is an important factor in the determination of vascular resistance, blood flow and blood pressure. This dissertation presents theoretical insights into some of the important and currently unresolved phenomena in microvascular tone regulation. Compartmental and continuum models of isolated EC and SMC, coupled EC-SMC and a multi-cellular vessel segment with deterministic and stochastic descriptions of the cellular components were developed, and the intra- and inter-cellular spatiotemporal Ca2+ mobilization was examined.^ Coupled EC-SMC model simulations captured the experimentally observed localized subcellular EC Ca2+ events arising from the opening of EC transient receptor vanilloid 4 (TRPV4) channels and inositol triphosphate receptors (IP3Rs). These localized EC Ca2+ events result in endothelium-derived hyperpolarization (EDH) and Nitric Oxide (NO) production which transmit to the adjacent SMCs to ultimately result in vasodilation. The model examined the effect of heterogeneous distribution of cellular components and channel gating kinetics in determination of the amplitude and spread of the Ca2+ events. The simulations suggested the necessity of co-localization of certain cellular components for modulation of EDH and NO responses. Isolated EC and SMC models captured intracellular Ca2+ wave like activity and predicted the necessity of non-uniform distribution of cellular components for the generation of Ca2+ waves. The simulations also suggested the role of membrane potential dynamics in regulating Ca2+ wave velocity. The multi-cellular vessel segment model examined the underlying mechanisms for the intercellular synchronization of spontaneous oscillatory Ca2+ waves in individual SMC. ^ From local subcellular events to integrated macro-scale behavior at the vessel level, the developed multi-scale models captured basic features of vascular Ca2+ signaling and provide insights for their physiological relevance. The models provide a theoretical framework for assisting investigations on the regulation of vascular tone in health and disease.^

Self-assembly of gold nanocrystals into discrete coupled plasmonic structures

Development of methodologies for the controlled chemical assembly of nanoparticles into plasmonic molecules of predictable spatial geometry is vital in order to harness novel properties arising from the combination of the individual components constituting the resulting superstructures. This paper presents a route for fabrication of gold plasmonic structures of controlled stoichiometry obtained by the use of a di-rhenium thio-isocyanide complex as linker molecule for gold nanocrystals. Correlated scanning electron microscopy (SEM)—dark-field spectroscopy was used to characterize obtained discrete monomer, dimer and trimer plasmonic molecules. Polarization-dependent scattering spectra of dimer structures showed highly polarized scattering response, due to their highly asymmetric D∞h geometry. In contrast, some trimer structures displayed symmetric geometry (D3h), which showed small polarization dependent response. Theoretical calculations were used to further understand and attribute the origin of plasmonic bands arising during linker-induced formation of plasmonic molecules. Theoretical data matched well with experimentally calculated data. These results confirm that obtained gold superstructures possess properties which are a combination of the properties arising from single components and can, therefore, be classified as plasmonic molecules

Disabling and Enabling Technologies for Learning in Higher Education for All : Issues and Challenges for Whom?

Integration, inclusion, and equity constitute fundamental dimensions of democracy in post-World War II societies and their institutions. The study presented here reports upon the ways in which individuals and institutions both use and account for the roles that technologies, including ICT, play in disabling and enabling access for learning in higher education for all. Technological innovations during the 20th and 21st centuries, including ICT, have been heralded as holding significant promise for revolutionizing issues of access in societal institutions like schools, healthcare services, etc. (at least in the global North). Taking a socially oriented perspective, the study presented in this paper focuses on an ethnographically framed analysis of two datasets that critically explores the role that technologies, including ICT, play in higher education for individuals who are “differently abled” and who constitute a variation on a continuum of capabilities. Functionality as a dimension of everyday life in higher education in the 21st century is explored through the analysis of (i) case studies of two “differently abled” students in Sweden and (ii) current support services at universities in Sweden. The findings make visible the work that institutions and their members do through analyses of the organization of time and space and the use of technologies in institutional settings against the backdrop of individuals’ accountings and life trajectories. This study also highlights the relevance of multi-scale data analyses for revisiting the ways in which identity positions become framed or understood within higher education.

Energy balances in sugar cane, coffee and natural vegetation in the northeastern side of the São Paulo state, Brazil

Under land and climate change scenarios, agriculture has experienced water competitions among other sectors in the São Paulo state, Brazil. On the one hand, in several occasions, in the northeastern side of this state, nowadays sugar-cane is expanding, while coffee plantations are losing space. On the other hand, both crops have replaced the natural vegetation composed by Savannah and Atlantic Coastal Forest species. Under this dynamic situation, geosciences are valuable tools for evaluating the large-scale energy and mass exchanges between these diffe rent agro-ecosystems and the lower atmosphere. For quantification of the energy balance components in these mixed agro-ecosystems, the bands 1 and 2 from the MODIS product MOD13Q1 we re used throughout SA FER (Surface Algorithm for Evapotranspiration Retrieving) algorithm, which was applied together with a net of 12 automatic weather stations, during the year 2015 in the main sugar cane and coffee growing regions, located at the no rtheastern side of the state. The fraction of the global solar radiation (R G ) transformed into net radiation (Rn) was 52% for sugar cane and 53% for both, coffee and natural vegetation. The respective annual fractions of Rn used as λ E were 0.68, 0.87 and 0.77, while for the sensible heat (H) fluxes they were 0.27, 0.07 and 0.16. From April to July, heat advection raised λ E values above Rn promoting negative H, however these effects were much and less strong in coffee and sugar cane crop s, respectively. The smallest daily Rn fraction for all agro-ecosystems was for the soil heat flux (G), with averages of 5%, 6% and 7% in sugar cane, coffee and natural vegetation. From the energy balance analyses, we could conclude that, sugar-cane crop presented lower annual water consumption than that for coffee crop , what can be seen as an advantage in situations of water scarcity. However, the replacement of natural vegetation by su gar cane can contribute for warming th e environment, while when this occur with coffee crop there was noticed co oling conditions. The large scale modeling satisfactory results confirm the suitability of using MODIS products togeth er with weather stations to study the energy balance components in mixed agro-ecosystems under land-use and climate change conditions.

Modeling small-scale dairy farms in central Mexico using multi-criteria programming

Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multicriteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, rye-grass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.