Different Scales Of Resolution Research Articles

Model simulation of carbonaceous fine particulate matter using SAFAR emission inventory and comparison with EDGAR-HTAP simulations

In this study, the evaluation of carbonaceous fine particulate matter (C-PM) was conducted using the SAFAR-India regional model. Two emission inventories were utilized: the newly developed SAFAR inventory and the global EDGAR-HTAP inventory, both for the year 2018. The simulation aimed to capture the seasonal and spatial patterns of black carbon (BC) and organic carbon (OC) concentrations. To validate model results, surface meteorological parameters, and C-PM concentrations were compared with the MERRA reanalysis data for the Indian region. Model simulated surface C-PM concentration with SAFAR emission inventory is found to be slightly overestimated (1.10), whereas simulated results with EDGAR emission inventory is significantly underestimated as compared to MERRA data. Model-simulated meteorological parameters showed a better correlation with MERRA reanalysis. Simulated geographical patterns of seasonal mean C-PM with SAFAR emission inventory exhibit quite a better comparison with MERRA reanalysis as against EDGAR simulated results. However, some differences in the present results are visible, particularly over the IGP region, as compared to MERRA data, but they are mainly attributed to a significant difference in the special resolution of present results (much finer) as compared to coarser MERRA data. In the Indo-Gangetic Plain (IGP) region, the concentration of BCSF and OCSF (BC and OC with SAFAR emission, respectively) show the peak during the winter, followed by the post-monsoon season. Although the correlation coefficients of hourly time series of surface BCSF and OCSF concentrations with MERRA over India are high (0.92 and 0.88), the poor RMSE, is attributed mainly to different scales of resolution. The model simulated BC, and OC concentrations with SAFAR emission input capture the pattern of spatial distribution reasonably well. The present evolution of BC and OC will help to better quantify their impact on climate and atmospheric conditions over the Indian region.

Lightweight Multiresolution Feature Fusion Network for Spectral Super-Resolution

Spectral super-resolution (SR), which reconstructs high spatial-resolution hyperspectral images (HSIs) from RGB inputs, has been demonstrated to be one of the effective computational imaging techniques to acquire HSIs. Though deep neural networks have shown their superiority in such a complex mapping problem, existing networks generally involve a very complex structure with huge amounts of parameters, resulting in giant memory occupation. In this article, a lightweight multiresolution feature fusion network (MRFN) is proposed, which adopts a multiresolution feature extraction and fusion framework to fully explore RGB inputs in different scales of resolution. Specifically, a lightweight feature extraction module (LFEM), which adopts cheap convolution and attention mechanisms, is constructed to explore different scales of features under a lightweight structure. Moreover, a hybrid loss function is proposed by encountering not only pixel-value level reconstruction error but also spectral continuity and fidelity. Experiments over three benchmark datasets, i.e., CAVE, Interdisciplinary Computational Vision Laboratory (ICVL), and NTIRE2022 datasets, have demonstrated that the proposed MRFN can reconstruct HSIs from RGB inputs in higher quality with fewer parameters and computational floating-point operations (FLOPs) compared with several state-of-the-art networks.

The Role of Digital Twins in Connected and Automated Vehicles

Digital twins found their genesis in the halls of NASA and the methods of product lifecycle management. Rapidly evolving trends around the proliferation of sensors, the Internet of Things, Industry 4.0, and cyber-physical systems have spurred the growth of digital twins. This paper reviews digital twins and their use in connected and automated vehicles (CAVs). Strictly speaking, digital twins must have communication between a physical system and its model, as opposed to similar methodologies that achieve indirect communication through iteration, or that substitute different parts of a system simulation with bits of hardware or software for testing. In practice, new methodologies for testing CAVs are sufficiently complex and difficult to apply simple labels. This is seen in our review of vehicular digital twins. Several gaps and challenges are apparent for the continued advancement of digital twin applications. We note some developing areas as traffic management centers, digital maps, onboard diagnostics, and logistics. Digital twins foster model reuse and encourage the use of multiple models at different scales of resolution. The role of digital twins will continue to grow as models become more tightly integrated to the physical systems they represent. This will drive such models towards uniqueness (matching a particular vehicle or road), adaptability (evolving with changing conditions and subject to wear and tear), and interpretability (conveying useful information to a human user). A maturing connected infrastructure and the development of smart cities will cause the number of new digital twin services to explode in a myriad of unforeseen ways.

Heuristic and Hierarchical-Based Population Mining of Salmonella enterica Lineage I Pan-Genomes as a Platform to Enhance Food Safety

The recent incorporation of bacterial whole-genome sequencing (WGS) into Public Health laboratories has enhanced foodborne outbreak detection and source attribution. As a result, large volumes of publicly available datasets can be used to study the biology of foodborne pathogen populations at an unprecedented scale. To demonstrate the application of a heuristic and agnostic hierarchical population structure guided pan-genome enrichment analysis (PANGEA), we used populations of S. enterica lineage I to achieve two main objectives: (i) show how hierarchical population inquiry at different scales of resolution can enhance ecological and epidemiological inquiries; and (ii) identify population-specific inferable traits that could provide selective advantages in food production environments. Publicly available WGS data were obtained from NCBI database for three serovars of Salmonella enterica subsp. enterica lineage I (S. Typhimurium, S. Newport, and S. Infantis). Using the hierarchical genotypic classifications (Serovar, BAPS1, ST, cgMLST), datasets from each of the three serovars showed varying degrees of clonal structuring. When the accessory genome (PANGEA) was mapped onto these hierarchical structures, accessory loci could be linked with specific genotypes. A large heavy-metal resistance mobile element was found in the Monophasic ST34 lineage of S. Typhimurium, and laboratory testing showed that Monophasic isolates have on average a higher degree of copper resistance than the Biphasic ones. In S. Newport, an extra sugE gene copy was found among most isolates of the ST45 lineage, and laboratory testing of multiple isolates confirmed that isolates of S. Newport ST45 were on average less sensitive to the disinfectant cetylpyridimium chloride than non-ST45 isolates. Lastly, data-mining of the accessory genomic content of S. Infantis revealed two cryptic Ecotypes with distinct accessory genomic content and distinct ecological patterns. Poultry appears to be the major reservoir for Ecotype 1, and temporal analysis further suggested a recent ecological succession, with Ecotype 2 apparently being displaced by Ecotype 1. Altogether, the use of a heuristic hierarchical-based population structure analysis that includes bacterial pan-genomes (core and accessory genomes) can (1) improve genomic resolution for mapping populations and accessing epidemiological patterns; and (2) define lineage-specific informative loci that may be associated with survival in the food chain.

Multipronged dental analyses reveal dietary differences in last foragers and first farmers at Grotta Continenza, central Italy (15,500\u20137000 BP)

This paper provides results from a suite of analyses made on human dental material from the Late Palaeolithic to Neolithic strata of the cave site of Grotta Continenza situated in the Fucino Basin of the Abruzzo region of central Italy. The available human remains from this site provide a unique possibility to study ways in which forager versus farmer lifeways affected human odonto-skeletal remains. The main aim of our study is to understand palaeodietary patterns and their changes over time as reflected in teeth. These analyses involve a review of metrics and oral pathologies, micro-fossils preserved in the mineralized dental plaque, macrowear, and buccal microwear. Our results suggest that these complementary approaches support the assumption about a critical change in dental conditions and status with the introduction of Neolithic foodstuff and habits. However, we warn that different methodologies applied here provide data at different scales of resolution for detecting such changes and a multipronged approach to the study of dental collections is needed for a more comprehensive and nuanced understanding of diachronic changes.

7T MRI super-resolution with Generative Adversarial Network

The high-resolution magnetic resonance image (MRI) provides detailed anatomical information critical for clinical application diagnosis. However, high-resolution MRI typically comes at the cost of long scan time, small spatial coverage, and low signal-to-noise ratio. The benefits of the convolutional neural network (CNN) can be applied to solve the super-resolution task to recover high-resolution generic images from low-resolution inputs. Additionally, recent studies have shown the potential to use the generative advertising network (GAN) to generate high-quality super-resolution MRIs using learned image priors. Moreover, existing approaches require paired MRI images as training data, which is difficult to obtain with existing datasets when the alignment between high and low-resolution images has to be implemented manually.This paper implements two different GAN-based models to handle the super-resolution: Enhanced super-resolution GAN (ESRGAN) and CycleGAN. Different from the generic model, the architecture of CycleGAN is modified to solve the super-resolution on unpaired MRI data, and the ESRGAN is implemented as a reference to compare GAN-based methods performance. The results of GAN-based models provide generated high-resolution images with rich textures compared to the ground-truth. Moreover, results from experiments are performed on both 3T and 7T MRI images in recovering different scales of resolution.

Multiresolution analysis of point processes and statistical thresholding for Haar wavelet-based intensity estimation

We take a wavelet-based approach to the analysis of point processes and the estimation of the first-order intensity under a continuous-time setting. A Haar wavelet multiresolution analysis is formulated which motivates the definition of homogeneity at different scales of resolution, termed J-th level homogeneity. Further to this, the activity in a point process’ first-order behaviour at different scales of resolution is also defined and termed L-th level innovation. Likelihood ratio tests for both these properties are proposed with asymptotic distributions provided, even when only a single realization is observed. The test for L-th level innovation forms the basis for a collection of statistical strategies for thresholding coefficients in a wavelet-based estimator of the intensity function. These thresholding strategies outperform the existing local hard thresholding strategy on a range of simulation scenarios. This methodology is applied to NetFlow data, characterizing multiscale behaviour on computer networks.

Modeling of thermal performance of multilayer protective clothing exposed to radiant heat

Studies presented in this paper concern wide issue of thermal comfort of protective clothing. The Computer Aided Design (CAD) software tools to analyze thermal insulation of multilayer textile assembly used in thermal protective clothing were applied. First, 3D geometry and morphology of a real textile assembly was modeled. In the designed model different scales of resolution were used for individual layers, ranging from a homogenized nonwoven fabrics model to mapping the geometry of yarns in woven fabrics model. Next, the finite volume method to estimate thermal insulation properties of this assembly, when exposed to heat radiation, was used. Finally, the simulation results were verified experimentally using method described in EN ISO 6942. On the basis of both simulation and experimental results obtained for the multilayer textile assembly, protective clothing parameters directly affecting the ability to protect against heat, were determined. Correlating simulated and experimental values of these parameters were obtained, which may indicate that applied software can be an effective tool in analyzing thermal properties of newly designed multilayer functional clothing.

The Extent of Infrastructure Causing Fragmentation in the Hydrocarbon Basin in the Arid and Semi-Arid Zones of Patagonia (Argentina)

Fragmentation is a disruption in the connectivity of landscapes. The aims of this paper are (i) to quantitatively assess the fragmentation rates in three landscape units located in a hydrocarbon basin, and (ii) to model their behavior between 2001 and 2013 using landscape metrics at different scales of resolution. The following metrics were selected using principal component analysis (PCA): The Clumpiness Index (CLUMPY), patch density (PD), perimeter-area fractal dimension (PAFRAC) and effective mesh size (MESH). Results from our investigations pointed out that hydrocarbon activity increased the fragmentation at the sites. In particular, the CLUMPY index increased in all three landscape units, the average of PD decreased from 60 to 14 patches per 100 hectares, whereas the mean of MESH was quite constant, however, due to oil production, it decreased mainly in the coastal valleys. Finally, the PAFRAC also decreased at sites with oil production, being more evident in the plateau and coastal canyons. As a whole, outputs from our analyses clearly pointed out that the monitoring of landscape fragmentation trends in arid and semi-arid zones can be successfully achieved using metrics derived from satellite spectral information.

Influence of alongslope processes on modern turbidite systems and canyons in the Alboran Sea (southwestern Mediterranean)

This is an interdisciplinary study that combines morphoseismics, sedimentology and numerical modelling to elucidate at different scales of resolution the influence of alongslope processes on the turbidite systems (TSs) and canyons in the Alboran Sea (southwestern Mediterranean). Nine TSs are mapped in the Spanish margin (La Linea, Guadiaro, Baños, Torrenueva, Fuengirola, Salobreña, Sacratif, Calahonda and Almeria) and two in the Alboran Ridge (Piedra Escuela and Al-Borani). In the Moroccan margin, there are only two canyons (Ceuta and Nekor). Distinctive morphoseismic and sedimentological signatures from TSs and canyons have enabled three regional models of alongslope influence to be distinguished: a) Alongslope processes are dominant. This scenario characterizes the canyons of the Moroccan margin. The diagnostic signature is the lack of leveed channels and lobes at the Ceuta and Nekor Canyon mouths. b) Different degrees of interplay exist between alongslope and downslope processes. This scenario occurs in the TSs of the western Spanish margin. Here, the alongslope influence on TSs (La Linea, Guadiaro, Baños, Torrenueva and Fuengirola) is evidenced by the lack of overbank deposits in the La Linea and Guadiaro Canyons and an alongslope trend in the morpho-architecture of the channelized lobes and in the textural distribution of canyon/channel deposits (mass-flow deposits and turbidites). Both signatures indicate sandier TSs as well as Bouma turbidite sequences lacking the finest levels towards the Strait of Gibraltar. Local intercalations of contourites are also present in the Guadiaro lobe deposits. c) Downslope processes are dominant. This scenario characterizes the TSs of the eastern and central Spanish margin and Alboran Ridge. There, TSs seem to be controlled solely by the characteristics of the downslope gravity flows that transport sediment. The hydrodynamic and sediment dispersion models confirm that the main oceanographic factors governing the variable alongslope influence in TSs and canyons are the following: a vigorous WMDW flow along the Moroccan margin and the energetic Atlantic Jet, western Atlantic anticyclonic gyre and general acceleration of the Mediterranean waters towards the Strait of Gibraltar, along the western Spanish margin. This study demonstrates the pivotal role that alongslope processes can play in the onset and formation of TSs and canyons at continental margins.

Hub connectivity, neuronal diversity, and gene expression in the Caenorhabditis elegans connectome.

Studies of nervous system connectivity, in a wide variety of species and at different scales of resolution, have identified several highly conserved motifs of network organization. One such motif is a heterogeneous distribution of connectivity across neural elements, such that some elements act as highly connected and functionally important network hubs. These brain network hubs are also densely interconnected, forming a so-called rich club. Recent work in mouse has identified a distinctive transcriptional signature of neural hubs, characterized by tightly coupled expression of oxidative metabolism genes, with similar genes characterizing macroscale inter-modular hub regions of the human cortex. Here, we sought to determine whether hubs of the neuronal C. elegans connectome also show tightly coupled gene expression. Using open data on the chemical and electrical connectivity of 279 C. elegans neurons, and binary gene expression data for each neuron across 948 genes, we computed a correlated gene expression score for each pair of neurons, providing a measure of their gene expression similarity. We demonstrate that connections between hub neurons are the most similar in their gene expression while connections between nonhubs are the least similar. Genes with the greatest contribution to this effect are involved in glutamatergic and cholinergic signaling, and other communication processes. We further show that coupled expression between hub neurons cannot be explained by their neuronal subtype (i.e., sensory, motor, or interneuron), separation distance, chemically secreted neurotransmitter, birth time, pairwise lineage distance, or their topological module affiliation. Instead, this coupling is intrinsically linked to the identity of most hubs as command interneurons, a specific class of interneurons that regulates locomotion. Our results suggest that neural hubs may possess a distinctive transcriptional signature, preserved across scales and species, that is related to the involvement of hubs in regulating the higher-order behaviors of a given organism.

GLOCAL: A global-local optimization template for multiple history-matched reservoir parameters

Parameterization of petroleum reservoirs is an important component of reservoir management. However, the process of reservoir parameterization is fraught with nonuniqueness of estimated parameters. Such nonuniqueness leads to large uncertainty and risks in reservoir management. One way to quantify and reduce the uncertainty in parameter estimation is to generate multiple realizations of the parameter field often through geostatistical simulations. Such realizations do not reproduce the production history and there is always a need to adjust such models to match the history data. Conditioning all geostatistically-simulated reservoir models to production data is often time-consuming, and the process does not usually produce maps that truly mimic the actual reservoir heterogeneity.This work presents a global-local optimization template (GLOCAL) that produces multiple estimates of the parameter field by history-matching production data. More fundamentally, the technique produces realizations of the parameter field at different scales of resolution. Two sample history-matching problems are presented to illustrate the effectiveness of the method. Results from these examples show that the method can produce several estimates that show some pattern of heterogeneity found in the true field. However, the resemblance to the true field varies across different scales of resolution of the parameter field in the global template.

Multimodal [GdO]+[ICG]− Nanoparticles for Optical, Photoacoustic, and Magnetic Resonance Imaging

Multimodal contrast agents with high biocompatibility and biodegradability, as well as low material complexity, are in great demand for clinical diagnostics at different scales of resolution and/or for translating preclinical diagnosis into intraoperative imaging. Multimodality, however, often results in multicomponent and multistructured materials with complexity becoming a severe restriction for synthesis, approval, and use in routine clinical practice. Here, we present sulfonate-based saline [GdO]+[ICG]− (ICG, indocyanine green) inorganic-organic hybrid nanoparticles (IOH-NPs with an inorganic [GdO]+ cation and an organic [ICG]− anion) as a novel, multimodality contrast agent for optical, photoacoustic, and magnetic resonance imaging (OI, PAI, MRI). [GdO]+[ICG]− IOH-NPs have a plain composition based on clinically used constituents and are prepared as an insoluble saline compound in water. The high [ICG]− content (81 wt %) ensures intense near-infrared emission (780–840 nm) and a strong photoacoustic s...

Urbanheart Surgery – a Collaborative Interdisciplinary Design Studio

<p class="Body1">The following paper presents an interdisciplinary design studio program at the School of Architecture and Built Environment, Deakin University, referred to as the ‘UrbanHeart Surgery’. This is a design based research forum that attempts to facilitate a landscape of decision-making that stimulates an integrated approach to design within the urban context.</p><p>The Urbanheart program has developed into a very successful teaching, research and public/community relations program. It has not only secured an ongoing relationship with various planning authorities, but its core of industrial partnerships has expanded to include four regional councils (Bendigo, Ballarat, Geelong, Surfcoast and Warrnambool), three metropolitan municipalities (Melbourne City, Port Phillip, Wyndham and Maribyrnong) and close links with various Victorian State government departments.</p><p>The program actively integrates postgraduate students from Architecture, Urban Design, Landscape Architecture and Planning. The different scales of resolution at which the unit operates would welcome further integration with students from Mechanical Engineering, Art and Design, Information Technology and Environmental Science.</p>

Two-Dimensional Wavelet Analysis of Supraorbital Margins of the Human Skull for Characterizing Sexual Dimorphism

The accurate determination of the sex of human skeletal remains is a critical challenge in forensic pathology and skeletal anthropology. The pelvis and the skull are the most commonly used skeletal sites for determining the sex of skeletons. In the skull, the supraorbital region, which includes the supraorbital margin, is considered a specific sexually dimorphic trait. In the traditional approach, sex is determined through visual and tactile assessment. This paper introduces a methodology for the objective quantification of sexually dimorphic features using wavelet transform, which is a multiscale mathematical tool that allows for the measurement of shape variations that are hidden at different scales of resolution. The method was successfully applied for the sex determination of a pilot sample of 3D meshes—digital records of supraorbital morphology. This information can be used by experts to improve the accuracy of biologic profile assessment of a human skeleton, and to describe the geographic and temporal variations within and among populations.

Holocene Supra-Regional Environmental Changes as Trigger for Major Socio-Cultural Processes in Northeastern Africa and the Sahara

This contribution presents the environmental changes that occurred over the last ten millennia in a vast region of North Africa, encompassing the Central Sahara, the Greater Nile Valley and the Horn of Africa. These areas are of particular significance in the continent because of the early socioeconomic transformations that occurred there. An up-to-date review of palaeoclimate research is proposed with the aim to highlight new theoretical approaches, analytical methods and innovative techniques. Results of recent research on high-resolution and well-dated palaeoenvironmental archives for proxy data have been used to understand the climatic variability at different scales of resolution. We trace the regional changes in Holocene palaeohydrology, mostly regulated by monsoonal precipitation, and their effects on the landscape, and highlight the occurrence of short-term climatic events, arid or humid that may have had disruptive consequences on human communities. The contribution also discusses the cultural dynamics that occurred in those regions because the latter were exploited by hunter/gatherer groups from the onset of the Holocene until historical times. A reconstruction of patterns of human adjustment to climatic variability is here presented, focusing on key processes such as the origin of food production, social complexity and power, and the rise and fall of complex polities and interregional networks.

Internal architecture of a till sheet, Tiskilwa Formation, north‐central Illinois, USA: Application of architectural element analysis

AbstractThick till sheets deposited during the Quaternary form significant aquitards in many areas of North America. However, the detailed sedimentary heterogeneity and architecture and depositional history of till units are not well understood. This study utilizes architectural element analysis to delineate the internal sedimentary architecture of the Tiskilwa Formation exposed at two outcrop sections in north‐central Illinois, USA. Architectural element analysis facilitates systematic delineation of sedimentary architecture based on the nature of facies contacts and change in facies associations, delineation of unit geometries and understanding of depositional processes at different scales of resolution; making architectural element analysis suitable for the sedimentological analysis and palaeoenvironmental reconstruction of subglacial deposits. Eleven facies types are identified in this study, including sand, gravel and diamict facies that record a suite of subglacial depositional processes. Detailed analysis of facies contacts (bounding surface hierarchy) and change in facies associations allows the delineation of five architectural elements, including coarse‐grained lens, coarse‐grained sheet, mixed zone, diamict lens and diamict sheet elements. The spatial arrangement and genetic interpretation of elements, and their spatial relationship with fifth‐order bounding surfaces, allows the delineation of five larger scale architectural units (‘element associations’), which can be mapped in the local study area and record at least three stacked successions of meltwater accumulation and till deposition. The results of this study can be utilized for architectural analysis of till sheets and provide insight to groundwater flow pathways through till in the study area and elsewhere.

Hierarchical representation of shapes in visual cortex-from localized features to figural shape segregation.

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1–V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy.

Spatial patterns and links between microbial community composition and function in cyanobacterial mats.

We imaged reflectance and variable fluorescence in 25 cyanobacterial mats from four distant sites around the globe to assess, at different scales of resolution, spatial variabilities in the physiological parameters characterizing their photosynthetic capacity, including the absorptivity by chlorophyll a (Achl), maximum quantum yield of photosynthesis (Ymax), and light acclimation irradiance (Ik). Generally, these parameters significantly varied within individual mats on a sub-millimeter scale, with about 2-fold higher variability in the vertical than in the horizontal direction. The average vertical profiles of Ymax and Ik decreased with depth in the mat, while Achl exhibited a sub-surface maximum. The within-mat variability was comparable to, but often larger than, the between-sites variability, whereas the within-site variabilities (i.e., between samples from the same site) were generally lowest. When compared based on averaged values of their photosynthetic parameters, mats clustered according to their site of origin. Similar clustering was found when the community composition of the mats' cyanobacterial layers were compared by automated ribosomal intergenic spacer analysis (ARISA), indicating a significant link between the microbial community composition and function. Although this link is likely the result of community adaptation to the prevailing site-specific environmental conditions, our present data is insufficient to identify the main factors determining these patterns. Nevertheless, this study demonstrates that the spatial variability in the photosynthetic capacity and light acclimation of benthic phototrophic microbial communities is at least as large on a sub-millimeter scale as it is on a global scale, and suggests that this pattern of variability scaling is similar for the microbial community composition.

Imods: Fast Exploration of Macromolecular Collective Motions

iModS is a web-based tool to approximate protein and nucleic acid flexibility using normal mode analysis in internal coordinates [1]. Given an input structure, the server provides a fast and powerful tool to model, visualize and analyze functional collective motions. Vibrational analysis, motion animations and morphing trajectories can be easily carried out at different scales of resolution. The server is very versatile, non-specialists can rapidly characterize potential conformational changes whereas advanced users can select between multiple coarse-grained representations and elastic network potentials. It includes advanced visualization capabilities for illustrating molecular flexibility based on affine-models and vector field representations. The visualization engine is also compatible with HTML5 and WebGL capabilities ensuring full accessibility to all devices. The web server can be freely accessed at http://imods.chaconlab.org.1. Lopez-Blanco JR, Garzon JI, Chacon P. (2011) iMod: multipurpose normal mode analysis in internal coordinates. Bioinformatics. 27 (20): 2843-2850.