The structure of the acto-myosin subfragment 1 complex: Results of searches using data from electron microscopy and x-ray crystallography

Surmises of how myosin subfragment 1 (S1) interacts with actin filaments in muscle contraction rest upon knowing the relative arrangement of the two proteins. Although there exist crystallographic structures for both S1 and actin, as well as electron microscopy data for the acto–S1 complex (AS1), modeling of this arrangement has so far only been done “by eye.” Here we report fitted AS1 structures obtained using a quantitative method that is both more objective and makes more complete use of the data. Using undistorted crystallographic results, the best-fit AS1 structure shows significant differences from that obtained by visual fitting. The best fit is produced using the F-actin model of Holmes et al. [Holmes, K. C., Popp, D., Gebhard, W. & Kabsch, W. (1990) Nature (London) 347, 44–49]. S1 residues at the AS1 interface are now found at a higher radius as well as being translated axially and rotated azimuthally. Fits using S1 plus loops missing from the crystal structure were achieved using a homology search method to predict loop structures. These improved fits favor an arrangement in which the loop at the 50- to 20-kDa domain junction of S1 is located near the N terminus of actin. Rigid-body movements of the lower 50-kDa domain, which further improve the fit, produce closure of the large 50-kDa domain cleft and bring conserved residues in the lower 50-kDa domain into an apparently appropriate orientation for close interaction with actin. This finding supports the idea that binding of ATP to AS1 at the end of the ATPase cycle disrupts the actin binding site by changing the conformation of the 50-kDa cleft of S1.

Data assimilation and its applications

In data assimilation, one prepares the grid data as the best possible estimate of the true initial state of a considered system by merging various measurements irregularly distributed in space and time, with a prior knowledge of the state given by a numerical model. Because it may improve forecasting or modeling and increase physical understanding of considered systems, data assimilation now plays a very important role in studies of atmospheric and oceanic problems. Here, three examples are presented to illustrate the use of new types of observations and the ability of improving forecasting or modeling.

Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Mathematical modeling of drying process of unripe banana slices

Unripe banana flour (UBF) production employs bananas not submitted to maturation process, is an interesting alternative to minimize the fruit loss reduction related to inappropriate handling or fast ripening. The UBF is considered as a functional ingredient improving glycemic and plasma insulin levels in blood, have also shown efficacy on the control of satiety, insulin resistance. The aim of this work was to study the drying process of unripe banana slabs (Musa cavendishii, Nanicão) developing a transient drying model through mathematical modeling with simultaneous moisture and heat transfer. The raw material characterization was performed and afterwards the drying process was conducted at 40 ºC, 50 ºC e 60 ºC, the product temperature was recorded using thermocouples, the air velocity inside the chamber was 4 m·s-1. With the experimental data was possible to validate the diffusion model based on the Fick\'s second law and Fourier. For this purpose, the sorption isotherms were measured and fitted to the GAB model estimating the equilibrium moisture content (Xe), 1.76 [g H2O/100g d.b.] at 60 ºC and 10 % of relative humidity (RH), the thermophysical properties (k, Cp, ?) were also measured to be used in the model. Five cases were contemplated: i) Constant thermophysical properties; ii) Variable properties; iii) Mass (hm), heat transfer (h) coefficient and effective diffusivity (De) estimation 134 W·m-2·K-1, 4.91x10-5 m-2·s-1 and 3.278?10-10 m·s-2 at 60 ºC, respectively; iv) Variable De, it presented a third order polynomial behavior as function of moisture content; v) The shrinkage had an effect on the mathematical model, especially in the 3 first hours of process, the thickness experienced a contraction of about (30.34 ± 1.29) % out of the initial thickness, finding two decreasing drying rate periods (DDR I and DDR II), 3.28x10-10 m·s-2 and 1.77x10-10 m·s-2, respectively. COMSOL Multiphysics simulations were possible to perform through the heat and mass transfer coefficient estimated by the mathematical modeling.

Modeling magnetar outbursts: flux enhancements and the connection with short bursts and glitches

The availability of a large amount of observational data recently collected from magnetar outbursts is now calling for a complete theoretical study of outburst characteristics. In this Letter (the first of a series dedicated to modeling magnetar outbursts), we tackle the long-standing open issue of whether or not short bursts and glitches are always connected to long-term radiative outbursts. We show that the recent detection of short bursts and glitches seemingly unconnected to outbursts is only misleading our understanding of these events. We show that, in the framework of the starquake model, neutrino emission processes in the magnetar crust limit the temperature, and therefore the luminosity. This natural limit to the maximum luminosity makes outbursts associated with bright persistent magnetars barely detectable. These events are simply seen as a small luminosity increase over the already bright quiescent state, followed by a fast return to quiescence. In particular, this is the case for 1RXS J1708–4009, 1E 1841–045, SGR 1806–20, and other bright persistent magnetars. On the other hand, a similar event (with the same energetics) in a fainter source will drive a more extreme luminosity variation and longer cooling time, as for sources such as XTE J1810–197, 1E 1547–5408, and SGR 1627–41. We conclude that the non-detection of large radiative outbursts in connection with glitches and bursts from bright persistent magnetars is not surprising per se, nor does it need any revision of the glitches and burst mechanisms as explained by current theoretical models.

A robust and fast method for 6DoF motion estimation from generalized 3D data

Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

On Modeling an Innovative Monitoring Network for Protecting and Managing Cultural Heritage from Risk Events

In this paper the model of an Innovative Monitoring Network involving properly connected nodes to develop an Information and Communication Technology (ICT) solution for preventive maintenance of historical centres from early warnings is proposed. It is well known that the protection of historical centres generally goes from a large-scale monitoring to a local one and it could be supported by a unique ICT solution. More in detail, the models of a virtually organized monitoring system could enable the implementation of automated analyses by presenting various alert levels. An adequate ICT solution tool would allow to define a monitoring network for a shared processing of data and results. Thus, a possible retrofit solution could be planned for pilot cases shared among the nodes of the network on the basis of a suitable procedure utilizing a retrofit catalogue. The final objective would consist in providing a model of an innovative tool to identify hazards, damages and possible retrofit solutions for historical centres, assuring an easy early warning support for stakeholders. The action could proactively target the needs and requirements of users, such as decision makers responsible for damage mitigation and safeguarding of cultural heritage assets.

A Simple RVoG Test for PolInSAR Data

In this paper, we present a simple algorithm for assessing the validity of the RVoG model for PolInSAR-based inversion techniques. This approach makes use of two important features characterizing a homogeneous random volume over a ground surface, i.e., the independence on polarization states of wave propagation through the volume and the structure of the polarimetric interferometric coherency matrix. These two features have led to two different methods proposed in the literature for retrieving the topographic phase within natural covers, i.e., the well-known line fitting procedure and the observation of the (1, 2) element of the polarimetric interferometric coherency matrix. We show that differences between outputs from both approaches can be interpreted in terms of the PolInSAR modeling based on the Freeman-Durden concept, and this leads to the definition of a RVoG/non-RVoG test. The algorithm is tested with both indoor and airborne data over agricultural and tropical forest areas.

A hydrological–economic model for sustainable groundwater use in sparse-data drylands: Application to the Amtoudi Oasis in southern Morocco, northern Sahara

A hydrological–economic model is introduced to describe the dynamics of groundwater-dependent economics (agriculture and tourism) for sustainable use in sparse-data drylands. The Amtoudi Oasis, a remote area in southern Morocco, in the northern Sahara attractive for tourism and with evidence of groundwater degradation, was chosen to show the model operation. Governing system variables were identified and put into action through System Dynamics (SD) modeling causal diagrams to program basic formulations into a model having two modules coupled by the nexus ‘pumping’: (1) the hydrological module represents the net groundwater balance (G) dynamics; and (2) the economic module reproduces the variation in the consumers of water, both the population and tourists. The model was operated under similar influx of tourists and different scenarios of water availability, such as the wet 2009–2010 and the average 2010–2011 hydrological years. The rise in international tourism is identified as the main driving force reducing emigration and introducing new social habits in the population, in particular concerning water consumption. Urban water allotment (PU) was doubled for less than a 100-inhabitant net increase in recent decades. The water allocation for agriculture (PI), the largest consumer of water, had remained constant for decades. Despite that the 2-year monitoring period is not long enough to draw long-term conclusions, groundwater imbalance was reflected by net aquifer recharge (R) less than PI + PU (G < 0) in the average year 2010–2011, with net lateral inflow from adjacent Cambrian formations being the largest recharge component. R is expected to be much less than PI + PU in recurrent dry spells. Some low-technology actions are tentatively proposed to mitigate groundwater degradation, such as: wastewater capture, treatment, and reuse for irrigation; storm-water harvesting for irrigation; and active maintenance of the irrigation system to improve its efficiency.

Amphibian Hotspots and Conservation Priorities in Eastern Cuba Identified by Species Distribution Modeling

The high rate of amphibian endemism and the severe habitat modification in the Caribbean islands make them an ideal place to test if the current protected areas network might protect this group. In this study, we model distribution and map species richness of the 40 amphibian species from eastern Cuba with the objectives of identify hotspots, detect gaps in species representation in protected areas, and select additional areas to fill these gaps. We used two modeling methods, Maxent and Habitat Suitability Models, to reach a consensus distribution map for each species, then calculate species richness by combining specific models and finally performed gap analyses for species and hotspots. Our results showed that the models were robust enough to predict species distributions and that most of the amphibian hotspots were represented in reserves, but 50 percent of the species were incompletely covered and Eleutherodactylus rivularis was totally uncovered by the protected areas. We identified 1441 additional km2 (9.9% of the study area) that could be added to the current protected areas, allowing the representation of every species and all hotspots. Our results are relevant for the conservation planning in other Caribbean islands, since studies like this could contribute to fill the gaps in the existing protected areas and to design a future network. Both cases would benefit from modeling amphibian species distribution using available data, even if they are incomplete, rather than relying only in the protection of known or suspected hotspots.

Comparing Common Data Environment Platforms for Student Collaborative Working: A Case Study from Ulster University

PAS1192-2 (2013) outlines the “fundamental principles of Level 2 information modeling”, one of these principles is the use of what is commonly referred to as a Common Data Environment (CDE). A CDE could be described as an internet-enabled cloudhosting platform, accessible to all construction team members to access shared project information. For the construction sector to achieve increased productivity goals, the next generation of industry professionals will need to be educated in a way that provides them with an appreciation of Building Information Modelling (BIM) working methods, at all levels, including an understanding of how data in a CDE should be structured, managed, shared and published. This presents a challenge for educational institutions in terms of providing a CDE that addresses the requirements set out in PAS1192-2, and mirrors organisational and professional working practices without causing confusion due to over complexity. This paper presents the findings of a two-year study undertaken at Ulster University comparing the use of a leading industry CDE platform with one derived from the in-house Virtual Learning Environment (VLE), for the delivery of a student BIM project. The research methodology employed was a qualitative case study analysis, focusing on observations from the academics involved and feedback from students. The results of the study show advantages for both CDE platforms depending on the learning outcomes required.

Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002

LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

Boston, Massachusetts, 2-Dimensional Building Footprints with Height Data (from LIDAR data), 2002

This dataset consists of 2D footprints of the buildings in the metropolitan Boston area, based on tiles in the orthoimage index (orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 237890, 237894, 237898, 237902, 241890, 241894, 241898, 241902, 245898, 245902). This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). Roof height and footprint elevation attributes (derived from 1-meter resolution LIDAR (LIght Detection And Ranging) data) are included as part of each building feature. This data can be combined with other datasets to create 3D representations of buildings and the surrounding environment.

Compensatory T-Cell Regulation in Unaffected Relatives of SLE Patients, and Opposite IL-2/CD25-Mediated Effects Suggested by Coreferentiality Modeling

In human systemic lupus erythematosus (SLE), diverse autoantibodies accumulate over years before disease manifestation. Unaffected relatives of SLE patients frequently share a sustained production of autoantibodies with indiscriminable specificity, usually without ever acquiring the disease. We studied relations of IgG autoantibody profiles and peripheral blood activated regulatory T-cells (aTregs), represented by CD4(+)CD25(bright) T-cells that were regularly 70-90% Foxp3(+). We found consistent positive correlations of broad-range as well as specific SLE-associated IgG with aTreg frequencies within unaffected relatives, but not patients or unrelated controls. Our interpretation: unaffected relatives with shared genetic factors compensated pathogenic effects by aTregs engaged in parallel with the individual autoantibody production. To study this further, we applied a novel analytic approach named coreferentiality that tests the indirect relatedness of parameters in respect to multivariate phenotype data. Results show that independently of their direct correlation, aTreg frequencies and specific SLE-associated IgG were likely functionally related in unaffected relatives: they significantly parallelled each other in their relations to broad-range immunoblot autoantibody profiles. In unaffected relatives, we also found coreferential effects of genetic variation in the loci encoding IL-2 and CD25. A model of CD25 functional genetic effects constructed by coreferentiality maximization suggests that IL-2-CD25 interaction, likely stimulating aTregs in unaffected relatives, had an opposed effect in SLE patients, presumably triggering primarily T-effector cells in this group. Coreferentiality modeling as we do it here could also be useful in other contexts, particularly to explore combined functional genetic effects.