Risky interpretations across the length scales: continuum vs. discrete models for soft tissue mechanobiology

Modelling and simulation in mechanobiology play an increasingly important role to unravel the complex mechanisms that allow resident cells to sense and respond to mechanical cues. Many of the in vivo mechanical loads occur on the tissue length scale, thus raising the essential question how the resulting macroscopic strains and stresses are transferred across the scales down to the cellular and subcellular levels. Since cells anchor to the collagen fibres within the extracellular matrix, the reliable representation of fibre deformation is a prerequisite for models that aim at linking tissue biomechanics and cell mechanobiology. In this paper, we consider the two-scale mechanical response of an affine structural model as an example of a continuum mechanical approach and compare it with the results of a discrete fibre network model. In particular, we shed light on the crucially different mechanical properties of the ‘fibres’ in these two approaches. While assessing the capability of the affine structural approach to capture the fibre kinematics in real tissues is beyond the scope of our study, our results clearly show that neither the macroscopic tissue response nor the microscopic fibre orientation statistics can clarify the question of affinity.

Contour features predict valence and threat judgements in scenes

Quickly scanning an environment to determine relative threat is an essential part of survival. Scene gist extracted rapidly from the environment may help people detect threats. Here, we probed this link between emotional judgements and features of visual scenes. We first extracted curvature, length, and orientation statistics of all images in the International Affective Picture System image set and related them to emotional valence scores. Images containing angular contours were rated as negative, and images containing long contours as positive. We then composed new abstract line drawings with specific combinations of length, angularity, and orientation values and asked participants to rate them as positive or negative, and as safe or threatening. Smooth, long, horizontal contour scenes were rated as positive/safe, while short angular contour scenes were rated as negative/threatening. Our work shows that particular combinations of image features help people make judgements about potential threat in the environment.

Cues to Danger: Contour Features Predict Valence and Threat Judgements in Scenes

Quickly scanning an environment to determine relative threat is an essential part of survival. Scene gist extracted rapidly from the environment may help people detect threats. Here, we probed this link between emotional judgements and features of visual scenes. We first extracted curvature, length, and orientation statistics of all images in the International Affective Picture System image set and related them to emotional valence scores. Images containing angular contours were rated as negative, and images containing long contours as positive. We then composed new abstract line drawings with specific combinations of length, curvature, and orientation values and asked participants to rate them as positive or negative, and as safe or threatening. Low curvature, long, horizontal contour scenes were rated as positive/safe, while short, high curvature contour scenes were rated as negative/threatening. Our work shows that particular combinations of image features help people make judgements about potential threat in the environment.

Quantitative characterization of fracture networks on Digital Outcrop Models obtained from avionic and terrestrial laser scanner

<p>We present a semi-automatic workflow aimed at extracting quantitative structural data from point clouds obtained with avionic and terrestrial laser scanners (Lidar and TLS). The workflow is characterized by a calibration phase followed by an automatic data-collection phase. The large datasets of “fractures” mapped in this way are analysed with statistical methods allowing to define representative parameters of the fracture network.</p><p>In the first phase, the intervention of an expert interpreter with structural geology skills is fundamental to evaluate which features can be interpreted as fractures in the point clouds. In the second phase, an automatic segmentation and classification is performed, based on phase 1 calibration, that allows extracting very large fracture datasets. The main steps in phase 1 are: manual segmentation of facets representing fracture surfaces, orientation analysis and definition of fracture sets (possibly supported by kinematic analysis), definition of orientation parameters to be used for automatic segmentation. Phase 2 analysis proceeds with the automatic segmentation of subset point clouds that include just one fracture set. In these point clouds, facets representing fractures lying on different planes are well separated and disconnected, and this allows applying automatic vectorization techniques that extract individual facets representing single fractures on the outcrop surface. The datasets issued from this processing are analysed with automatic algorithms allowing to define fracture spacing and orientation statistics with a very large support, that would not have been allowed by other methodologies.</p>

Graduate Students’ Perspective about the MA TEFL Program at Hashemite University in Jordan

This current study aimed to investigate MA students’ perspectives about the English as a foreign language (EFL) curriculum and methods of teaching program employed in the Department of Curriculum and Instruction at the Hashemite University. More specifically, the study attempted to explore the students’ perspectives of the program in terms of strengths and weaknesses. Data was collected through a questionnaire interview from 9 students who were about to finish their study. Findings showed that students highlighted the instructional and research-skill benefits for the program. They also revealed that the main weak points of the program were related to theory or theoretical orientation, statistics, the professor’s behavior, and research project. The findings can be valuable for teaching English as a foreign language (TEFL) syllabus designers, TEFL instructors, instructors of other subject areas, and researchers in higher education.

Optimized but not maximized cue integration for 3D visual perception

Reconstructing three-dimensional (3D) scenes from two-dimensional (2D) retinal images is an ill-posed problem. Despite this, our 3D perception of the world based on 2D retinal images is seemingly accurate and precise. The integration of distinct visual cues is essential for robust 3D perception in humans, but it is unclear if this mechanism is conserved in non-human primates, and how the underlying neural architecture constrains 3D perception. Here we assess 3D perception in macaque monkeys using a surface orientation discrimination task. We find that perception is generally accurate, but precision depends on the spatial pose of the surface and available cues. The results indicate that robust perception is achieved by dynamically reweighting the integration of stereoscopic and perspective cues according to their pose-dependent reliabilities. They further suggest that 3D perception is influenced by a prior for the 3D orientation statistics of natural scenes. We compare the data to simulations based on the responses of 3D orientation selective neurons. The results are explained by a model in which two independent neuronal populations representing stereoscopic and perspective cues (with perspective signals from the two eyes combined using nonlinear canonical computations) are optimally integrated through linear summation. Perception of combined-cue stimuli is optimal given this architecture. However, an alternative architecture in which stereoscopic cues and perspective cues detected by each eye are represented by three independent populations yields two times greater precision than observed. This implies that, due to canonical computations, cue integration for 3D perception is optimized but not maximized.Author summaryOur eyes only sense two-dimensional projections of the world (like a movie on a screen), yet we perceive the world in three dimensions. To create reliable 3D percepts, the human visual system integrates distinct visual signals according to their reliabilities, which depend on conditions such as how far away an object is located and how it is oriented. Here we find that non-human primates similarly integrate different 3D visual signals, and that their perception is influenced by the 3D orientation statistics of natural scenes. Cue integration is thus a conserved mechanism for creating robust 3D percepts by the primate brain. Using simulations of neural population activity, based on neuronal recordings from the same animals, we show that some computations which occur widely in the brain facilitate 3D perception, while others hinder perception. This work addresses key questions about how neural systems solve the difficult problem of generating 3D percepts, identifies a plausible neural architecture for implementing robust 3D vision, and reveals how neural computation can simultaneously optimize and curb perception.

Seismic, geologic, geomechanics, and dynamic constraints in flow models of unconventional fractured reservoirs: Example from a south Texas field

We present a workflow to build permeability models for flow simulation in unconventional naturally fractured reservoirs constrained by 3D seismic, geologic data and concepts, geomechanics observations, and dynamic data. Joints and faults are modeled separately to account for their differences in scale and flow properties. Seismic-derived orientation statistics are compared against orientations from outcrops and microseismic data to assess their validity and consistency across multiple scales. We show the impact of natural fractures and stress orientation in the flow and variability of the pressure field around producing wells in an unconventional reservoir from south Texas. Such variability can have a significant impact on well interference and optimal well spacing.