scholarly journals Trade-offs between burrowing and biting force in fossorial scincid lizards?

2020 ◽  
Vol 130 (2) ◽  
pp. 310-319
Author(s):  
Margot Le Guilloux ◽  
Aurélien Miralles ◽  
John Measey ◽  
Bieke Vanhooydonck ◽  
James C O’Reilly ◽  
...  
Keyword(s):  
Vital Role ◽  
Cranial Morphology ◽  
Energetic Cost ◽  
Evolutionary Divergence ◽  
Trade Offs ◽  
Large Head ◽  
Functional Advantage ◽  
Phenotypic Diversification ◽  
And Performance ◽  
The Brain

Abstract Trade-offs are thought to be important in constraining evolutionary divergence as they may limit phenotypic diversification. The cranial system plays a vital role in many functions including defensive, territorial, predatory and feeding behaviours in addition to housing the brain and sensory systems. Consequently, the morphology of the cranial system is affected by a combination of selective pressures that may induce functional trade-offs. Limbless, head-first burrowers are thought to be constrained in their cranial morphology as narrow heads may provide a functional advantage for burrowing. However, having a wide and large head is likely beneficial in terms of bite performance. We used 15 skink species to test for the existence of trade-offs between maximal push and bite forces, and explored the patterns of covariation between external head and body morphology and performance. Our data show that there is no evidence of a trade-off between bite and burrowing in terms of maximal force. Species that generate high push forces also generate high bite forces. Our data also show that overall head size covaries with both performance traits. However, future studies exploring trade-offs between force and speed or the energetic cost of burrowing may reveal other trade-offs.

Specialization and performance trade‐offs across hosts in cactophilic Drosophila species

2021 ◽  
Author(s):  
Santiago Bouzas ◽  
María F. Barbarich ◽  
Eduardo M. Soto ◽  
Julián Padró ◽  
Valeria P. Carreira ◽  
...  
Keyword(s):  
Drosophila Species ◽  
Cactophilic Drosophila ◽  
Trade Offs ◽  
And Performance

scholarly journals Noise and Breakdown Characterization of SPAD Detectors with Time-Gated Photon-Counting Operation

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5287
Author(s):  
Hiwa Mahmoudi ◽  
Michael Hofbauer ◽  
Bernhard Goll ◽  
Horst Zimmermann
Keyword(s):  
Breakdown Voltage ◽  
Single Photon ◽  
Photon Counting ◽  
Low Noise ◽  
Dark Count ◽  
Fully Integrated ◽  
Trade Offs ◽  
And Performance ◽  
Noise Models

Being ready-to-detect over a certain portion of time makes the time-gated single-photon avalanche diode (SPAD) an attractive candidate for low-noise photon-counting applications. A careful SPAD noise and performance characterization, however, is critical to avoid time-consuming experimental optimization and redesign iterations for such applications. Here, we present an extensive empirical study of the breakdown voltage, as well as the dark-count and afterpulsing noise mechanisms for a fully integrated time-gated SPAD detector in 0.35-μm CMOS based on experimental data acquired in a dark condition. An “effective” SPAD breakdown voltage is introduced to enable efficient characterization and modeling of the dark-count and afterpulsing probabilities with respect to the excess bias voltage and the gating duration time. The presented breakdown and noise models will allow for accurate modeling and optimization of SPAD-based detector designs, where the SPAD noise can impose severe trade-offs with speed and sensitivity as is shown via an example.

Renewable energy selection based on a new entropy and dissimilarity measure on an interval-valued neutrosophic set

2021 ◽  
pp. 1-18
Author(s):  
ShuoYan Chou ◽  
Truong ThiThuy Duong ◽  
Nguyen Xuan Thao
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Membership Function ◽  
Fossil Fuels ◽  
Multiple Criteria Decision Making ◽  
Clean Energy ◽  
Dissimilarity Measure ◽  
Neutrosophic Set ◽  
Trade Offs ◽  
And Performance

Energy plays a central part in economic development, yet alongside fossil fuels bring vast environmental impact. In recent years, renewable energy has gradually become a viable source for clean energy to alleviate and decouple with a negative connotation. Different types of renewable energy are not without trade-offs beyond costs and performance. Multiple-criteria decision-making (MCDM) has become one of the most prominent tools in making decisions with multiple conflicting criteria existing in many complex real-world problems. Information obtained for decision making may be ambiguous or uncertain. Neutrosophic is an extension of fuzzy set types with three membership functions: truth membership function, falsity membership function and indeterminacy membership function. It is a useful tool when dealing with uncertainty issues. Entropy measures the uncertainty of information under neutrosophic circumstances which can be used to identify the weights of criteria in MCDM model. Meanwhile, the dissimilarity measure is useful in dealing with the ranking of alternatives in term of distance. This article proposes to build a new entropy and dissimilarity measure as well as to construct a novel MCDM model based on them to improve the inclusiveness of the perspectives for decision making. In this paper, we also give out a case study of using this model through the process of a renewable energy selection scenario in Taiwan performed and assessed.

High-Performance Image Filters via Sparse Approximations

2020 ◽  
Vol 3 (2) ◽  
pp. 1-19
Author(s):  
Kersten Schuster ◽  
Philip Trettner ◽  
Leif Kobbelt
Keyword(s):  
High Performance ◽  
Hardware Acceleration ◽  
Optimization Method ◽  
Translation Invariant ◽  
Approximation Quality ◽  
Trade Offs ◽  
Sparse Approximations ◽  
Image Filters ◽  
Good Trade ◽  
And Performance

We present a numerical optimization method to find highly efficient (sparse) approximations for convolutional image filters. Using a modified parallel tempering approach, we solve a constrained optimization that maximizes approximation quality while strictly staying within a user-prescribed performance budget. The results are multi-pass filters where each pass computes a weighted sum of bilinearly interpolated sparse image samples, exploiting hardware acceleration on the GPU. We systematically decompose the target filter into a series of sparse convolutions, trying to find good trade-offs between approximation quality and performance. Since our sparse filters are linear and translation-invariant, they do not exhibit the aliasing and temporal coherence issues that often appear in filters working on image pyramids. We show several applications, ranging from simple Gaussian or box blurs to the emulation of sophisticated Bokeh effects with user-provided masks. Our filters achieve high performance as well as high quality, often providing significant speed-up at acceptable quality even for separable filters. The optimized filters can be baked into shaders and used as a drop-in replacement for filtering tasks in image processing or rendering pipelines.

Passthrough+

2020 ◽  
Vol 3 (1) ◽  
pp. 1-17
Author(s):  
Gaurav Chaurasia ◽  
Arthur Nieuwoudt ◽  
Alexandru-Eugen Ichim ◽  
Richard Szeliski ◽  
Alexander Sorkine-Hornung
Keyword(s):  
Real Time ◽  
Video Encoding ◽  
View Synthesis ◽  
Performance Constraints ◽  
Trade Offs ◽  
Stereoscopic View ◽  
Target User ◽  
Spatio Temporal ◽  
And Performance ◽  
3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

Musical training improves memory for instrumental music, but not vocal music or words

2018 ◽  
Vol 48 (1) ◽  
pp. 150-159
Author(s):  
Jonathan M. P. Wilbiks ◽  
Sean Hutchins
Keyword(s):  
Instrumental Music ◽  
Musical Training ◽  
Vocal Music ◽  
Verbal Material ◽  
The Other ◽  
Musical Experience ◽  
Facilitative Effect ◽  
Musical Excerpts ◽  
And Performance ◽  
The Brain

In previous research, there exists some debate about the effects of musical training on memory for verbal material. The current research examines this relationship, while also considering musical training effects on memory for musical excerpts. Twenty individuals with musical training were tested and their results were compared to 20 age-matched individuals with no musical experience. Musically trained individuals demonstrated a higher level of memory for classical musical excerpts, with no significant differences for popular musical excerpts or for words. These findings are in support of previous research showing that while music and words overlap in terms of their processing in the brain, there is not necessarily a facilitative effect between training in one domain and performance in the other.

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