Simulation of the Elastic Properties of Reinforced Kevlar-Graphene Composites

The compressive strength of unidirectional fiber composites in the form of Kevlar yarn with a thin outer layer of graphene was investigated and modeled. Such fiber structure may be fabricated by using a strong chemical bond between Kevlar yarn and graphene sheets. Chemical functionalization of graphene and Kevlar may achieved by modification of appropriate surface-bound functional (e.g., carboxylic acid) groups on their surfaces. In this report we studied elastic response to unidirectional in-plane applied load with load peaks along the diameter. The 2D linear elasticity model predicts that significant strengthening occurs when graphene outer layer radius is about 4 % of kevlar yarn radius. The polymer chains of Kevlar are linked into locally planar structure by hydrogen bonds across the chains, with transversal strength considerably weaker than longitudinal one. This suggests that introducing outer enveloping layer of graphene, linked to polymer chains by strong chemical bonds may significantly strengthen Kevlar fiber with respect to transversal deformations

The Specific Heat of a Ferromagnetic Film.

We analyze the specific heat for the $O(N)$ vector model on a $d$-dimensional film geometry of thickness $L$ using ``environmentally friendly'' renormalization. We consider periodic, Dirichlet and antiperiodic boundary conditions, deriving expressions for the specific heat and an effective specific heat exponent, \alpha\ef. In the case of $d=3$, for $N=1$, by matching to the exact exponent of the two dimensional Ising model we capture the crossover for \xi_L\ra\infty between power law behaviour in the limit {L\over\xi_L}\ra\infty and logarithmic behaviour in the limit {L\over\xi_L}\ra0 for fixed $L$, where $\xi_L$ is the correlation length in the transverse dimensions.Comment: 21 pages of Plain TeX. Postscript figures available upon request from [email protected]

Simple vs complex temporal recurrences for video saliency prediction

This paper investigates modifying an existing neural network architecture for static saliency prediction using two types of recurrences that integrate information from the temporal domain. The first modification is the addition of a ConvLSTM within the architecture, while the second is a conceptually simple exponential moving average of an internal convolutional state. We use weights pre-trained on the SALICON dataset and fine-tune our model on DHF1K. Our results show that both modifications achieve state-of-the-art results and produce similar saliency maps. Source code is available at https://git.io/fjPiB

The chiral and flavour projection of Dirac-Kahler fermions in the geometric discretization

It is shown that an exact chiral symmetry can be described for Dirac-Kahler fermions using the two complexes of the geometric discretization. This principle is extended to describe exact flavour projection and it is shown that this necessitates the introduction of a new operator and two new structures of complex. To describe simultaneous chiral and flavour projection, eight complexes are needed in all and it is shown that projection leaves a single flavour of chiral field on each.Comment: v2: 17 pages, Latex. 5 images eps. Added references, reformatted and clarification of some point

The relevance of the evolution of experimental studies for the interpretation and evaluation of some trace physical evidence

In order for trace evidence to have a high evidential value, experimental studies which mimic the forensic reality are of fundamental importance. Such primary level experimentation is crucial to establish a coherent body of theory concerning the generation, transfer and persistence of different forms of trace physical evidence. We contend that the forensic context, at whatever scale, will be specific to each individual forensic case and this context in which a crime takes place will influence the properties of trace evidence. it will, therefore, be necessary in many forensic cases to undertake secondary level experimental studies that incorporate specific variables pertinent to a particular case and supplement the established theory presented in the published literature. Such studies enable a better understanding of the specific forensic context and thus allow More accurate collection, analysis and interpretation of the trace physical evidence to be achieved. This paper presents two cases where the findings of secondary level experimental studies undertaken to address specific issues particular to two forensic investigations proved to be important. Specific pre-, syn- and post-forensic event factors were incorporated into the experimental design and proved to be invaluable in the recovery, analysis and in achieving accurate interpretations of both soil evidence from footwear and glass trace evidence from a broken window.These Studies demonstrate that a fuller understanding of the specific context within which trace physical evidence is generated and subsequently collected, as well as an understanding of the behaviour of certain forms of trace physical evidence under specific conditions, can add evidentiary weight to the analysis and interpretation of that evidence and thus help a court with greater certainty where resources (time and cost) permit

Exploring EEG for Object Detection and Retrieval

This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. We investigate if it is possible to capture useful EEG signals to detect if relevant objects are present in a dataset of realistic and complex images. We perform several experiments using a rapid serial visual presentation (RSVP) of images at different rates (5Hz and 10Hz) on 8 users with different degrees of familiarization with BCI and the dataset. We then use the feedback from the BCI and mouse-based interfaces to retrieve localized objects in a subset of TRECVid images. We show that it is indeed possible to detect such objects in complex images and, also, that users with previous knowledge on the dataset or experience with the RSVP outperform others. When the users have limited time to annotate the images (100 seconds in our experiments) both interfaces are comparable in performance. Comparing our best users in a retrieval task, we found that EEG-based relevance feedback outperforms mouse-based feedback. The realistic and complex image dataset differentiates our work from previous studies on EEG for image retrieval.Comment: This preprint is the full version of a short paper accepted in the ACM International Conference on Multimedia Retrieval (ICMR) 2015 (Shanghai, China

Theoretical predictions for how temperature affects the dynamics of interacting herbivores and plants

Concern about climate change has spurred experimental tests of how warming affects species' abundance and performance. As this body of research grows, interpretation and extrapolation to other species and systems have been limited by a lack of theory. To address the need for theory for how warming affects species interactions, we used consumer-prey models and the metabolic theory of ecology to develop quantitative predictions for how systematic differences between the temperature dependence of heterotrophic and autotrophic population growth lead to temperature-dependent herbivory. We found that herbivore and plant abundances change with temperature in proportion to the ratio of autotrophic to heterotrophic metabolic temperature dependences. This result is consistent across five different formulations of consumer-prey models and over varying resource supply rates. Two models predict that temperaturedependent herbivory causes primary producer abundance to be independent of temperature. This finding contradicts simpler extensions of metabolic theory to abundance that ignore trophic interactions, and is consistent with patterns in terrestrial ecosystems. When applied to experimental data, the model explained 77% and 66% of the variation in phytoplankton and zooplankton abundances, respectively. We suggest that metabolic theory provides a foundation for understanding the effects of temperature change on multitrophic ecological communities