A new empirical model to predict stress intensity factor for double interacting surface cracks located in hollow cylinder

Fracture in cylinders is one of the most popular types of failure. Owing to the impact of production processes, nondestructive testing, and severe operational conditions, etc., cracks exist. The cracks could be detected in single or multiple form, where multiple cracks considered among the significant concerns that cylinders expected to experience. This is because in the existence of multiple neighboring cracks, crack interaction can take place between cracks and accelerates fracture process and lead to a catastrophic failure. Consequently, this study focuses on the problem of double interacting surface cracks located on external and internal surfaces of a hollow cylinder and oriented into parallel and non-coplanar parallel cracks configuration. Stress Intensity Factor (SIFs) has been chosen as the driving force to define the crack interaction. The SIFs have been analyzed for a wide variety of crack geometry, and cylinder type as well as separation distances utilizing finite element software Ansys under different types of mechanical loadings. Based on the analysis results, an empirical mathematical model was produced to predict the SIFs for double parallel cracks using the SIFs for a single crack, for thick and thin cylinders, separately. The empirical model was verified in terms of performance evaluation metrics, which exhibited prediction error less than 5%. Also, it is shown that crack interaction influence for parallel cracks demonstrated by shielding interaction influence only, while both shielding, and amplification impacts produced for non-coplanar cracks. The crack separation distance (horizontal and angular) between the cracks displayed substantial influence on interaction since it exhibited the ability to convert the interaction behavior from shielding to amplification impact (for angular). The presented results in this research serve the literature database since SIFs for a wide variety of cracks geometry have been introduced under different types of loading. Besides, the proposed mathematical model could be used easily and confidently as it displayed a high rate of accuracy

Ultrafast Intramolecular Charge Transfer of Formyl Perylene Observed Using Femtosecond Transient Absorption Spectroscopy

The excited-state photophysics of formylperylene (FPe) have been investigated in a series of nonpolar, polar aprotic, and polar protic solvents. A variety of experimental and theoretical methods were employed including femtosecond transient absorption (fs-TA) spectroscopy with 130 fs temporal resolution. We report that the ultrafast intramolecular charge transfer from the perylene unit to the formyl (CHO) group can be facilitated drastically by hydrogen-bonding interactions between the carbonyl group oxygen of FPe and hydrogen-donating solvents in the electronically excited state. The excited-state absorption of FPe in methanol (MeOH) is close to the reported perylene radical cation produced by bimolecular quenching by an electron acceptor. This is a strong indication for a substantial charge transfer in the S1 state in protic solvents. The larger increase of the dipole moment change in the protic solvents than that in aprotic ones strongly supports this observation. Relaxation mechanisms including vibrational cooling and solvation coupled to the charge-transfer state are also discussed

Handwriting styles: benchmarks and evaluation metrics

Evaluating the style of handwriting generation is a challenging problem, since it is not well defined. It is a key component in order to develop in developing systems with more personalized experiences with humans. In this paper, we propose baseline benchmarks, in order to set anchors to estimate the relative quality of different handwriting style methods. This will be done using deep learning techniques, which have shown remarkable results in different machine learning tasks, learning classification, regression, and most relevant to our work, generating temporal sequences. We discuss the challenges associated with evaluating our methods, which is related to evaluation of generative models in general. We then propose evaluation metrics, which we find relevant to this problem, and we discuss how we evaluate the evaluation metrics. In this study, we use IRON-OFF dataset. To the best of our knowledge, there is no work done before in generating handwriting (either in terms of methodology or the performance metrics), our in exploring styles using this dataset.Comment: Submitted to IEEE International Workshop on Deep and Transfer Learning (DTL 2018

Style Transfer and Extraction for the Handwritten Letters Using Deep Learning

How can we learn, transfer and extract handwriting styles using deep neural networks? This paper explores these questions using a deep conditioned autoencoder on the IRON-OFF handwriting data-set. We perform three experiments that systematically explore the quality of our style extraction procedure. First, We compare our model to handwriting benchmarks using multidimensional performance metrics. Second, we explore the quality of style transfer, i.e. how the model performs on new, unseen writers. In both experiments, we improve the metrics of state of the art methods by a large margin. Lastly, we analyze the latent space of our model, and we see that it separates consistently writing styles.Comment: Accepted in ICAART 201

Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm

In the present era of the internet and multimedia, image compression techniques are essential to improve image and video performance in terms of storage space, network bandwidth usage, and secure transmission. A number of image compression methods are available with largely differing compression ratios and coding complexity. In this paper we propose a new method for compressing high-resolution images based on the Discrete Fourier Transform (DFT) and Matrix Minimization (MM) algorithm. The method consists of transforming an image by DFT yielding the real and imaginary components. A quantization process is applied to both components independently aiming at increasing the number of high frequency coefficients. The real component matrix is separated into Low Frequency Coefficients (LFC) and High Frequency Coefficients (HFC). Finally, the MM algorithm followed by arithmetic coding is applied to the LFC and HFC matrices. The decompression algorithm decodes the data in reverse order. A sequential search algorithm is used to decode the data from the MM matrix. Thereafter, all decoded LFC and HFC values are combined into one matrix followed by the inverse DFT. Results demonstrate that the proposed method yields high compression ratios over 98% for structured light images with good image reconstruction. Moreover, it is shown that the proposed method compares favorably with the JPEG technique based on compression ratios and image quality

Change of size and type of patent ductus arteriosus in a one year old infant during routine echocardiographic study

There are only very few publications which document reactivity of patent ductus arteriosus. This report documentes the reactivity of a patent arterial duct in a one year old infant, 6.5 kg weight during a routine echocardiographic color Doppler study. Echocardiographic images were obtained during conscious sedation.peer-reviewe

Five Quantum Algorithms Using Quipper

Quipper is a recently released quantum programming language. In this report, we explore Quipper's programming framework by implementing the Deutsch's, Deutsch-Jozsa's, Simon's, Grover's, and Shor's factoring algorithms. It will help new quantum programmers in an instructive manner. We choose Quipper especially for its usability and scalability though it's an ongoing development project. We have also provided introductory concepts of Quipper and prerequisite backgrounds of the algorithms for readers' convenience. We also have written codes for oracles (black boxes or functions) for individual algorithms and tested some of them using the Quipper simulator to prove correctness and introduce the readers with the functionality. As Quipper 0.5 does not include more than \ensuremath{4 \times 4} matrix constructors for Unitary operators, we have also implemented \ensuremath{8 \times 8} and \ensuremath{16 \times 16} matrix constructors.Comment: 27 page

Bodies tell stories: Freudian hysteria in Fay Weldon's The Life and Loves of a She-Devil

Fay Weldon's The Life and Loves of a She-Devil deals with the nature of the hysteric psychological state women in abusive relationships or situations may suffer from and how they may react in either passively relenting to these conditions or taking control of their lives to achieve change. Thus, the question is raised as to whether the hysteric condition may be used as a means to an end. Women's Freudian hysterical symptoms are often physically manifested by anorexia nervosa, loss of speech (muteness), disturbed sleep, and alienation, among other maladies which may be subsumed under the category of symptoms of Freudian hysteria. Such symptoms, according to Freud, appear as the consequences of sexual violations a subject may have encountered, resulting in the manifestation of psychological disturbances characteristic of hysteria. This paper aims to investigate Fay Weldon's The Life and Loves of a She-Devil from Freud's theoretical perspectives on hysteria in order to indicate the influences of hysteria and its symptoms and reactions, focusing on the actions taken by the heroine of the novel under discussion to actualise herself

Heating and Cooling Dynamics of Carbon Nanotubes Observed by Temperature-Jump Spectroscopy and Electron Microscopy

Microscopy imaging indicates that in situ carbon nanotubes (CNTs) irradiation with relatively low dosages of infrared radiation results in significant heating of the tubes to temperatures above 1300 K. Ultrafast temperature-jump experiments reveal that CNTs laser-induced heating and subsequent cooling in solution take tens and hundreds of picoseconds, respectively. Given the reported transient behavior, these observations suggest novel ways for a T-jump methodology, unhindered by the requirement for excitation of water in the study of biological structures. They also provide the rate information needed for optimization of photothermal therapy that invokes infrared irradiation to selectively heat and annihilate cancer cells