Exact solution for large amplitude flexural vibration of nanobeams using nonlocal Euler-Bernoulli theory

In this paper, nonlinear free vibration of nanobeams with various end conditions is studied using the nonlocal elasticity within the frame work of Euler-Bernoulli theory with von K´arm´an nonlinearity. The equation of motion is obtained and the exact solution is established using elliptic integrals. Two comparison studies are carried out to demonstrate accuracy and applicability of the elliptic integrals method for nonlocal nonlinear free vibration analysis of nanobeams. It is observed that the phase plane diagrams of nanobeams in the presence of the small scale effect are symmetric ellipses, and consideration the small scale effect decreases the area of the diagram

In Vitro Study of Transverse Strength of Fiber Reinforced Composites

Objective: Reinforcement with fiber is an effective method for considerable improvement in flexural properties of indirect composite resin restorations. The aim of this in-vitrostudy was to compare the transverse strength of composite resin bars reinforced with preimpregnated and non-impregnated fibers.Materials and Methods: Thirty six bar type composite resin specimens (3×2×25 mm)were constructed in three groups. The first group was the control group (C) without any fiber reinforcement. The specimens in the second group (P) were reinforced with preimpregnatedfibers and the third group (N) with non-impregnated fibers. These specimens were tested by the three-point bending method to measure primary transverse strength.Data were statistically analyzed with one way ANOVA and Tukey's tests.Results: There was a significant difference among the mean primary transverse strength in the three groups (P<0.001). The post-hoc (Tukey) test showed that there was a significant difference between the pre-impregnated and control groups in their primary transversestrength (P<0.001). Regarding deflection, there was also a significant difference among the three groups (P=0.001). There were significant differences among the mean deflection of the control group and two other groups (PC&N<.001 and PC&P=.004), but there was no significant difference between the non- and pre-impregnated groups (PN&P=.813).Conclusion: Within the limitations of this study, it was concluded that reinforcement with fiber considerably increased the transverse strength of composite resin specimens, but impregnationof the fiber used implemented no significant difference in the transverse strength of composite resin samples

A dynamical law for slow crack growth in polycarbonate films

We study experimentally the slow growth of a single crack in polycarbonate films submitted to uniaxial and constant imposed stress. For this visco-plastic material, we uncover a dynamical law that describes the dependence of the instantaneous crack velocity with experimental parameters. The law involves a Dugdale-Barenblatt static description of crack tip plastic zones associated to an Eyring's law and an empirical dependence with the crack length that may come from a residual elastic field

Know abnormal, find evil : frequent pattern mining for ransomware threat hunting and intelligence

Emergence of crypto-ransomware has significantly changed the cyber threat landscape. A crypto ransomware removes data custodian access by encrypting valuable data on victims’ computers and requests a ransom payment to reinstantiate custodian access by decrypting data. Timely detection of ransomware very much depends on how quickly and accurately system logs can be mined to hunt abnormalities and stop the evil. In this paper we first setup an environment to collect activity logs of 517 Locky ransomware samples, 535 Cerber ransomware samples and 572 samples of TeslaCrypt ransomware. We utilize Sequential Pattern Mining to find Maximal Frequent Patterns (MFP) of activities within different ransomware families as candidate features for classification using J48, Random Forest, Bagging and MLP algorithms. We could achieve 99% accuracy in detecting ransomware instances from goodware samples and 96.5% accuracy in detecting family of a given ransomware sample. Our results indicate usefulness and practicality of applying pattern mining techniques in detection of good features for ransomware hunting. Moreover, we showed existence of distinctive frequent patterns within different ransomware families which can be used for identification of a ransomware sample family for building intelligence about threat actors and threat profile of a given target

The performance of a cable-stayed bridge pylon under close-range blast loads

Recent bridge collapses have raised an awareness of, and a concern for, the safety and robustness of bridges subjected to blast loading scenarios. The incident pressure generated by the explosion can cause severe structural damage and a loss of critical structural members, resulting in partial collapse of the bridge. Previously, most relevant research effort has been devoted to understanding the response of buildings under blast loading and to develop guidelines to increase the resistance of such structures, while relatively little research attention has been focused on bridge structures. Recent advancements in numerical methods have enabled the viable and cost-effective simulation of complicated blast scenarios, and hence these methods provide a useful reference for safeguarding design and assessment of critical infrastructure. To reduce the computational costs, previous studies on long span bridges under blast loads typically take advantage of sub-structuring techniques, in which only part of the structure is modelled. However, such oversimplifications can lead to erroneous results. Accordingly, this study is an attempt to simulate the dynamic response of an entire cable-stayed bridge subjected to blast loading based on best practice techniques obtained from the literature. The response of a steel bridge, designed according to the minimum requirements of the Australian Standard AS5100, is investigated when subjected to blast loads ranging from small to large explosions at different positions above the deck using numerical simulations. In addition, the potential effects of blast loads on different structural components (i.e. the deck and pylons) are discussed and possible blast mitigation strategies such as the application of FRP and optimization of the geometry of the pylons are investigated

Management of retinal vein occlusion, who is responsible?

Retinal vein occlusion (RVO) is a common retinal vascular occlusive disorder and is associated with a variety of systemic risk factors. The aim of this study was to investigate whether the underlying diseases were evaluated and managed appropriately by ophthalmologists. We performed a study of 1344 patients with retinal vein occlusion (RVO). Patients were evaluated with a questionnaire including ten closed questions to determine whether ophthalmologists evaluated and informed their patients about the underlying systemic diseases. None of the patients� homocysteine levels were measured. Only a small percentage of the patients were asked about the history of thrombotic diseases or family history of thrombotic diseases. We believe that most ophthalmologists are still not entirely convinced of their responsibility of managing the underlying predisposing factors of RVO. Ophthalmologists should either manage or engage other healthcare providers in the management of RVO to guarantee the patient the best care. © 2016 Tehran University of Medical Sciences. All rights reserved

Deep dive into ransomware threat hunting and intelligence at fog layer

Ransomware, a malware designed to encrypt data for ransom payments, is a potential threat to fog layer nodes as such nodes typically contain considerably amount of sensitive data. The capability to efficiently hunt abnormalities relating to ransomware activities is crucial in the timely detection of ransomware. In this paper, we present our Deep Ransomware Threat Hunting and Intelligence System (DRTHIS) to distinguish ransomware from goodware and identify their families. Specifically, DRTHIS utilizes Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), two deep learning techniques, for classification using the softmax algorithm. We then use 220 Locky, 220 Cerber and 220 TeslaCrypt ransomware samples, and 219 goodware samples, to train DRTHIS. In our evaluations, DRTHIS achieves an F-measure of 99.6% with a true positive rate of 97.2% in the classification of ransomware instances. Additionally, we demonstrate that DRTHIS is capable of detecting previously unseen ransomware samples from new ransomware families in a timely and accurate manner using ransomware from the CryptoWall, TorrentLocker and Sage families. The findings show that 99% of CryptoWall samples, 75% of TorrentLocker samples and 92% of Sage samples are correctly classified

Evaluation and comparison of SYBR Green I Real-Time PCR and TaqMan Real-Time PCR methods for quantitative assay of Listeria monocytogenes in nutrient broth and milk

Specific traditional plate count method and real-time PCR systems based on SYBR Green I and TaqMan technologies using a specific primer pair and probe for amplification of iap-gene were used for quantitative assay of Listeria monocytogenes in seven decimal serial dilution series of nutrient broth and milk samples containing 1.58 to 1.58×107 cfu /ml and the real-time PCR methods were compared with the plate count method with respect to accuracy and sensitivity. In this study, the plate count method was performed using surface-plating of 0.1 ml of each sample on Palcam Agar. The lowest detectable level for this method was 1.58×10 cfu/ml for both nutrient broth and milk samples. Using purified DNA as a template for generation of standard curves, as few as four copies of the iap-gene could be detected per reaction with both real-time PCR assays, indicating that they were highly sensitive. When these real-time PCR assays were applied to quantification of L. monocytogenes in decimal serial dilution series of nutrient broth and milk samples, 3.16×10 to 3.16×105 copies per reaction (equals to 1.58×103 to 1.58×107 cfu/ml L. monocytogenes) were detectable. As logarithmic cycles, for Plate Count and both molecular assays, the quantitative results of the detectable steps were similar to the inoculation levels