DEM Modeling of Crushable Grain Material under Different Loading Conditions

This paper deals with the effect of contact conditions on the crushing mechanisms and the strength of granular materials. The computation of crushable grain material under different loading conditions is performed using 3D model of discrete element method (DEM). The crushable macro-grain is generated from a large number of identical spherical micro-grains which are connected according to the bonded particle model. First, the parameters of the proposed DEM model are calibrated to match the force-displacement curve obtained from Brazilian Tests performed on cylinders made of artificially crushable material. The damage profile right at the point when the force-displacement curve reaches its maximum is seen to replicate the same crack patterns observed in Brazilian test experiments. Then, parametric investigations are performed by varying the coordination number, the contact location distribution, and the contact area. The results show that these parameters play a significant role in determining the critical contact force and fracture mechanism of crushable particles compared to a traditional macro-grain crushing test. Increasing distribution and coordination number of the macro-grain increases particle strength when large area contact is permitted. However, for linear contact area, the effect of increasing coordination number on particle strength is marginal

Predicting the Discovery Pattern of Publically Known Exploited Vulnerabilities

Vulnerabilities with publically known exploits typically form 2-7% of all vulnerabilities reported for a given software version. With a smaller number of known exploited vulnerabilities compared with the total number of vulnerabilities, it is more difficult to model and predict when a vulnerability with a known exploit will be reported. In this paper, we introduce an approach for predicting the discovery pattern of publically known exploited vulnerabilities using all publically known vulnerabilities reported for a given software. Eight commonly used vulnerability discovery models (VDMs) and one neural network model (NNM) were utilized to evaluate the prediction capability of our approach. We compared their predictions results with the scenario when only exploited vulnerabilities were used for prediction. Our results show that, in terms of prediction accuracy, out of eight software we analyzed, our approach led to more accurate results in seven cases. Only in one case, the accuracy of our approach was worse by 1.6%

Cluster-based Vulnerability Assessment Applied to Operating Systems

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed

Cluster-based Vulnerability Assessment Applied to Operating Systems

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed

Cluster-based Vulnerability Assessment of Operating Systems and Web Browsers

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) and web browsers they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs (Windows, Mac, IOS, and Linux) and four web browsers (Internet Explorer, Safari, Firefox, and Chrome). Out of the total eight OSs and web browsers we analyzed using a power-law model issued from a family of SRMs, the model was statistically adequate for modeling in six cases. For these cases, in terms of estimation and forecasting capability, our results, compared to a power-law model without clustering, are more accurate in all cases but one

A Comparative Study on Critical Thinking Skills of Bachelor and Master's Degree Students in Critical Care Nursing

Background: Promoting critical thinking skills is an essential outcome of undergraduate and postgraduate nursing education. Objectives: The current study aims at comparing critical thinking skills of bachelor students of nursing (BSc) and master’s students of critical care nursing (MSc) in the academic year 2014 - 2015. Methods: The current cross-sectional study was conducted on 79 BSc students of nursing and 44 MSc students of critical care nursing in 3 universities of medical sciences including Semnan, Tehran, and Kashan. The California critical thinking test, form B, was used for data collection. Analysis of variance Mann-Whitney, and Kruskal-Wallis tests were used for statistical analyses. Results: Themeanscores of BS and MSc nursing students were 11.14�3.01 and 10.05�3.33, respectively, which were not significantly different. The mean scores of students in Semnan, Tehran, and Kashan universities of medical sciences were 9.84 � 3.13, 9.66 � 3.32, and 11.79 � 2.92, respectively, and the total mean score was 10.46 � 3.24. The scores of critical thinking domains showed that students in Kashan University gained higher scores in interference, and deductive and inductive reasoning domains compared with the students in other universities. Conclusions: The level of critical thinking in BSc students was higher. The overall level of critical thinking skills was low in nursing students. It is suggested that appropriate and effective methods should be employed to create and improve critical thinking in nursing education

A Comparative Study on Critical Thinking Skills of Bachelor and Master�s Degree Students in Critical Care Nursing

Background: Promoting critical thinking skills is an essential outcome of undergraduate and postgraduate nursing education. Objectives: The current study aims at comparing critical thinking skills of bachelor students of nursing (BSc) and master’s students of critical care nursing (MSc) in the academic year 2014 - 2015. Methods: The current cross-sectional study was conducted on 79 BSc students of nursing and 44 MSc students of critical care nursing in 3 universities of medical sciences including Semnan, Tehran, and Kashan. The California critical thinking test, form B, was used for data collection. Analysis of variance Mann-Whitney, and Kruskal-Wallis tests were used for statistical analyses. Results: Themeanscores of BS and MSc nursing students were 11.14�3.01 and 10.05�3.33, respectively, which were not significantly different. The mean scores of students in Semnan, Tehran, and Kashan universities of medical sciences were 9.84 � 3.13, 9.66 � 3.32, and 11.79 � 2.92, respectively, and the total mean score was 10.46 � 3.24. The scores of critical thinking domains showed that students in Kashan University gained higher scores in interference, and deductive and inductive reasoning domains compared with the students in other universities. Conclusions: The level of critical thinking in BSc students was higher. The overall level of critical thinking skills was low in nursing students. It is suggested that appropriate and effective methods should be employed to create and improve critical thinking in nursing education

Increasing the number of embryos transferred from two to three, does not increase pregnancy rates in good prognosis patients

Background: To compare the pregnancy outcomes after two embryos versus three embryos transfers (ETs) in women undergoing in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) cycles. Materials and Methods: This retrospective study was performed on three hundred eighty seven women with primary infertility and with at least one fresh embryo in good quality in order to transfer at each IVF/ICSI cycle, from September 2006 to June 2010. Patients were categorized into two groups according to the number of ET as follows: ET2 and ET3 groups, indicating two and three embryos were respectively transferred. Pregnancy outcomes were compared between ET2 and ET3 groups. Chi square and student t tests were used for data analysis. Results: Clinical pregnancy and live birth rates were similar between two groups. The rates of multiple pregnancies were 27 and 45.2 in ET2 and ET3 groups, respectively. The rate of multiple pregnancies in young women was significantly increased when triple instead of double embryos were transferred. Logistic regression analysis indicated two significant prognostic variables for live birth that included number and quality of transferred embryos; it means that the chance of live birth following ICSI treatment increased 3.2-fold when the embryo with top quality (grade A) was transferred, but the number of ET had an inverse relationship with live birth rate; it means that probability of live birth in women with transfer of two embryos was three times greater than those who had three ET. Conclusion: Due to the difficulty of implementation of the elective single-ET technique in some infertility centers in the world, we suggest transfer of double instead of triple embryos when at least one good quality embryo is available for transfer in women aged 39 years or younger. However, to reduce the rate of multiple pregnancies, it is recommended to consider the elective single ET strategy. � 2015, Royan Institute (ACECR). All rights reserved

Ten-tier and multi-scale supplychain network analysis of medical equipment: Random failure and intelligent attack analysis

Motivated by the COVID-19 pandemic, this paper explores the supply chain viability of medical equipment, an industry whose supply chain was put under a crucial test during the pandemic. This paper includes an empirical network-level analysis of supplier reachability under Random Failure Experiment (RFE) and Intelligent Attack Experiment (IAE). Specifically, this study investigates the effect of RFA and IAE across multiple tiers and scales. The global supply chain data was mined and analyzed from about 45,000 firms with about 115,000 intertwined relationships spanning across 10 tiers of the backward supply chain of medical equipment. This complex supply chain network was analyzed at four scales, namely: firm, country-industry, industry, and country. A notable contribution of this study is the application of a supply chain tier optimization tool to identify the lowest tier of the supply chain that can provide adequate resolution for the study of the supply chain pattern. We also developed data-driven-tools to identify the thresholds for breakdown and fragmentation of the medical equipment supply chain when faced with random failures or different intelligent attack scenarios. The novel network analysis tools utilized in the study can be applied to the study of supply chain reachability and viability in other industries.Comment: 47 page