Hereditary non-polyposis colorectal carcinoma (HNPCC) : morphological and immunohistochemical studies

Includes bibliographical references.Families with hereditary non-polyposis colorectal carcinoma (HNPCC) are not uncommon along the West-Coast of South Africa. These patients present with early onset carcinomas mostly colorectal, predominantly in the right colon. They may develop tumours of other organs, including uterus, breast, stomach and skin. To evaluate and compare the microscopic characteristics of three groups of colorectal carcinomas (HNPCC, early onset colorectal carcinomas and sporadic colorectal carcinomas). 2. To determine the features most characteristic of the group

Wage Earners’ Priority in Bankruptcy: Application to Welfare Fund Payments

This paper describes a study on how cyber security experts assess the importance of three variables related to the probability of successful remote code execution attacks – presence of: (i) non-executable memory, (ii) access and (iii) exploits for High or Medium vulnerabilities as defined by the Common Vulnerability Scoring System. The rest of the relevant variables were fixed by the environment of a cyber defense exercise where the respondents participated. The questionnaire was fully completed by fifteen experts. These experts perceived access as the most important variable and availability of exploits for High vulnerabilities as more important than Medium vulnerabilities. Non-executable memory was not seen as significant, however, presumably due to lack of address space layout randomization and canaries in the network architecture of the cyber defense exercise scenario.QC 20140908</p

A Model for Predicting the Likelihood of Successful Exploitation

This paper presents a model that estimates the likelihood that a detected vulnerability can be exploited. The data used to produce the model was obtained by carrying out an experiment that involved exploit attempts against 1179 different machines within a cyber range. Three machine learning algorithms were tested: support vector machines, random forests and neural networks. The best results were provided by a random forest model. This model has a mean cross-validation accuracy of 98.2% and an F1 score of 0.73

Integrating Economic and Ecological Benchmarking for a Sustainable Development of Hydropower

Hydropower reservoirs play an increasingly important role for the global electricity supply. Reservoirs are anthropogenically-dominated ecosystems because hydropower operations induce artificial water level fluctuations (WLF) that exceed natural fluctuations in frequency and amplitude. These WLF have detrimental ecological effects, which can be quantified as losses to ecosystem primary production due to lake bottoms that fall dry. To allow for a sustainable development of hydropower, these “ecological costs” of WLF need to be weighed against the “economic benefits” of hydropower that can balance and store intermittent renewable energy. We designed an economic hydropower operation model to derive WLF in large and small reservoirs for three different future energy market scenarios and quantified the according losses in ecosystem primary production in semi-natural outdoor experiments. Our results show that variations in market conditions affect WLF differently in small and large hydropower reservoirs and that increasing price volatility magnified WLF and reduced primary production. Our model allows an assessment of the trade-off between the objectives of preserving environmental resources and economic development, which lies at the core of emerging sustainability issues

KYPO4INDUSTRY: A Testbed for Teaching Cybersecurity of Industrial Control Systems

There are different requirements on cybersecurity of industrial control systems and information technology systems. This fact exacerbates the global issue of hiring cybersecurity employees with relevant skills. In this paper, we present KYPO4INDUSTRY training facility and a course syllabus for beginner and intermediate computer science students to learn cybersecurity in a simulated industrial environment. The training facility is built using open-source hardware and software and provides reconfigurable modules of industrial control systems. The course uses a flipped classroom format with hands-on projects: the students create educational games that replicate real cyber attacks. Throughout the semester, they learn to understand the risks and gain capabilities to respond to cyber attacks that target industrial control systems. Our described experience from the design of the testbed and its usage can help any educator interested in teaching cybersecurity of cyber-physical systems

McCarran-Ferguson Act’s Antitrust Exemption for Insurance: Language, History and Policy

Security vulnerabilities continue to be an issue in the software field and new severe vulnerabilities are discovered in software products each month. This paper analyzes estimates from domain experts on the amount of effort required for a penetration tester to find a zero-day vulnerability in a software product. Estimates are developed using Cooke's classical method for 16 types of vulnerability discovery projects – each corresponding to a configuration of four security measures. The estimates indicate that, regardless of project type, two weeks of testing are enough to discover a software vulnerability of high severity with fifty percent chance. In some project types an eight-to-five-week is enough to find a zero-day vulnerability with 95 percent probability. While all studied measures increase the effort required for the penetration tester none of them have a striking impact on the effort required to find a vulnerability.QC 20121018</p

Defense-related transcription factors WRKY70 and WRKY54 modulate osmotic stress tolerance by regulating stomatal aperture in Arabidopsis

Peer reviewe

Depression and social isolation during the COVID-19 pandemic in a student population: the effects of establishing and relaxing social restrictions

IntroductionIn a quasi-naturalistic study design, we evaluate the change in psychopathological syndromes and general well-being after the alleviation of social restrictions. The aim of this study was to investigate the specific relationship between social isolation and depressive syndromes.MethodsAt two timepoints, the first during maximal social restrictions, the second after social restrictions had widely ended for 9 months, depressive and other syndromes were measured in an online survey addressing the total cohort of students registered at Heidelberg University, Germany via e-mail (n = 27,162). The complete Patient Health Questionnaire (PHQ) was used with nine items for depressive syndromes. In addition, well-being was measured by the Well-Being Index WHO-5. In the quantitative and qualitative part of the study psychopathological syndromes and well-being were related to social isolation and feelings of loneliness.ResultsAfter 1.5 years of pandemic-related social restrictions, “major” depressive syndromes were reported by 40.16% of the respondents to the PHQ in a sample of 2,318 university students. 72.52% showed a severely reduced Well-Being-Index. Nine months after the end of social restrictions, “major” depressive syndromes were reported by 28.50% of the participants. Well-being improved after the alleviation of social restrictions, as well: 53.96% showed a Well-Being Index of below 50 vs. 72.52% in the first study. The quantitative and qualitative analysis of the free texts of the respondents suggest that a significant amount of depressive syndromes and reduced well-being are related to social isolation and loneliness. While in the times of the pandemic restrictions the participants mostly reported “loneliness and social isolation” (24.2%) as their main problem, only 7.7% described these as their main problem after social restrictions had been loosened for 9 months. The qualitative analysis hints that at t2 participants were more likely to mention possible ways to actively deal with loneliness than at t1, which might be interpreted along the lines of the decrease in depressive syndromes.DiscussionKeeping the self-selection bias in mind our study results suggest that one third of “major” depressive syndromes and one quarter of severely reduced well-being accompany social restrictions or are even caused by them, with loneliness being an important factor. These results should be taken into account by health policies when coping with future pandemics