Controllability of Social Networks and the Strategic Use of Random Information

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network, and considers two well-known strategies for influencing social contexts. One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad-hoc metrics defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills, supporting our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable

The Effect of Security Education and Expertise on Security Assessments: the Case of Software Vulnerabilities

In spite of the growing importance of software security and the industry demand for more cyber security expertise in the workforce, the effect of security education and experience on the ability to assess complex software security problems has only been recently investigated. As proxy for the full range of software security skills, we considered the problem of assessing the severity of software vulnerabilities by means of a structured analysis methodology widely used in industry (i.e. the Common Vulnerability Scoring System (\CVSS) v3), and designed a study to compare how accurately individuals with background in information technology but different professional experience and education in cyber security are able to assess the severity of software vulnerabilities. Our results provide some structural insights into the complex relationship between education or experience of assessors and the quality of their assessments. In particular we find that individual characteristics matter more than professional experience or formal education; apparently it is the \emph{combination} of skills that one owns (including the actual knowledge of the system under study), rather than the specialization or the years of experience, to influence more the assessment quality. Similarly, we find that the overall advantage given by professional expertise significantly depends on the composition of the individual security skills as well as on the available information.Comment: Presented at the Workshop on the Economics of Information Security (WEIS 2018), Innsbruck, Austria, June 201

Relationship between obesity and early failure of total knee prostheses

<p>Abstract</p> <p>Background</p> <p>Obesity is a risk factor for knee arthritis. Total knee arthroplasty is the definitive surgical treatment of this disease. Therefore, a high percentage of subjects treated are overweight. Since 2000 in the Emilia-Romagna Region the Register of Orthopedic Prosthetic Implantology, RIPO, has recorded data of all the primary and revision operations performed on the knee; height and weight of patients at the time of surgery have also been recorded.</p> <p>Methods</p> <p>To understand how overweight and obesity affect the outcome of knee arthroplasty, a population of subjects treated with cemented total knee arthroplasty between 2000 and 2005 was studied. 9735 knee prostheses were implanted in 8892 patients; 18.9% of the patients were normal weight, 48.2% were overweight (25 < Body Mass Index <= 30), 31.1% were obese (30 < BMI <= 40), and 1.8% were morbidly obese (BMI > 40). Mean and range of follow-up were respectively 3.1 and 1.5–6 yrs. Implant failure was defined as the exchange of at least one component for whatever reason.</p> <p>Results</p> <p>In normal weight patients there were 36 failures out of 1840 implants (1.96%), in overweight patients there were 87 out of 4692 (1.85%), in obese 59 out of 3031 (1.94%), and in morbidly obese there were 4 out of 172 (2.3%). The mean time to failure for each class was 1.57, 1.48, 1.60, 1.77 yrs. Cox regression analyses showed that the risk of implant failure was not influenced by BMI, absolute body weight, or sex. Conversely, an increased failure risk was observed in mobile meniscus prostheses in comparison with those with a fixed meniscus (Rate Ratio 1.88); an increased failure risk was also related to age (Rate Ratio 1.05 per year). These results were also confirmed when considering septic loosening as the end-point. There were no differences in the rate of perioperative complications and death in the 4 classes of BMI.</p> <p>Conclusion</p> <p>In conclusion, cemented knee prostheses, implanted in patients with arthritis do not have significantly different rates of survival or perioperative complications in obese subjects compared with normal weight subjects, at least up to 5 years after surgery. The conclusion also applies to subjects affected by morbid obesity, altough this findings should be regarded with caution due to the small sample examined.</p

Structural behaviour and strain distribution of the long bones of the human lower limbs

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