Information and Control in Networks

Information and Control in Networks demonstrates the way in which system dynamics and information flows intertwine as they evolve, and the central role played by information in the control of complex networked systems. It is a milestone on the road to that convergence from traditionally independent development of control theory and information theory which has emerged strongly in the last fifteen years, and is now a very active research field. In addition to efforts in control and information theory, the text is witness to strong research in such diverse fields as computer science, mathematics, and statistics. Aspects that are given specialist treatment include: ·                 data-rate theorems; ·                 computation and control over communication networks; ·                 decentralized stochastic control; ·                 Gaussian networks and Gaussian–Markov random fields; and ·                 routability in information networks. Information and Control in Networks collects contributions from world-leading researchers in the area who came together for the Lund Center for Control of Complex Engineering Systems Workshop in Information and Control in Networks from 17th–19th October 2012; the workshop being the centrepiece of a five-week-long focus period on the same theme. A source of exciting cross-fertilization and new ideas for extensive future research, this volume will be of great interest to any researcher or graduate student interested in the interaction of control and information theory

Inter-reader agreement of high-resolution computed tomography findings in patients with COVID-19 pneumonia: A multi-reader study

Purpose: To investigate the inter-reader agreement in assessing high-resolution computed tomography (HRCT) features of coronavirus disease 2019 (COVID-19) pneumonia. Method: Seventy-seven consecutive patients (mean age, 64 \ub1 15\ua0years) with mild COVID-19 pneumonia that underwent HRCT were retrospectively included. Three radiologists [two devoted to thoracic imaging (R1, R2), and one generalist (R3)] on a per-examination basis independently assessed ground-glass opacity (GGO), consolidation, and crazy-paving pattern. The extent of each feature (total feature score, TFS) was semi-quantitatively assessed, and each TFS summed up to obtain total lung score (TLS). Presence of organizing pneumonia (OP) pattern was also recorded. The inter-reader agreement was calculated with Cohen\u2019s Kappa (k) and Free-Marginal Multirater k. Multivariable analysis was run to determine whether imaging features were predictive of short-term evolution to severe disease (need for ventilation). Results: Most features showed substantial inter-reader agreement, including TLS > 6 (k = 0.69), which was an independent predictor of short-term occurrence of severe disease, regardless of the reader (OR 9\u201353.19). Consolidation TFS > 2 and OP pattern showed substantial and moderate agreement, respectively, only when comparing R1 and R2. Consolidation TFS > 2 and OP pattern were independent predictors of severe disease for R2 (OR 4.87) and R1 (OR 6), respectively. Conclusions: The inter-reader agreement for most HRCT features of COVID-19 pneumonia ranges moderate-to-substantial, though it depends on readers\u2019 experience in the case of consolidation and OP pattern

I sistemi multi-agents e gli algoritmi di consenso

Recently, multi-agent systems have become a central study topic in many different disciplines including biology, engineering, physics, and social science. This has led to the emergence of large and constantly growing interdisciplinary research field, known as network science. The analysis of the mathematical models describing such systems has achieved significant results, but remains mostly an open research field, where many fundamental breakthroughs are expected in the next years. Such analysis is especially motivated by the quest for the development of tools for control and design of such systems. In this paper, we deal with consensus algorithms, an important example of design of multi-agent systems that has been inspired by the dynamics of cooperative systems in natural and social sciences

The role of vitamin deficiency in liver disease: To supplement or not supplement?

Over the past few years, growing interest has been shown for the impact of dietary requirements and nutritional factors on chronic diseases. As a result, nutritional programs have been reinforced by public health policies. The precise role of micronutrients in chronic liver disease is currently receiving particular attention since abnormalities in vitamin levels are often detected. At present, treatment programs are focused on correcting vitamin deficiencies, which are frequently correlated to higher rates of comorbidities with poor outcomes. The literature reviewed here indicates that liver diseases are often related to vitamin disorders, due to both liver impairment and abnormal intake. More specific knowledge about the role of vitamins in liver disease is currently emerging from various results and recent evidence. The most significant benefits in this area may be observed when improved vitamin intake is combined with a pharmacological treatment that may also affect the progression of the liver disease, especially in the case of liver tumors. However, further studies are needed

Is There a Relationship between Objectively Measured Cognitive Changes in Cancer Patients Undergoing Chemotherapy Treatment and Their Health-related Quality of Life? A Systematic Review

Background/purpose: Many people living with cancer experience depression. Research suggests that the therapeutic effect of exercise on depression is similar to pharmacotherapy or psychological intervention, yet cancer survivors are under-exercising compared to recommended doses. Self-efficacy may be a factor to explain exercise engagement. This cross-sectional study investigated whether exercise task self-efficacy (ETSE) was associated with exercise engagement, further examining differences between cancer survivors with and without elevated depressive symptoms. \ud \ud Methods: Ninety-seven cancer survivors (60.8 ±9.9 years) were mailed self-report questionnaires on ETSE, exercise engagement, and depressive symptoms. A Hospital Anxiety and Depression Scale D cutoff score (≥8) was used to assign participants to a symptomatic (n = 34) or non-symptomatic group (n = 63). An independent t-test was used to examine differences in ETSE between groups. Correlational analyses were used to examine relationships between exercise task self-efficacy and exercise engagement. \ud \ud Results: There was a significant difference in the degree of exercise task self-efficacy between cancer survivors with (M=35.74, SD= 31.47) and without (M=57.30, SD= 26.71) depressive symptoms, t(95) =_3.56, p<0.01, with a large effect size (d =0.74). A positive association was found between ETSE and exercise engagement, r(95)= 0.49, p<0.01, which was similar for both groups. \ud \ud Conclusions: Exercise task self-efficacy appears to influence exercise engagement independently of mood status, but people with higher levels of depression symptoms tend to have lower self-efficacy. Therefore, future research should examine interventions to enhance exercise task self-efficacy, thereby potentially increasing exercise engagement in cancer survivors. Research Implications: These findings demonstrated that cancer survivors with depressive symptoms have low ETSE and that ETSE can predict exercise engagement. This suggests a role for enhancing ETSE to influence exercise engagement in cancer survivors. Future research could investigate causality between ETSE and exercise engagement and interventions to enhance ETSE. The findings of the present study could assist with more definitive research which could aid clinicians interested in behavioral change with regard to exercise engagement and improvement of depressive symptomatology in cancer survivors. Practice Implications: The findings illustrate that exercise self-efficacy predicts exercise engagement, independently of mood. Therefore, clinicians working with depressed or non-depressed cancer survivors should initially target increasing exercise self-efficacy as opposed to reinforcing the positive health benefits of increased physical activity

Opinion dynamics and stubbornness through mean-field games

This paper provides a mean field game theoretic interpretation of opinion dynamics and stubbornness. The model describes a crowd-seeking homogeneous population of agents, under the influence of one stubborn agent. The game takes on the form of two partial differential equations, the Hamilton-Jacobi-Bellman equation and the Kolmogorov- Fokker-Planck equation for the individual optimal response and the population evolution, respectively. For the game of interest, we establish a mean field equilibrium where all agents reach "-consensus in a neighborhood of the stubborn agent's opinion. ©2013 IEEE

Effect of Benzoic Acids on Barite and Calcite Precipitation

The effect of various benzoic acids on the precipitation of barite (BaSO4) and calcite (CaCO3) was investigated. The acids varied in the number of carboxylate groups, from dibenzoic acids (phthalic, isophthalic, and terephthalic) through to the hexabenzoic acid (mellitic acid). It was found that the stereochemistry of the dibenzoic acids was important, as was the pH of the solution (trimesic acid was used as a test case and showed that greatest inhibition was achieved with all carboxylate groups deprotonated). Interestingly, for both the calcite and barite systems, mellitic acid was found to be both a potent inhibitor and a significant crystal growth modifier. In the case of barite, the presence of mellitic acid produced nanoparticles that agglomerated. The nanoparticles were found to be 20 nm in size from X-ray diffraction (XRD) line width analysis and 20-50 nm from transmission electron microscopy (TEM). Humic acid was also tested and found to form bundled fibers of barium sulfate