Personal ethical settings for driverless cars and the utility paradox: An ethical analysis of public attitudes in UK and Japan

Driverless cars are predicted to dramatically reduce collisions and casualties on the roads. However, there has been controversy about how they should be programmed to respond in the event of an unavoidable collision. Should they aim to save the most lives, prioritise the lives of pedestrians, or occupants of the vehicle? Some have argued that driverless cars should all be programmed to minimise total casualties. While this would appear to have wide international public support, previous work has also suggested regional variation and public reluctance to purchase driverless cars with such a mandated ethical setting. The possibility that algorithms designed to minimise collision fatalities would lead to reduced consumer uptake of driverless cars and thereby to higher overall road deaths, represents a potential "utility paradox". To investigate this paradox further, we examined the views of the general public about driverless cars in two online surveys in the UK and Japan, examining the influence of choice of a "personal ethical setting" as well as of framing on hypothetical purchase decisions. The personal ethical setting would allow respondents to choose between a programme which would save the most lives, save occupants or save pedestrians. We found striking differences between UK and Japanese respondents. While a majority of UK respondents wished to buy driverless cars that prioritise the most lives or their family members' lives, Japanese survey participants preferred to save pedestrians. We observed reduced willingness to purchase driverless cars with a mandated ethical setting (compared to offering choice) in both countries. It appears that the public values relevant to programming of driverless cars differ between UK and Japan. The highest uptake of driverless cars in both countries can be achieved by providing a personal ethical setting. Since uptake of driverless cars (rather than specific algorithm used) is potentially the biggest factor in reducing in traffic related accidents, providing some choice of ethical settings may be optimal for driverless cars according to a range of plausible ethical theories

Timing interactions in social simulations: The voter model

The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table

Local variation of hashtag spike trains and popularity in Twitter

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamics, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media.Comment: 7 pages, 7 figure

Universal features of correlated bursty behaviour

Inhomogeneous temporal processes, like those appearing in human communications, neuron spike trains, and seismic signals, consist of high-activity bursty intervals alternating with long low-activity periods. In recent studies such bursty behavior has been characterized by a fat-tailed inter-event time distribution, while temporal correlations were measured by the autocorrelation function. However, these characteristic functions are not capable to fully characterize temporally correlated heterogenous behavior. Here we show that the distribution of the number of events in a bursty period serves as a good indicator of the dependencies, leading to the universal observation of power-law distribution in a broad class of phenomena. We find that the correlations in these quite different systems can be commonly interpreted by memory effects and described by a simple phenomenological model, which displays temporal behavior qualitatively similar to that in real systems

Lenvatinib versus Sorafenib as first-line treatment in hepatocellular carcinoma: A multi-institutional matched case-control study

Background: Advanced Hepatocarcinoma (HCC) is an important health problem worldwide. Recently, the REFLECT trial demonstrated the non-inferiority of Lenvatinib compared to Sorafenib in I line setting, thus leading to the approval of new first-line standard of care, along with Sorafenib. Aims and methods: With aim to evaluate the optimal choice between Sorafenib and Lenvatinib as primary treatment in clinical practice, we performed a multicentric analysis with the propensity score matching on 184 HCC patients. Results: The median overall survival (OS) were 15.2 and 10.5 months for Lenvatinib and Sorafenib arm, respectively. The median progression-free survival (PFS) was 7.0 and 4.5 months for Lenvatinib and Sorafenib arm, respectively. Patients treated with Lenvatinib showed a 36% reduction of death risk (p = 0.0156), a 29% reduction of progression risk (p = 0.0446), a higher response rate (p < 0.00001) and a higher disease control rate (p = 0.002). Sorafenib showed to be correlated with more hand-foot skin reaction and Lenvatinib with more hypertension and fatigue. We highlighted the prognostic role of Barcelona Clinic Liver Cancer (BCLC) stage, Eastern Cooperative Oncology Group Performance Status (ECOG-PS), bilirubin, alkaline phosphatase and eosinophils for Sorafenib. Conversely, albumin, aspartate aminotransferase (AST), alkaline phosphatase and Neutrophil-Lymphocyte Ratio (NLR) resulted prognostic in Lenvatinib arm. Finally, we highlighted the positive predictive role of albumin > Normal Value (NV), ECOG > 0, NLR < 3, absence of Hepatitis C Virus positivity, and presence of portal vein thrombosis in favor of Lenvatinib arm. Eosinophil < 50 and ECOG > 0 negatively predicted the response to Sorafenib. Conclusion: SLenvatinib showed to better perform in a real-word setting compared to Sorafenib. More researches are needed to validate the predictor factors of response to Lenvatinib rather than Sorafenib

Opinion dynamics: models, extensions and external effects

Recently, social phenomena have received a lot of attention not only from social scientists, but also from physicists, mathematicians and computer scientists, in the emerging interdisciplinary field of complex system science. Opinion dynamics is one of the processes studied, since opinions are the drivers of human behaviour, and play a crucial role in many global challenges that our complex world and societies are facing: global financial crises, global pandemics, growth of cities, urbanisation and migration patterns, and last but not least important, climate change and environmental sustainability and protection. Opinion formation is a complex process affected by the interplay of different elements, including the individual predisposition, the influence of positive and negative peer interaction (social networks playing a crucial role in this respect), the information each individual is exposed to, and many others. Several models inspired from those in use in physics have been developed to encompass many of these elements, and to allow for the identification of the mechanisms involved in the opinion formation process and the understanding of their role, with the practical aim of simulating opinion formation and spreading under various conditions. These modelling schemes range from binary simple models such as the voter model, to multi-dimensional continuous approaches. Here, we provide a review of recent methods, focusing on models employing both peer interaction and external information, and emphasising the role that less studied mechanisms, such as disagreement, has in driving the opinion dynamics. [...]Comment: 42 pages, 6 figure

Importance of individual events in temporal networks

Records of time-stamped social interactions between pairs of individuals (e.g., face-to-face conversations, e-mail exchanges, and phone calls) constitute a so-called temporal network. A remarkable difference between temporal networks and conventional static networks is that time-stamped events rather than links are the unit elements generating the collective behavior of nodes. We propose an importance measure for single interaction events. By generalizing the concept of the advance of event proposed by [Kossinets G, Kleinberg J, and Watts D J (2008) Proceeding of the 14th ACM SIGKDD International conference on knowledge discovery and data mining, p 435], we propose that an event is central when it carries new information about others to the two nodes involved in the event. We find that the proposed measure properly quantifies the importance of events in connecting nodes along time-ordered paths. Because of strong heterogeneity in the importance of events present in real data, a small fraction of highly important events is necessary and sufficient to sustain the connectivity of temporal networks. Nevertheless, in contrast to the behavior of scale-free networks against link removal, this property mainly results from bursty activity patterns and not heterogeneous degree distributions.Comment: 36 pages, 13 figures, 2 table

Nonalcoholic steatohepatitis in hepatocarcinoma: new insights about its prognostic role in patients treated with lenvatinib

Background: Hepatocellular carcinoma (HCC) treatment remains a big challenge in the field of oncology. The liver disease (viral or not viral) underlying HCC turned out to be crucial in determining the biologic behavior of the tumor, including its response to treatment. The aim of this analysis was to investigate the role of the etiology of the underlying liver disease in survival outcomes. Patients and methods: We conducted a multicenter retrospective study on a large cohort of patients treated with lenvatinib as first-line therapy for advanced HCC from both Eastern and Western institutions. Univariate and multivariate analyses were performed. Results: Among the 1232 lenvatinib-treated HCC patients, 453 (36.8%) were hepatitis C virus positive, 268 hepatitis B virus positive (21.8%), 236 nonalcoholic steatohepatitis (NASH) correlate (19.2%) and 275 had other etiologies (22.3%). The median progression-free survival (mPFS) was 6.2 months [95% confidence interval (CI) 5.9-6.7 months] and the median overall survival (mOS) was 15.8 months (95% CI 14.9-17.2 months). In the univariate analysis for OS NASH-HCC was associated with longer mOS [22.2 versus 15.1 months; hazard ratio (HR) 0.69; 95% CI 0.56-0.85; P = 0.0006]. In the univariate analysis for PFS NASH-HCC was associated with longer mPFS (7.5 versus 6.5 months; HR 0.84; 95% CI 0.71-0.99; P = 0.0436). The multivariate analysis confirmed NASH-HCC (HR 0.64; 95% CI 0.48-0.86; P = 0.0028) as an independent prognostic factor for OS, along with albumin–bilirubin (ALBI) grade, extrahepatic spread, neutrophil-to-lymphocyte ratio, portal vein thrombosis, Eastern Cooperative Oncology Group (ECOG) performance status and alpha-fetoprotein. An interaction test was performed between sorafenib and lenvatinib cohorts and the results highlighted the positive predictive role of NASH in favor of the lenvatinib arm (P = 0.0047). Conclusion: NASH has been identified as an independent prognostic factor in a large cohort of patients with advanced HCC treated with lenvatinib, thereby suggesting the role of the etiology in the selection of patients for tyrosine kinase treatment. If validated, this result could provide new insights useful to improve the management of these patients

Effects of temporal correlations in social multiplex networks

Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena. Despite its importance, however, the role of the temporal dimension in their structure and function has not been investigated in much detail so far. Here we study the temporal correlations between layers exhibited by real social multiplex networks. At a basic level, the presence of such correlations implies a certain degree of predictability in the contact pattern, as we quantify by an extension of the entropy and mutual information analyses proposed for the single-layer case. At a different level, we demonstrate that temporal correlations are a signature of a ‘multitasking’ behavior of network agents, characterized by a higher level of switching between different social activities than expected in a uncorrelated pattern. Moreover, temporal correlations significantly affect the dynamics of coupled epidemic processes unfolding on the network. Our work opens the way for the systematic study of temporal multiplex networks and we anticipate it will be of interest to researchers in a broad array of fields

Atezolizumab plus bevacizumab versus lenvatinib or sorafenib in non-viral unresectable hepatocellular carcinoma: an international propensity score matching analysis

A growing body of evidence suggests that non-viral hepatocellular carcinoma (HCC) might benefit less from immunotherapy