Non-equilibrium phase transition in negotiation dynamics

We introduce a model of negotiation dynamics whose aim is that of mimicking the mechanisms leading to opinion and convention formation in a population of individuals. The negotiation process, as opposed to ``herding-like'' or ``bounded confidence'' driven processes, is based on a microscopic dynamics where memory and feedback play a central role. Our model displays a non-equilibrium phase transition from an absorbing state in which all agents reach a consensus to an active stationary state characterized either by polarization or fragmentation in clusters of agents with different opinions. We show the exystence of at least two different universality classes, one for the case with two possible opinions and one for the case with an unlimited number of opinions. The phase transition is studied analytically and numerically for various topologies of the agents' interaction network. In both cases the universality classes do not seem to depend on the specific interaction topology, the only relevant feature being the total number of different opinions ever present in the system.Comment: 4 pages, 4 figure

Consensus formation on adaptive networks

The structure of a network can significantly influence the properties of the dynamical processes which take place on them. While many studies have been devoted to this influence, much less attention has been devoted to the interplay and feedback mechanisms between dynamical processes and network topology on adaptive networks. Adaptive rewiring of links can happen in real life systems such as acquaintance networks where people are more likely to maintain a social connection if their views and values are similar. In our study, we consider different variants of a model for consensus formation. Our investigations reveal that the adaptation of the network topology fosters cluster formation by enhancing communication between agents of similar opinion, though it also promotes the division of these clusters. The temporal behavior is also strongly affected by adaptivity: while, on static networks, it is influenced by percolation properties, on adaptive networks, both the early and late time evolution of the system are determined by the rewiring process. The investigation of a variant of the model reveals that the scenarios of transitions between consensus and polarized states are more robust on adaptive networks.Comment: 11 pages, 14 figure

Landing together: how flocks arrive at a coherent action in time and space in the presence of perturbations

Collective motion is abundant in nature, producing a vast amount of phenomena which have been studied in recent years, including the landing of flocks of birds. We investigate the collective decision making scenario where a flock of birds decides the optimal time of landing in the absence of a global leader. We introduce a simple phenomenological model in the spirit of the statistical mechanics-based self-propelled particles (SPP-s) approach to interpret this process. We expect that our model is applicable to a larger class of spatiotemporal decision making situations than just the landing of flocks (which process is used as a paradigmatic case). In the model birds are only influenced by observable variables, like position and velocity. Heterogeneity is introduced in the flock in terms of a depletion time after which a bird feels increasing bias to move towards the ground. Our model demonstrates a possible mechanism by which animals in a large group can arrive at an egalitarian decision about the time of switching from one activity to another in the absence of a leader. In particular, we show the existence of a paradoxical effect where noise enhances the coherence of the landing process.Comment: 15 pages, 7 figure

Crises and collective socio-economic phenomena: simple models and challenges

Financial and economic history is strewn with bubbles and crashes, booms and busts, crises and upheavals of all sorts. Understanding the origin of these events is arguably one of the most important problems in economic theory. In this paper, we review recent efforts to include heterogeneities and interactions in models of decision. We argue that the Random Field Ising model (RFIM) indeed provides a unifying framework to account for many collective socio-economic phenomena that lead to sudden ruptures and crises. We discuss different models that can capture potentially destabilising self-referential feedback loops, induced either by herding, i.e. reference to peers, or trending, i.e. reference to the past, and account for some of the phenomenology missing in the standard models. We discuss some empirically testable predictions of these models, for example robust signatures of RFIM-like herding effects, or the logarithmic decay of spatial correlations of voting patterns. One of the most striking result, inspired by statistical physics methods, is that Adam Smith's invisible hand can badly fail at solving simple coordination problems. We also insist on the issue of time-scales, that can be extremely long in some cases, and prevent socially optimal equilibria to be reached. As a theoretical challenge, the study of so-called "detailed-balance" violating decision rules is needed to decide whether conclusions based on current models (that all assume detailed-balance) are indeed robust and generic.Comment: Review paper accepted for a special issue of J Stat Phys; several minor improvements along reviewers' comment

Isolation and individual electrical stimulation of single smooth-muscle cells from the urinary bladder of the pig

In contrast to striated muscle, measurements on strips of smooth muscle cannot be uniquely interpreted in terms of an array of contractile units. Therefore scaling down to the single-cell level is necessary to gain detailed understanding of the contractile process in this type of muscle. The present study describes the development of a method for isolating contractile single smooth muscle cells from pig urinary bladders. Contractile responses evoked by individual electrical stimulation were used as a measure of cell quality during development of the method. Responses were evaluated by measuring latency, contraction and relaxation times, as indicated by visible length changes, and stored on-line in a computer. Initial length, relative shortening and shortening speed were determined by measuring cell lengths in previously timed still video frames using a computer-controlled crosshair device. Increase of stimulus pulse duration resulted in improved responses, indicating that the observed shortening represented a physiological contractile response. Ultimately this method of evaluation was applied to two sets of cell preparations obtained by two different methods, one using only collagenase digestion, the other using mechanical manipulation as well. Both sets showed two main patterns of response to electrical stimulation: a pattern of contraction upon stimulation followed by enhanced contraction when stimulation was switched off (CK), and a pattern of contraction upon stimulation followed by relaxation when the stimulus was switched off (CR). The set of preparations containing the highest percentage of CR cells was found to be superior (i.e. greater initial length, shorter latency and contraction times, increased shortening and higher shortening speed). The method of isolation used for this set gives a high yield of contractile cells available for experimental use over a long span of time

Information Revolutions and the Overthrow of Autocratic Regimes

This paper presents a model of information quality and political regime change. If enough citizens act against a regime, it is overthrown. Citizens are imperfectly informed about how hard this will be and the regime can, at a cost, engage in propaganda so that at face-value it seems hard. The citizens are rational and evaluate their information knowing the regime's incentives. The model makes three predictions. First, even rational citizens may not correctly infer the amount of manipulation. Second, as the intrinsic quality of information available becomes sufficiently high, the regime is more likely to survive. Third, the regime benefits from ambiguity about the amount of manipulation, and consequently, as it becomes cheaper to manipulate, the regime is also more likely to survive. Key results of the benchmark static model extend to a simple dynamic setting where there are waves of unrest

Metabolic cost of external work: a novel CPET parameter optimises characterisation of exercise performance in obese individuals

Abstract Purpose Both obesity and cardiorespiratory fitness are crucial determinants of symptoms and prognosis. However, interpreting the gold-standard cardiopulmonary exercise test (CPET) is complicated by increasing body size and varying body composition. We hypothesised that the ‘metabolic cost of external work’ (or oxygen uptake (ml/min)/workload (Watts); V̇O 2 /W), a body weight-independent determinant of endurance capacity, would reflect metabolic health more accurately than V̇O 2 alone. Methods A test cohort of 160 fit individuals underwent anthropomorphic and metabolic assessment, maximal bicycle ergometer CPET, and six-minute walk test (6MWT). V̇O 2 /W was calculated at VT1 and peak. The performance of V̇O 2 /W was validated in 62 older, less fit individuals, undergoing the same protocol. 24 obese volunteers were assigned a weight loss intervention, and the impact on V̇O 2 /W examined. Results In both test and validation cohort, V̇O 2 /W at VT1 and peak correlated with 6MWT distance, more strongly than standard CPET parameters. Including V̇O 2 /W improved the accuracy of predicting 6MWT distance. V̇O 2 /W correlated with BMI, insulin sensitivity and waist-to-hip ratio. Metabolic cost falls with weight loss, in parallel to metabolic and functional improvements, in contrast to other CPET parameters. Conclusion Metabolic cost is strongly associated with functional capacity and metabolic health across a range of body weight and fitness, outperforming standard CPET metrics. It is a simple measure which may improve our assessment of the extent to which exertional symptoms are determined by metabolic factors in an individual, and thereby target the most appropriate intervention to those who will benefit most. Graphical Abstract

Cardiopulmonary exercise testing excludes significant disease in patients recovering from COVID-19

Objective Post-COVID-19 syndrome presents a health and economic challenge affecting ~10% of patients recovering from COVID-19. Accurate assessment of patients with post-COVID-19 syndrome is complicated by health anxiety and coincident symptomatic autonomic dysfunction. We sought to determine whether either symptoms or objective cardiopulmonary exercise testing could predict clinically significant findings. Methods 113 consecutive military patients were assessed in a comprehensive clinical pathway. This included symptom reporting, history, examination, spirometry, echocardiography and cardiopulmonary exercise testing (CPET) in all, with chest CT, dual-energy CT pulmonary angiography and cardiac MRI where indicated. Symptoms, CPET findings and presence/absence of significant pathology were reviewed. Data were analysed to identify diagnostic strategies that may be used to exclude significant disease. Results 7/113 (6%) patients had clinically significant disease adjudicated by cardiothoracic multidisciplinary team (MDT). These patients had reduced fitness (V̇O 2 26.7 (±5.1) vs 34.6 (±7.0) mL/kg/min; p=0.002) and functional capacity (peak power 200 (±36) vs 247 (±55) W; p=0.026) compared with those without significant disease. Simple CPET criteria (oxygen uptake (V̇O 2 ) >100% predicted and minute ventilation (VE)/carbon dioxide elimination (V̇CO 2 ) slope <30.0 or VE/V̇CO 2 slope <35.0 in isolation) excluded significant disease with sensitivity and specificity of 86% and 83%, respectively (area under the receiver operating characteristic curve (AUC) 0.89). The addition of capillary blood gases to estimate alveolar–arterial gradient improved diagnostic performance to 100% sensitivity and 78% specificity (AUC 0.92). Symptoms and spirometry did not discriminate significant disease. Conclusions In a population recovering from SARS-CoV-2, there is reassuringly little organ pathology. CPET and functional capacity testing, but not reported symptoms, permit the exclusion of clinically significant disease