The Hidden Geometry of Complex, Network-Driven Contagion Phenomena

The spread of opinions in social networks underlies other important socio-economical processes such as the spread of innovations, the acceptance of new technologies, or the speed of modernization of infrastructure and industries. Here, we present our results on spread of opinion and the fundamental role played in this spread by two characteristics of the agents, average interconnectivity and level of commitment to the current opinion. Those in turn are dependent on many cultural characteristics of the agent's society, such as trust in others, openness to new views, willingness to discuss certain opinions outside the narrow group of family and close friends, and so on. We also report on our initial investigation how the first factor, average connectivity of social network nodes, varies across cultures based on a study of a real social network. In our Binary Adoption Model (BAM) with committed agents, the spreading of opinions involves two stages. Without sufficient support, the committed minority can advance its cause only by increasing its ranks to the so-called tipping point fraction. After such a fraction is achieved, the opinion spreads rapidly across the society. We discuss how the tipping point fraction is impacted by the two social-based factors mentioned above.

Isometric contractions induced by neuromuscular electrostimulation (NMES) have been shown to result in a prolonged force decrease but the time course of the potential central and peripheral factors have never been investigated. This study examined the specific time course of central and peripheral factors after isometric NMES-induced muscle damage. Twenty-five young healthy men were subjected to an NMES exercise consisting of 40 contractions for both legs. Changes in maximal voluntary contraction force of the knee extensors (MVC), peak evoked force during double stimulations at 10 Hz (Db10) and 100 Hz (Db100), its ratio (10∶100), voluntary activation, muscle soreness and plasma creatine kinase activity were assessed before, immediately after and throughout four days after NMES session. Changes in knee extensors volume and T2 relaxation time were also assessed at two (D2) and four (D4) days post-exercise. MVC decreased by 29% immediately after NMES session and was still 19% lower than the baseline value at D4. The decrease in Db10 was higher than in Db100 immediately and one day post-exercise resulting in a decrease (−12%) in the 10∶100 ratio. On the contrary, voluntary activation significantly decreased at D2 (−5%) and was still depressed at D4 (−5%). Muscle soreness and plasma creatine kinase activity increased after NMES and peaked at D2 and D4, respectively. T2 was also increased at D2 (6%) and D4 (9%). Additionally, changes in MVC and peripheral factors (e.g., Db100) were correlated on the full recovery period, while a significant correlation was found between changes in MVC and VA only from D2 to D4. The decrease in MVC recorded immediately after the NMES session was mainly due to peripheral changes while both central and peripheral contributions were involved in the prolonged force reduction. Interestingly, the chronological events differ from what has been reported so far for voluntary exercise-induced muscle damage.

Social network services and microblog are important application modes of Web2.0, in which opinion spread is quite different from that in other cyber-media and in traditional media. In this paper, we present an opinion-spreading model based on online social network services, to study the forms and features of the spread of public opinion in social network services. The simulation results show that the model can fit the actual data from a social network site. The speed of information spread is consistent with the conclusion of six degrees of separation theory. When an opinion with strong tendency spreads in a network in which intrinsic views obey uniform distribution, the opposite view cannot exist in the stable network. In a stable network, view distribution is related to the degree of source node and the depth of backtrack, but not related to confidence limit, which is different from Deffuant model and Hegselmann-Krause model. Meanwhile, in this paper, we the also analyze the influence of the probability of spreading will, the probability of opinion change and confidence limit on relaxation time. Finally, in the paper are shown two applications of the model: the spread of rumors and the role of opinion leaders.

We monitored optical signals from cortex stained with a voltage sensitive dye to study activity evoked by intracortical electrical stimulation. The objectives were to study the spatial and temporal spread of activity from intrinsic connections near the stimulating electrode and to develop a new technique to study extrinsic projections from striate cortex to extrastriate target areas. Various measures were made of the time course of the optical signal (latency, rise time, decay time, temporal summation, facilitation versus depression, and presence or absence of a slow undershoot); in general, these measures were found to vary significantly across different response positions, different experiments, and even different runs within the same experiment. The spatial distribution of responses near the stimulating electrode in striate cortex was usually elliptical and was most often elongated along the anterior-posterior axis, with a typical size (full width at 75% max) of 1.3 mm (anterior-posterior axis) by 0.75 mm (medio-lateral axis). In some cases, complex spatio-temporal patterns were observed, in which the position of the maximum optical signal shifted with time or split into multiple peaks. In eight experiments, a response focus was found in extrastriate cortex at an expected location within the lateromedial area (LM). The response focus in LM was typically about half the size of that in striate cortex. In some experiments we observed additional focal responses in the anterolateral visual area (AL). The extrastriate responses showed a significant delay (3-10 ms) in onset and time to peak relative to the striate response. The validity of this technique for determining extrinsic projections was tested in two types of experiments. In the first, stimulation from two electrodes in striate cortex generated response foci consistent with the known topographic organization of area LM. In the second, the optically measured response focus was shown to correlate with the histologically reconstructed projection of a chemical tracer injected near the site of stimulation. We discuss the chain of neurophysiological events that occur during and after focal electrical stimulation and how they relate to the observed optical signal. We conclude that direct passive responses were a small component of our signal, that the component due to action potentials in directly stimulated neurons should have occurred in the first 1-2 ms post stimulus and is small compared to the peak signal, and that overall our signals were probably dominated by a combination of asynchronously occurring action potentials and excitatory and inhibitory synaptic potentials.(ABSTRACT TRUNCATED AT 400 WORDS)

A biologically plausible model of myelin plasticity demonstrates how oligodendrocytes can selectively adjust conduction delays in axon bundles to allow robust communication between brain regions through long-range synchronization.

A biologically plausible model of myelin plasticity demonstrates how oligodendrocytes can selectively adjust conduction delays in axon bundles to allow robust communication between brain regions through long-range synchronization.

A biologically plausible model of myelin plasticity demonstrates how oligodendrocytes can selectively adjust conduction delays in axon bundles to allow robust communication between brain regions through long-range synchronization.

Our goal was to develop and test a 3D bolus-tracking MR technique for perfusion imaging of normal and pathological (infarcted) human brain. All experiments were performed on standard 1.5 T GE/Signa clinical scanners. Five normal volunteers and one patient with a subacute brain infarct were studied. Modified [frequency-shifted (FS)] BURST MRI was performed during injection of a bolus of Gd-DTPA (0.13 mmol/kg) in the antecubital vein. The 3D datasets were acquired with a time resolution of 2.2 s and an effective spatial resolution of 4.3 x 4.3 x 6.4 mm. Three-dimensional maps of blood volume and bolus arrival time were determined by fitting a synthetic curve to the intensity time course on a voxel-by-voxel basis. Both relative cerebral blood volume and arrival time maps demonstrated sensitivity to regional differences in blood supply in both normal brain and in the subacute brain infarction. The transit time maps showed arrival time delays of 5-7 s within and around the infarct and confirmed the diagnosis of left middle cerebral artery occlusion. The results of the measurements on both normal and diseased human brain demonstrated the ability to acquire valuable 3D information about brain perfusion using FS BURST MRI.

The core functionality of many socio-technical systems, such as supply chains, (inter)national trade and human mobility, concern transport over large geographically-spread complex networks. The dynamical intertwining of many heterogeneous operational elements, agents and locations are oft-cited generic factors to make these systems prone to large-scale disruptions: initially localised perturbations amplify and spread over the network, leading to a complete standstill of transport. Our level of understanding of such phenomena, let alone the ability to anticipate or predict their evolution in time, remains rudimentary. We approach the problem with a prime example: railways. Analysing spreading of train delays on the network by building a physical model, supported by data, reveals that the emergence of large-scale disruptions rests on the dynamic interdependencies among multiple ‘layers’ of operational elements (resources and services). The interdependencies provide pathways for the so-called delay cascading mechanism, which gets activated when, constrained by local unavailability of on-time resources, already-delayed ones are used to operate new services. Cascading locally amplifies delays, which in turn get transported over the network to give rise to new constraints elsewhere. This mechanism is a rich addition to some well-understood ones in, e.g., epidemiological spreading, or the spreading of rumours and opinions over (contact) networks, and stimulates rethinking spreading dynamics on complex networks. Having these concepts built into the model provides it with the ability to predict the evolution of large-scale disruptions in the railways up to 30-60 minutes up front. For transport systems, our work suggests that possible alleviation of constraints as well as a modular operational approach would arrest cascading, and therefore be effective measures against large-scale disruptions.

Background and AimThe spread of the COVID-19 pandemic has led to a number of instances of large-scale panic buying. Taking the COVID-19 pandemic as an example, this paper explores the impact of panic in uncertain environments on panic buying behavior. Under certain circumstances, the spread of rumors about shortage of goods is likely to cause large-scale panic buying. This paper focuses on the study of such panic buying caused by online rumors.MethodsFirstly, based on the improved BA network, this paper constructs a directed network for public opinion communication and integrates an offline communication network to build a two-layer synchronous coupling network based on online and offline communications. Secondly, the individual decision model and the panic emotion transmission model under the uncertain environment are constructed. Netizens judge the authenticity of network information, determine their own panic degree according to the above two models, and judge whether they participate in the panic buying based on the above factors. Finally, the spread of the public opinion of goods buying under the panic state is simulated and analyzed.ResultsThe experimental results of the two-layer synchronous network that integrates offline interaction are significantly different from the results of pure online interaction, which increases the speed of public opinions spread after offline interaction and affects a wider range of groups. Under the condition of sufficient supplies, panic in local areas will not cause large-scale panic buying on the whole network. However, the results under the same parameters suggest that if there is a shortage of supplies, panic will spread quickly across the network, leading to large-scale panic buying. It is very important to ensure sufficient supply of materials at the beginning of the spread of rumors, which can reduce the number of buyers. However, if there is a shortage of goods before the panic dissipates in the later stage, there will still be a large-scale rush purchase.ConclusionThese results explain the reasons why it is difficult to stop the buying events in many areas under the COVID-19 pandemic. Under the uncertain environment, the panic caused by people’s fear of stock shortage promotes the occurrence of large-scale rush buying. Therefore, in the event of major public health events, ensuring adequate supply of materials is the top priority.

(1997). The New Wave of Dynamism: Will it Engulf the Field? Psychological Inquiry: Vol. 8, No. 2, pp. 132-135.

pulse, which was found to give a minimal amount of time for reaching the detection threshold. Loading constitutes a constant and presumably relatively small part of the time between supplying of the pulse and its arrival in the sink. The time of arrival was generally measurable to within t-0.5 min. Distance was measured from the base of the source blade to the center of the sink leaf. Velocity measured in this manner represents a minimal estimate of the velocity of the fastest moving component of the translocate (11). The time courses of mass transfer for four plants studied by steady state labeling, and for 19 plants studied by pulse labeling are compared in Figures 1 and 2. Both show the temporary inhibition of translocation reported previously (8). The relative mass transfer rate time course is compared with the time course of translocation velocity in Figure 3. The pattern of change in velocity measured after 30, 60, and 240 min of cooling conforms well with that in relative mass transfer rates observed after the same treatment times. A linear regression analysis of relative accumulation rate as a function of apparent velocity is shown in Figure 4. These data have a correlation coefficient of 0.7, indicating a strong dependence of mass transfer rate on translocation velocity. Application of Student's t test revealed that both velocity and relative mass transfer rates differed from their re

Dynamic rumor spreading of public opinion reversal on Weibo based on a two-stage SPNR model

Context:Trauma in South Asia is an increasingly significant problem, particularly in light of increasing motorization. Societal changes are resulting in alterations in the epidemiology of trauma.Aims:To assess various epidemiological parameters that influence causation of injury in the patients admitted in a major trauma center in Northern India.Settings and Design:Prospective, cross-sectional, Hospital based study from August 2008 to July 2009.Materials and Methods:A prospective study of 748 patients chosen by random assortment was carried out over a period of 1 year (August 2008 to July 2009) and following parameters were noted: Age group, sex, mode of trauma, type of injury, place where the trauma occurred and factors leading to injury. The length of stay of patients, Kampala trauma score (KTS) and mortality depending on the arrival time in emergency department was also noted.Statistical Analysis:Data analysis was performed using SPSS Version 16.Results:Overall trauma was most common in the age group 15-30 years (Mean age: 29.43 ± 16.87 years), with male constituting 85.29% of the total patients. It was observed that road side injuries were the most frequent (66.71%) site of injuries, whereas household injuries (23.66%), farm site (6.28%), work place (1.60) were the next most common modes of trauma. Mean time of presentation of injured patient was 2.53 ± 4.92 days. About 48.13% patients were admitted after more than 24 h after the injury. Two wheelers (32.09) were found to be the most common mode of injury. Maximum injuries (65.31%) occurred in the rural setting. The overall length of hospital stay ranged from 2 days to 178 days (median15.6 days). Mortality is more in patients who arrive in night (between 9 pm and 5 pm).Conclusions:We conclude that the majority of injuries are preventable and the epidemiological trends differ from that of developed countries. Therefore, preventive strategies should be made on the basis of these epidemiological trends.

We introduce a novel non-contact fluorescence diffuse optical tomography (FDOT) approach for localizing a fluorescent inclusion embedded in a scattering medium. It uses the time of flight of early photons arriving at several detector positions around the medium. It is a true and direct time-of-flight approach in that arrival times are converted to distance. The arrival time of early photons is found via a recently introduced numerical constant fraction discriminator applied to fluoresced photons time-of-flight distributions (fluorescence time pointspread functions (FTPSFs)). Time-correlated single photon counting and an ultrafast photon counting avalanche photodiode are used for measuring FTPSFs that form tomographic data sets. The FDOT localization algorithm proceeds in two steps. The first determines the angular position of the inclusion as the average, over projections, of angular detector positions with smallest arrival time. The second determines the inclusion's radial position based on relative arrival times obtained at several detector positions within each tomographic projection relatively to a reference detector position, the latter being that of shortest arrival time in the projection. The radial position found minimizes the discrepancy between relative arrival times computed for several possible inclusion positions and relative arrival times deduced from experimental data. Two methods are presented for this.