Contagion processes on the static and activity driven coupling networks

The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and activity driven coupling (SADC) network model to characterize the coupling between static (strong) structure and dynamic (weak) structure. Epidemic thresholds of SIS and SIR model are studied on SADC both analytically and numerically with various coupling strategies, where the strong structure is of homogeneous or heterogeneous degree distribution. Theoretical thresholds obtained from SADC model can both recover and generalize the classical results in static and time-varying networks. It is demonstrated that weak structures can make the epidemics break out much more easily in homogeneous coupling but harder in heterogeneous coupling when keeping same average degree in SADC networks. Furthermore, we show there exists a threshold ratio of the weak structure to have substantive effects on the breakout of the epidemics. This promotes our understanding of why epidemics can still break out in some social networks even we restrict the flow of the population

Origins of 1/f noise in nanostructure inclusion polymorphous silicon films

In this article, we report that the origins of 1/f noise in pm-Si:H film resistors are inhomogeneity and defective structure. The results obtained are consistent with Hooge's formula, where the noise parameter, αH, is independent of doping ratio. The 1/f noise power spectral density and noise parameter αH are proportional to the squared value of temperature coefficient of resistance (TCR). The resistivity and TCR of pm-Si:H film resistor were obtained through linear current-voltage measurement. The 1/f noise, measured by a custom-built noise spectroscopy system, shows that the power spectral density is a function of both doping ratio and temperature

Cloud optical thickness variations during 1983-1991: Solar cycle or ENSO?

Based on a detailed analysis of the cloud data obtained by the International Satellite Cloud Climatology Project (ISCCP) in the years 1983–1991, we show that besides the reported 3% variation in global cloudiness (Svensmark and Friis-Christensen, 1997), the global mean cloud optical thickness (MCOT) also has significant variation which is out of phase with that of the global cloudiness. The combined effect of the two opposing variations may be a null effect on the cloud reflectivity. These results are consistent with the Total Ozone Mapping Spectrometer (TOMS) reflectivity measurements. The MCOT variation is further shown to be correlated with both the solar cycle and the ENSO cycle. Our present analysis cannot distinguish which of the above two provides better correlation, although independent data from the High resolution Infrared Radiation Sounder (HIRS) from 1990 to 1996 favor the solar cycle. Future data are needed to identify the true cause of these changes

Field emission from in situ-grown vertically aligned SnO2 nanowire arrays

Vertically aligned SnO2 nanowire arrays have been in situ fabricated on a silicon substrate via thermal evaporation method in the presence of a Pt catalyst. The field emission properties of the SnO2 nanowire arrays have been investigated. Low turn-on fields of 1.6 to 2.8 V/μm were obtained at anode-cathode separations of 100 to 200 μm. The current density fluctuation was lower than 5% during a 120-min stability test measured at a fixed applied electric field of 5 V/μm. The favorable field-emission performance indicates that the fabricated SnO2 nanowire arrays are promising candidates as field emitters

Assessing Accuracy with Locality-Sensitive Hashing in Multiple Source Environment

Accuracy assessment is a key issue in data quality management. Most of current studies focus on how to qualitatively analyze accuracy dimension and the analysis depends heavily on experts’ knowledge. Seldom work is given on how to automatically quantify accuracy dimension. Based on Jensen-Shannon Divergence (JSD) measure, we propose accuracy of data can be automatically quantified by comparing data with its entity’s most approximation in available context. To quickly identify most approximation in large scale data sources, Locality-Sensitive Hashing (LSH) is employed to extract most approximation at multiple levels, namely column, record and field level. Our approach can not only give each data source an objective accuracy score very quickly as long as context member is available but also avoid human’s laborious interaction. Theory and experiment show our approach performs well in achieving metadata on accuracy dimension

Exploring crowd persistent dynamism from pedestrian crossing perspective: An empirical study

Crowd studies have gained increasing relevance due to the recurring incidents of crowd crush accidents. In addressing the issue of the crowd's persistent dynamism, this paper explored the macroscopic and microscopic features of pedestrians crossing in static and dynamic contexts, employing a series of systematic experiments. Firstly, empirical evidence has confirmed the existence of crowd's persistent dynamism. Subsequently, the research delves into two aspects, qualitative and quantitative, to address the following questions:(1) Cross pedestrians tend to avoid high-density areas when crossing static crowds and particularly evade pedestrians in front to avoid deceleration, thus inducing the formation of cross-channels, a self-organization phenomenon.(2) In dynamic crowds, when pedestrian suffers spatial constrained, two patterns emerge: decelerate or detour. Research results indicate the differences in pedestrian crossing behaviors between static and dynamic crowds, such as the formation of crossing channels, backward detours, and spiral turning. However, the strategy of pedestrian crossing remains consistent: utilizing detours to overcome spatial constraints. Finally, the empirical results of this study address the final question: pedestrians detouring causes crowds' persistent collective dynamism. These findings contribute to an enhanced understanding of pedestrian dynamics in extreme conditions and provide empirical support for research on individual movement patterns and crowd behavior prediction.Comment: 31pages, 17figure

Predictive algorithm for run-in value of warp knitting based on weave matrix

To predict the run-in values of single-needle-bar warp-knitted fabrics, three-dimensional weave matrixes have been established by considering main parameters of shogging movement, take-up density and total bar number. Length of a stitch has been deduced from the parameters in weave matrixes, and a new predictive algorithm model is developed. Moreover, to validate the accuracy of the proposed predictive algorithm, 30 samples with different parameters are knitted on HKS4-EL warp-knitting machine, and the predicted run-in values and measured run-in values of the samples are compared. It can be deduced from the comparison that the predictive algorithm model can provide high prediction accuracy with a relative error of < 4.26%