Patterns,Entropy, and Predictability of Human Mobility and Life

Cellular phones are now offering an ubiquitous means for scientists to observe life: how people act, move and respond to external influences. They can be utilized as measurement devices of individual persons and for groups of people of the social context and the related interactions. The picture of human life that emerges shows complexity, which is manifested in such data in properties of the spatiotemporal tracks of individuals. We extract from smartphone-based data for a set of persons important locations such as “home”, “work” and so forth over fixed length time-slots covering the days in the data-set (see also [1], [2]). This set of typical places is heavy-tailed, a power-law distribution with an exponent close to −1.7. To analyze the regularities and stochastic features present, the days are classified for each person into regular, personal patterns. To this are superimposed fluctuations for each day. This randomness is measured by “life” entropy, computed both before and after finding the clustering so as to subtract the contribution of a number of patterns. The main issue that we then address is how predictable individuals are in their mobility. The patterns and entropy are reflected in the predictability of the mobility of the life both individually and on average. We explore the simple approaches to guess the location from the typical behavior, and of exploiting the transition probabilities with time from location or activity A to B. The patterns allow an enhanced predictability, at least up to a few hours into the future from the current location. Such fixed habits are most clearly visible in the working-day length.     

Psychological Resilience after Hurricane Sandy: The Influence of Individual- and Community-Level Factors on Mental Health after a Large-Scale Natural Disaster

Several individual-level factors are known to promote psychological resilience in the aftermath of disasters. Far less is known about the role of community-level factors in shaping postdisaster mental health. The purpose of this study was to explore the influence of both individual- and community-level factors on resilience after Hurricane Sandy. A representative sample of household residents (N = 418) from 293 New York City census tracts that were most heavily affected by the storm completed telephone interviews approximately 13–16 months postdisaster. Multilevel multivariable models explored the independent and interactive contributions of individual- and community-level factors to posttraumatic stress and depression symptoms. At the individual-level, having experienced or witnessed any lifetime traumatic event was significantly associated with higher depression and posttraumatic stress, whereas demographic characteristics (e.g., older age, non-Hispanic Black race) and more disaster-related stressors were significantly associated with higher posttraumatic stress only. At the community-level, living in an area with higher social capital was significantly associated with higher posttraumatic stress. Additionally, higher community economic development was associated with lower risk of depression only among participants who did not experience any disaster-related stressors. These results provide evidence that individual- and community-level resources and exposure operate in tandem to shape postdisaster resilience.     

Patterns of Human Papillomavirus Types in Multiple Infections: An Analysis in Women and Men of the High Throughput Human Papillomavirus Monitoring Study

Background

To evaluate the pattern of co-infection of human papillomavirus (HPV) types in both sexes in Sweden.

Methods

Cell samples from genital swabs, first-void urine, and genital swabs immersed in first-void urine were collected in the present cross-sectional High Throughput HPV Monitoring study. Overall, 31,717 samples from women and 9,949 from men (mean age 25) were tested for 16 HPV types using mass spectrometry. Multilevel logistic regression was used to estimate the expected number of multiple infections with specific HPV types, adjusted for age, type of sample, and accounting for correlations between HPV types due to unobserved risk factors using sample-level random effects. Bonferroni correction was used to allow for multiple comparisons (120).

Results

Observed-to-expected ratio for any multiple infections was slightly above unity in both sexes, but, for most 2-type combinations, there was no evidence of significant departure from expected numbers. HPV6/18 was found more often and HPV51/68 and 6/68 less often than expected. However, HPV68 tended to be generally underrepresented in co-infections, suggesting a sub-optimal performance of our testing method for this HPV type.

Conclusions

We found no evidence for positive or negative clustering between HPV types included in the current prophylactic vaccines and other untargeted oncogenic types, in either sex.     

Influence of Genetic Background and Tissue Types on Global DNA Methylation Patterns

Recent studies have shown a genetic influence on gene expression variation, chromatin, and DNA methylation. However, the effects of genetic background and tissue types on DNA methylation at the genome-wide level have not been characterized extensively. To study the effect of genetic background and tissue types on global DNA methylation, we performed DNA methylation analysis using the Affymetrix 500K SNP array on tumor, adjacent normal tissue, and blood DNA from 30 patients with esophageal squamous cell carcinoma (ESCC). The use of multiple tissues from 30 individuals allowed us to evaluate variation of DNA methylation states across tissues and individuals. Our results demonstrate that blood and esophageal tissues shared similar DNA methylation patterns within the same individual, suggesting an influence of genetic background on DNA methylation. Furthermore, we showed that tissue types are important contributors of DNA methylation states.     

Supersampling and Network Reconstruction of Urban Mobility

Understanding human mobility is of vital importance for urban planning, epidemiology, and many other fields that draw policies from the activities of humans in space. Despite the recent availability of large-scale data sets of GPS traces or mobile phone records capturing human mobility, typically only a subsample of the population of interest is represented, giving a possibly incomplete picture of the entire system under study. Methods to reliably extract mobility information from such reduced data and to assess their sampling biases are lacking. To that end, we analyzed a data set of millions of taxi movements in New York City. We first show that, once they are appropriately transformed, mobility patterns are highly stable over long time scales. Based on this observation, we develop a supersampling methodology to reliably extrapolate mobility records from a reduced sample based on an entropy maximization procedure, and we propose a number of network-based metrics to assess the accuracy of the predicted vehicle flows. Our approach provides a well founded way to exploit temporal patterns to save effort in recording mobility data, and opens the possibility to scale up data from limited records when information on the full system is required.     

Encoding of Natural Sounds at Multiple Spectral and Temporal Resolutions in the Human Auditory Cortex

Functional neuroimaging research provides detailed observations of the response patterns that natural sounds (e.g. human voices and speech, animal cries, environmental sounds) evoke in the human brain. The computational and representational mechanisms underlying these observations, however, remain largely unknown. Here we combine high spatial resolution (3 and 7 Tesla) functional magnetic resonance imaging (fMRI) with computational modeling to reveal how natural sounds are represented in the human brain. We compare competing models of sound representations and select the model that most accurately predicts fMRI response patterns to natural sounds. Our results show that the cortical encoding of natural sounds entails the formation of multiple representations of sound spectrograms with different degrees of spectral and temporal resolution. The cortex derives these multi-resolution representations through frequency-specific neural processing channels and through the combined analysis of the spectral and temporal modulations in the spectrogram. Furthermore, our findings suggest that a spectral-temporal resolution trade-off may govern the modulation tuning of neuronal populations throughout the auditory cortex. Specifically, our fMRI results suggest that neuronal populations in posterior/dorsal auditory regions preferably encode coarse spectral information with high temporal precision. Vice-versa, neuronal populations in anterior/ventral auditory regions preferably encode fine-grained spectral information with low temporal precision. We propose that such a multi-resolution analysis may be crucially relevant for flexible and behaviorally-relevant sound processing and may constitute one of the computational underpinnings of functional specialization in auditory cortex.     

Types of Phyllotaxis and Patterns of Their Realization

The types of phyllotaxis have been considered. The types of phyllotaxis occurring in plants allow them to keep unchanged the position of leaves on the shoot during growth, despite unequal stretching of stem in length and diameter.     

Types of Systemic Reactions of Human Hemodynamics and Hemostasis to Multiple Occupational Migrations to the Polar Circle Regions

Effects of meridional migrations in shuttle from middle latitudes to regions beyond the Polar Circle, where an expedition and the organization of work shifts were being conducted, were studied. Three main types of systemic reactions of human hemodynamics and hemostasis were established. The first type was characterized by a moderate increase in the arterial blood pressure (BP) at the beginning of the shift with its subsequent normalization; by hypocoagulemia; and by an increase in the total phospholipid content, with a significant increase in the content of lysolecithins (an adaptive type). The second type was characterized by hypertension throughout the whole shift, by hypercoagulemia with significant changes in the phospholipid spectrum, and with a pronounced increase in the lysolecithin and cardiolipin fractions (a hypertensive type). The third type was characterized by a decrease in BP and an increase in heart rate (HR), by hypocoagulemia and an asthenic state associated with sleep disorders, and a decreased mental capacity (an asthenic type).     

Resilience of the Natural Phyllosphere Microbiota of the Grapevine to Chemical and Biological Pesticides

The phyllosphere is colonized by complex microbial communities, which are adapted to the harsh habitat. Although the role and ecology of nonpathogenic microorganisms of the phyllosphere are only partially understood, leaf microbiota could have a beneficial role in plant growth and health. Pesticides and biocontrol agents are frequently applied to grapevines, but the impact on nontarget microorganisms of the phyllosphere has been marginally considered. In this study, we investigated the effect of a chemical fungicide (penconazole) and a biological control agent (Lysobacter capsici AZ78) on the leaf microbiota of the grapevine at three locations. Amplicons of the 16S rRNA gene and of the internal transcribed spacer were sequenced for bacterial and fungal identification, respectively. Pyrosequencing analysis revealed that the richness and diversity of bacterial and fungal populations were only minimally affected by the chemical and biological treatments tested, and they mainly differed according to grapevine locations. Indigenous microbial communities of the phyllosphere are adapted to environmental and biotic factors in the areas where the grapevines are grown, and they are resilient to the treatments tested. The biocontrol properties of phyllosphere communities against downy mildew differed among grapevine locations and were not affected by treatments, suggesting that biocontrol communities could be improved with agronomic practices to enrich beneficial populations in vineyards.     

Randomization Modeling to Ascertain Clustering Patterns of Human Papillomavirus Types Detected in Cervicovaginal Samples in the United States

Detection of multiple human papillomavirus (HPV) types in the genital tract is common. Associations among HPV types may impact HPV vaccination modeling and type replacement. The objectives were to determine the distribution of concurrent HPV type infections in cervicovaginal samples and examine type-specific associations. We analyzed HPV genotyping results from 32,245 cervicovaginal specimens collected from women aged 11 to 83 years in the United States from 2001 through 2011. Statistical power was enhanced by combining 6 separate studies. Expected concurrent infection frequencies from a series of permutation models, each with increasing fidelity to the real data, were compared with the observed data. Statistics were computed based on the distributional properties of the randomized data. Concurrent detection occurred more than expected with 0 or ≥3 HPV types and less than expected with 1 and 2 types. Some women bear a disproportionate burden of the HPV type prevalence. Type associations were observed that exceeded multiple hypothesis corrected significance. Multiple HPV types were detected more frequently than expected by chance and associations among particular HPV types were detected. However vaccine-targeted types were not specifically affected, supporting the expectation that current bivalent/quadrivalent HPV vaccination will not result in type replacement with other high-risk types.     

Skunkworks in the Embers of the Cedar Fire: Enhancing Resilience in the Aftermath of Disaster

A coalition of environmental activists and professionals created the San Diego Fire Recovery Network (SDFRN) while the largest wildfire in California history was still burning at the city’s edge in October 2003. Acting quickly while the citizenry questioned governmental ability to protect their rapidly growing region, SDFRN proposed to reduce fire risk in a way that altered residential knowledge practices and identity while reshaping governance relationships. While this effort stalled after governmental agencies restored public confidence through massive fire prevention initiatives, SDFRN’s efforts may not have been in vain. Retained within collective memory, SDFRN contributed to community resilience by diversifying possible responses to environmental change and uncertainty. In this way, flexible, informal learning organizations such as SDFRN may serve as “skunkworks,” seizing on disaster in order to incubate social–ecological relationships that might avert greater tragedies to come.

Resource-Use Patterns in Swidden Farming Communities: Implications for the Resilience of Cassava Diversity

Resource-use patterns, especially through exchanges among farmers, may ultimately confer resilience to the local agrobiodiversity. We investigated the use of cassava ethnovarieties by swidden farming communities in Brazil, exploring the structure of networks depicting farmers and the varieties they cultivate. The emergent nested resource-use pattern indicated that all farmers shared a core of top-ranked ethnovarieties (most common/abundant) while some farmers also cultivate rarer varieties. This pattern may result of individual preferences. Due to the current loss of interest and cultivation area for traditional agriculture, we simulated the extinction of crop fields to evaluate whether nestedness conferred robustness to cassava diversity. The diversity of ethnovarieties of cassava tended to be conserved when farmers were randomly removed from the network than when we preferentially removed farmers with more diverse crop fields. Stem cuttings of ethnovarieties are commonly exchanged among farmers, thus the extinction of ethnovarieties within crop fields could be restored. Therefore, we suggest that the interplay between the farmer’s resource-use patterns and exchange system strengthens the resilience of cassava diversity, which is an important staple resource for such communities.     

On the Use of Human Mobility Proxies for Modeling Epidemics

Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Correctly modeling and quantifying human mobility is critical for improving epidemic control, but may be hindered by data incompleteness or unavailability. Here we explore the opportunity of using proxies for individual mobility to describe commuting flows and predict the diffusion of an influenza-like-illness epidemic. We consider three European countries and the corresponding commuting networks at different resolution scales, obtained from (i) official census surveys, (ii) proxy mobility data extracted from mobile phone call records, and (iii) the radiation model calibrated with census data. Metapopulation models defined on these countries and integrating the different mobility layers are compared in terms of epidemic observables. We show that commuting networks from mobile phone data capture the empirical commuting patterns well, accounting for more than 87% of the total fluxes. The distributions of commuting fluxes per link from mobile phones and census sources are similar and highly correlated, however a systematic overestimation of commuting traffic in the mobile phone data is observed. This leads to epidemics that spread faster than on census commuting networks, once the mobile phone commuting network is considered in the epidemic model, however preserving to a high degree the order of infection of newly affected locations. Proxies'' calibration affects the arrival times'' agreement across different models, and the observed topological and traffic discrepancies among mobility sources alter the resulting epidemic invasion patterns. Results also suggest that proxies perform differently in approximating commuting patterns for disease spread at different resolution scales, with the radiation model showing higher accuracy than mobile phone data when the seed is central in the network, the opposite being observed for peripheral locations. Proxies should therefore be chosen in light of the desired accuracy for the epidemic situation under study.