Re-Identification Risk versus Data Utility for Aggregated Mobility Research Using Mobile Phone Location Data

Mobile phone location data is a newly emerging data source of great potential to support human mobility research. However, recent studies have indicated that many users can be easily re-identified based on their unique activity patterns. Privacy protection procedures will usually change the original data and cause a loss of data utility for analysis purposes. Therefore, the need for detailed data for activity analysis while avoiding potential privacy risks presents a challenge. The aim of this study is to reveal the re-identification risks from a Chinese city’s mobile users and to examine the quantitative relationship between re-identification risk and data utility for an aggregated mobility analysis. The first step is to apply two reported attack models, the top N locations and the spatio-temporal points, to evaluate the re-identification risks in Shenzhen City, a metropolis in China. A spatial generalization approach to protecting privacy is then proposed and implemented, and spatially aggregated analysis is used to assess the loss of data utility after privacy protection. The results demonstrate that the re-identification risks in Shenzhen City are clearly different from those in regions reported in Western countries, which prove the spatial heterogeneity of re-identification risks in mobile phone location data. A uniform mathematical relationship has also been found between re-identification risk (x) and data (y) utility for both attack models: y = -ax ^b+c, (a, b, c>0; 0<x<1), where the exponent b increases with the background knowledge of the attackers. The discovered mathematical relationship provides data publishers with useful guidance on choosing the right tradeoff between privacy and utility. Overall, this study contributes to a better understanding of re-identification risks and a privacy-utility tradeoff benchmark for improving privacy protection when sharing detailed trajectory data.     

Interplay between Telecommunications and Face-to-Face Interactions: A Study Using Mobile Phone Data

In this study we analyze one year of anonymized telecommunications data for over one million customers from a large European cellphone operator, and we investigate the relationship between people''s calls and their physical location. We discover that more than 90% of users who have called each other have also shared the same space (cell tower), even if they live far apart. Moreover, we find that close to 70% of users who call each other frequently (at least once per month on average) have shared the same space at the same time - an instance that we call co-location. Co-locations appear indicative of coordination calls, which occur just before face-to-face meetings. Their number is highly predictable based on the amount of calls between two users and the distance between their home locations - suggesting a new way to quantify the interplay between telecommunications and face-to-face interactions.     

Multidimensional Human Dynamics in Mobile Phone Communications

In today''s technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today''s information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.     

Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator

The advent of publishing anonymized call detail records opens the door for temporal and spatial human dynamics studies. Such studies, besides being useful for creating universal models for mobility patterns, could be also used for creating new socio-economic proxy indicators that will not rely only on the local or state institutions. In this paper, from the frequency of calls at different times of the day, in different small regional units (sub-prefectures) in Côte d''Ivoire, we infer users'' home and work sub-prefectures. This division of users enables us to analyze different mobility and calling patterns for the different regions. We then compare how those patterns correlate to the data from other sources, such as: news for particular events in the given period, census data, economic activity, poverty index, power plants and energy grid data. Our results show high correlation in many of the cases revealing the diversity of socio-economic insights that can be inferred using only mobile phone call data. The methods and the results may be particularly relevant to policy-makers engaged in poverty reduction initiatives as they can provide an affordable tool in the context of resource-constrained developing economies, such as Côte d''Ivoire''s.     

Changes in Urination According to the Sound of Running Water Using a Mobile Phone Application

ObjectiveThe sound of running water (SRW) has been effectively used for toilet training during toddlerhood. However, the effect of SRW on voiding functions in adult males with lower urinary tract symptoms (LUTS) has not been evaluated. To determine the effect of SRW on urination in male patients with LUTS, multiple voiding parameters of uroflowmetry with postvoid residual urine (PVR) were assessed according to the presence of SRW played by a mobile application.MethodsEighteen consecutive male patients with LUTS were prospectively enrolled between March and April 2014. Uroflowmetry with PVR measured by a bladder scan was randomly performed once weekly for two consecutive weeks with and without SRW in a completely sealed room after pre-checked bladder volume was scanned to be more than 150 cc. SRW was played with river water sounds amongst relaxed melodies from a smartphone mobile application.ResultsThe mean age of enrolled patients and their mean International Prostate Symptom Score (IPSS) were 58.9 ± 7.7 years (range: 46–70) and 13.1 ± 5.9, respectively. All patients had not been prescribed any medications, including alpha-blockers or anti-muscarinic agents, in the last 3 months. There was a significant increase in mean peak flow rate (PFR) with SRW in comparison to without SRW (15.7 mL/s vs. 12.3 mL/s, respectively, p = 0.0125). However, there were no differences in other uroflowmetric parameters, including PVR.ConclusionsThe study showed that SRW from a mobile phone application may be helpful in facilitating voiding functions by increasing PFR in male LUTS patients.     

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.     

Mobile Phone Radiation Alters Proliferation of Hepatocarcinoma Cells

This study investigated the effects of intermittent exposure (15 min on, 15 min off for 1, 2, 3, or 4 h, at a specific absorption rate of 2 W/kg) to enhanced data rates for global system for mobile communication evolution-modulated radiofrequency radiation (RFR) at 900- and 1,800-MHz frequencies on the viability of the Hepatocarcinoma cells (Hep G2). Hep G2 cell proliferation was measured by a colorimetric assay based on the cleavage of the tetrazolium salt WST-1 by mitochondrial dehydrogenases in viable cells. Cell injury was evaluated by analyzing the levels of lactate dehydrogenase (LDH) and glucose released from lysed cells into the culture medium. Morphological observation of the nuclei was carried out by 4′,6-diamidino-2-phenylindole (DAPI) staining using fluorescence microscopy. In addition, TUNEL assay was performed to confirm apoptotic cell death. It was observed that cell viability, correlated with the LDH and glucose levels, changed according to the frequency and duration of RFR exposure. Four-hour exposure produced more pronounced effects than the other exposure durations. 1,800-MHz RFR had a larger impact on cell viability and Hep G2 injury than the RFR at 900 MHz. Morphological observations also supported the biochemical results indicating that most of the cells showed irregular nuclei pattern determined by using the DAPI staining, as well as TUNEL assay which shows DNA damage especially in the cells after 4 h of exposure to 1,800-MHz RFR. Our results indicate that the applications of 900- and 1,800-MHz (2 W/kg) RFR cause to decrease in the proliferation of the Hep G2 cells after 4 h of exposure. Further studies will be conducted on other frequency bands of RFR and longer duration of exposure.     

Using Human Data to Develop Risk Values

One of the criticisms of industry-sponsored human subject testing of toxicants is based on the perception that it is often motivated by an attempt to raise the acceptable exposure limit for the chemical. When Reference Doses (RfDs) or Reference Concentrations (RfCs) are based upon no-effect levels from human rather than animal data, an animal-to-human uncertainty factor (usually 10) is not required, which could conceivably result in a higher safe exposure limit. There has been little in the way of study of the effect of using human vs. animal data on the development of RfDs and RfCs to lend empirical support to this argument. We have recently completed an analysis comparing RfDs and RfCs derived from human data with toxicity values for the same chemicals based on animal data. The results, published in detail elsewhere, are summarized here. We found that the use of human data did not always result in higher RfDs or RfCs. In 36% of the comparisons, human-based RfDs or RfCs were lower than the corresponding animal-based toxicity values, and were more than 3-fold lower in 23% of the comparisons. In 10 out of 43 possible comparisons (23%), insufficient experimental animal data are readily available or data are inappropriate to estimate either RfDs or RfCs. Although there are practical limitations in conducting this type of analysis, it nonetheless suggests that the use of human data does not routinely lead to higher toxicity values. Given the inherent ability of human data to reduce uncertainty regarding risks from human exposures, its use in conjunction with data gathered from experimental animals is a public health protective policy that should be encouraged.     

A Spatiotemporal Database to Track Human Scrub Typhus Using the VectorMap Application

Scrub typhus is a potentially fatal mite-borne febrile illness, primarily of the Asia-Pacific Rim. With an endemic area greater than 13 million km² and millions of people at risk, scrub typhus remains an underreported, often misdiagnosed febrile illness. A comprehensive, updatable map of the true distribution of cases has been lacking, and therefore the true risk of disease within the very large endemic area remains unknown. The purpose of this study was to establish a database and map to track human scrub typhus. An online search using PubMed and the United States Armed Forces Pest Management Board Literature Retrieval System was performed to identify articles describing human scrub typhus cases both within and outside the traditionally accepted endemic regions. Using World Health Organization guidelines, stringent criteria were used to establish diagnoses for inclusion in the database. The preliminary screening of 181 scrub typhus publications yielded 145 publications that met the case criterion, 267 case records, and 13 serosurvey records that could be georeferenced, describing 13,739 probable or confirmed human cases in 28 countries. A map service has been established within VectorMap (www.vectormap.org) to explore the role that relative location of vectors, hosts, and the pathogen play in the transmission of mite-borne scrub typhus. The online display of scrub typhus cases in VectorMap illustrates their presence and provides an up-to-date geographic distribution of proven scrub typhus cases.     

Evaluating Chlorinated Hydrocarbon Plume Behavior Using Historical Case Population Analyses

A nationwide survey of chlorinated volatile organic compound (CVOC) plumes was conducted across a spectrum of sites from diverse hydrogeologic environments and contaminant release scenarios. The goal was to evaluate significant trends in the data that relate plume behavior to site variables (e.g., source strength, mean groundwater velocity, reductive dehalogenation regime) through correlation and population analyses. Data from 65 sites (government facilities, dry cleaners, landfills) were analyzed, yielding 247 individual CVOC plumes by compound. Data analyses revealed several trends, notably correlations between plume length and maximum observed concentration (presumably reflecting the source term) and mean groundwater velocities. Reductive dehalogenation, indicated by daughter products and groundwater geochemistry, appears to exert a relatively subtle effect on plume length, apparent only after the contributions of source strength and groundwater velocity are factored out. CVOC properties (K_oc, Henry's Law constant) exert significant effects on variability in maximum observed concentrations between sites but hold little influence on plume length. Probabilistic plume modeling, entailing Monte Carlo simulation of an analytical solution for average plume behavior with parameter distributions derived from site data, was used to produce a synthetic plume set for comparison with field data. Modeling results exhibited good agreement with field data in terms of parameter sensitivity.     

Improving the Accuracy and Efficiency of Identity-by-Descent Detection in Population Data

Segments of indentity-by-descent (IBD) detected from high-density genetic data are useful for many applications, including long-range phase determination, phasing family data, imputation, IBD mapping, and heritability analysis in founder populations. We present Refined IBD, a new method for IBD segment detection. Refined IBD achieves both computational efficiency and highly accurate IBD segment reporting by searching for IBD in two steps. The first step (identification) uses the GERMLINE algorithm to find shared haplotypes exceeding a length threshold. The second step (refinement) evaluates candidate segments with a probabilistic approach to assess the evidence for IBD. Like GERMLINE, Refined IBD allows for IBD reporting on a haplotype level, which facilitates determination of multi-individual IBD and allows for haplotype-based downstream analyses. To investigate the properties of Refined IBD, we simulate SNP data from a model with recent superexponential population growth that is designed to match United Kingdom data. The simulation results show that Refined IBD achieves a better power/accuracy profile than fastIBD or GERMLINE. We find that a single run of Refined IBD achieves greater power than 10 runs of fastIBD. We also apply Refined IBD to SNP data for samples from the United Kingdom and from Northern Finland and describe the IBD sharing in these data sets. Refined IBD is powerful, highly accurate, and easy to use and is implemented in Beagle version 4.     

Calibrating Statistical Population Reconstruction Models Using Catch-Effort and Index Data

Abstract: This paper illustrates how age-at-harvest data, when combined with hunter-effort information routinely collected by state game management agencies, can be used to estimate and monitor trends in big game abundance. Twenty-four years of age-at-harvest data for black-tailed deer (Odocoileus hemionus) were analyzed to produce abundance estimates ranging from 1,281 adult females to 3,232 adult females on a 22,079-ha tree farm in Pierce County, Washington, USA. The annual natural survival probability was estimated to be 0.7293 ( = 0.0097) for this female population. The estimated abundance was highly correlated with an independent browse damage index (r = 0.8131, P < 0.001). A population reconstruction incorporating the browse index did not substantially improve the model fit but did provide an auxiliary model for predicting deer abundance. This population reconstruction illustrates a cost-effective alternative to expensive big game survey methods.     

手机支付在医院服务流程中的应用探讨

第三方手机支付平台正在打造的“未来医院计划”项目有望使患者可以在手机上完成挂号、候诊、缴费等环节,为患者就医提供便利。但与此同时,第三方手机支付平台也存在着如何克服支付主体资格不合法、支付安全无法保障以及患者隐私可能受到侵害等缺陷的难题。本文通过对第三方手机支付系统在医疗体系中应运的优缺点进行分析,旨在针对其在运作中存在的问题提出完善建议。     

Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, “Random Forest” estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America.     

Ancestral Alleles in the Human Genome Based on Population Sequencing Data

Ancestral allele information is useful for genetics studies. Previously, the identification of ancestral alleles was primarily based on sequence alignments between species. Alternative ways to identify ancestral alleles were proposed in this study based on population sequencing data. The methods described here utilized the diversity between haplotypes harboring ancestral and newly emerged alleles. Simulations showed that these methods were reliable for identifying ancestral alleles when the variants had not aged too greatly. Application to the human genome sequencing data suggested the role of indels in maintaining the GC content in the human genome. The deletion-to-insertion ratios and GC proportions were correlated depending on the sizes of insertions and deletions in the direction of increasing GC content. There were GC-biased fixations in single base-pair insertions and AT-biased fixations in single base-pair deletions in the results based on the proposed methods. In the current study, GC-biased gene conversions in nucleotide substitutions were very slight or insignificant. In the variants of several quantitative trait loci (QTLs), slight GC-biased gene conversion was observed in nucleotide substitutions. For the QTL indels, insertions were observed more often than deletions, and deletion-biased fixation was observed, providing new insights into the evolution of functional genes.     

Mobile Phone Radiation Induces Reactive Oxygen Species Production and DNA Damage in Human Spermatozoa In Vitro

Background

In recent times there has been some controversy over the impact of electromagnetic radiation on human health. The significance of mobile phone radiation on male reproduction is a key element of this debate since several studies have suggested a relationship between mobile phone use and semen quality. The potential mechanisms involved have not been established, however, human spermatozoa are known to be particularly vulnerable to oxidative stress by virtue of the abundant availability of substrates for free radical attack and the lack of cytoplasmic space to accommodate antioxidant enzymes. Moreover, the induction of oxidative stress in these cells not only perturbs their capacity for fertilization but also contributes to sperm DNA damage. The latter has, in turn, been linked with poor fertility, an increased incidence of miscarriage and morbidity in the offspring, including childhood cancer. In light of these associations, we have analyzed the influence of RF-EMR on the cell biology of human spermatozoa in vitro.

Principal Findings

Purified human spermatozoa were exposed to radio-frequency electromagnetic radiation (RF-EMR) tuned to 1.8 GHz and covering a range of specific absorption rates (SAR) from 0.4 W/kg to 27.5 W/kg. In step with increasing SAR, motility and vitality were significantly reduced after RF-EMR exposure, while the mitochondrial generation of reactive oxygen species and DNA fragmentation were significantly elevated (P<0.001). Furthermore, we also observed highly significant relationships between SAR, the oxidative DNA damage bio-marker, 8-OH-dG, and DNA fragmentation after RF-EMR exposure.

Conclusions

RF-EMR in both the power density and frequency range of mobile phones enhances mitochondrial reactive oxygen species generation by human spermatozoa, decreasing the motility and vitality of these cells while stimulating DNA base adduct formation and, ultimately DNA fragmentation. These findings have clear implications for the safety of extensive mobile phone use by males of reproductive age, potentially affecting both their fertility and the health and wellbeing of their offspring.     

Reducing Stock-Outs of Life Saving Malaria Commodities Using Mobile Phone Text-Messaging: SMS for Life Study in Kenya

Background

Health facility stock-outs of life saving malaria medicines are common across Africa. Innovative ways of addressing this problem are urgently required. We evaluated whether SMS based reporting of stocks of artemether-lumefantrine (AL) and rapid diagnostic tests (RDT) can result in reduction of stock-outs at peripheral facilities in Kenya.

Methods/Findings

All 87 public health facilities in five Kenyan districts were included in a 26 week project. Weekly facility stock counts of four AL packs and RDTs were sent via structured incentivized SMS communication process from health workers’ personal mobile phones to a web-based system accessed by district managers. The mean health facility response rate was 97% with a mean formatting error rate of 3%. Accuracy of stock count reports was 79% while accuracy of stock-out reports was 93%. District managers accessed the system 1,037 times at an average of eight times per week. The system was accessed in 82% of the study weeks. Comparing weeks 1 and 26, stock-out of one or more AL packs declined by 38 percentage-points. Total AL stock-out declined by 5 percentage-points and was eliminated by the end of the project. Stock-out declines of individual AL packs ranged from 14 to 32 percentage-points while decline in RDT stock-outs was 24 percentage-points. District managers responded to 44% of AL and 73% of RDT stock-out signals by redistributing commodities between facilities. In comparison with national trends, stock-out declines in study areas were greater, sharper and more sustained.

Conclusions

Use of simple SMS technology ensured high reporting rates of reasonably accurate, real-time facility stock data that were used by district managers to undertake corrective actions to reduce stock-outs. Future work on stock monitoring via SMS should focus on assessing response rates without use of incentives and demonstrating effectiveness of such interventions on a larger scale.     

Weather Effects on the Patterns of People's Everyday Activities: A Study Using GPS Traces of Mobile Phone Users

This study explores the effects that the weather has on people''s everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People''s daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people''s regular activity patterns, certain weather conditions affected people''s movements and activities noticeably at different times of the day. On cold days, people''s activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people''s activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM–1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people''s accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics.