Modeling the Temporal Nature of Human Behavior for Demographics Prediction

Mobile phone metadata is increasingly used for humanitarian purposes in developing countries as traditional data is scarce. Basic demographic information is however often absent from mobile phone datasets, limiting the operational impact of the datasets. For these reasons, there has been a growing interest in predicting demographic information from mobile phone metadata. Previous work focused on creating increasingly advanced features to be modeled with standard machine learning algorithms. We here instead model the raw mobile phone metadata directly using deep learning, exploiting the temporal nature of the patterns in the data. From high-level assumptions we design a data representation and convolutional network architecture for modeling patterns within a week. We then examine three strategies for aggregating patterns across weeks and show that our method reaches state-of-the-art accuracy on both age and gender prediction using only the temporal modality in mobile metadata. We finally validate our method on low activity users and evaluate the modeling assumptions.Comment: Accepted at ECML 2017. A previous version of this paper was titled 'Using Deep Learning to Predict Demographics from Mobile Phone Metadata' and was accepted at the ICLR 2016 worksho

Improving official statistics in emerging markets using machine learning and mobile phone data

Mobile phones are one of the fastest growing technologies in the developing world with global penetration rates reaching 90%. Mobile phone data, also called CDR, are generated everytime phones are used and recorded by carriers at scale. CDR have generated groundbreaking insights in public health, official statistics, and logistics. However, the fact that most phones in developing countries are prepaid means that the data lacks key information about the user, including gender and other demographic variables. This precludes numerous uses of this data in social science and development economic research. It furthermore severely prevents the development of humanitarian applications such as the use of mobile phone data to target aid towards the most vulnerable groups during crisis. We developed a framework to extract more than 1400 features from standard mobile phone data and used them to predict useful individual characteristics and group estimates. We here present a systematic cross-country study of the applicability of machine learning for dataset augmentation at low cost. We validate our framework by showing how it can be used to reliably predict gender and other information for more than half a million people in two countries. We show how standard machine learning algorithms trained on only 10,000 users are sufficient to predict individual’s gender with an accuracy ranging from 74.3 to 88.4% in a developed country and from 74.5 to 79.7% in a developing country using only metadata. This is significantly higher than previous approaches and, once calibrated, gives highly accurate estimates of gender balance in groups. Performance suffers only marginally if we reduce the training size to 5,000, but significantly decreases in a smaller training set. We finally show that our indicators capture a large range of behavioral traits using factor analysis and that the framework can be used to predict other indicators of vulnerability such as age or socio-economic status. Mobile phone data has a great potential for good and our framework allows this data to be augmented with vulnerability and other information at a fraction of the cost

Facilitating simulation development for global challenge response and anticipation in a timely way

Data availability: No data was used for the research described in the article.Copyright © 2023 The Author(s). An important subset of today’s global crises, such as the 2015 migration crisis in Syria and the 2020 COVID pandemic, has a rapid and hard-to-extrapolate evolution that complicates the preparation of a community response. Simulation-based forecasts for such crises can help to guide the selection or development of mitigation policies or inform the efficient allocation of support resources. However, the time required to develop, execute and validate these models can often be intractably long, causing many of these forecasts to only become accurate after the damage has already occurred. In this paper, we present a generic simulation development approach (or SDA) to tackle this challenge. It consists of three important phases: identifying anticipatory activities required for developing application-agnostic modelling tools, identifying activities required to adapt these models to address specific (global) challenges, and automating a large subset of the aforementioned activities using existing software tool. Here, a key aspect is to ensure that our models are reliable: this involves a range of tasks for validation, ensemble forecasting, uncertainty quantification and sensitivity analysis. To showcase the added value of a generic simulation development approach, we present and discuss two specific applications of this approach: one in the context of modelling conflict-driven migration and one in the context of modelling the spread of COVID-19.This work is supported by the ITFLOWS, HiDALGO and STAMINA projects, which have received funding from the European Union Horizon 2020 research and innovation programme under grant agreement nos 882986, 824115 and 883441. This work has also been supported by the SEAVEA ExCALIBUR project, which has received funding from EPSRC under grant agreement EP/W007711/1

The Mortality Rate in Children Aged 1-59 Months in Affiliated Healthcare Centers of Babol University of Medical Sciences Based on ICD10

Background and Objective: The mortality in children aged 1-59 months is one of the important indicators in assessing the general health status of a community. The death control system for children aged 1-59 months is used to record and review this indicator in Iran. This study was performed to investigate the mortality rate in children aged 1-59 months in affiliated healthcare centers of Babol University of Medical Sciences based on ICD10. Methods: In this cross-sectional study, all cases of death in children aged 1-59 months registered in affiliated healthcare centers of Babol University of Medical Sciences in 2009-2020 were collected by referring to the reports recorded in the death control system for children aged 1-59 months. Then, information about the cause of death and the trends of mortality during the years 2009-2020 were reviewed. Findings: Out of a total of 303 cases of death in children aged 1-59 months, 179 cases (59.07%) were boys, the mean age of children was 13.08±15.12 months and with 175 cases (57.75%), the highest mortality rate was related to urban areas. The general trend of mortality was declining; from 41 cases in 2009 to 14 cases in 2020 (p≤0.001). Congenital and chromosomal abnormalities in 100 cases (34%), endocrine, nutritional and metabolic diseases in 56 cases (18.48%), nervous system diseases in 23 cases (7.59%) and cancers in 22 cases (7.26%) were respectively the most common causes of death. Conclusion: The results show a declining trend in the mortality of children aged 1-59 months

Species composition monitoring in artificial reefs area in Khuzestan coastal waters

This study was carried out in continuation of previous studies on artificial reefs monitoring in Khozestan coastal waters. The main purpose was the zoo species composition on and around the artificial reefs. Sampling was done from May 2012 to April 2013, from 4 stations in artificial reefs area. Reef structures were sampled by scuba diving. Physical and chemical parameters were measured and water quality status was determined by using WQS index. Zooplankton and macrozooplankton communities were sampled by 100 and 300 micrometer mesh size nets respectively. Benthic animal's samples from sediments around of the reefs body were collected by Ekman grab. Sediment characters, TOM and grain size were analyzed by using ignition loss and size series sieves methods respectively. Secondary production of macrobenthic animals based on dominant species length classes was estimated. Ichthyological information recorded by diver (census and video recording) and Gargoor traps were used for fishing effort calculation .Except for nitrite parameter (p<0.05) in different stations and silica parameters (p<0.05) in different months, other parameters were not shown significant differences in studied stations and months. The mean of zooplankton density was (914±52) N/m^3 and the Copepoda species were the most abundant group (235 ±10) N/m^3.Anosim analysis showed no significant differences in reefs specie composition. Different Crustacean groups were included more than 82 percent of macrozooplanktons communities. Among macrozooplankons, the mean density of decapoda, branchiopoda and copepoda were 302, 296 and 191.5 N/m3 respectively. The mean density of macrobenthic animals was 418±90.26 N/m^2 and mollusk, crustacean and polychaets were the most abundant benthic animals respectively. During the study period, total macrobenthos biomass 11.37 g-wet/m^2 and its mean value 2.84 g -wet /m^2, were estimated. Annual production for polychaets and crustacean groups 154g-wet/m^2 and 182 g-wet/m^2 were estimated respectively. Annual production of total macrobenthic animals was about 675 g-wet/m^2/y. According to sediment analysis, the range of silt-clay (8.7-95.6)% and seasonal mean TOM (4.47-13.25)% were calculated in studied stations. According to attached organisms biomass (wet weight), Cnidarian Anthozoa class with (88)% was the most abundant and then sponge (10)%, Cnidarian Hydrozoan class and arthropoda each one with 1% were included total attached organisms. Due to high biomass of Anthozoa species the most abundant mean was observed in spring season. The Malacostraca group especially Crustacean (72)% was the main mobile animals on reef bodies and then Echinodermata (Ophiurida and marine Orchids) (18)%, Mollusca (Bivalves and Gastropods) (4)% and Polychaets (3)% were the main mobile organisms. The range of Shannon diversity index was (3.22-3.46) and (2.44-3.38) in studied stations and months respectively. Totaly in studied area, the number 15 fishes species were observed and Sparidae family with 3 species were the diverse fish family. The fish Hamour (Epinephelus coiodes,Seranidae) (87)% was presented in all studied months and stations. After Hamour the Neopomacentrue sindensis and Diplodus sargus Kotschyi were the most abundant fishes. The maximum and the minimum of hamour catch per unit effort were in reef B in spring and reef C in autumn respectively .Data comparing showed that except for nitrite the other physical and chemical parameters were observed in the same range by 2005-2007 study. According to obtained results, Zoo communities in different part of ecosystem showed greater diversity than to past years and in comparing to mudflat coastal waters in Khozestan waters, new ecosystem has been created in the region. High diversity of different animal groups that were disperses in water column in early phases of its life and need to settlement to substrate to continuing the life were observed in area. Attached animals plays an important role in biological and ecological characters in the coastal area

Directed self-assembly of a helical nanofilament liquid crystal phase for use as structural color reflectors

The fabrication of molecular structures with a desired morphology, e.g., nanotubes, nanoribbons, nanosprings, and sponges, is essential for the advancement of nanotechnology. Unfortunately, realization of this objective is expensive and complicated. Here, we report that irradiating a film comprising azobenzene derivatives with UV light produces oriented arrays of helical nanofilaments via the photoisomerization-induced Weigert effect. As a result, structural colors are observed due to the extrinsic chiral reflection in the visible wavelength range, and the reflected color can be tuned by adjusting the molecular length of the azobenzene derivative. This simple fabrication method can be used for fabricating large, reversible, and patternable color reflectors, providing a new platform for interference-based structural coloration as it exists in nature, such as morpho butterflies, green-winged teal, and various beetles

The risk factors of prostate cancer: A multicentric case-control study in Iran

Prostate cancer (PC), in Iran, is the third most frequently diagnosed visceral cancer among men and the seventh most common underlying cause of cancer mortality. We evaluated the relation between speculated factors and PC risk using data from a multicentric case-control study conducted in Iran from 2005 to 2007 on 130 cases of incident, clinicopathologically confirmed PC, and 75 controls admitted to the same network of hospitals without any malignant disease. Odds ratios(OR) and corresponding 95 confidence intervals (CIs) were estimated using conditional logistic regression models. The risk of PC was increased with aging (OR: 5.35, 95 CI: 2.17-13.19; P<0.0001), and with the number of sexual intercourse �2 times/week (OR: 3.14, 95 CI: 1.2-8.2; P=0.02). One unit elevation in serum estradiol and testosterone concentration was related to increase (OR: 1.04, 95 CI: 1.01-1.06; P=0.006) and decrease (OR: 0.79; 95 CI: 0.64-0.96; P=0.02) of PC risk, respectively. Cases were less likely to have a history of diabetes (OR: 0.34, 95 CI: 0.12-0.98; P=0.04). Increasing in dietary consumption of lycopene and fat was associated with declined (OR: 0.45, 95 CI: 0.09-2.12) and increased (OR: 2.38, 95 CI: 0.29-19.4) PC development, respectively. Other factors including educational level, marriage status, dietary meat consumption, vasectomy and smoking have not been shown to affect PC risk in the Iranian population. Ourstudy adds further information on the potential risk factors of PC and is the first epidemiologic report from Iran. However, justification of these results requires more well-designed studies with a larger number of participants

Glutamate Induces Mitochondrial Dynamic Imbalance and Autophagy Activation: Preventive Effects of Selenium

Glutamate-induced cytotoxicity is partially mediated by enhanced oxidative stress. The objectives of the present study are to determine the effects of glutamate on mitochondrial membrane potential, oxygen consumption, mitochondrial dynamics and autophagy regulating factors and to explore the protective effects of selenium against glutamate cytotoxicity in murine neuronal HT22 cells. Our results demonstrated that glutamate resulted in cell death in a dose-dependent manner and supplementation of 100 nM sodium selenite prevented the detrimental effects of glutamate on cell survival. The glutamate induced cytotoxicity was associated with mitochondrial hyperpolarization, increased ROS production and enhanced oxygen consumption. Selenium reversed these alterations. Furthermore, glutamate increased the levels of mitochondrial fission protein markers pDrp1 and Fis1 and caused increase in mitochondrial fragmentation. Selenium corrected the glutamate-caused mitochondrial dynamic imbalance and reduced the number of cells with fragmented mitochondria. Finally, glutamate activated autophagy markers Beclin 1 and LC3-II, while selenium prevented the activation. These results suggest that glutamate targets the mitochondria and selenium supplementation within physiological concentration is capable of preventing the detrimental effects of glutamate on the mitochondria. Therefore, adequate selenium supplementation may be an efficient strategy to prevent the detrimental glutamate toxicity and further studies are warranted to define the therapeutic potentials of selenium in animal disease models and in human

Ant stings in military forces on three Persian islands of Abu-Musa, Greater Tunb and Lesser Tunb

Aims: Ants with the ability of biting and injecting venom to human body are called sting ants. This study was conducted to identify and determine the ant species and the prevalence of ant sting and related epidemiological factors in three Greater Tunb, Lesser Tunb and Abu-Musa islands, Iran. Methods: This descriptive cross-sectional study was performed during Jan-July 2010 in Greater Tunb, Lesser Tunb and Abu-Musa islands on 318 military individuals who were selected by random sampling method. The ant collection was done by active hand-catch method. The ant sting prevalence and related epidemiological factors were determined by questionnaire. Data were analyzed by descriptive statistical methods including Chi-square test, Mann-Whitney test and Spearman and Gamma correlation. Results: Sting ants in these islands were identified as Pachycondyla sennaarensis (Mayr, 1862) (Hymenoptera: Formicidae). The mean prevalence of ant stings was 70.1%. The seasonal incidence of sting in three islands had the same pattern and was more common in spring and summer. 84.4% of ant stings had occurred in limbs. The main symptoms caused by the ant stings include pain, severe itching and local inflammation and blisters in some cases. Conclusion: Although ant stings in these islands is not much dangerous and does not lead to anaphylactic shock and death, ant stings prevalence is very high and the pain, itching and burning would cause discomfort for soldiers and reduce their efficiency. Therefore, preventive measures and control of these ants should be considered