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

Neurofeedback effect on perceptual-motor skills of children with ADHD

Objectives: This study investigates the impact of neurofeedback on perceptual-motor skills of 5 to 12 years old children with Attention Deficit Hyperactive Disorder (ADHD). Methods: In this clinical study, 40 children between the ages of 5-12 years, who were patients of the Tavanesh Clinic and diagnosed with ADHD, were randomly chosen and divided into two groups of control and test. 20-neurofeedback intervention sessions were performed. The tools utilized in this study included Bruninks-Oseretsky Test of Motor Proficiency and Child behavior checklist (CBCL) survey questionnaire. For evaluation after the intervention, Bruninks-Oseretsky Test of Motor Proficiency scale for children, along with CBCL questionnaire surveys were asked to fill up by the participants' mothers. Results: After the intervention, the analysis of the scores in all perceptual-motor skills showed significant differences in both groups, but no significant difference was observed in the subtest of strength. The CBCL survey questionnaire revealed that the average scores on attention disorder, aggression, lack of attention and hyperactivity, externalizing and general problems in the test group is significantly less than that of the control group. However, in the confrontational behavior (internalization), there was no statistically significant difference between the test and control groups. There was a correlation between the change of motor skills and change of behavioral patterns in ADHD children. Discussion: Neurofeedback intervention can have positive effects on improving the perceptualmotor skills of children with ADHD

The Causes of Morphological and Sedimentary Changes of Jajrood River Upstream of Latyan Dam

Studying the morphology of rivers leads to a better prediction of the rivers' behavior. Two categories of natural and human factors affect the behavior of rivers. Natural factors such as floods, soil erosion, landslides and human factors such as construction and installation of facilities, change of land use along the river and sand removal from the riverbed have an impact on the intensification of river morphological changes. In this research, it has been investigated the morphological changes of Jajrood river and its causes upstream of the dam with an approximate length of 140 km. For ease of work, the river is divided into four zones: A) mountainous and high area, B) split zone under the influence of Mosha -Fasham fault, C) transition zone between the riffle and the mountain, D) the river riffle and Latyan dam. In general, Jajrood river is morphologically steep (average slope of 4%), mountainous, braided and gravel. The torsion factor of the river is 1.06. Jajrood River is a straight river upstream, and braided and gravel downstream that particle size and sorting changes from upstream to downstream does not follow a specific trend. Tectonic activity in the Mosha Fasham fault causes the large particles to enter the river environment as the debris streams. Some erosion-sensitive geological formations, such as the shale units of the Shemshak Formation and the shale parts of the Karaj Formation in the Mosha-Fasham fault zone, under the influence of landslide processes, introduce a large sedimentary load into the river channel during heavy rainfall. In general, common forms of river canals in the region include canal bed sediments, inter Channel Islands, foothills and old alluvial terraces in the downstream areas (Lavasan). Examination of the longitudinal profile of the main part the river from the junction of Sarbandan and Shemshak tributaries downstream to the dam site showed that the middle part of this section of the river is affected by a sudden change of slope due to the Mosha Fasham fault. The changes in the bed level and the increase of the mentioned slope in the river route are due to the function of fault displacements in the region and the entry of large volumes of gravel flows from the river valley walls into the river channel flow path. In the riffle of Jajrood River, Lavasan Municipality has implemented dams to beautify and build a park for tourism that have upset the balance of the waterway. This raises the bed level upstream. Besides, river water quality has also been affected due to time delays in water flow.O estudo da morfologia dos rios permite uma melhor previsão do comportamento dos rios. Duas categorias de fatores naturais e humanos afetam o comportamento dos rios. Fatores naturais como inundações, erosão do solo, deslizamentos de terra e fatores humanos como construção e instalação de instalações, alteração do uso do solo ao longo do rio e remoção de areia do leito do rio têm impacto na intensificação das mudanças morfológicas do rio. Nesta pesquisa, foram investigadas as mudanças morfológicas do rio Jajrood e suas causas a montante da barragem com extensão aproximada de 140 km. Para facilitar o trabalho, o rio está dividido em quatro zonas: A) zona montanhosa e alta, B) zona dividida sob a influência de Mosha -Falha de Fasham, C) zona de transição entre o riffle e a montanha, D) o riffle e Barragem da Letônia. Em geral, o rio Jajrood é morfologicamente íngreme (declive médio de 4%), montanhoso, trançado e de cascalho. O fator de torção do rio é 1,06. O Rio Jajrood é um rio direto a montante, e trançado e cascalho a jusante que o tamanho das partículas e as mudanças de classificação de montante para jusante não seguem uma tendência específica. A atividade tectônica na falha de Mosha Fasham faz com que as grandes partículas entrem no ambiente do rio como o fluxo de detritos. Algumas formações geológicas sensíveis à erosão, como as unidades de xisto da Formação Shemshak e as partes de xisto da Formação Karaj na zona de falha de Mosha-Fasham, sob a influência de processos de deslizamento de terra, introduzem uma grande carga sedimentar no canal do rio durante chuva. Em geral, as formas comuns de canais de rios na região incluem sedimentos do leito do canal, ilhas do canal inter, contrafortes e antigos terraços aluviais nas áreas a jusante (Lavasan). O exame do perfil longitudinal da parte principal do rio da junção dos afluentes Sarbandan e Shemshak a jusante até o local da barragem mostrou que a parte média desta seção do rio é afetada por uma mudança repentina de declive devido à falha de Mosha Fasham. As alterações no nível do leito e o aumento da referida declividade no percurso do rio devem-se à função de deslocamentos de falhas na região e à entrada de grandes volumes de fluxos de cascalho das paredes do vale do rio para o curso de escoamento do canal do rio. No riffle do rio Jajrood, o município de Lavasan implantou represas para embelezar e construir um parque turístico que alterou o equilíbrio do curso de água. Isso aumenta o nível do leito rio acima. Além disso, a qualidade da água do rio também foi afetada devido a atrasos no fluxo de água

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

Parámetros sedimentarios y texturales de continuidad y características mineralógicas del río Jajrood, Irán

In this research, we try to study the sedimentary characteristics and the trend of textural changes in the sediments of the Jajrood River from upstream to downstream at the point of junction to Latiyan dam. Based on the textural changes of sediments along the path from the upstream in the Garmabdar area to the downstream to the Latiyan Dam, the Jajrood River is divided into four A, B, C and D basins. Twenty sediment samples were collected and all sieved by dry and wet method also the specimens were morphoscopically studied. Data from field and laboratory phases were combined and interpreted using reliable scientific sources and finally a detailed summary was obtained regarding sedimentology of the study area. Mineralogically, the sediment type of the river is a clastic carbonate sedimentary type with fragments ranging from 30 to 58 percent and rock fragments between 25 to 50 percent abundance. Other minerals, such as feldspar minerals, account for about 1 to 4 percent, quartz 5 to 10 percent, and opauqe minerals from 1 to 5 percent. Examination of the average particle size in the A to D basins shows that decreasing trend of sediment size from the A to C basin occurs and reverses in the D basin. In the first three basins, the sorting grade of the river sediments is very bad and in the last basin it has become extremely bad. The amount of kurtosis of the particle distribution curve from upstream to downstream of the river is generally increasing trend. Textural changes along the river do not follow natural conditions due to the influence of various natural factors such as the entry of distributary into the main River, and phenomena such as landslide and rock collapses and debris flows, especially during floods along the riverbank.En esta investigación, tratamos de estudiar las características sedimentarias y la tendencia de los cambios de textura en los sedimentos del río Jajrood desde aguas arriba hacia aguas abajo en el punto de unión con la presa de Latiyan. Basado en los cambios de textura de los sedimentos a lo largo del camino desde el río arriba en el área de Garmabdar hasta la presa de Latiyan, el río Jajrood se divide en cuatro cuencas A, B, C y D. Se recogieron veinte muestras de sedimentos y todas se tamizaron por método seco y húmedo, y las muestras se estudiaron morfoscópicamente. Los datos de las fases de campo y laboratorio se combinaron e interpretaron utilizando fuentes científicas confiables y finalmente se obtuvo un resumen detallado sobre la sedimentología del área de estudio. Desde el punto de vista mineralógico, el tipo de sedimento del río es un tipo sedimentario de carbonato clástico con fragmentos que van del 30 al 58 por ciento y fragmentos de roca entre el 25 y el 50 por ciento de abundancia. Otros minerales, como los minerales de feldespato, representan alrededor del 1 al 4 por ciento, los cuarzos del 5 al 10 por ciento y los minerales opacos del 1 al 5 por ciento. El examen del tamaño promedio de partícula en las cuencas A a D muestra que se produce una tendencia decreciente del tamaño del sedimento de la cuenca A a C y se invierte en la cuenca D. En las primeras tres cuencas, el grado de clasificación de los sedimentos del río es muy malo y en la última cuenca se ha vuelto extremadamente malo. La cantidad de curtosis de la curva de distribución de partículas de río arriba a río abajo es generalmente una tendencia creciente. Los cambios de textura a lo largo del río no siguen las condiciones naturales debido a la influencia de varios factores naturales, como la entrada de distribución en el río principal, y fenómenos como derrumbes y derrumbes de rocas y flujos de escombros, especialmente durante las inundaciones a lo largo de la orilla del río

Titanium dioxide nanoparticles catalyzed synthesis of Hantzsch esters and polyhydroquinoline derivatives

1,4-Dihydropyridine and polyhydroquinoline derivatives have been prepared efficiently in a one-pot synthesis via Hantzsch condensation using nanosized titanium dioxide as a heterogeneous catalyst. The present methodology offers several advantages such as excellent yields, short reaction times (30-120 min), environmentally benign, and mild reaction conditions. The catalyst can be readily separated from the reaction products and recovered in excellent purity for direct reuse

Modeling extra-deep electromagnetic logs using a deep neural network

Modern geosteering is heavily dependent on real-time interpretation of deep electromagnetic (EM) measurements. We have developed a methodology to construct a deep neural network (DNN) model trained to reproduce a full set of extra-deep EM logs consisting of 22 measurements per logging position. The model is trained in a 1D layered environment consisting of up to seven layers with different resistivity values. A commercial simulator provided by a tool vendor is used to generate a training data set. The data set size is limited because the simulator provided by the vendor is optimized for sequential execution. Therefore, we design a training data set that embraces the geologic rules and geosteering specifics supported by the forward model. We use this data set to produce an EM simulator based on a DNN without access to the proprietary information about the EM tool configuration or the original simulator source code. Despite using a relatively small training set size, the resulting DNN forward model is quite accurate for the considered examples: a multilayer synthetic case and a section of a published historical operation from the Goliat field. The observed average evaluation time of 0.15 ms per logging position makes it also suitable for future use as part of evaluation-hungry statistical and/or Monte Carlo inversion algorithms within geosteering workflows.POCTEFA 2014-2020 PIXIL (EFA362/19) MTM2016-76329-

Chemoresistance in human ovarian cancer: the role of apoptotic regulators

Ovarian cancer is among the most lethal of all malignancies in women. While chemotherapy is the preferred treatment modality, chemoresistance severely limits treatment success. Recent evidence suggests that deregulation of key pro- and anti-apoptotic pathways is a key factor in the onset and maintenance of chemoresistance. Furthermore, the discovery of novel interactions between these pathways suggests that chemoresistance may be multi-factorial. Ultimately, the decision of the cancer cell to live or die in response to a chemotherapeutic agent is a consequence of the overall apoptotic capacity of that cell. In this review, we discuss the biochemical pathways believed to promote cell survival and how they modulate chemosensitivity. We then conclude with some new research directions by which the fundamental mechanisms of chemoresistance can be elucidated

Parámetros sedimentarios y texturales de continuidad y características mineralógicas del río Jajrood, Irán

In this research, we try to study the sedimentary characteristics and the trend of textural changes in the sediments of the Jajrood River from upstream to downstream at the point of junction to Latiyan dam. Based on the textural changes of sediments along the path from the upstream in the Garmabdar area to the downstream to the Latiyan Dam, the Jajrood River is divided into four A, B, C and D basins. Twenty sediment samples were collected and all sieved by dry and wet method also the specimens were morphoscopically studied. Data from field and laboratory phases were combined and interpreted using reliable scientific sources and finally a detailed summary was obtained regarding sedimentology of the study area. Mineralogically, the sediment type of the river is a clastic carbonate sedimentary type with fragments ranging from 30 to 58 percent and rock fragments between 25 to 50 percent abundance. Other minerals, such as feldspar minerals, account for about 1 to 4 percent, quartz 5 to 10 percent, and opauqe minerals from 1 to 5 percent. Examination of the average particle size in the A to D basins shows that decreasing trend of sediment size from the A to C basin occurs and reverses in the D basin. In the first three basins, the sorting grade of the river sediments is very bad and in the last basin it has become extremely bad. The amount of kurtosis of the particle distribution curve from upstream to downstream of the river is generally increasing trend. Textural changes along the river do not follow natural conditions due to the influence of various natural factors such as the entry of distributary into the main River, and phenomena such as landslide and rock collapses and debris flows, especially during floods along the riverbank.En esta investigación, tratamos de estudiar las características sedimentarias y la tendencia de los cambios de textura en los sedimentos del río Jajrood desde aguas arriba hacia aguas abajo en el punto de unión con la presa de Latiyan. Basado en los cambios de textura de los sedimentos a lo largo del camino desde el río arriba en el área de Garmabdar hasta la presa de Latiyan, el río Jajrood se divide en cuatro cuencas A, B, C y D. Se recogieron veinte muestras de sedimentos y todas se tamizaron por método seco y húmedo, y las muestras se estudiaron morfoscópicamente. Los datos de las fases de campo y laboratorio se combinaron e interpretaron utilizando fuentes científicas confiables y finalmente se obtuvo un resumen detallado sobre la sedimentología del área de estudio. Desde el punto de vista mineralógico, el tipo de sedimento del río es un tipo sedimentario de carbonato clástico con fragmentos que van del 30 al 58 por ciento y fragmentos de roca entre el 25 y el 50 por ciento de abundancia. Otros minerales, como los minerales de feldespato, representan alrededor del 1 al 4 por ciento, los cuarzos del 5 al 10 por ciento y los minerales opacos del 1 al 5 por ciento. El examen del tamaño promedio de partícula en las cuencas A a D muestra que se produce una tendencia decreciente del tamaño del sedimento de la cuenca A a C y se invierte en la cuenca D. En las primeras tres cuencas, el grado de clasificación de los sedimentos del río es muy malo y en la última cuenca se ha vuelto extremadamente malo. La cantidad de curtosis de la curva de distribución de partículas de río arriba a río abajo es generalmente una tendencia creciente. Los cambios de textura a lo largo del río no siguen las condiciones naturales debido a la influencia de varios factores naturales, como la entrada de distribución en el río principal, y fenómenos como derrumbes y derrumbes de rocas y flujos de escombros, especialmente durante las inundaciones a lo largo de la orilla del río