ALBERT

Description: The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) of the United Nations mentions that extreme rainfalls might increase their intensity and frequency in most mid-latitude locations and tropical regions by the end of this century, as a consequence of the rise of the average global surface temperature. Human action has given way to global warming which manifests with an increase in extreme rainfall. If these climatic conditions are added to the waterproofing that cities have been experiencing as a result of urban development, a scenario of growing concern for the managers of drainage systems is generated. The objective of drainage networks is preventing the accumulation of rainwater on the surface. Under the new conditions of climate change, these need to be modified and adapted to provide cities with the security they demand. The following article describes a method for flood control by using a rehabilitation model that connects the Storm Water Management Model (SWMM) 5 model with a genetic algorithm to find the best solutions to the flood problem. The final analysis is performed using the Pareto efficiency criteria. The innovation of this method is the inclusion of a local head loss in the drainage network, allowing the upstream flow to be retained by decreasing the downstream concentration time. These elements called hydraulic controls improve system performance and are installed in the initial part of some pipes coming out of storm tanks. As a case study, the developed method has been applied in a section of the drainage network of the city of Bogotá.

Description: In the present work, the performance of carbon nanotubes (c-CNTs) functionalized polydimethylsiloxane (PDMS) based coatings as extractive phases for in-tube solid phase microextraction (IT-SPME) coupled to Capillary LC (CapLC) has been evaluated. Carboxylic-single walled carbon nanotubes (c-SWNTs) and carboxylic-multi walled carbon nanotubes (c-MWNTs) have been immobilized on the activated surface of PDMS capillary columns. The effect of different percentages of diphenyl groups in the PDMS extractive phase has also been evaluated. The extraction capability of the capillary columns has been tested for different organic pollutants, nitrogen heterocyclic compounds and polycyclic aromatic compounds (PAHs). The results indicated that the use of the c-CNTs-PDMS capillary columns improve pyriproxyfen and mainly PAH extraction. Triazines were better extracted by unmodified TRB-35 and modified c-CNTs-PDMSTRB-5. The results showed that the extraction capability of the c-CNT capillary columns depends not only on the polarity of the analytes (as it occurs with PDMS columns) but also on the interactions that the analytes can establish with the immobilized c-CNTs on the PDMS columns. The extraction efficiency has been evaluated on the basis of the preconcentration rate that can be achieved, and, in this sense, the best c-CNTs-PDMS capillary column for each group of compounds can be proposed.

Description: A deformed exponential family is a generalization of exponential families. Since the useful classes of power law tailed distributions are described by the deformed exponential families, they are important objects in the theory of complex systems. Though the deformed exponential families are defined by deformed exponential functions, these functions do not satisfy the law of exponents in general. The deformed algebras have been introduced based on the deformed exponential functions. In this paper, after summarizing such deformed algebraic structures, it is clarified how deformed algebras work on deformed exponential families. In fact, deformed algebras cause generalization of expectations. The three kinds of expectations for random variables are introduced in this paper, and it is discussed why these generalized expectations are natural from the viewpoint of information geometry. In addition, deformed algebras cause generalization of independences. Whereas it is difficult to check the well-definedness of deformed independence in general, the κ-independence is always well-defined on κ-exponential families. This is one of advantages of κ-exponential families in complex systems. Consequently, we can well generalize the maximum likelihood method for the κ-exponential family from the viewpoint of information geometry.

Description: We consider the problem of learning a Bayesian network structure given n examples and the prior probability based on maximizing the posterior probability. We propose an algorithm that runs in O(n log n) time and that addresses continuous variables and discrete variables without assuming any class of distribution. We prove that the decision is strongly consistent, i.e., correct with probability one as n ! 1. To date, consistency has only been obtained for discrete variables for this class of problem, and many authors have attempted to prove consistency when continuous variables are present. Furthermore, we prove that the “log n” term that appears in the penalty term of the description length can be replaced by 2(1+ε) log log n to obtain strong consistency, where ε > 0 is arbitrary, which implies that the Hannan–Quinn proposition holds.

Description: Background: In 2012, a pilot health policy of contractual service relations between general practitioners and patients was implemented in China. Due to the decline in body and cognitive function, as well as the lack of family care and narrow social support networks, the demand of health services among the elderly is much higher than that among the general population. This study aims to probe into the empty nesters’ willingness-to-pay for general practitioners using a contractual service policy, investigating empty nesters’ payment levels for the service, and analyze the main factors affecting the willingness of empty-nesters’ general practitioners using contractual service supply cost. Methods: This cross-sectional study adopted a multistage stratified sampling method to survey 865, city empty nesters (six communities in three districts of one city) aged 60–85 years. A condition value method was used to infer the distribution of the willingness-to-pay; Cox’s proportional hazards regression model was used to analyze the influencing factors of willingness-to-pay. Results: More than seventy percent (76.6%) of the empty nesters in this city were willing to pay general practitioners using contract service in Chongqing. The level of willingness-to-pay for the surveyed empty nesters was 34.1 yuan per year. The median value was 22.1 yuan per year, which was below the Chongqing urban and rural cooperative medical insurance individual funding level (60 yuan per year) in 2013. Cox’s proportional hazards regression model analysis showed that the higher the education level was, the worse the self-reported health status would be, accompanied by higher family per capita income, higher satisfaction of community health service, and higher willingness-to-pay empty nesters using a contract service. Women had a higher willingness-to-pay than men. Conclusions: The willingness-to-pay for general practitioners by contractual service is high among city empty nesters in Chongqing, thus, individual financing is feasible. However, people are willing to pay less than half of the current personal financing of cooperative medical insurance of urban and rural residents. Education level, family per capita income, and self-reported health status are the main factors affecting the cost sharing intention for general practitioners using contract service supply. According to the existing situation of different empty nesters, it is important to perfect the design of general practitioners using a contractual service policy system, according to differentiated personal financing levels.

Description: Lightweighting in the transportation industry is today recognized as one of the most important strategies to improve fuel efficiency and reduce anthropogenic climate-changing, environment-damaging, and human death-causing emissions. However, the structural applications of lightweight alloys are often limited by some inherent deficiencies such as low stiffness, high wear rate and inferior strength. These properties could be effectively enhanced by the addition of stronger and stiffer reinforcements, especially nano-sized particles, into metal matrix to form composites. In most cases three common strengthening mechanisms (load-bearing effect, mismatch of coefficients of thermal expansion, and Orowan strengthening) have been considered to predict the yield strength of metal matrix nanocomposites (MMNCs). This study was aimed at developing a unified model by taking into account the matrix grain size and porosity (which is unavoidable in the materials processing such as casting and powder metallurgy) in the prediction of the yield strength of MMNCs. The Zener pinning effect of grain boundaries by the nano-sized particles has also been integrated. The model was validated using the experimental data of magnesium- and titanium-based nanocomposites containing different types of nano-sized particles (namely, Al2O3, Y2O3, and carbon nanotubes). The predicted results were observed to be in good agreement with the experimental data reported in the literature.

Description: In order to achieve process intensification for adsorption chillers and heat pumps, a new composite material was developed based on sintered aluminum fibers from a melt-extraction process and a dense layer of silico-aluminophosphate (SAPO-34) on the fiber surfaces. The SAPO-34 layer was obtained through a partial support transformation (PST) process. Preparation of a composite sample is described and its characteristic pore size distribution and heat conductivity are presented. Water adsorption data obtained under conditions of a large pressure jump are given. In the next step, preparation of the composite was scaled up to larger samples which were fixed on a small adsorption heat exchanger. Adsorption measurements on this heat exchanger element that confirm the achieved process intensification are presented. The specific cooling power for the adsorption step per volume of composite is found to exceed 500 kW/m3 under specified conditions.

Description: An ultrasonic technique, invariant to temperature changes, for a density measurement of different liquids under in situ extreme conditions is presented. The influence of geometry and material parameters of the measurement system (transducer, waveguide, matching layer) on measurement accuracy and reliability is analyzed theoretically along with experimental results. The proposed method is based on measurement of the amplitude of the ultrasonic wave, reflected from the interface of the solid/liquid medium under investigation. In order to enhance sensitivity, the use of a quarter wavelength acoustic matching layer is proposed. Therefore, the sensitivity of the measurement system increases significantly. Density measurements quite often must be performed in extreme conditions at high temperature (up to 220 °C) and high pressure. In this case, metal waveguides between piezoelectric transducer and the measured liquid are used in order to protect the conventional transducer from the influence of high temperature and to avoid depolarization. The presented ultrasonic density measurement technique is suitable for density measurement in different materials, including liquids and polymer melts in extreme conditions. A new calibration algorithm was proposed. The metrological evaluation of the measurement method was performed. The expanded measurement uncertainty Uρ = 7.4 × 10−3 g/cm3 (1%).

Description: The relationship between soil fauna and different fertilizer management practices is of growing concern. The aim of this research was to investigate the response of soil fauna to fertilization regimes, to explore the relationships among the community of soil animals, soil moisture and crop yields. The application of organic fertilizers (i.e., sheep manure or crop residues) increased crop yields and promoted the number of individuals and species of soil fauna owing to the exogenous organic matter that fertilizers provided for the survival and development of soil fauna. Furthermore, the treatments that applied sheep manure (i.e., sheep manure only or nitrogen, phosphorus, potassium and sheep manure plus) were significantly beneficial for increasing crop yields and diversity of soil fauna compared to treatments with crop residues returned (i.e., crop residues returned only or nitrogen, phosphorus, potassium and crop residues returned to the field) (p 〈 0.05) due to the response of soil fauna to diverse exogenous nutrients and the effect of soil fertility. Therefore, the finding that soil fauna abundance is significantly positively correlated with soil moisture and crop yield may mean the effects of fertilizer applications on soil animals were partly masked by the soil moisture and crop yield.

Description: Urban areas are one of the most important components of human society. Their extents have been continuously growing during the last few decades. Accurate and timely measurements of the extents of urban areas can help in analyzing population densities and urban sprawls and in studying environmental issues related to urbanization. Urban extents detected from remotely sensed data are usually a by-product of land use classification results, and their interpretation requires a full understanding of land cover types. In this study, for the first time, we mapped urban extents in the continental United States using a novel one-class classification method, i.e., positive and unlabeled learning (PUL), with multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data for the year 2010. The Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) night stable light data were used to calibrate the urban extents obtained from the one-class classification scheme. Our results demonstrated the effectiveness of the use of the PUL algorithm in mapping large-scale urban areas from coarse remote-sensing images, for the first time. The total accuracy of mapped urban areas was 92.9% and the kappa coefficient was 0.85. The use of DMSP-OLS night stable light data can significantly reduce false detection rates from bare land and cropland far from cities. Compared with traditional supervised classification methods, the one-class classification scheme can greatly reduce the effort involved in collecting training datasets, without losing predictive accuracy.