Hubble Space Telescope imaging survey of sub-mJy star-forming galaxies – I. Morphologies at z ∼ 0.2

We present the first results of our Hubble Space Telescope HST WFPC2 F814W snapshot imaging survey, targeting virtually all sub-mJy decimetric radio-selected star-forming galaxies. The radio selection at ∼1 GHz is free from extinction effects and the radio luminosities are largely unaffected by AGN contamination, making these galaxies ideal tracers of the cosmic star formation history. A subsample of four targets is presented here, selected at 1.4 GHz from the spectroscopically homogenous and complete samples of Benn et al. and Hopkins et al. The redshifts are confined to a narrow range around z ∼0.2, to avoid differential evolution, with a radio luminosity close to L ∗ where the galaxies dominate the comoving volume-averaged star formation rate. We find clearly disturbed morphologies resembling those of ultraluminous infrared galaxies, indicating that galaxy interactions may be the dominant mechanism for triggering star formation at these epochs. The morphologies are also clearly different from those of coeval quasars and radio galaxies, as found in star-forming galaxies selected at other wavelengths. This may prove challenging for models that propose direct causal links between AGN evolution and the cosmic star formation history at these epochs. The asymmetries are typically much larger than seen in the Canada–France Redshift Survey at similar redshifts, optical luminosities and H α -derived star formation rates, indicating the possible existence of an obscuration-related morphological bias in such samples.     

Assessing and Modeling the Impacts of Wetland Land Cover Changes on Water Provision and Habitat Quality Ecosystem Services

Natural Resources Research - Understanding the spatial–temporal dynamics of wetland land cover (LC) changes and their impacts on ecosystem services (ESs) is essential for wetland conservation...     

Solving land-use suitability analysis and planning problem by a hybrid meta-heuristic algorithm

The aim of Land-use Suitability Analysis and Planning Problem (LSAPP) is to identify the most suitable parcels of land for future land-uses considering several conflicting criteria. LSAPP can be modeled using a variant of a well-known combinatorial optimization problem called Quadratic Assignment Problem (QAP). In this paper, a multi-objective mathematical model is developed for LSAPP based on QAP modeling. The large-size instances of the proposed multi-objective mathematical model are difficult to solve in a reasonable CPU time using exact algorithms. So, an efficient three-phase hybrid solution procedure is proposed. In the first phase, the compensatory objectives are integrated using Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory. Then, based on the aforementioned suitability objective function and other spatial objectives and constraints, a multi-objective LSAPP is constructed. Finally, a hybrid multiple objective meta-heuristic algorithm is proposed to solve the LSAPP. The core of the proposed algorithm is based on Scatter Search while Tabu Search and Variable Neighborhood Search are also utilized. The proposed algorithm is equipped with the concepts of Pareto optimality and Veto Threshold, which improve its efficacy. The proposed algorithm is applied on a real LSAPP case study, in ‘Persian Gulf Knowledge Village’, wherein its performance is compared with a well-known evolutionary computation algorithm called Vector Evaluated Genetic Algorithm (VEGA) using comprehensive statistical analysis. A survey on time complexity of the proposed algorithm is also accomplished. The results show that MOSVNS is significantly superior to VEGA both in single and in multi-objective modes. Furthermore, analysis of time complexity of the proposed algorithm shows that it is of polynomial time and can be applied to significantly larger problems with multiple compensatory and non-compensatory objectives.     

Biofiltration of Hexane Vapor: Experimental and Neural Model Analysis

Biofiltration is a commonly practiced biological technique to remove volatile compounds from waste gas streams. From an industrial view‐point, biofilter (BF) operation should be flexible to handle temperatures and inlet load (IL) variations. A compost BF was operated at different temperatures (30–45°C) and at various inlet loading rates (ILR; 8–598 g m^?3 h^?1) under intermittent loading conditions. Complete removal of n‐hexane was observed at 30 and 35°C at ILRs up to 330 g m^?3 h^?1. Besides, 20–75% of the pollutant was removed at 40°C, corresponding to the different ILs applied to the BF. Increasing the temperature to 45°C decreased the removal efficiency (RE) significantly. A feed forward neural network was used to predict the RE of BF with temperature and ILR as the input variables. The experimental data was divided into training (2/3) and test datasets (1/3). The best structure of neural network was obtained by trial and error on the basis of the least differences between predicted and experimental values, as ascertained from their coefficient of regression (R²) values. The modeling results showed that a multilayer network with the topology 2?10?1 was able to predict BF performance effectively with R²‐value of 0.995 for the test data. The results from this study showed the predicting capability of ANNs which can be considered as an alternative for conventional knowledge‐based models.     

Modification of MCM‐41 with Anionic Surfactant: A Convenient Design for Efficient Removal of Cationic Dyes from Wastewater

The potential of MCM‐41 for the removal of cationic dyes from water solution was evaluated using sodium dodecyl sulfate (SDS) for the surface modification of this mesoporous material. Admicelle structures formed on the surface of the calcined MCM‐41 are capable of removing organic pollutants and cationic species from water environment. The structural, textural, and surface chemical characteristics of the prepared SDS‐modified MCM‐41 (SDS‐MCM‐41) were studied. The adsorption capacity of SDS‐MCM‐41 was evaluated for methylene blue (MB) as a target cationic dye. Equilibrium adsorption isotherm data were manipulated employing nonlinear regression analysis. The Langmuir, Freundlich, and Sips isotherm models were examined. The adsorption data were well fitted to both Langmuir and Sips isotherm models. The maximum adsorption capacity of SDS‐MCM‐41 for MB, based on Langmuir and Sips models, were 290.8 and 297.3 mg g^?1, respectively. Ethanol was found to be an effective solvent for partial regeneration of the adsorbent.     

A Complete Microjansky Radio Survey

The Phoenix Deep Survey is an ongoing multi-wavelength survey of a 2^° diameter field aimed at studying the properties of the sub-mJy and μJy radio population. Here, we present the latest 1.4 GHz observations of this field. The new data, reaching a 5 σ flux level of 45 μJy at the centre of a 50′ diameter field, comprise more than 700 sources with flux densities less than 1 mJy (187 of which have S_1.4 < 100 μJy). This provides one of the deepest radio (1.4 GHz) surveys currently available. The 1.4 GHz source counts are presented and show a flattening down to the 50 μJy level. At flux densities around 300 μJy there are indications that the sources detected may exhibit higher clustering than those observed at higher flux levels. This suggests that deep radio surveys could be useful for studies of large-scale structure but it also presents a warning for the representativity of sources in deep pencil-beam radio surveys. The study of the optical counterparts of the μJy population seems to indicate that the median R magnitude starts to decrease below 100 μJy. Spectroscopic classification of a sample of sources in this survey confirms the trend for an increasing fraction of star-forming galaxies over other systems down to ～ 100 μJy.     

Assessing prediction models of advance rate in tunnel boring machines—a case study in Iran

Tunnel boring machine applies in tunnel construction and in mining operation. During the last years, different methods have been introduced to analyze and assess suitable operations of digging systems presented. These methods are divided in two groups: (1) the first group is based on mathematical equations and shear strength applied on each cutter, (2) the second group is based on databanks and experimental relationship. This paper compares and analyzes two experimental methods as introduced by Barton and Norwegian Institute of Technology (NTNU) as well as using a mathematic model introduced by Colorado School of Mines and analyzed the validity scope of each of them. A case study is made in the 16-km Karaj–Tehran water supply tunnel. At the end, it is concluded that mathematical models are not suitable because they are highly dependent on the results of special laboratory tests; also, it attends less to rock mass characteristics. In jointed or nonhomogen rocks, as well as in this project with less value of laboratory data, using Barton model is more creditable. It enjoys high ability for definite measurement. Also, NTNU model attend to machine parameters and in case of availability of laboratory tests data, NTNU model is a suitable method. According to the available information and executing conditions of Karaj–Tehran water supply tunnel project including geology of area, experimental parameters, etc, the Barton method is more valid than the other methods.     

Multiple linear regression,multi-layer perceptron network and adaptive neuro-fuzzy inference system for forecasting precipitation based on large-scale climate signals

ABSTRACT

Nowadays, mathematical models are widely used to predict climate processes, but little has been done to compare the models. In this study, multiple linear regression (MLR), multi-layer perceptron (MLP) network and adaptive neuro-fuzzy inference system (ANFIS) models were compared for precipitation forecasting. The large-scale climate signals were considered as inputs to the applied models. After selecting the most effective climate indices, the effects of large-scale climate signals on the seasonal standardized precipitation index (SPI) of the Maharlu-Bakhtaran catchment, Iran, simultaneously and with a delay, was analysed using a cross-correlation function. Hence, the SPI time series was forecasted up to four time intervals using MLR, MLP and ANFIS. The results showed that most of the indices were significant with SPI of different lag times. Comparison of the SPI forecast results by MLR, MLP and ANFIS models showed better performance for the MLP network than the other two models (RMSE = 0.86, MAE = 0.74 for the first step ahead of SPI forecasting).

Editor D. Koutsoyiannis; Associate editor F. Pappenberger     

Numerical Investigation of the Optimum Location for Vertical Drains in Gravity Dams

The seepage beneath a concrete dam causes an upward force acting to the dam foundation, known as uplift. Previous literatures show that implementation of drainage wells in gravity dam foundations causes a reduction in uplift forces. The main aim of these wells is to drain excess seepage flow bypassed from the cutoff wall and to reduce the uplift force. The location of the drains in the foundation plays a key role in reducing the pressure. In the present study, effect of the location of drain pipes from the upstream face of the dam (s), space among them (n) and drain’s diameter (d) in uplift force reduction is investigated. The processes of the study have been performed by the Seep/w software based on the finite element method. Results show that the use of a drain system reduced the uplift forces developed beneath the floor of the structure. If the drain is located close to the face of the dam, it may not be effective in reducing the uplift. On the other hand, shifting it too much away from the upstream face of the dam will lead to increased total uplift. It is, therefore, desirable to find out the location of the drain such that the total uplift is optimum. Optimum location of the vertical drains is not fixed, and by increasing vertical drains distances from each other and also decreasing drain diameter, optimum location would be shifted to the downstream. For example introduction of system of pipe drains to the floor of gravity dams reduced the uplift force acting on the floor by up to 80% for d/l = 0.0004, n/l = 0.024 and s/l = 0.08. This reduction in uplift becomes up to 65% for d/l = 0.0004, n/l = 0.048 and s/l = 0.12. The best location of the drain is such that the total uplift is minimum and this is presented in both design charts and algebraic equations in this study.     

System dynamics approach for simulating water resources of an urban water system with emphasis on sustainability of groundwater

Water resources management is an important driver in social and economic development. Water shortage is one of the most critical issues threatening human welfare, public health, and ecosystems. This issue has turned into a major challenge in many river basins all around the world due to the imbalance in water supply and demand. Use of simulation models can be effective tools in providing water managers with scientifically supported decisions in dealing with complex and uncertain water resource systems. System dynamics approach serves as a management tool and may play an important role in understanding the cause–effect in water resources systems. In the present study, system dynamics approach was applied to simulate management strategies dealing with Tehran metropolitan water resources systems. In the developed model, the trend of water storage in the next 30-year period and the effectiveness of water supply strategies were simulated. The results showed that, despite the growing shortage of the water resources, optimal use of existing resources under appropriate strategies could reduce water deficit within the next 30 years.