Application of Bayesian Decision Networks for Groundwater Resources Management Under the Conditions of High Uncertainty and Data Scarcity

This paper presents management of groundwater resource using a Bayesian Decision Network (BDN). The Kordkooy region in North East of Iran has been selected as study area. The region has been sub-divided into three zones based on transmissivity (T) and electrical conductivity (EC) values. The BDN parameters: prior probabilities and Conditional Probability Tables - CPTs) have been identified for each of the three zones. Three groups of management scenarios have been developed based on the two decision variables including “Crop pattern” and “Domestic water demand” across the three zones of the study area: 1) status quo management for all three zones represent current conditions; 2) the effect of change in cropping pattern on management endpoints and 3) the effect of future increased domestic water demand on management endpoints. The outcomes arising from implementing each scenario have been predicted by use of the constructed BDN for each of the zones. Results reveal that probability of drawdown in groundwater levels of southern areas is relatively high compared with other zones. Groundwater withdrawal from northern and northwestern areas of the study area should be limited due to the groundwater quality problems associated with shallow groundwater of these two zones. The ability of the Bayesian Decision Network to take into account key uncertainties in natural resources and perform meaningful analysis in cases where there is not a vast amount of information and observed data available – and opportunities for enabling inputs for the analysis based partly on expert elicitation,emphasizes key advantages of this approach for groundwater management and addressing the groundwater related problems in a data-scarce area.     

Comparison of sintering behavior and piezoelectric properties of (K,Na)NbO3-based ceramics sintered in conventional and microwave furnace

In this study (1 − x) K_0.48Na_0.48Li_0.04Nb_0.96Ta_0.04O₃ − xSrTiO₃ (0.0 ≤ x ≤ 0.10) ceramics were fabricated by sintering in microwave furnace for first time as well as in conventional furnace (either via single step or two-step procedures). Sintering behavior and piezoelectric properties of sintered samples were studied and compared. It was found that two-step sintering decreases sintering temperature effectively and enhances densification compared to single step sintering. Microstructure analysis revealed that, two-step sintering suppresses grain growth and promotes densification. On the other hand, microwave sintering enhanced densification more effectively and reduced sintering time and temperature. The maximum piezoelectric constants of ceramics were measured for those sintered in microwave furnace. Piezoelectric constant of the sample containing 1 mol% SrTiO₃ which was sintered in microwave furnace was measured 310 pC N⁻¹ while by sintering in conventional furnace via single and two-step sintering it was obtained 208 and 278 pC N⁻¹, respectively.     

Analysing ‘Simple’ Image Registrations

Processes such as growth and atrophy cause changes through time that can be visible in a series of medical images, following the hypothesis that form follows function. As was hypothesised by D’Arcy Thompson more than 100 years ago, models of the changes inherent in these actions can aid understanding of the processes at work. We consider how image registration using finite-dimensional planar Lie groups (in contrast to general diffeomorphisms) can be used in this process. The deformations identified can be described as points in the Lie algebra, thus enabling processes such as evolutionary change, growth, and deformation from disease, to be described in a linear space. The choice of appropriate Lie group becomes a modelling choice and can be selected using model selection; Occam’s razor suggests that groups with the smallest number of parameters (which Thompson referred to as ‘simple transformations’) are to be preferred. We demonstrate our method on an example from Thompson of the cannon-bones of three hoofed mammals and a set of outline curves of the development of the human skull, with promising results.

     

Sodium-dodecyl-sulphate-assisted synthesis of Ni nanoparticles: electrochemical properties

Stabilized nickel nanoparticles (SNNPs) were prepared using \(\hbox {Ni(acac)}_{2}\) (\(\hbox {acac} = \hbox {acetylacetonate}\)) via a simple solvothermal method. The synthesis of the nickel nanoparticles was performed in the presence of sodium dodecyl sulphate (SDS) of different concentrations (mole ratios of SDS:\(\hbox {Ni(acac)}_{2} = 1{:}1\), 2:1 and 4:1), as the stabilizer, in order to appraise their influence on the morphology, size, dispersion, magnetic properties and electrochemical activity of the nickel nanoparticles. The synthesized products have been characterized by powder X-ray diffraction, scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectra, energy-dispersive X-ray spectroscopy, vibrating sample magnetometry and electrochemical studies. It is noteworthy that the average particles size of the SNNPs has been reduced by increasing the SDS concentration, while at high concentration (mole ratio of SDS:\(\hbox {Ni(acac)}_{2} = 4{:}1\)), the small particles tend to coalesce and create a big one. The stabilized Ni nanoparticles could be used as electrode materials for hydrogen evolution in alkaline medium. The electrochemical measurements demonstrated that the higher conductivity and lower value of faraday resistance of the as-prepared samples were when the mole ratio of SDS:\(\hbox {Ni(acac)}_{2}\) was 2:1.     

In situ synthesis of ZrB2–ZrC–SiC ultra-high-temperature nanocomposites by a sol–gel process

ABSTRACT

ZrB₂–ZrC–SiC is one of the ultra-high-temperature ceramic composites with excellent properties. In this research, high-purity ZrB₂–ZrC–SiC nanopowders were synthesised using a carbothermal reduction reaction at a relatively low temperature (1370°C) from cost-effective zirconium(IV) chloride by a sol–gel method. The effect of heat treatment temperature on the synthesis of ZrB₂–ZrC–SiC composite powder was studied. X-ray diffractometry results showed that the phases ZrB₂, β-SiC and ZrC were synthesised at 1370°C. The mean crystallite sizes for each of the phases were calculated using the Scherrer method. The specific surface area for the sample calcined at 1370°C was 81.479?m²?g^?1. SEM observation revealed that the particles had a size lower than 250?nm. Backscattered electron image and map analysis with scanning electron microscopy showed that a suitable phase homogeneity was achieved, as confirmed by energy-dispersive X-ray spectroscopy.     

Implications of Urban Form on Water Distribution Systems Performance

This paper presents the results of an investigation into the relationship between urban form and the performance of a water distribution system. The effect of new development or redevelopment on the performance of an expanded rehabilitation of the well-known Anytown water distribution system is examined to provide an insight into their interaction, which can be considered along with other aspects of renewal to achieve more sustainable urban areas. A range of urban growth rates, urban form and water efficiency strategies are studied in relation to the system’s key performance indicators of total cost, resilience and water quality. The urban forms considered in this work are compact/uniform, monocentric, polycentric and edge developments. These development patterns are representative of common development approaches widely applied in urban planning. They also correspond to future settlement patterns, based on adopting four future (socio-economic) scenarios so called Policy Reform (PR), Fortress World (FW), New Sustainability Paradigm (NSP), and Market Forces (MF) respectively. Three growth rates and two water demand efficiency levels are considered. It is concluded the rate and type of urban development has major implications for the redesign and operation of existing water infrastructure in terms of total cost, water quality and system resilience, with uniform expansion (PR) resulting in the most cost-effective system upgrade by a considerable margin. Polycentric expansion as a representative urban form for New Sustainability Paradigm is the least cost-effective if it relies on centralised water distribution system to provide service to customers. Edge expansion (MF) has both the cheapest and the most expensive expansion costs depending on location of the expansion. Monocentric urban development (FW) does not result in the most cost-effective system contrary to what has been reported in the literature. Water efficiency measures had relatively little impact on overall performance as it was balanced out with demand increase due to new growth.     

Novel mesoporous Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>/SiO<Subscript>2</Subscript>/CTAB–SiO<Subscript>2</Subscript> as an effective adsorbent for the removal of amoxicillin and tetracycline from water

The current study was carried out to investigate the efficiency of using magnetic mesoporous of cetyltrimethylammonium bromide-functionalized silica-coated magnetite for removing amoxicillin (AMX) and tetracycline (TC) from tap water, river water, and medical wastewater as real samples. The properties of the synthesized adsorbent were characterized through transmission electron microscopy (TEM), scanning electron microscopy, X-ray diffraction spectrometry, Fourier transform infrared spectroscopy, vibrating sample magnetometry, pH_pzc, and also Brunauer, Emmett, and Teller (BET) methods. The BET surface area and the average diameter of mesoporous Fe₃O₄/SiO₂/CTAB–SiO₂ in accordance with TEM were 157.8 m² g^?1 and around 55 nm, respectively. In batch tests, the adsorption parameters, including the initial concentration, contact time, pH of solution, ionic strength, and adsorbent dose, were analysed. The experimental adsorption data were modelled using different classical and recently developed models. According to the results, the maximum adsorption capacities of AMX and TC on mesoporous Fe₃O₄/SiO₂/CTAB–SiO₂ were found to be 362.66 and 220.70 mg g^?1, respectively. Also, the results indicated that AMX and TC loaded on the adsorbent could be easily desorbed with 0.1 mol L^?1 HNO₃⁺ acetonitrile (1:1, v/v) and the adsorbent showed good reusability for the adsorption of the drugs studied.     

An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination

An integrated methodology, based on Bayesian belief network (BBN) and evolutionary multi-objective optimization (EMO), is proposed for combining available evidence to help water managers evaluate implications, including costs and benefits of alternative actions, and suggest best decision pathways under uncertainty. A Bayesian belief network is a probabilistic graphical model that represents a set of variables and their probabilistic relationships, which also captures historical information about these dependencies. In complex applications where the task of defining the network could be difficult, the proposed methodology can be used in validation of the network structure and the parameters of the probabilistic relationship. Furthermore, in decision problems where it is difficult to choose appropriate combinations of interventions, the states of key variables under the full range of management options cannot be analyzed using a Bayesian belief network alone as a decision support tool. The proposed optimization method is used to deal with complexity in learning about actions and probabilities and also to perform inference. The optimization algorithm generates the state variable values which are fed into the Bayesian belief network. It is possible then to calculate the probabilities for all nodes in the network (belief propagation). Once the probabilities of all the linked nodes have been updated, the objective function values are returned to the optimization tool and the process is repeated. The proposed integrated methodology can help in dealing with uncertainties in decision making pertaining to human behavior. It also eliminates the shortcoming of Bayesian belief networks in introducing boundary constraints on probability of state values of the variables. The effectiveness of the proposed methodology is examined in optimum management of groundwater contamination risks for a well field capture zone outside Copenhagen city.