The role of social capital,personal networks,and emergency responders in post-disaster recovery and resilience: a study of rural communities in Indiana

The factors that explain the speed of recovery after disaster remain contested. While many have argued that physical infrastructure, social capital, and disaster damage influence the arc of recovery, empirical studies that test these various factors within a unified modeling framework are few. We conducted a mail survey to collect data on household recovery in four small towns in southern Indiana that were hit by deadly tornadoes in March 2012. The recovery effort is ongoing; while many of the homes, businesses, and community facilities were rebuilt in 2013, some are still under construction. We investigate how households in these communities are recovering from damage that they experienced and the role of social capital, personal networks, and assistance from emergency responders on the overall recovery experience. We used an ordered probit modeling framework to test the combined as well as relative effects of (a) damage to physical infrastructures (houses, vehicles, etc.); (b) recovery assistance from emergency responders (FEMA) as well as friends and neighbors; (c) personal network characteristics (size, network density, proximity, length of relationship); (d) social capital (civic engagement, contact with neighbors, trust); and (e) household characteristics. Results show that while households with higher levels of damage experienced slower recovery, those with recovery assistance from neighbors, stronger personal networks, and higher levels of social capital experienced faster recovery. The insights gained in this study will enable emergency managers and disaster response personnel to implement targeted strategies in facilitating post-disaster recovery and community resilience.     

An interacting new holographic dark energy in the framework of fractal cosmology

In this paper, we study an interacting holographic dark energy model in the framework of fractal cosmology. The features of fractal cosmology could pass ultraviolet divergencies and also make a better understanding of the universe in different dimensions. We discuss a fractal FRW universe filled with the dark energy and cold dark matter interacting with each other. It is observed that the Hubble parameter embraces the recent observational range while the deceleration parameter demonstrates an accelerating universe and a behavior similar to \(\Lambda \mbox{CDM}\). Plotting the equation of state shows that it lies in phantom region for interaction mode. We use \(\mathit{Om}\)-diagnostic tool and it shows a phantom behavior of dark energy which is a condition of avoiding the formation of black holes. Finally we execute the StateFinder diagnostic pair and all the trajectories for interacting and non-interacting state of the model meet the fixed point \(\Lambda \mbox{CDM}\) at the start of the evolution. A behavior similar to Chaplygin gas also can be observed in statefinder plane. We find that new holographic dark energy model (NHDE) in fractal cosmology expressed the consistent behavior with recent observational data and can be considered as a model to avoid the formation of black holes in comparison with the main model of NHDE in the simple FRW universe. It has also been observed that for the interaction term varying with matter density, the model generates asymptotic de-Sitter solution. However, if the interaction term varies with energy density, then the model shows Big-Rip singularity. Using our modified CAMB code, we observed that the interacting model suppresses the CMB spectrum at low multipoles \(l<50\) and enhances the acoustic peaks. Based on the observational data sets used in this paper and using Metropolis-Hastings method of MCMC numerical calculation, it seems that the best value with \(1\sigma \) and \(2\sigma \) confidence interval are \(\Omega _{m0}=0.278^{+0.008~+0.010} _{-0.007~-0.009}\), \(H_{0}=69.9^{+0.95~+1.57}_{-0.95~-1.57}\), \(r_{c}=0.08^{+0.02~+0.027}_{-0.002~-0.0027}\), \(\beta =0.496^{+0.005~+0.009} _{-0.005~-0.009}\), \(c= 0.691^{+0.024~+0.039}_{-0.025~-0.037}\) and \(b^{2}=0.035\) according to which we find that the proposed model in the presence of interaction is compatible with the recent observational data.     

Response surface methodology approach to the optimization of oil hydrocarbon polluted soil remediation using enhanced soil washing

One of the environmental concerns in recent decades is the prevalence of different pollutants in soil. Hence, the importance of remediation has led to the development of various methods to remediate polluted soil. Among these methods, soil washing has gained significant attention to treat polluted soils. In this paper, the response surface methodology was applied in order to determine the optimal conditions for total petroleum hydrocarbon remediation using nonionic surfactant Brij35 in soil environment. The effect of different factors in soil washing process including surfactant solution concentration and volume, washing time, age of pollution and frequency of washing are evaluated. The predicted values for total petroleum hydrocarbon remediation efficiency by the response functions are in a very close agreement with experimental data (R-2= 98.75 %). The second order model was developed as experimented response and optimal conditions were obtained by analyzing the contour and surface plots and also by solving the regression equation using LINGO 9.0 software. The optimal concentrations (8 g/L), volume of surfactant solution (500 mL), washing time (75 min), age of pollution (29 days) and frequency of washing (three times) are determined. In this optimal condition, the removal efficiency has been observed to be 93.54 % which conforms to the results of process optimization using response surface methodology. Based on the results, it can be concluded that the response surface methodology is a suitable approach to determine the optimal conditions of soil washing to remediate organic hydrophobic pollutants using the nonionic surfactant Brij35 from the soil.     

Response Surface Optimization of Acid Red 119 Dye Adsorption by Mixtures of Dried Sewage Sludge and Sewage Sludge Ash

The mixtures of dried sewage sludge (DSS) and sewage sludge ash were studied for removal of acid red 119 (AR119) dye as a new, more environmental friendly, and low cost adsorbent. For this purpose, response surface methodology was applied to optimize the dye removal efficiency and turbidity of treated dye solutions as two individual responses. Results revealed that an optimum condition under specified constraints (dye removal efficiency >95% and turbidity <50 NTU) was obtained at a contact time of 60 min, 40 wt% DSS in the mixture, an initial pH of 6, and an initial dye concentration of 200 mg dye/L in distilled water. Under the optimal condition, dye removal efficiency of 94.98% and effluent turbidity of 24.9 NTU was observed. In further studies, at optimum condition, the effect of some additives on adsorption process and desorption/reusability of adsorbent was investigated. It was observed that removal efficiency was significantly decreased to 83.76% when a simulated dye wastewater (containing the selected dye, acetic acid, and Glauber's salt dissolved in tap water) was used. Desorption studies revealed that AR119 dye could be well removed from dye‐loaded adsorbent by 0.3 M NaOH solution.     

A new holographic dark energy model in Brans-Dicke theory with logarithmic scalar field

We study a holographic dark energy model in the framework of Brans-Dicke (BD) theory with taking into account the interaction between dark matter and holographic dark energy. We use the recent observational data sets, namely SN Ia compressed Joint Light-Analysis (cJLA) compilation, Baryon Acoustic Oscillations (BAO) from BOSS DR12 and the Cosmic Microwave Background (CMB) of Planck 2015. After calculating the evolution of the equation of state as well as the deceleration parameters, we find that with a logarithmic form for the BD scalar field the phantom crossing can be achieved in the late time of cosmic evolution. Unlike the conventional theory of holographic dark energy in standard cosmology (\(\omega_{D}=0\)), our model results in a late time accelerated expansion. It is also shown that the cosmic coincidence problem may be resolved in the proposed model. We execute the statefinder and Om diagnostic tools and demonstrate that interaction term does not play a significant role. Based on the observational data sets used in this paper it seems that the best value with \(1\sigma \) and \(2\sigma \) confidence interval are \(\varOmega_{m}=0.268^{+0.008~+0.010}_{-0.007~-0.009}\), \(\alpha =3.361^{+0.332~+0.483} _{-0.401~-0.522}\), \(\beta =5.560^{+0.541~+0.780}_{-0.510~-0.729}\), \(c=0.777^{+0.023~+0.029}_{-0.017~-0.023}\) and \(b^{2} =0.045\), according to which we find that the proposed model in the presence of interaction is compatible with the recent observational data.