Conceptualization and Development of a Dam Break Life-Loss Estimation Model

Catastrophic events such as dam failures or severe floods are considered to be of low probability, although their consequences can be extremely high and might include loss of life. Earlier studies have linked circumstances surrounding historical darn failure events to actual loss of life and produced formulations using statistical analysis of these events. Shortcomings of these methods include the inability to adjust life-loss estimates based on the type of darn failure, global averaging of population at risk, and ignoring the dynamics of the evacuation process. The main objective of this research is to develop a practical and improved life-loss estimation approach for use in dam safety risk assessment and emergency planning. The methodology is specifically formulated to overcome the limitations of previous. purely empirical, approaches. The approach takes into account the spatial and temporal distribution of flood water depth and velocity, fate of buildings, simulation of warning diffusion, and tracking the movement of people from their original location towards safe shelters. The model created, called LlFESim, is designed to serve multiple function s. First, it can be used in a Deterministic Mode using best estimate inputs to obtain point estimates, or to test different policies for evacuation as well as different times of the day and for different dam breach flooding scenarios. Second, the Uncertainty Mode represents input and parameter uncertainties to provide estimates of life loss, and other variables relating to warning and evacuation effectiveness, as probability distributions. These distributions of life loss can be combined with estimates of the uncertainties in other risk assessment inputs, to obtain estimates of uncertainties in risk assessment results, including evaluations against tolerable risk guidelines. Two communities were used to demonstrate the model performance. Deterministic Mode results display the various possible model outputs. Sensitivity analysis for the Deterministic Mode shows that the effect of warning issuance time is the dominant factor in the estimated life loss. However, other factors play an important role such as the time of day, effectiveness of the warning system, and shelter location. Uncertainty Mode results demonstrate the effect of uncertainties in model parameters and inputs on the model results

Stability of Nucleic Acid Secondary Structures and Their Contribution to Gene Expression

Bacteriorhodopsin (bR) is a highly expressed transmembrane protein that acts as a light-driven proton pump converting light energy into a proton gradient. The extraordinary levels of expression achieved (15-30 mg per liter of culture) are a result of very efficient biogenesis that originates from molecular information encoded in the bacterio-opsin gene {bop) (1). DNA sequence analysis and predictive folding algorithms suggest that the first twenty-five bases of the bop gene mRNA can form a secondary structural element (a stem-loop ). Using biophysical methods, the goal was to determine if the stem-loop structure exists in solution conditions that mimic the in vivo biological environment (42°C and 4M KCl) (2-4). The salt-dependent thermal stability of a DNA model of the stem-loop sequence was obtained using temperature-controlled UVabsorption and Circular Dichroism (CD) spectroscopy and Differential Scanning Calorimetry (DSC). The combinatorial analysis indicates that an energetically favorable stem-loop structure forms in all solution conditions examined. The stem-loop structure is stabilized at very high salt concentrations, a requirement for a role in bop gene expressivity (AG= -1.13 kcal/mol, AH= -16.78 kcal/mol, AS= - 49.67 cal/mol/K). While the Tm values evaluated by all three physical techniques were comparable, comparison of the calorimetrie and van\u27t Hoff enthalpies indicate that the folding mechanism is not a two-state process. SVD analysis of the UV and CD spectral transitions confirm that formation of the stem-loop structure proceeds through a single significant folding intermediate. Similar analysis of the RNA sequence demonstrates that an RNA stem- loop structure can form and is significantly more stable than that of the DNA structure at all salt concentrations evaluated

Economic & social determinants of CO₂ emission trends

2021 Spring.Includes bibliographical references.The increase in the concentration of carbon dioxide caused by human activity is a major cause of climate change, which is the most prominent international environmental problem in recent decades. This research aims to study the relationship between economic growth and CO2 emissions resulting from production-related fossil fuel burning, under the assumptions of the Environmental Kuznets Curve (EKC), with an emphasis on the impact of underlying variables which may affect CO2 emissions through the "technique" variables (structure and technology). From our survey of the literature, we extract the general trends of the CO2 EKC hypothesis, studies which mostly follow the traditional method of the standard regression model (with emissions as a quadratic function of GDP per capita). Many of those studies confirm the EKC hypothesis but find that the critical value, or turning point, is at a relatively high level of GDP. Generally speaking, those findings were confirmed in all three levels of our analysis. In our Level 1 analysis, we develop a standard EKC regression model as a benchmark, using a panel data sample. The results confirm the EKC hypothesis, where CO2 emissions have a positive relationship to the level of income before the EKC threshold and then a negative relationship beyond the threshold (at a relatively high level of GDP). Then a subsample analysis, on the basis of education quality, transparency, regulatory effort, and democracy, suggests that underlying variables may have a beneficial effect on emissions efficiency; on the other hand, the trade openness subsample analysis may indicate a detrimental effect on emissions efficiency, iii though further study is needed to determine the effect of the scale factor and the technique factor that may tend to induce or inhibit the down-turning of the CO2 EKC. In our Level 2 analysis we break out the technique factor (structural and technological) from the scale factor and the result confirms the EKC hypothesis and supports the idea that a downturn is due to improved technology or emissions efficiency. The analysis contains additional information about the role of structural change in explaining the EKC. When countries become affluent, they start to demand proportionally more services, decreasing the pollution intensity of production, though with the possibility of two-way causality between industrial share and income. The Level 3 analysis isolates the impact of each underlying variable on its own, ceteris paribus, to investigate which variables may tend to encourage or inhibit the down turning of the CO2 EKC through the technique factor; the results confirm the EKC hypothesis. Moreover, we find that some underlying variables (Education, Trade Openness, and Regulatory Effort) affect the relationship between carbon dioxide emissions and income with beneficial impact on the emissions efficiency of production; others (Transparency and Democracy) may not have the same effect on emissions efficiency, while evidence is insufficient to confirm a negative impact of global free riding ability. By comparing the effects of the underlying variables both in terms of GDP elasticity effects on emissions and of the turning points, in both Levels 1 and 3, we find that Education and Regulatory Effort affect the income-emissions relationship with a beneficial impact on emissions. For Trade Openness, there is a detrimental impact but the net beneficial effect of high openness compared to low openness suggests a benefit from the composition effect relative to any scale effect; openness lessens the negative impact of affluence. Regarding Democracy and Transparency, there is a contradiction in the conclusions between Level 1 and 3, and results also contradict our expectation, which leads us to not draw any strong implications overall

Discriminant analysis for the prediction and classification of tick-borne infections in some dairy cattle herds at Dakahlia Governorate, Egypt

This study was undertaken to use the variable loadings in linear discriminant analysis (LDA) to determine the most important predictors for the discrimination of tick-borne diseases (TBDs), particularly babesiosis and anaplasmosis and predict the group membership from the predictors. In total, 163 cattle, from different localities at Dakahlia Governorate, Egypt, were investigated in 2012 and 2013 for the presence of TBDs. All cattle were clinically examined and a clinical index score was determined for each cow. Blood samples were also collected from each animal for adopting microscopy and diagnostic laboratory methods. Out of the examined cattle, 83 animals were acutely-ill (Babesia bovis and Anaplasma marginale were identified in 11 and 10 animals, respectively), while 80 cows were apparently healthy but having previous attacks of blood parasites (23 animals harbored anaplasma marginale (asymptomatic carriers)). The remained 119 animals were negative to TBDs. Fourteen animals were not survived and 149 cases were survived. As the result of the first LDA to discriminate babesiosis, anaplasmosis and negative to TBDs, 89.0% of animals were correctly classified; 78.8% (26/33) for anaplasma, 100% (11/11) for babesia infections, 90.8% (108/119) for negative to TBDs, respectively. The important predictors for the discrimination were oculonasal discharge, bloody feces, hemoglobinuria, bloody feces and respiratory rate. On the other hand, the second LDA discrimination showed high classification accuracy of 87.1% for the discrimination of survivors and non-survivors; 89.9% (134/149) for survivors and 57.1% (8/14) for non-survivors, while the important predictors included oculonasal discharge, recumbent posture and nervous sign

Shape Memory Alloy Reinforced Concrete Frames Vulnerable to Strong Vertical Excitations

Reinforced concrete (RC) framed buildings dissipate the seismic energy through yielding of the reinforcing bars. This yielding jeopardizes the serviceability of these buildings as it results in residual lateral deformations. Superelastic shape memory alloys (SMAs) can recover inelastic strains by stress removal. This paper extends previous research by the authors that optimized the use of SMA bars in RC frames considering the horizontal seismic excitation by addressing the effect of the vertical seismic excitation. A steel RC six-storey building designed according to current seismic standards is considered as case study. Five different earthquake records with strong vertical components are selected for the nonlinear dynamic analysis. The results were used to evaluate the effect of the vertical excitation on the optimum locations of SMA bars

Prediction of local seismic damage in steel moment resisting frames

Steel moment resisting frames (SMRFs) are widely utilized as a lateral load resisting system. Their seismic performance is usually assessed by examining the maximum value of inter-storey drift (MID) of all floors. The accuracy of such assessment is debatable given the wide spread of values of MID at collapse that exist in the literature. In this study, a simplified method to define the failure inter-storey drift for each floor of a SMRF is proposed. The method was validated with the experimental and analytical studies by other researchers. Three- and ten-storey SMRFs were considered to further validate the proposed method. The effects of the vertical and/or horizontal seismic components of five different ground motions on the SMRFs were evaluated using incremental dynamic analysis. The proposed method accurately identified the severely damaged floors of SMRFs

Seismic performance of modular steel frames equipped with shape memory alloy braces

The demand for modular steel buildings (MSBs) has increased because of the improved quality, fast on-site installation, and lower cost of construction. Steel braced frames are usually utilized to form the lateral load resisting system of MSBs. During earthquakes, the seismic energy is dissipated through yielding of the components of the braced frames, which results in residual drifts. Excessive residual drifts complicate the repair of damaged structures or render them irreparable. Researchers have investigated the use of superelastic shape memory alloys (SMAs) in steel structures to reduce the seismic residual deformations. This study explores the potential of using SMA braces to improve the seismic performance of typical modular steel braced frames. The study utilizes incremental dynamic analysis to judge on the benefits of using such a system. It is observed that utilizing superelastic SMA braces at strategic locations can significantly reduce the inter-storey residual drifts

STR-852: PERFORMANCE ASSESSMENT OF THREE-STORY SHAPE MEMORY ALLOY REINFORCED CONCRETE WALLS

The need for sustainable structures, that provide adequate ductility without experiencing major damage, has led researchers to develop methods to achieve self-centering structures. One of these methods involves the use of superelastic Shape Memory Alloy (SMA) bars. This study assesses the seismic performance of a three-story SMA Reinforced Concrete (RC) shear wall considering different potential locations for the SMA bars. The maximum inter-story drift, residual drift, and damage scheme are evaluated using Incremental Dynamic Analysis (IDA). The use of SMA bars at the plastic hinge of the first floor was found to significantly reduce the residual drifts and associated damage

Seismic fragility assessment of superelastic shape memory alloy reinforced concrete shear walls

Mitigation of seismic damage can be achieved through self-centering techniques. One of the potential techniques involves the use of Superelastic Shape Memory Alloy (SE-SMA) bars in Reinforced Concrete (RC) structures. This study explores the use of such bars in the plastic-hinge regions of RC walls. The seismic performance and vulnerability of SE‑SMA RC walls of ten- and twenty-story buildings are analytically assessed using fragility curves. The maximum inter-story drift, residual drift, and fragility are evaluated using multi strip analysis. The results clearly demonstrate the superior seismic performance of SE-SMA RC walls as compared to steel RC walls