Levels of Resilience and Life Satisfaction in Those with a History of Child Sexual Abuse

The current study investigates the relationship between those with a history of child sexual abuse (CSA) and existing levels of resilience and life satisfaction. The purpose of this study is to gain a better understanding of life events and current functioning among emerging adults. Previous literature has established predictable outcomes in those with a history of CSA, including resiliency. Resilience is defined as the process of effectively negotiating, adapting to, or managing significant stress or trauma (Windle, 2010). In studying levels of resilience, Liem et al., 1997, found that about 40% of participants reported resilience despite having experienced CSA. Life satisfaction is defined as an individual’s conscious, cognitive appraisal of the quality of his or her life (Diener, Emmons, Larsen, & Griffin, 1985). The relationship between life satisfaction and resilience has yet to be examined in those with a history of CSA. However, there have been several studies examining the relationship between resilience and life satisfaction in stress; such that as life satisfaction increased, resilience to stress increased (Shi et al., 1997). Adults enrolled in a psychology course at Georgia Southern University are being recruited through the SONA system to participate in the current study. The survey consists of demographic questions, the Assessment of Previous Traumatic Events, the Connor-Davidson Resilience Scale 25 (CD-RISC-25), and the Satisfaction with Life Scale. Data collection is expected to continue until February 29, 2016. The expected outcome of the current study is that participants reporting histories of CSA and high levels of resilience will also report high levels of life satisfaction

Evaluation of Equalization Basins as Initial Treatment for Flue Gas Desulfurization Waters

Coal-fired power plants are introducing flue gas desulfurization (FGD) scrubbers to reduce sulfur dioxide and mercury emissions in order to meet air quality standards. FGD scrubber systems utilize a mixture of limestone, water, and organic acids to precipitate sulfur compounds. The resulting FGD water and associated particulates often contain constituents of concern including chlorides, inorganic elements (Hg, As, and Se), and sulfates that must be treated before discharge. Constructed wetland treatment systems, consisting of an equalization basin followed by wetland reactors, present a viable option to efficiently treat FGD waters. Equalization basins are designed to cool and homogenize FGD water and settle particulates. Specific research objectives focused on equalization basins are: 1) to characterize FGD particulates in terms of elemental and mineralogical composition; 2) to determine size and settling rates of FGD particulates; 3) to determine if Hg, As, and Se concentrations within FGD water stored in an equalization basin change with time; and 4) to determine if toxicity of FGD water within an equalization basin changes during a 24 hr hydraulic retention time. The most common FGD particle type was characterized as gypsum. Other particle types identified included fly ash and iron oxides. FGD particulates settled in an equalization basin are interpreted to have originated during coal combustion and FGD processes. The majority of FGD particulates were determined to be silt size, and settling analysis shows that 95% of these particulates settled to the bottom of a typical 2.5 m deep equalization basin within approximately 4 hrs. FGD particulates contained concentrations of Hg, As, and Se, and as particulates settled, constituents were removed from the water column. Analysis of FGD water samples indicate that aqueous concentrations of Hg and Se decreased in the pilot-scale equalization basins by 20 µg/L and 200 µg/L, respectively, during a 24 hr hydraulic retention time. Data from toxicity tests indicate that equalization basins do not decrease toxicity of FGD water to aquatic organisms. Equalization basins are necessary for initial treatment of FGD water by settling particulates, which may contain Hg, As, and Se. Additional treatment for these waters occurs in the wetland reactors

Synthesis and Characterization of β-Cyclodextrin Polymers

Cyclodextrin polymers (CDPs) are water Joluble polymers composed of either a, fl, or y cyclodextrin (CDl monomers. TI,ese commercially available polymers are synthesized ming epichlorohydrin and consist of CD monomers joined by repeating glycer;l linkers (-(CH2-CHOH-CH2-ln) with an average n value of 12-15. GPC analysis of these polymers indicate two major component peaks that have molecular weights (MW) of 2,000 (one CD/ polymer chain) and 9-10,000 (4-5 CDs/polymer chain). These polymers have been used to study the binding interactions of various fluorescence probes. It has been shown that the pyrene fluorescence lifetime increases and its emission I/III ratio decreases in the hydrophobic CD c.avity. In addition, it has been reported that pyrene exists in a more open, hydrophilic environment when bound to the CDPs than that observed with the CDs. We have used these fluorescence properties to study the binding of pyrene to our synthesized fl-CDPs with shorter linker units. We have shown that as the MW of the synthesized fl-CDPs increases (increase in length of linker units), the pyrene I/III increases and the fluorescence lifetime decreases, indicating a more hydrophilic environment. Competitive experiments involving both fl-CD and commercial fl-CDP indicate that pyrene has a strong affinity for the commercial fl-CDP despite the enhanced hydrophobic environment when complexed with fl-CD. We have calculated a K value for the 1:1 fl-CDP:pyrene complex t\u3c\u27 be 1.9 x 103 using competitive binding experiments

Accumulation of population polymorphisms in the mitonuclear genome with probable adaptive effect to extreme environments as altitude for forensic purposes

We analyzed the accumulation of population polymorphism in 2504 individuals - nuclear genomes (nDNA) of 26 populations (81 genes associated to extreme environments) and 3295 mitochondrial genomes (mtDNA) of 47 populations with the aim to found mitonuclear relationship associated an extremes environment as altitude. For that, we use an algorithm developed by us to determine the accumulation of polymorphisms by segments in the genome and thus be able to perform the multivariate analysis to found SNPs differences and similarities among populations. The results showed in Peruvian population a statistically significant mitonuclear relationship for 113/293970 nDNA SNPs in 16/81 genes. In the case of the mtDNA, we found a statistically significant mitonuclear relationship for 6/22 mtDNA positions – Gene. Additionally for the Peruvian population, the MRPP3 had the greatest polymorphism contribution with respect to other populations. Then, these nDNA and mtDNA SNPs in genetically close populations to Peru can be applied to forensic genomic phenotyping to identify groups likely adapted to extreme conditions (such as altitude) or make individualization between low and high altitude populations.Revisión por pare

PACE: Pattern Accurate Computationally Efficient Bootstrapping for Timely Discovery of Cyber-Security Concepts

Public disclosure of important security information, such as knowledge of vulnerabilities or exploits, often occurs in blogs, tweets, mailing lists, and other online sources months before proper classification into structured databases. In order to facilitate timely discovery of such knowledge, we propose a novel semi-supervised learning algorithm, PACE, for identifying and classifying relevant entities in text sources. The main contribution of this paper is an enhancement of the traditional bootstrapping method for entity extraction by employing a time-memory trade-off that simultaneously circumvents a costly corpus search while strengthening pattern nomination, which should increase accuracy. An implementation in the cyber-security domain is discussed as well as challenges to Natural Language Processing imposed by the security domain.Comment: 6 pages, 3 figures, ieeeTran conference. International Conference on Machine Learning and Applications 201

Simulating interacting multiple natural-hazard events for lifecycle consequence analysis

Among different types of natural-hazard interactions (simply multi-hazard interactions hereinafter), some occur through the nature of the hazards themselves, regardless of the presence of any physical assets: they are often called ﾓLevel Iﾔ (or occurrence) interactions. In such cases, one hazard event triggers or modifies the occurrence of another (e.g., severe wind and flooding; liquefaction and landslides triggered by an earthquake), thus creating a dependency between the parameters characterising such hazard events. They differ from ﾓLevel IIﾔ (or consequence) interactions, which instead occur through impacts/consequences on physical assets/components and systems (e.g., accumulation of physical damage or social impact due to earthquake sequences, landslides due to the earthquake-induced collapse of a retaining structure). Multi-hazard Life Cycle Analysis (LCA) aims to quantify the consequences (e.g., repair costs, downtime, and casualty rates) expected throughout a systemﾒs service life, accounting for both Level I and Level II interactions. Nevertheless, the available literature generally considers these interactions mainly defining relevant taxonomies, often qualitatively, without providing a computational framework to simulate a sequence of hazard events in terms of their occurrence times and features and resulting consequences. This paper aims to partly fill this gap by identifying modelling approaches associated with different Level I interactions. It describes a simulation-based approach for generating multi-hazard scenarios (i.e., a sequence of hazard events and associated features through the systemﾒs life cycle) based on the theory of competing Poisson processes. The proposed approach incorporates the different types of interactions in a sequential Monte Carlo sampling method. The method outputs potential sequences of events throughout a systemﾒs life cycle, which can be integrated into LCA frameworks to quantify interacting hazard consequences. A simple application is presented to illustrate the potential of the proposed method.