Mental Health Outcomes, Parenting Skills and Family Functioning of Adult and Family Treatment Court Participants

Background: Parental substance use places children at risk for poor social, emotional, and behavioral outcomes. Many parents with substance use disorders (SUD) are treated through accountability drug courts including adult drug courts (ADC) through the criminal justice system and family drug treatment courts (FTC) through the child welfare system. Little is known about the children of parents who participate in treatment through adult drug courts, which could serve as an important treatment venue for improving child outcomes. Children treated through family treatment courts are often the center of treatment. This research compared outcomes of parents and children involved in adult drug and family treatment courts. Methods: Participants were 105 drug court clients (80 from ADC; 25 from FTC) from four Georgia based drug courts. Participants completed computerized interviews containing a variety of measures focusing on adult mental health, parenting behaviors and communication, and child mental health and behavior. Results: Parents in FTC compared to those in ADC reported greater social support (p =.05) and better family functioning (p =.03). Parents in ADC reported poorer parental involvement and poorer monitoring of children than FTC, but no differences in positive parenting (p =.13), inconsistent discipline (p =.27), or child abuse potential (total risk \u3e 9, p =.42; total risk \u3e12, p =.37). Regarding mental health, ADC parents reported a greater number of symptoms or poor mental health than FTC. No differences were found for parent-child communication skills (p =.38), post-traumatic stress symptom severity (p =.62), or child behavior problems. Conclusions: This data suggests that children of caregivers in drug treatment via ADC are at equal and perhaps greater risk than children of caregivers in FTC because of increased parental risk factors. ADC should consider offering family -based treatments that can enhance the parent-child relationship and promote recovery by reducing family conflict

Structural Test and Analysis of a Hybrid Inflatable Antenna

NASA is developing ultra-lightweight structures technology for communication antennas for space missions. One of the research goals is to evaluate the structural characteristics of inflatable and rigidizable antennas through test and analysis. Being able to test and analyze the structural characteristics of a full scale antenna is important to enable the simulation of various mission scenarios to determine system performance in space. Recent work completed to evaluate a Hybrid Inflatable Antenna concept will be discussed. Tests were completed on a 2-m prototype to optimize its static shape and identify its modal dynamics that are important for analytical model validation. These test results were used to evaluate a preliminary finite element model of the antenna, and this model development and correlation activity is also described in the paper

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Intervisibility analysis of an offshore wind farm using GIS tools.

One of Kyoto’s protocol targets is to limit greenhouse gas emissions produced by human activities through renewable energy and the conversion of wind energy into a useful form of energy (for example electricity) which is a kind of renewable source undergoing strong development. In this work, the study is focused on offshore aeolic parks. The term “offshore aeolic” indicates wind turbines installed a few miles from the coasts of seas or lakes, exploiting the exposure of strong currents. The offshore aeolic farms have some disadvantages including the impact of these generators on the landscape, but they produce a minimum visual disturbance compared to onshore aeolic farms. Environmental Impact Assessment (known as the EIA), introduced in Europe by the 377/85/EEC Directive and amended three times, in 1997 (Directive 97/11/EC), in 2003 (Directive 2003/35/EC) and in 2009 (Directive 009/31/EC), ensures that natural resources, usability and identity of landscapes are not compromised by engineering operations. Planning applications must be accompanied by an Environmental Statement (ES), with the purpose of giving an idea about the effect that the operations will have on the local environment. One of the main aims of the ES is the understanding of the likely visual intrusion of he proposed wind farm, which necessitates the use of visual techniques. A visual technique commonly used is the intervisibility map, normally represented by a two-dimensional map, centered on the location of the wind farm. Digital Terrain Models (DTMs) are used to achieve Thematic Maps obtained with GIS software. In this paper, GIS tools are used to identify the effects of wind farms on the landscape; in particular, attention is focused on Map Algebra functions and the study of the analysis of the intervisibility of an offshore aeolic farm is tested in a zone in Italy, localized in the Adriatic sea, along the coast of the Apulia and Molise Regions

A Proposal for Automatic Coastline Extraction from Landsat 8 OLI Images Combining Modified Optimum Index Factor (MOIF) and K-Means

The coastal environment is a natural and economic resource of extraordinary value, but it is constantly modifying and susceptible to climate change, human activities and natural hazards. Remote sensing techniques have proved to be excellent for coastal area monitoring, but the main issue is to detect the borderline between water bodies (ocean, sea, lake or river) and land. This research aims to define a rapid and accurate methodological approach, based on the k-means algorithm, to classify the remotely sensed images in an unsupervised way to distinguish water body pixels and detect coastline. Landsat 8 Operational Land Imager (OLI) multispectral satellite images were considered. The proposal requires applying the k-means algorithm only to the most appropriate multispectral bands, rather than using the entire dataset. In fact, by using only suitable bands to detect the differences between water and no-water (vegetation and bare soil), more accurate results were obtained. For this scope, a new index based on the optimum index factor (OIF) was applied to identify the three best-performing bands for the purpose. The direct comparison between the automatically extracted coastline and the manually digitized one was used to evaluate the product accuracy. The results were very satisfactory and the combination involving bands B2 (blue), B5 (near infrared), and B6 (short-wave infrared-1) provided the best performance