Leaks in pipe networks cause significant problems for utilities and water users in terms of lost revenue and interrupted service. In many cities the leakage is as high as forty percent. A water audit is carried out to assess system-wide leakage. However, to detect leakage at the level of a pipeline, a physical measurement technique is generally employed. For large cities the distribution piping length amounts to a few thousand miles. Therefore, the physical measurements can become tedious and expensive. In this thesis it is assumed that a spatial distribution of leakage can be estimated at nodes based on a water audit bookkeeping scheme. A mathematical formulation consisting of continuity, energy (headloss), pressure-dependent demands and/or leakage, and flow direction preservation equations are utilized to distribute demand flows and leakage among pipes. The leakage is attributed to the formation of corrosion holes. Based upon the extent of corrosion, the leakage flow arriving at a particular node is apportioned among all pipes that are converging at that node. Therefore, the formulation presented in this thesis captures the two essential elements behind leakage, namely, pressure driven flow distribution and the vulnerability of pipes to corrosion. The proposed formulation allows utilities to be more proactive in identifying leakage prone districts within the water distribution system. An understanding of the pressure-dependent leakage in the system is helpful when performing a water audit and in developing strategies for leak repair programs. Restoring the full capacity of the water distribution system will greatly increase the reliability of the system, thereby benefiting local utilities and water users. / Master of Science

Behavioral Modification and Relapse Rates in Opioid-Dependent Pregnant Women Managed with Subutex by Tammy Minor MSN, Walden University, 2009 BSN, Marshall University, 1986 Project Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Nursing Practice Walden University March 2016 Opioid dependency affects not only the individual who is dependent on opioids but negatively impactsalso the family unit, the community, and society as a whole. Opioid use in the prenatal period can have devastating effects on both the mother and the fetus. The purpose of this paper is to perform a secondary analysis of the effectiveness of behavioral modification in reducing relapse rates and improving compliance of treatment regimen in opioid- dependent pregnant women who were being managed in a FamilyCare Health Center in West Virginia. The transtheoretical model was used as a framework to determine participants' behavioral readiness to change. The Stetler model was used to evaluate outcomes and goal achievement. The sample consisted of 43 pregnant opioid-dependent women who had participated in the Subutex-assisted program at 3 Family Care Health Centers in West Virginia. Descriptive statistics and regressive analysis were used to analyze relapse data at weeks 2, 6, and 10. A secondary analysis was conducted to determine if behavioral modification contributed to a reduction in relapse rates and improved compliance with the treatment regimen using ANOVA and MANOVA. The results of ANOVA and MANOVA tests showed that behavioral modification has a potential to influence a reduction in relapse rates in the target population. The information obtained from this analysis can be used to influence social change by assisting healthcare providers in revising or modifying existing programs; this information can also and inform the help to design of future programs that effectively meet the needs of this target population .

No description available.

No description available.

Abnormal regulation of growth hormone (GH) secretion has been reported in some patients with insulin-dependent diabetes (IDD). We compared the GH responses in 32 healthy subjects (age 25 ± 2 SE years) and in 23 IDD patients (28 ± 1.9 years old, diabetes duration 10.4 ± 2 years, and glycohemoglobin levels 9.3 ± 2.0%). During acute, severe hypoglycemia (glucose < 40 mg/dl), the mean GH levels were similar. When prolonged mild hypoglycemia was induced (58.0 ± 2.0 mg/dl in the controls and 54.0 ± 2.0 mg/dl in the IDD patients), the mean GH levels were similar, although the increase in GH was delayed in the latter group. During brief (30 min) exercise at 40-50% of VO2 max, GH rose comparably in both groups (IDD patients maintained euglycemia with basal insulin infusion). However, with more prolonged and intense exercise using a glucose clamp to maintain euglycemia, GH rose to 5.4 ± 2.2 ng/ml in controls and 26.4 ± 12.6 ng/ml in the diabetics (P < 0.05). When the combination of intense exercise and hypoglycemia (~ 55 mg/dl) was used, GH rose to a peak of 21.7 ± 2.7 ng/ml in the controls and to 33 ± 3.0 ng/ml in the diabetics (P = NS). Our data show that in insulin-infused IDD patients made euglycemic for these experiments: a) The GH response to acute, severe hypoglycemia was identical to that in the controls and the response to mild, prolonged hypoglycemia was delayed, but of similar magnitude compared with controls; b) Exercise-induced GH responses were observed in both groups, but exaggerated in the diabetics at a higher exercise intensity; c) Hypoglycemia during exercise produced an additive effect on GH secretion in the controls but not in the IDD patients. We conclude that the wide range of abnormal GH secretory responses in type I diabetes reflects a central, possibly hypothalamic, defect in GH regulation.

<p> This thesis describes the isolation and investigation of a DNA-dependent RNA polymerase from the extreme halophile Halobacterium cutirubrum.</p> <p> The enzyme system was analyzed under conditions of very high ionic strengths which are characteristic of the internal salt concentrations of extreme halophiles and at much lower ionic strengths found in conventional bacterial systems. The enzyme was found to have activity in a wide range of salt concentrations when attached to its DNA template in the form of a DNA-Membrane-Protein complex. The enzyme, however, lost the ability to function at high ionic strengths when freed from this complex.</p> <p> The properties of the isolated DNA-dependent RNA polymerase from the halophile were then compared to the properties of the same enzyme isolated from the non-halophilic bacterium, Eschericia coli. Both enzymes were found to have the same approximate molecular weights and to share the same substrate requirements. The enzymes differed, however, in their response to inhibitors specific for RNA synthesis. </p> / Thesis / Master of Science (MSc)

<p> In this thesis new joint target tracking and classification techniques for aspect-dependent measurements are developed. Joint target tracking and classification methods can result in better tracking and classification performance than those treating these as two separate problems. Significant improvement in state estimation and classification performance can be achieved by exchanging useful information between the tracker and the classifier. Target classification in many target tracking algorithms is not typically done by taking into consideration the target-to-sensor orientation. However, the feature information extracted from the signal that originated from the target is generally a strong function of the target-to-sensor orientation. Since sensor returns are sensitive to this orientation, classification from a single sensor may not give exact target classes. Better classification results can be obtained by fusing feature measurements from multiple views of a target. In multitarget scenarios, handling the classification becomes more challenging due to the identifying the feature information corresponding to a target. That is, it is difficult to identify the origin of measurements. In this case, feature measurement origin ambiguities can be eliminated by integrating the classifier into multiframe data association. This technique reduces the ambiguity in feature measurements while improving track purity. </p> <p> A closed form expression for multiaspect target classification is not feasible. Then, training based statistical modeling can be used to model the unknown feature measurements of a target. In this thesis, the Observable Operator Model (OOM), a better alternative to the Hidden Markov Model (HMM), is used to capture unknown feature distribution of each target and thus can be used as a classifier. The proposed OOM based classification technique incorporates target-to-sensor orientation with a sequence of feature information from multiple sensors. Further, the multi-aspect classifier can be modeled using the OOM to handle unknown target orientation. The target orientation estimation using OOM can also be used to find improved estimates of the states of highly maneuverable targets with noisy kinematic measurements. One limiting factor in obtaining accurate estimates of highly maneuvering target states is the high level of uncertainty in velocity and acceleration components. The target orientation information is helpful in alleviating this problem to accurately determine the velocity and acceleration components. </p> <p> Various simulation studies based on two-dimensional scenarios are presented in this thesis to demonstrate the merits of the proposed joint target tracking and classification algorithms that use aspect-dependent feature measurements.</p> / Thesis / Doctor of Philosophy (PhD)

No description available.

No description available.

No description available.