38 research outputs found
Postpartum haemorrhage in midwifery care in the Netherlands: validation of quality indicators for midwifery guidelines
Predictors of Hepatitis Knowledge Improvement Among Methadone Maintained Clients Enrolled in a Hepatitis Intervention Program
This randomized, controlled study (n = 256) was conducted to compare three interventions designed to promote hepatitis A virus (HAV) and hepatitis B virus (HBV) vaccination completion, among clients undergoing methadone maintenance treatment (MMT) in Los Angeles and Santa Monica. The participants were randomized into three groups: Motivational Interviewing-Single Session (MI-Single), Motivational Interviewing-Group (MI-Group), or Nurse-Led Hepatitis Health Promotion (HHP). All three treatment groups received the 3-series HAV/HBV vaccine. The MI sessions were provided by trained therapists, the Nurse-Led HHP sessions were delivered by a research nurse. The main outcome variable of interest was improvement in HBV and HCV knowledge, measured by a 6-item HBV and a 7-item HCV knowledge and attitude tool that was administered at baseline and at 6-month follow-up. The study results showed that there was a significant increase in HBV- and HCV-related knowledge across all three groups (p < 0.0001). There were no significant differences found with respect to knowledge acquisition among the groups. Irrespective of treatment group, gender (P = 0.008), study site (P < 0.0001) and whether a participant was abused as a child (P = 0.017) were all found to be predictors of HCV knowledge improvement; only recruitment site (P < 0.0001) was found to be a predictor of HBV knowledge. The authors concluded that, although MI-Single, MI-Group and Nurse-Led HHP are all effective in promoting HBV and HCV knowledge acquisition among MMT clients, Nurse-Led HHP may be the method of choice for this population as it may be easier to integrate and with additional investigation may prove to be more cost efficient
A stress-based formulation of the free material design problem with the trace constraint and multiple load conditions
Molecular detection of TEM and AmpC (Dha, mox) broad spectrum β-lactamase in clinical isolates of Escherichia coli
"nBackground: Beta- lactamase enzymes are the most important resistant factors to beta lactam antibiotics among gram negative bacteria. Nowadays, the prevalence of beta- lactamase infection is increasing worldwide and drawn the scientists attention as an important subject. Due to high prevalence of bacteria contained TEM beta lactamase and AmpC enzymes, using molecular methods especially designing universal primers could be valuable to detect all of them. The aim of this study was to determine the prevalence of TEM and AmpC (Dha and MOX) beta- lactamase genes using universal primers. "nMethods: A total of 500 clinical specimens from various Hospitals in Tehran, Iran were collected and analyzed for E. coli based on biochemical tests. These clinical specimens were also screened by Disk diffusion agar, combined disk method and PCR to detect the samples producing extended- spectrum beta- lactamase. "nResults: Overall 200 isolates of Escherichia coli were collected from the 500 clinical specimens out of which 128(64%) isolates were positive by PCR assay and showed bla- TEM, bla- AmpC (Dha, MOX) genes, 74(57.8%) and 5(3.9%) to have bla- TEM and bla Dha, respectively. Mox gene was not detected in any of the specimens. "nConclusions: Our results revealed that using the molecular methods with phenotype methods is very essential for complete detection of Beta- lactamases. There is the need for updating the treatment protocol because the prevalence of this resistance is increasing
Calibration and Finite Element Implementation of an Energy-Based Material Model for Shape Memory Alloys
Non-contact stress measurement in granular materials via neutron and X-ray diffraction: theoretical foundations
Prediction of Apparent Trabecular Bone Stiffness through Fourth-Order Fabric Tensors
The apparent stiffness tensor is an important mechanical parameter for characterizing trabecular bone. Previous studies have modeled this parameter as a function of mechanical properties of the tissue, bone density and a second-order fabric tensor, which encodes both anisotropy and orientation of trabecular bone. Although these models yield strong correlations between observed and predicted stiffness tensors, there is still space for reducing accuracy errors.In this paper we propose a model that uses fourth-order instead of second-order fabric tensors. First, the totally symmetric part of the stiffness tensor is assumed proportional to the fourth-order fabric tensor in the logarithmic scale. Second, the asymmetric part of the stiffness tensor is derived from relationships among components of the harmonic tensor decomposition of the stiffness tensor. The mean intercept length (MIL), generalized MIL (GMIL) and global structure tensor fourth-order were computed from images acquired through micro computed tomography of 264 specimens of the femur. The predicted tensors were compared to the stiffness tensors computed by using the micro finite element method (micro-FE), which was considered as the gold standard, yielding strong correlations (R^2 above 0.962). The GMIL tensor yielded the best results among the tested fabric tensors. The Frobenius error, geodesic error and the error of the norm were reduced by applying the proposed model by 3.75%, 0.07% and 3.16%, respectively compared to the model by Zysset and Curnier (1995) with the second-order MIL tensor. From the results, fourth-order fabric tensors are a good alternative to the more expensive micro-FE stiffness predictions.QC 20160115</p