Fluid - Structure - Soil Interaction of Cylindrical Liquid Storage Tank Subjected to Horizontal Earthquake Loading

Shallow founded tanks are strategic structures used to store a variety of kind of liquids. The fluid develops hydrodynamic effect on solid domain of container during an earthquake. This paper provides the theoretical background for numerical model on seismic response of fluid-structure-soil interaction. The Finite Element Method (FEM) was used for seismic response of shallow founded cylindrical container. The Fluid- Structure-Soil interaction of shallow founded tank was analysed according to theories of I. Limit States - the ultimate limit state (ULS) and II. Limit States - the serviceability limit state (SLS) pursuant to EN 1997-1. Summary of the results: the maximum rotation of foundation is growing with the reduction of the stiffness of the subsoil and the vertical and horizontal bearing capacity depends on the strength properties of the subsoil

Prediction of the Levodopa Challenge Test in Parkinson's Disease Using Data from a Wrist-Worn Sensor.

The response to levodopa (LR) is important for managing Parkinson's Disease and is measured with clinical scales prior to (OFF) and after (ON) levodopa. The aim of this study was to ascertain whether an ambulatory wearable device could predict the LR from the response to the first morning dose. The ON and OFF scores were sorted into six categories of severity so that separating Parkinson's Kinetigraph (PKG) features corresponding to the ON and OFF scores became a multi-class classification problem according to whether they fell below or above the threshold for each class. Candidate features were extracted from the PKG data and matched to the class labels. Several linear and non-linear candidate statistical models were examined and compared to classify the six categories of severity. The resulting model predicted a clinically significant LR with an area under the receiver operator curve of 0.92. This study shows that ambulatory data could be used to identify a clinically significant response to levodopa. This study has also identified practical steps that would enhance the reliability of this test in future studies

Hepatitis C virus seroprevalence in the general female population of 9 countries in Europe, Asia and Africa

Abstract BACKGROUND: New oral treatments with very high cure rates have the potential to revolutionize global management of hepatitis C virus (HCV), but population-based data on HCV infection are missing in many low and middle-income countries (LMIC). METHODS: Between 2004 and 2009, dried blood spots were collected from age-stratified female population samples of 9 countries: China, Mongolia, Poland, Guinea, Nepal, Pakistan, Algeria, Georgia and Iran. HCV antibodies were detected by a multiplex serology assay using bead-based technology. RESULTS: Crude HCV prevalence ranged from 17.4% in Mongolia to 0.0% in Iran. In a pooled model adjusted by age and country, in which associations with risk factors were not statistically heterogeneous across countries, the only significant determinants of HCV positivity were age (prevalence ratio for ≥45 versus \u3c35 years = 2.84, 95%CI 2.18-3.71) and parity (parous versus nulliparous = 1.73, 95%CI 1.02-2.93). Statistically significant increases in HCV positivity by age, but not parity, were seen in each of the three countries with the highest number of HCV infections: Mongolia, Pakistan, China. There were no associations with sexual partners nor HPV infection. HCV prevalence in women aged ≥45 years correlated well with recent estimates of female HCV-related liver cancer incidence, with the slight exception of Pakistan, which showed a higher HCV prevalence (5.2%) than expected. CONCLUSIONS: HCV prevalence varies enormously in women worldwide. Medical interventions/hospitalizations linked to childbirth may have represented a route of HCV transmission, but not sexual intercourse. Combining dried blood spot collection with high-throughput HCV assays can facilitate seroepidemiological studies in LMIC where data is otherwise scarc

Measuring downstream supply chain performance using Bayesian networks

Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are qualitative. On the other hand just in few quantitative models, the effects of risks on each other have been not evaluated. In this paper the risk metrics will be modeled in downstream supply chain which is a part of chain related to sale, distribution and products' costumers. First qualitative assessment will be done by recognizing risk metrics of supply chain model and then by combining qualified and quantified metrics, downstream supply chain performance will be measured and key factors will be recognized. Total cost is the most important factor and production cost is the most important criteria which can affect downstream supply chain performance. Also style change between criteria has the least impact and importance. Finally through a case study example, the performance and validation of proposed model will be presented.</p

The Use of Data from the Parkinson's KinetiGraph to Identify Potential Candidates for Device Assisted Therapies

Device-assisted therapies (DAT) benefit people with Parkinsons Disease (PwP) but many referrals for DAT are unsuitable or too late, and a screening tool to aid in identifying candidates would be helpful. This study aimed to produce such a screening tool by building a classifier that models specialist identification of suitable DAT candidates. To our knowledge, this is the first objective decision tool for managing DAT referral. Subjects were randomly assigned to either a construction set (n = 112, to train, develop, cross validate, and then evaluate the classifier's performance) or to a test set (n = 60 to test the fully specified classifier), resulting in a sensitivity and specificity of 89% and 86.6%, respectively. The classifier's performance was then assessed in PwP who underwent deep brain stimulation (n = 31), were managed in a non-specialist clinic (n = 81) or in PwP in the first five years from diagnosis (n = 22). The classifier identified 87%, 92%, and 100% of the candidates referred for DAT in each of the above clinical settings, respectively. Furthermore, the classifier score changed appropriately when therapeutic intervention resolved troublesome fluctuations or dyskinesia that would otherwise have required DAT. This study suggests that information from objective measurement could improve timely referral for DAT

Recovery of valuable metals from zinc plant residue through separation between manganese and cobalt with n-n reagent

Recovery and separation of cobalt and manganese from one of zinc plant residues (ZPR), namely hot filter cake (HFC) using a hydrometallurgical process was studied. The process is carried out in four steps as follows: (1) washing zinc, (2) reductive leaching with hydrogen peroxide, (3) cadmium cementation with zinc powder and (4) separation of cobalt from manganese with beta naphthol. In this research, the separation between manganese and cobalt from the HFC using N-N reagent was investigated. The influence of several parameters on the course of the reaction such as N-N quantity, pH, temperature and reaction time was also examined. The optimum separation conditions were found to be N-N quantity: 8 times of stoichiometric value, time: 30 min, temperature: 25 °C and pH = 1.5. Using the optimized conditions, the cobalt and manganese precipitation was nearly 99% and 0%, respectively. A kinetic study of manganese precipitation through N-N reagent has been carried out to assess the effect of kinetics parameters. The data obtained for the leaching kinetics indicated that the precipitation of manganese is an ash diffusion controlled reaction and the reaction activation energy is equal to 1.4kJ/mol