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Adsorptive desulfurization of model oil using untreated, acid activated and magnetite nanoparticle loaded bentonite as adsorbent
No full textAbstractThe present research work focuses on a novel ultraclean desulfurization process of model oil by the adsorption method using untreated, acid activated and magnetite nanoparticle loaded bentonite as adsorbent. The parameters investigated are effect of contact time, adsorbent dose, initial dibenzothiophene (DBT) concentration and temperature. Experimental tests were conducted in batch process. Pseudo first and second order kinetic equations were used to examine the experimental data. It was found that pseudo second order kinetic equation described the data of the DBT adsorption onto all types of adsorbents very well. The isotherm data were analyzed using Langmuir and Freundlich isotherm models. The Langmuir isotherm model fits the data very well for the adsorption of DBT onto all three forms of adsorbents. The adsorption of DBT was also investigated at different adsorbent doses and was found that the percentage adsorption of DBT was increased with increasing the adsorbent dose, while the adsorption in mg/g was decreased with increasing the adsorbent dose. The prepared adsorbents were analyzed by scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDX) and X-ray diffraction (XRD)
Molecularly controlled epoxy network nanostructures
No full textAbstractEpoxy thermosets continue to be used in a variety of coatings, adhesives, and structural composites. Nanostructural heterogeneities have been proposed to determine the physical properties of these materials, but the presence and origin of these features is disputed. Here, we combine nano-chemical imaging and nano-thermal analysis to establish a connection between internal crosslinking and the appearance of nanoscale chemical heterogeneities in epoxy resins. Deflection of an AFM probe is used as a local sensor to detect photothermal expansion in response to infrared excitation, and nanoscale lateral variations are detected in response to illumination at wavenumbers associated with crosslinking. Furthermore, these heterogeneous chemical features correspond to an increased range of local thermal transitions, and only arise within highly cross-linked resins; lightly cross-linked specimens are found to be homogeneous
Heart rate control by carvedilol in Japanese patients with chronic atrial fibrillation: The AF Carvedilol study
No full textAbstractBackgroundβ-Blockers are used to control heart rate (HR) in patients with atrial fibrillation (AF). However, the appropriate dosage and efficacy of carvedilol in Japanese AF patients are yet to be clarified.MethodsIn this multicenter, randomized, double-blind study, Japanese patients with persistent or permanent AF received carvedilol for 6 weeks in the following three dosage-regimen groups: 5-mg fixed-dose (n=42), 10-mg dose-escalation (n=42), or 20-mg dose-escalation (n=43). To evaluate the efficacy of each dosage regimen and the dose–response relationship, changes in 24-h mean HR (mHR) on Holter electrocardiograms from baseline to weeks 2, 4, and 6 were determined as primary endpoints. The effects on circadian changes in HR, the proportion of patients achieving target HR, clinical symptoms, and adverse events were also examined.ResultsAfter 2 weeks, carvedilol 5mg decreased 24-h mHR significantly [6.6 (95% CI: 5.2–8.0)beats/min, p<0.0001]. After 6 weeks, carvedilol showed a trend of dose-dependent HR reduction (p=0.0638): 7.6 (5.4–9.8) in the 5-mg fixed-dose group; 8.9 (6.7–11.1) in the 10-mg dose-escalation group; and 10.6 (8.4–12.8)beats/min in the 20-mg dose-escalation group. There were no serious adverse events related to carvedilol.ConclusionsIn Japanese patients with persistent or permanent AF, carvedilol at 5mg once daily demonstrated a significant HR reduction, and step-wise dose escalation from 5mg to 20mg showed a trend of dose-dependent HR reduction
Approximate Bayes estimators applied to the Bilal model
No full textAbstractThis paper develops approximate Bayes estimators of the parameter of the Bilal failure model by using the method of Tierney and Kadane [Accurate approximations for posterior moments and marginal densities, J. Amer. Statist. Assoc. 81 (1986) 82–86.] based on Type-2 censored sample and four different loss functions. Existence and uniqueness theorem for the maximum likelihood estimate are established. Based on Monte Carlo simulation study, comparisons are made between those estimators and their corresponding Bayes estimators obtained by using Gibb’s sampling approach
Draft genome sequence of Thermoactinomyces sp. Gus2-1 isolated from the hot-spring Gusikha in Bargusin Valley (Baikal Rift Zone, Russia)
No full textAbstractThe Thermoactinomyces sp. strain Gus2-1 was isolated from hot-spring sediments sample from the hot-spring Gusikha in Bargusin Valley (Baikal Rift Zone, Russia). The sequenced and annotated genome is 2,623,309bp and encodes 2513 genes. The draft genome sequence of the Thermoactinomyces sp. strain Gus2-1 has been deposited at DDBJ/EMBL/GenBank under the accession JPZM01000000 and the sequences could be found at the site https://www.ncbi.nlm.nih.gov/nuccore/JPZM01000000
Numerical determination of the mechanical stiffness of a force measurement device based on capacitive probes: Application to roller bearings
No full textAbstractBearings allow external loadings to be transferred from one raceway to the other through rolling elements, which induces strains in the bearing constituents. In order to measure the radial component of these forces, the fixed ring is inserted within a housing equipped with capacitive probes able to measure displacements with very high sensitivity. This work mainly focuses on determining the optimal housing shape using FE simulations and their influence on the global stress state undergone by the structure. Finally, an averaged global stiffness is computed, allowing proper calculation of the contact forces involved in the bearing
The blood-brain barrier in systemic inflammation
No full textAbstractThe blood-brain barrier (BBB) plays a key role in maintaining the specialized microenvironment of the central nervous system (CNS), and enabling communication with the systemic compartment. BBB changes occur in several CNS pathologies. Here, we review disruptive and non-disruptive BBB changes in systemic infections and other forms of systemic inflammation, and how these changes may affect CNS function in health and disease. We first describe the structure and function of the BBB, and outline the techniques used to study the BBB in vitro, and in animal and human settings. We then summarise the evidence from a range of models linking BBB changes with systemic inflammation, and the underlying mechanisms. The clinical relevance of these BBB changes during systemic inflammation are discussed in the context of clinically-apparent syndromes such as sickness behaviour, delirium, and septic encephalopathy, as well as neurological conditions such as Alzheimer’s disease and multiple sclerosis. We review emerging evidence for two novel concepts: (1) a heightened sensitivity of the diseased, versus healthy, BBB to systemic inflammation, and (2) the contribution of BBB changes induced by systemic inflammation to progression of the primary disease process
Critical weather situations for renewable energies – Part A: Cyclone detection for wind power
No full textAbstractA constantly increasing share of weather dependent renewable energies in Germany's power mix poses new challenges concerning grid management and security of energy supply. An evaluation of the three year period from 2012 to 2014 reveals, that 60% of days with largest errors in the day-ahead wind power forecasts for Germany are linked to cyclones and troughs traversing the North Sea, the Baltic Sea or Germany. A cyclone detection algorithm has been developed to automatically indicate these critical weather situations. The algorithm is based on Numerical Weather Prediction model forecasts of mean sea level pressure. The cyclone detection is used to design an automated weather information tool for end-users such as Transmission System Operators (TSOs). For 2014, it identified a critical weather development in 38% of all days. The root mean square error of day-ahead wind power forecasts increased by 1% of installed capacity during these periods. A real time application of the tool is being implemented in order to support a sustainable and save integration of the increasing wind power production. It will then be provided to, and will be tested by, three German TSOs with the purpose of an operative usage to guarantee the security of supply
Lifetime antipsychotic medication and cognitive performance in schizophrenia at age 43 years in a general population birth cohort
No full textAbstractThis naturalistic study analysed the association between cumulative lifetime antipsychotic dose and cognition in schizophrenia after an average of 16.5 years of illness. Sixty participants with schizophrenia and 191 controls from the Northern Finland Birth Cohort 1966 were assessed at age 43 years with a neurocognitive test battery. Cumulative lifetime antipsychotic dose-years were collected from medical records and interviews. The association between antipsychotic dose-years and a cognitive composite score based on principal component analysis was analysed using linear regression. Higher lifetime antipsychotic dose-years were significantly associated with poorer cognitive composite score, when adjusted for gender, onset age and lifetime hospital treatment days. The effects of typical and atypical antipsychotics did not differ. This is the first report of an association between cumulative lifetime antipsychotic dose and global cognition in midlife schizophrenia. Based on these data, higher lifetime antipsychotic dose-years may be associated with poorer cognitive performance at age 43 years. Potential biases related to the naturalistic design may partly explain the results; nonetheless, it is possible that large antipsychotic doses harm cognition in schizophrenia in the long-term
A new LPV modeling approach using PCA-based parameter set mapping to design a PSS
No full textAbstractThis paper presents a new methodology for the modeling and control of power systems based on an uncertain polytopic linear parameter-varying (LPV) approach using parameter set mapping with principle component analysis (PCA). An LPV representation of the power system dynamics is generated by linearization of its differential-algebraic equations about the transient operating points for some given specific faults containing the system nonlinear properties. The time response of the output signal in the transient state plays the role of the scheduling signal that is used to construct the LPV model. A set of sample points of the dynamic response is formed to generate an initial LPV model. PCA-based parameter set mapping is used to reduce the number of models and generate a reduced LPV model. This model is used to design a robust pole placement controller to assign the poles of the power system in a linear matrix inequality (LMI) region, such that the response of the power system has a proper damping ratio for all of the different oscillation modes. The proposed scheme is applied to controller synthesis of a power system stabilizer, and its performance is compared with a tuned standard conventional PSS using nonlinear simulation of a multi-machine power network. The results under various conditions show the robust performance of the proposed controller