Superparamagnetic colloids in viscous fluids

The influence of a magnetic field on the aggregation process of superparamagnetic colloids has been well known on short time for a few decades. However, the influence of important parameters, such as viscosity of the liquid, has received only little attention. Moreover, the equilibrium state reached after a long time is still challenging on some aspects. Indeed, recent experimental measurements show deviations from pure analytical models in extreme conditions. Furthermore, current simulations would require several years of computing time to reach equilibrium state under those conditions. In the present paper, we show how viscosity influences the characteristic time of the aggregation process, with experimental measurements in agreement with previous theories on transient behaviour. Afterwards, we performed numerical simulations on equivalent systems with lower viscosities. Below a critical value of viscosity, a transition to a new aggregation regime is observed and analysed. We noticed this result can be used to reduce the numerical simulation time from several orders of magnitude, without modifying the intrinsic physical behaviour of the particles. However, it also implies that, for high magnetic fields, granular gases could have a very different behaviour from colloidal liquids

Prevalence and incidence of iron deficiency in European community-dwelling older adults : An observational analysis of the DO-HEALTH trial

Background and aim Iron deficiency is associated with increased morbidity and mortality in older adults. However, data on its prevalence and incidence among older adults is limited. The aim of this study was to investigate the prevalence and incidence of iron deficiency in European community-dwelling older adults aged ≥ 70 years. Methods Secondary analysis of the DO-HEALTH trial, a 3-year clinical trial including 2157 community-dwelling adults aged ≥ 70 years from Austria, France, Germany, Portugal and Switzerland. Iron deficiency was defined as soluble transferrin receptor (sTfR) > 28.1 nmol/L. Prevalence and incidence rate (IR) of iron deficiency per 100 person-years were examined overall and stratified by sex, age group, and country. Sensitivity analysis for three commonly used definitions of iron deficiency (ferritin  1.5) were also performed. Results Out of 2157 participants, 2141 had sTfR measured at baseline (mean age 74.9 years; 61.5% women). The prevalence of iron deficiency at baseline was 26.8%, and did not differ by sex, but by age (35.6% in age group ≥ 80, 29.3% in age group 75–79, 23.2% in age group 70–74); P  1.5. Occurrences of iron deficiency were observed with IR per 100 person-years of 9.2 (95% CI 8.3–10.1) and did not significantly differ by sex or age group. The highest IR per 100 person-years was observed in Austria (20.8, 95% CI 16.1–26.9), the lowest in Germany (6.1, 95% CI 4.7–8.0). Regarding the other definitions of iron deficiency, the IR per 100 person-years was 4.5 (95% CI 4.0–4.9) for ferritin  1.5. Conclusions Iron deficiency is frequent among relatively healthy European older adults, with people aged ≥ 80 years and residence in Austria and Portugal associated with the highest risk

Normal parameter reduction algorithm in soft set based on hybrid binary particle swarm and biogeography optimizer

© 2019, Springer-Verlag London Ltd., part of Springer Nature. Existing classification techniques that are proposed previously for eliminating data inconsistency could not achieve an efficient parameter reduction in soft set theory, which effects on the obtained decisions. Meanwhile, the computational cost made during combination generation process of soft sets could cause machine infinite state, which is known as nondeterministic polynomial time. The contributions of this study are mainly focused on minimizing choices costs through adjusting the original classifications by decision partition order and enhancing the probability of searching domain space using a developed Markov chain model. Furthermore, this study introduces an efficient soft set reduction-based binary particle swarm optimized by biogeography-based optimizer (SSR-BPSO-BBO) algorithm that generates an accurate decision for optimal and sub-optimal choices. The results show that the decision partition order technique is performing better in parameter reduction up to 50%, while other algorithms could not obtain high reduction rates in some scenarios. In terms of accuracy, the proposed SSR-BPSO-BBO algorithm outperforms the other optimization algorithms in achieving high accuracy percentage of a given soft dataset. On the other hand, the proposed Markov chain model could significantly represent the robustness of our parameter reduction technique in obtaining the optimal decision and minimizing the search domain.Published versio

Recovery of phenol and copper from soils by electric field

Application of a direct elec. field in contaminated soils is expected to produce an important in situ means of environmental restoration. The factors that det. the success of the process are the combined effects of electroosmosis, ionic migration, electrochem. and chem. reactions. During extn. of copper, the pH of the purging soln. had significant influence on process efficiency. Extn. of 94-99 % of the initial copper present in kaolinite clay, under controlled acidic pH, has been achieved. During extn. of phenol, the efficiency of the process is detd. by the electroosmotic flow rate. More than 80 % of the initial phenol present in kaolinite clay has been recovered. The compn. of the pore soln. and the applied elec. field are the detg. parameters of the optimization of the process. [on SciFinder (R)