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Superparamagnetic iron oxide nanoparticles (SPION) are extensively used for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), as well as for magnetic fluid hyperthermia (MFH). We here describe a sequential centrifugation protocol to obtain SPION with well-defined sizes from a polydisperse SPION starting formulation, synthesized using the routinely employed co-precipitation technique. Transmission electron microscopy, dynamic light scattering and nanoparticle tracking analyses show that the SPION fractions obtained upon size-isolation are well-defined and almost monodisperse. MRI, MPI and MFH analyses demonstrate improved imaging and hyperthermia performance for size-isolated SPION as compared to the polydisperse starting mixture, as well as to commercial and clinically used iron oxide nanoparticle formulations, such as Resovist® and Sinerem®. The size-isolation protocol presented here may help to identify SPION with optimal properties for diagnostic, therapeutic and theranostic applications.
Socio-technical scenarios for energy-intensive industries: the future of steel production in Germany
(2019)
Soft Materials in Technology and Biology – Characteristics, Properties, and Parameter Identification
(2008)
There is a very large number of very important situations which can be modeled with nonlinear parabolic partial differential equations (PDEs) in several dimensions. In general, these PDEs can be solved by discretizing in the spatial variables and transforming them into huge systems of ordinary differential equations (ODEs), which are very stiff. Therefore, standard explicit methods require a large number of iterations to solve stiff problems. But implicit schemes are computationally very expensive when solving huge systems of nonlinear ODEs. Several families of Extrapolated Stabilized Explicit Runge-Kutta schemes (ESERK) with different order of accuracy (3 to 6) are derived and analyzed in this work. They are explicit methods, with stability regions extended, along the negative real semi-axis, quadratically with respect to the number of stages s, hence they can be considered to solve stiff problems much faster than traditional explicit schemes. Additionally, they allow the adaptation of the step length easily with a very small cost.
Two new families of ESERK schemes (ESERK3 and ESERK6) are derived, and analyzed, in this work. Each family has more than 50 new schemes, with up to 84.000 stages in the case of ESERK6. For the first time, we also parallelized all these new variable step length and variable number of stages algorithms (ESERK3, ESERK4, ESERK5, and ESERK6). These parallelized strategies allow to decrease times significantly, as it is discussed and also shown numerically in two problems. Thus, the new codes provide very good results compared to other well-known ODE solvers. Finally, a new strategy is proposed to increase the efficiency of these schemes, and it is discussed the idea of combining ESERK families in one code, because typically, stiff problems have different zones and according to them and the requested tolerance the optimum order of convergence is different.
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
At the present time, one of the most serious environmental problems of Central Asia and South Kazakhstan is the ongoing large-scale deterioration of principal urban tree populations. Several major centers of massive spread of invasive plant pests have been found in urban dendroflora of this region. The degree of damage of seven most wide-spread aboriginal tree species was found to range from 21.4±1.1 to 85.4±1.8%. In particular, the integrity of the native communities of sycamore (Platanus spp.), willow (Salix spp.), poplar (Populus spp.) and elm (Ulmus spp.) is highly endangered. Our taxonomic analysis of the most dangerous tree pests of the region has revealed them as neobiontic xylophilous insects such as Cossus cossus L. (Order: Lepidoptera L.) Monochamus urussovi Fisch., Monochamus sutor L., Acanthocinus aedelis L. and Ñetonia aureate L. (Order: Coleoptera L.). We relate the origin of this threatening trend with the import of industrial wood in the mid 90s of the last century that was associated with high degree of the constructional work in the region. Because of the absence of efficient natural predators of the pest species, the application of microbiological methods of the pest control and limitation is suggested.
In this work, a spore-based biosensor is evaluated to monitor the microbicidal efficacy of sterilization processes applying gaseous hydrogen peroxide (H2O2). The sensor is based on interdigitated electrode structures (IDEs) that have been fabricated by means of thin-film technologies. Impedimetric measurements are applied to study the effect of sterilization process on spores of Bacillus atrophaeus. This resilient microorganism is commonly used in industry to proof the sterilization efficiency. The sensor measurements are accompanied by conventional microbiological challenge tests, as well as morphological characterizations with scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The sensor measurements are correlated with the microbiological test routines. In both methods, namely the sensor-based and microbiological one, a tailing effect has been observed. The results are evaluated and discussed in a three-dimensional calibration plot demonstrating the sensor's suitability to enable a rapid process decision in terms of a successfully performed sterilization.
Objective
To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval.
Methods
We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics.
Results
Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings.
Conclusions
Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks.
Significance
An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.
The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L²-distances to uniformity based on the empirical distribution function, the integrated empirical distribution function and the integrated empirical survival function. Approximations of power functions, confidence intervals for the L²-distances and statistical neighbourhood-of-uniformity validation tests are obtained as main applications. The finite sample behaviour of the procedures is illustrated by a simulation study.