Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

Magnetic Resonance Materials in Physics, Biology and Medicine - MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate...     

Recent advances in evolutionary and bio-inspired adaptive robotics: Exploiting embodied dynamics

Applied Intelligence - This paper explores current developments in evolutionary and bio-inspired approaches to autonomous robotics, concentrating on research from our group at the University of...     

A proposal for future data organization in enterprise systems—an analysis of established database approaches

The digital transformation sets new requirements to all classes of enterprise systems in companies. ERP systems in particular, which represent the dominant class of enterprise systems, are struggling to meet the new requirements at all levels of the architecture. Therefore, there is an urgent need to reconsider the overall architecture of the systems and address the root of the related issues. Given that many restrictions ERP pose on their adaptability are related to the standardization of data, the database layer of ERP systems is addressed. Since database serve as the foundation for data storage and retrieval, they limit the flexibility of enterprise systems and the chance to adapt to new requirements accordingly. So far, relational databases are widely used. Using a systematic literature approach, recent requirements for ERP systems were identified. Prominent database approaches were assessed against the 23 requirements identified. The results reveal the strengths and weaknesses of recent database approaches. To this end, the results highlight the demand to combine multiple database approaches to fulfill recent business requirements. From a conceptual point of view, this paper supports the idea of federated databases which are interoperable to fulfill future requirements and support business operation. This research forms the basis for renewal of the current generation of ERP systems and proposes to ERP vendors to use different database concepts in the future.

     

A Modular Approach for Surrogate Modeling of Flowsheets

Flowsheet simulation, an important building block in chemical process development and design, generally requires the solution of a nonlinear system of equations. Such a simulation can fail if either no solution exists for the chosen specifications or if the initial values for the solver are chosen unfavorably. In this work, to overcome such convergence failures, AI-based surrogate models are trained for unit operations of a flowsheet and then interconnected. For a pressure swing distillation with recycle, it is shown that such an interconnection of surrogate models yields more accurate results compared to a surrogate model for the whole flowsheet at once, and that adequate starting points for the flowsheet simulation can be obtained from the interconnected surrogates.     

Efficient Site-Specific Antibody–Drug Conjugation by Engineering a Nature-Derived Recognition Tag for Microbial Transglutaminase

Microbial transglutaminase (mTG) has recently emerged as a powerful tool for antibody engineering. In nature, it catalyzes the formation of amide bonds between glutamine side chains and primary amines. Being applied to numerous research fields from material sciences to medicine, mTG enables efficient site-specific conjugation of molecular architectures that possess suitable recognition motifs. In monoclonal antibodies, the lack of native transamidation sites is bypassed by incorporating specific peptide recognition sequences. Herein, we report a rapid and efficient mTG-catalyzed bioconjugation that relies on a novel recognition motif derived from its native substrate Streptomyces papain inhibitor (SPI_P). Improved reaction kinetics compared to commonly applied sequences were demonstrated for model peptides and for biotinylation of Her2-targeting antibody trastuzumab variants. Moreover, an antibody–drug conjugate assembled from trastuzumab that was C-terminally tagged with the novel recognition sequence revealed a higher payload-antibody ratio than the reference antibody.     

Perturbations and phase transitions in swarm optimization algorithms

Natural Computing - Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular...     

Effect of carbon nanotubes decorated with silver nanoparticles as hybrid filler on properties of natural rubber nanocomposites

Decoration of carbon nanotube (CNT) surfaces with silver nanoparticles (AgNPs) was performed using N,N-dimethylformamide reducing agent. The CNT-decorated with AgNP (CNT-AgNP) was then used to prepare natural rubber (NR) nanocomposites via latex mixing method. Cure characteristics, mechano-thermal relaxation, electrical conductivity, and thermal properties of the composites were investigated. It was found that the CNT-AgNP gave cure properties improved over plain NR compounds in terms of scorch time, degree of vulcanization, and activation energy. In addition, temperature scanning stress relaxation measurement revealed stronger network formation after incorporation of AgNP into the NR matrix due to the interaction among CNT and AgNP particles. This also provided high conductivity and low percolation threshold concentration for the CNT-AgNP filled NR, relative to plain CNT filled NR composites. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47281.     

Design and Hydrodynamic Characterization of a Draft Tube Baffle Tank for Lab-Scale

For process development on lab-scale, it is necessary to have equipment that represents the industrial apparatuses as similar as possible to offer short time-to-market. Accordingly, a draft tube baffle (DTB) crystallizer was scaled down from typical m³-scale to 1 L filling volume. The suspension characteristics were determined for fluidized crystals in saturated solution. For further characterization of the DTB tank, the residence time of the liquid and solid phases were experimentally determined for the continuous operation mode. Additionally, the classifying behavior of the particles in the DTB was investigated.     

Non-destructive microstructural analysis by electrical conductivity: Comparison with hardness measurements in different materials

The use of non-destructive evaluation (NDE) techniques for assessing microstructural changes in processed materials is of particular importance as it can be used to assess, qualitatively, the integrity of any material/structure. Among the several NDE techniques available, electrical conductivity measurements using eddy currents attract great attention owing to its simplicity and reliability. In this work, the electrical conductivity profiles of friction stir processed Ti6Al4V, Cu, Pb, S355 steel and gas tungsten arc welded AISI 304 stainless steel were determined through eddy currents and four-point probe. In parallel, hardness measurements were also performed. The profiles matched well with the optical macrographs of the materials: while entering in the processed region a variation in both profiles was always observed. One particular advantage of electrical conductivity profiles over hardness was evident: it provides a better resolution of the microstructural alterations in the processed materials. Moreover, when thermomechanical processing induces microstructural changes that modify the magnetic properties of a material, eddy currents testing can be used to qualitatively determine the phase fraction in a given region of the material. A qualitative relation between electrical conductivity measurements and hardness is observed.