Injection of Microporous Annealing Particle (MAP) Hydrogels in the Stroke Cavity Reduces Gliosis and Inflammation and Promotes NPC Migration to the Lesion

With the number of deaths due to stroke decreasing, more individuals are forced to live with crippling disability resulting from the stroke. To date, no therapeutics exist after the first 4.5 h after the stroke onset, aside from rest and physical therapy. Following stroke, a large influx of astrocytes and microglia releasing proinflammatory cytokines leads to dramatic inflammation and glial scar formation, affecting brain tissue's ability to repair itself. Pathological conditions, such as a stroke, trigger neural progenitor cells (NPCs) proliferation and migration toward the damaged site. However, these progenitors are often found far from the cavity or the peri‐infarct tissue. Poststroke tissue remodeling results in a compartmentalized cavity that can directly accept a therapeutic material injection. Here, this paper shows that the injection of a porous hyaluronic acid hydrogel into the stroke cavity significantly reduces the inflammatory response following stroke while increasing peri‐infarct vascularization compared to nonporous hydrogel controls and stroke only controls. In addition, it is shown that the injection of this material impacts NPCs proliferation and migration at the subventricular zone niche and results, for the first time, in NPC migration into the stroke site.     

Take care of your belongings today – securing accessibility to complex electronic business processes

Most of today’s business processes are based solely on digital data. Input, output, and intermediate results are pure digital objects. Keeping such data accessible and meaningful but even more importantly keeping the business processes functional is challenging. With regards to complex electronic business processes traditional archiving does not provide satisfactory results. Due to the fast technical life-cycle the time gap between archiving and re-enactment or reuse of a process poses risks and increases the uncertainty on achievable results. We propose a novel strategy bridging this specific time gap. For this we present a scalable and cost-effective infrastructure with associated workflows focusing on a process’ execution context. Most importantly the process’ developers are able to assess the preserved results in a timely manner, and thus, reduce the uncertainty on future re-enactment results.     

Effect of iron chelates on oil–water interface,stabilized by milk proteins: The role of phosphate groups and pH. Prediction of iron transfer from aqueous phase toward fat globule surface by changes of interfacial properties

Iron incorporated into food systems induces oxidation and precipitation. The consequences are reduced bioavailability and a functional modification of other food components such as proteins. The iron-chelates such as ferrous bisglycinate represent a possibility to avoid side effects, since the iron is protected. The aim of this study is to investigate the effects of iron-chelates compounds on the properties of an oil/water interface stabilized by caseinate or β-lacotoglobulin, under environmental conditions at 20 °C. Analyses were performed using dynamic drop tensiometry during 5000 s. The aqueous bulk phase is an imidazole/acetate buffer (0.1 M), containing 0.4 × 10⁻⁶ M protein, and 0.2 × 10^-6 9 M iron-chelates compounds. The results indicate that, under neutral conditions, the addition of some irons salts (NaFe-EDTA or Fe-bisglycinate) do not change the structure of the interface stabilized by a protein containing no phosphate groups (β-lactoglobulin). In the case of caseinate, NaFe-EDTA addition increases the lowering rate of surface tension at pH 6.5. On the contrary, the lowering rate of surface tension with caseinate is inhibited by Fe-bisglycinate at pH 6.5. Such an effect is not observed with β-lactoglobulin. The low transfer of irons ions from the bulk to the interface stabilized by β-lactoglobulin is confirmed by zetameter and FTIR measurements. These results indicate an effective strategy to follow for controlling the physical and chemical stability of an emulsion stabilized with proteins.     

Robustness of quantized control systems with mismatch between coder/decoder initializations

This paper analyzes the stability of linear systems with quantized feedback in the presence of mismatch between the initial conditions at the coder and decoder. Under the assumption of the perfect channel, we show that using the scheme proposed in [Liberzon, D., & Neši?, D. (2007). Input-to-state stabilization of linear systems with quantized state measurements. Institute of Electrical and Electronic Engineers Transaction on Automatic Control, 52, 767-781] it is possible to achieve stability with exponential convergence of linear systems with quantized feedback when the coder and decoder are initialized at different initial conditions.     

Long-Wave and Integral Boundary Layer Analysis of Falling Film Flow on Walls With Three-Dimensional Periodic Structures

Falling films exhibit very complex wavy patterns, which depend on the properties of the liquid, the Reynolds number, the wall inclination angle, and the distance from the film inlet. The film hydrodynamics governs the heat and mass transfer in the liquid films. Our vision is to control and enhance heat and mass transport by using walls with specific microscale topographies that influence the falling film flow, stability, and wavy pattern. In this work, long-wave theory and integral boundary layer approximation are used for modeling the falling film flow on walls with three-dimensional periodic microstructures. The wall topography is periodic both in the main flow direction and in the transverse direction. Examples of such microstructures are longitudinal grooves with sinusoidal path (or meandering grooves) and herringbone structures. The effects of the Reynolds number, the wall inclination angle, and the longitudinal and transverse periods of the structure on the shape of liquid–gas interface are investigated. It is shown that, as opposed to straight grooves in longitudinal direction, grooves with meandering paths may lead to significant interface deformations.     

Approach to 3-d ultrasound high resolution imaging for mechanically moving large-aperture transducer based upon Fourier transform

A new three-dimensional (3-D) acoustic image formation technique is proposed that is based on the transmission of wide bandwidth pulse signals and the application of the 3-D fast Fourier transform. A solution to the Helmholtz wave equation has been obtained using the Born approximation. The solution contains analytical expressions for the spatial spectra of the transmit and receive radiation patterns for transducers of various geometries with lenses of fixed focal distances. It has been shown that the proposed algorithms allow for radiation patterns with constant widths at depths both behind and in front of the focal point, starting practically from the plane of the transducer. The theoretical and experimental investigations and computer simulation for both spherical and rectangular transducer shapes have been performed. The results were used to estimate the beamwidths and the side lobe levels. A variant of the linear array has been studied for a cylindrical lens of a fixed focal distance moving in a lateral direction. It has been shown that, in this case, a high resolution (of the order of a few wavelengths) can be achieved along all three Cartesian coordinates at a very high scanning velocity. The influence of the moving scatterers' velocity in inhomogeneous medium on the spatial radiation pattern characteristics has been estimated.     

Bayesian testing for non-linearity in volatility modeling

Neural networks provide a tool for describing non-linearity in volatility processes of financial data and help to answer the question “how much” non-linearity is present in the data. Non-linearity is studied under three different specifications of the conditional distribution: Gaussian, Student-t and mixture of Gaussians. To rank the volatility models, a Bayesian framework is adopted to perform a Bayesian model selection within the different classes of models. In the empirical analysis, the return series of the Dow Jones Industrial Average index, FTSE 100 and NIKKEI 225 indices over a period of 16 years are studied. The results show different behavior across the three markets. In general, if a statistical model accounts for non-normality and explains most of the fat tails in the conditional distribution, then there is less need for complex non-linear specifications.