Dedicated thermal emulator for analysis of thermal coupling in many-core processors

This paper discusses the problem of thermal coupling in many-core processors manufactured in non-planar FinFET technologies. Our work focuses on two research goals. Firstly, the results obtained from the thermal simulations allow the investigation of mutual thermal influence between neighboring cores in such processors, what can be used to develop thermal models of such architectures. Secondly, we describe a test integrated circuit designed specifically to mimic the thermal behavior of microprocessors manufactured in various technologies. In particular, this paper describes its design and presents selected simulation results obtained using Green?s function-based thermal software.     

Current-controlled switches for HV SoI processes

The paper presents an approach for the design of high-voltage (HV) current-controlled switches. HV switch structures, properties, application possibilities as well as ways of merging these switches into structure of HV signal processing components, are discussed. New HV switch structures are specialized and modified for specific applications. The switch applications include voltage switching with minimized current-load imposed on circuitry attached to input and output side of the proposed switches, as well as current switching with minimal or no current load to the current-mode signal-path, in HV power and smart-power integrated systems, like DC/DC converters or output power stages. The switch structures and modes of operation are introduced, simulated and discussed.     

Mechanical Compression by Simulating Orthodontic Tooth Movement in an In Vitro Model Modulates Phosphorylation of AKT and MAPKs via TLR4 in Human Periodontal Ligament Cells

Mechanical compression simulating orthodontic tooth movement in in vitro models induces pro-inflammatory cytokine expression in periodontal ligament (PDL) cells. Our previous work shows that TLR4 is involved in this process. Here, primary PDL cells are isolated and characterized to better understand the cell signaling downstream of key molecules involved in the process of sterile inflammation via TLR4. The TLR4 monoclonal blocking antibody significantly reverses the upregulation of phospho-AKT, caused by compressive force, to levels comparable to controls by inhibition of TLR4. Phospho-ERK and phospho-p38 are also modulated in the short term via TLR4. Additionally, moderate compressive forces of 2 g/cm², a gold standard for static compressive mechanical stimulation, are not able to induce translocation of Nf-kB and phospho-ERK into the nucleus. Accordingly, we demonstrated for the first time that TLR4 is also one of the triggers for signal transduction under compressive force. The TLR4, one of the pattern recognition receptors, is involved through its specific molecular structures on damaged cells during mechanical stress. Our findings provide the basis for further research on TLR4 in the modulation of sterile inflammation during orthodontic therapy and periodontal remodeling.     

Targeting and ultrasound imaging of microbubble-based contrast agents

Preparation and characterization of targeted microbubbles (ultrasound contrast agents) is described. Specific ligands were attached to the microbubble shell, and ligand-coated microbubbles were selectively attached to various targets, using either an avidin-biotin model system or an antigen-antibody system for targeting to live activated endothelial cells. Firm attachment of microbubbles to the target was achieved. Forces necessary to detach microbubbles from the target were estimated to exceed dozens of pN. Microbubbles were bound to the target even in the rapidly moving stream of the aqueous medium. Down to 20 ng of the ultrasound contrast material on the target surface could be detected by the ultrasound imaging with a commercial medical imaging system. At high bubble density on the target surface, strong ultrasound image attenuation was observed.     

Reinforcement learning-based control to suppress the transient vibration of semi-active structures subjected to unknown harmonic excitation

The problem of adaptive semi-active control of transient structural vibration induced by unknown harmonic excitation is studied. The controller adaptation is attained by using a specially designed reinforcement learning algorithm that adjusts the parameters of a switching control policy to guarantee efficient dissipation of the structural energy. This algorithm relies on an efficient gradient-based sequence that accelerates the learning protocol and results in suboptimal control. The performance of this method is examined through numerical experiments for a span structure that is equipped with a semi-active device of controlled stiffness and damping parameters. The experiments cover a selection of control learning scenarios and comparisons to optimal open-loop and heuristic state-feedback control strategies. This study has confirmed that the developed method has high stabilizing performance, and the relatively low computational burden of the incorporated iterative learning algorithm facilitates its application to multi–degree-of-freedom structures.