Nonlinearity and hysteresis of resonant strain gauges

Nonlinearity and hysteresis effects of electrostatically activated, voltage driven resonant microbridges have been studied theoretically and experimentally. It is shown, that, in order to avoid vibration instability and hysteresis to occur, the choices of the ax. and d.c. driving voltages and of the quality factor of a resonator, with a given geometry and choice of materials, are limited by a hysteresis criterion. The limiting conditions are also formulated as hysteresis-free design rules. An expression for the maximum attainable figure of merit is also given. Experimental results, as obtained from electrostatically driven vacuum-encapsulated polysilicon microbridges, are presented and show good agreement with the theory

LIP: Learning Instance Propagation for Video Object Segmentation

In recent years, the task of segmenting foreground objects from background in a video, i.e. video object segmentation (VOS), has received considerable attention. In this paper, we propose a single end-to-end trainable deep neural network, convolutional gated recurrent Mask-RCNN, for tackling the semi-supervised VOS task. We take advantage of both the instance segmentation network (Mask-RCNN) and the visual memory module (Conv-GRU) to tackle the VOS task. The instance segmentation network predicts masks for instances, while the visual memory module learns to selectively propagate information for multiple instances simultaneously, which handles the appearance change, the variation of scale and pose and the occlusions between objects. After offline and online training under purely instance segmentation losses, our approach is able to achieve satisfactory results without any post-processing or synthetic video data augmentation. Experimental results on DAVIS 2016 dataset and DAVIS 2017 dataset have demonstrated the effectiveness of our method for video object segmentation task.Comment: ICCVW1

LIP:Learning instance propagation for video object segmentation

In recent years, the task of segmenting foreground objects from background in a video, i.e. video object segmentation (VOS), has received considerable attention. In this paper, we propose a single end-to-end trainable deep neural network, convolutional gated recurrent Mask-RCNN, for tackling the semi-supervised VOS task. We take advantage of both the instance segmentation network (Mask-RCNN) and the visual memory module (Conv-GRU) to tackle the VOS task. The instance segmentation network predicts masks for instances, while the visual memory module learns to selectively propagate information for multiple instances simultaneously, which handles the appearance change, the variation of scale and pose and the occlusions between objects. After offline and online training under purely instance segmentation losses, our approach is able to achieve satisfactory results without any post-processing or synthetic video data augmentation. Experimental results on DAVIS 2016 dataset and DAVIS 2017 dataset have demonstrated the effectiveness of our method for video object segmentation task.</p

Scalar Electroweak Multiplet Dark Matter

We revisit the theory and phenomenology of scalar electroweak multiplet thermal dark matter. We derive the most general, renormalizable scalar potential, assuming the presence of the Standard Model Higgs doublet, $H$, and an electroweak multiplet $\Phi$ of arbitrary SU(2$)_L$ rank and hypercharge, $Y$. We show that, in general, the $\Phi$-$H$ Higgs portal interactions depend on three, rather than two independent couplings as has been previously considered in the literature. For the phenomenologically viable case of $Y=0$ multiplets, we focus on the septuplet and quintuplet cases, and consider the interplay of relic density and spin-independent direct detection cross section. We show that both the relic density and direct detection cross sections depend on a single linear combination of Higgs portal couplings, $\lambda_{\rm eff}$. For $\lambda_{\rm eff}\sim \mathcal{O}(1)$, present direct detection exclusion limits imply that the neutral component of a scalar electroweak multiplet would comprise a subdominant fraction of the observed DM relic density.Comment: 15 pages, 4 figure

Systematic investigation of the influence of electronic substituents on dinuclear gold( i ) amidinates: synthesis, characterisation and photoluminescence studies

Dinuclear gold(I) compounds are of great interest due to their aurophilic interactions that influence their photophysical properties. Herein, we showcase that gold–gold interactions can be influenced by tuning the electronic properties of the ligands. Therefore, various para substituted (R) N,N′-bis(2,6-dimethylphenyl)formamidinate ligands (pRXylForm; Xyl = 2,6-dimethylphenyl and Form = formamidinate) were treated with Au(tht)Cl (tht = tetrahydrothiophene) to give via salt metathesis the corresponding gold(I) compounds [pRXylForm$_2$Au$_2$] (R = –OMe, –Me, –Ph, –H, –SMe, and –CO$_2$Me). All complexes showed intense luminescence properties at low temperatures. Alignment with the Hammett parameter σ$_p$ revealed the trends in the $^1$H and $^{13}$C NMR spectra. These results showed the influence of the donor–acceptor abilities of different substituents on the ligand system which were confirmed with calculated orbital energies. Photophysical investigations showed their lifetimes in the millisecond range indicating phosphorescence processes and revealed a redshift with the decreasing donor ability of the substituents in the solid state

Fusion bonding of rough surfaces with polishing technique for silicon micromachining

Surface roughness is one of the crucial factors in silicon fusion bonding. Due to the enhanced surface roughness, it is almost impossible to bond wafers after KOH etching. This also applies when wafers are heavily doped, have a thick LPCVD silicon nitride layer on top or have a LPCVD polysilicon layer of poor quality. It has been demonstrated that these wafers bond spontaneously after a very brief chemical mechanical polishing step. An adhesion parameter, that comprises of both the mechanical and chemical properties of the surface, is introduced when discussing the influence of surface roughness on the bondability. Fusion bonding, combined with a polishing technique, will broaden the applications of bonding techniques in silicon micromachining

Accelerating Oxygen Reduction Catalysts through Preventing Poisoning with Non-Reactive Species by Using Hydrophobic Ionic Liquids

Poster presentation given at the 68th Annual Meeting of the International Society of Electrochemistr