High-sensitivity microfluidic calorimeters for biological and chemical applications

High-sensitivity microfluidic calorimeters raise the prospect of achieving high-throughput biochemical measurements with minimal sample consumption. However, it has been challenging to realize microchip-based calorimeters possessing both high sensitivity and precise sample-manipulation capabilities. Here, we report chip-based microfluidic calorimeters capable of characterizing the heat of reaction of 3.5-nL samples with 4.2-nW resolution. Our approach, based on a combination of hard- and soft-polymer microfluidics, provides both exceptional thermal response and the physical strength necessary to construct high-sensitivity calorimeters that can be scaled to automated, highly multiplexed array architectures. Polydimethylsiloxane microfluidic valves and pumps are interfaced to parylene channels and reaction chambers to automate the injection of analyte at 1 nL and below. We attained excellent thermal resolution via on-chip vacuum encapsulation, which provides unprecedented thermal isolation of the minute microfluidic reaction chambers. We demonstrate performance of these calorimeters by resolving measurements of the heat of reaction of urea hydrolysis and the enthalpy of mixing of water with methanol. The device structure can be adapted easily to enable a wide variety of other standard calorimeter operations; one example, a flow calorimeter, is described

High-order spectral singularity

Exceptional point and spectral singularity are two types of singularity that are unique to non-Hermitian systems. Here, we report the high-order spectral singularity as a high-order pole of the scattering matrix for a non-Hermitian scattering system, and the high-order spectral singularity is a unification of the exceptional point and spectral singularity. At the high-order spectral singularity, the scattering coefficients have high-order divergence and the scattering system stimulates high-order lasing. The wave emission intensity is polynomially enhanced, and the order of the growth in the polynomial intensity linearly scales with the order of the spectral singularity. Furthermore, the coherent input controls and alters the order of the spectral singularity. Our findings provide profound insights into the fundamentals and applications of high-order spectral singularities.Comment: 8 pages, 3 figure

Co-training an improved recurrent neural network with probability statistic models for named entity recognition

© Springer International Publishing AG 2017. Named Entity Recognition (NER) is a subtask of information extraction in Natural Language Processing (NLP) field and thus being wildly studied. Currently Recurrent Neural Network (RNN) has become a popular way to do NER task, but it needs a lot of train data. The lack of labeled train data is one of the hard problems and traditional co-training strategy is a way to alleviate it. In this paper, we consider this situation and focus on doing NER with co-training using RNN and two probability statistic models i.e. Hidden Markov Model (HMM) and Conditional Random Field (CRF). We proposed a modified RNN model by redefining its activation function. Compared to traditional sigmoid function, our new function avoids saturation to some degree and makes its output scope very close to [0, 1], thus improving recognition accuracy. Our experiments are conducted ATIS benchmark. First, supervised learning using those models are compared when using different train data size. The experimental results show that it is not necessary to use whole data, even small part of train data can also get good performance. Then, we compare the results of our modified RNN with original RNN. 0.5% improvement is obtained. Last, we compare the co-training results. HMM and CRF get higher improvement than RNN after co-training. Moreover, using our modified RNN in co-training, their performances are improved further

Bi-objective Optimization for Robust RGB-D Visual Odometry

This paper considers a new bi-objective optimization formulation for robust RGB-D visual odometry. We investigate two methods for solving the proposed bi-objective optimization problem: the weighted sum method (in which the objective functions are combined into a single objective function) and the bounded objective method (in which one of the objective functions is optimized and the value of the other objective function is bounded via a constraint). Our experimental results for the open source TUM RGB-D dataset show that the new bi-objective optimization formulation is superior to several existing RGB-D odometry methods. In particular, the new formulation yields more accurate motion estimates and is more robust when textural or structural features in the image sequence are lacking

Vibration Characteristics of Lightweight Floors Using Cold-formed Steel Joist

Presented in this paper are the results of a recent study carried out at the University of Waterloo on vibration characteristics of cold-formed steel-supported residential floor systems and different design criteria available for the evaluation of lightweight floor systems. Laboratory tests were conducted for the floors with different spans and assemblies. Both static and dynamic tests were carried out on the floor systems. The static tests were used to evaluate the stiffness and the load sharing among the joists, while the dynamic tests were used to evaluate the relevant dynamic characteristics, such as natural frequencies and damping ratios, of the floor systems. The test results were then compared with those obtained from different design methods. Concluding remarks regarding the acceptance criteria from the comparison are also presented

Wide field epiretinal micro-electrode-design and feature test

This study was aimed to design and fabricate a wide field implantable epi-retinal microelectrode array for the purpose of retinal repair, and to perform electrochemical test on the array. With parylene as flexible substrate material and Pt as electrode and route material, microelectrode array prototypes was designed and fabricated, and electric characteristics of the array was tested with the three-electrode test system. The feature analysis showed that morphological and electrical properties of the array well met the requirements of implantation and electrical stimulation of retina. The microelectrode array can be put in the in vivo electrophysiological experiments on animal and can perform reliably. © 2013 IEEE.published_or_final_versio