Fabrication of Embedded Microvalve on PMMA Microfluidic Devices through Surface Functionalization

The integration of a PDMS membrane within orthogonally placed PMMA microfluidic channels enables the pneumatic actuation of valves within bonded PMMA-PDMS-PMMA multilayer devices. Here, surface functionalization of PMMA substrates via acid catalyzed hydrolysis and air plasma corona treatment were investigated as possible techniques to permanently bond PMMA microfluidic channels to PDMS surfaces. FTIR and water contact angle analysis of functionalized PMMA substrates showed that air plasma corona treatment was most effective in inducing PMMA hydrophilicity. Subsequent fluidic tests showed that air plasma modified and bonded PMMA multilayer devices could withstand fluid pressure at an operational flow rate of 9 mircoliters/min. The pneumatic actuation of the embedded PDMS membrane was observed through optical microscopy and an electrical resistance based technique. PDMS membrane actuation occurred at pneumatic pressures of as low as 10kPa and complete valving occurred at 14kPa for 100 micrometers x 100 micrometers channel cross-sections.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

An ultrafast 1 x M all-optical WDM packet-switched router based on the PPM header address

This paper presents an all-optical 1 x M WDM router architecture for packet routing at multiple wavelengths simultaneously, with no wavelength conversion modules. The packet header address adopted is based on the pulse position modulation (PPM) format, thus enabling the use of only a singlebitwise optical AND gate for fast header address correlation. It offers multicast as well as broadcast capabilities. It is shown that a high speed packet routing at 160 Gb/s can be achieved with a low channel crosstalk (CXT) of ~ -27 dB at a channel spacing of greater than 0.4 THz and a demultiplexer bandwidth of 500 GHz

Double intelligent reflecting surface-assisted multi-user MIMO mmWave systems with hybrid precoding

This work investigates the effect of double intelligent reflecting surface (IRS) in improving the spectrum efficient of multi-user multiple-input multiple-output (MIMO) network operating in the millimeter wave (mmWave) band. Specifically, we aim to solve a weighted sum rate maximization problem by jointly optimizing the digital precoding at the transmitter and the analog phase shifters at the IRS, subject to the minimum achievable rate constraint. To facilitate the design of an efficient solution, we first reformulate the original problem into a tractable one by exploiting the majorization-minimization (MM) method. Then, a block coordinate descent (BCD) method is proposed to obtain a suboptimal solution, where the precoding matrices and the phase shifters are alternately optimized. Specifically, the digital precoding matrix design problem is solved by the quadratically constrained quadratic programming (QCQP), while the analog phase shift optimization is solved by the Riemannian manifold optimization (RMO). The convergence and computational complexity are analyzed. Finally, simulation results are provided to verify the performance of the proposed design, as well as the effectiveness of double-IRS in improving the spectral efficiency

Masked Gradient-Based Causal Structure Learning

This paper studies the problem of learning causal structures from observational data. We reformulate the Structural Equation Model (SEM) in an augmented form with a binary graph adjacency matrix and show that, if the original SEM is identifiable, then this augmented form can be identified up to super-graphs of the true causal graph under mild conditions. Three methods are further provided to remove spurious edges to recover the true graph. We next utilize the augmented form to develop a masked structure learning method that can be efficiently trained using gradient-based optimization methods, by leveraging a smooth characterization on acyclicity and the Gumbel-Softmax approach to approximate the binary adjacency matrix. It is found that the obtained entries are typically near zero or one, and can be easily thresholded to identify the edges. We conduct experiments on synthetic and real datasets to validate the effectiveness of the proposed method and show that the method can readily include different smooth functions to model causal relationships

Proximity fingerprint of s+- superconductivity

We suggest a straightforward and unambiguous test to identify possible opposite signs of superconducting order parameter in different bands proposed for iron-based superconductors (s+- state). We consider proximity effect in a weakly coupled sandwich composed of a s+- superconductor and thin layer of s-wave superconductor. In such system the s-wave order parameter is coupled differently with different s+- gaps and it typically aligns with one of these gaps. This forces the other s+- gap to be anti-aligned with the s-wave gap. In such situation the aligned band induces a peak in the s-wave density of states (DoS), while the anti-aligned band induces a dip. Observation of such contact-induced negative feature in the s-wave DoS would provide a definite proof for s+- superconductivity.Comment: 4 pages, one figur