Uniform Microgels Containing Agglomerates of Silver Nanocubes for Molecular Size‐Selectivity and High SERS Activity

Surface‐enhanced Raman scattering (SERS) is a promising technique for molecular analysis as the molecular fingerprints (Raman spectra) are amplified to detectable levels compared with common spectroscopy. Metal nanostructures localize electromagnetic field on their surfaces, which can lead to dramatic increase of Raman intensity of molecules adsorbed. However, the metal surfaces are prone to contamination, thereby requiring pretreatment of samples to remove adhesive molecules. To avoid the pretreatment and potentially achieve point‐of‐care (POC) analysis, we have developed SERS‐active microgels using the droplet‐microfluidic system. As the microgels are composed of water‐swollen network with consistent mesh size, they selectively allow diffusion of molecules smaller than the mesh, thereby excluding large adhesives. To render the microgels highly SERS‐active, we destabilize silver nanocubes to form agglomerates, which are embedded in the matrix of microgels. The nanogaps in the agglomerates provide high sensitivity in Raman measurement and size‐selective permeability of the microgel matrix obviates the pretreatment of samples. To validate the functions, we demonstrate the direct detection of Aspirin dissolved in whole blood without any pretreatment.     

A highly sensitive chemical gas detecting transistor based on highly crystalline CVD-grown MoSe<Subscript>2</Subscript> films

Layered semiconductors with atomic thicknesses are becoming increasingly important as active elements in high-performance electronic devices owing to their high carrier mobilities,large surface-to-volume ratios,and rapid electrical responses to their surrounding environments.Here,we report the first implementation of a highly sensitive chemical-vapor-deposition-grown multilayer MoSe2 field-effect transistor (FET) in a NO2 gas sensor.This sensor exhibited ultra-high sensitivity (S =ca.1,907 for NO2 at 300 ppm),real-time response,and rapid on-off switching.The high sensitivity of our MoSe2 gas sensor is attributed to changes in the gap states near the valence band induced by the NO2 gas absorbed in the MoSe2,which leads to a significant increase in hole current in the off-state regime.Device modeling and quantum transport simulations revealed that the variation of gap states with NO2 concentration is the key mechanism in a MoSe2 FET-based NO2 gas sensor.This comprehensive study,which addresses material growth,device fabrication,characterization,and device simulations,not only indicates the utility of MoSe2 FETs for high-performance chemical sensors,but also establishes a fundamental understanding of how surface chemistry influences carrier transport in layered semiconductor devices.     

Action rule discovery from incomplete data

Action rule is an implication rule that shows the expected change in a decision value of an object as a result of changes made to some of its conditional values. An example of an action rule is ‘credit card holders of young age are expected to keep their cards for an extended period of time if they receive a movie ticket once a year’. In this case, the decision value is the account status, and the condition value is whether the movie ticket is sent to the customer. The type of action that can be taken by the company is to send out movie tickets to young customers. The conventional action rule discovery algorithms build action rules from existing classification rules. This paper discusses an agglomerative strategy that generates the shortest action rules directly from a decision system. In particular, the algorithm can be used to discover rules from an incomplete decision system where attribute values are partially incomplete. As one of the testing domains for our research we take HEPAR system that was built through a collaboration between the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences and physicians at the Medical Center of Postgraduate Education in Warsaw, Poland. HEPAR was designed for gathering and processing clinical data on patients with liver disorders. Action rules will be used to construct the decision-support module for HEPAR.     

Motion control of an omnidirectional mobile platform for trajectory tracking using an integral sliding mode controller

In this paper, a new tracking controller that integrates a kinematic controller (KC) with an integral sliding mode dynamic controller (ISMC) is designed for an omnidirectional mobile platform (OMP) to track a desired trajectory at a desired velocity. First, a posture tracking error vector is defined, and a kinematic controller (KC) is chosen to make the posture tracking error vector convergent to zero asymptotically. Second, an integral sliding surface vector is defined based on the angular velocity tracking error vector and its integral term. An integral sliding mode dynamic controller (ISMC) is designed to make the integral sliding surface vector and the angular velocity tracking error vector convergent to zero asymptotically. The above controllers are obtained based on the Lyapunov stability theory. To implement the designed tracking controller, a control system is developed based on PIC18F452. A scheme for measuring the posture tracking error vector using a camera sensor combined with an angular sensor is introduced. The simulation and experimental results are presented to illustrate the effectiveness and applicability of the proposed tracking controller.     

Stochastic distributed data stream partitioning using task locality: design,implementation, and optimization

The Journal of Supercomputing - Distributed stream processing engines (DSPEs) provide stream partitioning methods for distributing messages to tasks deployed in the distributed environment for...     

The Farthest Spatial Skyline Queries

Pareto-optimal objects are favored as each of such objects has at least one competitive edge against all other objects, or “not dominated”. Recently, in the database literature, skyline queries have gained attention as an effective way to identify such pareto-optimal objects. In particular, this paper studies the pareto-optimal objects in perspective of facility or business locations. More specifically, given data points P and query points Q in two-dimensional space, our goal is to retrieve data points that are farther from at least one query point than all the other data points. Such queries are helpful in identifying spatial locations far away from undesirable locations, e.g., unpleasant facilities or business competitors. To solve this problem, we first study a baseline Algorithm TFSS and propose an efficient progressive Algorithm BBFS, which significantly outperforms TFSS by exploiting spatial locality. We also develop an efficient approximation algorithm to trade accuracy for efficiency. We validate our proposed algorithms using extensive evaluations over synthetic and real datasets.     

Sintering period dependence of composition and superconducting properties of (BiPb)SrCaCu,1.8Ox system

The material system (Bi_0.7Pb_0.3)Sr₁ Ca₁ Cu_1.8O _x forms, at 840° C, two major phases having a highT _c (100K) and a lowT _c (70 K) both of which consist of platelets and a non-superconducting minor phase which has a rod-like shape and is isolated by the major phases. As the sintering period increases, the amount of highT _c phase increases accompanying the decrease in lowT _c phase while the amount of the non-superconducting phase is independent of sintering period, resulting in a superconductor withT _c of 100 K. Changes in compositions of each phase also occur during sintering due to evaporation of bismuth and lead.     

Analysis of void closure in open-die forging

Void closure studies have been conducted numerically and experimentally for open-die forging processes. The plane-strain FEM analysis was compared with bite forging experiments in order to determine how well the plane-strain approximation predicted the material flow in open-die forging. In addition physical modeling with plasticine was used to compare the measured and calculated deformation of the internal defect. The FEM analysis was in good agreement with the experimental results. Correlations for the computed effective strain and hydrostatic stress to the void closure were then calculated. Simulations of a solid cylinder side pressed with flat dies, V-shaped dies, and FML dies were done to determine the effectiveness of these dies at consolidating internal porosity based on the calculated strain and hydrostatic stress at the center of the billet. The V-shaped dies were found to be the most effective among those investigated. However, the press load for the V-shaped dies was also the highest.     

Enhanced longterm stability of aluminum solid electrolyte capacitor containing thiophene derivatives as a solid electrolyte

The derivatives of thiophene, 3,4-ethylene-1-methyl-2-oxy-5-thio-thiophene (EMOTT) and 3,4-ethylene-1-propyl-2-oxy-5-thio-thiophene (EPOTT), are synthesized and then, 3,4-ethylenedioxythiophene (EDOT), EMOTT, and EPOTT are polymerized with ferric 4-methylbenzenesulfonate (oxidant) to obtain PEDOT-OMBs, PEMOTT-OMBs, and PEPOTT-OMBs, respectively. The surface conductivity of PEDOT-OMBs shows the highest value among the fabricated materials because PEDOT-OMBs shows the better defined crystalline structure and the doping concentration of PEDOT-OMBs is much higher than that of PEMOTT-OMBs and PEPOTT-OMBs. Capacitance and equivalent series resistance (ESR) of PEDOT-OMBs show the slightly enhanced value compared to PEMOTT-OMBs and PEPOTT-OMBs because of high electrical conductivity of PEDOT-OMBs. The PEDOT-OMBs shows the highest decrease rate of capacitance and increase rate of ESR because the extent of separation between the PEDOT-OMBs and the dielectric is much larger than that of PEMOTT-OMBs and PEPOTT-OMBs since it has the lowest density and hardness compared to other polymerized materials.     

Vision-Based Indoor Localization for Unmanned Aerial Vehicles

Small unmanned aerial vehicles are cost-effective and easy to operate, and especially suitable in dangerous indoor environments. However, because GPS is not available in an indoor environment, indoor localization is a crucial problem in developing small unmanned aerial vehicles (UAVs). This paper suggests vision-based indoor localization for UAVs in GPS-denied environments. Our approach is based on image matching by applying the scale invariant feature transform algorithm.