Bandwidth Enhancement of Single-Layer Microstrip Reflectarrays with Multi-Dipole Elements

The gain bandwidth limit of a single-layer microstrip reflectarray is analyzed using multi-dipole elements. By observing the reflection phase characteristics of the multi-dipole elements with different numbers of dipoles, it is shown how the bandwidth can be enhanced by increasing the number of element resonant structures. The fundamental limit of the bandwidth enhancement is then derived by analyzing the coupling between the surface wave and the incident plane wave. It is shown that the surface wave can be excited even with the plane wave of normal incidence on the reflectarray and that the excitation frequency of the surface wave is dominated by array parameters and is almost independent of the number of resonant structures. The degradation of the element reflection characteristics caused by the surface wave, which limits the reflectarray bandwidth, is investigated. By comparing the radiation characteristics of three reflectarrays with three-, five-, and seven-dipole element, respectively, the analysis of the bandwidth enhancement and its limit is verified. The measured 1-dB gain bandwidth of the three-dipole element reflectarray is 25.12%, and the bandwidth is enhanced to 33.52% with the five-dipole element. However, because of the surface wave, no further bandwidth enhancement is achieved when the seven-dipole element is used, as predicted

On the limit of the sequence {Cm(D)}m=1∞\left\{ C^m(D) \right\}_{m=1}^{\infty} for a multipartite tournament DD

For an integer $k \ge 2$, let $A$ be a Boolean block matrix with blocks $A_{ij}$ for $1 \le i,j \le k$ such that $A_{ii}$ is a zero matrix and $A_{ij}+A_{ji}^T$ is a matrix with all elements $1$ but not both corresponding elements of $A_{ij}$ and $A_{ji}^T$ equal to $1$ for $i \neq j$. Jung~{\em et al.} [Competition periods of multipartite tournaments. {\it Linear and Multilinear Algebra}, https://doi.org/10.1080/03081087.2022.2038057] studied the matrix sequence $\{A^m(A^T)^m\}_{m=1}^{\infty}$. This paper, which is a natural extension of the above paper and was initiated by the observation that $\{A^m(A^T)^m\}_{m=1}^{\infty}$ converges if $A$ has no zero rows, computes the limit of the matrix sequence $\{A^m(A^T)^m\}_{m=1}^{\infty}$ if $A$ has no zero rows. To this end, we take a graph theoretical approach: noting that $A$ is the adjacency matrix of a multipartite tournament $D$, we compute the limit of the graph sequence $\left\{ C^m(D) \right\}_{m=1}^{\infty}$ when $D$ has no sinks

Cosimulation of MBD (Multi Body Dynamics) and DEM of many spheres using GPU technology

In this paper, dynamic simulation model which have many sphere particles and MBD (Multi Body Dynamics) entities, i.e. bodies, joints, forces, is built and simulated. Many sphere particles are solved with DEM (Discrete Element Method) and simulated with GPU technology. Fast algorithm is applied to calculate hertzian contact forces between many sphere particles (from 100,000 to 1,000,000) and NVIDIA’s CUDA is used to accelerate the calculation. Explicit integration method is applied to solve the many spheres. MBD (Multi Body Dynamics) entities are simulated with recursive formulation. Constraints are reduced by recursive formulation and implicit generalized alpha method is applied to solve dynamic model. Many sphere particles and MBD (Multi Body Dynamics) entities are co-simulated within commercial software RecurDyn. The interaction forces between many sphere particles and rigid body mesh are calculated and applied to each body to simulate two parts simultaneously. These models are built and simulated; fork lifter with sand model, oil in oil tank model, oil filled engine system and water filled washing machine model. All models are simulated with NVIDIA’s GPU and the result is shown

Expression of matrix metalloproteinases to induce the expression of genes associated with apoptosis during corpus luteum development in bovine

Here we investigated the expressions of apoptosis-associated genes known to induce programed cell death through mRNA expressions of two matrix metalloproteinases (MMPs) that are involved in the degradation of collagen and basal membrane in luteal cells cultured in the treatment media. Our results show that the activity of MMP-2 gelatinase was higher in the CL2 and CL1 of luteal phase, was gradually decreased in the CH2 and CH3 of luteal phase. In particular, the expressions of P4-r and survival-associated genes (IGFr, PI3K, AKT, and mTOR) were strongly induced during CL3 stage, whereas the levels of these genes in corpus luteum (CL) were lower during CL2 and CL1 stages. In the cultured lutein cells analyzed, we found that as MMPs increase, genes related to apoptosis (20α-hydroxy steroid dehydrogenase and caspase-3) also increase. In other words, the results for P4-r and survival-related gene expression patterns in the luteal cells were contrary to the MMPs activation results. These results indicate that active MMPs are differentially expressed to induce the expression of genes associated with programed cell death from the degrading luteal cells. Therefore, our results suggest that the MMPs activation may lead to luteal cell development or death

The predictability of claim-data-based comorbidity-adjusted models could be improved by using medication data

Background : Recently, claim-data-based comorbidity-adjusted methods such as the Charlson index and the Elixhauser comorbidity measures have been widely used among researchers. At the same time, there have been an increasing number of attempts to improve the predictability of comorbidity-adjusted models. We tried to improve the predictability of models using the Charlson and Elixhauser indices by using medication data; specifically, we used medication data to estimate omitted comorbidities in the claim data. Methods : We selected twelve major diseases (other than malignancies) that caused large numbers of in-hospital mortalities during 2008 in hospitals with 700 or more beds in South Korea. Then, we constructed prediction models for in-hospital mortality using the Charlson index and Elixhauser comorbidity measures, respectively. Inferring missed comorbidities using medication data, we built enhanced Charlson and Elixhauser comorbidity-measures-based prediction models, which included comorbidities inferred from medication data. We then compared the c-statistics of each model. Results : 247,712 admission cases were enrolled. 55 generic drugs were used to infer 8 out of 17 Charlson comorbidities, and 106 generic drugs were used to infer 14 out of 31 Elixhauser comorbidities. Before the inclusion of comorbidities inferred from medication data, the c-statistics of models using the Charlson index were 0.633-0.882 and those of the Elixhauser index were 0.699-0.917. After the inclusion of comorbidities inferred from medication data, 9 of 12 models using the Charlson index and all of the models using the Elixhauser comorbidity measures were improved in predictability but, the differences were relatively small. Conclusion : Prediction models using Charlson index or Elixhauser comorbidity measures might be improved by including comorbidities inferred from medication data.This study was accomplished by financial support of the Health Insurance Review and Assessment Service of Korea (HIRA). Original data were provided by the HIRA (Registered No.: 0411-20090054).Peer Reviewe

Effects of a dianion compound as a surface modifier on the back reaction of photogenerated electrons in TiO2-based solar cells

The TiO2 films were modified with a dianion compound, 1,2-ethanedisulfonic acid disodium salt (ESD), to give a negative charge (ethane sulfonate anion) on the TiO2 surface, i.e., TiO2-O-SO2-CH2-CH2-SO3 −), and effects of repulsion between the negative charge and ions (I3 −) of the electrolyte on the performance of dye-sensitized solar cells (DSSCs) were investigated. The reference device without any modification showed a power conversion efficiency (PCE) of 9.89%, whereas for the device with ESD(20)-TiO2/FTO, which was prepared by soaking bare TiO2/FTO in an ESD solution for 20 min, the PCE was increased to 10.97%, due to an increase in both short-circuit current (Jsc) and open-circuit voltage(Voc). It was verified from the measurements of electrochemical impedance, open-circuit voltage decay and dark current that the enhancement in the Jsc and Voc values was attributed to the reduced back reaction between photoinjected electrons and I3 − ions, resulting from the presence of the ethane sulfonate anions on the TiO2 surface. © 2018 King Saud University1

Human dopamine receptor nanovesicles for gate-potential modulators in high-performance field-effect transistor biosensors

The development of molecular detection that allows rapid responses with high sensitivity and selectivity remains challenging. Herein, we demonstrate the strategy of novel bio-nanotechnology to successfully fabricate high-performance dopamine (DA) biosensor using DA Receptor-containing uniform-particle-shaped Nanovesicles-immobilized Carboxylated poly(3,4-ethylenedioxythiophene) (CPEDOT) NTs (DRNCNs). DA molecules are commonly associated with serious diseases, such as Parkinson's and Alzheimer's diseases. For the first time, nanovesicles containing a human DA receptor D1 (hDRD1) were successfully constructed from HEK-293 cells, stably expressing hDRD1. The nanovesicles containing hDRD1 as gate-potential modulator on the conducting polymer (CP) nanomaterial transistors provided high-performance responses to DA molecule owing to their uniform, monodispersive morphologies and outstanding discrimination ability. Specifically, the DRNCNs were integrated into a liquid-ion gated field-effect transistor (FET) system via immobilization and attachment processes, leading to high sensitivity and excellent selectivity toward DA in liquid state. Unprecedentedly, the minimum detectable level (MDL) from the field-induced DA responses was as low as 10 pM in real- time, which is 10 times more sensitive than that of previously reported CP based-DA biosensors. Moreover, the FET-type DRNCN biosensor had a rapid response time (<1 s) and showed excellent selectivity in human serum

Analysis of the Penn Korean Universal Dependency Treebank (PKT-UD): Manual Revision to Build Robust Parsing Model in Korean

In this paper, we first open on important issues regarding the Penn Korean Universal Treebank (PKT-UD) and address these issues by revising the entire corpus manually with the aim of producing cleaner UD annotations that are more faithful to Korean grammar. For compatibility to the rest of UD corpora, we follow the UDv2 guidelines, and extensively revise the part-of-speech tags and the dependency relations to reflect morphological features and flexible word-order aspects in Korean. The original and the revised versions of PKT-UD are experimented with transformer-based parsing models using biaffine attention. The parsing model trained on the revised corpus shows a significant improvement of 3.0% in labeled attachment score over the model trained on the previous corpus. Our error analysis demonstrates that this revision allows the parsing model to learn relations more robustly, reducing several critical errors that used to be made by the previous model.Comment: Accepted by The 16th International Conference on Parsing Technologies, IWPT 202