Hi,KIA: A Speech Emotion Recognition Dataset for Wake-Up Words

Wake-up words (WUW) is a short sentence used to activate a speech recognition system to receive the user's speech input. WUW utterances include not only the lexical information for waking up the system but also non-lexical information such as speaker identity or emotion. In particular, recognizing the user's emotional state may elaborate the voice communication. However, there is few dataset where the emotional state of the WUW utterances is labeled. In this paper, we introduce Hi, KIA, a new WUW dataset which consists of 488 Korean accent emotional utterances collected from four male and four female speakers and each of utterances is labeled with four emotional states including anger, happy, sad, or neutral. We present the step-by-step procedure to build the dataset, covering scenario selection, post-processing, and human validation for label agreement. Also, we provide two classification models for WUW speech emotion recognition using the dataset. One is based on traditional hand-craft features and the other is a transfer-learning approach using a pre-trained neural network. These classification models could be used as benchmarks in further research.Comment: Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), 202

A Circuit Model for ESD Performance Analysis of Printed Circuit Boards

This paper provides a SPICE-compatible circuit model for characterizing electrostatic discharge (ESD) clamping performance of protection devices mounted on printed circuit boards (PCBs). An equivalent circuit model for a commercial ESD generator is introduced and a simulation methodology of an ESD protection device with non-linear resistance characteristic using voltage controlled current source is described. These models combined to create a full circuit model with a PCB model in a SPICE-like circuit simulator. Comparison results between the simulated and measured are presented to verify the accuracy of the proposed circuit model. A trade-off analysis between the ESD clamping performance and signal integrity with the ESD protection device in high-speed applications is also presented as a case study

Optic neuritis associated with seronegative autoimmune encephalitis: a case report

Optic neuritis is an inflammatory demyelinating disorder that primarily affects the optic nerve and is often associated with multiple sclerosis. While it is rare for optic neuritis to be accompanied by autoimmune encephalitis, it can occur in some cases. A 65-year-old woman with bipolar disorder presented with a progressively altered mentality. Magnetic resonance imaging of the brain showed no definite abnormal findings. Electroencephalography revealed nonconvulsive status epilepticus. Cerebrospinal fluid study and autoimmune and paraneoplastic encephalitis antibodies were negative. The patient was diagnosed with seronegative autoimmune encephalitis and treated with methylprednisolone, intravenous immunoglobulin, and rituximab. Her condition gradually improved except for persistent blindness on the left side. This case highlights the importance of considering autoimmune encephalitis even in the absence of identifiable pathogenic antibodies when clinical manifestations and response to immunotherapy support such a diagnosis

A comparison of phenotypic and WGS drug susceptibility testing in Mycobacterium tuberculosis isolates from the Republic of Korea

BACKGROUND: WGS has significant potential to help tackle the major public health problem of TB. The Republic of Korea has the third highest rates of TB of all Organisation for Economic Cooperation and Development countries but there has been very limited use of WGS in TB to date. OBJECTIVES: A retrospective comparison of Mycobacterium tuberculosis (MTB) clinical isolates from 2015 to 2017 from two centres in the Republic of Korea using WGS to compare phenotypic drug susceptibility testing (pDST) and WGS drug susceptibility predictions (WGS-DSP). METHODS: Fifty-seven MTB isolates had DNA extracted and were sequenced using the Illumina HiSeq platform. The WGS analysis was performed using bwa mem, bcftools and IQ-Tree; resistance markers were identified using TB profiler. Phenotypic susceptibilities were carried out at the Supranational TB reference laboratory (Korean Institute of Tuberculosis). RESULTS: For first-line antituberculous drugs concordance for rifampicin, isoniazid, pyrazinamide and ethambutol was 98.25%, 92.98%, 87.72% and 85.96%, respectively. The sensitivity of WGS-DSP compared with pDST for rifampicin, isoniazid, pyrazinamide and ethambutol was 97.30%, 92.11%, 78.95% and 95.65%, respectively. The specificity for these first-line antituberculous drugs was 100%, 94.74%, 92.11% and 79.41%, respectively. The sensitivity and specificity for second-line drugs ranged from 66.67% to 100%, and from 82.98% to 100%, respectively. CONCLUSIONS: This study confirms the potential role for WGS in drug susceptibility prediction, which would reduce turnaround times. However, further larger studies are needed to ensure current databases of drug resistance mutations are reflective of the TB present in the Republic of Korea

Weighted-DESYNC and Its Application to End-to-End Throughput Fairness in Wireless Multihop Network

The end-to-end throughput of a routing path in wireless multihop network is restricted by a bottleneck node that has the smallest bandwidth among the nodes on the routing path. In this study, we propose a method for resolving the bottleneck-node problem in multihop networks, which is based on multihop DESYNC (MH-DESYNC) algorithm that is a bioinspired resource allocation method developed for use in multihop environments and enables fair resource allocation among nearby (up to two hops) neighbors. Based on MH-DESYNC, we newly propose weighted-DESYNC (W-DESYNC) as a tool artificially to control the amount of resource allocated to the specific user and thus to achieve throughput fairness over a routing path. Proposed W-DESYNC employs the weight factor of a link to determine the amount of bandwidth allocated to a node. By letting the weight factor be the link quality of a routing path and making it the same across a routing path via Cucker-Smale flocking model, we can obtain throughput fairness over a routing path. The simulation results show that the proposed algorithm achieves throughput fairness over a routing path and can increase total end-to-end throughput in wireless multihop networks

Intracellular gallium nitride microrod laser

We report laser emission from gallium nitride (GaN) microrods that are introduced into mammalian cells and the application of these microrods for cell labeling. GaN microrods were grown on graphene-coated SiO2/Si substrates by metal-organic vapor phase epitaxy. The GaN microrods are easily detached from the substrates because of the weakness of the van der Waals forces between GaN and graphene. The uptake of microrods into HeLa cells via endocytosis and viability after uptake were investigated. Normal cellular activities, including migration and division, were observed over 2 weeks in culture. Furthermore, the photoluminescence spectra of the internalized microrods exhibited sharp laser emission peaks with a low lasing threshold of 270kW/cm(2)

Enhanced Immunogenicity of Engineered HER2 Antigens Potentiates Antitumor Immune Responses

For cancer vaccines, the selection of optimal tumor-associated antigens (TAAs) that can maximize the immunogenicity of the vaccine without causing unwanted adverse effects is challenging. In this study, we developed two engineered Human epidermal growth factor receptor 2 (HER2) antigens, K965 and K1117, and compared their immunogenicity to a previously reported truncated HER2 antigen, K684, within a B cell and monocyte-based vaccine (BVAC). We found that BVAC-K965 and BVAC-K1117 induced comparable antigen-specific antibody responses and antigen-specific T cell responses to BVAC-K684. Interestingly, BVAC-K1117 induced more potent antitumor activity than the other vaccines in murine CT26-HER2 tumor models. In addition, BVAC-K1117 showed enhanced antitumor effects against truncated p95HER2-expressing CT26 tumors compared to BVAC-K965 and BVAC-K684 based on the survival analysis by inducing T cell responses against intracellular domain (ICD) epitopes. The increased ICD epitope-specific T cell responses induced by BVAC-K1117 compared to BVAC-K965 and BVAC-K684 were recapitulated in human leukocyte antigen (HLA)-untyped human PBMCs and HLA-A*0201 PBMCs. Furthermore, we also observed synergistic antitumor effects between BVAC-K1117 and anti-PD-L1 antibody treatment against CT26-HER2 tumors. Collectively, our findings demonstrate that inclusion of a sufficient number of ICD epitopes of HER2 in cellular vaccines can improve the antitumor activity of the vaccine and provide a way to optimize the efficacy of anticancer cellular vaccines targeting HER2.Y

Performance of a silica-polyethyleneimine adsorbent for post-combustion CO2 capture on a 100 kg scale in a fluidized bed continuous unit

© 2020 Elsevier B.V. Polyethyleneimine (PEI)/silica adsorbents have been considered as a promising candidate for post-combustion CO2 capture, but the limited process study has been performed on a pilot-scale unit. Herein we report the 150 h continuous test results using a 100 kg sample of silica-PEI on a fluidized bed continuous unit. The CO2 removal efficiency and dynamic sorption capacity were evaluated continuously by changing a number of variables. For the sorption reactor, the changing variables were inlet H2O concentrations of 0–8.3 vol%, inlet CO2 concentrations of 12.0–21.5 vol%, bed temperatures of 50–70 °C and the bed differential pressures of 176–370 mmH2O. For the desorption reactor operated at the bed temperature of 129–130 °C, inlet H2O concentrations of 8.0–13.5 vol%, inlet CO2 concentrations of 14.6–81.2 vol% and bed differential pressures of 430–580 mmH2O were used. During continuous operation, CO2 removal efficiencies of over 90% were achieved with dynamic sorption capacities of 7.5 wt%. Solid sample collected during continuous operation were analyzed by TGA and 13C NMR to identity the decrease of CO2 adsorption capacity and the extent of thermo-oxidative side reactions. Slow oxidative degradation of the silica-PEI occurred because the transporting adsorbent was exposure to the non-humidified air in the solid transport system

Engineering In vitro Models: Bioprinting of Organoids with Artificial Intelligence

In the last decade, organoids have gained popularity for developing mini-organs to support advancements in the study of organogenesis, disease modeling, and drug screening and, subsequently, in the development of new therapies. To date, such cultures have been used to replicate the composition and functionality of organs such as the kidney, liver, brain, and pancreas. However, depending on the experimenter, the culture environment and cell conditions may slightly vary, resulting in different organoids; this factor significantly affects their application in new drug development, especially during quantification. Standardization in this context can be achieved using bioprinting technology—an advanced technology that can print various cells and biomaterials at desired locations. This technology offers numerous advantages, including the manufacturing of complex three-dimensional biological structures. Therefore, in addition to the standardization of organoids, bioprinting technology in organoid engineering can facilitate automation in the fabrication process as well as a closer mimicry of native organs. Further, artificial intelligence (AI) has currently emerged as an effective tool to monitor and control the quality of final developed objects. Thus, organoids, bioprinting technology, and AI can be combined to obtain high-quality in vitro models for multiple applications