Plasmonic Circular Nanostructure for Enhanced Light Absorption in Organic Solar Cells

This study attempts to enhance broadband absorption in advanced plasmonic circular nanostructures (PCN). Experimental results indicate that the concentric circular metallic gratings can enhance broadband optical absorption, due to the structure geometry and the excitation of surface plasmon mode. The interaction between plasmonic enhancement and the absorption characteristics of the organic materials (P3HT:PCBM and PEDOT:PSS) are also examined. According to those results, the organic material's overall optical absorption can be significantly enhanced by up to ~51% over that of a planar device. Additionally, organic materials are enhanced to a maximum of 65% for PCN grating pitch = 800 nm. As a result of the PCN's enhancement in optical absorption, incorporation of the PCN into P3HT:PCBM-based organic solar cells (OSCs) significantly improved the performance of the solar cells: short-circuit current increased from 10.125 to 12.249 and power conversion efficiency from 3.2% to 4.99%. Furthermore, optimizing the OSCs architectures further improves the performance of the absorption and PCE enhancement

On the Momentum Dependence of the Flavor Structure of the Nucleon Sea

Difference between the $\bar u$ and $\bar d$ sea quark distributions in the proton was first observed in the violation of the Gottfried sum rule in deep-inelastic scattering (DIS) experiments. The parton momentum fraction $x$ dependence of this difference has been measured over the region $0.02 < x < 0.35$ from Drell-Yan and semi-inclusive DIS experiments. The Drell-Yan data suggested a possible sign-change for $\bar d(x)-\bar u(x)$ near $x \sim 0.3$, which has not yet been explained by existing theoretical models. We present an independent evidence for the $\bar d(x)-\bar u(x)$ sign-change at $x \sim 0.3$ from an analysis of the DIS data. We further discuss the $x$-dependence of $\bar d(x)-\bar u(x)$ in the context of meson cloud model and the lattice QCD formulation.Comment: 5 pages, 5 figures, final versio

A case of acute appendicitis with Vibrio fluvialis peritonitis

AbstractHuman infections caused by Vibrio fluvialis are rarely reported. The most common clinical presentation of V. fluvialis infection is acute gastroenteritis with diarrhea. Reported extra-intestinal infections caused by V. fluvialis have included bacteremia, hemorrhagic cellulitis and cerebritis. Peritonitis is an uncommon clinical presentation of Vibrio infections, and most cases have occurred in patients receiving peritoneal dialysis or those with liver cirrhosis. Herein, we report the first case of acute appendicitis with V. fluvialis peritonitis

Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement

Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems. In this paper, we introduce a novel audio-visual SE approach, termed DCUC-Net (deep complex U-Net with conformer network). The proposed DCUC-Net leverages complex domain features and a stack of conformer blocks. The encoder and decoder of DCUC-Net are designed using a complex U-Net-based framework. The audio and visual signals are processed using a complex encoder and a ResNet-18 model, respectively. These processed signals are then fused using the conformer blocks and transformed into enhanced speech waveforms via a complex decoder. The conformer blocks consist of a combination of self-attention mechanisms and convolutional operations, enabling DCUC-Net to effectively capture both global and local audio-visual dependencies. Our experimental results demonstrate the effectiveness of DCUC-Net, as it outperforms the baseline model from the COG-MHEAR AVSE Challenge 2023 by a notable margin of 0.14 in terms of PESQ. Additionally, the proposed DCUC-Net performs comparably to a state-of-the-art model and outperforms all other compared models on the Taiwan Mandarin speech with video (TMSV) dataset

Mechanics of Optimal Structural Design for Extreme Loads to Peak System Responses

[[abstract]]Over the past decades, with the development of modern manufacturing and information technology, demands of smart and economical structural designs have been increasing considerably. Central to this engineering issue is that a good structural design needs to embrace both necessary capabilities to afford critical load distributions and the best arrangement of materials serving the performance criteria using limited resources. Here, a new analysis technique is proposed to achieve optimal structural designs considering peak system responses as design constraints respective to extreme load distributions. We anticipate that the technique will open a door for designing efficient structural systems which satisfy safety requirements under various sophisticated loadings from the environment.[[sponsorship]]Tamkang University[[sponsorship]]Taiwan Association of Wind Engineering[[sponsorship]]Institute of Theoretical and Applied Mechanics, Academy of Sciences of the Czech Republic[[conferencetype]]國際[[conferencetkucampus]]淡水校園[[conferencedate]]20151101~20151102[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]New Taipe

Audio-Visual Speech Enhancement and Separation by Leveraging Multi-Modal Self-Supervised Embeddings

AV-HuBERT, a multi-modal self-supervised learning model, has been shown to be effective for categorical problems such as automatic speech recognition and lip-reading. This suggests that useful audio-visual speech representations can be obtained via utilizing multi-modal self-supervised embeddings. Nevertheless, it is unclear if such representations can be generalized to solve real-world multi-modal AV regression tasks, such as audio-visual speech enhancement (AVSE) and audio-visual speech separation (AVSS). In this study, we leveraged the pre-trained AV-HuBERT model followed by an SE module for AVSE and AVSS. Comparative experimental results demonstrate that our proposed model performs better than the state-of-the-art AVSE and traditional audio-only SE models. In summary, our results confirm the effectiveness of our proposed model for the AVSS task with proper fine-tuning strategies, demonstrating that multi-modal self-supervised embeddings obtained from AV-HuBERT can be generalized to audio-visual regression tasks.Comment: ICASSP AMHAT 202

Assembling a cellulase cocktail and a cellodextrin transporter into a yeast host for CBP ethanol production

Background: Many microorganisms possess enzymes that can efficiently degrade lignocellulosic materials, but donot have the capability to produce a large amount of ethanol. Thus, attempts have been made to transform suchenzymes into fermentative microbes to serve as hosts for ethanol production. However, an efficient host for aconsolidated bioprocess (CBP) remains to be found. For this purpose, a synthetic biology technique that cantransform multiple genes into a genome is instrumental. Moreover, a strategy to select cellulases that interactsynergistically is needed.Results: To engineer a yeast for CBP bio-ethanol production, a synthetic biology technique, called “promoter-basedgene assembly and simultaneous overexpression” (PGASO), that can simultaneously transform and express multiplegenes in a kefir yeast, Kluyveromyces marxianus KY3, was recently developed. To formulate an efficient cellulasecocktail, a filter-paper-activity assay for selecting heterologous cellulolytic enzymes was established in this study andused to select five cellulase genes, including two cellobiohydrolases, two endo-β-1,4-glucanases and onebeta-glucosidase genes from different fungi. In addition, a fungal cellodextrin transporter gene was chosen totransport cellodextrin into the cytoplasm. These six genes plus a selection marker gene were one-step assembledinto the KY3 genome using PGASO. Our experimental data showed that the recombinant strain KR7 could expressthe five heterologous cellulase genes and that KR7 could convert crystalline cellulose into ethanol.Conclusion: Seven heterologous genes, including five cellulases, a cellodextrin transporter and a selection marker,were simultaneously transformed into the KY3 genome to derive a new strain, KR7, which could directly convertcellulose to ethanol. The present study demonstrates the potential of our strategy of combining a cocktailformulation protocol and a synthetic biology technique to develop a designer yeast host