Luminescence Property of Rare-Earth Doped Bismuth-Borate Glasses

AbstractWe fabricated rare-earth doped bismuth borate glasses by using melt-quench technique. Two different types glass samples of xBi2O3: (100-x)B2O3 (x=30 and 50) were made to compare the luminescence properties. We measured x-ray luminescence of Bi-glass by using a x-ray tube. Several dopants were doped into the Bi-glass to measure the x-ray luminescence such as CeO2, Nd2O3, Er2O3, Dy2O3, Pr2O3, Sm2O3, Ho2O3, Gd2O3 and CeF3. Among them, Dy2O3, Nd2O3 and Sm2O3 doped Bi-glass emitted luminescence. We measured emission spectrum of each samples. Dy2O3 doped bi-glass has emission band at 482nm, 575nm, 662nm and 765nm. Nd2O3 doped bi-glass have emission band at 895nm and Sm2O3 doped Bi-glass has emission band at 569nm, 598nm, 641nm and 705nm. Moreover, Bi-glass scintillators with high light yield with good radiation hardness and low cost can be applied in high energy and nuclear physics, medical imaging, homeland security and radiation detection

Risk Prediction Using Genome-Wide Association Studies on Type 2 Diabetes

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the “large p and small n” problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes

How to Mask in Error Correction Code Transformer: Systematic and Double Masking

In communication and storage systems, error correction codes (ECCs) are pivotal in ensuring data reliability. As deep learning's applicability has broadened across diverse domains, there is a growing research focus on neural network-based decoders that outperform traditional decoding algorithms. Among these neural decoders, Error Correction Code Transformer (ECCT) has achieved the state-of-the-art performance, outperforming other methods by large margins. To further enhance the performance of ECCT, we propose two novel methods. First, leveraging the systematic encoding technique of ECCs, we introduce a new masking matrix for ECCT, aiming to improve the performance and reduce the computational complexity. Second, we propose a novel transformer architecture of ECCT called a double-masked ECCT. This architecture employs two different mask matrices in a parallel manner to learn more diverse features of the relationship between codeword bits in the masked self-attention blocks. Extensive simulation results show that the proposed double-masked ECCT outperforms the conventional ECCT, achieving the state-of-the-art decoding performance with significant margins.Comment: 8 pages, 5 figure

Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar

Boundary integral equation method for resonances in gradient index cavities designed by conformal transformation optics

In the case of two-dimensional gradient index cavities designed by the conformal transformation optics, we propose a boundary integral equation method for the calculation of resonant mode functions by employing a fictitious space which is reciprocally equivalent to the physical space. Using the Green's function of the interior region of the uniform index cavity in the fictitious space, resonant mode functions and their far-field distributions in the physical space can be obtained. As a verification, resonant modes in lima\c{c}on-shaped transformation cavities were calculated and mode patterns and far-field intensity distributions were compared with those of the same modes obtained from the finite element method.Comment: 13 pages, 6 figure

Facile synthesis of metal-free organic dyes featuring a thienylethynyl spacer for dye sensitized solar cells

In this article, we report the facile synthesis of metal-free dyes 6 and 7, their solution-based optical and redox properties and their use as sensitizers in dye-sensitized solar cells (DSSCs). Our studies indicate that the addition of the second thiophene unit in dye 7, decreases the oxidation and reduction potential and consequently the band gap of the molecule compared to 6. Furthermore, increasing the length of the conjugated spacer also affects on the properties of the DSSCs, with dye 7 providing a higher power conversion efficiency compared to 6 (η = 4.49 versus 3.23%)