X-SNS: Cross-Lingual Transfer Prediction through Sub-Network Similarity

Cross-lingual transfer (XLT) is an emergent ability of multilingual language models that preserves their performance on a task to a significant extent when evaluated in languages that were not included in the fine-tuning process. While English, due to its widespread usage, is typically regarded as the primary language for model adaption in various tasks, recent studies have revealed that the efficacy of XLT can be amplified by selecting the most appropriate source languages based on specific conditions. In this work, we propose the utilization of sub-network similarity between two languages as a proxy for predicting the compatibility of the languages in the context of XLT. Our approach is model-oriented, better reflecting the inner workings of foundation models. In addition, it requires only a moderate amount of raw text from candidate languages, distinguishing it from the majority of previous methods that rely on external resources. In experiments, we demonstrate that our method is more effective than baselines across diverse tasks. Specifically, it shows proficiency in ranking candidates for zero-shot XLT, achieving an improvement of 4.6% on average in terms of NDCG@3. We also provide extensive analyses that confirm the utility of sub-networks for XLT prediction.Comment: Accepted to EMNLP 2023 (Findings

Inter-Device Agreement of Retinal Nerve Fiber Layer Thickness Measurements Using Spectral Domain Cirrus HD OCT

PURPOSE: To assess the inter-device agreement of peripapillary retinal nerve fiber layer (RNFL) thickness measurements by 2 spectral domain Cirrus HD optical coherence tomography (OCT) devices in healthy Korean subjects. METHODS: Eleven eyes of 11 healthy volunteers were enrolled in the present study. Each eye was scanned with the Optic Disc Cube 200 x 200 scan of 2 Cirrus HD OCT devices for peripapillary RNFL thickness calculation. The inter-device agreements of the 2 Cirrus HD OCTs for average, quadrant, and clock-hour RNFL thickness values were determined with Wilcoxon signed rank test, Friedman test, Cronbach's alpha (alpha), intraclass correlation coefficient (ICC), coefficient of variation (COV), and Bland-Altman plot. RESULTS: The mean age of the participants was 25.82 +/- 3.28 years and all had a 0.00 logarithm of the minimum angle of resolution of best-corrected visual acuity. The signal strengths of scans from the 2 Cirrus HD OCT were not significantly different (p = 0.317). The inter-device agreement of average RNFL thickness was excellent (alpha, 0.940; ICC, 0.945; COV, 2.45 +/- 1.52%). However, the agreement of nasal quadrant RNFL thickness was not very good (alpha, 0.715; ICC, 0.716; COV, 5.72 +/- 4.64%). Additionally, on the Bland-Atman plot, the extent of agreement of the 2 Cirrus HD OCTs for RNFL thickness was variable according to scanned sectors. CONCLUSIONS: The inter-device agreement of 2 spectral domain Cirrus HD OCT devices for peripapillary RNFL thickness measurements was generally excellent but variable according to the scanned area. Thus, physicians should consider this fact before judging a change of RNFL thicknesses if they were measured by different OCT devices.ope

The Fruit Hull of Gleditsia sinensis

Lung cancer has substantial mortality worldwide, and chemotherapy is a routine regimen for the treatment of patients with lung cancer, despite undesirable effects such as drug resistance and chemotoxicity. Here, given a possible antitumor effect of the fruit hull of Gleditsia sinensis (FGS), we tested whether FGS enhances the effectiveness of cis-diammine dichloridoplatinum (II) (CDDP), a chemotherapeutic drug. We found that CDDP, when administered with FGS, significantly decreased the viability and increased the apoptosis and cell cycle arrest of Lewis lung carcinoma (LLC) cells, which were associated with the increase of p21 and decreases of cyclin D1 and CDK4. Concordantly, when combined with FGS, CDDP significantly reduced the volume and weight of tumors derived from LLC subcutaneously injected into C57BL/6 mice, with concomitant increases of phosphor-p53 and p21 in tumor tissue. Together, these results show that FGS could enhance the antitumor activity of CDDP, suggesting that FGS can be used as a complementary measure to enhance the efficacy of a chemotherapeutic agent such as CDDP

Materialization of single multicomposite nanowire: entrapment of ZnO nanoparticles in polyaniline nanowire

We present materialization of single multicomposite nanowire (SMNW)-entrapped ZnO nanoparticles (NPs) via an electrochemical growth method, which is a newly developed fabrication method to grow a single nanowire between a pair of pre-patterned electrodes. Entrapment of ZnO NPs was controlled via different conditions of SMNW fabrication such as an applied potential and mixture ratio of NPs and aniline solution. The controlled concentration of ZnO NP results in changes in the physical properties of the SMNWs, as shown in transmission electron microscopy images. Furthermore, the electrical conductivity and elasticity of SMNWs show improvement over those of pure polyaniline nanowire. The new nano-multicomposite material showed synergistic effects on mechanical and electrical properties, with logarithmical change and saturation increasing ZnO NP concentration

On Stein's Identity and Near-Optimal Estimation in High-dimensional Index Models

We consider estimating the parametric components of semi-parametric multiple index models in a high-dimensional and non-Gaussian setting. Such models form a rich class of non-linear models with applications to signal processing, machine learning and statistics. Our estimators leverage the score function based first and second-order Stein's identities and do not require the covariates to satisfy Gaussian or elliptical symmetry assumptions common in the literature. Moreover, to handle score functions and responses that are heavy-tailed, our estimators are constructed via carefully thresholding their empirical counterparts. We show that our estimator achieves near-optimal statistical rate of convergence in several settings. We supplement our theoretical results via simulation experiments that confirm the theory

Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event Detection

2D convolution is widely used in sound event detection (SED) to recognize 2D patterns of sound events in time-frequency domain. However, 2D convolution enforces translation-invariance on sound events along both time and frequency axis while sound events exhibit frequency-dependent patterns. In order to improve physical inconsistency in 2D convolution on SED, we propose frequency dynamic convolution which applies kernel that adapts to frequency components of input. Frequency dynamic convolution outperforms the baseline model by 6.3% in DESED dataset in terms of polyphonic sound detection score (PSDS). It also significantly outperforms dynamic convolution and temporal dynamic convolution on SED. In addition, by comparing class-wise F1 scores of baseline model and frequency dynamic convolution, we showed that frequency dynamic convolution is especially more effective for detection of non-stationary sound events. From this result, we verified that frequency dynamic convolution is superior in recognizing frequency-dependent patterns as non-stationary sound events show more intricate time-frequency patterns.Comment: Submitted to INTERSPEECH 202