Distributed Estimation and Inference for Spatial Autoregression Model with Large Scale Networks

The rapid growth of online network platforms generates large-scale network data and it poses great challenges for statistical analysis using the spatial autoregression (SAR) model. In this work, we develop a novel distributed estimation and statistical inference framework for the SAR model on a distributed system. We first propose a distributed network least squares approximation (DNLSA) method. This enables us to obtain a one-step estimator by taking a weighted average of local estimators on each worker. Afterwards, a refined two-step estimation is designed to further reduce the estimation bias. For statistical inference, we utilize a random projection method to reduce the expensive communication cost. Theoretically, we show the consistency and asymptotic normality of both the one-step and two-step estimators. In addition, we provide theoretical guarantee of the distributed statistical inference procedure. The theoretical findings and computational advantages are validated by several numerical simulations implemented on the Spark system. Lastly, an experiment on the Yelp dataset further illustrates the usefulness of the proposed methodology

OR Residual Connection Achieving Comparable Accuracy to ADD Residual Connection in Deep Residual Spiking Neural Networks

Spiking Neural Networks (SNNs) have garnered substantial attention in brain-like computing for their biological fidelity and the capacity to execute energy-efficient spike-driven operations. As the demand for heightened performance in SNNs surges, the trend towards training deeper networks becomes imperative, while residual learning stands as a pivotal method for training deep neural networks. In our investigation, we identified that the SEW-ResNet, a prominent representative of deep residual spiking neural networks, incorporates non-event-driven operations. To rectify this, we introduce the OR Residual connection (ORRC) to the architecture. Additionally, we propose the Synergistic Attention (SynA) module, an amalgamation of the Inhibitory Attention (IA) module and the Multi-dimensional Attention (MA) module, to offset energy loss stemming from high quantization. When integrating SynA into the network, we observed the phenomenon of "natural pruning", where after training, some or all of the shortcuts in the network naturally drop out without affecting the model's classification accuracy. This significantly reduces computational overhead and makes it more suitable for deployment on edge devices. Experimental results on various public datasets confirmed that the SynA enhanced OR-Spiking ResNet achieved single-sample classification with as little as 0.8 spikes per neuron. Moreover, when compared to other spike residual models, it exhibited higher accuracy and lower power consumption. Codes are available at https://github.com/Ym-Shan/ORRC-SynA-natural-pruning.Comment: 16 pages, 8 figures and 11table

Two new genera of Apsilocephalidae from mid-Cretaceous Burmese amber

Apsilocephalidae is an enigmatic dipteran family erected by Nagatomi et al. (1991), including three extant genera and three additional extinct genera from the Eocene Baltic amber, Eocene Florissant, and mid-Cretaceous Burmese amber. We describe herein two new taxa, Myanmarpsilocephala grimaldii gen. et sp. nov. and Irwinimyia spinosa gen. et sp. nov., from mid-Cretaceous Burmese amber. The female genitalia of Myanmarpsilocephala gen. nov. and male genitalia of Irwinimyia gen. nov. are described and illustrated. The distribution of all Apsilocephalidae species and a key to all genera of Apsilocephalidae is provided. The described diversity of Apsilocephalidae in Burmese amber strongly suggests that apsilocephalid flies diversified at least by the mid-Cretaceous.This research was supported by the National Natural Science Foundation of China (41572010, 41622201, 41688103), the Chinese Academy of Sciences (XDPB05), and Youth Innovation Promotion Association of CAS (No. 2011224)

Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training

We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference. Our method incorporates a gating mechanism and LID loss, enabling transformer experts to learn language-specific information. By combining gated transformer experts with shared transformer layers, we construct multilingual transformer blocks and utilize linear experts to effectively regularize the joint network. The curriculum training scheme leverages LID to guide the gated experts in improving their respective language performance. Experimental results on a bilingual task involving English and Spanish demonstrate significant improvements, with average relative word error reductions of 12.5% and 7.3% compared to the baseline bilingual and monolingual models, respectively. Notably, our method achieves performance comparable to the upper-bound model trained and inferred with oracle LID. Extending our approach to trilingual, quadrilingual, and pentalingual models reveals similar advantages to those observed in the bilingual models, highlighting its ease of extension to multiple languages

On decoder-only architecture for speech-to-text and large language model integration

Large language models (LLMs) have achieved remarkable success in the field of natural language processing, enabling better human-computer interaction using natural language. However, the seamless integration of speech signals into LLMs has not been explored well. The "decoder-only" architecture has also not been well studied for speech processing tasks. In this research, we introduce Speech-LLaMA, a novel approach that effectively incorporates acoustic information into text-based large language models. Our method leverages Connectionist Temporal Classification and a simple audio encoder to map the compressed acoustic features to the continuous semantic space of the LLM. In addition, we further probe the decoder-only architecture for speech-to-text tasks by training a smaller scale randomly initialized speech-LLaMA model from speech-text paired data alone. We conduct experiments on multilingual speech-to-text translation tasks and demonstrate a significant improvement over strong baselines, highlighting the potential advantages of decoder-only models for speech-to-text conversion

Topological Edge Transport in Twisted Double-Bilayer Graphene

Topological insulators realized in materials with strong spin-orbit interactions challenged the long-held view that electronic materials are classified as either conductors or insulators. The emergence of controlled, two-dimensional moire patterns has opened new vistas in the topological materials landscape. Here we report on evidence, obtained by combining thermodynamic measurements, local and non-local transport measurements, and theoretical calculations, that robust topologically non-trivial, valley Chern insulators occur at charge neutrality in twisted double-bilayer graphene (TDBG). These time reversal-conserving valley Chern insulators are enabled by valley-number conservation, a symmetry that emerges from the moir\'e pattern. The thermodynamic gap extracted from chemical potential measurements proves that TDBG is a bulk insulator under transverse electric field, while transport measurements confirm the existence of conducting edge states. A Landauer-Buttiker analysis of measurements on multi-terminal samples allows us to quantitatively assess edge state scattering and demonstrate that it does not destroy the edge states, leaving the bulk-boundary correspondence largely intact

Exchange renormalized crystal field excitation in a quantum Ising magnet KTmSe2_2

Rare-earth delafossite compounds, ARCh$_2$ (A = alkali or monovalent ion, R = rare earth, Ch = chalcogen), have been proposed for a range of novel quantum phenomena. Particularly, the Tm series, ATmCh$_2$, featuring Tm ions on a triangular lattice, serves as a representative group of compounds to illustrate the interplay and competition between spin-orbit coupling, crystal fields, and exchange couplings in the presence of geometric frustration. Here we report the thermodynamic and inelastic neutron scattering studies on the newly discovered triangular-lattice magnet KTmSe$_2$. Both heat capacity and neutron diffraction reveal the absence of long-range magnetic order. Magnetic susceptibility shows strong Ising-like interactions with antiferromagnetic correlations. Furthermore, inelastic neutron scattering measurements reveal a branch of dispersive crystal field excitations. To analyze these observations, we employ both the transverse field Ising model and the full crystal field scheme, along with exchange interactions. Our results suggest a strong competition between spin exchange interactions and crystal field effects. This work is expected to offer a valuable framework for understanding low-temperature magnetism in KTmSe$_2$ and similar materials.Comment: 9 pages, 4 figures. Submitted on the behalf of Shiyi Zhen

Clinical characteristics and prognosis of basaloid squamous cell carcinoma of the lung: a population-based analysis

Background This study analyzed the clinical features and prognosis of basaloid squamous cell carcinoma of the lung (BSC), and constructed a nomogram to predict the prognoses of patients. Methods The information of pure BSC patients was obtained in the Surveillance, Epidemiology, and End Results database between 2004 and 2015. Then, it was evaluated, and compared with the data of lung squamous cell carcinoma (SCC), lung large cell carcinoma (LCC) and lung adenocarcinoma (LAC) patients. Subsequently, we used univariate and multivariate analyses to investigate the independent factors related to the prognoses of patients with BSC and constructed a nomogram to verify the prognoses. Results A total of 425 patients diagnosed with BSC were enrolled. Compared with patients with SCC, LCC and LAC, the mean survival time of BSC patients was better than all of them. Compared with SCC, there were significant differences between the characteristics of grade (P < 0.001), total stage (P < 0.001), T stage (P < 0.001), N stage (P < 0.001), M stage (P < 0.001), surgery (P < 0.001), radiotherapy (P < 0.001), and chemotherapy (P < 0.001), while BSC also had significantly different clinical characteristics from LCC and LAC. Univariate and multivariate survival analyses showed that age (P < 0.001), T stage (P < 0.001), N stage (P = 0.009), M stage (P < 0.001), and surgery (P < 0.001) were independent prognostic factors of BSC. The survival of patients undergoing lobectomy was significantly better than sublobar resection, with an OR of 0.389 (0.263–0.578). We constructed a nomogram with a C-index of 0.750 (95% confidence interval) based on the results of multivariate analysis. The calibration curves based on nomogram scores indicated that the nomogram could accurately predict the prognosis of patients. Conclusions BSC had unique clinical and prognostic features. T stage, N stage, M stage, age, and surgery were independently associated with overall survival (OS). Lobectomy was a relative ideal choice for patients with BSC. The nomogram effectively predicted the OS at 1-, 3-, and 5-years

The western extension of Xiahe fault in West Qinling：Discussion on seismogenic structure of Qinghai Zeku MS4.9 earthquake in 2017

The epicenter of the 2017 Qinghai Zeku MS4.9 earthquake was located near the SN-striking Riyueshan fault, while the focal mechanism solutions and the dominant arrangement of seismic sequence are inconsistent with the Riyueshan fault. In this paper, we have discovered EW- and NW-trending faults near the epicenter, by methods of remote sensing interpretation and field investigation. These faults are western terminal structures of Xiahe fault, in which the EW-trending faults are north-dipping and associated with kinematics including both left-lateral and vertical slip. Meanwhile, we use double differential positioning to relocate seismic sequences of Zeku MS4.9 earthquake. Results show that seismic arrangements consist of two segments striking NW and EW. The seismic profile crossing EW-striking segment indicates a north-dipping fault plane. Well consistence is found between Xiahe fault and seismic arrangements of Zeku MS4.9 earthquake, which leads us to the speculation that the seismogenic fault of Zeku earthquake is Xiahe fault. From a regional perspective, the Xiahe fault might be one strand of dissipating faults in the western end of the West Qinling fault, and the Zeku MS4.9 earthquake represents tectonic activity of the western end of the West Qinling fault. Besides，the northwestward turn of fault striking and reverse slipping of Xiahe fault might also be attributed to the right-lateral shearing effects of Riyueshan fault. Results of this paper highlight the significance of improving active fault traces, especially for the secondary or pre-existing faults in a tectonic active area

Binding specificities of human RNA-binding proteins toward structured and linear RNA sequences

RNA-binding proteins (RBPs) regulate RNA metabolism at multiple levels by affecting splicing of nascent transcripts, RNA folding, base modification, transport, localization, translation, and stability. Despite their central role in RNA function, the RNA-binding specificities of most RBPs remain unknown or incompletely defined. To address this, we have assembled a genome-scale collection of RBPs and their RNA-binding domains (RBDs) and assessed their specificities using high-through-put RNA-SELEX (HTR-SELEX). Approximately 70% of RBPs for which we obtained a motif bound to short linear sequenc-es, whereas similar to 30% preferred structured motifs folding into stem-loops. We also found that many RBPs can bind to multiple distinctly different motifs. Analysis of the matches of the motifs in human genomic sequences suggested novel roles for many RBPs. We found that three cytoplasmic proteins-ZC3H12A, ZC3H12B, and ZC3H12C-bound to motifs resembling the splice donor sequence, suggesting that these proteins are involved in degradation of cytoplasmic viral and/or unspliced transcripts. Structural analysis revealed that the RNA motif was not bound by the conventional C3H1 RNA-binding domain of ZC3H12B. Instead, the RNA motif was bound by the ZC3H12B's PilT N terminus (PIN) RNase domain, revealing a po-tential mechanism by which unconventional RBDs containing active sites or molecule-binding pockets could interact with short, structured RNA molecules. Our collection containing 145 high-resolution binding specificity models for 86 RBPs is the largest systematic resource for the analysis of human RBPs and will greatly facilitate future analysis of the various bi-ological roles of this important class of proteins.Peer reviewe