An Efficient Method for GPS Multipath Mitigation Using the Teager-Kaiser-Operator-based MEDLL

An efficient method for GPS multipath mitigation is proposed. The motivation for this proposed method is to integrate the Teager-Kaiser Operator (TKO) with the Multipath Estimating Delay Lock Loop (MEDLL) module to mitigate the GPS multipath efficiently. The general implementation process of the proposed method is that we first utilize the TKO to operate on the received signal’s Auto-Correlation Function (ACF) to get an initial estimate of the multipaths. Then we transfer the initial estimated results to the MEDLL module for a further estimation. Finally, with a few iterations which are less than those of the original MEDLL algorithm, we can get a more accurate estimate of the Line-Of-Sight (LOS) signal, and thus the goal of the GPS multipath mitigation is achieved. The simulation results show that compared to the original MEDLL algorithm, the proposed method can reduce the computation load and the hardware and/or software consumption of the MEDLL module, meanwhile, without decreasing the algorithm accuracy

A Quantitative Review on Language Model Efficiency Research

Language models (LMs) are being scaled and becoming powerful. Improving their efficiency is one of the core research topics in neural information processing systems. Tay et al. (2022) provided a comprehensive overview of efficient Transformers that have become an indispensable staple in the field of NLP. However, in the section of "On Evaluation", they left an open question "which fundamental efficient Transformer one should consider," answered by "still a mystery" because "many research papers select their own benchmarks." Unfortunately, there was not quantitative analysis about the performances of Transformers on any benchmarks. Moreover, state space models (SSMs) have demonstrated their abilities of modeling long-range sequences with non-attention mechanisms, which were not discussed in the prior review. This article makes a meta analysis on the results from a set of papers on efficient Transformers as well as those on SSMs. It provides a quantitative review on LM efficiency research and gives suggestions for future research.Comment: 29 pages, 24 table

Embedding Mental Health Discourse for Community Recommendation

Our paper investigates the use of discourse embedding techniques to develop a community recommendation system that focuses on mental health support groups on social media. Social media platforms provide a means for users to anonymously connect with communities that cater to their specific interests. However, with the vast number of online communities available, users may face difficulties in identifying relevant groups to address their mental health concerns. To address this challenge, we explore the integration of discourse information from various subreddit communities using embedding techniques to develop an effective recommendation system. Our approach involves the use of content-based and collaborative filtering techniques to enhance the performance of the recommendation system. Our findings indicate that the proposed approach outperforms the use of each technique separately and provides interpretability in the recommendation process.Comment: Accepted to the 4th workshop on Computational Approaches to Discourse (CODI-2023) at ACL 202

Preparation and Characterization of Colon-Specific Microspheres of Diclofenac for Colorectal Cancer

Purpose: To prepare and evaluate colon specific drug delivery system of diclofenac sodium for highly localized delivery to the colon.Methods: The colon specific drug delivery system was prepared as matrix-type microspheres using Ethyl Cellulose (EC), Cellulose Acetate Phthalate (CAP), and Eudragit L 100-55 by the Solvent Evaporation Method. Microspheres were evaluated for physical properties like drug content, particle size, bulk density and angle of repose.Results: The size range of the microcapsules was 228 to 608 μm while drug content was between 74.49 and 91.50 % depending on the polymer used and the  polymer ratio. Mean bulk density was < 1.2 g/ml which indicates the good flow properties, while angle of repose was < 40 o, indicating free-flowing properties. The microspheres were spherical in shape with smooth and nonporous surface, except that the microspheres containing EC and CAP exhibited a rough and porous  surface. The microspheres containing Eudragit L 100-55 in combination with other polymers gave better sustained release (78.9 and 76.6 % at the end of 8 h for  formulation F4 and F5, respectively) than the others.Conclusion: Microspheres prepared with drug: EC: CAP ratio of 1:2:1 show the highest drug content, possess good flow properties and surface morphology, as well as promising drug release for colon specific drug delivery of diclofenac sodium for possible treatment of colorectal cancer.Keywords: Diclofenac, Colorectal cancer, Microspheres, Ethyl cellulose, Cellulose acetate phthalate, Eudragit L 100-5

Numerical study on wind profiles change trend of upright reticulation barriers under different configuration models

To explore how to lay the same specifications to maximize the protection benefits of mechanical sand barriers is an essential issue in the actual production process. We used the Reynolds-Averaged Navier-Stokes (RANS) method and the shear stress transport (SST) K-ε turbulence model to study the windbreak efficiency of sand barriers with different structures. Among them, the structure of the sand barriers includes rhombus 60° (cTnI = 60°, R60°), rhombus 90° (cTnI = 90°, R90°), rhombus 120° (cTnI = 120°, R120°) and parallel straight line (belt). The sand barrier was set to a porous jump model, where the surface permeability a was 2.6 × 108, and the inertial resistance coefficient c2 was 9,400. The wind velocity field results showed that the sand barrier’s blocking effect on wind velocity decreases with the increase in height. The leading edge of the 120° obstacle has the strongest weakening effect on the inlet wind speed. The minimum wind speed (0.97 m/s to 1.41 m/s) occurs near the sand barrier, and the vortex appears on both sides of the node, and the wind speed increases. The order of the blocking effect of different angles on airflow is as follows: 120° > 90°> brand >60°. Under R120° conditions, the wind speed is reduced by more than 60% at 0.05 m and 0.1 m height behind the barrier compared to the initial wind speed. This will be conducive to the design and control engineering planning of the laying angle of the gauze sand barrier in the main wind direction

De Novo Assembly and Characterization of Bud, Leaf and Flowers Transcriptome from Juglans Regia L. for the Identification and Characterization of New EST-SSRs

Persian walnut (Juglans regia L.), valued for both its nut and wood, is an ecologically important temperate tree species native to the mountainous regions of central Asia. Despite its importance, there are still few transcriptomic resources in public databases for J. regia, limiting gene discovery and breeding. Here, more than 49.9 million sequencing reads were generated using Illumina sequencing technology in the characterization of the transcriptome of four J. regia organs (bud, leaf, female flowers, and male flowers). De novo assembly yielded 117,229 unigenes with an N50 of 1955 bp. Based on sequence similarity searches against known proteins, a total of 20,413 (17.41%) genes were identified and annotated. A set of 27,584 unigenes with SSR (simple sequence repeats) motifs were identified as potential molecular markers, and a sample of 77 of these EST-SSRs (express sequence tags) were further evaluated to validate their amplification and assess their polymorphism. Next, we developed 39 polymorphic microsatellite markers to screen 88 Persian walnut individuals collected from 11 populations. These markers and transcriptomic resources will be useful for future studies of population genetic structure, evolutionary ecology, and breeding of Persian walnut and other Juglans species

Mott transition in the triangular lattice Hubbard model: a dynamical cluster approximation study

Based on dynamical cluster approximation (DCA) quantum Monte Carlo simulations, we study the interaction-driven Mott metal-insulator transition (MIT) in the half-filled Hubbard model on the anisotropic two-dimensional triangular lattice, where the degree of frustration is varied between the unfrustrated case and the fully frustrated, isotropic triangular lattice. Upon increasing the DCA cluster size, we analyze the evolution of the MIT phase boundary as a function of frustration in the phase diagram spanned by the interaction strength and temperature, and provide a quantitative description of the MIT phase boundary in the triangular lattice Hubbard model. Qualitative differences in the phase boundary between the unfrustrated and fully frustrated cases are exhibited. In particular, a change in the sign of the phase boundary slope is observed, which via an impurity cluster eigenstate analysis, may be related to a change in the nature of the insulating state. We discuss our findings within the scenario that the triangular lattice electron system might exhibit a quantum critical Mott MIT with a possible quantum spin liquid insulating state, such as considered for the organic charge transfer salts $\kappa$-(BEDT-TTF)$_{2}$Cu$_{2}$(CN)$_{3}$ and EtMe$_{3}$Sb[Pd(dmit)$_{2}$]$_{2}$

MIMO-DoAnet: Multi-channel Input and Multiple Outputs DoA Network with Unknown Number of Sound Sources

Recent neural network based Direction of Arrival (DoA) estimation algorithms have performed well on unknown number of sound sources scenarios. These algorithms are usually achieved by mapping the multi-channel audio input to the single output (i.e. overall spatial pseudo-spectrum (SPS) of all sources), that is called MISO. However, such MISO algorithms strongly depend on empirical threshold setting and the angle assumption that the angles between the sound sources are greater than a fixed angle. To address these limitations, we propose a novel multi-channel input and multiple outputs DoA network called MIMO-DoAnet. Unlike the general MISO algorithms, MIMO-DoAnet predicts the SPS coding of each sound source with the help of the informative spatial covariance matrix. By doing so, the threshold task of detecting the number of sound sources becomes an easier task of detecting whether there is a sound source in each output, and the serious interaction between sound sources disappears during inference stage. Experimental results show that MIMO-DoAnet achieves relative 18.6% and absolute 13.3%, relative 34.4% and absolute 20.2% F1 score improvement compared with the MISO baseline system in 3, 4 sources scenes. The results also demonstrate MIMO-DoAnet alleviates the threshold setting problem and solves the angle assumption problem effectively.Comment: Accepted by Interspeech 202

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies