Self-interference cancellation in underwater acoustic communications systems using orthogonal pilots in IBFD

This paper proposes a Self-interference (SI) cancellation system model of Underwater acoustic (UWA) communication for in-band full-duplex (IBFD) technology. The SI channel is separated from the Far channel by exploiting a concurrently orthogonal pilot channel estimation technique using two orthogonal frequency-division multiplexing (OFDM) blocks to establish orthogonality between them based on a unitary matrix. Compared to the half-duplex channel estimator, the mean squared error (MSE) and the bit error rate (BER) provided strong evidence for the efficiency of the proposed SI cancellation. Since full-duplex systems are more efficient than half-duplex ones, the proposed approach might be seen as a viable option for them. The proposed method proved effective when used with a fixed full-duplex (FD) position and FD shifting of up to 4°. Different channel lengths and distances are adopted to evaluate the proposed method. Initial findings indicate that MSE for the SI channel minimum mean-square error (MMSE) estimator at 20 dB is 0.118 · 10−3, for fixed FD. In addition, this paper presents a geometry channel model for the Far channel in the IBFD underwater communication system that describes the propagation delay of the multipath reflection. The simulation results for the multipath propagation delay spread are similar to the traditional results, with the delay spread of the suggested model reaching (79 ms), which is close to the Bellhop simulator result (78 ms)

Dense agent-based HPC simulation of cell physics and signaling with real-time user interactions

Introduction: Distributed simulations of complex systems to date have focused on scalability and correctness rather than interactive visualization. Interactive visual simulations have particular advantages for exploring emergent behaviors of complex systems. Interpretation of simulations of complex systems such as cancer cell tumors is a challenge and can be greatly assisted by using “built-in” real-time user interaction and subsequent visualization.Methods: We explore this approach using a multi-scale model which couples a cell physics model with a cell signaling model. This paper presents a novel communication protocol for real-time user interaction and visualization with a large-scale distributed simulation with minimal impact on performance. Specifically, we explore how optimistic synchronization can be used to enable real-time user interaction and visualization in a densely packed parallel agent-based simulation, whilst maintaining scalability and determinism. We also describe the software framework created and the distribution strategy for the models utilized. The key features of the High-Performance Computing (HPC) simulation that were evaluated are scalability, deterministic verification, speed of real-time user interactions, and deadlock avoidance.Results: We use two commodity HPC systems, ARCHER (118,080 CPU cores) and ARCHER2 (750,080 CPU cores), where we simulate up to 256 million agents (one million cells) using up to 21,953 computational cores and record a response time overhead of ≃350 ms from the issued user events.Discussion: The approach is viable and can be used to underpin transformative technologies offering immersive simulations such as Digital Twins. The framework explained in this paper is not limited to the models used and can be adapted to systems biology models that use similar standards (physics models using agent-based interactions, and signaling pathways using SBML) and other interactive distributed simulations

LLM-Assisted Code Cleaning For Training Accurate Code Generators

Natural language to code generation is an important application area of LLMs and has received wide attention from the community. The majority of relevant studies have exclusively concentrated on increasing the quantity and functional correctness of training sets while disregarding other stylistic elements of programs. More recently, data quality has garnered a lot of interest and multiple works have showcased its importance for improving performance. In this work, we investigate data quality for code and find that making the code more structured and readable leads to improved code generation performance of the system. We build a novel data-cleaning pipeline that uses these principles to transform existing programs by 1.) renaming variables, 2.) modularizing and decomposing complex code into smaller helper sub-functions, and 3.) inserting natural-language based plans via LLM based transformations. We evaluate our approach on two challenging algorithmic code generation benchmarks and find that fine-tuning CodeLLaMa-7B on our transformed modularized programs improves the performance by up to 30% compared to fine-tuning on the original dataset. Additionally, we demonstrate improved performance from using a smaller amount of higher-quality data, finding that a model fine-tuned on the entire original dataset is outperformed by a model trained on 15% of our cleaned dataset. Even in comparison to closed-source models, our models outperform the much larger AlphaCoder models

Entre o rio e o mar

Constituída no encontro do rio com o mar, Itajaí possui uma intensa ligação com as águas, devido à criação do porto, à pesca como atividade econômica, além dos processos migratórios da região. Diante disso, o presente artigo objetiva compreender como as águas, principalmente o mar, foram utilizados como espaços de educação do corpo e de difusão da cultura física na cidade de Itajaí entre o final do século XIX e a segunda década do século XX. Em termos metodológicos, realizou-se uma pesquisa historiográfica que teve como fontes os jornais “O Pharol” (1904), “O Arauto” (1903) e o “O Alphabeto” (1909). A investigação fornece indícios de que Itajaí foi aos poucos potencializando novas formas de sociabilidades, tendo o cenário ligado às águas como lócus central