Simple Coded Amplify-and-Forward Two-Way Relay Systems with Imperfect Side Information

This paper proposes a very simple, near capacity achieving coding scheme for an amplify-and-forward two-way relaying system with imperfect side information, in which two sources communicate with their respective destinations with the help of one relay. To avoid heavy computational complexity at the destinations, we assume a very short memory convolutional code. At the destinations iterative decoding between Joint-over- Antennas (JA) demapper and channel decoder is used to separate and decode the two signals. We present extrinsic information transfer (EXIT) chart analysis of the system. It is shown that demapper and decoder EXIT curves intersect each other before (1, 1) mutual information (MI) point, causing an error floor in the bit-error-rate (BER) performance. With a rate-1 doped accumulator (D-Acc) following the short memory convolutional encoder via an interleaver, the demapper curve and the decoder curve match very well, and the convergence tunnel opens until the (1,1) MI point, and thus the error floor can be completely removed. Simulations were conducted in two cases: without side information, and with imperfect side information. Simulation results show that in case of no side information turbo cliff happens at 1.25 dB away from the Shannon limit of a single link. With the help of side information, cliff happens at a value of received signal-to-noise power ratio even closer to the limit

Variants at the ASIP locus contribute to coat color darkening in Nellore cattle

Background: Nellore cattle (Bos indicus) are well-known for their adaptation to warm and humid environments. Hair length and coat color may impact heat tolerance. The Nellore breed has been strongly selected for white coat, but bulls generally exhibit darker hair ranging from light grey to black on the head, neck, hump, and knees. Given the potential contribution of coat color variation to the adaptation of cattle populations to tropical and sub-tropical environments, our aim was to map positional and functional candidate genetic variants associated with darkness of hair coat (DHC) in Nellore bulls. Results: We performed a genome-wide association study (GWAS) for DHC using data from 432 Nellore bulls that were genotyped for more than 777 k single nucleotide polymorphism (SNP) markers. A single major association signal was detected in the vicinity of the agouti signaling protein gene (ASIP). The analysis of whole-genome sequence (WGS) data from 21 bulls revealed functional variants that are associated with DHC, including a structural rearrangement involving ASIP (ASIP-SV1). We further characterized this structural variant using Oxford Nanopore sequencing data from 13 Australian Brahman heifers, which share ancestry with Nellore cattle; we found that this variant originates from a 1155-bp deletion followed by an insertion of a transposable element of more than 150 bp that may impact the recruitment of ASIP non-coding exons. Conclusions: Our results indicate that the variant ASIP sequence causes darker coat pigmentation on specific parts of the body, most likely through a decreased expression of ASIP and consequently an increased production of eumelanin

Ultrasonic intensification as a tool for enhanced microbial biofuel yields

peer-reviewedUltrasonication has recently received attention as a novel bioprocessing tool for process intensification in many areas of downstream processing. Ultrasonic intensification (periodic ultrasonic treatment during the fermentation process) can result in a more effective homogenization of biomass and faster energy and mass transfer to biomass over short time periods which can result in enhanced microbial growth. Ultrasonic intensification can allow the rapid selective extraction of specific biomass components and can enhance product yields which can be of economic benefit. This review focuses on the role of ultrasonication in the extraction and yield enhancement of compounds from various microbial sources, specifically algal and cyanobacterial biomass with a focus on the production of biofuels. The operating principles associated with the process of ultrasonication and the influence of various operating conditions including ultrasonic frequency, power intensity, ultrasonic duration, reactor designs and kinetics applied for ultrasonic intensification are also described

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

The ATLAS inner detector trigger performance in pp collisions at 13 TeV during LHC Run 2

The design and performance of the inner detector trigger for the high level trigger of the ATLAS experiment at the Large Hadron Collider during the 2016-2018 data taking period is discussed. In 2016, 2017, and 2018 the ATLAS detector recorded 35.6 fb(-1), 46.9 fb(-1), and 60.6 fb(-1) respectively of proton-proton collision data at a centre-of-mass energy of 13TeV. In order to deal with the very high interaction multiplicities per bunch crossing expected with the 13TeV collisions the inner detector trigger was redesigned during the long shutdown of the Large Hadron Collider from 2013 until 2015. An overview of these developments is provided and the performance of the tracking in the trigger for the muon, electron, tau and b-jet signatures is discussed. The high performance of the inner detector trigger with these extreme interaction multiplicities demonstrates how the inner detector tracking continues to lie at the heart of the trigger performance and is essential in enabling the ATLAS physics programme

Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at \sqrt{s}=13 TeV

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 \hbox {fb}^{-1} of pp collision data at \sqrt{s}=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Z\rightarrow \mu \mu and J/\psi \rightarrow \mu \mu decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |\eta |<2.7

Direct constraint on the Higgs–charm coupling from a search for Higgs boson decays into charm quarks with the ATLAS detector

A search for the Higgs boson decaying into a pair of charm quarks is presented. The analysis uses proton–proton collisions to target the production of a Higgs boson in association with a leptonically decaying W or Z boson. The dataset delivered by the LHC at a centre-of-mass energy of and recorded by the ATLAS detector corresponds to an integrated luminosity of 139 fb−1. Flavour-tagging algorithms are used to identify jets originating from the hadronisation of charm quarks. The analysis method is validated with the simultaneous measurement of WW, WZ and ZZ production, with observed (expected) significances of 2.6 (2.2) standard deviations above the background-only prediction for the (W/Z)Z(→cc¯) process and 3.8 (4.6) standard deviations for the (W/Z)W(→cq) process. The (W/Z)H(→cc¯) search yields an observed (expected) upper limit of 26 (31) times the predicted Standard Model cross-section times branching fraction for a Higgs boson with a mass of , corresponding to an observed (expected) constraint on the charm Yukawa coupling modifier |κc|<8.5 (12.4), at the 95% confidence level. A combination with the ATLAS (W/Z)H,H→bb¯ analysis is performed, allowing the ratio κc/κb to be constrained to less than 4.5 at the 95% confidence level, smaller than the ratio of the b- and c-quark masses, and therefore determines the Higgs-charm coupling to be weaker than the Higgs-bottom coupling at the 95% confidence level