Hasil untuk "q-bio.CB"

DeepSeek-AI, Daya Guo, Dejian Yang et al.

General reasoning represents a long-standing and formidable challenge in artificial intelligence (AI). Recent breakthroughs, exemplified by large language models (LLMs)1,2 and chain-of-thought (CoT) prompting3, have achieved considerable success on foundational reasoning tasks. However, this success is heavily contingent on extensive human-annotated demonstrations and the capabilities of models are still insufficient for more complex problems. Here we show that the reasoning abilities of LLMs can be incentivized through pure reinforcement learning (RL), obviating the need for human-labelled reasoning trajectories. The proposed RL framework facilitates the emergent development of advanced reasoning patterns, such as self-reflection, verification and dynamic strategy adaptation. Consequently, the trained model achieves superior performance on verifiable tasks such as mathematics, coding competitions and STEM fields, surpassing its counterparts trained through conventional supervised learning on human demonstrations. Moreover, the emergent reasoning patterns exhibited by these large-scale models can be systematically used to guide and enhance the reasoning capabilities of smaller models. A new artificial intelligence model, DeepSeek-R1, is introduced, demonstrating that the reasoning abilities of large language models can be incentivized through pure reinforcement learning, removing the need for human-annotated demonstrations.

David Rein, Betty Li Hou, Asa Cooper Stickland et al.

We present GPQA, a challenging dataset of 448 multiple-choice questions written by domain experts in biology, physics, and chemistry. We ensure that the questions are high-quality and extremely difficult: experts who have or are pursuing PhDs in the corresponding domains reach 65% accuracy (74% when discounting clear mistakes the experts identified in retrospect), while highly skilled non-expert validators only reach 34% accuracy, despite spending on average over 30 minutes with unrestricted access to the web (i.e., the questions are"Google-proof"). The questions are also difficult for state-of-the-art AI systems, with our strongest GPT-4 based baseline achieving 39% accuracy. If we are to use future AI systems to help us answer very hard questions, for example, when developing new scientific knowledge, we need to develop scalable oversight methods that enable humans to supervise their outputs, which may be difficult even if the supervisors are themselves skilled and knowledgeable. The difficulty of GPQA both for skilled non-experts and frontier AI systems should enable realistic scalable oversight experiments, which we hope can help devise ways for human experts to reliably get truthful information from AI systems that surpass human capabilities.

T. Dinh, Jianhua Tang, Q. La et al.

Jin Zhang, Hongling Zou, Q. Qing et al.

L. C. R. Aaij, C. Beteta, T. Ackernley et al.

The standard model of particle physics currently provides our best description of fundamental particles and their interactions. The theory predicts that the different charged leptons, the electron, muon and tau, have identical electroweak interaction strengths. Previous measurements have shown that a wide range of particle decays are consistent with this principle of lepton universality. This article presents evidence for the breaking of lepton universality in beauty-quark decays, with a significance of 3.1 standard deviations, based on proton–proton collision data collected with the LHCb detector at CERN’s Large Hadron Collider. The measurements are of processes in which a beauty meson transforms into a strange meson with the emission of either an electron and a positron, or a muon and an antimuon. If confirmed by future measurements, this violation of lepton universality would imply physics beyond the standard model, such as a new fundamental interaction between quarks and leptons. The Large Hadron Collider beauty collaboration reports a test of lepton flavour universality in decays of bottom mesons into strange mesons and a charged lepton pair, finding evidence of a violation of this principle postulated in the standard model.

M. Ablikim, M. Achasov, P. Adlarson et al.

There has recently been a dramatic renewal of interest in hadron spectroscopy and charm physics. This renaissance has been driven in part by the discovery of a plethora of charmonium-like XYZ states at BESIII and B factories, and the observation of an intriguing proton-antiproton threshold enhancement and the possibly related X(1835) meson state at BESIII, as well as the threshold measurements of charm mesons and charm baryons. We present a detailed survey of the important topics in tau-charm physics and hadron physics that can be further explored at BESIII during the remaining operation period of BEPCII. This survey will help in the optimization of the data-taking plan over the coming years, and provides physics motivation for the possible upgrade of BEPCII to higher luminosity.

G. Ambrosi, Q. An, R. Asfandiyarov et al.

High-energy cosmic-ray electrons and positrons (CREs), which lose energy quickly during their propagation, provide a probe of Galactic high-energy processes and may enable the observation of phenomena such as dark-matter particle annihilation or decay. The CRE spectrum has been measured directly up to approximately 2 teraelectronvolts in previous balloon- or space-borne experiments, and indirectly up to approximately 5 teraelectronvolts using ground-based Cherenkov γ-ray telescope arrays. Evidence for a spectral break in the teraelectronvolt energy range has been provided by indirect measurements, although the results were qualified by sizeable systematic uncertainties. Here we report a direct measurement of CREs in the energy range 25 gigaelectronvolts to 4.6 teraelectronvolts by the Dark Matter Particle Explorer (DAMPE) with unprecedentedly high energy resolution and low background. The largest part of the spectrum can be well fitted by a ‘smoothly broken power-law’ model rather than a single power-law model. The direct detection of a spectral break at about 0.9 teraelectronvolts confirms the evidence found by previous indirect measurements, clarifies the behaviour of the CRE spectrum at energies above 1 teraelectronvolt and sheds light on the physical origin of the sub-teraelectronvolt CREs.

L. C. R. Aaij, A. Abdelmotteleb, C. Beteta et al.

Conventional, hadronic matter consists of baryons and mesons made of three quarks and a quark–antiquark pair, respectively1,2. Here, we report the observation of a hadronic state containing four quarks in the Large Hadron Collider beauty experiment. This so-called tetraquark contains two charm quarks, a u¯\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{{{{{u}}}}}$$\end{document} and a d¯\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\overline{{{{{d}}}}}$$\end{document} quark. This exotic state has a mass of approximately 3,875 MeV and manifests as a narrow peak in the mass spectrum of D0D0π+ mesons just below the D*+D0 mass threshold. The near-threshold mass together with the narrow width reveals the resonance nature of the state. The LHCb Collaboration reports the observation of an exotic, narrow, tetraquark state that contains two charm quarks, an up antiquark and a down antiquark.

L. C. R. Aaij, C. Beteta, T. Ackernley et al.

Using proton-proton collision data at centre-of-mass energies of s=7,8 and 13TeV recorded by the LHCb experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 9fb-1, the invariant mass spectrum of J/ψ pairs is studied. A narrow structure around 6.9GeV/c2 matching the lineshape of a resonance and a broad structure just above twice the J/ψ mass are observed. The deviation of the data from nonresonant J/ψ-pair production is above five standard deviations in the mass region between 6.2 and 7.4GeV/c2, covering predicted masses of states composed of four charm quarks. The mass and natural width of the narrow X(6900) structure are measured assuming a Breit-Wigner lineshape.

Rafael Rafailov, Joey Hejna, Ryan Park et al.

Reinforcement Learning From Human Feedback (RLHF) has been critical to the success of the latest generation of generative AI models. In response to the complex nature of the classical RLHF pipeline, direct alignment algorithms such as Direct Preference Optimization (DPO) have emerged as an alternative approach. Although DPO solves the same objective as the standard RLHF setup, there is a mismatch between the two approaches. Standard RLHF deploys reinforcement learning in a specific token-level MDP, while DPO is derived as a bandit problem in which the whole response of the model is treated as a single arm. In this work we rectify this difference. We theoretically show that we can derive DPO in the token-level MDP as a general inverse Q-learning algorithm, which satisfies the Bellman equation. Using our theoretical results, we provide three concrete empirical insights. First, we show that because of its token level interpretation, DPO is able to perform some type of credit assignment. Next, we prove that under the token level formulation, classical search-based algorithms, such as MCTS, which have recently been applied to the language generation space, are equivalent to likelihood-based search on a DPO policy. Empirically we show that a simple beam search yields meaningful improvement over the base DPO policy. Finally, we show how the choice of reference policy causes implicit rewards to decline during training. We conclude by discussing applications of our work, including information elicitation in multi-turn dialogue, reasoning, agentic applications and end-to-end training of multi-model systems.

The Cms, LHCb Collaborations V. Khachatryan, A. Sirunyan et al.

The standard model of particle physics describes the fundamental particles and their interactions via the strong, electromagnetic and weak forces. It provides precise predictions for measurable quantities that can be tested experimentally. The probabilities, or branching fractions, of the strange B meson () and the B0 meson decaying into two oppositely charged muons (μ+ and μ−) are especially interesting because of their sensitivity to theories that extend the standard model. The standard model predicts that the and decays are very rare, with about four of the former occurring for every billion mesons produced, and one of the latter occurring for every ten billion B0 mesons. A difference in the observed branching fractions with respect to the predictions of the standard model would provide a direction in which the standard model should be extended. Before the Large Hadron Collider (LHC) at CERN started operating, no evidence for either decay mode had been found. Upper limits on the branching fractions were an order of magnitude above the standard model predictions. The CMS (Compact Muon Solenoid) and LHCb (Large Hadron Collider beauty) collaborations have performed a joint analysis of the data from proton–proton collisions that they collected in 2011 at a centre-of-mass energy of seven teraelectronvolts and in 2012 at eight teraelectronvolts. Here we report the first observation of the µ+µ− decay, with a statistical significance exceeding six standard deviations, and the best measurement so far of its branching fraction. Furthermore, we obtained evidence for the µ+µ− decay with a statistical significance of three standard deviations. Both measurements are statistically compatible with standard model predictions and allow stringent constraints to be placed on theories beyond the standard model. The LHC experiments will resume taking data in 2015, recording proton–proton collisions at a centre-of-mass energy of 13 teraelectronvolts, which will approximately double the production rates of and B0 mesons and lead to further improvements in the precision of these crucial tests of the standard model.

Q. An, R. Asfandiyarov, P. Azzarello et al.

DAMPE satellite has directly measured the cosmic ray proton spectrum from 40 GeV to 100 TeV and revealed a new feature at about 13.6 TeV. The precise measurement of the spectrum of protons, the most abundant component of the cosmic radiation, is necessary to understand the source and acceleration of cosmic rays in the Milky Way. This work reports the measurement of the cosmic ray proton fluxes with kinetic energies from 40 GeV to 100 TeV, with 2 1/2 years of data recorded by the DArk Matter Particle Explorer (DAMPE). This is the first time that an experiment directly measures the cosmic ray protons up to ~100 TeV with high statistics. The measured spectrum confirms the spectral hardening at ~300 GeV found by previous experiments and reveals a softening at ~13.6 TeV, with the spectral index changing from ~2.60 to ~2.85. Our result suggests the existence of a new spectral feature of cosmic rays at energies lower than the so-called knee and sheds new light on the origin of Galactic cosmic rays.

K. Mackie, Y. Lai, R. Westenbroek et al.

Rat brain cannabinoid receptor (CB-1) was stably transfected into the murine tumor line AtT-20 to study its coupling to inwardly rectifying potassium currents (Kir) and high voltage-activated calcium currents (ICa). In cells expressing CB-1 (“A-2” cells), cannabinoid agonist potently and stereospecifically activated Kir via a pertussis toxin- sensitive G protein. ICa in A-2 cells was sensitive to dihydropyridines and omega CTX MVIIC, less so to omega CgTX GVIA and insensitive to omega Aga IVa. In CB-1 expressing cells, cannabinoid agonist inhibited only the omega CTX MVIIC-sensitive component of ICa. Inhibition of Q- type ICa was voltage dependent and PTX sensitive, thus similar in character to the well-studied modulation of N-type ICa. An endogenous cannabinoid, anandamide, activated Kir and inhibited ICa as efficaciously as potent cannabinoid agonist. Immunocytochemical studies with antibodies specific for class A, B, C, D, and E voltage-dependent calcium channel alpha 1 subunits revealed that AtT-20 cells express each of these major classes of alpha 1 subunit.

Liaofu Luo, Jun Lv

Predicting the future evolutionary trajectory of SARS-CoV-2 remains a critical challenge, particularly due to the pivotal role of spike protein mutations. It is therefore essential to develop evolutionary models capable of continuously integrating new experimental data. In this study, we employ a cladogram algorithm that incorporates established assumptions for mutant representation -- using both four-letter and two-letter formats -- along with an n-mer distance algorithm to construct a cladogenetic tree of SARS-CoV-2 mutations. This tree accurately captures the observed changes across macro-lineages. We introduce a stochastic method for generating new strains on this tree based on spike protein mutations. For a given set A of existing mutation sites, we define a set X comprising x randomly generated mutation sites on the spike protein. The intersection of A and X, denoted as set Y, contains y sites. Our analysis indicates that the position of a generated strain on the tree is primarily determined by x. Through large-scale stochastic sampling, we predict the emergence of new macro-lineages. As x increases, the dominance among macro-lineages shifts: lineage O surpasses N, P surpasses O, and eventually Q surpasses P. We identify threshold values of x that delineate transitions between these macro-lineages. Furthermore, we propose an algorithm for predicting the timeline of macro-lineage emergence. In conclusion, our findings demonstrate that SARS-CoV-2 evolution adheres to statistical principles: the emergence of new strains can be driven by randomly generated spike protein sites, and large-scale stochastic sampling reveals evolutionary patterns underlying the rise of distinct macro-lineages.

Q. Quan, M. Lončar

Photonic crystal nanobeam cavities are versatile platforms of interest for optical communications, optomechanics, optofluidics, cavity QED, etc. In a previous work [Appl. Phys. Lett. 96, 203102 (2010)], we proposed a deterministic method to achieve ultrahigh Q cavities. This follow-up work provides systematic analysis and verifications of the deterministic design recipe and further extends the discussion to air-mode cavities. We demonstrate designs of dielectric-mode and air-mode cavities with Q > 10⁹, as well as dielectric-mode nanobeam cavities with both ultrahigh-Q (> 10⁷) and ultrahigh on-resonance transmissions (T > 95%).

Harshal Potdar, Ignacio Pagonabarraga, Sudipto Muhuri

Experiments performed using micro-patterned one dimensional collision assays have allowed a precise quantitative analysis of the collective manifestation of contact inhibition locomotion (CIL) wherein, individual migrating cells reorient their direction of motion when they come in contact with other cells. Inspired by these experiments, we present a discrete, minimal 1D Active spin model that mimics the CIL interaction between cells in one dimensional channels. We analyze the emergent collective behaviour of migrating cells in such confined geometries, as well as the sensitivity of the emergent patterns to driving forces that couple to cell motion. In the absence of vacancies, akin to dense cell packing, the translation dynamics is arrested and the model reduces to an equilibrium spin model which can be solved exactly. In the presence of vacancies, the interplay of activity-driven translation, cell polarity switching, and CIL results in an exponential steady cluster size distribution. We define a dimensionless Péclet number Q - the ratio of the translation rate and directional switching rate of particles in the absence of CIL. While the average cluster size increases monotonically as a function of Q, it exhibits a non-monotonic dependence on CIL strength, when the Q is sufficiently high. In the high Q limit, an analytical form of average cluster size can be obtained approximately by effectively mapping the system to an equivalent equilibrium process involving clusters of different sizes wherein the cluster size distribution is obtained by minimizing an effective Helmholtz free energy for the system. The resultant prediction of exponential dependence on CIL strength of the average cluster size and Q^{1/2} dependence of the average cluster size is borne out to reasonable accuracy as long as the CIL strength is not very large.

T. Zhu, J. Harris, B. Biondi

R. Blundell, Stephen R. Bond, M. Devereux et al.

Miguel Ramos Pascual

A dynamic model of non-lineal time-dependent ordinary differential equations (ODE) has been applied to the interactions of a HIV infection with the immune system cells. This model has been simplified into two compartments: lymph node and peripheral blood. The model includes CD4 T-lymphocytes in several states (quiescent Q, naive N and activated T), cytotoxic CD8 T-cells, B-cells and dendritic cells. Cytokines and immunoglobulins specific for each antigen (i.e. gp41 or p24) have been also included in the model, modelling the atraction effect of CD4 T-cells to the infected area and the reduction of virus concentration by immunoglobulins. HIV virus infection of CD4 T-lymphocytes is modelled in several stages: before fusion as HIV-attached (H) and after fusion as non-permissive / abortively infected (M), and permissive / latently infected (L) and permissive / actively infected (I). These equations have been implemented in a C++/Python interface application, called Immune System app, which runs Open Modelica software to solve the ODE system through a 4th order Runge-Kutta numerical approximation. Results of the simulation show that although HIV virus concentration in both compartments is lower than $10^{-10}$ virus/$μL$ after t=2 years, quiescent lymphocytes reach an equilibrium with a concentration lower than the initial conditions, due to the latency state, which serves as a reservoir in time of virus production. As a conclusion, this model can provide reliable results in other conditions, such as antiviral therapies.

Haym Benaroya

We review current thinking about, and draw connections between, brain energetics and metabolism, mitochondria and traumatic brain injury. In addition to summarizing current thinking in these disciplines, our goal is to suggest a framework for mechanisms and pathways based on optimal energetic decisions.