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.
This case details the diagnosis and treatment process of a patient with bilateral facial nerve palsy accompanied with limb sensory disturbance secondary to head trauma, who was ultimately diagnosed with Bifacial weakness with paresthesias (BFP) , a rare variant of Guillain-Barré Syndrome(GBS) . The patient underwent plasma exchange therapy and showed favorable recovery . In this article, for the first time we report a case of BFP secondary to trauma.
This paper introduces a configuration and integration model for mobile robots deployed in emergency and special operations scenarios. The proposed method is designed for implementation within the Operational Technology (OT) domain, enforcing security protocols that ensure both data encryption and network isolation. The primary objective is to establish a dedicated operational environment encompassing a command and control center, where the robotic network server resides, alongside real-time data storage from network clients and remote control of field-deployed mobile robots. Building on this infrastructure, operational strategies are developed to enable efficient robotic response in critical situations. By leveraging remote robotic networks, significant benefits are achieved in terms of personnel safety and mission efficiency minimizing response time and reducing the risk of injury to human operators during hazardous interventions. The technologies employed create a synergistic system that ensures data security, encryption, and user interaction through a web-based interface. Additionally, the system includes mobile robots and a read-only application positioned within the DMZ (Demilitarized Zone), allowing for secure data monitoring without granting control access to the robotic network.
Anna Singley, Carrie Manore, Hannah Highlander
et al.
We present a stochastic differential equation model of suicidal progression in U.S. veterans, simulating transitions across mental health states under dynamic stress and covariate influence. Transition rates are modulated by an Ornstein-Uhlenbeck stress process and clinical features derived from retrospective case-control data. Simulations reveal profile-dependent tipping behavior, with risk-loaded individuals exhibiting persistent ideation and attempt states. Area-under-the-curve and phase plane analyses suggest early warning signals and support the use of individualized dynamical models for suicide risk assessment.
In this commentary I review the claim by Luebbert and Pachter (arXiv:2405.12998v1) that the reported R-Squared value in Srinivasan et al. (Science, 287(5454):851-853, 2000), describing the relationship between distance to a food source and mean waggle duration of honeybee dances, was too high to be consistent with the reported means and standard deviations in the latter study. There is one serious limitation of the simulations conducted by Luebbert and Pachter, and two flaws that compromise their findings. The reported R-squared value of Srinivasan. et al. is within the expected range, as far as that can be determined given the limitations of the available data.
How does the genome encode the form of the organism? What is the nature of this genomic code? Inspired by recent work in machine learning and neuroscience, we propose that the genome encodes a generative model of the organism. In this scheme, by analogy with variational autoencoders, the genome comprises a connectionist network, embodying a compressed space of latent variables, with weights that get encoded by the learning algorithm of evolution and decoded through the processes of development. The generative model analogy accounts for the complex, distributed genetic architecture of most traits and the emergent robustness and evolvability of developmental processes, while also offering a conception that lends itself to formalisation.
In this work, we consider an extension of symmetric teleparallel gravity, namely, f(Q) gravity, where the fundamental block to describe spacetime is the nonmetricity, Q. Within this formulation of gravitation, we perform an observational analysis of several modified f(Q) models using the redshift approach, where the f(Q) Lagrangian is reformulated as an explicit function of the redshift, f(z). Various different polynomial parametrizations of f(z) are proposed, including new terms which would allow for deviations from the Λ Cold Dark Matter model. Given a variety of observational probes, such as the expansion rate data from early type galaxies, type Ia supernovae, quasars, gamma ray bursts, baryon acoustic oscillations data, and cosmic microwave background distance priors, we have checked the validity of these models at the background level in order to verify if this new formalism provides us with plausible alternative models to explain the late time acceleration of the Universe. Indeed, this novel approach provides a different perspective on the formulation of observationally reliable alternative models of gravity.
Cosmography is an ideal tool to investigate the cosmic expansion history of the Universe in a model-independent way. The equations of motion in modified theories of gravity are usually very complicated; cosmography may select practical models without imposing arbitrary choices a priori. We use the model-independent way to derive $f(z)$ and its derivatives up to fourth order in terms of measurable cosmographic parameters. We then fit those functions into the luminosity distance directly. We perform the MCMC analysis by considering three different sets of cosmographic functions. Using the largest supernovae Ia Pantheon sample, we derive the constraints on the Hubble constant $H_0$ and the cosmographic functions, and find that the former two terms in Taylor expansion of luminosity distance work dominantly in $f(Q)$ gravity.