The COGs (context, object, and goals) in multisensory processing

Our understanding of how perception operates in real-world environments has been substantially advanced by studying both multisensory processes and “top-down” control processes influencing sensory processing via activity from higher-order brain areas, such as attention, memory, and expectations. As the two topics have been traditionally studied separately, the mechanisms orchestrating real-world multisensory processing remain unclear. Past work has revealed that the observer’s goals gate the influence of many multisensory processes on brain and behavioural responses, whereas some other multisensory processes might occur independently of these goals. Consequently, other forms of top-down control beyond goal dependence are necessary to explain the full range of multisensory effects currently reported at the brain and the cognitive level. These forms of control include sensitivity to stimulus context as well as the detection of matches (or lack thereof) between a multisensory stimulus and categorical attributes of naturalistic objects (e.g. tools, animals). In this review we discuss and integrate the existing findings that demonstrate the importance of such goal-, object- and context-based top-down control over multisensory processing. We then put forward a few principles emerging from this literature review with respect to the mechanisms underlying multisensory processing and discuss their possible broader implications

Mobile Phones and Multiple Sclerosis – A Nationwide Cohort Study in Denmark

We investigated the risk of, prognosis of and symptoms of multiple sclerosis (MS) among all Danish residents who owned a mobile phone subscription before 1996. Using the Danish Multiple Sclerosis Registry and Civil Registration System, study subjects were followed up for MS through 2004. Poisson models were used to calculate incidence rate ratios (IRR, age range: 18–64 years) and mortality rate ratios (MRR, age range: 18+) and to compare presenting symptoms among subscribers and all non-subscribers. A total of 405 971 subscription holders accrued four million years of follow up, with men accounting for 86% of the observation time. Among subscription holding men, the IRR of MS was close to unity, overall as well as 13+ years after first subscription (IRR 1.02, 95% CI: 0.48–2.16). Among women, the IRR was 3.43 (95% CI: 0.86–13.72) 13+ years after first subscription, however, based on only two cases. Presenting symptoms of MS differed between subscribers and non-subscribers (p = 0.03), with slightly increased risk of diplopia in both genders (IRR: 1.38, 95% CI: 1.02–1.86), an increased risk of fatigue among women (IRR: 3.02, 95% CI: 1.45–6.28), and of optic neuritis among men (IRR: 1.38, 95% CI: 1.03–1.86). Overall the MRR was close to one (MRR: 0.91, 95%CI 0.70–1.19) among MS-patients with a subscription and although we observed some increased MRR estimates among women, these were based on small numbers. In conclusion, we found little evidence for a pronounced association between mobile phone use and risk of MS or mortality rate among MS patients. Symptoms of MS differed between subscribers and nonsubscribers for symptoms previously suggested to be associated with mobile phone use. This deserves further attention, as does the increased long-term risk of MS among female subscribers, although small numbers and lack of consistency between genders prevent causal interpretation

Measurement of the muon flux at the SND@LHC experiment

The Scattering and Neutrino Detector at the LHC (SND@LHC) started taking data at the beginning of Run 3 of the LHC. The experiment is designed to perform measurements with neutrinos produced in proton-proton collisions at the LHC in an energy range between 100 GeV and 1 TeV. It covers a previously unexplored pseudo-rapidity range of 7.2 < η< 8.4 . The detector is located 480 m downstream of the ATLAS interaction point in the TI18 tunnel. It comprises a veto system, a target consisting of tungsten plates interleaved with nuclear emulsion and scintillating fiber (SciFi) trackers, followed by a muon detector (UpStream, US and DownStream, DS). In this article we report the measurement of the muon flux in three subdetectors: the emulsion, the SciFi trackers and the DownStream Muon detector. The muon flux per integrated luminosity through an 18 × 18 cm 2 area in the emulsion is: 1.5±0.1(stat)×104fb/cm2. The muon flux per integrated luminosity through a 31 × 31 cm 2 area in the centre of the SciFi is: 2.06±0.01(stat)±0.12(sys)×104fb/cm2 The muon flux per integrated luminosity through a 52 × 52 cm 2 area in the centre of the downstream muon system is: 2.35±0.01(stat)±0.10(sys)×104fb/cm2 The total relative uncertainty of the measurements by the electronic detectors is 6 % for the SciFi and 4 % for the DS measurement. The Monte Carlo simulation prediction of these fluxes is 20–25 % lower than the measured values

Search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks in proton-proton collisions at root s=13TeV

A search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks is performed in proton-proton collisions at a center-of-mass energy of 13 TeV collected with the CMS detector at the LHC. The analyzed data sample corresponds to an integrated luminosity of 35.9 fb(-1). The signal is characterized by a large missing transverse momentum recoiling against a bottom quark-antiquark system that has a large Lorentz boost. The number of events observed in the data is consistent with the standard model background prediction. Results are interpreted in terms of limits both on parameters of the type-2 two-Higgs doublet model extended by an additional light pseudoscalar boson a (2HDM+a) and on parameters of a baryonic Z simplified model. The 2HDM+a model is tested experimentally for the first time. For the baryonic Z model, the presented results constitute the most stringent constraints to date.Peer reviewe

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions