Recent Results Research Articles

The impact of rotation on the stochastic excitation of stellar acoustic modes in solar-like pulsators

Recent observational results from asteroseismic studies show that an important fraction of solar-like stars do not present detectable stochastically excited acoustic oscillations. This non-detectability seems to correlate with a high rotation rate in the convective envelope and a high surface magnetic activity. At the same time, the properties of stellar convection are affected by rotation and magnetism. We investigate the role of rotation in the excitation of acoustic modes in the convective envelope of solar-like stars, to evaluate its impact on the energy injected in the oscillations. We derived theoretical prescriptions for the excitation of acoustic waves in the convective envelope of rotating solar-like stars. We adopted the rotating mixing-length Theory to model the influence of rotation on convection. We used the MESA stellar evolution code and the GYRE stellar oscillation code to estimate the power injected in the oscillations from our theoretical prescriptions. We demonstrate that the power injected in the acoustic modes is insensitive to rotation if a Gaussian time-correlation function is assumed, while it can decrease by up to 60 % for a Lorentzian time-correlation function, for a $20 Ω_ ⊙ $ rotation rate. We show that the modification of the excitation rate by rotation depends not only on the rotation rate but also on the radial and angular orders of the considered oscillation mode. This result can allow for better constraints on the properties of stellar convection by studying observationally acoustic mode excitation. These results demonstrate how important it is to take into account the modification of stellar convection by rotation when evaluating the amplitude of the stellar oscillations it stochastically excites. They open the path for understanding the large variety of observed acoustic-mode amplitudes at the surface of solar-like stars as a function of surface rotation rates.

Where is the Supervirial Gas? II. Insight from the Survey of Galactic Sightlines

Abstract Recent observations have revealed a supervirial temperature gas phase at log(T/K) ∼ 7 in the Milky Way, challenging existing galaxy formation models. This hot gas phase was discovered toward extragalactic absorption sightlines and blank-sky emission fields, both at high Galactic latitudes. The location of this hot component is unknown; is it in the extended circumgalactic medium (CGM) or in the interstellar medium (ISM) instead? We analyzed X-ray spectra from Chandra’s High-Energy Transmission Grating observations of 27 Galactic X-ray binaries (XRBs) to investigate whether the hot gas component is present in the ISM. We searched for absorption lines of S xvi Kα, Si xiv Kα, and Ne x Kα, which are the telltale signatures of the hot gas and which have been detected toward extragalactic sightlines. Of the 27 targets, these lines were detected in the spectra of only 7, with two sources displaying broad line features likely intrinsic to the XRB systems. Additionally, most of the detected lines are time variable, reinforcing their likely association with the XRBs. Our results suggest that the supervirial temperature gas is not a widespread component of the ISM but may instead be located in extraplanar regions or the extended CGM, which aligns with some recent simulation results.

A-posteriori error estimates for systems of hyperbolic conservation laws via computing negative norms of local residuals

Abstract We prove rigorous a-posteriori error estimates for first-order finite-volume approximations of nonlinear systems of hyperbolic conservation laws in one spatial dimension. Our estimators rely on recent stability results by Bressan, Chiri and Shen, a new way to localize residuals and a novel method to compute negative-order norms of these local residuals. Computing negative-order norms becomes possible by suitably projecting test functions onto a finite dimensional space. Numerical experiments show that the error estimator converges with the rate predicted by a-priori error estimates.

Enhancing postharvest food safety: the essential role of non-thermal technologies in combating fungal contamination and mycotoxins.

During the production and storage of agricultural products, molds frequently occur as contaminants that can produce a wide range of secondary metabolites, the most important of which are mycotoxins. To solve these problems, the industry uses various methods, products and processes. This review examines the latest advances in novel non-thermal technologies for post-harvest inactivation of filamentous fungi and reduction of mycotoxins. These technologies include high pressure processes (HPP), ozone treatment, UV light, blue light, pulsed light, pulsed electric fields (PEF), cold atmospheric plasma (CAP), electron beams, ultrasound (US) and nanoparticles. Using data from previous studies, this review provides an overview of the primary mechanisms of action and recent results obtained using these technologies and emphasizes the limitations and challenges associated with each technology. The innovative non-thermal methods discussed here have been shown to be safe and efficient tools for reducing food mold contamination and infection. However, the effectiveness of these technologies is highly dependent on the fungal species and the structural characteristics of the mycotoxins. New findings related to the inactivation of fungi and mycotoxins underline that for a successful application it is essential to carefully determine and optimize certain key parameters in order to achieve satisfactory results. Finally, this review highlights and discusses future directions for non-thermal technologies. It emphasizes that they meet consumer demand for clean and safe food without compromising nutritional and sensory qualities.

Accelerated Objective Gap and Gradient Norm Convergence for Gradient Descent via Long Steps

This work considers gradient descent for L-smooth convex optimization with stepsizes larger than the classic regime where descent can be ensured. The stepsize schedules considered are similar to but differ slightly from the recent silver stepsizes of Altschuler and Parrilo. For one of our stepsize sequences, we prove a [Formula: see text] convergence rate in terms of objective gap decrease and for the other, we show the same rate of decrease for squared-gradient-norm decrease. This first result improves on the recent result of Altschuler and Parrilo by a constant factor, while the second results improve on the exponent of the prior best squared-gradient-norm convergence guarantee of [Formula: see text]. Funding: B. Grimmer’s work was supported in part by the Air Force Office of Scientific Research under award number FA9550-23-1-0531.

Patients Presenting With Reflux Symptoms - Whom to Test and Whom to Treat?

Gastroesophageal reflux disease (GERD) is a complex condition with diverse clinical presentations, ranging from typical heartburn and regurgitation symptoms to extraesophageal manifestations and alarm symptoms. Determining which patients should be tested first versus those who should receive empirical treatment remains a key clinical challenge. If not recently performed, initial patient testing, commonly involving upper endoscopy, is recommended for patients presenting with alarm or refractory symptoms and for those at high risk for Barrett’s esophagus. Additionally, testing should be prioritized for patients with underlying comorbidities, such as scleroderma, increased body mass index, or a suspected large hiatal hernia. Older patients with atypical symptom presentations and those with extraesophageal symptoms or signs, especially in the absence of typical GERD symptoms, should also be referred for endoscopy if recent endoscopic results are not available. In contrast, patients with typical GERD symptoms in the absence of alarm features and those with extraesophageal symptoms accompanied by typical GERD symptoms could begin empirical treatment with a proton pump inhibitor (PPI) or potassium competitive acid blocker (PCAB). For individuals without alarm symptoms who do not respond to once-daily PPI therapy, escalation to twice-daily PPI therapy or switching to a PCAB, without further testing, is appropriate. Overall, an individualized approach is recommended, with patient presentation guiding the decision to test or treat first.

Optimization of Relevant Functions of Urban Computing in the Direction of Traffic Flow Prediction

As an important application direction of urban computing, traffic flow prediction plays an important role in modern traffic management, urban planning and sustainable development. In recent years, many cutting-edge studies in the field of traffic flow prediction have had a significant impact and promoted the development of practical applications in this field. This paper mainly focuses on the research results of various traffic prediction directions. According to the actual environment and the functional characteristics of the research results, the research is classified into three aspects: data acquisition, feature engineering, and prediction model optimization. It also summarizes the optimization effects of research on traffic flow prediction in sensor data acquisition, data outlier processing, neural network prediction technology, etc. This paper first proposes three important aspects that affect traffic flow prediction and classifies recent research results. Then, the functions and impacts are analyzed from various aspects, and the advantages and progress of the research results are analyzed by comparing most mainstream methods. Then, the problems and limitations of the research are analyzed and discussed in combination with the actual road environment. Finally, the future research direction and development trend of this field are prospected, and the full text is summarized.

Recent Developments in the Management of Renal Cell Cancer.

The management of renal cell carcinoma (RCC) has seen significant advancements in recent years with the introduction of novel therapeutic agents and combination regimens. Immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape, particularly for advanced and metastatic RCC, where ICI-based combinations have shown substantial improvements in survival outcomes. Dual immunotherapy combinations, such as nivolumab plus ipilimumab, and ICI-vascular endothelial growth factor (VEGF) tyrosine kinase inhibitor (TKI) combinations, including pembrolizumab with axitinib, nivolumab with cabozantinib, and pembrolizumab with lenvatinib, have demonstrated overall survival (OS) benefits in first-line treatment, redefining the standard of care for advanced RCC. Adjuvant pembrolizumab is also approved for resected high-risk RCC and is the only adjuvant therapy that prolongs the OS in RCC. Additionally, the development of belzutifan, a hypoxia-inducible factor-2 alpha inhibitor, offers a new treatment option for patients whose disease progresses after ICI and VEGF TKI therapies. Recent results from CONTACT-3 and TiNiVo-2 confirm that ICI rechallenge should be generally discouraged. This review provides a detailed overview of the current evidence supporting immune-based combinations and novel agents such as belzutifan, as well as insights into treatment sequencing strategies for RCC.

Capacity of fullerenols to modulate neurodegeneration induced by ferroptosis: Focus on multiple sclerosis.

Capacity of fullerenols to modulate neurodegeneration induced by ferroptosis: Focus on multiple sclerosis.

Radial projection theorems in finite spaces

Motivated by recent results on radial projections and applications to the celebrated Falconer distance problem, we study radial projections in the setting of finite fields. More precisely, we extend results due to Mattila and Orponen [Proc. Amer. Math. Soc. 144 (2016), pp. 3419–3430], Orponen [Bull. Lond. Math. Soc. 50 (2018), pp. 1–6], and Liu [Rev. Mat. Iberoam. 37 (2020), pp. 1307–1319] to finite spaces. In some cases, our results are stronger than the corresponding results in the continuous setting. In particular, we solve the finite field analog of a conjecture due to Liu and Orponen on the exceptional set of radial projections of a set of dimension between d − 2 d-2 and d − 1 d-1 .

Fractional Analytic QCD: The Recent Results

In this work, we present an overview of the recent results, obtained in the framework of the fractional analytic QCD in the space-like (Euclidean) and time-like regions. The Higgs boson decays into a bottom–antibottom pair, and the polarized Bjorken sum rule is considered as an application of the obtained results.

The Italian government’s relations with the EU and with European and G7 leaders

In the first half of 2024, the Italian government has confirmed a collaborative approach with the European Union institutions and leaders based on pragmatism, in particular in the economic sector, on the support to Ukraine against the Russian aggression, and on migration.In parallel, Meloni jas consolidated her relations with international leaders and realunched her politicl agenda, in particular the Mattei Plan for Africa, through the Italian Presidency of the G7. The campaign for the June European elections has exposed political divergences on European affairs within the government’s coalition, and Giorgia Meloni has been marginalised in the negotiations for the new EU top positions, then partly recovered through the assignment of a weighty role to the Italian Commissioner. This chapter illustrates the political trajectory of the Italian government in its European and foreign policy, also in light of the recent electoral results in the United States, and identifies the possible repercussions on the role of the country at European and international level.

Bayesian variance change point detection with credible sets.

This paper introduces a novel Bayesian approach to detect changes in the variance of a Gaussian sequence model, focusing on quantifying the uncertainty in the change point locations and providing a scalable algorithm for inference. We do that by framing the problem as a product of multiple single changes in the scale parameter. We fit the model through an iterative procedure similar to what is done for additive models. The novelty is that each iteration returns a probability distribution on time instances, which captures the uncertainty in the change point location. Leveraging a recent result in the literature, we can show that our proposal is a variational approximation of the exact model posterior distribution. We study the convergence of the algorithm and the change point localization rate. Extensive experiments in simulation studies and applications to biological data illustrate the performance of our method.

Quantitative Mechanochemistry: A Chemical Tool to Bridge Polymer Physics and Mechanics of Soft Polymer Networks.

In recent years, mechanochemistry has imposed itself as a novel promising chemical tool to bridge the gap between polymer physics and continuum mechanics in soft materials. The suitable incorporation of force-sensitive molecules (mechanophores) in load-bearing positions in soft (entropic) polymer networks and in linear chains has provided a tool to detect stresses and bond scission in 2D and 3D through the intensity of an optical signal. We review recent results linking the optical signal detected upon mechanophore activation with the applied mechanical load. Recent investigations have addressed critical questions, such as detecting and quantifying stress fields and measuring quantitative damage by bond scission in diverse cases, including failure in uniaxial tension, crack propagation in continuous loading, cyclic fatigue, or crack initiation in uniaxial and triaxial tension. We also discuss the requirements to go from simple imaging to quantitative detection, enabling comparisons between different materials and the calibration of continuum mechanics models. In ideal cases, the optical signal provides highly sensitive information on the size and intensity of damage zones in front of cracks-regions that would otherwise be undetectable.

Gravitational memory: new results from post-Newtonian and self-force theory

Abstract We compute the (displacement) gravitational wave memory due to a quasicircular inspiral of two black holes using a variety of perturbative techniques. Within post-Newtonian theory, we extend previous results for non-spinning binaries to 3.5PN order. Using the gravitational self-force approach, we compute the memory at first order in the mass ratio for inspirals into a Kerr black hole. We do this both numerically and via a double post-Newtonian--self-force expansion which we carry out to 5PN order. At second order in the self-force approach, near-zone calculations encounter an infrared divergence associated with memory, which is resolved through matching the near-zone solution to a post-Minkowskian expansion in the far zone. We describe that matching procedure for the first time and show how it introduces nonlocal-in-time memory effects into the two-body dynamics at second order in the mass ratio, as was also predicted by recent 5PN calculations within the effective field theory approach. We then compute the gravitational-wave memory through second order in the mass ratio (excluding certain possible memory distortion effects) and find that it agrees well with recent results from numerical relativity simulations for near-comparable-mass binaries.

Multiple geodesic acoustic modes destabilization in the presence of energetic particles with finite orbit width effects

Abstract Finite orbit width (FOW) effects on energetic particle induced geodesic acoustic modes (EGAMs) are investigated using gyrokinetic theory. A dispersion relation is derived, accounting for the FOW effects and assuming a double-shifted Maxwellian distribution in parallel velocity for energetic particles. Numerical solutions of the dispersion relation show good agreement with gyrokinetic simulations. The FOW effects are shown to enhance EGAM damping, consistent with their conventional role in GAM dynamics. Interestingly, when the FOW becomes large enough, a new unstable EGAM branch, referred to as δEGAM, emerges at a higher frequency than the GAM. This phenomenon is consistent with recent analytic EGAM results obtained using a slowing-down distribution for energetic particles. Depending on the safety factor and the parallel velocity shift of energetic particles, the δEGAM shows two distinct destabilization patterns and its relationship with the GAM. Based on these characteristics, the δEGAM is classified into two types, each showing a distinct energetic particle density threshold and frequency range. If energetic particles exhibit a positive slope at the FOW-induced transit resonance, their kinetic energy is transferred to the δEGAM via inverse Landau damping.

Multimodal Pre-Training of Vision Models Yields Better Embeddings for Visual Art

Deep pre-trained vision models provide automated ways of analyzing large digitized corpora of visual art. Central to the success of these models is their ability to extract rich embeddings for downstream tasks such as style classification or painting retrieval. Recent results suggest that multimodal models trained on a combination of visual and linguistic input yield semantically enhanced and higher-quality representations of images compared to unimodal vision models. While these multimodal models seem extremely promising for the computational study of visual art, where semantic knowledge might be relevant to produce informative representations of artworks, research benchmarking multimodal models for feature extraction in the art domain is limited, and their potential for representing visual art remains to be explored. This paper aims to fill this gap, and it compares the representational abilities of seven uni-modal and multimodal state-of-the-art pre-trained vision models by employing their embeddings in three domain-specific downstream tasks: genre classification, style classification, and artist classification in the WikiArt dataset. Results reveal that multimodal models perform best as feature extractors for artworks as opposed to unimodal models. We hypothesize that pre-training on natural language descriptions provides multimodal models with enhanced abilities to infer global semantic representations of an image, which is beneficial to identifying key characteristics of artworks such as their genre, author, and style.

Note on disjoint faces in simple topological graphs

Note on disjoint faces in simple topological graphs

Precision timing measurements at the CMS ETL with Low-Gain Avalanche Diodes

Precision timing measurements at the CMS ETL with Low-Gain Avalanche Diodes

Correlations between the pediatric sleep questionnaire and the pediatric overnight pulse oximetry.

Correlations between the pediatric sleep questionnaire and the pediatric overnight pulse oximetry.