Theoretical kinetic study of the reactions between pyridyl radicals and O2

Reactions of the primary pyridine radicals, ortho-, meta-, and para-pyridyls with oxygen control the overall rate of pyridine oxidation. In the present work, the potential energy surfaces of o-, m-, and p-pyridyls + O2 previously developed by the authors have been employed for a systematic theoretical kinetic study of the rate constants of these reactions. The geometries of reactants, products, intermediates, and transition states of the reactions of pyridyl radicals with O2 were optimized at the level of density functional theory using the ωB97XD functional with the 6-311G** basis set. The temperature- and pressure-dependent rate constants of 31 reactions were evaluated within the framework of the Rice-Ramsperger-Kassel-Marcus (RRKM) theory combined with the Master Equation approach (RRKM–ME) in the temperature range from 300 to 3000 K, covering pressures from 0.01 to 100 atm. For several reactions previously investigated in the literature, good agreement was demonstrated, indicating consistency and correctness of the present theoretical calculations. Moreover, thermodynamic data for all important reactants, products, and intermediates have been revisited and calculated at the G4 theoretical level. The calculated rate constants and thermodynamic data provide a backbone for the development of detailed kinetic models for pyridine combustion

Towards effective decision support for structural design and risk management : An information-dependent probabilistic system representation enhanced with support vector machine and unfair sampling

Structural design and risk management typically involve uncertainties related to structural performance and loading conditions, which must be effectively managed to ensure compliance with safety requirements. Additionally, the relationships among parameters influencing structural performance are often complex and not easily discernible, thereby complicating the decision-making process. To address these challenges, this paper proposes a decision support framework based on the concept of information-dependent probabilistic system representation. The framework aims to identify unacceptable design parameters in structural design and enhance risk management by updating probabilistic models of uncertain parameters for similar structures when new observational information becomes available. To overcome the computational challenges of structural reliability analysis, a support vector machine (SVM) is employed as a surrogate model for the finite element analysis typically used to evaluate the performance of engineering structures. Additionally, to handle the imbalance issue in the SVM training dataset, an unfair sampling method is introduced. An illustrative example involving a reinforced concrete structure subjected to earthquake loading is presented to demonstrate the effectiveness of the proposed framework

Oxy-ethane combustion : Measurements of the laminar burning velocities and kinetic insights into CO2 effects

Oxy-fuel combustion is regarded as an underpinning technology for carbon capture and utilization. Ethane (C2H6) is the primary non-methane component in natural gas and a fundamental C2 fuel. In this work, laminar burning velocities (LBV) of C2H6/O2/CO2 mixtures were measured using the heat flux method at atmospheric pressure, spanning initial temperatures of 308–348 K, equivalence ratios of 0.6–1.5, and CO2 fractions of 0.16–0.75. The temperature dependence of the LBV of C2H6/O2/CO2 mixtures was first determined, and the consistency of the new measurements was validated. Evaluations of three kinetic models (Oxymech 2.0, Konnov 2023, Alzueta 2015) demonstrated that Oxymech 2.0 accurately predicts LBVs and ignition delay times (IDTs) across all conditions. Nonlinear variation of LBV with CO2 amount in the mixture was observed from both experiments and simulations. Decoupling thermal, transport, and chemical effects revealed that the thermal and transport inhibiting effects of CO2 linearly increase with CO2 concentration, while CO2′s chemical inhibition initially strengthens (CO2 range: 0.16–0.39), then plateaus (CO2: 0.39–0.65). This nonlinearity stems from the reaction CO + OH=H + CO2 depleting H radicals, suppressing chain-branching, while the reduced ratio of 2CH3=H + C2H5 versus C2H4 + H(+M)=C2H5(+M) (promoting flame propagation) offsets inhibition at higher CO2 fractions

Impact of deep learning model uncertainty on manual corrections to MRI-based auto-segmentation in prostate cancer radiotherapy

Background: Deep learning (DL)-based organ segmentation is increasingly used in radiotherapy. While methods exist to generate voxel-wise uncertainty maps from DL-based auto-segmentation models, these maps are rarely presented to clinicians. Purpose: This study aimed to evaluate the impact of DL-generated uncertainty maps on experienced radiation oncologists during the manual correction of DL-based auto-segmentation for prostate radiotherapy. Methods: Two nnUNet DL models were trained with 10-fold cross-validation on a dataset of 434 patient cases undergoing ultra-hypofractionated MRI-only radiotherapy for prostate cancer. The models performed prostate clinical target volume (CTV) and rectum segmentation. Each cross-validation model was evaluated on an independent test set of 35 patient cases. Segmentation uncertainty was calculated voxel-wise as the SoftMax standard deviation (0–0.5, n = 10) and visualized as a fixed scale color-coded map. Four experienced oncologists were asked to:. Step 1: Rate the quality of and confidence in the DL segmentations using a four- and five-point Likert scale, respectively, and edit the segmentations without access to the uncertainty map. Step 2: Repeat step 1 after at least 4 weeks, but this time with the color-coded uncertainty map available. Oncologists were asked to blend the uncertainty map with the DL segmentation and MRI volume. Segmentation edit time was recorded for both steps. In step 2, oncologists also provided free-text feedback on the benefits and drawbacks of using the uncertainty map during segmentation. A histogram analysis was performed to compare the number of voxels edited between step 1 and step 2 for different uncertainty levels (bins with 0.1 intervals). Results: The DL models achieved high-quality segmentations with a mean Dice coefficient per oncologist of 0.97–0.99, calculated between edited and unedited segmentation in step 1 for the prostate CTV and rectum. While the overall quality rating for rectum segmentations decreased slightly on a group level in step 2 compared to step 1, individual responses varied. Some oncologists rated the quality higher for the prostate CTV segmentation with the uncertainty map present, while others rated it lower. Similarly, confidence ratings varied across oncologists for prostate CTV and rectum. Decreased segmentation time was recorded for three oncologists using uncertainty maps, saving 1–2 min per patient case, corresponding to 14%–33% time reduction. Three oncologists found the uncertainty maps helpful, and one reported benefit was the ability to identify regions of interest more quickly. The histogram analysis had fewer voxel edits in regions of low uncertainty in step 2 compared to step 1. Specifically, 50% fewer voxel edits were recorded for the uncertainty region 0.0–0.1, suggesting increased trust in the DL model's prediction in these areas. Conclusions: Presenting DL uncertainty information to experienced radiation oncologists influences their decision-making, quality perception, and confidence in the DL segmentations. Regions with low uncertainty were less likely to be edited, indicating increased reliance on the model's predictions. Additionally, uncertainty maps can improve efficiency by reducing segmentation time. DL-based segmentation uncertainty can be a valuable tool in clinical practice, enhancing the efficiency of radiotherapy planning

Evaluation of Software-Optimized Protocols for Acoustic Noise Reduction During Brain MRI at 7 Tesla

Background: MR-generated acoustic noise may be particularly concerning at 7-Tesla (T) systems. Noise levels can be reduced by altering gradient output using software optimization. However, such alterations might influence image quality or prolong scan times, and these optimizations have not been well characterized. Purpose: To evaluate image quality, sound pressure levels (SPLs), and perceived noise levels when using the acoustic noise reduction technique SofTone for T2-weighted fast spin echo (T2W FSE) and three-dimensional T1-weighted turbo field echo (3D T1W TFE), and to compare with conventional imaging during 7-T brain MRI. Study Type: Prospective. Subjects: Twenty-eight volunteers underwent brain MRI, with n = 26 for image quality evaluations. Field Strength/Sequence: Conventional and SofTone versions of T2W FSE and 3D T1W TFE at 7 T. Assessment: Peak SPLs (A-weighted decibels, dBA), participant-perceived noise levels (Borg CR10-scale), qualitative image assessments by three neuroradiologists (four-graded ordinal scales), interrater reliability, and percentage agreement. Statistical Test: Paired t-test, Wilcoxon's Signed-Rank Test, and Krippendorff's alpha; p < 0.05 were considered statistically significant. Results: SofTone significantly reduced peak SPLs: from 116.3 to 97.0 dBA on T2W FSE, and from 123.7 to 101.5 dBA on 3D T1W TFE. SofTone was perceived as significantly quieter than conventional scanning. T2W FSE showed no significant differences in image quality assessments (p = 0.21–1.00), except one radiologist noting significantly less artifact interference with SofTone. General image quality remained acceptable for 3D T1W TFE, though one radiologist scored it significantly lower with SofTone (mean scores: 3.08 vs. 3.65), and two radiologists observed significantly worse white and gray matter differentiation with SofTone (mean scores: 3.19 vs. 3.54; 2.27 vs. 2.81). Data Conclusion: SofTone can significantly reduce sound intensity and perceived noise levels while maintaining acceptable image quality with T2W FSE and 3D T1W TFE in brain MRI. It appears to be an effective tool for providing a safer, quieter 7-T scan environment. Evidence Level: 4. Technical Efficacy: Stage 5

Der Iran-Israel-Krieg: Ein massives Versagen der Gegenspionage und das strategische Auseinanderbrechen der Islamischen Republik

The Iran-Israel war, launched on June 13, 2025, marked a historic intelligence failure for the Islamic Republic. Israel’s surprise offensive devastated Iran’s military leadership and exposed deep systemic flaws in its counterintelligence apparatus. The strategic collapse of the regime now raises urgent questions about its survivability and the necessity of regime change

River flow response to changing electricity demand and centralized hydropower operations in the Paranapanema River basin, Brazil

Study region: The Paranapanema River Basin, located in southeastern Brazil, is characterized by a cascade of large hydropower plants regulated by a nationally coordinated dispatch system. This basin is a representative case of reservoir-regulated rivers in the country, where multiple dams interact to supply electricity while reshaping natural flow regimes. Study focus: This study examines hydropower-induced variability in river discharge and reservoir volumes using multiresolution wavelet decomposition and signal reconstruction. By analyzing continuous records under operational conditions, the method isolates fluctuations from sub-daily to multi-annual scales. This approach moves beyond average-based analyses, providing a scale-specific view of hydropower modulation. It shows how discharge dynamics arise not only from cascade configuration but also from dispatch coordination, plant design, and hydrological conditions. New hydrological insights for the region: Results show that flow variability patterns align with electricity demand profiles, drought episodes, and institutional milestones in the Brazilian power sector. Hydropower operations display distinct signatures at different time scales, highlighting the responsiveness and complexity of reservoir management. Reconstructing signals in original units improves interpretability and supports regulatory evaluation and energy planning. The proposed framework provides a standardized and reproducible way to assess variability in reservoir-regulated systems, enhancing comparability of hydropower assessments and identifying operational dynamics that shape river flow regimes. It also supports more adaptive and ecologically grounded approaches to hydropower governance in the Paranapanema Basin and beyond

Integrating flight mechanics, energetics and migration ecology in vertebrates

Animal locomotion is constrained by Newtonian laws of motion and therefore biomechanics is a useful approach for quantitative analysis of force and power requirements. Aerial locomotion in vertebrates is no exception, and arguably the most significant developments are to be found in this journal. Evolutionary birds and bats are very successful groups, doubtless largely because of their ability to shift location in a short time. This has enabled birds and to a lesser extent bats to perform seasonal long-distance migrations between habitats suitable for reproduction and survival. Power required to fly and potential flight range in relation to fuel load are two fundamental relationships derived from flight mechanics, which both serve as a foundation for the development of optimal migration theory. From this framework where biomechanics, energetics and ecology combine, we can analyse which of the alternative strategies migrants adopt. Such adaptive behaviours include the selection of optimal flight speed and the migratory travel itinerary. However, despite decades of research efforts, there are still many unsolved problems concerning flight mechanics and energetics of vertebrate flight. One such is how the power–speed relationship maps onto metabolic rate during flight, the so-called energy conversion efficiency. There is conflicting empirical evidence concerning how energy conversion possibly varies with flight speed, body mass and body size. As ultimately it is the metabolic energy consumption that is under selection pressure, this is an urgent question for the utility of flight mechanical principles in ecology. In this Review, I discuss this and other knowledge gaps in vertebrate flight and migration

Nordic Society for Radiation Protection - An important forum for radiological protection knowledge

The Nordic Society for Radiation Protection (NSFS) was founded in 1964 at the initiative of Rolf Sievert. Its task is to activate the exchange of knowledge and experience in the Nordic countries regarding protection against ionizing and non-ionizing radiation, for all kinds of occupational, medical, or public exposures. NSFS has always included members from all five Nordic countries and was a founding member of IRPA, the International Radiation Protection Association. Since 1966, NSFS has had regular meetings at 3- or 4-year intervals, in turn in each of the Nordic countries. In addition, NSFS has arranged various themed meetings. The meetings of the Society have been informal and collaborative and important for transfer of skills between generations. The activities have stimulated Nordic co-operation regarding nuclear safety research, nuclear waste, radioecology, medical radiology, and clinical physics, as well as Nordic postgraduate courses. NSFS lives up to the IRPA motto of being the international voice of the RP profession

Gravitational waves from supercooled phase transitions in conformal Majoron models of neutrino mass

We study supercooled first-order phase transitions above the QCD scale in a wide class of conformal Majoron-like U(1)′ models that explain the totality of active neutrino oscillation data and produce a detectable stochastic gravitational wave background (SGWB) at LIGO, LISA and ET. We place constraints on the U(1)′ breaking scale and gauge coupling using current LIGO-Virgo-Kagra data. We find that strong supercooling can be ruled out in large regions of parameter space if a SGWB is not detected by these experiments. A null signal at LIGO and ET will disfavor a type-I seesaw scale above 1014 GeV, while a positive signal is a signature of heavy right-handed neutrinos. On the other hand, LISA will be sensitive to seesaw scales as low as a TeV, and could detect a SGWB even if the right-handed neutrinos are decoupled