Browse Articles

Optimising the caffeine nap for counteracting driver sleepiness in CPAP treated obstructive sleep apnoea patients

Abstract Driver sleepiness contributes to a substantial proportion of road crashes. Drivers experiencing sleepiness are advised to take a break and have a caffeinated drink followed by a short nap (caffeine nap). However, previous research advocating this countermeasure has not considered participants with obstructive sleep apnoea (OSA), the most prevalent sleep disorder. Across three studies the effectiveness of caffeine, nap opportunity and caffeine nap countermeasures on subjective sleepiness (KSS), objective sleepiness (Alpha and Theta activity) and driving performance (standard deviation of lateral position and out-of-lane events) are considered. Twenty-one CPAP treated OSA participants (mean age = 59 years) engaged with a protocol of six laboratory visits: one after a normal night’s CPAP-treated sleep and five after sleep restriction (4 h CPAP-treated sleep), driving a monotonous simulated scenario before and after a countermeasure. Results showed that two cans of coffee (255 mg caffeine) mitigated driver sleepiness more than one can (127.5 mg) and little benefit to 30 min compared with 15 min nap opportunity. An optimised caffeine nap of two coffees followed by a 15 min nap opportunity provides some temporary benefit, but for OSA drivers a caffeine nap offers little practical improvement compared to two coffees alone. All countermeasures are temporary and cannot replace a good night of sleep before driving.

Spectroscopic and lifetime measurements of C2 in the 33Πg and 43Πg states

Spectroscopic and lifetime measurements of C2, one of the most important diatoms in the universe, provide valuable insights into its molecular structure, electronic transitions, and dissociation dynamics. In this work, we present an experimental investigation of the high-lying 33Πg and 43Πg states of C2 in the ultraviolet region. By using the resonance-enhanced multi-photon ionization (REMPI) scheme in combination with the spectral hole-burning technique, a new vibronic transition band assigned as 33Πg(vʹ = 6)−a3Πu(vʹʹ = 5) is identified. The spectroscopic parameters are derived, and the vibrational levels of the 33Πg state are analyzed based on the newly obtained spectra. In addition, by employing the UV-pump–UV-probe scheme, the rotational state lifetimes in various vibrational levels of the 33Πg and 43Πg states are experimentally measured. The measurements reveal complex dependencies of the lifetimes on both the vibrational and rotational quantum numbers. Our findings advance the understanding of the excited state dynamics of C2 and underscore the further need for theoretical calculations to elucidate its high-lying potential energy surfaces and their mutual interactions, which are important for modeling the carbon chemistry in various gas environments.

Assessment of thermally induced strength loss in alkali-activated concrete through ensemble regression models

Local diffusion analysis using square displacement averaged in subspace

There is a well-known linear relation between the mean square displacement (MSD) and time, with the slope corresponding to the global diffusion coefficient of the particle of interest. Similarly, the local MSD computed as a statistical average over a subspace of the system exhibits a nonlinear relationship with time, reflecting the local diffusion coefficient within the subspace. Thus, by analyzing this relationship, we can extract the local diffusion coefficient. To enable this analysis, in this work, we derived an analytical expression for the nonlinear behavior of the local MSD using the Edgeworth expansion up to fourth order. Combining this expression with regression analysis, we estimated the local diffusion coefficient of a hydrogen molecule in homogeneous bulk water as a proof of concept. As a result, at a spatial resolution as high as 0.23 nm, the estimated local diffusion coefficients deviate by less than 20% from the reference value obtained from the standard linear relation between the regular MSD and time. We also demonstrated the utility of our approach in heterogeneous systems by analyzing the diffusion of a methane molecule in aqueous solution near a hydrophobic interface. The estimated local diffusion coefficients of the methane molecule are in good agreement with previous studies, except in a specific region ∼0.6 nm from the interface, where the influence of higher-order terms of the Edgeworth expansion omitted in this work becomes significant. This limitation is shared by previous approaches, and resolving this issue remains a challenge for future work in local diffusion analysis.

Projection Kernel regularization for diffusion-based multimodal remote sensing segmentation

Formation and rearrangement of HCCF⋯HF complexes after CF2CH2 photolysis: A matrix isolation and <i>ab initio</i> study

Studies on the reactions between neighbors and rearrangements occurring in noble gas matrices in the same matrix cage at temperatures of a few kelvins may improve our understanding of intermolecular interactions, quantum-mechanical tunneling, and the effect of a medium on low-temperature processes. Here, we present experimental evidence of the rearrangement of HCCF⋯HF complexes taking place in solid Ar at 5.5 K. The complexes were obtained by 193 nm photolysis of CF2CH2 matrix-isolated precursors and characterized on the basis of CCSD(T) computations and available literature data. The absorption bands, which remain virtually unchanged during the argon matrix standing in the dark at 5.5 K after photolysis (set III), were attributed to the T-shaped HCCF⋯HF complex (π-complex), while those observed to increase (set I) were assigned to the “hockey-stick”-shaped FCCH⋯FH complex (FH-complex). The decrease in another group of absorption bands (set II) was found to negatively correlate with the growth of I, indicating II → I rearrangement. The speed of the process is roughly the same in the 5.5–6.5 K region and dramatically increases at higher temperatures. Set II was attributed to the L-shaped complex of the FCCH⋯FH geometry stabilized by a matrix (outlined here as point L). No similar transformations were observed in solid Ne, Kr, and Xe, making this process a remarkable example of a matrix-specific rearrangement.

A multivariate decomposition analysis of urban–rural disparities in contraceptive use among women in Ethiopia

Efficient recursive Gaussian integral calculation of anion photodetachment cross sections

Photodetachment cross sections (PDCSs) are key parameters for quantitatively characterizing the generation and annihilation of anions, with transition moment integrals being the critical component in their theoretical calculation. This work introduces an efficient method for calculating transition moments within the plane wave approximation, based on the analytical expressions of the recursive Cartesian two-center Gaussian integral. This method effectively bypasses the convergence issues commonly associated with traditional plane wave expansion techniques. By incorporating the random orientation of gas-phase molecular anions, the total PDCSs can be derived. For molecules with low anisotropy wavefunctions, the integration is further simplified to three orthogonal directions, dramatically reducing computational costs. Benchmark tests on a variety of atomic and molecular anions (H−, Li−, C−, O−, F−, S−, Cl−, OH−, NH2−, CN−, and C2H−) show excellent agreement with previous experimental measurements and high-level theoretical results. Furthermore, the method’s superior computational efficiency is demonstrated through applications to larger systems, such as benzyl anion, glycine anion, and water tetramer anion. The proposed method holds significant potential for advancing the field of vacuum ultraviolet photochemistry.

Apigenin combined with aerobic exercise alleviates oxidative stress and inflammation in high-fat diet-induced NAFLD mice by modulating the Keap1/Nrf2/ARE pathway

Modular construction of Jastrow factors for the transcorrelated method

In this work, we explore the reuse of terms in the Jastrow factor between systems for use in the transcorrelated method to reduce the number of optimizable parameters for a given system. In particular, we propose a workflow in which atom-specific parts of Jastrow factors, optimized in atoms, may be reused in the molecule, with only a few parameters in the electron–electron part of the Jastrow left to optimize, while maintaining performance. We find that the modified workflow not only reduces the number of terms needing to be optimized but can also improve the accuracy of xTC-CCSD(T) energies.

Development and validation of a gra1–bag1 RT-qPCR assay as an alternative to the mouse bioassay for assessing Toxoplasma gondii viability

Magic wavelengths with QED correction for the 23 <i>S</i> 1 → 23 <i>P</i> <i>J</i> transitions of helium-4

A series of magic wavelengths for the 23S1 → 23PJ (J = 0, 1, 2) transitions in helium is determined with high precision using the relativistic configuration interaction combined with the radiative potential method. The calculation explicitly incorporates relativistic, finite nuclear mass, and quantum electrodynamic corrections through the inclusion of mass shift and radiative potential operators into the Dirac–Coulomb–Breit Hamiltonian. The resulting magic wavelengths lie entirely within the visible spectrum (400–700 nm) and converge to seven significant digits, making them directly accessible for experimental verification. These accurate predictions serve as benchmarks for testing atomic structure theory and support the development of state-insensitive optical trapping schemes in precision spectroscopy.

Enhanced smart commuting with artificial intelligence for intelligent health and safety monitoring in school buses

Abstract This paper introduces ESC.AI (Enhanced Smart Commuting with Artificial Intelligence) , an intelligent and integrated safety framework designed to improve health monitoring, environmental awareness, behavioral detection, driver supervision, and route optimization in school bus transportation systems. The proposed framework combines multimodal sensing, edge-based artificial intelligence, adaptive routing, and secure data management to enable proactive risk detection and real-time decision-making during transit. Although school buses remain one of the safest modes of transportation for students, recent national statistics continue to highlight persistent risks related to health emergencies, behavioral incidents, and environmental hazards. According to data from the National Safety Council (NSC) and the National Highway Traffic Safety Administration (NHTSA), school bus–related crashes resulted in 104 fatalities in the United States in 2022, representing a 3.7% decrease from 2021. Between 2013 and 2022, approximately 71% of fatalities involved occupants of other vehicles, 16% were pedestrians, and only 5% were school bus passengers. Injury statistics show a similar pattern, emphasizing the need for safety solutions that protect both students and surrounding road users. ESC.AI addresses these challenges through a unified platform that integrates Internet of Things (IoT) sensors for physiological and environmental monitoring, computer vision–based behavioral analysis, driver monitoring, and intelligent routing. Edge–cloud computing is employed to ensure low-latency responses, while blockchain-based mechanisms are used selectively to enhance data integrity, traceability, and access control for sensitive safety records. Together, these components form a cohesive and scalable framework aimed at improving transparency, responsiveness, and reliability in school transportation systems.

Analytical interaction potentials for disks in two dimensions

Compact analytical forms are derived for the interactions involving thin disks in two dimensions using an integration approach. These include interactions between a disk and a material point, between two disks, and between a disk and a wall. Each object is treated as a continuous medium of materials points interacting by the Lennard-Jones 12–6 potential. By integrating this potential in a pairwise manner, expressions for the potentials and resultant forces between extended objects are obtained. All the results are validated with numerical integrations. The analytical potentials are implemented in LAMMPS and used to simulate two-dimensional suspension of disks with an explicit solvent modeled as a Lennard-Jones liquid. In monodisperse disk suspensions, a disorder-to-order transition of disk packing is observed as the area fraction of disks is increased or as the solvent evaporates. In bidisperse disk suspensions being rapidly dried, stratification is found with the smaller disks enriched at the evaporation front. Such “small-on-top” stratification echoes the similar phenomenon occurring in three-dimensional polydisperse colloidal suspensions that undergo fast drying. These potentials can be applied to a wide range of two-dimensional systems involving disk-like objects.

Association of ACAG with short-term mortality in liver failure patients: a retrospective analysis based on the MIMIC-IV database

Abstract Traditional scoring systems are challenging for early diagnosis and intervention in liver failure. While albumin-corrected anion gap (ACAG) predicts adverse outcomes in various conditions, its effectiveness in liver failure remains unclear. This study analyzed hepatic failure patients from MIMIC-IV, stratified into Q1-Q4 by ACAG quartiles. Kaplan-Meier survival curves examined mortality differences. The connection of ACAG with mortality was examined using Cox regression and restricted cubic spline (RCS) analyses. Additionally, we compared the predictive performance of ACAG, MELD, and their combination for mortality using receiver operating characteristic (ROC) curve analysis, calculated the area under the curve (AUC), and compared the AUC values using the DeLong test. Finally, subgroup analyses were conducted to evaluate the relationship between ACAG and prognosis in different types of liver failure. Current study involving 2,016 patients with liver failure revealed 30- and 90-day mortality rates of 27.23% and 30.01%, respectively. Kaplan-Meier survival curves demonstrated mortality increased with ACAG levels. Multivariate Cox regression confirmed ACAG’s positive association with mortality [HR 1.032 (30-day), 1.031 (90-day); both P  &lt; 0.001], and the RCS showed a linear relationship. The AUCs for 30-day mortality were 0.641 (ACAG), 0.634 (MELD), and 0.668 (combined); the corresponding values for 90-day mortality were 0.630, 0.621, and 0.654. The AUC of the combined model was significantly higher than that of ACAG alone ( P  = 0.0009 and 0.0016) and MELD alone ( P  = 0.0004 and 0.0002) for 30- and 90-day mortality, respectively. Although ACAG yielded a marginally higher AUC than MELD, DeLong’s test indicated no significant difference ( P  = 0.7035 and 0.5387 for 30-and 90-day mortality, respectively). Subgroup analyses observed interactions in the age subgroups and CRRT subgroups; ACAG was consistently elevated in non-survivors across all liver-failure subtypes. Our study demonstrates that the ACAG index is significantly associated with mortality in patients with hepatic failure; its integration with the MELD score further enhances predictive accuracy.

Interaction-region decoupling for deep-well quantum dynamics: Overcoming the interpolation bottleneck and revealing the intrinsic high-energy efficiency

Deep-well chemical reactions pose a long-standing challenge for rigorous quantum dynamical calculations because of their extended interaction regions. The interaction-region decoupling (IRD) framework based on structured imaginary potentials offers a principled solution, but its practical efficiency has not yet been fully realized due to the prohibitive cost of mutual interpolation. Here, we introduce a block-wise interpolation scheme, in which the interaction region is divided into several spatial blocks and the wave function is interpolated only within the relevant blocks. The resulting IRD-based TDWP approach is applied to the O + OH reaction over a wide range of collision energies. Benchmark calculations show that the block-wise strategy removes the interpolation bottleneck and enables the IRD approach to achieve a speedup of about two orders of magnitude compared with the conventional TDWP method. Moreover, we find that increasing collision energy enhances SIP absorption, allowing for shorter absorbing regions and a reduced effective interaction region, which leads to further improvements in computational efficiency. Our work establishes IRD as a general and efficient framework for the quantum dynamics of complex-forming reactions.

Performance of a GPU- and time-efficient pseudo-3D network for magnetic resonance image super-resolution and motion artifact reduction

Abstract Minimizing acquisition time and motion-artifacts remains challenging in magnetic resonance imaging (MRI) with demands on high-resolution images for accurate diagnosis and treatment. Deep learning-based image restoration offers promising solution by generating high-resolution and artifact-free MR images from low-resolution or motion-corrupted data. To facilitate practical deployment in clinical workflows, this study presents a time-/GPU-efficient framework using 2D network (TS-RCAN) for pseudo-3D MRI super-resolution reconstruction (SRR) and motion-artifact reduction (MAR). Optimal down-sampling factors were identified to balance SRR accuracy and acquisition time. MAR training used a standardized method to induce controllable motion-artifacts of varying severity. Network performance was benchmarked against state-of-the-art 3D networks. Results showed the down-sampling factor $$1\times 1\times 2$$ for $$\times 2$$ acceleration and $$2\times 2\times 2$$ for $$\times 4$$ acceleration achieved optimal SRR performance. TS-RCAN outperformed most 3D networks by &gt; 0.01/1.5 dB in SSIM/PSNR while reducing GPU load and inference time by up to 90%. For MAR, TS-RCAN exceeded UNet by up to 0.014/1.48 dB in SSIM/PSNR. Additionally, uncertainty estimation correlated with image quality metrics, enabling accuracy prediction without ground truth. TS-RCAN provides an efficient, accurate framework for SRR and MAR with practical relevance to clinical MRI, and offers a flexible basis for future extension to other imaging contrasts and pathological cases.

Quantum dynamics of water dissociation on a Cu/Ni(111) bimetallic alloy surface: A nine-dimensional model

The dissociative chemisorption of water on a Cu/Ni(111) bimetallic alloy surface was investigated using a combined neural-network potential energy surface and quantum dynamics approach. A full-dimensional (9D) PES was constructed and validated, enabling efficient seven-dimensional (7D) quantum wave packet calculations. Approximate 9D dissociation probabilities were obtained by site-averaging the 7D, site-specific results. The Cu monolayer is under 3.2% compressive strain, leading to a higher barrier height of 1.20 eV on Cu/Ni(111) than on pure Cu(111) (1.08 eV) and, consequently, to lower dissociation probabilities. The more reactive subsurface Ni atom induces a distinct site reactivity order (hcp &amp;gt; fcc &amp;gt; bridge &amp;gt; top). Strong mode specificity was observed, where vibrational excitations of the symmetric stretching, asymmetric stretching, and bending modes of H2O were found to be more efficacious than increasing the translational energy in promoting the reaction, with the asymmetric stretching mode providing the greatest enhancement and the bending mode the smallest. This mode-specific behavior aligns with earlier findings for water dissociation on pure Cu(111) and Ni(111) surfaces.

Validation of ferroptosis in zebrafish as a reliable model for phenotypic studies

Structural and dynamic studies on vapor-deposited amorphous methane hydrate

Methane hydrate has been studied extensively not only as a future energy resource but also due to interest in quantum and classical rotations of methane molecules. In this study, amorphous methane hydrate (a-MH) was formed at 7 K by a low temperature vapor deposition method. To investigate the local amorphous structure and the dynamics of guest methane molecules, x-ray and neutron diffraction, quasi-elastic neutron scattering, and adiabatic calorimetry experiments were performed for both as-deposited and annealed samples. After the deposition, a-MH has a disordered and distorted cage-like structure. Annealing at 120 K promotes local hydrogen-bond ordering while keeping the amorphous state, and the resulting, more well-defined cages align as in structure I hydrate. Crystallization (decomposition to methane gas and cubic ice) occurred at 165 K. In the as-deposited sample, the motions of the guest methane molecules are more hindered, and the rotational potential barrier is also higher. While after annealing, the motions are more like spherical rotation, as in structure I hydrate.