Wide Time Range Research Articles

RIGEL: Simulating dwarf galaxies at solar mass resolution with radiative transfer and feedback from individual massive stars

Context. Feedback from stars in the form of radiation, stellar winds, and supernovae is crucial to regulating the star formation activity of galaxies. Dwarf galaxies are especially susceptible to these processes, making them an ideal test bed for studying the effects of stellar feedback in detail. Recent numerical models have aimed to resolve the interstellar medium (ISM) in dwarf galaxies with a very high resolution of several solar masses. However, when it comes to modeling the radiative feedback from stars, many models opt for simplified approaches instead of explicitly solving radiative transfer (RT) because of the computational complexity involved. Aims. We introduce the Realistic ISM modeling in Galaxy Evolution and Lifecycles (RIGEL) model, a novel framework to self-consistently model the effects of stellar feedback in the multiphase ISM of dwarf galaxies with explicit RT on a star-by-star basis. Methods. The RIGEL model integrates detailed implementations of feedback from individual massive stars into the state-of-the-art radiation-hydrodynamics code, AREPO-RT. It forms individual massive stars from the resolved multiphase ISM by sampling the initial mass function and tracks their evolution individually. The lifetimes, photon production rates, mass-loss rates, and wind velocities of these stars are determined by their initial masses and metallicities based on a library that incorporates a variety of stellar models. The RT equations are solved explicitly in seven spectral bins accounting for the infrared to He II ionizing bands, using a moment-base scheme with the M1 closure relation. The thermochemistry model tracks the nonequilibrium H, He chemistry as well as the equilibrium abundance of C I, C II, O I, O II, and CO in the irradiated ISM to capture the thermodynamics of all ISM phases, from cold molecular gas to hot ionized gas. Results. We evaluated the performance of the RIGEL model using 1 M⊙ resolution simulations of isolated dwarf galaxies. We found that the star formation rate (SFR) and interstellar radiation field (ISRF) show strong positive correlations with the metallicity of the galaxy. Photoionization and photoheating can reduce the SFR by an order of magnitude by removing the available cold, dense gas fuel for star formation. The presence of ISRF also significantly changes the thermal structure of the ISM. Radiative feedback occurs immediately after the birth of massive stars and rapidly disperses the molecular clouds within 1 Myr. As a consequence, radiative feedback reduces the age spread of star clusters to less than 2 Myr, prohibits the formation of massive star clusters, and shapes the cluster initial mass function to a steep power-law form with a slope of ∼ − 2. The mass-loading factor (measured at z = 1 kpc) of the fiducial galaxy has a median of ηM ∼ 50, while turning off radiative feedback reduces this factor by an order of magnitude. Conclusions. We demonstrate that RIGEL effectively captures the nonlinear coupling of early radiative feedback and supernova feedback in the multiphase ISM of dwarf galaxies. This novel framework enables the utilization of a comprehensive stellar feedback and ISM model in cosmological simulations of dwarf galaxies and various galactic environments spanning a wide dynamic range in both space and time.

Chemical-Physical Synergistic Assembly of MXene/CNT Nanocoatings in Silicone Foams for Reliable Piezoresistive Sensing in Harsh Environments.

Owing to their high sensitivity across a wide stress range, mechanical reliability, and rapid response time, flexible polymer foam piezoresistive sensors have been extensively used in various fields. The reliable application of these sensors under harsh environments, however,is severely limited by structural devastation and poor interfacial bonding between polymers and conductive nanoparticles. To address the above issues, robust MXene/CNT nanocoatings on the foam surface, where the chemical assembly of MXene nanosheets and the physical anchoring of CNTs lead to strong interfacial bonding, are designed and described, which endows foams with structural reliability and unexpected multi-functionalities without compromising their instinct properties. The optimized foam nanocomposites thus maintain outstanding wide-temperature flexibility (-60-210 °C) and elasticity (≈3% residual strain after 1000 cycles). Moreover, the nanocomposites display good sensitivity at a relatively wide stress range of 0-70% and remarkable stability under acidic and alkaline settings. Furthermore, the foams with exceptional fire resistance (UL-94 V-0 rating) can provide stable sensing behavior (over 300 cycles) even after being exposed to flames for 5 s, making them one of the most reliable sensing materials so far. Clearly, this work widens applications of flexible piezoresistive sensors based on silicone foam nanocomposites for various harsh environments.

Synthesis and structure of compounds of the homological series TinO2n–1 obtained by reduction in a hydrogen environment

The paper considers one of the insufficiently explored methods for the synthesis of compounds of the homologous series TinO2n–1, in particular the method of hydrogen reduction. A series of samples (n = 2–8) were obtained from initial TiO2 powders of various chemical purities (99.0–99.99%) with modification with rutile in a wide range of temperatures and reduction times in a hydrogen environment. The influence of the purity of the initial samples, temperature and recovery time on the structure of the resulting compounds was established. Differences in the crystal structure of compounds of the homologous series TinO2n–1, as well as β- and λ-polymorphic modifications of Ti3O5, are shown. An approach to selecting the temperature and time of reduction of TiO2 powders to obtain a specific phase in compounds of the homologous series TinO2n–1 is substantiated.

Evaluation of Fecal Sample Pooling for Real-Time RT-PCR Testing SARS-CoV-2 in Animals

During the COVID-19 pandemic, veterinary diagnostic laboratories tested both human and animal samples and needed to ensure that they could accurately perform large numbers of diagnostic tests in a timely manner. Sample pooling, a methodology used effectively for over 80 years as a surveillance tool for screening large numbers of potentially infected individuals, was employed. Given its sensitivity, real-time polymerase chain reaction (PCR) is more suitable for employing this strategy, as compared to other less sensitive testing methods. In this study, we evaluated the capability of detecting SARS-CoV-2 in both 5-sample and 10-sample pools of feces using real-time reverse transcriptase polymerase chain reaction (rRT-PCR) as well as determined the level of sensitivity. A blinded method test (BMT) by an independent laboratory was conducted to assess the five-sample fecal pool. To complement detection capability, the stability of the genome within a PBS fecal suspension was measured under various time and temperature conditions across a 28-day period. Our results showed that the limit of detection for 5-sample and 10-sample fecal pools is 12.8 and 6.4 genome copies in a 25 µL PCR, respectively. The 5-sample and 10-sample pooling resulted in a cycle threshold (Ct) value loss of 2.35 and 3.45, as compared to Ct values of known positive individual samples, but consistent detection was still achieved in pools containing positive samples with an original Ct below 36 and 34, respectively. The simulation of clinical five-sample pooling showed that all positive samples could be detected regardless of the number (1–3) of positive samples in each pool. The BMT results demonstrated excellent sensitivity (100 copies/reaction) in five-sample pools for the detection of SARS-CoV-2 RNA even though a fecal matrix effect was observed. Finally, our results show that the SARS-CoV-2 genome remains stable over a wide range of time and temperature variations. Overall, our findings provide solid data to scale up SARS-CoV-2 testing capacity in veterinary diagnostic laboratories.

Constraints on the impact history of the Apollo 16 landing site: Implications of soil‐like breccia noble gas records

AbstractThe Apollo 16 regolith breccia sample suite provides a record of lunar regolith formation from the basin‐forming epoch (~3.9 Ga) through to a time of declining impactor flux (~2 Ga). These rocks have been characterized into three groups: the “ancient,” “young,” and “soil‐like” regolith breccias on the basis of their petrographic characteristics, and, in the case of the “ancient” and “young” regolith breccias, noble gas inventory. This study investigates the as‐yet unexamined noble gas records of the “soil‐like” regolith breccias to understand more recent regolith evolution processes that occurred at the Apollo 16 landing site. The range of gas concentrations measured for each noble gas in these samples is comparable to those previously reported for the local Apollo 16 soils. The “soil‐like” regolith breccias were found to be more gas rich than the gas poor “young” and “ancient” regolith breccias, consistent with them having formed from comparatively mature soil(s). Our results further confirm the scientific value of lunar regolith breccias and bulk regolith samples as probes of the impact history and the space environment of the lunar surface across a wide range of time.

Intergranular phase transformation in post-sinter annealed Nd–Dy–Fe–Cu–Ga–B magnet: from Ia[formula omitted]-cubic to I4/mcm-tetragonal structure

High-coercivity Nd–Fe–B permanent magnets crucially depend on the deliberate modulation of intergranular phases, an important embodiment being I4/mcm-tetragonal Nd6Fe13Ga intergranular phase in the Nd–Fe–Ga–B magnet. Particularly, for the Nd–Dy–Fe–Cu–Ga–B magnet containing multiple rare earths (RE) and alloying metals (M), understanding the evolution of RE6(Fe,M)14 intergranular phase becomes more critical in the quest for higher coercivity. Here we design the (Nd,Pr)29.0Dy3.0FebalCu0.5Ga0.5B0.9N1.15 (N=Co, Al, Zr, wt.%) as-sintered magnets, where the major RE/Cu/Ga-rich Ia3¯-cubic intergranular phase is agglomerated in triple junctions. These pristine as-sintered magnets are subjected to annealing over a wide temperature range (390∼900 °C for 3 h) and quenching over a wide time range (0.5∼12 h at 460 °C). Through systematic microstructural characterization and first-principle calculation, the intergranular phase transformation from RE/Cu/Ga-rich Ia3¯-cubic to Fe/Ga-rich I4/mcm-tetragonal structure, and accompanying elemental segregation is unveiled. During post-sinter annealing, metastable state I firstly occurs, consisting of nanostructured RE/Cu-rich Ia3¯-cubic and I4/mcm-tetragonal lamellas, with the emergence of multi-twins and coherent interface. Then it evolves into metastable state II, consisting of lath-shaped Fe/Cu/Ga-rich I4/mcm-tetragonal structure with fluctuating Fe/Cu concentrations. Simultaneously, metastable state III occurs, exhibiting P4-tetragonal platelets with lower Cu content and reduced crystallographic symmetry. Finally, heightened Fe/Ga diffusion into the lattice of tetragonal phase with synchronous Cu discharge generates the thermodynamically more stable Fe/Ga-rich RE6Fe13Ga phase. The implication of phase transformation pathways on the coercivity is discussed, offering valuable insights into the optimization of RE6(Fe,M)14 intergranular phase and allowing more space for enhanced coercivity.

Global Observations of Geomagnetically Induced Currents Caused by an Extremely Intense Density Pulse During a Coronal Mass Ejection

AbstractA variety of magnetosphere‐ionosphere current systems and waves have been linked to geomagnetic disturbance (GMD) and geomagnetically induced currents (GIC). However, since many location‐specific factors control GMD and GIC intensity, it is often unclear what mechanisms generate the largest GMD and GIC in different locations. We address this challenge through analysis of multi‐satellite measurements and globally distributed magnetometer and GIC measurements. We find embedded within the magnetic cloud of the 23–24 April 2023 coronal mass ejection (CME) storm there was a global scale density pulse lasting for 10–20 min with compression ratio of . It caused substantial dayside displacements of the bow shock and magnetopause, changes of and , respectively, which in turn caused large amplitude GMD in the magnetosphere and on the ground across a wide local time range. At the time this global GMD was observed, GIC measured in New Zealand, Finland, Canada, and the United States were observed. The GIC were comparable (within factors of 2–2.5) to the largest ever recorded during 14 year monitoring intervals in New Zealand and Finland and represented 2‐year maxima in the United States during a period with several Kp7 geomagnetic storms. Additionally, the GIC measurements in the USA and other mid‐latitude locations exhibited wave‐like fluctuations with 1–2 min period. This work suggests that large density pulses in CME should be considered an important driver of large amplitude, global GMD and among the largest GIC at mid‐latitude locations, and that sampling intervals are required to capture these GMD/GIC.

SOD1 gene screening in ALS – frequency of mutations, patients’ attitudes to genetic information and transition to tofersen treatment in a multi-center program

Objective: To report the frequency of pathogenic SOD1 gene variants in a screening program in amyotrophic lateral sclerosis (ALS), and the clinical practice of transition to an expanded access program (EAP) of tofersen treatment. Methods: From October 2021 to February 2024, at 11 ALS centers in Germany genetic testing for SOD1, FUS, TARDBP, and C9orf72 was performed. Patients were offered to opt for notification either about all genetic variants or SOD1 variants relevant for tofersen therapy. The transition to the EAP with tofersen was assessed. Results: 1935 patients were screened (94.7% sporadic ALS). 48.8% (n = 928) opted for notification of treatment-relevant information. Genetic variants were found as follows: SOD1 (likely) pathogenic variants (class 4/5) 1.8% (n = 34), variants of unknown significance (class 3) 0.8% (n = 16), FUS (class 4/5) 0.9% (n = 17), TARDBP (class 4/5) 1.3% (n = 25), C9orf72 hexanucleotide repeat expansion 7.0% (n = 135). In SOD1-ALS (encompassing class 3–5 variants, n = 50), 68.0% (n = 34) reported a negative family history. 74.0% (n = 37) of SOD1-ALS patients – which represent 1.9% of all participants of the screening program – were transitioned to tofersen. Median duration from start of genetic testing to treatment was 94 days (57 to 295 days). Eight patients declined treatment whereas five individuals died before initiation of therapy. Conclusion: The finding of SOD1 variants in patients with a negative family history underscores the need for a broad genetic screening in ALS. In SOD1-ALS, the treatment option with tofersen was mostly utilized. The wide range in the transition time to tofersen calls for a SOD1-ALS management program.

Intranasal administration of octavalent next-generation influenza vaccine elicits protective immune responses against seasonal and pre-pandemic viruses.

Influenza is a respiratory virus which infects around a billion people globally every year, with millions experiencing severe illness. Commercial vaccine efficacy varies year to year and can be low due to mismatch of circulating virus strains. Thus, the formulation of current vaccines has to be adapted accordingly every year. The development of a broadly reactive influenza vaccine would lessen the global economic and public health burden caused by the different types of influenza viruses. The significance of our research is producing a promising universal vaccine candidate which provides protection against a wider range of virus strains over a wider range of time.

Rational construction of positively charged polyamide nanofiltration membranes for precision cation separations

Nanofiltration has gained extensive attention in various energetically efficient separations towards a sustainable water–energy nexus. However, state-of-the-art polyamide nanofiltration membranes are constrained by the inherent trade-off between water permeance and solute selectivity, and a remarkable improvement in membrane permselectivity remains a big challenge. Here we conceived a density functional theory (DFT) assisted surface modification approach using triaminoguanidine hydrochloride (TGH) as the functional modifier to fabricate polyamide membranes with extremely high surface electropositivity and well-defined nanopores to overcome this challenge. Experimental data and DFT simulation results show that TGH surface modification can significantly manipulate surface charges and polarity to facilitate water permeation and enhance Donnan exclusion selectivity. Compared with the pristine benchmark membrane, the TGH-modified membrane exhibited a 4-fold increase in water permeance and a 6-fold increase in salt rejection, which successfully breaks the trade-off, excellent monovalent/divalent cation selectivity, and superior operational stability over a wide range of testing pressure, feed pH, and operation time, outperforming state-of-the-art membranes with similar chemistry. Taken together, this study demonstrates a feasible and reliable method combining DFT and experiments to rationally tailor the membrane characteristics at the molecular level, enabling the successful fabrication of effective polyamide nanofiltration membranes with precisely regulated structural and surface properties for water purification and precision ion separations.

Prompt-critical power excursion measurements with optical fibers in the CABRI experimental reactor

This paper presents our experimental work to assess the capability of estimating the transient-induced power distribution evolution in the CABRI experimental reactor, using Cherenkov radiation in optical fibers. The CABRI reactor is designed to produce power transients from 100 kW up to 21 GW in less than 100 ms, in order to irradiate a test fuel pin under conditions representative of a Reactivity Insertion Accident in pressurized water reactors. Because of the wide response range and short response time required to follow the reactor power evolution during a complete transient, the usual means of detection, such as ionization or fission chamber, are rendered inoperable, especially for in-core or core vicinity measurements. For this reason, we suggest measuring the Cherenkov light produced within the optical fibers. The Cherenkov light emission is linked to local electron production, which is proportional to local gamma flux through the Compton or pair production cross-section. In other words, the intensity of Cherenkov radiation is related to the photon flux intensity. Knowledge of the fission photons emitted by the reactor gives direct insight into the fission rate, hence a spatial power density distribution could be reconstructed by using the measurement of Cherenkov light at different points in the reactor. The radio-luminescence measurements taken using photodiodes show very good linearity with the reactor power monitoring system despite the transient radiation induced attenuation observed in the optical fibers. The radio-luminescent light shows steady values with around 5% of variations over the 15 transients for low OH fibers and high OH fibers. Low OH tends to overestimate the FWHM of the power peak by 1–4%.

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

Highly Defective Zirconium-Based Metal-Organic Frameworks for the Efficient Adsorption and Detection of Sugar Phosphates in the Biological Sample.

Enrichment and quantification of sugar phosphates (SPx) in biological samples were of great significance in biological medicine. In this work, a series of zirconium-based metal-organic frameworks (MOFs) with different degrees of defects, namely, HP-UiO-66-NH2-X, were synthesized using acetic acid as a modulator and were utilized as high-capacity adsorbents for the adsorption of SPx in biological samples. The results indicated that the addition of acetic acid altered the morphology of HP-UiO-66-NH2-X, with corresponding changes in pore size (3.99-9.28 nm) and specific surface area (894.44-1142.50 m2·g-1). HP-UiO-66-NH2-10 showed the outstanding performance by achieving complete adsorption of all four SPx using only 80 μg of the adsorbent. The excellent adsorption efficiency of HP-UiO-66-NH2-10 was also obtained with a wide pH range and short adsorption time (10 min). Adsorption experiments demonstrated that the adsorption process involved chemical adsorption and multilayer adsorption. By utilizing X-ray photoelectron spectroscopy and density functional theory to explain the adsorption mechanism, it was found that various interactions (including coordination, hydrogen bonding, and electrostatic interactions) collectively contributed to the exceptional adsorption capability of HP-UiO-66-NH2-10. Those results indicated that the defect strategy not only increased the specific surface area and pore size, providing additional adsorption sites, but also reduced the adsorption energy between HP-UiO-66-NH2-10 and SPx. Moreover, HP-UiO-66-NH2-10 showed a low limit of detection (0.001-0.01 ng·mL-1), high precision (<13.77%), and accuracy (80.10-111.83%) in serum, liver, and cells, good stability, high selectivity (SPx/glucose, 1:100 molar ratio), and high adsorption capacity (292 mg·g-1 for SPx). The practical detection of SPx from human serum was also verified, prefiguring the great potentials of defective zirconium-based MOFs for the enrichment and detection of SPx in the biological medicine.

A Vision for the Future of Neutron Scattering and Muon Spectroscopy in the 2050s.

Neutron scattering and muon spectroscopy are techniques that use subatomic particles to understand materials across a wide range of energy (μeV to tens of eV), length (Å to cm) and time (attosecond to hour) scales. The methods are widely used to study condensed phase materials in areas that span physics, chemistry, biology, engineering and cultural heritage. In this Perspective we consider three questions: (i) will neutron scattering and muon spectroscopy still be needed in the 2050s? (ii) What might the technology to produce neutron and muon beams look like in the 2050s? (iii) What will be the applications in the 2050s? Overall, the neutron/muon ecosystem in the 2050s will have less capacity than now, but greater capability because of the somewhat higher power sources, better instrumentation and data analysis.

Enhancing the description of multi-time-scale geophysical phenomena: Incorporating finite time Scale separation and feedback, illustrated with the case of a 1D variable of interest.

Stochastic approaches play a vital role in weather, climate, and, more in general, geophysics systems, addressing processes and scales beyond the resolution of deterministic models. Similar to equilibrium/non-equilibrium thermodynamics, intricate fast and local dynamics may not always be the primary focus. Practical applications often prioritize observables capturing phenomena at dominant temporal and spatial scales. Developing models for these "large-scale" observables, resulting from averaging fast and local contributions, can be simplified into Low Order Models (LOMs) with reduced degrees of freedom described by ordinary differential equations. Unresolved degrees of freedom are introduced as stochastic components, exhibiting either Markovian or non-Markovian characteristics. The challenge lies in deriving dependable stochastic differential equations representing the statistics of real large-scale, slow features in the climate/ocean system. While paralleling material physics, it is crucial to recognize that direct transfer of tools and outcomes is hindered by the non-Hamiltonian nature of climate/geophysical LOMs and the impracticality of a Markovian treatment of noise due to wide-ranging time scales. A critical examination of the conventional statistical mechanics approach, customized for such LOMs, becomes essential. To this end, we propose utilizing an approach based on the operator cumulant method, which has been recently revisited and generalized, along with the linear response method in a non-Hamiltonian setting. Formal results are then derived, and applications to some typical classes of examples are presented to clarify this approach.

Discovering dynamic laws from observations: The case of self-propelled, interacting colloids.

Active matter spans a wide range of time and length scales, from groups of cells and synthetic self-propelled colloids to schools of fish and flocks of birds. The theoretical framework describing these systems has shown tremendous success in finding universal phenomenology. However, further progress is often burdened by the difficulty of determining forces controlling the dynamics of individual elements within each system. Accessing this local information is pivotal for the understanding of the physics governing an ensemble of active particles and for the creation of numerical models capable of explaining the observed collective phenomena. In this work, we present ActiveNet, a machine-learning tool consisting of a graph neural network that uses the collective motion of particles to learn active and two-body forces controlling their individual dynamics. We verify our approach using numerical simulations of active Brownian particles, active particles undergoing underdamped Langevin dynamics, and chiral active Brownian particles considering different interaction potentials and values of activity. Interestingly, ActiveNet can equally learn conservative or nonconservative forces as well as torques. Moreover, ActiveNet has proven to be a useful tool to learn the stochastic contribution to the forces, enabling the estimation of the diffusion coefficients. Therefore, all coefficients of the equationof motion of Active Brownian Particles are captured. Finally, we apply ActiveNet to experiments of electrophoretic Janus particles, extracting the active and two-body forces controlling colloids' dynamics. On the one side, we have learned that the active force depends on the electric field and area fraction. On the other side, we have also discovered a dependence of the two-body interaction with the electric field that leads us to propose that the dominant force between active colloids is a screened electrostatic interaction with a constant length scale. We believe that the proposed methodological tool, ActiveNet, might open a new avenue for the study and modeling of experimental suspensions of active particles.

Tracing the evolutionary pathways of dust and cold gas in high-z quiescent galaxies with SIMBA

Recent discoveries of copious amounts of dust in quiescent galaxies (QGs) at high redshifts ($z 1-2$) challenge the conventional view that these objects have a negligible interstellar medium (ISM) in proportion to their stellar mass. We made use of the SIMBA hydrodynamic cosmological simulation to explore how dust and cold gas evolve in QGs and are linked to the quenching processes affecting them. We applied a novel method for tracking the changes in the ISM dust abundance across the evolutionary history of QGs identified at $0 &lt; z in both cluster and field environments. The QGs transition from a diversity of quenching pathways, both rapidly and slowly, and they exhibit a wide range of times that elapsed between the quenching event and cold gas removal (from $ Myr to $ Gyr). Contrary to some claims, we find that quenching modes attributed to the feedback from active galactic nuclei (AGNs) do not affect dust and cold gas within the same timescales. Remarkably, QGs may replenish their dust content in the quenched phase primarily due to internal processes and marginally by external factors such as minor mergers. Prolonged grain growth on gas-phase metals appears to be the key mechanism for dust re-formation, which is effective within $ Myr after the quenching event and rapidly increases the dust-to-gas mass ratio in QGs above the standard values ($ DGR Consequently, despite heavily depleted cold gas reservoirs, roughly half of QGs maintain little evolution of their ISM dust with stellar age within the first 2 Gyr following the quenching. Overall, we predict that relatively dusty QGs dust /M_ star $) arise from both fast and slow quenchers, and they are prevalent in quenched systems of intermediate and low stellar masses ($9&lt; star /M_ odot )&lt;10.5$). This strong prediction poses an immediate quest for observational synergy between, for example, the James Webb Space Telescope (JWST) and the Atacama Large Millimetre Array (ALMA).

Broadband Quasielastic Scattering Spectroscopy Using a Multiline Frequency Comblike Spectrum in the Hard X-Ray Region.

We developed a novel quasielastic scattering spectroscopy system that uses a multiline frequency comblike resolution function to overcome the limit on the accessible timescale imposed by the inherent single-energy resolution of conventional spectroscopy systems. The new multiline system possesses multiple resolutions and can efficiently cover a wide time range, from 100ps to 100ns, where x-ray-based dynamic measurement techniques are being actively developed. It enables visualization of the relaxation shape and wave-number-dependent dynamic behavior using a two-dimensional detector, as demonstrated for the natural polymer polybutadine without deuteration.

Ion migration mechanisms in the early stages of drying and degradation of oil paint films

The study of film-formation processes of oil paints has been extensively addressed over the last decade and the influence of metal ions in the drying and degradation stages of oil paints has been demonstrated. This research aimed to determine a suitable methodology for monitoring the early drying stages of selected commercial oil paint films and to gain an insight into the migration mechanisms of material degradation taking place between adjacent paint films, with special attention to the influence of the lead white. For this purpose, a hybrid approach was adopted to characterize the composition of the paint and highlight failure mechanisms in the paint films through a wide range of time. The methods included scribe tests, percentage weight variation (ΔW%), attenuated reflectance Fourier transform infrared spectrophotometry (ATR-FTIR), gas chromatography-mass spectrometry (GC-MS), and thermal analysis with differential scanning calorimetry (TG-DSC). The results show how metal ions interact with the oil binder and the pigment in the adjacent paint film: the transverse migration of lead white is shown to affect the reactivity of polyunsaturated triglycerides, increasing the rate of oxygen uptake and promoting the formation of radicals and bonds between polymer chains, depending on the pigment with which it interacts.

Long-time exposure to sunlight is associated with the risk of sudden cardiac arrest and coronary heart disease

Abstract Background With ongoing climate change, the duration of sunshine hours will likely increase over the coming decades that escalating air temperature. Little is known about the potential cardiovascular risk from this climate factor. Purpose The aim of this study was to test whether duration of sunlight exposure is associated with incident sudden cardiac arrest (SCA), coronary heart disease (CHD), and hospitalization for heart failure (HF) and whether this association depends on seasonal variation. Methods A total of 308,851 participants from UK Biobank were included and were followed for a median time of 11.8 years. Participants reported how many hours they respectively spent the daylight outdoors on summer and winter typical days. Extreme outliers (&amp;gt;12 hours/day in summer and &amp;gt;8 hours/day in winter) were excluded. Average exposure time was calculated to unify the daylight outdoors time standard. Duration of sunlight exposure (average, summer, and winter) were categorized using quantiles and a restricted cubic spline for outcomes. Multivariate cox proportional hazard regression adjusted by age, sex, demographics, lifestyle, clinical and environmental factors was used for the analysis. Results During a follow-up, 1,572 (0.51%), 11,557 (3.74%) and 2,145 (0.68%) participants were diagnosed with SCA, CHD and hospitalization for HF. Compared with the participants exposed to short-time sunlight (average ≤ 1.5 hours/day), those who exposed to long-term sunlight (average ≥ 3.5 hours/day) had increased risk of SCA (HR 1.22, 95% CI 1.06 to 1.40) and CHD (HR 1.22, 95% CI 1.06 ~1.40). The associations between long-time exposure to sunlight and SCA were largely attributable to summer (HR 1.22, 95% CI 1.06 to 1.39) and not winter (HR 1.02, 95% CI 0.86 to 1.20), respectively. An hour increase of sunlight exposure was associated with increased risk of SCA in summer (HR, 1.03; 95% CI, 1.01 to 1.05), but not in winter (HR, 1.03, 95% CI, 0.99 to 1.06). Subgroup analysis identified that exposure to long-term sunlight was consistently increased risk of SCA, regardless of age, sex, body mass index, previous cardiovascular diseases, total physical activity, types of physical activity in last 4 weeks, use of sun/UV protection, sedentary time, natural environment percentage (buffer 1000m), and PM2.5. Finally, long-time exposure to sunlight was also associated with increased risk of CHD, but not associated with increased risk of HF hospitalization. Conclusions Findings from the present study indicate that daily long-time exposure to sunlight that increase in air temperature is a risk factor for SCA and CHD. These associations revealed graded relationship according to the duration of exposure to sunlight and more pronounced in summer. Our results suggest that public health efforts to reduce cardiovascular risk should take a wide range of exposure time to sunlight into account.