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GRB 250702DBE was time consequently triggered by the Gamma-ray Burst Monitor (GBM) on board the Fermi satellite. It is uncertain which celestial catalog is suitable for this special ultralong event to belong to. In this paper, we comprehensively investigate the lightcurves obtained by Fermi GBM detectors. In the energy band of 8–1000 keV, no quasiperiodic oscillation (QPO) signals are found in the lightcurve of the first burst 250702D, a possible QPO signal of 0.046 Hz corresponding to a period of 21.7 s is found in the lightcurve of the second burst 250702B, and a possible QPO signal of 0.024 Hz corresponding to a period of 41.7 s is found in the lightcurve of last burst 250702E. The significance level of the possible QPO signals is comprehensively examined. In addition, we examine the spectral properties of the sources. In general, a broken power law is suitable for modeling the spectral data from 8 keV to 40 MeV. We qualitatively suggest some kinds of celestial object with the periodic characteristic that might be the progenitors of this unique event.

Background Burns is a type of injury, caused by unintentional exposure to substances of high temperature, including hot liquid, solid, and objects radiating heat energy, placing a high burden not only on patients’ families but also on national healthcare systems globally. It is difficult for policymakers and clinicians to formulate targeted management strategies for burns because data on current epidemiological patterns worldwide are lacking. Methods Data on burns were obtained from the Global Burden of Disease (GBD) 2019 Study. The incidence, disability-adjusted life years (DALYs), and deaths of burns in 204 countries and regions from 1990 to 2019 were calculated and stratified by sex, age, geographical location, and sociodemographic index (SDI). The estimated annual percentage change (EAPC) of incidence, DALYs, and deaths was calculated to evaluate the temporal trends. All analyses were performed using R software, version 4.1.1, with 2-sided P -values < .05 indicating a statistically significant difference. Results A total of 8,378,122 new cases (95% UI, 6,531,887–10,363,109cases) of burns were identified globally in 2019, which is almost evenly split between men and women, and most of the new cases were concentrated in the 10–19-year age group. Besides, burns account for 111,292 deaths (95% UI, 132,392–88,188) globally in 2019, most of which were concentrated in those aged 1–4 years. The burden of burns measured in DALYs was 7,460,448.65 (95% UI, 5,794,505.89–9,478,717.81) in 2019, of which 67% and 33% could be attributed to YLLs and YLDs, respectively. The EAPC of incidence, DALYs, and deaths were negative, the age-standardized rate (ASR) of incidence, DALYs, and deaths were considered to be decreasing in most of the regions, and the EAPCs were negatively correlated with SDI levels, universal health coverage (UHC), and gross domestic product (GDP). Conclusion Globally, the age-standardized rates of burn incidence, DALYs, and mortality, as well as the number of burn DALYs and death cases will continuously decrease, but the number of new burn cases has an increasing tendency globally. In addition, the EAPCs of burns in incidence, DALYs, and deaths indicated that the burden of burns was considered to be decreasing in most of the regions. And from the relationship of EAPCs with SDI, UHC index, and GDP, indicate that prevention burns not only depend on health spending per capita but also depend on the education level per capita and healthcare system performance, but it does not mean higher health spending corresponds to higher UHC index, which needs high efficiency of translating health spending into individuals health gains.

The study of temporal properties of variable sources can elucidate their physical processes. In this context, we present a critical study comparing three approaches to periodic or quasiperiodic behavior: Gaussian process, power spectrum, and wavelet analysis, using celerite, Lomb–Scargle periodograms, and weighted wavelet Z-transforms, respectively. We use 15 Swift X-ray Telescope light curves of short gamma-ray bursts (sGRBs) as examples. A comprehensive analysis of two sGRB X-ray light curves is performed. The results reveal the importance of artifacts, largely in the form of false quasiperiodic oscillation signals, possibly introduced by preprocessing (such as detrending) or other aspects of the analysis. The exploration described in this paper can be helpful for future studies of variability in gamma-ray bursts, active galactic nuclei, and other astronomical sources.

The production of hydrogen through water splitting using earth-abundant metal catalysts is a promising pathway for converting solar energy into chemical fuels. However, existing approaches for fine stoichiometric control, structural and catalytic modification of materials by appropriate choice of earth abundant elements are either limited or challenging. Here we explore the tuning of redox active immobilised molecular metal-chalcoxide electrocatalysts by controlling the chalcogen or metal stoichiometry and explore critical aspects of the hydrogen evolution reaction (HER). Linear sweep voltammetry (LSV) shows that stoichiometric and structural control leads to the evolution of hydrogen at low overpotential with no catalyst degradation over 1000 cycles. Density functional calculations reveal the effect of the electronic and structural features and confer plausibility to the existence of a unimolecular mechanism in the HER process based on the tested hypotheses. We anticipate these findings to be a starting point for further exploration of molecular catalytic systems. While hydrogen offers a potential carbon neutral fuel, its production from water using earth-abundant, heterogeneous materials has proven challenging to understand. Here, authors present a series of molecular electrocatalysts based on molybdenum, sulphur, and oxygen for aqueous hydrogen evolution.

The CRISPR-Cas (clustered regularly interspaced short palindromic repeats-associated proteins) technology enables rapid and precise genome editing at any desired genomic position in almost all cells and organisms. In this study, we analyzed the impact of different repair templates on the frequency of homology-directed repair (HDR) and non-homologous end joining (NHEJ). We used a stable HEK293 cell line expressing the traffic light reporter (TLR-3) system to quantify HDR and NHEJ events following transfection with Cas9, eight different guide RNAs, and a 1,000 bp donor template generated either as circular plasmid, as linearized plasmid with long 3′ or 5′ backbone overhang, or as PCR product. The sequence to be corrected was either centrally located (RS55), with a shorter 5′ homologous region (RS37), or with a shorter 3′ homologous region (RS73). Guide RNAs targeting the transcriptionally active strand (T5, T7) showed significantly higher NHEJ frequencies compared with guide RNAs targeting the transcriptionally inactive strand. HDR activity was highest when using the linearized plasmid with the short 5′ backbone overhang and the RS37 design. The results demonstrate the importance of the design of the guide RNA and template DNA on the frequency of DNA repair events and, ultimately, on the outcome of treatment approaches using HDR.

With increasing awareness of healthy living and social pressure, more and more people have begun to pay attention to their sleep state. Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or traditional machine learning, which suffer from low classification efficiency and insufficient accuracy. This study explores an improved feature extractor based on the Constrained Cross Network to enhance the accuracy of the sleep-wake binary classification problem. The feature extractor consists of Feature Derivation Module and Feature Interaction Module. Feature Derivation Module leverages dilated convolutions, gated recurrent units, and attention mechanisms to construct new features in batches. The main structure of Feature Interaction Module is composed of Constrained Cross Network. This module is based on the improved Cross Network in the Improved Deep&Cross Network (DCN-v2), aiming to model high-order feature interactions. The dataset consists of 277 individuals, with varying numbers of recorded days. The ratio of sleep to wake states is 3:7. We extracted 80% of the 7,523 subsamples (divided by day) for training and validation, while the remaining 20% was used as the test set. Compared with the CNN-based method, the proposed method improves the F1-score from 75.84% to 91.14%, and the accuracy increases from 90.03% to 95.70%. After adding a non-wear identification mask, the proposed method achieves an F1-score of 94.25%, with the accuracy further improved to 97.38%. When using the same classifier, the Constrained Cross Network contributed approximately 34% to the feature extractor’s performance, while the entire feature extractor further improved the effectiveness of feature extraction. Compared to traditional DNNs, the proposed method offers a more efficient approach to feature extraction, resulting in a notable enhancement in model performance, albeit with a moderate increase in computational complexity. Furthermore, given the explicit feature construction characteristics of the Cross Network, this method has the potential to assist in developing more pronounced manual features in future research.

The separation of trivalent actinides and lanthanides is a key step in the sustainable development of nuclear energy, and it is currently mainly realized via liquid–liquid extraction techniques. The underlying mechanism is complicated and remains ambiguous, which hinders the further development of extraction. Herein, to better understand the mechanism of the extraction, the contributing factors for the extraction are discussed (specifically, the sulfur-donating ligand, Cyanex301) by combing molecular dynamics simulations and experiments. This work is expected to contribute to improve our systematic understanding on a molecular scale of the extraction of lanthanides and actinides, and to assist in the extensive studies on the design and optimization of novel ligands with improved performance.

This protocol from Kitson et al . describes an approach to create bespoke 3D-printed chemical reactors known collectively as “reactionware”. In recent decades, 3D printing (also known as additive manufacturing) techniques have moved beyond their traditional applications in the fields of industrial manufacturing and prototyping to increasingly find roles in scientific research contexts, such as synthetic chemistry. We present a general approach for the production of bespoke chemical reactors, termed reactionware, using two different approaches to extrusion-based 3D printing. This protocol describes the printing of an inert polypropylene (PP) architecture with the concurrent printing of soft material catalyst composites, using two different 3D printer setups. The steps of the PROCEDURE describe the design and preparation of a 3D digital model of the desired reactionware device and the preparation of this model for use with fused deposition modeling (FDM) type 3D printers. The protocol then further describes the preparation of composite catalyst–silicone materials for incorporation into the 3D-printed device and the steps required to fabricate a reactionware device. This combined approach allows versatility in the design and use of reactionware based on the specific needs of the experimental user. To illustrate this, we present a detailed procedure for the production of one such reactionware device that will result in the production of a sealed reactor capable of effecting a multistep organic synthesis. Depending on the design time of the 3D model, and including time for curing and drying of materials, this procedure can be completed in ∼3 d.

Layered double hydroxides (LDHs) are an important large class of two-dimensional (2D) anionic lamellar materials that possess flexible modular structure, facile exchangeability of inter-lamellar guest anions and uniform distribution of metal cations in the layer. Owing to the modular accessible gallery and unique inter-lamellar chemical environment, polyoxometalates (POMs) intercalated with LDHs has shown a vast array of physical properties with applications in environment, energy, catalysis, etc. Here we describe how polyoxometalate clusters can be used as building components for the construction of systems with important catalytic properties. This review article mainly focuses on the discussion of new synthetic approaches developed recently that allow the incorporation of the element of design in the construction of a fundamentally new class of materials with pre-defined functionalities in catalytic applications. Introducing the element of design and taking control over the finally observed functionality we demonstrate the unique opportunity for engineering materials with modular properties for specific catalytic applications.

Efficient 2D membranes play a critical role in water purification and desalination. However, most 2D membranes, such as graphene oxide (GO) membranes, tend to swell or disintegrate in liquid, making precise ionic sieving a tough challenge. Herein, the fabrication of the polyoxometalate clusters (PW12) intercalated reduced graphene oxide (rGO) membrane (rGO‐PW12) is reported through a polyoxometalate‐assisted in situ photoreduction strategy. The intercalated PW12 result in the interlayer spacing in the sub‐nanometer scale and induce a nanoconfinement effect to repel the ions in various salt solutions. The permeation rate of rGO‐PW12 membranes are about two orders of magnitude lower than those through the GO membrane. The confinement of nanochannels also generate the excellent non‐swelling stability of rGO‐PW12 membranes in aqueous solutions up to 400 h. Moreover, when applied in forward osmosis, the rGO‐PW12 membranes with a thickness of 90 nm not only exhibit a high‐water permeance of up to 0.11790 L m−2 h−1 bar−1 and high NaCl rejection (98.3%), but also reveal an ultrahigh water/salt selectivity of 4740. Such significantly improved ion‐exclusion ability and high‐water flux benefit from the multi‐interactions and nanoconfinement effect between PW12 and rGO nanosheets, which afford a well‐interlinked lamellar structure via hydrogen bonding and van der Waals interactions. A highly efficient polyoxometalate‐assisted in situ photoreduction strategy is applied for the fabrication of the highly ordered rGO‐PW12 membranes, which shows excellent water permeance of 0.11790 L m−2h−1bar‐1, high dye rejection of 98.3% for NaCl and ultrahigh water/salt selectivity of 4740. The strong multi‐interactions between PW12 and rGO nanosheets contribute to these membranes excellent non‐swelling stability up to 400 h.