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Abstract Selective uptake and elution of trace amounts of hazardous radioactive 90Sr from large-scale high-level liquid waste (HLW) is crucial for sustainable development. Here, we propose a site differentiation strategy, based on the presence of distinct selective metal capture sites (concavity site and tweezer site) within the giant polyoxoniobate (PONb) nanoclusters of an all-inorganic PONb framework (FZU-1). Through this strategy, FZU-1 can not only effectively remove 98.9% of Sr²⁺ from simulated nuclear liquid waste, performing best among the reported Sr adsorbents, but also achieve desorption of adsorbed Sr²⁺ ions by selectively loading Na⁺ ions, thus enabling the recycling of FZU-1. Based on the well-defined single-crystal structures and theoretical studies, it can be revealed that the rapid and selective uptake of Sr²⁺ is attributed to the strong binding energy between the Sr²⁺ ions and the concavity sites. The effective elution of Sr²⁺, on the other hand, stems from the preferential binding of Na⁺ ions at the tweezer sites, elevating the cluster’s electrostatic potential and indirectly facilitating the elution of Sr²⁺ ions. The exceptional stability of FZU-1, along with its rapid and selective Sr²⁺ capture and elution capabilities, positions it as a promising candidate for large-scale nuclear waste treatment and groundwater remediation applications.

Although most cognitive impairments induced by prolonged alcohol consumption tend to improve within the initial months of abstinence, there is evidence suggesting certain cognitive deficits may persist. This study aimed to investigate the impact of aerobic exercise on learning and memory in alcohol use disorder (AUD) mice following a period of abstinence from alcohol. We also sought to assess the levels of monoamine neurotransmitters in the hippocampus. To this end, we established an AUD mouse model through a two‐bottle choice (sucrose fading mode and normal mode) and chronic intermittent alcohol vapor (combined with intraperitoneal injection) and randomly allocated mice into exercise groups to undergo treadmill training. Learning and memory abilities were assessed through the Morris water maze test and spontaneous activity was evaluated using the open field test. The levels of dopamine, norepinephrine, serotonin, and brain‐derived neurotrophic factor in the hippocampus were quantified using enzyme‐linked immunoassay (ELISA) kits. The findings reveal that after cessation of alcohol consumption, learning and memory abilities in AUD mice did not completely return to normal levels. The observed enhancement of cognitive functions in AUD mice through aerobic exercise may be attributed to restoring levels of monoamine neurotransmitters in the hippocampus, boosting brain‐derived neurotrophic factor (BDNF) concentrations, and facilitating an increase in hippocampal mass. These results offer empirical evidence to support aerobic exercise as a viable therapeutic strategy to alleviate cognitive deficits associated with AUD.

The National Council of Teachers of Mathematics (NCTM) emphasizes the teaching of "Big Ideas" in mathematics. This study focuses on the part-part-whole (PPW) relationship as a crucial aspect of word problem solving involving addition and subtraction. This study, conducted in the United States, evaluated the effects of conceptual model-based problem-solving (COMPS) with the concrete-representational-abstract (CRA) sequence on teaching addition and subtraction word problem solving to students with autism spectrum disorder (ASD). Using a multiple-probe design across the participants, the researchers examined the impact of the intervention on students' performance across three types of word problems: join-in, take-away, and combine. Results demonstrated significant improvements in students' problem-solving abilities on criterion tests. In addition, students successfully generalized their skills to solve problems with new contexts. The findings of this study provide implications for future research and educational practice.

ObjectiveThe goal of this study is to assess the clinical attributes exhibited by patients aged 85 years and older who present different manifestations of COVID-19, and to examine the factors influencing the classification of the disease severity.MethodThis retrospective study was conducted at a single center, encompassing an analysis of clinical data obtained from patients with COVID-19 admitted to a general geriatric hospital in Hangzhou, Zhejiang, China, during the period from December 20, 2022, to February 1, 2023. The study focused on 91 eligible patients whose disease severity was compared based on the imaging findings.ResultsA total of 91 patients aged 85 years and older, with a median age of 92, including 46 males, 10 exhibiting mild symptoms, 48 moderate cases, and 33 severe cases met the inclusion criteria. Notably, disease severity displayed a significant correlation with age (p

Abstract Objective To analyse the relationship between the polymorphisms of the H-type hypertensive methylenetetrahydrofolate reductase (MTHFR) C677T gene and neutrophil gelatinase-associated lipocalin (NGAL) in early kidney injury. Method A total of 279 hospitalised patients with hypertension were selected and grouped according to their homocysteine (Hcy) level. If their blood Hcy level was ≥ 10 µmol/L they were assigned to the H-type hypertensive group, and if it was

AbstractContext Duhuo Jisheng pill (DHJS) is a classic traditional Chinese medicine (TCM) formula for rheumatoid arthritis (RA). The effective components and therapeutic mechanisms of DHJS for treating RA are still unclear.Objective To explore the potential mechanism of DHJS against RA by means of network pharmacology and experimental verification.Materials and methods A network pharmacology and molecular docking analysis based on phytochemistry was used to elucidate the mechanism of DHJS against RA. The targets of DHJS anti-RA active ingredient were obtained by searching TCMSP, ETCM and TCMSID. The RA model induced by collagen was established in Wistar rats. The rats in the DHJS group were administered doses of 0.5, 1.0 and 2.0 g/kg for a period of 10 d. The expression of targets was measured with Western blot.Results Network pharmacology analysis showed that the anti-RA effect of DHJS was mediated by targets involved in immunity, inflammation and apoptosis, as well as PI3K-Akt and NF-κB signalling pathways. Of 2.0 g/kg DHJS significantly alleviated the ankle inflammation (IL-6: 62.73 ± 8.39 pg/mL, IL-1β: 50.49 ± 11.47 pg/mL, TNF-α: 16.88 ± 3.05 pg/mL, IL-17A: 12.55 ± 1.87 pg/mL, IL-10: 16.24 ± 3.00 pg/mL), comparing with the model group (IL-6: 92.02 ± 13.25 pg/mL, IL-1β: 71.85 ± 4.12 pg/mL, TNF-α: 25.64 ± 3.69 pg/mL, IL-17A: 22.14 ± 4.56 pg/mL, IL-10: 9.51 ± 3.03 pg/mL) (p

Insurance promotes financial resilience for individuals and households, aiding them in risk management and welfare improvement. Despite concerted efforts by countries and international bodies to promote financial inclusion through various programs, the roles of life and non-life insurance remain underemphasized as measure to close the financial gap in most countries. Our research is motivated by the realization that the existing literature lacks a unified measure of financial inclusion that considers the impact of life and non-life insurance. The objective of this study is to examine the roles of insurance and banking services in financial inclusion through an innovative measure. This study employs Principal Component Analysis to compute different sets of a multidimensional Financial Inclusion Index (FI index) that incorporate banking, life, and non-life insurance indicators for 72 countries from 2015 to 2019. When the role of life insurance is considered, some countries experience significant leaps in their financial inclusion levels, while the opposite holds true for most countries regardless of their developmental stage. In the meantime, non-life insurance has a strong positive impact on the overall financial inclusivity of the sample countries, with more than half of them recording higher financial inclusion. These results necessitate a reevaluation of financial inclusion strategies worldwide. We advocate for a more comprehensive approach that integrates insurance services into the financial system alongside traditional banking, especially non-life insurance given its significant contribution in enabling financial inclusion.

Abstract Coronary artery tortuosity (CAT) is frequently detected during coronary angiography or coronary electron‐beam computed tomography angiography by cardiovascular interventionalists. In this article, we described the case of a 69‐year‐old female patient with recurrent chest discomfort for 1 month and recurrence 1 week ago, accompanied by emaciation, gastrointestinal discomfort, and low skin temperature at the extremities. After a series of tests, the patient was finally diagnosed with severe CAT and coexisting connective tissue disease. Accordingly, she was treated with conventional medications, and diet and lifestyle modifications. The symptoms of the patient resolved gradually after 1 year of follow‐up. Although there is no unanimous conclusion on the pathogenesis and clinical characteristics of CAT, this disease may provide a clue to the diagnosis of connective tissue disease, and warrants exploration through further research.

We present our optical observations and multiwavelength analysis of the GRB 200613A detected by the Fermi satellite. Time-resolved spectral analysis of the prompt gamma-ray emission was conducted utilizing the Bayesian block method to determine statistically optimal time bins. Based on the Bayesian Information Criterion, the data generally favor the Band+blackbody (BB) model. We speculate that the main Band component comes from the Blandford–Znajek mechanism, while the additional BB component comes from the neutrino annihilation process. The BB component becomes significant for a low-spin, high-accretion-rate black hole central engine, as evidenced by our model comparison with the data. The afterglow light curve exhibits typical power-law decay, and its behavior can be explained by the collision between the ejecta and the constant interstellar medium. Model fitting yields the following parameters: ${E}_{K,{\rm{iso}}}=({2.04}_{-1.50}^{+11.8})\times {10}^{53}$ erg, ${{\rm{\Gamma }}}_{0}={354}_{-217}^{+578}$ , $p={2.09}_{-0.03}^{+0.02}$ , ${n}_{18}=({2.04}_{-1.87}^{+9.71})\times {10}^{2}$ cm ^−3 , ${\theta }_{j}={24.0}_{-5.54}^{+6.50}$ degree, ${\epsilon }_{e}={1.66}_{-1.39}^{+4.09})\times {10}^{-1}$ and ${\epsilon }_{B}=({7.76}_{-5.9}^{+48.5})\times {10}^{-6}$ . In addition, we employed the public Python package Prospector to perform a spectral energy distribution modeling of the host galaxy. The results suggest that the host galaxy is a massive galaxy ( $\mathrm{log}({M}_{* }/{M}_{\odot })={11.75}_{-0.09}^{+0.10}$ ) with a moderate star formation rate ( ${\rm{SFR}}={22.58}_{-7.22}^{+13.63}{M}_{\odot }$ yr ^−1 ). This SFR is consistent with the SFR of ∼34.2 M _⊙ yr ^−1 derived from the [O ii ] emission line in the observed spectrum.

The standard external shock model in the thin-shell scenario predicts an onset bump in the early optical afterglow light curves of gamma-ray bursts (GRBs). We collect such a textbook-version light-curve sample of 30 GRBs and derive the jet properties from our joint fit to their X-ray and optical afterglow light curves. It is found that the distributions of the isotropic initial Lorentz factors (Γ _0 ), the deceleration radii ( R _dec ), and the magnetic field strength ( B _0 ) are log-normal, but the distributions of the isotropic kinetic energy ( E _k,iso ), medium density ( n _0 ), and magnetization parameter ( σ _B ≡ ϵ _B / ϵ _e ) are tentatively bimodal. A tight R _dec – B _0 – σ _B relation is found. It infers a universal ϵ _e E _k,iso among bursts, plausibly supporting the previous argument of a universal GRB radiation energy among GRBs. A jet break is required for modeling the light curves of 26 GRBs. The distributions of the jet opening angles and the jet-corrected kinetic energies log-normally center at $\mathrm{log}{\theta }_{{\rm{j}},{\rm{c}}}/\mathrm{rad}=-1.51$ (standard deviation σ = 0.27) and $\mathrm{log}({E}_{{\rm{k}},{\rm{j}},{\rm{c}}}/\mathrm{erg})=51.78$ ( σ = 0.54), respectively. Those GRBs (19 GRBs), whose prompt gamma-ray emission is well estimated with broad energy-band observations, satisfy the previously discovered L _γ _,p,iso – E _p,z –Γ _0 relation, and their gamma-ray radiation efficiencies log-normally distribute in the range from 0.04% to 10% with a central value of 0.42%. Such a low efficiency favors the baryonic fireball model, and the distribution of their baryon mass loading in the GRB ejecta log-normally centers at $\mathrm{log}({M}_{\mathrm{fb},{\rm{c}}}/{M}_{\odot })=-5$ ( σ = 0.75).

M-type stars are the ones that flare most frequently, but how big their maximum flare energy can reach is still unknown. We present 163 flares from 162 individual M2 through L1-type stars that triggered the GWAC, with flare energies ranging from 10 ^32.2 to 10 ^36.4 erg. The flare amplitudes range from △ G = 0.84 to ∼10 mag. Flare energy increases with stellar surface temperature ( T _eff ) but both △ G and equivalent duration ${\mathrm{log}}_{10}(\mathrm{ED})$ seem to be independent of T _eff . Combining periods detected from light curves of TESS and K2, spectra from LAMOST, the Sloan Digital Sky Survey, the 2.16 m telescope, and the Gaia DR3 data, we found that these GWAC flare stars are young. For the stars that have spectra, we found that these stars are in or very near the saturation region, and ${\mathrm{log}}_{10}({L}_{{\rm{H}}\alpha }/{L}_{\mathrm{bol}})$ is lower for M7–L1 stars than for M2–M6 stars. We also studied the relation between GWAC flare bolometric energy E _bol and stellar hemispherical area S , and found that ${\mathrm{log}}_{10}{E}_{\mathrm{bol}}$ (in erg) increases with increasing S (in square centimeters), and the maximum flare energy ${\mathrm{log}}_{10}{E}_{\mathrm{bol},\ \max }\geqslant {\mathrm{log}}_{10}S+14.25$ . For M7–L1 stars, there seem to be other factors limiting their maximum flare energies in addition to the stellar hemispherical area.

We present photometric and spectroscopic observations and analysis of the Type IIb supernova (SN) SN 2019tua, which exhibits multiple bumps in its declining light curves between 40 and 65 days after discovery. SN 2019tua shows a time to peak of about 25 days, similar to other Type IIb SNe. Our observations indicate a decrease in its brightness of about 1 mag in the 60 days after the peak. At about days 50 and 60, its multiband light curves exhibit bumpy behavior. The complex luminosity evolution of SN 2019tua could not be well modeled with a single currently popular energy source model, e.g., radioactive decay of ^56 Ni, magnetar, interaction between the ejecta and a circumstellar shell. Even though the magnetar model has a smaller χ ^2 /dof value, the complex changes in SN 2019tua’s brightness suggest that more than one physical process might be involved. We propose a hybrid circumstellar medium (CSM) interaction plus ^56 Ni model to explain the bolometric light curve of SN 2019tua. The fitting results show that the ejecta mass M _ej ≈ 2.4 M _⊙ , the total CSM mass M _CSM ≈ 1.0 M _⊙ , and the ^56 Ni mass M _Ni ≈ 0.4 M _⊙ . The total kinetic energy of the ejecta is E _k ≈ 0.5 × 10 ^51 erg. Preexisting multiple shells suggest that the progenitor of SN 2019tua experienced mass ejections within approximately ∼6–44 yr prior to the explosion.

Underactuated Unmanned Surface Vessels (USVs) are widely used in civil and military fields due to their small size and high flexibility, and trajectory tracking control is a critical research area for underactuated USVs. This paper proposes a trajectory tracking control strategy using the Biologically Inspired Neural Network (BINN) for USVs to improve tracking speed and accuracy. A virtual control law is designed to obtain the required virtual velocity for trajectory tracking control, in which the velocity error is calibrated to ensure that the position error converges to zero. To observe and compensate for unknown and complex environmental disturbances such as wind, waves, and currents, a nonlinear extended state observer (NESO) is designed. Then, a controller based on Non-singular Terminal Sliding Mode (NTSM) is designed to resolve the problems of singular value and controller chattering and to improve the controller response speed. A BINN is introduced to simplify the process of differentiation, reduce the input values of the initial state, and solve the problem of thruster input saturation. Finally, the Lyapunov stability theory is utilized to analyze the stability of the proposed algorithm. The simulation results show that the proposed algorithm has a higher trajectory tracking accuracy and speed than traditional methods.

Palladium‐catalyzed bicyclization of 1‐(2,2‐dibromovinyl)‐2‐alkenylbenzene with allenyl malonates has been achieved to afford a series of bicyclic compounds. The protocol involves intermolecular carbopalladation of allenes/cyclization/internal Heck reaction. Three C−C bonds and two rings are formed in one step. [ABSTRACT FROM AUTHOR]

This study investigated the impact of visual cueing on attention guidance, deep-thinking promotion, and performance optimization in arithmetic word problem solving for students with mathematical learning difficulties (MLD). The participants included eight students with MLD and twenty students without MLD who attempted to solve mathematical word problems with and without visual cueing. Eye movements were recorded during the tasks. A repeated-measure design and nonparametric tests were applied to enhance the statistical power of the study. The data analysis results indicated that visual cueing effectively guided and sustained the attention of students with MLD, reducing their off-task duration. However, it showed limited influence in facilitating deep thinking and performance improvement for these students. There were no significant attention-guidance or performance-improvement effects observed in the problem-solving processes of students without MLD, who initially demonstrated better concentration levels and performance. The potential explanations for these findings are further discussed in this paper.

The focus of the current research is how to effectively identify aircraft targets in SAR images. There are only 2000 SAR images and 6556 aircraft instances in our dataset. SAR images have complex backgrounds, and the sizes of aircraft targets are multi-scale. How to improve the detection accuracy of aircraft targets is the research topic of this paper, especially for small target detection. We proposed four improved methods based on YOLOv5s. Firstly, this paper proposed the structure of the multi-scale receptive field and channel attention fusion. It is applied at the shallow layer of the backbone of YOLOv5s. It can adjust the weights of the multi-scale receptive field during the training process to enhance the extraction ability of feature information. Secondly, we proposed four decoupled detection heads to replace the original part in YOLOv5s. It can improve the efficiency and accuracy of SAR image interpretation for small targets. Thirdly, in the case of the limited amount of SAR images, this paper proposed multiple data-augmentation methods, which can enhance the diversity and generalization of the network. Finally, this paper proposed the K-means++ to replace the original K-means to improve the network convergence speed and detection accuracy. Experiments demonstrate that the improved YOLOv5s can enhance the accuracy of SAR image interpretation by 9.3%, and the accuracy of small targets is improved more obviously, reaching 13.1%.

The essential role of store-operated Ca2+ entry (SOCE) through Ca2+ release-activated Ca2+ (CRAC) channels in T cells is well established. In contrast, the contribution of individual Orai isoforms to SOCE and their downstream signaling functions in B cells are poorly understood. Here, we demonstrate changes in the expression of Orai isoforms in response to B cell activation. We show that both Orai3 and Orai1 mediate native CRAC channels in B cells. The combined loss of Orai1 and Orai3, but not Orai3 alone, impairs SOCE, proliferation and survival, nuclear factor of activated T cells (NFAT) activation, mitochondrial respiration, glycolysis, and the metabolic reprogramming of primary B cells in response to antigenic stimulation. Nevertheless, the combined deletion of Orai1 and Orai3 in B cells did not compromise humoral immunity to influenza A virus infection in mice, suggesting that other in vivo co-stimulatory signals can overcome the requirement of BCR-mediated CRAC channel function in B cells. Our results shed important new light on the physiological roles of Orai1 and Orai3 proteins in SOCE and the effector functions of B lymphocytes.

Aiming at the problem that it is difficult to maximize market profits when various types of distributed generation work together in the power grid, this paper proposes a distributed generation parameter optimization method based on Internet of Things and fuzzy C-means clustering. Firstly, a grid distributed generation model is established under the Internet of Things architecture, and its internal parameter relationships are determined correspondingly. Secondly, the comprehensive evaluation criteria and constraints of distributed generation are proposed for maximizing market benefits. Finally, the distributed communication model based on Internet of Things and fuzzy C-means clustering are adopted to achieve the adaptive optimization of grid distributed generation parameters. The experiment simulation is carried out with IEEE standard test system. The results show that the total load and total revenue of the proposed algorithm are increased by 8.41% and 14.66% respectively compared with the traditional optimization algorithm considering generation side benefits and the algorithm considering energy loss only. Experimental results fully demonstrate the effectiveness of proposed algorithm.

Students with learning disabilities/difficulties in mathematics often apply ineffective procedures to solve word problems due to a lack of conceptual understanding of word problem solving, which results in poor mathematics performance and falling further behind the normal achievements of their peers. Current mathematics curriculum standards emphasize conceptual understanding in problem solving as well as higher-order thinking and reasoning, including all students. The purpose of this study was to evaluate the impact of a computer-assisted model-based problem-solving intervention program (MBPS) on elementary students’ word problem-solving performance by analyzing the error patterns. Results indicate that after the MBPS intervention, participants significantly improved their problem-solving performance and made fewer errors in solving problems across a range of additive word problem situations. Specifically, the participating students made their attempt to represent the mathematical relation, decontextualized from the word problem story, in the model equation before solving the problem, rather than blindly applying an operation or relying on the “keyword” strategy as they did during the preassessment. Implications of the study are discussed in the context of the National Council of Teachers of Mathematics’ calling for teaching big ideas to help students develop a deep understanding of mathematics knowledge.

Track tension is a major factor influencing the reliability of a track. In order to reduce the risk of track peel-off, it is necessary to keep track tension constant. However, it is difficult to measure the dynamic tension during off-road operation. Based on the analysis of the relation and external forces depending on free body diagrams of the idler, idler arm, road wheel and road arm, a theoretical estimation model of track tension is built. Comparing estimation results with multibody dynamics simulation results, the rationality of track tension monitor is validated. By the aid of this monitor, a track tension control system is designed, which includes a self-tuning proportional-integral-derivative (PID) controller based on radial basis function neural network, an electro-hydraulic servo system and an idler arm. The tightness of track can be adjusted by turning the idler arm. Simulation results of the vehicle starting process indicate that the controller can reach different expected tensions quickly and accurately. Compared with a traditional PID controller, the proposed controller has a stronger anti-disturbance ability by amending control parameters online.

Madagascar, a globally renowned biodiversity hotspot characterized by high rates of endemism, is one of the few remaining refugia for many plants and animal species. However, global climate change has greatly affected the natural ecosystem and endemic species living in Madagascar, and will likely continue to influence species distribution in the future. Madagascar is home to six endemic baobab (Adansonia spp., Bombacoideae [Malvaceae]) species (Adansonia grandidieri, A. suarezensis, A. madagascariensis, A. perrieri, A. rubrostipa, A. za), which are remarkable and endangered plants. This study aimed to model the current distribution of suitable habitat for each baobab species endemic to Madagascar and determine the effect that climate change will have on suitable baobab habitat by the years 2050 and 2070. The distribution was modeled using MaxEnt based on locality information of 245 occurrence sites of six species from both online database and our own field work. A total of seven climatic variables were used for the modeling process. The present distribution of all six Madagascar's baobabs was largely influenced by temperature-related factors. Although both expansion and contraction of suitable habitat are predicted for all species, loss of original suitable habitat is predicted to be extensive. For the most widespread Madagascar baobab, A. za, more than 40% of its original habitat is predicted to be lost because of climate change. Based on these findings, we recommend that areas predicted to contract in response to climate change should be designated key protection regions for baobab conservation.

Synthetic aperture radar (SAR) is an active ground-surveillance radar system, which can observe targets regardless of time and weather. Passenger aircrafts are important targets for SAR, as it is of great importance for accurately recognizing the type of aircraft. SAR can provide dynamic monitoring of aircraft flights in civil aviation, which is helpful for the efficient management of airports. Due to the unique imaging characteristics of SAR, traditional target-detection algorithms have poor generalization ability, low detection accuracy, and a cumbersome recognition process. Target detection in high-resolution SAR images based on deep-learning methods is currently a major research hotspot. You Only Look Once v5 (YOLOv5) has the problems of missed detection and false alarms. In this study, we propose an improved version of YOLOv5. A multiscale feature adaptive fusion module is proposed to adaptively assign different weights to each scale of the feature layers, which can extract richer semantic and textural information. The SIOU loss function is proposed to replace the original CIOU loss function to speed up the convergence of the algorithm. The improved Ghost structure is proposed to optimize the YOLOv5 network to decrease the parameters of the model and the amount of computation. A coordinate attention (CA) module is incorporated into the backbone section to help extract useful information. The experimental results demonstrate that the improved YOLOv5 performs better in terms of detection without affecting calculation speed. The mean average precision (mAP) value of the improved YOLOv5 increased by 5.8% compared with the original YOLOv5.

A rare all-inorganic high-nuclearity mixed-valent {Mn11} cluster embedded polyoxoniobate, K25H43{(Te4Nb9O33)3(Nb6O19)5(TeVI-Nb5O14)[(TeIVO3)2(MnII7MnIII4 O19)]}•97H2O (1), has been synthesized by a one-pot reaction. Compound 1 contains the largest manganese cluster {Mn11} core among polyoxoniobates reported to date. {Mn11} consists of three quasi-cubane {Mn3O4} units and is simultaneously encapsulated by lacunary α-Keggin {Te4Nb9O36} and Lindqvist {Nb6O19} units. Compound 1 exhibits significant magnetic anisotropy and excellent water solubility and stability. The findings suggest a new, all-inorganic polynulear Mn-based structural paradigm for aqueous solution chemistry and magnetic materials. [ABSTRACT FROM AUTHOR]