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Aims: To validate cardiovascular risk prediction models for individuals with diabetes using the UK Biobank in order to assess their applicability. Methods: We externally validated 19 cardiovascular risk scores from seven risk prediction models (Chang et al., Framingham, University of Hong Kong‐Singapore [HKU‐SG], Li et al, RECODe [risk equations for complications of type 2 diabetes], SCORE [Systematic Coronary Risk Evaluation] and the UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2]), identified from systematic reviews, using UK Biobank data from 2006 to 2021 (n = 23 685; participant age 40–71 years, 63.5% male). We evaluated performance by assessing the discrimination and calibration of the models for the endpoints of mortality, cardiovascular mortality, congestive heart failure, myocardial infarction, stroke, and ischaemic heart disease. Results: Over a total of 269 430 person‐years of follow‐up (median 11.89 years), the models showed low‐to‐moderate discrimination performance on external validation (concordance indices [c‐indices] 0.50–0.71). Most models had low calibration with overprediction of the observed risk. RECODe outperformed other models across four comparable endpoints for discrimination: all‐cause mortality (c‐index 0.67, 95% confidence interval [CI] 0.65–0.69), congestive heart failure (c‐index 0.71, 95% CI 0.69–0.72), myocardial infarction (c‐index 0.67, 95% CI 0.65–0.68); and stroke (c‐index 0.65, 95% CI 0.62–0.68), and for calibration (except for all‐cause mortality). The UKPDS OM2 had comparable performance to RECODe for all‐cause mortality (c‐index 0.67, 95% CI 0.66–0.69) and cardiovascular mortality (c‐index 0.71, 95% CI 0.70–0.73), but worse performance for other outcomes. The models performed better for younger participants and somewhat better for non‐White ethnicities. Models developed from non‐Western datasets showed worse performance in our UK‐based validation set. Conclusions: The RECODe model led to better risk estimations in this predominantly White European population. Further validation is needed in non‐Western populations to assess generalizability to other populations. [ABSTRACT FROM AUTHOR]

Natural rubber is an important national strategic and industrial raw material. The leaf anthracnose of rubber trees caused by the Colletotrichum species is one of the important factors restricting the yields of natural rubber. In this study, we isolated and identified strain Bacillus velezensis SF334, which exhibited significant antagonistic activity against both C. australisinense and C. siamense, the dominant species of Colletotrichum causing rubber tree leaf anthracnose in the Hainan province of China, from a pool of 223 bacterial strains. The cell suspensions of SF334 had a significant prevention effect for the leaf anthracnose of rubber trees, with an efficacy of 79.67% against C. siamense and 71.8% against C. australisinense. We demonstrated that SF334 can lead to the lysis of C. australisinense and C. siamense mycelia by causing mycelial expansion, resulting in mycelial rupture and subsequent death. B. velezensis SF334 also harbors some plant probiotic traits, such as secreting siderophore, protease, cellulase, pectinase, and the auxin of indole-3-acetic acid (IAA), and it has broad-spectrum antifungal activity against some important plant pathogenic fungi. The genome combined with comparative genomic analyses indicated that SF334 possesses most genes of the central metabolic and gene clusters of secondary metabolites in B. velezensis strains. To our knowledge, this is the first time a Bacillus velezensis strain has been reported as a promising biocontrol agent against the leaf anthracnose of rubber trees caused by C. siamense and C. australisinense. The results suggest that B. velezensis could be a potential candidate agent for the leaf anthracnose of rubber trees. [ABSTRACT FROM AUTHOR]

• Operando observation system is developed to make in-situ test on lab-on-a-chip. • Actual evolution process of charged submicron particles is recorded intuitively. • This work demonstrates direct influence of drag force on particle chain fracture. • It is first-time visualization of mechanism elucidation of particle re-entrainment. Inhalable particle is a harmful air pollutant that causes a significant threat to people's health and ecological environments, which should be removed to purify air, but there exists limited removal efficiency due to particle re-entrainment. Here, Operando observation system based on microscopic visualization method is developed to make in situ test of particle migration, deposition and re-entrainment characteristics on a lab-on-a-chip to achieve the investigation in micro-level scale. The deposition evolution of charged particles is recorded in electric field region intuitively, which confirms the fracture of particle chain occurs during the growth process of deposited particles. It captures the instantaneous process that a larger particle with micron size due to the coagulation of submicron particles fractures from main body of the particle chain for the first time. The analysis of migration behavior of a single submicron particle near electrode surface demonstrates the direct influence of drag force on the fracture of particle chain. This work is the first-time visualization of dynamic process and mechanism elucidation of particle re-entrainment at the micron level, and the findings will provide the theory support for the particle re-entrainment mechanism and bring inspires of enhancing capture efficiency of inhalable particle. [Display omitted] [ABSTRACT FROM AUTHOR]

The high integration density of microelectronic devices leads to local heat accumulation, and effective heat dissipation and signal transmission of packaging materials have become the primary issues to be solved. However, existing polymer materials have difficulty meeting the requirements due to their unsatisfactory thermal conductivity and thermal expansion properties. In this work, we proposed the use of digital light processing (DLP) printing technology to construct a triply periodic minimum surface (TPMS) skeleton, and a continuous and efficient heat conduction path was successfully constructed in epoxy resin by impregnating h-BN on the skeleton surface. When the loading of h-BN was 20 vol%, the thermal conductivity of the TPMS(SiO 2)@BN/EP(BN) composites was 1.86 W/(m·K), which was 786 % higher than that of pure epoxy resin. In addition, the thermal expansion coefficient of the composites decreased by more than 70 %. At the test frequencies of 3∼10 MHz, the composites showed stable dielectric properties, and the dielectric constant was always maintained in a low range, between 3.85 and 4.15. This work has realized the transformation of the method for constructing a heat conduction path from disordered to ordered and from random to repeatable. This provides a new strategy for the selection of microelectronic packaging materials. [ABSTRACT FROM AUTHOR]

The magnetocaloric effect (MCE) has been extensively studied in various magnetic solids, aiming to both facilitate practical applications in magnetic cooling and deepen our understanding these materials' intrinsic properties. This study presents a systematic investigation of Gd 2 Ti 2 O 7 oxide, characterized by a geometrically frustrated magnetic structure, focusing on its structural and magnetic characteristics through experimental analysis and theoretical calculations. Emphasis is placed on its magnetic phase transition (MPT) and magnetocaloric properties, scrutinizing temperatures as low as 0.4 K and magnetic fields up to 16 T. The results reveal that Gd 2 Ti 2 O 7 oxide possesses a crystalline cubic pyrochlore-type structure with an antiferromagnetic (AFM) semiconductor ground state. The material undergoes a first-order MPT in low field and low-temperature regimes, transitioning to a second-order MPT above 2 K up to 16 T. Evaluation of magnetocaloric parameters, including maximum magnetic entropy change, temperature-averaged entropy change, relative cooling power, and refrigerant capacity, indicates moderate values under low magnetic field changes, while significantly large values are achievable under high magnetic field changes. This finding suggests that potential cryogenic magnetocaloric materials (MCMs) with optimal performance should exhibit low MPT temperatures induced by magnetic frustration and possess a ground state with a sufficiently large magnetic moment induced by low magnetic fields, thus avoiding excessively strong AFM coupling. This study lays the groundwork for future cryogenic MCM design and provides valuable insights into the intrinsic properties of geometrically frustrated magnetic materials. [Display omitted] [ABSTRACT FROM AUTHOR]

We herein provided a systematical determination of the structural and magnetic properties, especially of the magnetocaloric effect (MCE) and magnetocaloric performances of four rare-earth oxychlorides, i. e., the RE OCl (RE = Ho, Dy, Tb and Gd) compounds. The studied RE OCl compounds are all crystallized in the tetragonal matlockite structure (P 4/ nmm space group) and the RE , O, and Cl elements are with the RE 3+, O2−, and Cl− valence states, respectively. The DyOCl, TbOCl and GdOCl compounds reveal an antiferromagnetic transition at around approximate 9.5, 3.7 and 4.8 K, respectively. The magnetocaloric performances are checked by the maximum magnetic entropy change, relative cooling power, and temperature-averaged entropy change with 5 K lift, which are found to be 14.16 J/kgK, 375.55 J/kg and 13.89 J/kgK for HoOCl, to be 14.88 J/kgK, 488.14 J/kg, and 14.60 J/kgK for DyOCl, to be 14.59 J/kgK, 419.67 J/kg, and 14.42 J/kgK for TbOCl, and to be 16.16 J/kgK, 213.68 J/kg, and 14.39 J/kgK for GdOCl, with the magnetic field change of 0–7 T, respectively. [ABSTRACT FROM AUTHOR]

We herein investigated four rare earth (RE)-based oxides, the RE 2 SiO 5 (RE = Gd, Dy, Ho, and Er) silicates, regarding their structural and cryogenic magnetic properties. All the RE 2 SiO 5 silicates are found to crystallized in a monoclinic structure. X-ray photoemission spectroscopy spectra illustrate that RE , Si and O elements in RE 2 SiO 5 silicates are present as RE 3+, Si4+, and O2−, respectively. The Dy 2 SiO 5 reveals a first-order magnetic transition around 4.5 K. The magnetic phase transition temperatures are probably below 2 K for the RE 2 SiO 5 (RE = Gd, Ho, and Er) silicates. Large cryogenic magnetocaloric effects (MCE) and good magnetocaloric performances were observed in the RE 2 SiO 5 silicates. The MCE parameters in terms of the maximum magnetic entropy changes, the temperature-averaged entropy change (5 K-lift) and refrigerant capacity under a magnetic field change of 0–5 T are determined to be 35.5, 30.4 J/kgK, and 215.7 J/kg for Gd 2 SiO 5 , to be 13.3, 12.9 J/kgK, and 190.5 J/kg for Dy 2 SiO 5 , to be 15.3, 15.1 J/kgK, and 274.1 J/kg for Ho 2 SiO 5 and to be 17.9, 16.5 J/kgK, and 181.14 J/kg for Er 2 SiO 5 , respectively. These derived values of MCE parameters of the RE 2 SiO 5 silicates, especially for Gd 2 SiO 5 , are at similarly high level with or better than those of the updated candidate materials, making them also of potential for practical magnetic refrigeration applications. [ABSTRACT FROM AUTHOR]

We fabricated the amorphous Ho 0.2 Tm 0.2 Gd 0.2 Co 0.2 Al 0.2 ribbon by melt-spun method and systematically investigated its glass forming ability (GFA) and magnetic properties, especially of the magnetic phase transition (MPT) and magneto-caloric (MC) effect. The melt-spun Ho 0.2 Tm 0.2 Gd 0.2 Co 0.2 Al 0.2 ribbon is found to exhibit a fully amorphous structure and good GFA. The amorphous Ho 0.2 Tm 0.2 Gd 0.2 Co 0.2 Al 0.2 ribbon undergoes a second order type MPT around 32.6 K from ferromagnetic to paramagnetic state. Large reversible low temperature MC effect and good MC performances in the amorphous Ho 0.2 Tm 0.2 Gd 0.2 Co 0.2 Al 0.2 ribbon were realized which was identified by the parameters of magnetic entropy change, temperature-averaged entropy change, and refrigerant capacity. These parameters are are at similarly high level with recently reported low temperature MC materials, making the amorphous Ho 0.2 Tm 0.2 Gd 0.2 Co 0.2 Al 0.2 ribbon also attractive for magnetic cooling. [ABSTRACT FROM AUTHOR]

[Display omitted] • Operando observation system is constructed to make in situ test on lab-on-a-chip. • Image processing method is developed based on automatic object detection. • It is first-time visualization of dynamic deposition process of submicron particle. • The growth site and direction of particle chain are investigated systematically. • This work confirms the effect of drag force on ultimate height of particle chain. Submicron particle is a harmful air pollutant due to size effect, gathering characteristic and biological activity, which not only causes a serious threat to human health and public sanitary security, but also is difficult to capture with lowest removal efficiency. Here, Operando investigation system is constructed to explore deposition characteristics of submicron particles in electric-flow coupled fields through combining microfluidic technology for forming micro electric field on the lab-on-a-chip with micro-visualization technology for capturing dynamic deposition process. Besides, based on object detection and deep learning, an image processing method is developed which can realize automatic object detection and rapid extraction of required information. Results show that particle chain grows preferentially from the convex position to prove the influence of electrode surface roughness on the growth site. The global electric field has a positive effect on keeping particle chain growing up at upright direction, and the growth process of particle chain is proposed: forming growth site stage, grow fast stage and fluctuation stage. Particle velocity in the airflow direction presents a decrease trend during the process particle migrates towards to electrode surface, which proves the direct influence of boundary layer effect on the ultimate height of particle chain. [ABSTRACT FROM AUTHOR]

• a novel interpretable model based on a convolutional dictionary learning network and nonlocal group sparse prior, called DCDL-GS, for sparse view CT image reconstruction. • In this work, we apply a statistical iterative reconstruction algorithm for a fixed number of iterations with a neural network to improve the image reconstruction quality. Inspired by a group sparsity prior, we adopt a novel group thresholding operation to improve the feature representation and constraint ability and obtain a theoretical interpretation. • To improving model applicability, filtered backprojection (FBP) reconstruction, fast sliding window nonlocal self-similarity operations, and a lightweight convolutional dictionary learning network are integrated into our DCDL-GS model. Purpose Numerous techniques based on deep learning have been utilized in sparse view computed tomography (CT) imaging. Nevertheless, the majority of techniques are instinctively constructed utilizing state-of-the-art opaque convolutional neural networks (CNNs) and lack interpretability. Moreover, CNNs tend to focus on local receptive fields and neglect nonlocal self-similarity prior information. Obtaining diagnostically valuable images from sparsely sampled projections is a challenging and ill-posed task. Method To address this issue, we propose a unique and understandable model named DCDL-GS for sparse view CT imaging. This model relies on a network comprised of convolutional dictionary learning and a nonlocal group sparse prior. To enhance the quality of image reconstruction, we utilize a neural network in conjunction with a statistical iterative reconstruction framework and perform a set number of iterations. Inspired by group sparsity priors, we adopt a novel group thresholding operation to improve the feature representation and constraint ability and obtain a theoretical interpretation. Furthermore, our DCDL-GS model incorporates filtered backprojection (FBP) reconstruction, fast sliding window nonlocal self-similarity operations, and a lightweight and interpretable convolutional dictionary learning network to enhance the applicability of the model. Results The efficiency of our proposed DCDL-GS model in preserving edges and recovering features is demonstrated by the visual results obtained on the LDCT-P and UIH datasets. Compared to the results of the most advanced techniques, the quantitative results are enhanced, with increases of 0.6-0.8 dB for the peak signal-to-noise ratio (PSNR), 0.005-0.01 for the structural similarity index measure (SSIM), and 1-1.3 for the regulated Fréchet inception distance (rFID) on the test dataset. The quantitative results also show the effectiveness of our proposed deep convolution iterative reconstruction module and nonlocal group sparse prior. Conclusion In this paper, we create a consolidated and enhanced mathematical model by integrating projection data and prior knowledge of images into a deep iterative model. The model is more practical and interpretable than existing approaches. The results from the experiment show that the proposed model performs well in comparison to the others. [ABSTRACT FROM AUTHOR]

• The RE 2 Ga 2 Mg (RE = Tm, Er, Ho) compounds were fabricated. • The magnetic and magnetocaloric properties were investigated. • Large conventional and inverse magnetocaloric effects were observed. • The Tm 2 Ga 2 Mg is considerable for cryogenic magnetic cooling. The Mo 2 FeB 2 -type compounds RE 2 Ga 2 Mg (RE = Tm, Er, Ho) (space group P 4/ mbm) exhibit a large magnetocaloric (MC) effect which makes them promising for use in cryogenic magnetic cooling applications. They exhibit low temperature metamagnetic nature below their Néel temperatures of 6.8, 11.7 and 18.4 K for Tm 2 Ga 2 Mg, Er 2 Ga 2 Mg and Ho 2 Ga 2 Mg, respectively. The magnetic entropy change, the temperature-averaged entropy change (3 K-lift), and the relative cooling power under a magnetic field change of 0–7 T are 15.6, 15.4 J/kgK and 275.8 J/kg for Tm 2 Ga 2 Mg; 13.2, 13.0 J/kgK and 268.0 J/kg for Er 2 Ga 2 Mg; as well as 9.1, 9.0 J/kgK and 223.0 J/kg for Ho 2 Ga 2 Mg, respectively. [ABSTRACT FROM AUTHOR]