Dispersed Distribution Research Articles

Interfacial adhesion features of high-viscosity asphalt and aggregate under water conditioning: Micro perspective and molecular simulation

Interface properties between asphalt and aggregate intimately affect the service performance and long-term durability of asphalt pavement. This study seeks to explore the interfacial adhesion features of high-viscosity asphalt (HVA)-aggregate under water conditioning to provide the understanding for the moisture damage of HVA-aggregate interface and asphalt pavement. To this end, the HVA was initially suffered from different durations of water conditioning, and atomic force microscopy (AFM) test was employed to gather the microscopic phase structure and adhesion force of water-conditioned HVA and aggregate, to analyze the adhesion variations of HVA-aggregate interface. Further, molecular dynamics method was used to simulate the changing process and influencing mechanism of adhesion effect at the HVA-aggregate interface under water immersion. The findings indicated that with the increasing water immersion, Catana phase of HVAs vanished, and concave and convex structures appeared on the surface, along with pit groove dispersion phase structures. Longer immersion time resulted in augmented surface roughness of HVA and a more dispersed height distribution in the area domain, most notably during the initial stages of water immersion. Aging increased sensitivity to immersion duration in terms of surface roughness, mechanical properties and adhesion ability of HVAs. Water immersion had a diminishing effect on the mechanical properties of HVA at different aging degrees, although it increased the micro-mechanical modulus of HVAs and impaired the interface adhesion with aggregates. Under water immersion, the phase structure and mechanical properties of HVAs and the interface adhesion indexes all distinguished a prominent negative Pearson correlation (correlation coefficient |R| > 0.7000), and these factors were critical for HVA-aggregate interface adhesion, as alterations in surface phase structure and micro-mechanical traits of HVAs triggered variations in the HVA-aggregate interface adhesion. In addition, water content in the interface layer, simulation temperature and mineral anisotropy significantly affected the interfacial adhesion of HVA and aggregate in water environment. The introduction of water and the rise of temperature considerably weakened the interfacial adhesion effect of asphalt-aggregate system, and the interface adhesion failure occurred once the water layer thickness surpassed 5 Å. Comparatively, the HVA-calcite system demonstrated better interfacial adhesion competence than the HVA-α-quartz system, and the HVA-calcite {1 0 4} system showed the optimal interfacial adhesion.

A Numerical Study of Smoke Concentration Distribution near Low-Intensity Fires: Sensitivity to Vertical Canopy Structure and Fire Heat Source Strength

Abstract Broadly speaking, prediction of the negative impacts of prescribed fire on air quality is limited by gaps in our understanding of the underlying fire, fuels, and atmospheric processes. These knowledge gaps hinder our ability to accurately predict smoke concentration distributions, leading to unintended smoke intrusions into nearby communities and subsequent threats to public health and safety. In this study, numerical simulations are performed using the Flexible Particle Weather Research and Forecasting (FLEXPART-WRF) Model, a Lagrangian particle dispersion model, with particle motion driven by output from a full-physics atmospheric model with a forest canopy submodel and 10-m horizontal grid spacing [Advanced Regional Prediction System (ARPS)-CANOPY], to address two research questions. First, what is the relationship between near-fire (within ∼50–150 m of fire) smoke concentration distribution and (i) vertical canopy structure and (ii) fire heat source strength? Second, what roles do mean transport (i.e., transport by the mean wind) and turbulent diffusion play in shaping the near-fire smoke concentration distribution? To address these questions, simulations are run with 25 combinations of plant area density profile and fire sensible heat flux magnitude, and smoke is represented by particles with diameters ≤ 2.5 μm (PM2.5). Results show that near-fire PM2.5 concentration distribution is primarily controlled by vertical canopy structure, with fire heat source strength primarily controlling the PM2.5 concentration magnitude. Analysis of the underlying ARPS-CANOPY variables driving the FLEXPART-WRF particle dispersion helps elucidate the roles of mean transport and turbulent diffusion. In total, the study findings suggest that the vertical distribution of canopy vegetation and fire heat source strength are important factors influencing PM2.5 dispersion and concentration distribution near low-intensity fires.

A novel TaMoNbCrTi refractory high-entropy alloy produced by powder metallurgy

The process of mechanical alloying (MA) and spark plasma sintering (SPS) were employed to manufacture a novel TaMoNbCrTi refractory high-entropy alloy. The investigation concentrated on how variations in sintering temperatures resulted in microstructural differences, which in turn altered the mechanical properties of TaMoNbCrTi. A BCC-structured solid solution phase was formed as a result of the MA process. During further sintering, the Cr2(Ta, Nb) phase and Ti(O, N) phase precipitated from the BCC phase. The Cr2(Ta, Nb) phase volume fraction declined and transitioned from a reticular distribution to a dispersed distribution as the sintering temperature rose. Additionally, a considerable enhancement in the Ti(O, N) phase size was observed. Because of the uniform distribution of the fine precipitated phases, the TaMoNbCrTi alloy sintered at 1200 °C demonstrated superior mechanical properties.

Bio-inspired metal extraction: Tailoring peptides for highly selective scandium recovery

Scandium, a pivotal metal with widespread applications, faces challenges in recovery due to its highly dispersed distribution. Biological molecules such as proteins and peptides have shown great potential in the field of metal recovery due to their unparalleled affinity and remarkable selectivity. This research aims to design a scandium-binding peptide by mutating the amino acids and optimizing the structure of the EF-hand peptide derived from lanmodulin, a naturally lanthanides-binding protein. Utilizing computer-aided techniques, three peptides-P1 and its two variants (P2 and P3), were screened and synthesized to characterize their interaction with scandium and other competing metals through circular dichroism (CD), atomic force microscopy (AFM), fourier transform infrared spectroscopy (FTIR) as well as column adsorption experiments. Results showed that the peptide P2 and P3 exhibited higher affinity to scandium than P1, as a result of the more binding sites and the existence of hydrogen bonds in the peptides. Moreover, scandium could induce the significant change in backbone structure of these peptides, and coordinated with carboxyl groups of aspartic acid and glutamic acid. The column adsorption experiments with immobilized peptide P3 on microbeads revealed that a final scandium purity of 96.71 % was achieved and a enrichment coefficient of > 103 was obtained. This study offers a transformative strategy for selective scandium extraction from complex industrial matrices and lays the foundation for future innovations in green extraction technologies.

Risk management under weighted limited expected loss

We present and solve an optimal asset allocation problem under a weighted limited expected loss (WLEL) constraint. This formulation encompasses the risk management problem with a limited expected loss (LEL) constraint as a specialized instance and offers a pertinent internal risk management instrument for firms. We observe that a WLEL constraint makes the optimizing investor pursue less volatile payoffs than the unconstrained Merton solution. Compared to the LEL-constrained problem with the same weighted default threshold, the WLEL optimal terminal wealth displays a less dispersed distribution with a smaller variance, suggesting a more secure risk management framework. Conducting a comprehensive equilibrium analysis in the presence of a WLEL risk manager, we validate the relatively conservative investment approach undertaken by the WLEL manager. Subsequently, we expand our findings to encompass broader incomplete market settings, wherein the uniqueness of the equivalent local martingale measure is not assured.

Anisotropic optoelectronic properties of lead-free Cs3Bi2I9 single-crystal photodetectors

Lead-free halide perovskites have attracted widespread research interest due to their excellent optoelectronic properties and environmental friendliness. As one of the bismuth iodide compounds, Cs3Bi2I9 perovskite has been extensively explored in the field of photovoltaic devices and radiation detectors due to their non-toxic lead-free components and excellent stability. In this work, we successfully grow large-sized Cs3Bi2I9 single crystals (SC) with (l00) and (00l) crystal exposure facets by inverse temperature crystallization method. Under 525 nm light illumination with the intensity 15 mW cm−2 and 7 V bias, the (l00) Cs3Bi2I9 SC shows 2 times higher photocurrent, 3.6 times higher responsivity, and 2.8 times higher detectivity than the (00l) Cs3Bi2I9 SC, respectively. Superior response time in the scale of millisecond is obtained in both (l00) and (00l) Cs3Bi2I9 SCs. Based on the first-principle calculation, the (l00) SC possesses a higher charge distribution density and a wider dispersion distribution than (00l) SC, suggesting that more electrons in the (l00) SC can be excited in a wider range. The tighter arrangement of Cs+ and [BiI6]− octahedra in the (l00) SC than (00l) SC leads to the anisotropic photoelectric performance in (l00) and (00l) Cs3Bi2I9 SCs. Our results provide a strategy for the oriental growth of Cs3Bi2I9 SCs and the design of anisotropic optoelectronic devices with excellent performance.

Multi-Scale Habitat Selection by the Wintering Whooper Swan (Cygnus cygnus) in Manas National Wetland Park, Northwestern China

Habitat selection has been a central focus of animal ecology, with research primarily concentrating on habitat choice, utilization, and evaluation. However, studies confined to a single scale often fail to reveal the habitat selection needs of animals fully and accurately. This paper investigates the wintering whooper swan (Cygnus cygnus) in Manas National Wetland Park, Xinjiang, using satellite tracking to determine their locations. The Maximum Entropy model (MaxEnt) was applied to explore the multi-scales habitat selection needs of Manas National Wetland Park’s wintering whooper swans across nighttime, daytime, and landscape scales. This study showed that the habitat selection of the wintering whooper swans varied in different scales. At the landscape scale, wintering whooper swans prefer habitats with average winter precipitations of 6.9 mm and average temperatures of −6 °C, including water bodies and wetlands, indicating that climate (precipitation and temperature) and land type (wetlands and water bodies) influence their winter habitat selection. During daytime, whooper swans prefer areas close to wetlands, water bodies, and bare land, with a more dispersed distribution of water bodies. For nighttime, they tend to choose areas within the wetland park where human disturbance is minimal and safety is higher. This study can provide scientific basis and data support for habitat conservation and management of wintering waterbirds like whooper swans, recommending targeted conservation measures to effectively manage and protect the wintering grounds of whooper swans.

Effects of different extraction methods on the structure and function of blackberry seed polysaccharides

SummaryThe different extraction methods including hot‐water extraction, ultrasound‐assisted extraction, and microwave‐assisted extraction, enzyme‐assisted extraction, ultrasound and microwave‐assisted extraction, and ultrasound and enzyme‐assisted extraction (UEE) methods were carried out to extract blackberry seed polysaccharides (BSPs). The extraction yield, structure, antioxidant capacity, and glucometabolic enzyme inhibition activities of BSPs were determined in this work. Extraction methods have no influence on the monosaccharide composition of BSPs but affected the molar ratio of monosaccharides. Fourier transform infrared spectroscopy and X‐ray diffraction results showed that the extraction method cannot effect on the functional groups and crystal forms of BSPs. The findings also revealed that UEE led to the highest BSP extraction yield (4.56%), highest antioxidant capacities, and highest α‐amylase (48.49%) and α‐glucosidase (67.33%) inhibitory rates, which may because of the dispersed molecular weight distribution and loose microstructure of BSPs. These results suggest that UEE may be used in the industry to obtain BSPs with high functional activities.

Minimizing Structural Heterogeneity in DNA Self-Assembled Dye Templating via DNA Origami-Tuned Conformations.

With recent advances in DNA-templated dye aggregation for leveraging and engineering molecular excitons, a need exists for minimizing structural heterogeneity. Holliday Junction complexes (HJ) are commonly used to covalently template dye aggregates on their core; however, the global conformation of HJ is detrimentally dynamic. Here, the global conformation of the HJ is selectively tuned by restricting its position and orientation by using a sheet-like DNA origami construct (DOC) physisorbed on glass. The HJ arms are fixed with four different designed interduplex angles (IDAs). Atomic force microscopy confirmed that the HJs are bound to the surface of DOC with tuned IDAs. Dye orientation distributions were determined by combining dipole imaging and super-resolution microscopy. All IDAs led to dye orientations having dispersed distributions along planes perpendicular to the HJ plane, suggesting that stacking occurred between the dye and the neighboring DNA bases. The dye-base stacking interpretation was supported by increasing the size of the core cavity. The narrowest IDA minimizes structural heterogeneity and suggests dye intercalation. A strong correlation is found between the IDA and the orientation of the dye along the HJ plane. These results show that the HJ imposes restrictions on the dye and that the dye-DNA interactions are always present regardless of global conformation. The implications of our results are discussed for the scalability of dye aggregates using DNA self-assembly. Our methodology provides an avenue for the solid-supported single-molecule characterization of molecular assemblies templated on biomolecules─such as DNA and protein templates involved in light-harvesting and catalysis─with tuned conformations and restricted in position and orientation.

Mechanical, Flame-Retardant and Dielectric Properties of Intumescent Flame Retardant/Glass Fiber-Reinforced Polypropylene through a Novel Dispersed Distribution Mode.

The application of continuous glass fiber-reinforced polypropylene thermoplastic composites (GF/PP) is limited due to the inadequate flame retardancy of the polypropylene (PP) matrix. Apart from altering the composition of the flame retardants, the distribution modes of flame retardants also impact material performance. In this study, an alternative approach involving non-uniform distribution is proposed, namely, dispersed distribution, in which non-flame-retardant-content layers (NFRLs) and/or low-flame-retardant-content layers (LFRLs) are dispersed among high-flame-retardant-content layers (HFRLs). The mechanical, flame retardant and dielectric properties of GF/PP with intumescent flame retardant (IFR/GF/PP) are investigated comparatively under uniform, gradient, and dispersed distributions of the flame retardants. The results demonstrate that non-uniform distribution exhibits superior flame retardant performance compared to uniform distribution. Dispersed distribution enables IFR/GF/PP to attain enhanced mechanical properties and reduced dielectric constants while maintaining excellent flame-retardant properties.

Rapid Investigation of Oil Pollution in Water-Combined Induced Fluorescence and Random Sample Consensus Algorithm

The global issue of oil spreading in water poses a significant environmental challenge, emphasizing the critical need for the accurate determination and monitoring of oil content in aquatic environments to ensure sustainable development of the environment. However, the complexity arises from challenges such as oil dispersion, clustering, and non-uniform distribution, making it difficult to obtain real-time oil concentration data. This paper introduces a sophisticated system for acquiring induced fluorescence spectra specifically designed for the quantitative analysis of oil pollutants. The paper involved measuring the fluorescence spectra across 20 concentration gradients (ranging from 0 to 1000 mg/L) for four distinct oil samples: 92# Gasoline, Mobil Motor Oil 20w-40, Shell 10w-40 engine oil, and Soybean Oil. The research focused on establishing a relationship model between relative fluorescence intensity and concentration, determined at the optimal excitation wavelength, utilizing the segmented Random Sample Consensus (RANSAC) algorithm. Evaluation metrics, including standard addition recovery, average recovery, relative error, and average relative error, were employed to assess the accuracy of the proposed model. The experimental findings suggest that the average recovery rates for the four samples ranged between 99.61% and 101.15%, with the average relative errors falling within the range of 2.04% to 3.14%. These results underscore the accuracy and efficacy of the detection methodology presented in this paper. Importantly, this accuracy extends to scenarios involving heavier oil pollution. This paper exhibits exceptional sensitivity, enabling precise detection of diverse oil spills within the concentration range of 0~1000 mg/L in water bodies, offering valuable insights for water quality monitoring and sustainable development of the environment.

LES investigations of turbulent heat transfer structures with exponential power escalation

The BORAX-type accident is a key scenario in the safety design of pool-type experimental nuclear reactors. It considers a reactivity insertion large enough to initiate an exponential power escalation with a period as small as tens of milliseconds, necessitating effective heat removal by the coolant system. This study presents a computational analysis of single-phase transient heat transfer under thermal-hydraulic conditions relevant to such reactors, focusing on turbulent channel flow between planar fuel plates with highly subcooled water. Our investigation uses Large Eddy Simulation (LES) performed with TrioCFD, the open-source CFD code developed by the French Atomic Energy Commission (CEA). Several modeling options are tested: incompressible flow with temperature as a passive scalar, incompressible flow with varying viscosity, and quasicompressible flow with temperature-dependent viscosity and mass density. To evaluate the accuracy of our physical models, all simulations were performed under uniform conditions, using the same experimental parameters, mesh, and numerical strategies. The specific examined scenario involves a highly subcooled turbulent channel flow at moderate pressure, experiencing an exponential power increase. We ensure detailed turbulence resolution at the Batchelor scale in the wall normal direction close to the heating wall. This communication presents a comparative study of LES simulations of the single-phase flow under exponential power excursion at the wall. Subsequent analyses focused on the impact of different velocity-temperature couplings on the prediction of wall heat transfer, incorporating comparisons with experimental infrared thermometry measurements. Early in the transient phase, temperature peaks are confined within turbulent streaks, as reported in the existing literature. However, as the exponential power transient unfolds, the viscous layer and streak structures destabilize, leading to a more dispersed distribution of hot spots. Preliminary findings suggest a transition in heat transfer modes from turbulence-driven to conduction during the final stages of the single-phase transient.

Density and volume of adsorbed methane in key applications for in-situ gas content: Insights from molecular simulation

The evaluation of the in-situ gas content in deep coal seams, potentially containing free gas in saturated-oversaturated reservoirs, holds practical significance for exploration and production compared with shallow undersaturated-saturated reservoirs dominated by adsorbed gas. However, owing to the inherent limitations of volumetric and gravimetric methods, the accurate assessment of adsorbed and free gases faces significant challenges. In this study, based on molecular simulations, we focused on slit-shaped pores to explore the microscopic interaction mechanisms between coal and methane molecules under different pore sizes, temperatures, and pressures. By combining isothermal adsorption and pore structure experiments, the distribution characteristics of the adsorbed phase density (APD) and adsorbed phase volume (APV) were determined. The results showed that, in pores smaller than 1.5 nm, methane exhibited an aggregated state distribution (containing only adsorbed methane) characterized by micropore filling adsorption. In pores larger than 1.5 nm, methane showed a dispersed state distribution (coexistence of adsorbed and free methane) characterized by monolayer adsorption. The APD increased with pressure and decreased with temperature and pore size, whereas the APV remained independent of the pressure and temperature. In the in-situ gas content evaluation, three adsorption models (SL, SDR, and SL + SDR models) considering APV and APD were utilized to describe the methane adsorption behavior. The SDR model considering the APV was consistent with the actual physical properties and molecular simulation results. Traditional correction methods often lead to an overestimation of the adsorbed methane content, and neglecting the APV can result in an overestimation of the free methane content. In summary, the SDR model considering the APV can provide more rigorous scientific support for the refined study of methane occurrence states and gas content distribution.

Modulating single-atom sulfur-vacancy defect in MoS2-x catalysts to boost cathode redox kinetics for vanadium flow batteries

Vanadium flow batteries (VFBs) have great potential for application in energy storage systems. However, the sluggish cathode redox kinetics still greatly restricts their operation at high current densities. Herein, we boost cathode redox chemistry by modulating single-atom sulfur-vacancy (S-vacancy) defect of MoS2-x in-situ grown on carbon felts via a facile chemical etching method. Firstly, the optimized S-vacancy concentration is figured out via high throughput calculations based on d-band center theory. By precisely controlling etching duration, we achieve a tailored S-vacancy concentration, leading to highly dispersed S-vacancies, increased specific surface area, and improved hydrophilicity. Electrochemical characterizations demonstrate that optimized S-vacancy state can significantly facilitate the VO2+/VO2+ kinetics. Moreover, analysis of electron density difference and integrated crystal orbital Hamiltonian group further reveals that dispersed S-vacancy distribution also contribute to efficient surface electronic structure and enhanced adsorption process. Benefiting from enhanced VO2+/VO2+ kinetics, VFB single cell achieves a superior EE of 78.73 % at 300 mA cm−2 and is able to last for 500 cycles without decay. This work demonstrates the promising potential of single-atom S-vacancies catalysts in the fabrication of flow battery electrodes and more importantly sheds light on the fundamental modulation essence of d-band center in MoS2-x towards enhanced cathode redox kinetics.

Twin and phase boundaries synergistic effect on multiscale dynamic fracture in Ni-based deformed superalloy

A multi-scale model of dynamic impact fracture of Ni-based deformed superalloy was proposed based on molecular dynamics and finite element methods, and verified by experiments to reveal the synergistic effect of twin and phase boundaries on dynamic fracture properties and behavior from nanoscale to macroscale. The results show that the synergistic effect of twin and phase boundaries can effectively suppress the unfavorable brittle propagation in the nanoscale owing to the dispersed distribution of strengthening phase-induced reduction of the stress concentration on the twin boundary. The nucleation and emission of perfect dislocations, Shockley dislocations, and Frank dislocations promote ductile propagation, while the pile-up of stair-rod dislocations induced stress concentration leads to brittle propagation. In the macroscale, the synergistic effect of twin and phase boundaries can effectively inhibit the loss of dynamic fracture toughness, and impede crack initiation and crack propagation through the reduction of Mises stress concentration and the decrease of maximum equivalent strain caused by the dispersed Ni3Al precipitates. The physical mechanism of the multi-scale crack propagation and fracture, and the influence law of dynamic fracture toughness of Ni-based deformed superalloy, can provide a guide to the failure prediction, protection, and development of aviation turbine blades.

Air-blast atomization of a liquid film

Air-blast atomizers are extensively used for a variety of purposes. Due to its complexity, the atomization mechanism has not been elucidated. In this study, a mechanistic model is proposed to predict the droplet diameter distribution based on the atomization process of a planar liquid film with co-current gas flows, and its validity is examined by comparing the estimated and measured droplet diameters using high-speed image analysis and laser measurement. As a result, using high-speed imaging, we clarified that the bag film rupture is caused not by the turbulence of the gas flow but by the impact of floating droplets on the liquid film of the expanding bag when the film is thin enough. The average thickness of the liquid film at the bag breakup is of the order of micrometres and varies greatly, resulting in a dispersed distribution of droplet diameters. After the film ruptures, the bag film shrinks towards its transversal and vertical rims due to surface tension, forming large-diameter ligaments. During the contraction process of the bag film, tiny droplets of the order of micrometers are formed at the edge of the perforation. Finally, the remaining ligaments with large diameters fragment into large droplets with submillimetre diameters. The good agreement between the measured and predicted droplet diameter distributions validated the mechanistic model.

Design of a gradient elastic modulus transition layer based on film-substrate adhesion

The codeformation process of Ti6Al4V (TC4) substrate and chromium nitride (CrN) films with dense/loose CrN and gradient elastic modulus CrN/CrNx/Cr(N) (G-CrN) structures under normal impact load were simulated by changing the thicknesses of the films or the loose CrN and G layers. The dispersed distribution of interfacial tensile stresses and strains of G-CrN films improved the layers’ codeformation, compared with the firm large layer of the dense/loose CrN films. The stress reduced as the loose/G layer thicknesses increased. The 4.7 μm CrN films with various thicknesses of the G-layers, 0.2 µm, 0.6 µm, 0.75 µm and 0.9 µm, were prepared on TC4 to evaluate the film-substrate adhesions and verify the simulated deformation procedure. A G-layer between a ceramic film and its alloy substrate is needed, and the 0.83–1.08 µm thicknesses of the G-layers were suggested for the CrN/TC4 system varied with the films’ thicknesses. The dispersed distribution of the tensile stress and strain within the G-CrN film was the mechanism of the film-substrate adhesion improvement.

Microwave hydrothermal in situ synthesis of highly dispersed metal-organic framework@SiC as a promising structured catalyst

Metal-organic framework (MOF) materials with loaded catalysts have recently garnered substantial interest in the catalysis field. However, the catalytic performance of MOF catalysts is hindered by particle aggregation. This study introduces a microwave-assisted anchoring strategy to improve the dispersion of UIO-66-NH2 on SiC surfaces. The dispersion can be effectively controlled by varying the SiC carrier content. Scanning electron microscopy and transmission electron microscopy analyses show that as the SiC content increases from 2% to 10%, MOFs exhibit a more dispersed distribution on the surface. This is exemplified in the esterification reaction between acetic acid and cyclohexene, where a higher MOF dispersion leads to a conversion rate boost from 70% to 75%. Numerical simulations reveal that microwave's selective heating property plays a crucial role in achieving this enhanced dispersion. This work contributes a systematic approach to enhance MOF dispersion and advances the development of structured catalysts based on MOFs.

Impact of Nature of Medical Data on Machine and Deep Learning for Imbalanced Datasets: Clinical Validity of SMOTE Is Questionable

Dataset imbalances pose a significant challenge to predictive modeling in both medical and financial domains, where conventional strategies, including resampling and algorithmic modifications, often fail to adequately address minority class underrepresentation. This study theoretically and practically investigates how the inherent nature of medical data affects the classification of minority classes. It employs ten machine and deep learning classifiers, ranging from ensemble learners to cost-sensitive algorithms, across comparably sized medical and financial datasets. Despite these efforts, none of the classifiers achieved effective classification of the minority class in the medical dataset, with sensitivity below 5.0% and area under the curve (AUC) below 57.0%. In contrast, the similar classifiers applied to the financial dataset demonstrated strong discriminative power, with overall accuracy exceeding 95.0%, sensitivity over 73.0%, and AUC above 96.0%. This disparity underscores the unpredictable variability inherent in the nature of medical data, as exemplified by the dispersed and homogeneous distribution of the minority class among other classes in principal component analysis (PCA) graphs. The application of the synthetic minority oversampling technique (SMOTE) introduced 62 synthetic patients based on merely 20 original cases, casting doubt on its clinical validity and the representation of real-world patient variability. Furthermore, post-SMOTE feature importance analysis, utilizing SHapley Additive exPlanations (SHAP) and tree-based methods, contradicted established cerebral stroke parameters, further questioning the clinical coherence of synthetic dataset augmentation. These findings call into question the clinical validity of the SMOTE technique and underscore the urgent need for advanced modeling techniques and algorithmic innovations for predicting minority-class outcomes in medical datasets without depending on resampling strategies. This approach underscores the importance of developing methods that are not only theoretically robust but also clinically relevant and applicable to real-world clinical scenarios. Consequently, this study underscores the importance of future research efforts to bridge the gap between theoretical advancements and the practical, clinical applications of models like SMOTE in healthcare.

Cerium oxide and neodymium oxide phytoextraction by ryegrass in bioenhanced hydroponic environments

Sustainable technologies for the recovery of rare earth elements (REE) from waste need to be developed to decrease the volume of ore mining extractions and its negative environmental consequences, while simultaneously restoring previously impacted lands. This is critical due to the extensive application of REE in everyday life from electronic devices to energy and medical technologies, and the dispersed distribution of REE resources in the world. REE recovery by plants has been previously studied but the feasibility of REE phytoextraction from a poorly soluble solid phase (i.e., nanoparticles) by different plant species has been rarely investigated. In this study, the effect of biostimulation and bioaugmentation on phytorecovery of REE nanoparticles (REE-NP) was investigated by exposing ryegrass seeds to REE-NP in hydroponic environments. This was studied in two sets of experiments: bioaugmentation (using CeO2 nanoparticles and Methylobacterium extorquens AM1 pure culture), and biostimulation (using CeO2 or Nd2O3 nanoparticles and endogenous microorganisms). Addition of M. extorquens AM1 in bioaugmentation experiment including 500 mg/L CeO2 nanoparticles could not promote the nanoparticles accumulation in both natural and surface-sterilized treatments. However, it enhanced the translocation of Ce from roots to shoots in sterile samples. Moreover, another REE-utilizing bacterium, Bacillus subtilis, was enriched more than M. extorquens in control samples (no M. extorquens AM1), and associated with 52% and 14% higher Ce extraction in both natural (165 μg/gdried-plant) and surface-sterilized samples (136 μg/gdried-plant), respectively; showing the superior effect of endogenous microorganisms’ enrichment over bioaugmentation in this experiment. In the biostimulation experiments, up to 705 μg/gdried-plant Ce and 19,641 μg/gdried-plant Nd could be extracted when 500 mg/L REE-NP were added. Furthermore, SEM-EDS analysis of the surface and longitudinal cross-sections of roots in Nd2O3 treatments confirmed surface and intracellular accumulation of Nd2O3-NP. These results demonstrate stimulation of endogenous microbial community can lead to an enhanced REE phytoaccumulation.