Structural State Research Articles

Seismic performance loss evaluation of reinforced concrete frame structure based on updatable damage model

AbstractAs structural seismic damage develops, the internal force transfer and damage weight relationship of component are constantly changing, and the fixed weighted coefficient is adopted by the traditional weighted method, which cannot reflect the changes in the structural damage state. The structure is a network formed by connecting a large number of components, and the network state undergoes complex changes with the development of component damage. In this paper, a novel method for component damage transfer to structural seismic performance loss is proposed using network shortest paths. First, a directed weighted complex network based on force transfer direction and component stiffness is constructed for reinforced concrete (RC) frame structures. Then, the component damage is calculated by the degradation of its stiffness and is used to update the weight distribution of the damage network. Finally, the structural performance loss is evaluated by the degradation of damage network efficiency. Results show that the proposed method with an updated component weight relationship is able to reflect the true loss of structural performance according to the finite element dynamic elastic‐plastic analysis of RC frame structures. For the structural performance loss degree (none, slight, moderate, severe, complete), the proposed method and the weighted method both exhibit high accuracy (number correctly classified/total number of samples) when structural performance loss is none, severe, or complete loss. The accuracy of the proposed method is significantly higher than that of the weighted method when structural performance loss is slight and moderate loss, with 58.1% and 84.2% improvement, respectively. For structural typical damage modes (global, local, and weak layer damage mode), the proposed method and the weighted method both exhibit high accuracy when structures exhibit global damage mode. The accuracy of the proposed method is significantly higher than that of the weighted method when structures exhibit local and weak layer damage mode. The accuracy of the proposed method is stable at 95.2%, while the accuracy of the weighted method is 76.2% and 70.2%, respectively. Overall, the weighted method exhibits high accuracy when structural performance loss is less than slight loss or greater than moderate loss, while the proposed method exhibits high accuracy throughout the entire process of structural performance loss, especially in moderate loss.

Pioneering preparation and analysis of a clean surface on a microcrystal, mined by a focused ion beam

We demonstrate a series of procedures to prepare a clean surface of micro-sized graphite, mined from a bulk flake and securely affixed onto a macroscopic Si plate by focused ion beam scanning electron microscope. Analyses of structure and electronic (chemical) states were made using micro-beam X-ray photoelectron spectroscopy and angle-resolved photoemission spectroscopy. At the surface of the micro graphite, the band dispersion from a single-domain structure was observed. The proposed methodology showcases its capability to produce clean and high-quality micro samples suitable for surface-sensitive analyses. This technique paves the way to investigate surfaces of unexplored microcrystals embedded in complex materials.

Ultrahigh Critical Current Density across Sliding Electrical Contacts in Structural Superlubric State.

In conventional sliding electrical contacts (SECs), large critical current density (CCD) requires a high ratio between actual and apparent contact area, while low friction and wear require the opposites. Structural superlubricity (SSL) has the characteristics of zero wear, near zero friction, and all-atoms in real contact between the contacting surfaces. Here, we show a measured current density up to 17.5 GA/m^{2} between microscale graphite contact surfaces while sliding under ambient conditions. This value is nearly 146 times higher than the maximum CCD of other SECs reported in literatures (0.12 GA/m^{2}). Meanwhile, the coefficient of friction for the graphite contact is less than 0.01 and the sliding interface is wear-free according to the Raman characterization, indicating the presence of the SSL state. Furthermore, we estimate the intrinsic CCD of single crystalline graphite to be 6.69 GA/m^{2} by measuring the scaling relation of CCD. Theoretical analysis reveals that the CCD is limited by thermal effect due to the Joule heat. Our results show the great potential of the SSL contacts to be used as SECs, such as micro- or nanocontact switches, conductive slip rings, or pantographs.

Mechanical behaviors of segmental lining of shield tunnels: A comparison between stagger-jointed and cross-jointed assembly type

The assembly type of segmental linings has a great impact on mechanical behaviors and failure mechanism of the linings. In this paper, a sophisticated 3D FEM model for segmental linings with different assembly types (single ring, three rings cross-jointed and stagger-jointed) was established to investigate the mechanical behaviors and failure mechanism of the linings under loading condition, with particular focus on the structural effect of the staggered-jointed linings. The effectiveness of the numerical model was verified by the data from the on-site measurements. The results show that the segmental linings turn into horizontal ellipse under the overloading condition. For the stagger-jointed linings, the initial cracks are emerged on the segment body and some oblique cracks and circumferential cracks are generated due to the interaction among rings. The failure process of the stagger-jointed linings was illustrated by the damaged plasticity point which are mainly staggered distributed on segment body and the time sequence of the points reaching certain structural performance state are progressive and discrete. The stagger effect is captured on the internal force of stagger-jointed linings and the major reasons causing the bending moment transmission are analyzed. Above analysis will contribute to the structural safety evaluation of the tunnels.

Synthesis of humic acid with the obtaining of potassium humate based on coal waste from the Lenger deposit, Kazakhstan

Abstract This article a synthesis of humic acid with the obtaining of potassium humate based on coal waste from the Lenger deposit. Accumulated industrial waste heavily pollutes the environment and has a direct impact on all living things. The accumulation of waste in landfills increases the pollution level of the atmosphere, soil, groundwater, and surface water, destroys the functioning of ecosystems, and damages agriculture and construction. A sieve analysis was carried out to study the fine fractions of coal waste, and a scanning electron microscope analysis was performed to study the mineralogical, structural state and X-ray chemical phase composition. The chemical composition of coal waste was studied using differential thermal analysis during heat treatment. The optimal parameters of the process for obtaining humic acids are established, and the results of experimental work are presented. The results are confirmed by mathematical planning of the experiment using the method of orthogonal plan of the second order. The mathematical planning results were tested according to the Student and Fischer criteria. Based on the conducted studies, it was identified that the degree of extraction of humic acid reaches up to 95.90% in terms of the organic phase, and the concentration of humic acid is 49.13%. From the humic acids obtained using potassium hydroxide, potassium humate was synthesized. The potassium humate obtained in its composition has fertilizer properties. Therefore, the obtained potassium humate will be used for the production of humic fertilizers to improve soil fertility and crop yields. The synthesis of humic acids with the production of potassium humate is aimed at reducing the accumulated industrial waste, which in turn allows you to regulate and improve the ecological situation and green ecology in the region.

Unsupervised deep learning approach for structural anomaly detection using probabilistic features

Civil structures may deteriorate during their service life due to degradation or damage imposed by natural hazards such as earthquakes, wind, and impact. Structural performance anomaly detection is essential to provide an early warning of structural degradation limit states in order to prevent potential catastrophic failure. Data-driven machine learning approaches have been widely used for this, due to their capability in capturing features sensitive to damage-induced anomalies from structural health monitoring (SHM) data, assuming that such data are available. Although machine learning models have been used, many are challenged by the vast operational and environmental variability that can corrupt SHM data and by (typically) strongly correlated information from different sensors in the SHM data. This paper proposes an unsupervised deep learning approach for the detection of structural anomaly based on a deep convolutional variational autoencoder (DCVAE) for feature extraction coupled with support vector data description (SVDD) for anomaly detection. The proposed DCVAE-SVDD method has several appealing strengths. First, the variational latent encoding is used to capture the features of monitoring data through a probability distribution. The integration of the Kullback–Leibler divergence in the loss function provides accurate estimation of the probability distributions. Second, the DCVAE designed with convolutional and deconvolutional operations utilizes the correlation among multisensor data to avoid loss of correlation features and achieve better performance in feature extraction. Third, the SVDD is utilized to create a minimum-volume hypersphere that contains the anomaly-sensitive statistical features of the state. The hypersphere accurately separates anomaly-sensitive statistical features of reference states of structure from the anomalous ones. A computational frame model and a laboratory grandstand model are used to evaluate the performance of the proposed method for detecting structural anomaly. The results demonstrate the superiority of the proposed DCVAE-SVDD in detection accuracy over the other commonly used structural anomaly detection methods (deep autoencoder combined with SVDD autoregressive model with one-class support vector machine, and principal component analysis).

Data-Driven Fatigue Failure Probability Updating of OSD by Bayesian Backward Propagation

This study introduces a data-driven approach for updating the fatigue failure probability of the orthotropic steel deck (OSD) using Bayesian backward propagation. The OSD in steel bridges is considered as a parallel system composed of two critical fatigue-prone components, namely, the rib-to-diaphragm and rib-to-deck joints. A probabilistic model for fatigue reliability is established based on the equivalent structural stress method and limit state function. The system-level fatigue reliability model is then constructed, taking into account the correlations between limit states of individual components through Bayesian network forward propagation. The key advantage of the Bayesian network-based framework is its ability to perform backward propagation, allowing for the updating of failure probabilities for critical components when the system-level failure of the OSD is observed. Consequently, the proposed approach enables the identification of vulnerable components through data-driven fatigue failure probability updating. Finally, the approach is applied to a real instrumented steel bridge to determine the time-dependent fatigue failure probability at both the system and component levels over its service life. The results show that the component-level fatigue failure probability model will underestimate the fatigue life in comparison to the system-level model. Meanwhile, the proposed method could identify vulnerable components by quantifying the fatigue failure probability of in-service steel bridges.

Artificial Intelligence-Based Damage Identification Method Using Principal Component Analysis with Spatial and Multi-Scale Temporal Windows

Previous studies have demonstrated the superior damage identification performance of the double-window principal component analysis (DWPCA) method over traditional PCA methods and other traditional techniques, such as wavelet and regression analysis. DWPCA uses temporal windows to discriminate structural states and spatial windows to exclude damage-insensitive responses, making it more effective for damage identification. However, determining the optimal temporal window scale and its impact on damage identification performance still remains unclear. In this study, different scales of temporal windows, including yearly, seasonal and monthly windows, are employed to obtain corresponding damage features, i.e., eigenvectors derived from DWPCA. These damage-sensitive eigenvectors from various temporal windows are then used as inputs for artificial intelligence (AI) algorithms to localize and quantify damages. In this paper two types of AI algorithms are employed: random forest (RF) and bidirectional gated recurrent unit (BiGRU). A numerical study using a benchmark model is used to evaluate the contribution of the eigenvector of each temporal scale to damage identification. The results demonstrate that the combined DWPCA eigenvectors [Formula: see text] from the three temporal windows effectively enhance the AI-based damage identification capability. Besides, AI algorithm with [Formula: see text] can have high accuracy exceeding 95% under limited training data sets and strong noise. Additionally, when DWPCA eigenvectors from monthly or seasonal windows as inputs, which is both sensitive to damages and noise, the BiGRU also achieves high accuracy of over 90% for damage identification, due to its advantages in feature extraction. These findings suggest that the proposed approach has significant potential for real-life structural health monitoring applications.

Прогнозирование и оценка триботехнической эффективности азотированного слоя деталей машин

Following the laws of tribology and tribotechnics, also the results of experimental studies of reality of structure and properties change in the zone of contact tribodeformation of structural steels and alloys of different structural classes subjected to nitriding, an approach to forecasting and comprehensive assessment of the tribotechnical efficiency of nitriding of structural materials and products made of them has been developed. Analysis of the patterns of changes in the structure of the diffusion zone of nitriding steels: abnormal, martensitic and austenic, and relative wear resistance tests, taking into account their composition and technological parameters of the treatment process, showed that maximum wear resistance was provided by a nitration coating containing hardening dispersed particles of incoherent nitrides, ensuring a lower liability to brittle behavior of the nitration case due to low level of matrix level microdeformation. At the same time, preliminary types of treatment (thermal treating and deformation processing) of nitriding steels contribute to structural and phase state of the surface layer, which has added tribological performance. For nitrided ferroalloys with different matrix lattices, the most significant characteristics of the structural state and properties of the surface layers affecting the level of surface fracture under friction have been found empirically: the particle size of nitrides of alloying elements, the distance between them, the density of their distribution, the matrix lattice microdeformation, the values of X-ray lines intrinsic broadening for structural components of the material in the friction deformation zone, the hardness of the nitration case and its changes under friction. These experimental results are taken as a principle of the proposed method for forecasting and assessment of metal tribotechnical efficiency. This principle of method is based on a tribological criterion containing micro- and macroscopic characteristics of the material in the zone of contact deformation under friction, the choice of fabricating methods for the product takes place to ensure an acceptable level of wear intensity. Then, by measurement, using surface large deformation method, the ability of the nitration case formed as a result of treatment according to the selected treatment schedule to perceive surface nondestructive plastic deformation is evaluated. It affords a basis for the selected nitriding treatment schedule. The completion of the assessment is the determination of the values of the maximum operability of the nitriding material under conditions of friction and wear (alarm pressure when a tribocouple operates steadily; critical pressure when it is inoperable, but its operation is possible with short-term overloads; the average total wear intensity of the couple combined). The totality of the identified parameters allows recommending the material, its working and predicting operating modes and durability of tribounit.

DNA G-Quadruplex Is a Transcriptional Control Device That Regulates Memory.

The conformational state of DNA fine-tunes the transcriptional rate and abundance of RNA. Here, we report that G-quadruplex DNA (G4-DNA) accumulates in neurons, in an experience-dependent manner, and that this is required for the transient silencing and activation of genes that are critically involved in learning and memory in male C57/BL6 mice. In addition, site-specific resolution of G4-DNA by dCas9-mediated deposition of the helicase DHX36 impairs fear extinction memory. Dynamic DNA structure states therefore represent a key molecular mechanism underlying memory consolidation.One-Sentence Summary: G4-DNA is a molecular switch that enables the temporal regulation of the gene expression underlying the formation of fear extinction memory.

Deciphering non-elastic deformation in amorphous alloy: Simultaneous aging-induced ordering and rejuvenation-induced disordering

The mechanical and physical properties of amorphous alloys depend on their time, temperature, and stress history. Due to their out-of-thermodynamic-equilibrium nature, describing the nonelastic deformation while considering the evolution of the structural state poses a significant challenge. We address this challenge by incorporating a parameter for structural state changes into a conventional deformation theory. This allows us to account for aging-induced ordering and deformation-induced disordering in the description of the mechanical deformation. In the apparent elastic regime (small strain), aging dominates while disorder caused by deformation can be disregarded. In this context, we have also made modifications to the widely used stretched exponential function, incorporating in-situ aging during deformation. This modification successfully describes the stress relaxation behavior under small deformation conditions and provides insights into parameter evolution in this process. Under large deformation conditions, both aging and deformation induced rejuvenation effects on the structural state must be considered simultaneously. By analyzing the evolution of defect concentration during this process, we describe relevant experimental results within the framework of the free volume theory, effectively separating the contributions of aging and rejuvenation to the structural state during the deformation process.

Effects of manganese doping on the lattice structure and iron ion states in La2/3Ca1/3Fe1-xMnxO3-δ

In this paper, La2/3Ca1/3Fe1-xMnxO3-δ(x = 0–0.6) nano particles have been prepared by the sol-gel method. X-ray diffraction (XRD) analysis revealed that with the increase of Mn doping content, the main diffraction peak shifted to the right, the lattice parameters decreased overall, and the degree of lattice distortion gradually reduced. X-ray photoelectron spectroscopy (XPS) analysis indicates that the valence states of Fe and Mn in the system coexist as trivalent and tetravalent, and with the increase in Mn doping, the ratio of Fe3+/Fe4+ decreases, while the ratio of Mn3+/Mn4+ slightly increases. The results of Mössbauer spectrum analysis revealed that as the Mn doping content increased, some Fe ion valence states in the system gradually changed from Fe3+ to Fe4+, and the presence of the paramagnetic phase became increasingly prominent. Furthermore, with the increase of Mn doping content, the degree of lattice distortion in the system decreased, which is consistent with the results obtained from the XRD analysis. This work will provide a reference for future research on the effects of manganese doping in similar systems.

Distinct superconducting states in the pressure-induced metallic structures of topological heterostructure BiTe

The (Bi2)m(Bi2Te3)n homologous series possess natural multilayer heterostructure with intriguing physical properties at ambient pressure. Herein, we report the pressure-dependent evolution of the structure and electrical transport of the dual topological insulator BiTe, a member of the (Bi2)m(Bi2Te3)n series. With applied pressure, BiTe exhibits several different crystal structures and distinct superconducting states, which is remarkably similar to other members of the (Bi2)m(Bi2Te3)n series. Our results provide a systematic phase diagram for the pressure-induced superconductivity in BiTe, contributing to the highly interesting physics in this (Bi2)m(Bi2Te3)n series.

Peculiarities of morphological indicators of quail spleen (Coturnix japonica Temminck et Schlegel, 1849) when using protein-vitamin mineral supplements

In most countries of the world, poultry farming is one of the main branches of agriculture, which provides the population with high-quality food products. To date, the positive dynamics of the growth of such a branch of industrial poultry farming as quail breeding has been noted. Quails have a complex of excellent economic and productive advantages compared to other agricultural birds – high body temperature, intensive metabolism in the body, small size, precocity, high egg productivity. The question of increasing the productivity of quail breeding, as a branch of precocious animal husbandry, has always occupied the attention of biologists, morphologists, physiologists, geneticists and technologists. This topical problem has various scientific aspects: morphological, histochemical, physiological, genetic, etc. Special attention in the conducted research is required to study the impact of additives on the body of quails, the absence of negative effects and the production of safe products for humans. We chose the spleen as a biomarker, because the spleen is an important peripheral organ of immune protection, sensitive to the action of various factors, whose morphofunctional indicators determine the magnitude and nature of the impact. The purpose of the research was to determine the effect of modern protein-vitamin mineral supplements, which are advertised and offered by producers in the poultry industry to stimulate the growth and development of the bird, on the quail body. In the studies, the features of the microscopic structure and morphometry of the spleen of control and experimental animals were used as sensitive characteristics of the action of additives. The proposed methods are aimed at researching the impact of protein-vitamin mineral supplements on the relevant industry. So, for 21 days, mineral supplements “Multilife”, “Missy” and “Standard Agro” were added to the main ration of quails. Using macrometric methods, the body weight of quails, the weight of the spleen (absolute and relative) were determined. For histological studies, pieces of the spleen were fixed in a 10 % formalin solution, and after embedding in paraffin, histological sections were prepared from it, which after deparaffinization were stained with hematoxylin and eosin, according to the methods of Brachet and Van Gieson. For electron microscopic examination, the spleen was immediately fixed with a 2.5 % solution of glutaraldehyde in a phosphate buffer with additional fixation in a 1 % solution of osmium tetroxide according to Caulfield. For the first time, the ultrastructural organization of the spleen of Japanese quail was investigated after feeding protein-vitamin mineral supplements, which may indicate the absence of their negative impact on the structural and functional state of the spleen. Important morphological structural indicators of the morphofunctional state of the spleen were determined: the relative area of the white pulp, red pulp, lymphoid nodules, periarterial lymphoid sheaths, and the contractile apparatus. According to the analysis of the morphological results obtained by us, it was investigated that the microscopic structure of the quail spleen is characterized by the presence of a support-contractile apparatus with a relative area of 4.58 ± 0.76 % and single radial trabeculae. The parenchyma is formed by white and red pulp without clear boundaries. Lymphoid nodules without bright centers, periarterial lymphoid sheaths, and ellipsoids were identified as part of the white pulp. The ultrastructural organization of the spleen of quails had peculiarities: the nuclei of leukocytes contain large nucleoli, the endotheliocytes of the central artery of the lymphoid follicle perform a phagocytic function by accumulating autophagosomes in their cytoplasm. The macroscopic, microscopic and ultramicroscopic structure of quails that were added to the main diet with the listed additives did not undergo any changes. As a result, the following supplements led to an increase in the body weight of quails: by 5.78 % when using the Multilife supplement, by 12.51 % when using the Missy supplement, and by 8.12 % when using the Standard Agro supplement, and the weight of the spleen on 7.17 %, 16.04 % and 10.54 %, respectively. The conducted studies showed that the relative weight of the organ practically did not change. At the same time, there is a trend towards an increase in the relative area of the white pulp and the supporting-contractile apparatus. Taking into account the obtained data, it can be concluded that our research confirms the feasibility of using modern protein-vitamin mineral supplements in poultry farming to stimulate the growth and development of poultry. Especially valuable is the absence of a negative effect on the morphofunctional indicators of the spleen, which was used as a biomarker in research.

Alteration of chromosome structure impacts gene expressions implicated in pancreatic ductal adenocarcinoma cells

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with a five-year survival rate of approximately 10%. Genetic mutations are pivotal drivers in PDAC pathogenesis, but recent investigations also revealed the involvement of non-genetic alterations in the disease development. In this study, we undertook a multi-omics approach, encompassing ATAC-seq, RNA-seq, ChIP-seq, and Hi-C methodologies, to dissect gene expression alterations arising from changes in chromosome accessibility and chromatin three-dimensional interactions in PDAC.ResultsOur findings indicate that chromosomal structural alterations can lead to abnormal expressions on key genes during PDAC development. Notably, overexpression of oncogenes FGFR2, FOXA2, CYP2R1, and CPOX can be attributed to the augmentation of promoter accessibility, coupled with long-range interactions with distal elements. Additionally, our findings indicate that chromosomal structural alterations caused by genomic instability can lead to abnormal expressions in PDACs. As an example, by analyzing chromosomal changes, we identified a putative oncogenic gene, LPAR1, which shows upregulated expression in both PDAC cell lines and clinical samples. The overexpression is correlated with alterations in LPAR1-associated 3D genome structure and chromatin state. We further demonstrated that high LPAR1 activity is required for enhanced PDAC cell migration in vitro.ConclusionsCollectively, our findings reveal that the chromosomal conformational alterations, in addition to the well-known genetic mutations, are critical for PDAC tumorigenesis.

Improving the high-voltage behavior of LiNiO2 through electrochemical property regulation by Mg doping

In this study, high-temperature solid-phase techniques are used to prepare pristine and Mg-modified LiNiO2 cathode materials. Various characterizations are performed to analyze the morphology, structure, and electrical state of the two materials. Electrochemical tests show that Mg doping effectively improves the electrochemical properties of the materials. In particular, the modified sample exhibits a higher specific discharge capacity of 244.5 mA h g−1 than the pristine sample. Moreover, its maximum capacity retention after 304 cycles at 1 C is 54.1%. In situ X-ray powder diffraction imaging reveals that the modified material has better phase-transition reversibility than the pristine material. Density functional theory calculations indicate that Mg-doped Li sites can accelerate Li+ transport. Atomic force microscopy results demonstrate that Mg-doped Li sites act as supportive skeletons that enhance the mechanical properties of the material. Therefore, the proposed strategy for the Mg doping of Li sites can improve the architecture of LiNiO2 cathode materials.

Enhancing the Vickers hardness of Yttrium borides through bond optimization

The hard nature of transition metal boride reminds a conundrum. Compared to the diboride, we propose that the high hardness of transition metal boride strongly depends on the structural feature and bonding state (bond type, bond number and bond direction) in addition to the network B-B covalent bond. To demonstrate our idea, we symmetrically study the structural configuration, hardness, elastic properties and bonding state of the B-rich Y-B borides by using the first-principles method. The hexagonal YB2, tetragonal YB4, cubic YB6 and cubic YB12 are studied. The convex hull implies that YB4 has better thermodynamic stability in comparison to the YB2, YB6 and YB12. Importantly, it is found that the calculated Vickers hardness of the cubic YB12 is 41.4 GPa, indicating that YB12 is a potential superhard material. However, the Vickers hardness of YB2, YB4 and YB6 is lower than 40 GPa. Naturally, the high harness of YB12 is determined by the network B-B covalent bond. For non-superhard materials (YB2, YB4 and YB6), the hardness is related not only to the 3D network B-B covalent bond but also to the structural feature and bond state, particularly for TM-B bond. Compared to the strong B-B covalent bond, the Y-B bond plays an important role in harness because the Y-B bond is not surrounded by the 3D network B-B covalent bond. Therefore, we believe that the bond type and bond arrangement play an important role in hardness. This work can provide new design rule to adjust the structural feature and bond state to enhance the Vickers hardness of transition metal borides superhard materials.

Review on Medical Applications of Manganese Oxide (Mn2+, Mn3+, and Mn4+) Magnetic Nanoparticles

Apart from our imagination, the nanotechnology industry is rapidly growing and promises that the substantial changes that will have significant economic and scientific impacts be applicable to a wide range of areas, such as aerospace engineering, nanoelectronics, environmental remediation, and medical healthcare. In the medical field, magnetic materials play vital roles such as magnetic resonance imaging (MRI), hyperthermia, and magnetic drug delivery. Among them, manganese oxide garnered great interest in biomedical applications due to its different oxidation states (Mn2+, Mn3+, and Mn4+). Manganese oxide nanostructures are widely explored for medical applications due to their availability, diverse morphologies, and tunable magnetic properties. In this review, cogent contributions of manganese oxides in medical applications are summarized. The crystalline structure and oxidation states of Mn oxides are highlighted. The synthesis approaches of Mn-based nanoparticles are outlined. The important medical applications of manganese-based nanoparticles like magnetic hyperthermia, MRI, and drug delivery are summarized. This review is conducted to cover the future impact of MnOx in diagnostic and therapeutic applications.

Modal signal analysis of parabolic shell structures with flexoelectric sensors

The flexoelectric effect, garnering extensive attention in recent years, is an electro-mechanical coupled gradient effect that widely exists in dielectric materials and holds great potential for applications in structural sensing and actuation. The parabolic shell structure, characterized by line focusing, finds widespread use in key structural components such as solar trough collectors and communication antennas. Distributed sensing of the structural states of these parabolic shells is critical for vibration control, health monitoring, and shape control of precision structural systems. Therefore, flexoelectric sensing research based on parabolic shell structure has become an important topic. This study establishes a mathematical model for flexoelectric sensing in a parabolic shell with four-sided simply supported boundary conditions. The model is based on the direct flexoelectric effect, and thin shell assumption, and incorporates specific Lamé parameters and curvature radius. The electro-mechanical strain gradient/signal generation characteristics and distributed modal flexoelectric signals on the parabolic shell are investigated. The sensing signal under the open-circuit conditions is deduced, and the flexoelectric sensing signal and sensing characteristics of different modes are analyzed. The formulation of the flexoelectric neural sensing signal for the parabolic shell structure is provided and divided into two components: a circumferential bending component and a longitudinal bending component. In the case studies, the effects of design parameters such as flexoelectric sensor thickness, size, and aspect ratios are evaluated and compared. The analysis and results of this study offer a theoretical foundation and reference for refining the design parameters of the flexoelectric sensor and determining its optimal sensing position, and potentially paving the way for new applications of flexoelectric sensing technology.

Causal phase-dependent control of non-spatial attention in human prefrontal cortex

Non-spatial attention is a fundamental cognitive mechanism that allows organisms to orient the focus of conscious awareness towards sensory information that is relevant to a behavioural goal while shifting it away from irrelevant stimuli. It has been suggested that attention is regulated by the ongoing phase of slow excitability fluctuations of neural activity in the prefrontal cortex, a hypothesis that has been challenged with no consensus. Here we developed a behavioural and non-invasive stimulation paradigm aiming at modulating slow excitability fluctuations of the inferior frontal junction. Using this approach, we show that non-spatial attention can be selectively modulated as a function of the ongoing phase of exogenously modulated excitability states of this brain structure. These results demonstrate that non-spatial attention relies on ongoing prefrontal excitability states, which are probably regulated by slow oscillatory dynamics, that orchestrate goal-oriented behaviour.