Multi-layer Hierarchical Structure Research Articles

Lithium-Doped Titanium Dioxide-Based Multilayer Hierarchical Structure for Accelerating Nerve-Induced Bone Regeneration.

Despite considerable advances in artificial bone tissues, the absence of neural network reconstruction in their design often leads to delayed or ineffective bone healing. Hence, we propose a multilayer hierarchical lithium (Li)-doped titanium dioxide structure, constructed through microarc oxidation combined with alkaline heat treatment. This structure can induce the sustained release of Li ions, mimicking the environment of neurogenic osteogenesis characterized by high brain-derived neurotrophic factor (BDNF) expression. During in vitro experiments, the structure enhanced the differentiation of Schwann cells (SCs) and the growth of human umbilical vein endothelial cells (HUVECs) and mouse embryo osteoblast progenitor cells (MC3T3-E1). Additionally, in a coculture system, the SC-conditioned media markedly increased alkaline phosphatase expression and the formation of calcium nodules, demonstrating the excellent potential of the material for nerve-induced bone regeneration. In an in vivo experiment based on a rat distal femoral lesion model, the structure substantially enhanced bone healing by increasing the density of the neural network in the tissue around the implant. In conclusion, this study elucidates the neuromodulatory pathways involved in bone regeneration, providing a promising method for addressing bone deformities.

Seafood waste derived Pt/Chitin nanocatalyst for efficient hydrogenation of nitroaromatic compounds

The fabrication of reliable, reusable and efficient catalyst is crucial for the conversion of nitroaromatic compounds into more chemically valuable amine-based molecules. In this study, a series of chitin supported platinum (Pt) catalysts with high catalytic activity, stability, and reusability were developed by using chitin derived from seafood waste as raw materials. The catalytic performance differences among these catalysts activated by different methods were investigated by hydrogenation of nitroaromatic compounds. The results showed that the multilayer hierarchical pore structure and abundance of hydroxyl and acetamido groups in chitin provided ample anchoring sites for Pt nanoparticles (NPs), ensuring the high dispersion of Pt NPs. Moreover, the interconnected channels between chitin nanofibrous microspheres facilitated rapid transport of reaction substrates. The best Pt/Chitin catalyst exhibited excellent catalytic activity and broad substrate applicability in hydrogenation of nitroaromatic compounds. Significantly, even after 20 runs, no discernible deactivation of activity was observed, demonstrating exceptional catalytic reusability. The application of seafood waste-based catalysts is conducive to the development of a green/sustainable society.

Dealloying-derived TiC hierarchical porous frameworks as stable host for advanced Li metal electrode

Metallic Li has been presented to be an attractive anode for next generation energy storage devices. Nevertheless, uncontrollable Li dendrites growth and great volume change seriously restrict its applicability. Herein, we designed a hierarchical porous TiC as Li host for the advanced Li metal anode through a one-step mild dealloying method. The Li nucleation overpotential was effectively reduced due to the lithiophilic TiC as nucleation sites. Furthermore, the multilayered hierarchical structure could homogenize the current distribution and provide enough space to restrict the volume change during the cycling. As a result, the half-cell assembled with as-dealloyed TiC exhibited a markedly enhanced Coulombic efficiency of 98.5% over 400 cycles at 1 mA cm−2. The TiC/Li electrode cycled for over 1000 h with an ultralow voltage hysteresis of 17.1 mV in a symmetrical cell at 1 mA cm−2 for 1 mAh cm−2, which showed a stable cycle capacity of 117.2 mAh g− 1 at 1 C after 700 cycles in a full cell with a LiFePO4 cathode. This work provided a facile strategy to design stable host and solve the problem with Li metal batteries.

Reconfigurable and Privacy-Preserving Economical Operation for Interconnected DC Microgrid Clusters

This article presents a new distributed and reconfigurable strategy for global economical consensus operation of multiple, interconnected dc microgrid clusters in a leader–follower graph architecture. The generation costs associated with the distributed energy resources are optimized globally by observer-based controllers in a multilayered hierarchical control structure, equipped with privacy-preserving feature. Self-rearranging and event-based reconfiguration of graphs are also incorporated for obtaining feasible solution to the economic dispatch problem. This is an important aspect of the proposed work as, unlike previously reported research works, it equally prioritizes both voltage regulation and optimal operation. Moreover, continuity of supply to critical loads is a challenging criterion in autonomous systems in which the pinning or leader node plays a pivotal role. Therefore, the multifold benefits of choosing the highest generation unit as the leader in improving the power quality is highlighted for the first time, which remained undiscovered in previous works in literature. The feasibility of the proposed scheme is tested by time-domain simulations in MATLAB/Simulink. Moreover, the results obtained from the controller hardware in loop environment using a real-time digital simulator and field-programmable-gate-array-based WAVECT controller demonstrate the economical operation of the clusters with renewable energy sources.

Nitrogen-doped expanded graphite derived from spent graphite induce uniform growth of lithium peroxide for high-performance Li-oxygen battery

Clean treatment and recycling of retired graphite are of great significance to void environmental pollution and resource waste. For this reason, a simple chemical intercalation process combined melamine-assisted expansion strategy is used to prepare nitrogen-doping expanded graphite (N-EG) with a worm-like structure from waste graphite as an ideal lithium-oxygen (Li-O2) battery cathode. The pyrolysis of melamine during annealing can realize the reduction and nitrogen-doping of the expanded graphite in one step, so as to improve the conductivity and electrocatalytic activity of expanded graphite. Moreover, the continuous multilayer hierarchical porous structure of worm-like expanded graphite can not only provide sufficient free-space for the storage of discharge products but also facilitate the mass transfer for battery reactions. As a proof of concept, the as-prepared N-EG have been used as the cathode in Li-O2 battery and achieve excellent electrochemical performances, including high specific capacity, excellent rate performance and long cycle stability. Furthermore, by combining density functional theory (DFT) calculations with experimental data, we demonstrate that the introduction of N-doping in expanded graphite can induce surface combine solution-mediated growth of Li2O2 on the cathode. Such a universal method provides an environmentally friendly approach for the reuse of waste graphite to construct high-performance Li-O2 battery cathode.

Adaptive signal adjustments in humpback whale songs

The use of vocal flexibility by humpback whales (Megaptera noavaengliae) often described as “singing” is a highly sophisticated communicative process, possessing a multilayered hierarchical structure across the various acoustical parameters. A deeper spectral analysis of songs made available through Google's Pattern Radio website studied in the month of February 2015 display several adaptive signal adjustments in humpback whale songs. As single singer variations in song properties become more clear, multi-singer variations in song properties remain hypothetical. This raises an important question of incorporating a temporal analysis approach to determine the multi-singer variations in song properties.

Key influencing factors of vertical integration of electronic health records in medical consortiums

BackgroundSimilar to other countries around the world, China has incorporated the recording of electronic health data into its national strategy. After the completion of the decentralized construction phase, the construction of electronic health records in China has reached the stages of integration, sharing, and utilization. “Vertical integration” is the premise and foundation of “shared utilization” of electronic health records within the medical consortium, but it is also a bottleneck in realizing this goal. ObjectiveThe main purpose of this paper is to find out the key factors affecting the vertical integration of electronic health records in the medical consortiums, and to clarify the impact mechanism of these key factors, so as to provide reference for improving relevant policies. MethodsIn this study, an index system of influencing factors is established for cross-institutional vertical integration of electronic health records within a medical consortium, identifying key influencing factors using the combined fuzzy-DEMATEL-ASIM method and revealing the influence relationship and action mechanism among the key influencing factors using a multi-layer hierarchical influence structure model. ResultsThere are 32 factors influencing the vertical integration of electronic health records in the medical consortium, 17 of which are key factors. According to the hierarchical structure of key influencing factors, they can be divided into three categories: surface-level factors, middle-level factors and deep-level factors. ConclusionsIn practice, these key factors should be prioritized for improvement and optimization to promote integration projects. In the future, we should focus on key influencing factors to precisely implement policies, such as introducing special promotion policies, unifying development planning, changing health insurance payment methods, establishing sharing standards, and raising public awareness.

DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants

Genomic prediction is an effective way to accelerate the rate of agronomic trait improvement in plants. Traditional methods typically use linear regression models with clear assumptions; such methods are unable to capture the complex relationships between genotypes and phenotypes. Non-linear models (e.g., deep neural networks) have been proposed as a superior alternative to linear models because they can capture complex non-additive effects. Here we introduce a deep learning (DL) method, deep neural network genomic prediction (DNNGP), for integration of multi-omics data in plants. We trained DNNGP on four datasets and compared its performance with methods built with five classic models: genomic best linear unbiased prediction (GBLUP); two methods based on a machine learning (ML) framework, light gradient boosting machine (LightGBM) and support vector regression (SVR); and two methods based on a DL framework, deep learning genomic selection (DeepGS) and deep learning genome-wide association study (DLGWAS). DNNGP is novel in five ways. First, it can be applied to a variety of omics data to predict phenotypes. Second, the multilayered hierarchical structure of DNNGP dynamically learns features from raw data, avoiding overfitting and improving the convergence rate using a batch normalization layer and early stopping and rectified linear activation (rectified linear unit) functions. Third, when small datasets were used, DNNGP produced results that are competitive with results from the other five methods, showing greater prediction accuracy than the other methods when large-scale breeding data were used. Fourth, the computation time required by DNNGP was comparable with that of commonly used methods, up to 10 times faster than DeepGS. Fifth, hyperparameters can easily be batch tuned on a local machine. Compared with GBLUP, LightGBM, SVR, DeepGS and DLGWAS, DNNGP is superior to these existing widely used genomic selection (GS) methods. Moreover, DNNGP can generate robust assessments from diverse datasets, including omics data, and quickly incorporate complex and large datasets into usable models, making it a promising and practical approach for straightforward integration into existing GS platforms.

개항기 단일통화체제의 법제화와 이중통화의 운영

Existing currency research looked at the efforts and failure process to establish a single currency system based on the gold standard. Recent research is moving toward exploring the characteristics of monetary management, but still maintains the view that the establishment of a single currency system based on the gold standard is the basis of industrialization, and no research has been conducted on the characteristics of monetary management and the effect of the single currency system. Silver, which was outside the control of the state, was included in the state-managed currency system, thereby establishing a dual currency of white coins(白銅貨) and coins(葉錢). Although the volatility of high value-added currencies and inflation have deepened, the relative stability of the currency has led to the effect of blocking this volatility in the local market. At the same time, however, the multi-layered hierarchical structure of the trade market and the domestic regional market had a dual effect that contributed to capital expansion. The operation of a dual currency system through the legislation of a single currency has contributed to accelerating capitalization on the premise of a multi-layered hierarchical structure of value.

Hazard identification, risk assessment and management of industrial system: Process safety in mining industry

Hazard identification, risk assessment and management are of great significance for the safe and efficient production of industrial system. However, due to the lack of quantitative methods, the production of industrial systems still lacks safety guarantees. Firstly, we revise the accident causation model of mining industry based on the “Swiss-Cheese” model and construct a three-dimensional multi-granular structure model applied to the mining industry. To identify hazards of mining industry, a multi-layer hierarchical structure model and a system safety assessment model are established according to finite covering theorem. Then, the hazard identification is carried out based on the multi-layer hierarchical model and the risk matrix method, and a quantitative method is proposed to calculate the process indicators. Subsequently, the weighted grey relational analysis method is used for risk assessment on the driving system in mining industry. To improve the safety level of the driving system, the Hazard Identification-Assessment-Check-Action risk closed-loop management mode is used for risk management in the purpose of obtaining hazard rectification measures. Risk assessment is carried out again after risk rectification, and the safety level of the driving system can reach higher level. This research can provide guidance for the process safety improvement of industrial systems.

Evaluation of industrial development quality and analysis of influencing factors in Xi'an, China.

Industry is the lifeblood of the national economy, and it is the inevitable course of sustainability for China to promote the high-quality development of industry. A theoretical framework of industrial development quality (IDQ) was constructed, and 32 influencing factors were selected based on complex system theory. The IDQ in Xi'an from 2004 to 2019 was evaluated, and the influencing mechanisms of each IDQ factor were analyzed through an integrated maximum generalized information entropy (MGIE)-self-organizing feature mapping (SOFM) neural network-decision-making trial and evaluation laboratory (DEMATEL)-interpretive structural modeling (ISM) approach. The results show that the IDQ in Xi'an is on the rise, but the development of internal subsystems is uneven, with the technology subsystem contributing the most and the social subsystem contributing the least. There is a multi-layer hierarchical structure among the influencing factors of IDQ, and the multi-layer structure model can be divided into 10 layers. The first layer is the investment intensity of industrial pollution control, which is the most direct factor that affects IDQ. The tenth layer is the industrial wastewater discharge intensity, industrial waste gas emission intensity, water consumption per unit of industrial added value, highway density, and energy consumption per unit of industrial added value, which are the root factors affecting IDQ. This study can provide a theoretical basis and reference for the promotion of high-quality industrial development.

Supercapacitor characteristics of MoS2 and MoOx coated onto honeycomb-shaped carbon nanotubes

Two-dimensional molybdenum disulfide (MoS2) with multilayer hierarchical structures is generally considered to be able to provide more active sites and shorter diffusion channels for electrolytes, which make them extremely suitable for supercapacitor applications. Nevertheless, the MoS2 poor conductivity and rare surface area are the major technical obstacles. Herein, we demonstrated a honeycomb basis using carbon nanotubes (CNTs). The honeycomb-shaped carbon skeleton provides a relatively larger surface area to store more ions with a more stable and stronger structure to maintain long-term electrochemical tests. During MoS2 fabrication, MoOx was also synthesized onto CNTs. MoOx influenced the electrochemical test results. Thermal annealing was conducted to remove the MoOx attachments to assure the optimal capacitance value. For the particular composite honeycomb structure (MoS2/CNTs) used in this research, the specific capacitance increased from 4.7 F/g (CNTs) to 75 F/g (MoS2 + MoOx/CNTs), measured using cyclic voltammetry measurements. The specific capacitance further reached 425 F/g using thermal annealing at optimal temperature, 700 °C. The designed electrode materials demonstrated excellent electrochemical characteristics and had great potential for future electrochemical applications.

Hierarchical construction of Co3S4 nanosheet coated by 2D multi-layer MoS2 as an electrode for high performance supercapacitor

Two-dimensional materials with multi-layer hierarchical structures are generally accepted to be able to provide more active sites and shorter electrolyte diffusion channels, which are highly desired for application in supercapacitors. Nonetheless, their uncontrollability and inaccurate phase composition of elaborate nanostructures remain amajortechnologicalhurdle. To address the issue, an exquisite layered structure of Co3S4 nanosheet coated by 2D multi-layer MoS2 (Co3S4@MoS2) is constructed through one-step sulfidation, using carbonized leaf-like Co-ZIF (Co-ZIF-L) nanosheet arrays as a precursor. The carbon skeleton formed by carbonization of Co-ZIF-L effectively prevents structural collapse, especially to ensures the cycle stability. Meanwhile, the nanosheet arrays reduces the agglomeration and promotes the multi-layer 2D MoS2 simultaneously. The as-prepared Co3S4@MoS2 exhibits an appreciable specific capacity (576 C g−1 at 1 A g−1). The Co3S4@MoS2// reduced graphene oxide (RGO) asymmetric supercapacitor shows an energy density of 53.96 Wh kg−1 at a power density of 887.01 W kg−1, and outstanding cycle life with the 94.5% of capacity retention after 10,000 cycles. Such excellent performance is attributed to the rational structure, and the multi-layer 2D MoS2 improves the reaction kinetics of the electrode. Thestrategypresentedhereofferspromisingopportunitiesinimproving electrode performance of energy storage devices.

Hierarchical Array Design Strategy Composed of Irregular and Overlapped Subarrays in Large-Scale Planar Array

Effective cost reduction is the primary task of the commercialization of phased array antenna technology. In this communication, a novel array structure composed of irregular and overlapped subarrays is proposed. The advantages of two kinds of subarrays are integrated to achieve the performance requirements while reducing the cost. The basic idea is departing the array into a multilayer hierarchical structure. The first layer is subtly designed by irregular subarray tiles. In this case, the number of active devices can be effectively reduced, thereby reducing the cost. The second layer is an overlapped subarray structure which is able to ensure scanning performance. Both limited field of view and wideband wide-angle scanning applications are discussed to show the compatibility of the proposed structure. The effectiveness is verified by various numerical results.

Three-Dimensional (3D) Nanostructured Skeleton Substrate Composed of Hollow Carbon Fiber/Carbon Nanosheet/ZnO for Stable Lithium Anode.

The practical applications of Li metal batteries (LMBs) have long been limited by the obstacles of low Coulombic efficiency (CE) and formation of dendrites on Li metal electrode. Herein, we demonstrated the synthesis of a novel three-dimensional (3D) nanostructured skeleton substrate composed of nitrogen-doped hollow carbon fiber/carbon nanosheets/ZnO (NHCF/CN/ZnO) using 2-methylimidazole (2-MIZ)-coated 3D cloth as a scaffold. The mechanism of formation of this novel hierarchical structure was investigated. The multilayered hierarchical structure and abundant lithiophilic nucleation sites of the substrate provide a stable environment for the deposition and stripping of lithium metal, thus preventing the generation of lithium dendrites. Consequently, the lithium anode based on the NHCF/CN/ZnO current collector demonstrated an excellent Coulombic efficiency of 96.47% after 400 cycles at 0.5 mA cm-2. The prepared NHCF/CN/ZnO/Li electrode also showed outstanding cycling performance of over 800 h and an ultralow voltage hysteresis of less than 30 mV in a symmetric cell at 5 mA cm-2 and 5 mAh cm-2. Even at a high loading of the cathode with 10.4 mg cm-2, the full cell of NHCF/CN/ZnO/Li anode with LiFePO4 can also work very well. Our work offers a path toward the facial preparation of 3D hierarchical structure for high-performance lithium metal batteries.

Parts beget parts: Bootstrapping hierarchical object representations through visual statistical learning

Previous research has shown that humans are able to acquire statistical regularities among shape parts that form various spatial configurations, via exposure to these configurations without any task or feedback. The present study extends this approach of visual statistical learning to examine whether prior knowledge of parts, acquired in a separate learning context, facilitates acquisition of multi-layer hierarchical representations of objects. After participants had learned to encode a shape-pair as a chunk into memory, they viewed cluttered scenes containing multiple shape chunks. One of the larger configurations was constructed by combining the learned shape-pair with an unfamiliar, complementary shape-pair. Although the complementary shape-pair had never been presented separately during learning, it was remembered better than other shape pairs that were parts of larger configurations. The greater perceived familiarity of the complementary shape-pair depended on the encoding strength of the previously learned shape-pair. This “parts-beget-parts” effect suggests that statistical learning, in combination with prior knowledge, can represent objects as a coherent whole and also as a spatial configuration of parts by bootstrapping multi-layer hierarchical structures.

Development of an approach to managing dry fruit supply chains using expert systems

The paper outlines an approach to the management of dry fruit supply chains (DSC) using expert systems (ES), which implies modernization of the concept of supply chain management by complementing it with knowledge-oriented tools of decision-making support. It was shown that the technologies of ES development existing in engineering are not effective in organizing a unified information space within the DSC. In the framework of this approach, we considered the methodical approach to decomposition of the general problem of business processes management in the DSC into a series of interconnected functional sub-problems and the procedure of synthesis of a typical decision-making support unit (DMSU) by the DSC participants in the form of ES. The essence of the approach is to represent the DSC management process as a multi-layered hierarchical structure of problems, which can be implemented by a totality of interconnected typical DMSU by correspondent DSC participants. At the same time, a specialized ES shell was developed for each type of DMSU. Application of the approach under discussion will in practice ensure the homogeneity of the general information space of the DSC due to: clear positioning of each DMSU in the general management structure; widespread use of typical solutions in the synthesis of information support tools for DSC participants. The effectiveness of the described approach is shown using the example of implementation of the ES shell for the problem of choosing a rational route of delivery of dried fruit batches from foreign suppliers to wholesalers in Ukraine. The results of the study can be used by logistics companies in the formation of a rational route for the delivery of a batch of goods for various purposes from foreign suppliers to a focus company

Differentiation of bMSCs on Biocompatible, Biodegradable, and Biomimetic Scaffolds for Largely Defected Tissue Repair.

Biocompatible, biodegradable, and biomimetic scaffolds in combination with stem cells are of great importance for tissue engineering, especially the repairing and regeneration of defected organs. As a case in point, esophageal diseases have become serious clinical problems because of the poor self-repairing ability of the organ. It is crucial to prepare artificial replacements with biological function for serious lesions of the esophagus. However, the pH value, mechanical strength, thickness, and other physical conditions are very different in different organs or different parts of the same organ, which pose high difficulty for successful tissue engineering. In this work, bone marrow mesenchymal stem cells (bMSCs) were isolated from rabbits and transfected with green fluorescent protein (GFP) to follow their capabilities of growth, stemness, and differentiation in ex vivo culture. These bMSCs were seeded on biocompatible, biodegradable, and biomimetic scaffolds to detect the tissue regenerative capability of the esophagus with multilayer hierarchical structure. According to the esophageal bilayer muscle architecture, we designed discontinuous and continuous microchannel patterned scaffolds with medical level polyurethane (PU) as the matrix to guide the inner-circular and outer-longitudinal muscle growth. The gap on the discontinuous walls not only helped cells to communicate with each other but also assisted cells to infiltrate through the gap and grew into the inner circular muscle. The graft of silk fibroin on the scaffold surface using the aminolysis and glutaraldehyde cross-linking method enhanced the substrate's hydrophilicity and biocompatibility. Mucosa-submucosa tissue of rabbit's esophagus was decellularized to obtain the extracellular matrix (ECM) and implanted in situ after recellularizing with bMSCs to repair the partially defected rabbits' esophagus. On the basis of both in vitro and in vivo results, we concluded that esophagus regeneration was promoted by the differentiation of bMSCs on the biocompatible, biodegradable, and biomimetic scaffolds, starting from tissue "niches", to repair the largely defected esophagus, which paves the way for tissue engineering and defected organ treatments.

Модель педагогического предупреждения виктимизации и насилия над подростками

The study describes the educational model preventing victimization of adolescents affected by violence which is implemented in the secondary school. This model has a multi-layered hierarchical structure consisting of the following units: goals and objectives; evaluation criteria; content; design and technology; evaluation and correction. The focus of the model is on the nonviolent interaction between victimized adolescents and adults. It involves pedagogical interaction providing effective cooperation without coercion and punishment. Its implementation demonstrated a positive effect because of the safe living and school environment created for minors and aimed at the personal development of victimized adolescents, the non-influence of victimization factors, as well as purposeful dealing with teachers and pedagogical education of parents. The model developed by the author to prevent victimization and violence against adolescents allows one to achieve the goal, meet the research challenges in an integrated manner, improve considerably the qualitative and quantitative characteristics of this process, and reduce the level of victimization of abused minors as well.

Synthesis of organosiloxane-coated SiO2/CeO2 with multilayered hierarchical structure and its application in optical diffusers

In this study, a simple, convenient and green approach for the preparation of organosiloxane-coated SiO2/CeO2 (SiO2/CeO2/poly(VTMS)) with multilayered hierarchical structure is demonstrated by consecutive surface cerium deposition and organosiloxane grafting on the bare silica spheres. The results of the UV–Vis spectrum and photoluminescence analysis suggest that the fillers may be potentially applied in UV absorbers and bioimaging materials. Moreover, the optical diffusers based on the multilayered spheres can be prepared via a solvent-free UV curing process and exhibit enhanced properties like suitable light transmittance, good diffusion capacity and low-incident angle dependence, which are critical for the optical diffusers. In addition, when the concentration of the fillers was 15 wt%, the optical diffusers presented superior light-diffusing properties among all the as-prepared samples. Thus, the films based on the SiO2/CeO2/poly(VTMS) with multilayered hierarchical structure may open up new possibilities in applications as multifunctional light diffusion films in liquid crystal displays.