Specific Structure Research Articles

Adsorption mechanism and interactions of coal particles modified with a novel hyperbranched dispersant

This account, a hyperbranched dispersant (Es-SAF-DBM-PSS) was assembled with the skeleton of Es-SAF-DBM (the functional modification of hydroquinone-based sulfonated acetone formaldehyde (SAF)) and numbers of linear polystyrene sodium sulfonate (PSS) chains by single electron transfer living radical polymerization (SET-LRP) in the system of PhBr2m4/Cu wire/PMDETA. The structure of the synthesized Es-SAF-DBM-PSS was detected by FTIR, 1H NMR, XPS, UV and GPC. Series of tests about the polymerization kinetics of Es-SAF-DBM-PSS were executed. Effects of temperatures and initiator concentration on the apparent polymerization rate were investigated, the results showed the low activation energy and higher initiation rate fitted the characteristic of SET-LRP. The rheological behaviors of Es-SAF-DBM-PSS as dispersant applied to coal water slurry (CWS) were tested. The following results were found as expected: the best usage of Es-SAF-DBM-PSS was only 0.3%, maximum coal content reached 63.7%, the viscosity dropped as low as 1000mPa·s. And the penetration ratio of slurry mixed with Es-SAF-DBM-PSS was still 100% even after 35days. Adsorption mechanism and interparticle interactions of coal particles modified with Es-SAF-DBM-PSS were investigated by Langmuir equation, dynamic equations and extended Derjaguin-Landau-Verwey-Overbeek (eDLVO) theory, the results showed the excellent dispersion and stability performance of Es-SAF-DBM-PSS were mainly related to the specific hyperbranched structure.

A crown-ether-enabled eutectic electrolyte for ultra-high temperature lithium metal batteries

Lithium metal batteries (LMBs) are generally restricted to operating below 60 °C and not suitable for high-temperature applications due to their thermally susceptible carbonate electrolytes. Deep eutectic electrolytes (DEE) with strong supramolecular interactions are a new emerging type of liquid-state ionic conductors, and here we present a novel DEE—which is composed of 18-crown-6 ether (18C6) and lithium difluoro(oxalate)borate (LiDFOB)—to extend the working temperature up to 150 °C. Via combined physiochemical and theoretical characterizations, it is identified that such high thermotolerance is a result of specific solvation structure of Li(18C6)4DFOB with multiple Li–O interactions. Moreover, our newly developed DEE triggers the formation of a B/F-rich solid electrolyte interphase, contributing to superior thermal stability and enhanced compatibility with Li-metal anodes. Consequently, Li|DEE|LiFePO4 cell exhibits great tolerance to extremely high temperatures with a capacity reversibility of 83 % after 250 cycles at 120 °C. Even at 150 °C, the cell can retain 77 % of the initial capacity (105 mAh g−1) after 100 cycles. To our knowledge, the DEE is the first liquid electrolyte for LMBs working at unprecedented high-temperature. This work opens intriguing perspectives to design novel electrolytes for demanded performance of LMBs across a wide temperature range.

A comparative analysis of soil physicochemical properties and microbial community structure among four shelterbelt species in the northeast China plain.

The focal point of this study lies in the implementation of a controlled experiment conducted under field conditions. In this experiment, we deliberately selected four shelterbelts within the same field, characterized by identical planting density, and planting year. This deliberate selection effectively mitigated the potential impact of extraneous factors on the three microbiomes, thereby enhancing the reliability and validity of our findings.

Preparation of transition metal oxide mixed graphene electrode materials and its application in supercapacitors

The increasing prevalence of wearable electronic devices in contemporary society has led to heightened expectations for energy storage devices. These expectations encompass not only high power density and energy density, but also robust stability and resistance to bending. Consequently, the design and development of supercapacitors with versatile functionalities has emerged as a prominent area of research. The electrode material, which is one of the elements that can have the biggest impact on the operation of supercapacitors, has been the subject of numerous scientific advancements over the years. One promising approach is the combination of transition metal oxide and graphene material composite. By conducting a comprehensive review of relevant literature, this study synthesizes preparation methods from multiple sources, integrates the benefits of multiple technologies to develop a novel preparation method utilizing ultrasonic shock and the two-step interface self-assembly method, and compares the physical and chemical properties of different transition metal oxide mixed graphene electrode materials and their application in supercapacitors. In conclusion, the preparation methods of transition metal oxide mixed graphene electrode materials typically control their microscopic morphology in order to support structure, agglomeration, and spalling reduction, thereby enhancing the specific capacitance and cycle stability of supercapacitors and achieving the desired result of increasing specific surface area and support structure.

A Dual-Branch Speech Enhancement Model with Harmonic Repair

Recent speech enhancement studies have mostly focused on completely separating noise from human voices. Due to the lack of specific structures for harmonic fitting in previous studies and the limitations of the traditional convolutional receptive field, there is an inevitable decline in the auditory quality of the enhanced speech, leading to a decrease in the performance of subsequent tasks such as speech recognition and speaker identification. To address these problems, this paper proposes a Harmonic Repair Large Frame enhancement model, called HRLF-Net, that uses a harmonic repair network for denoising, followed by a real-imaginary dual branch structure for restoration. This approach fully utilizes the harmonic overtones to match the original harmonic distribution of speech. In the subsequent branch process, it restores the speech to specifically optimize its auditory quality to the human ear. Experiments show that under HRLF-Net, the intelligibility and quality of speech are significantly improved, and harmonic information is effectively restored.

Locational enrichment of low-abundance analytes through force-environment-modulation microsystem with ion concentration polarization

Ion concentration polarization (ICP) effect in micro-nanofluidic devices can concentrate low-concentration molecules. In this paper, we proposed a novel ICP-based enrichment system with horizontal barriers that adjust the force environment of charged particles, to achieve specific locational analytes enrichment. Mechanism of analyte enrichment through force modulation is revealed through numerical simulation using microchannels with varied channels widths, which is further validated through physical experiment. Overall, a specific target-oriented structure and load regulation method was proposed, under which the low-abundance analytes could be locationally concentrated by ∼ 4000 times. This study is expected to develop an innovative method for specifically locational ion enrichment in terms of scientific principles, providing theoretical and technical support for concentration and detection of charged substances in both research and industry such as biology, environment, chemistry studies, etc.

Stability and Change of Personal Value in South Korean Adolescents: The Effect of Social Networks

Adolescence is a period of life when an individual’s values become differentiated. Moreover, social networks undergo changes throughout the school years, making this a suitable research area for confirming the effect of network composition on the formation of human values. In this study, we examined the stability and change of values among Korean adolescents, while assessing the influence of one’s social network on the importance and change of values. Our findings reveal that the importance of conservation values among Korean teenagers increases during mid-late adolescence, and that the self-transcendence value is a settled disposition. We argue that these changes arise from a specific social structure and culture in South Korea, where children assume adult roles at an earlier age. In addition, the structural equation model revealed that social support enhances individuals’ prosocial and post-materialistic values. Consequently, this research significantly contributes to the academic discourse by confirming the stability and changes in personal values during adolescence, while also considering the impact of social factors.

Reliability Evaluation of a Dynamic-Pressure Mechanical Seal Based on Liquid Film Vaporization Phase Transition

Aiming at the problem of researching the reliability of dynamic-pressure mechanical seals, this paper proposes a reliability evaluation method for dynamic-pressure mechanical seals based on the Monte Carlo method. Based on the influence of the mass transfer coefficient on vaporization phase transition, a liquid film vaporization model of a hydrodynamic mechanical seal’s end face is established, and the working condition parameters and groove structure parameters are designed using the experimental design method. The vaporization characteristics of the liquid film under various parameters are analyzed, and the functional functions of the vaporization characteristics are obtained by fitting. Combined with the maximum vapor phase volume fraction when the dynamic-pressure mechanical seal changes from the liquid miscible phase to the vapor miscible phase, the limit state equation of the vapor phase volume fraction is obtained. Finally, based on the Monte Carlo simulation method, the sealing reliability under specific groove structure parameters is calculated. Our research shows that this method has practicability and effectiveness for the reliability evaluation of mechanical seals with different working conditions and different groove structures.

Biofabrication's Contribution to the Evolution of Cultured Meat.

Cultured Meat (CM) is a growing field in cellular agriculture, driven by the environmental impact of conventional meat production, which contributes to climate change and occupies ≈70% of arable land. As demand for meat alternatives rises, research in this area expands. CM production relies on tissue engineering techniques, where a limited number of animal cells are cultured in vitro and processed to create meat-like tissue comprising muscle and adipose components. Currently, CM is primarily produced on a small scale in pilot facilities. Producing a large cell mass based on suitable cell sources and bioreactors remains challenging. Advanced manufacturing methods and innovative materials are required to subsequently process this cell mass into CM products on a large scale. Consequently, CM is closely linked with biofabrication, a suite of technologies for precisely arranging cellular aggregates and cell-material composites to construct specific structures, often using robotics. This review provides insights into contemporary biomedical biofabrication technologies, focusing on significant advancements in muscle and adipose tissue biofabrication for CM production. Novel materials for biofabricating CM are also discussed, emphasizing their edibility and incorporation of healthful components. Finally, initial studies on biofabricated CM are examined, addressing current limitations and future challenges for large-scale production.

High-Throughput Ensemble-Learning-Driven Band Gap Prediction of Double Perovskites Solar Cells Absorber

Perovskite materials have attracted much attention in recent years due to their high performance, especially in the field of photovoltaics. However, the dark side of these materials is their poor stability, which poses a huge challenge to their practical applications. Double perovskite compounds, on the other hand, can show more stability as a result of their specific structure. One of the key properties of both perovskite and double perovskite is their tunable band gap, which can be determined using different techniques. Density functional theory (DFT), for instance, offers the potential to intelligently direct experimental investigation activities and predict various properties, including band gap. In reality, however, it is still difficult to anticipate the energy band gap from first principles, and accurate results often require more expensive methods such as hybrid functional or GW methods. In this paper, we present our development of high-throughput supervised ensemble learning-based methods: random forest, XGBoost, and Light GBM using a database of 1306 double perovskites materials to predict the energy band gap. Based on elemental properties, characteristics have been vectorized from chemical compositions. Our findings demonstrate the efficiency of ensemble learning methods and imply that scientists would benefit from recently employed methods in materials informatics.

Three-dimensional measurements of symmetry for the mandibular ramus

BackgroundThe study examines a sample of patients presenting for viscerocranial computer tomography that does not display any apparent signs of asymmetry, assesses the three-dimensional congruency of the mandibular ramus, and focuses on differences in age and gender. MethodsThis cross-sectional cohort study screened viscerocranial CT data of patients without deformation or developmental anomalies. Segmentations were obtained from the left and right sides and superimposed according to the best-fit alignment. Comparisons were made to evaluate three-dimensional congruency and compared between subgroups according to age and gender. ResultsTwo hundred and sixty-eight patients were screened, and one hundred patients met the inclusion criteria. There were no statistical differences between the left and right sides of the mandibular ramus. Also, there were no differences between the subgroups. The overall root mean square was 0.75 ± 0.15 mm, and the mean absolute distance from the mean was 0.54 ± 0.10 mm. ConclusionThe mean difference was less than one millimetre, far below the two-millimetre distance described in the literature that defines relative symmetry. Our study population displays a high degree of three-dimensional congruency.Our findings help to understand that there is sufficient three-dimensional congruency of the mandibular ramus, thus contributing to facilitating CAD-CAM-based procedures based on symmetry for this specific anatomic structure.

Training of a deep learning based digital subtraction angiography method using synthetic data.

Digital subtraction angiography (DSA) is a fluoroscopy method primarily used for the diagnosis of cardiovascular diseases (CVDs). Deep learning-based DSA (DDSA) is developed to extract DSA-like images directly from fluoroscopic images, which helps in saving dose while improving image quality. It can also be applied where C-arm or patient motion is present and conventional DSA cannot be applied. However, due to the lack of clinical training data and unavoidable artifacts in DSA targets, current DDSA models still cannot satisfactorily display specific structures, nor can they predict noise-freeimages. In this study, we propose a strategy for producing abundant synthetic DSA image pairs in which synthetic DSA targets are free of typical artifacts and noise commonly found in conventional DSA targets for DDSA modeltraining. More than 7,000 forward-projected computed tomography (CT) images and more than 25,000 synthetic vascular projection images were employed to create contrast-enhanced fluoroscopic images and corresponding DSA images, which were utilized as DSA image pairs for training of the DDSA networks. The CTprojection images and vascular projection images were generated from eight whole-body CT scans and 1,584 3D vascular skeletons, respectively. All vessel skeletons were generated with stochastic Lindenmayer systems. We trained DDSA models on this synthetic dataset and compared them to the trainings on a clinical DSA dataset, which contains nearly 4,000 fluoroscopic x-ray images obtained from different models ofC-arms. We evaluated DDSA models on clinical fluoroscopic data of different anatomies, including the leg, abdomen, and heart. The results on leg data showed for different methods that training on synthetic data performed similarly and sometimes outperformed training on clinical data. The results on abdomen and cardiac data demonstrated that models trained on synthetic data were able to extract clearer DSA-like images than conventional DSA and models trained on clinical data. The models trained on synthetic data consistently outperformed their clinical data counterparts, achieving higher scores in the quantitative evaluation of peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) metrics for DDSA images, as well as accuracy, precision, and Dice scores for segmentation of the DDSAimages. We proposed an approach to train DDSA networks with synthetic DSA image pairs and extract DSA-like images from contrast-enhanced x-ray images directly. This is a potential tool to aid indiagnosis.

Light field control and automatic identification experimental system for physical impairment of glass samples

In this paper, we firstly propose a novel identification method for physical impairment of glass spheres samples based on the light field control. An identification simulation subsystem based on the finite difference time domain (FDTD) method to numerically study the light field control is proposed. The numerical results are consistent with the experimental data. On the basis of above numerical investigation, an automaticidentification experimental system for physical impairment of glass samples based on the Cortex-M3 is proposed. The relevanthardware circuitdesign,main program design, subprogram design of circuit modules, system specific framework structure and corresponding component design,andmaininterface between the master computer and slave microcontroller are accomplished. An automaticidentification experimental system for physical impairment of glass samples with automatic feeding subsystem and automatic sorting subsystem is achieved.

A Survey on Implementing Augmented Reality in Learning Data Structures

Data structures are fundamental building blocks of computer science, but their abstract nature can pose challenges for students. This research explores the potential of Augmented Reality (AR) to enhance the learning of data structures. The paper describes the development and analysis of an AR-based learning system for specific data structures. The system utilizes data visualization and interactive manipulation through 3D models and animations to explain how AR features aid in learning. The results were compelling, demonstrating significant improvement in both understanding and performance among students utilizing the AR tool. In general, this study indicates that AR can function as a valuable tool for studying data structures. This study not only highlights the effectiveness of AR in demonstrating data structures but also paves the way for future advancements in computer science education, ultimately leading to a more easily accessible and engaging learning environment for all.

Elastic programmable properties and dynamic dissipation of gradient unstable structures

Metamaterials derive promising properties mainly from an internal micromechanical mechanism, rather than their chemical composition. Many interesting mechanical behaviors can be obtained by orderly assembling buckling elements. Elastic programmable properties, corresponding potential energy landscape and dynamic dissipation mechanism of elastic beam structures are studied in detail. To accomplish this work, a combination of theoretical models and extensive numerical calculations are applied to investigate a single element as well as homogeneous and gradient structures. This comprehensive investigation not only provides insights into the complex internal buckling behaviors and mechanisms of a specific unstable structure but also establishes conclusions that are applicable to other unstable structures having similar buckling behaviors. The potential energy of a serial combination of unstable elements is extremely wiggly, enabling multiple equilibrium configurations and resulting in multistable transformations and energy dissipation with elastic deformation and loading timescale independence. To the best of our knowledge, the most of programming properties investigated in this paper, the complex energy landscape, the deformation of internal elements, and programmable dynamic responses of gradient unstable structures have not been reported in previous papers.

Precise selection and separation of ribavirin by nanoconfined imprinted MOFs membrane

Metal-organic frameworks (MOFs) are highly tunable materials with potential as porous media in membrane separations. However, traditional MOFs are usually not specific and selective. Here, we demonstrate a nanocomposite molecularly imprinted MOFs membrane material that can selectively adsorb and separate specific molecules. We demonstrated this adsorption-separation mechanism by introducing ribavirin molecules into multicomponent MOFs by molecular imprinting strategy and performing permeation and dynamic permeation tests. Due to the previously formed nanocages with a specific structure inside the MOFs, combined with the synergistic effect of the subsequent secondary imprinting, excellent selectivity (more than 6) and effective adsorption (46.46 mg g−1) were displayed by the obtained imprinted membrane. The stability of the membrane was measured by the process of dynamic osmosis, and the results showed that the membrane always had a large factor of separation (greater than 7). The experimental results and conclusions of this paper provide new theoretical and practical support for solving the key scientific issues of the “trade-off” effect between the permeation flux and permeation selectivity of template molecules in the traditional molecularly imprinted membranes (MIMs) osmotic separation process.

Sustainable political commitment is necessary for institutionalizing community participation in health policy-making: Insights from Iran

BackgroundCommunity participation is currently utilized as a national strategy to promote public health and mitigate health inequalities across the world. While community participation is acknowledged as a civic right in the Constitution of Iran and other related upstream documents, the government has typically failed in translating, integrating and implementing community participation in health system policy. The present study was conducted to determine the level of public voice consideration within the health policy in Iran and address fundamental interventions required to promote the public voice in the context of Islamic Republic of Iran (IRI). This study has originality because there is no study that addresses the requirements of institutionalizing community participation especially in low-middle-income countries, so Iran’s experience can be useful for other countries.MethodsMethodologically, this study utilized a multi-method and multi-strand sequential research design, including qualitative, comparative and documentary studies. In the first phase, the current level of community participation in the health policy cycle of Iran was identified using the International Association for Public Participation (IAP2) spectrum. In the second phase, a comparative study was designed to identify relevant interventions to promote the community participation level in the selected countries under study. In the third phase, a qualitative study was conducted to address the barriers, facilitators and strategies for improving the level of public participation. Accordingly, appropriate interventions and policy options were recommended. Interventions were reviewed in a policy dialogue with policy-makers and community representatives, and their effectiveness, applicability and practical feasibility were evaluated.ResultsBased on the IAP2 spectrum, the level of community participation in the health policy-making process is non-participation, while empowerment is set at the highest level in the upstream documents. Moreover, capacity-building, demand, mobilization of the local population, provision of resources and setting a specific structure were found to be among the key interventions to improve the level of community participation in Iran’s health sector. More importantly, “political will for action” was identified as the driving force for implementing the necessary health interventions.ConclusionsTo sum up, a paradigm shift in the governing social, economic and political philosophy; establishing a real-world and moral dialogue and communication between the government and the society; identifying and managing the conflicts of interest in the leading stockholders of the healthcare system; and, more importantly, maintaining a stable political will for action are integral to promote and institutionalize participatory governance in the health sector of Iran. All of the above will lead us to scheme, implement and institutionalize suitable interventions for participatory governance in health and medicine.

Cell contacts and pericellular matrix in the Xenopus gastrula chordamesoderm.

Convergent extension of the chordamesoderm is the best-examined gastrulation movement in Xenopus. Here we study general features of cell-cell contacts in this tissue by combining depletion of adhesion factors C-cadherin, Syndecan-4, fibronectin, and hyaluronic acid, the analysis of respective contact width spectra and contact angles, and La3+ staining of the pericellular matrix. We provide evidence that like in other gastrula tissues, cell-cell adhesion in the chordamesoderm is largely mediated by different types of pericellular matrix. Specific glycocalyx structures previously identified in Xenopus gastrula tissues are absent in chordamesoderm but other contact types like 10-20 nm wide La3+ stained structures are present instead. Knockdown of any of the adhesion factors reduces the abundance of cell contacts but not the average relative adhesiveness of the remaining ones: a decrease of adhesiveness at low contact widths is compensated by an increase of contact widths and an increase of adhesiveness proportional to width. From the adhesiveness-width relationship, we derive a model of chordamesoderm cell adhesion that involves the interdigitation of distinct pericellular matrix units. Quantitative description of pericellular matrix deployment suggests that reduced contact abundance upon adhesion factor depletion is correlated with excessive accumulation of matrix material in non-adhesive gaps and the loss of some contact types.

Magnetic properties of ferro-antiferromagnetic spin triangle chain

Frustrated spin- 12 model consisting of a linear chain of triangles with ferro (F)- and antiferromagnetic interactions connected by ferromagnetic interactions (triangles chain) is studied. The ground state phase diagram depending on the interaction ratios consists of ferromagnetic, two ferrimagnetic and singlet phases. The magnetic properties in these phases are analyzed both analytically and numerically. We show that in some regions of the singlet phase the magnetization curves have magnetization plateau and magnetization jumps. We study the thermodynamics and its relation to the specific structure of the excitation spectrum of the triangle chain.

Study on the Influence and Optimization Design of Viscous Damper Parameters on the Damping Efficiency of Frame Shear Wall Structure

This study investigates the influence of viscous damper parameters on the damping efficiency of frame shear wall structures. Taking a specific frame shear wall structure as the background, a three-dimensional finite element model is established using a nonlinear dynamic time–history analysis method. The damping ratio, reduction in vertex displacement, reduction in base shear, and inter-story drift utilization rate are selected as the damping performance indicators. Firstly, a sensitivity analysis is conducted to study the influence of different viscous damper parameters on these indicators. Then, the relationship models between the viscous damper parameters and the indicators are fitted using the response surface method, and the fitting effect is evaluated through an F-test and determination coefficient R2. Finally, an objective function based on key damping performance indicators is established to solve for the optimal parameters. The results show that the traditional sensitivity analysis method is unable to comprehensively consider the combined effects of different damping efficiency indicators. The response surface method has high fitting accuracy and good predictability and can serve as an optimization model. Considering the stiffness of supporting components matched with the viscous damper parameters, the feasibility of the optimal damping parameters is demonstrated from an engineering application perspective. A simple and easy-to-operate damping design flowchart is proposed, providing important guidance and reference for designers in frame shear wall structure damping design in the future.