bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the Degradation of Core-Shell Nanogels Using Asymmetrical Flow Field Flow Fractionation
Authors: Niezabitowska Edyta , Gray Dominic M. , Gallardo-Toledo Eduardo , Owen Andrew , Rannard Steve P. , McDonald Tom O.
Published: June 2023

Nanogels are candidates for biomedical applications, and core-shell nanogels offer the potential to tune thermoresponsive behaviour with the capacity for extensive degradation. These properties were achieved by the combination of a core of poly(N-isopropylmethacrylamide) and a shell of poly(N-isopropylacrylamide), both crosslinked with the degradable crosslinker N,N′-bis(acryloyl)cystamine. In this work, the degradation behaviour of these nanogels was characterised using asymmetric flow field flow fractionation coupled with multi-angle and dynamic light scattering. By monitoring the degradation products of the nanogels in real-time, it was possible to identify three distinct stages of degradation: nanogel swelling, nanogel fragmentation, and nanogel fragment degradation. The results indicate that the core-shell nanogels degrade slower than their non-core-shell counterparts, possibly due to a higher degree of self-crosslinking reactions occurring in the shell. The majority of the degradation products had molecule weights below 10 kDa, which suggests that they may be cleared through the kidneys. This study provides important insights into the design and characterisation of degradable nanogels for biomedical applications, highlighting the need for accurate characterisation techniques to measure the potential biological impact of nanogel degradation products.
Neuroprotective Effect of Platinum Nanoparticles Is Not Associated with Their Accumulation in the Brain of Rats
Authors: Filippov Alexander Gennadievich , Alexandrin Valery Vasil’evich , Ivanov Alexander Vladimirovich , Paltsyn Alexander Alexandrovich , Sviridkina Nadezhda Borisovna , Virus Edward Danielevich , Bulgakova Polina Olegovna , Burmiy Joanna Petrovna , Kubatiev Aslan Amirkhanovich
Published: June 2023

Platinum nanoparticles (nPts) have neuroprotective/antioxidant properties, but the mechanisms of their action in cerebrovascular disease remain unclear. We investigated the brain bioavailability of nPts and their effects on brain damage, cerebral blood flow (CBF), and development of brain and systemic oxidative stress (OS) in a model of cerebral ischemia (hemorrhage + temporary bilateral common carotid artery occlusion, tBCAO) in rats. The nPts (0.04 g/L, 3 ± 1 nm diameter) were administered to rats (N = 19) intraperitoneally at the start of blood reperfusion. Measurement of CBF via laser Doppler flowmetry revealed that the nPts caused a rapid attenuation of postischemic hypoperfusion. The nPts attenuated the apoptosis of hippocampal neurons, the decrease in reduced aminothiols level in plasma, and the glutathione redox status in the brain, which were induced by tBCAO. The content of Pt in the brain was extremely low (≤1 ng/g). Thus, nPts, despite the extremely low brain bioavailability, can attenuate the development of brain OS, CBF dysregulation, and neuronal apoptosis. This may indicate that the neuroprotective effects of nPts are due to indirect mechanisms rather than direct activity in the brain tissue. Research on such mechanisms may offer a promising trend in the treatment of acute disorders of CBF.
The Study of the Failure Envelopes of Hollow Shaft Single-Plate Helical Piles in Clay
Authors: Wang Le , Zhao Xing , Zhang Puyang , Ding Hongyan , Guo Yaohua , Tian Yinghui , Liu Mengmeng
Published: June 2023

Helical piles are utilized worldwide as foundations for onshore infrastructure, providing fast installation and high capacity. Their unique advantages have led to their potential as an alternative to monopile foundations for offshore wind turbines. One challenge in their service life is dealing with combined loading caused by wind, waves, current, and the weight of the structure itself. While research has focused on helical piles’ capacity for uniaxial tensile loads, there is limited knowledge regarding their performance under combined loads. This study used FEM analysis to investigate the impact of aspects such as helix-to-shaft diameter ratios and helix position on the capacity and failure mechanisms of hollow shaft single-plate helical piles in clay. With 561 analysis cases under both uniaxial and combined loading, failure envelopes were evaluated for various helix-to-shaft diameter ratios and positions. The study revealed a linear positive correlation between helix-to-shaft diameter aspect ratios and load-bearing ability, while the effect of helix positioning on failure envelopes was more complex and nonlinear. The outcomes from this comprehensive analysis enabled the development of a formula to predict the bearing capacity of helical anchors under combined loading.
An Emergency Port Decision-Making Method for Maritime Accidents in Arctic Waters
Authors: Wang Ting , Ma Xiaoxue , Ma Laihao , Zhao Yulan
Published: June 2023

The complex and variable hydro-meteorological conditions in Arctic waters and scattered and limited port infrastructures pose a great threat and challenge to Arctic emergency search and rescue. It is crucial to determine an available and effective emergency port for rescue in the event of a maritime accident occurring in Arctic waters. In the present study, a directed-weighted emergency port network consisting of maritime accident nodes and port nodes for maritime accident-prone areas in Arctic waters is developed based on complex network theory. For this, the maritime accident nodes are identified by using a K-means clustering algorithm based on historical accident data; the port nodes are determined by screening of the port location and scale; the weights for edges between accident nodes and port nodes are characterized in terms of ERT (emergency rescue time) and PEC (port emergency capacity), and the PECs for different emergency ports along Arctic waters are acquired by entropy-weighted TOPSIS. With the developed emergency port network, the topological properties associated with the accident nodes, port nodes, and the edge weights between accident nodes and port nodes are analyzed. What is more, the emergency ports for each maritime accident point occurring in Arctic waters are obtained and ranked.
A Method for Inverting Shallow Sea Acoustic Parameters Based on the Backward Feedback Neural Network Model
Authors: Zhu Hanhao , Cui Zhiqiang , Liu Jia , Jiang Shenghui , Liu Xu , Wang Jiahui
Published: June 2023

In response to the drawbacks of low efficiency, cumbersome calculation, and easy-to-fall local optimal solutions in existing shallow water acoustic parameters inversion research, this paper proposes a shallow water acoustic parameters inversion method based on a feedback (BP) neural network model. Firstly, the theoretically predicted values of the shallow water sound pressure field are obtained through the fast field method (FFM). Secondly, a relationship model between the predicted sound pressure field and the inversion of ground sound parameter values is established based on the BP neural network model. Finally, the measured sound pressure field data are brought into the neural network model to obtain the inversion results. The application results of the method indicate that, compared to the classical simulated annealing (SA) algorithm, the BP neural network model converts the data-matching process of the optimization algorithm into the construction of a relationship model between the input data and the desired parameters, avoiding repeated matching and optimization processes. Therefore, it can directly, accurately, and efficiently output the inversion results. Under the premise of setting the same accuracy, the iteration number of the BP neural network model is reduced to 2% of the SA algorithm, cutting the calculation time to 30% of the SA algorithm. It has broad application prospects in shallow sea acoustic parameters inversion algorithms.
Improved Bathymetry in the South China Sea from Multisource Gravity Field Elements Using Fully Connected Neural Network
Authors: Li Qianqian , Zhai Zhenhe , Li Qi , Wu Lin , Bao Lifeng , Sun Heping
Published: June 2023

Traditional bathymetry inversion methods that rely on an altimetry-derived gravity anomaly (GA) and/or a vertical gravity gradient anomaly (VGG) have been widely used for bathymetry prediction in the South China Sea. However, few studies attempt new methods to combine multisource gravity data to improve the accuracy of the bathymetry. In this study, we introduce a fully connected deep neural network (FC-DNN) to merge GA, VGG, and the deflection of vertical (DOV) to predict the bathymetry in the South China Sea. Single beam sounding depths were used as sample data for neural network training. Independent shipboard depths and GEBCO2023, topo_25.1, and ETOPO2022 models were applied as validation data. The assessment results showed that the FC-DNN model reached a high precision level with an STD of 49.20 m. More than 70% of the differences between the FC-DNN bathymetric model and other depth models were less than 100 m. Furthermore, the spectral analysis results showed that the FC-DNN bathymetry model has stronger energy in medium and short wavelengths than other models, which indicates that additional gravity field element DOVs can recover richer topographic signals in those particular bands.
Special Issue “Genomics of Fungal Plant Pathogens”
Authors: Wang Baohua , Abubakar Yakubu Saddeeq , Wang Zonghua
Published: June 2023

Plant diseases can be classified according to pathogenic organisms, and 70–80% of them are fungal diseases [...]
Mortality Caused by Candida auris Bloodstream Infections in Comparison with Other Candida Species, a Multicentre Retrospective Cohort
Authors: Ortiz-Roa Cynthia , Valderrama-Rios Martha Carolina , Sierra-Umaña Sebastián Felipe , Rodríguez José Yesid , Muñetón-López Gerardo Antonio , Solórzano-Ramos Carlos Augusto , Escandón Patricia , Alvarez-Moreno Carlos Arturo , Cortés Jorge Alberto
Published: June 2023

Candida auris is an emerging pathogen considered to be critical in the World Health Organization fungal organisms list. The study aims to determine the mortality and hospital stays attributed to Candida auris (C. auris) compared to other Candida species in adult patients with candidemia. A retrospective cohort of adults with candidemia was examined from seven centres in Colombia between 2016 and 2021. The primary outcome was 30-day mortality, and the secondary outcome was the length of hospital stay among survivors. Adjustment of the confounding variables was performed using inverse probability weights of exposure propensity score (candidemia by C. auris), survival regression models (Weibull distribution), and a counting model (negative binomial distribution). A value of 244 (47.6%) of the 512 patients with candidemia died within the first 30 days. The crude mortality in C. auris was 38.1% vs. 51.1% in Candida non-auris (CNA). In the Weibull model, mortality in the C. auris group was lower (adjusted HR: aHR- 0.69, 95% CI: 0.53–0.90). Antifungal treatment also decreased mortality, with an aHR of 0.36 (95% CI 0.27–0.47), while the presence of septic shock on patient progression increased it, with an aHR of 1.73 (95% CI 1.41–2.13). Among the patients who survived, no differences in the length of hospital stay were observed between the C. auris and the CNA groups, with an incidence rate ratio of 0.92 (95% CI: 0.68–1.22). Mortality in patients with C. auris bloodstream infections appears lower when adjusted for numerous confounding variables regarding treatment and the presence of septic shock in patient progression. We identified no significant effect of C. auris on the length of hospital stay in surviving patients.
Hybrid Value-Aware Transformer Architecture for Joint Learning from Longitudinal and Non-Longitudinal Clinical Data
Authors: Shao Yijun , Cheng Yan , Nelson Stuart J. , Kokkinos Peter , Zamrini Edward Y. , Ahmed Ali , Zeng-Treitler Qing
Published: June 2023

Transformer is the latest deep neural network (DNN) architecture for sequence data learning, which has revolutionized the field of natural language processing. This success has motivated researchers to explore its application in the healthcare domain. Despite the similarities between longitudinal clinical data and natural language data, clinical data presents unique complexities that make adapting Transformer to this domain challenging. To address this issue, we have designed a new Transformer-based DNN architecture, referred to as Hybrid Value-Aware Transformer (HVAT), which can jointly learn from longitudinal and non-longitudinal clinical data. HVAT is unique in the ability to learn from the numerical values associated with clinical codes/concepts such as labs, and in the use of a flexible longitudinal data representation called clinical tokens. We have also trained a prototype HVAT model on a case-control dataset, achieving high performance in predicting Alzheimer’s disease and related dementias as the patient outcome. The results demonstrate the potential of HVAT for broader clinical data-learning tasks.
Research on the Healing Potential of Urban Parks from the Perspective of Audio-Visual Integration: A Case Study of Five Urban Parks in Chengdu
Authors: Yang Zhenhong , Zhao Xiaoying , Zhu Lin , Xia Yishi , Ma Yixin , Wu Jingyan , Xiong Xueqian , Yang Ni , Lu Miao
Published: June 2023

In recent decades, rapid urbanization has been linked to negative impacts on people’s mental health. However, the healing potential of urban parks as central features of cityscapes has not been fully explored from the perspective of audio-visual integration. This gap limits designers’ ability to leverage parks’ healing systems to their full potential. To address this gap, this study used the Mindwave monitoring and recovery component scale to evaluate the healing function of urban parks in Chengdu, specifically focusing on audio-visual integration. Based on audio-visual scene combination samples collected through shooting and recording, we found that: (1) The visual and audio qualities of birdsong (the sky above the blue space and the green space) can significantly differ. (2) Birdsong and conversation seem to provide healing effects from seemingly contradictory dimensions of “quiet” and “social”, with gender differences as the primary influencing factor. (3) Visible children laughing at low levels (30% and 50%) has a more negative impact than invisible traffic noise at the same sound pressure level. (4) Audio-visual interaction does not always have a positive effect, with the visibility of the sound source as the primary influencing factor. (5) An increase in audio proportion did not necessarily correspond to a linear increase in the healing effect. Through exploring the influence of audio-visual combination scenes on healing effects in urban parks, this study provides an empirical basis for park design and planning that considers audio-visual healing effects. It offers insights into designing healing systems for parks and urban areas as well.
Land Use and Climate Change Effects on Streamflow and Nutrient Loads in a Temperate Catchment: A Simulation Study
Authors: Ayele Gebiaw T. , Yu Bofu , Hamilton David P.
Published: June 2023

Climate and land use changes impact catchment hydrology and water quality (WQ), yet few studies have investigated the amount of land use changes required to meet specific WQ targets under future climate projections. The aim of this study was to determine streamflow and nutrient load responses to future land use change (LUC) and climate change scenarios. We hypothesized that (1) increasing forest coverage would decrease nutrient loads, (2) climate change, with higher temperatures and more intense storms, would lead to increased flow and nutrient loads, and (3) LUC could moderate potential nutrient load increases associated with climate change. We tested these hypotheses with the Soil and Water Assessment Tool (SWAT), which was applied to a lake catchment in New Zealand, where LUC strategies with afforestation are employed to address lake WQ objectives. The model was calibrated from 2002 to 2005 and validated from 2006 to 2010 using measured streamflow (Q) and total nitrogen (TN), total phosphorus (TP), nitrate (NO3-N), and ammonium (NH4-N) concentrations of three streams in the catchment. The model performance across the monitored streams was evaluated using coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) metrics to provide a basis for model projections. Future scenarios incorporated LUC and climate change (CC) based on the Representative Concentration Pathway 8.5 and were compared to the baseline streamflow and WQ indicators. Consistent with our hypotheses, Q, TN, and TP loads were predicted to decrease with afforestation. Specifically, afforestation of 1.32 km2 in one of the monitored stream sub-catchments (subbasin 3), or 8.8% of the total lake catchment area, would result in reductions of 11.9, 26.2, and 17.7% in modeled annual mean Q, TN, and TP loads, respectively. Furthermore, when comparing simulations based on baseline and projected climate, reductions of 13.6, 22.8, and 19.5% were observed for Q, TN, and TP loads, respectively. Notably, the combined implementation of LUC and CC further decreased Q, TN, and TP loads by 20.2, 36.7, and 28.5%, respectively. This study provides valuable insights into the utilization of LUC strategies to mitigate nutrient loads in lakes facing water quality challenges, and our findings could serve as a prototype for other lake catchments undergoing LUC. Contrary to our initial hypotheses, we found that higher precipitation and temperatures did not result in increased flow and nutrient loading.
Determination and Prediction of Time-Varying Parameters of Mooney–Rivlin Model of Rubber Material Used in Natural Rubber Bearing under Alternating of Aging and Seawater Erosion
Authors: Niu Wanbao , Li Yanmin , Ma Yuhong , Zhao Guifeng
Published: June 2023

In this paper, we examined the parameters of the Mooney–Rivlin model based on the effects of alternative aging and sea corrosion tests for natural rubber bearings and rubber materials in seawater. The model parameters for rubber material used in natural rubber bearings were determined using the least-squares method. Meanwhile, the time-varying law formula of the Mooney–Rivlin model parameters of rubber were fitted, and the fitting and calculated values were compared. Both fitting values and calculated values coincide with each other well. Then, the rubber material parameters were predicted based on the calculated results and combined with nonlinear auto-regressive (NAR). The predicted values were compared with both the fitting and calculated values. The average deviations between predicted and fitting values for C10 and C01 were 2.6% and 5.1%, respectively, and average deviations between predicted and calculated values for C10 and C01 were 5.2% and 4.1%. Compared results show that the predicted values are in good agreement with both the fitting and calculated values; meanwhile, the proposed time-varying law formula of the Mooney–Rivlin model parameters of rubber material have been well verified.
A Finite Element Analysis on the Effect of Scanning Pattern and Energy on Residual Stress and Deformation in Wire Arc Additive Manufacturing of EH36 Steel
Authors: Ali Muhammad Hassaan , Han You Sung
Published: June 2023

Wire arc additive manufacturing (WAAM) is a metal additive manufacturing (AM) technique that has a high throughput and has seen a potential interest for replacing currently available subtractive manufacturing techniques. Contrary to other metal AM machines, WAAM rigs can be built using existing welding plants and using welding wire as feedstock, thus, making it a cheap and viable manufacturing technique for a number of industries, such as the maritime industry. However, the effects of AM parameters, such as the scanning pattern and energy, on the residual stress and deformation, are still not completely understood. In this work, a finite element (FE) study has been conducted to understand the influence of different scanning patterns (alternate, in-out, raster and zigzag) and energies on residual stress and warpage. Analyses show that the in-out scanning pattern leads to the highest residual stress, while the zigzag pattern results in the lowest residual stress for all scanning energies considered in this study. Findings in the present study also show that the scanning pattern affects the residual stress and deformation more than does the scanning energy.
The Mechanical Properties of Direct Metal Laser Sintered Thin-Walled Maraging Steel (MS1) Elements
Authors: Bochnia Jerzy , Kozior Tomasz , Zyz Jarosław
Published: June 2023

The aim of this study was to explore the mechanical properties of thin-walled maraging steel (MS1) elements fabricated using direct metal laser sintering (DMLS). This article first explains the fabrication procedure and then analyzes the results of the static tensile strength tests and microscopic (SEM) examinations. From this study, it is evident that the mechanical properties of such objects, particularly their tensile strength, are not affected by the build direction; no significant anisotropy was found. The experiments confirm, however, that the mechanical properties of thin-walled elements fabricated from MS1 by DMLS are largely dependent on thickness. The microscopic images of such elements show local discontinuities in the macrostructure of the molten material (powder). Although the research described here mainly contributes to the field of additive manufacturing, it also considers some aspects of Lean manufacturing.
Two New Red/Near-Infrared Ir(Ⅲ) Complexes with Reversible and Force-Induced Enhanced Mechanoluminescence
Authors: Yang Yuzhen , Zeng Qin , Zhou Weiqiao , Jiang Junjie , Zhang Zihao , Guo Song , Liu Yuanli
Published: June 2023

Two novel ionic red/near-infrared Ir(III) complexes (Ir1 and Ir2) were reasonably designed and prepared using 2-(1-isoquinolinyl)-9,10-anthraquinone as the main ligand and 4,4′-dimethyl-2,2′-bipyridyl and 4,4′-dimethoxy-2,2′-bipyridyl as the auxiliary ligands, respectively. Both complexes showed bright phosphorescence in solution (peak at 618 nm with a shoulder at 670 nm). Interestingly, the phosphorescence peak of two Ir(III) complexes showed a blue-shift of about 36 nm after being ground. Simultaneously, both complexes exhibited mechanical force-induced enhanced emission, and the intensity of the luminescence for Ir1 and Ir2 increased by around two times compared to the one before being ground, respectively. Powder X-ray diffraction (PXRD) and time-dependent density functional theory (TD-DFT) calculation were utilized to understand well the mechanism of this phenomenon and suggested that the destruction of the well-ordered crystalline nature and the decline in triplet-triplet annihilation maybe responsible for the pressure-induced blue-shift and the enhancement of the phosphorescence.
Carbon Peaking and Carbon Neutrality in the Cement-Based Materials
Authors: Zhang Gui-Yu , Wang Xiao-Yong
Published: June 2023

The cement industry plays a significant role in global carbon emissions, accounting for approximately 8% of global anthropogenic carbon dioxide (CO2) emissions [...]
Size- and Chirality-Dependent Structural and Mechanical Properties of Single-Walled Phenine Nanotubes
Authors: Liu Yanjun , Wang Ruijie , Wang Liya , Xia Jun , Wang Chengyuan , Tang Chun
Published: June 2023

Phenine nanotubes (PNTs) have recently been synthesized as a promising new one-dimensional material for high-performance electronics. The periodically distributed vacancy defects in PNTs result in novel semiconducting properties, but may also compromise their mechanical properties. However, the role of these defects in modifying the structural and mechanical properties is not yet well understood. To address this, we conducted systematic molecular dynamics simulations investigating the structural evolution and mechanical responses of PNTs under various conditions. Our results demonstrated that the twisting of linear carbon chains in both armchair and zigzag PNTs led to interesting structural transitions, which were sensitive to chiralities and diameters. Additionally, when subjected to tensile and compressive loading, PNTs’ cross-sectional geometry and untwisting of linear carbon chains resulted in distinct mechanical properties compared to carbon nanotubes. Our findings provide comprehensive insights into the fundamental properties of these new structures while uncovering a new mechanism for modifying the mechanical properties of one-dimensional nanostructures through the twisting–untwisting of linear carbon chains.
Laser Powder Bed Fusion of Inconel 718 Tools for Cold Deep Drawing Applications: Optimization of Printing and Post-Processing Parameters
Authors: Jiang Cho-Pei , Maidhah Andi Ard , Wang Shun-Hsien , Wang Yuh-Ru , Pasang Tim , Ramezani Maziar
Published: June 2023

Inconel 718 (IN 718) powder is used for a laser powder bed fusion (LPBF) printer, but the mechanical properties of the as-built object are not suited to cold deep drawing applications. This study uses the Taguchi method to design experimental groups to determine the effect of various factors on the mechanical properties of as-built objects produced using an LPBF printer. The optimal printing parameters are defined using the result for the factor response to produce an as-built object with the greatest ultimate tensile strength (UTS), and this is used to produce a specimen for post-processing, including heat treatment (HT) and surface finishing. The HT parameter value that gives the maximum UTS is the optimal HT parameter. The optimal printing and HT parameter values are used to manufacture a die and a punch to verify the suitability of the manufactured tool for deep drawing applications. The experimental results show that the greatest UTS is 1091.33 MPa. The optimal printing parameters include a laser power of 190 W, a scanning speed of 600 mm/s, a hatch space of 0.105 mm and a layer thickness of 40 μm, which give a UTS of 1122.88 MPa. The UTS for the post-processed specimen increases to 1511.9 MPa. The optimal parameter values for HT are heating to 720 °C and maintaining this temperature for 8 h, decreasing the temperature to 620 °C and maintaining this temperature for 8 h, and cooling to room temperature in the furnace. Surface finishing increases the hardness to HRC 55. Tools, including a punch and a die, are manufactured using these optimized parameter values. The deep drawing experiment demonstrates that the manufactured tools that are produced using these values form a round cup of Aluminum alloy 6061. The parameter values that are defined can be used to manufacture IN 718 tools with a UTS of more than 1500 MPa and a hardness of more than 50 HRC, so these tools are suited to cold deep drawing specifications.
Mesoscopic Mechanical Properties of Aggregate Structure in Asphalt Mixtures and Gradation Optimization
Authors: Chen Jingchun , Wang Jian , Li Min , Zhao Zedong , Ren Jiaolong
Published: June 2023

Particle media are widely used in engineering and greatly influence the performance of engineering materials. Asphalt mixtures are multi-phase composite materials, of which coarse aggregates account for more than 60%. These coarse aggregates form a stable structure to transfer and disperse traffic loads. Therefore, knowing how to adjust the structural composition of coarse aggregates to optimize their performance is the key to optimize the performance of asphalt mixtures. In this study, the effects of different roughness and different sizes on the interlocking force and contact force of coarse aggregates were investigated through means of simulation (DEM), and then the formation-evolution mechanism of the coarse aggregate structure and the role of different sizes of aggregates in the coarse aggregate structure were analyzed. Subsequently, the optimal ratio of coarse aggregates was explored through indoor tests, and finally, the gradation of asphalt mixture based on the optimization of fine structure was formed and verified through indoor tests. The results showed that the major model can effectively reveal the role of different types of aggregates in the fine structure and the relationship between the strength of contact forces between them and clarify that the strength of the fine structure increases with the increase in aggregate roughness. Hence, the coarse aggregate structure can be regarded as a contact force transmission system composed of some strong and sub-strong contact forces. Their formation-evolution mechanism can be regarded as a process of the formation of strong and sub-strong contact forces and the transformation from sub-strong contact force to strong contact force. Moreover, the dynamic stability of the optimized graded asphalt mixture was increased by 30%, and the fracture toughness was increased by 26%.
Failure Mechanism of Tensile CFRP Composite Plates with Variable Hole Diameter
Authors: Wysmulski Pawel
Published: June 2023

Real thin-walled composite structures such as aircraft or automotive structures are exposed to the development of various types of damage during operation. The effect of circular hole size on the strength of a thin-walled plate made of carbon fibre-reinforced polymer (CFRP) was investigated in this study. The test object was subjected to tensile testing to investigate the strength and cracking mechanism of the composite structure with variable diameter of the central hole. The study was performed using two independent test methods: experimental and numerical. With increasing diameter of the central hole, significant weakening of the composite plate was observed. The study showed qualitative and quantitative agreement between the experimental and numerical results. The results confirmed the agreement of the proposed FEM model with the experimental test. The novelty of this study is the use of the popular XFEM technique to describe the influence of the hole size on the cracking and failure of the composite structure. In addition, the study proposes a new method for determining the experimental and numerical damage and failure loads of a composite plate under tension.
A Study on Optimal Indium Tin Oxide Thickness as Transparent Conductive Electrodes for Near-Ultraviolet Light-Emitting Diodes
Authors: Kim Min-Ju
Published: June 2023

This research study thoroughly examines the optimal thickness of indium tin oxide (ITO), a transparent electrode, for near-ultraviolet (NUV) light-emitting diodes (LEDs) based on InGaN/AlGaInN materials. A range of ITO thicknesses from 30 to 170 nm is investigated, and annealing processes are performed to determine the most favorable figure of merit (FOM) by balancing transmittance and sheet resistance in the NUV region. Among the films of different thicknesses, an ITO film measuring 110 nm, annealed at 550 °C for 1 min, demonstrates the highest FOM. This film exhibits notable characteristics, including 89.0% transmittance at 385 nm, a sheet resistance of 131 Ω/□, and a contact resistance of 3.1 × 10−3 Ω·cm2. Comparing the performance of NUV LEDs using ITO films of various thicknesses (30, 50, 70, 90, 130, 150, and 170 nm), it is observed that the NUV LED employing ITO with a thickness of 110 nm achieves a maximum 48% increase in light output power at 50 mA while maintaining the same forward voltage at 20 mA.
Triple-Band and Ultra-Broadband Switchable Terahertz Meta-Material Absorbers Based on the Hybrid Structures of Vanadium Dioxide and Metallic Patterned Resonators
Authors: Zou Yuke , Lin Hongyan , Tian Gaowen , Zhou Haiquan , Zhu Huaxin , Xiong Han , Wang Ben-Xin
Published: June 2023

A bifunctional terahertz meta-material absorber with three layers is designed. The surface of the bifunctional meta-material absorber is a periodically patterned array composed of hybrid structures of vanadium dioxide (VO2) and metallic resonators; the middle layer is a nondestructive TOPAS film, and the bottom layer is a continuous metallic plane. Utilizing the phase-transition property of VO2, the responses of the meta-material absorber could be dynamically switched between triple-band absorption and ultra-broadband absorption. When VO2 is in the metallic state, an ultra-broadband absorption covering the bandwidth of 6.62 THz is achieved over the range from 4.71 THz to 11.33 THz. When VO2 is in the di-electric state, three absorption peaks resonated at 10.57 THz, 12.68 THz, and 13.91 THz. The physical mechanisms of the bifunctional meta-material absorber were explored by analyzing their near-field distributions. The effects of varying structural parameters on triple-band and ultra-broadband absorption were investigated. It is revealed that by optimizing the structure parameters, the number of absorption peaks could be increased for a certain sacrifice of absorption bandwidth. FDTD Solutions and CST Microwave Studio were used to simulate the data of the absorber, and similar results were obtained.
Experimental Investigation of Wave Propagation Characteristics in Entangled Metallic Wire Materials by Acoustic Emission
Authors: Ma Yanhong , Liang Tianyu , Wang Yongfeng , Zhang Qicheng , Hong Jie
Published: June 2023

In this paper, the response characteristics of wave propagation in entangled metallic wire materials (EMWMs) are investigated by acoustic emission. The frequency, amplitude of wave emission, and the pre-compression force of the specimen can be adjusted in the experimental setup. EMWM specimens fabricated from stainless steel wires and with different design parameters are tested in this work. The results show that waves of different amplitudes propagate in EMWMs with approximate linear characteristics and the fluctuation coefficient of wave passing ratios is calculated below 15%. The response spectrum of passing waves shows a distinct single-peak characteristic, with the peak response at approximately 14 kHz. The parameters of pre-compression force, porosity, wire diameter, helix diameter, specimen height, and the layered structure of specimens have no significant effect on the frequency characteristics but moderately affect the wave passing ratios. Notably, EMWMs exhibit a lower wave passing ratio (ranging from 0.01 to 0.18) compared to aluminum alloy and natural rubber. The characteristics of response spectrums can be successfully reproduced by the finite element simulation. This work demonstrates EMWMs’ potential as an acoustic frequency vibration isolation material, offering excellent performance and engineering design convenience.
Structural Design and Controllability of Magnetorheological Grease Buffers under Impact Loading
Authors: Kong Gaoyang , Ouyang Qing , Hu Hongsheng , Xiang Wenfeng , Zhao Wei
Published: June 2023

Shock loads can pose a great threat to personnel or instruments, and efficient control of the buffering process is an effective means of reducing damage from shock energy. In this paper, magneto-rheological grease was used as the internal controllable material of the buffer to address the turbulence and settling problems of conventional magneto-rheological fluid. A bending and folding back magnetic circuit is proposed, and the magnetic circuit simulation was verified. The corresponding dynamic mechanical model was established, and the mechanical response characteristics of the buffer under impact load were also simulated dynamically. The mechanical properties of the designed and processed device were tested, and a variable current control method was used to improve the performance of the shock resistance of the buffer. The response of the magnetorheological grease buffer under different drop hammer impacts was investigated. The buffering effect and controllability of the buffer were analyzed by comparing the acceleration, velocity, and top-end cap displacement at the same drop hammer height for different current magnitudes. The results show that the buffer performance of the buffer gradually improved as the current increased. The response time of the designed new magnetorheological buffer was determined by the jump time of the peak damping force to be 9 ms. Lastly, the controllability was verified by manually and automatically adjusting the current magnitude, and the results were compared with those at 300 mm drop hammer height and 0.5 A current magnitude, and the continuous variable current control was found to be effective. This provides a feasible reference for scholars to study optimal buffer control.
Genetic-Algorithm-Based Inverse Optimization Identification Method for Hot-Temperature Constitutive Model Parameters of Ti6Al4V Alloy
Authors: Chen Xuewen , Su Zhiyi , Sun Jiawei , Yang Zhen , Zhang Bo , Zhou Zheng
Published: June 2023

A precise constitutive model is the foundation and key to finite element simulation in material volume forming and the optimization of the hot working process. Hence, to build a precise constitutive model, a method based on a genetic algorithm (GA) for the inverse optimization identification of parameters is presented in this paper. The idea of this method is to continuously adjust the model parameters through GA until the objective function reaches the minimum value. In this study, hot compression experiments were performed on the Gleeble-1500D thermal simulator at temperatures ranging from 800 °C to 1000 °C and strain rates of 0.01 s−1 to 1 s−1. The Arrhenius-type (A-T) model considering strain compensation and the Johnson–Cook (JC) model considering the coupling effects of strain, temperature and strain rate were constructed, respectively, by using the regression method and the parameter inverse optimization identification method. For the purposes of comparing and verifying the reliability of the predictions of the two established constitutive models, the correlation coefficient (R), average absolute relative error (AARE), and relative error (RE) were adopted. The results show that both the optimized A-T model and the optimized JC model have high prediction accuracy. Compared to the optimized JC model, the optimized A-T model demonstrated a higher correlation coefficient, by 0.003, and a lower average absolute relative error, by 1.43%. Furthermore, the relative error distribution of the optimized A-T model was found to be more concentrated than that of the optimized JC model. These results suggest that the A-T model is more appropriate than the JC model for characterizing the high-temperature deformation behavior of Ti6Al4V alloy.
Bifurcation of an SIRS Model with a Modified Nonlinear Incidence Rate
Authors: Zhang Yingying , Li Chentong
Published: June 2023

An SIRS epidemic model with a modified nonlinear incidence rate is studied, which describes that the infectivity is strong at first as the emergence of a new disease or the reemergence of an old disease, but then the psychological effect will weaken the infectivity. Lastly, the infectivity goes to a saturation state as a result of a crowding effect. The nonlinearity of the functional form of the incidence of infection is modified, which is more reasonable biologically. We analyze the stability of the associated equilibria, and the basic reproduction number and the critical value which determine the dynamics of the model are derived. The bifurcation analysis is presented, including backward bifurcation, saddle-node bifurcation, Bogdanov–Takens bifurcation of codimension two and Hopf bifurcation. To study Hopf bifurcation of codimension three of the model when some assumptions hold, the focus values are calculated. Numerical simulations are shown to verify our results.
Sakaguchi Type Starlike Functions Related with Miller-Ross-Type Poisson Distribution in Janowski Domain
Authors: El-Deeb Sheza M. , Alharbi Asma , Murugusundaramoorthy Gangadharan
Published: June 2023

In this research, using the Poisson-type Miller-Ross distribution, we introduce new subclasses Sakaguchi type of star functions with respect to symmetric and conjugate points and discusses their characteristic properties and coefficient estimates. Furthermore, we proved that the class is closed by an integral transformation. In addition, we pointed out some new subclasses and listed their geometric properties according to specializing in parameters that are new and no longer studied in conjunction with a Miller-Ross Poisson distribution.
Optimizing Air Pollution Modeling with a Highly-Convergent Quasi-Monte Carlo Method: A Case Study on the UNI-DEM Framework
Authors: Todorov Venelin , Georgiev Slavi , Georgiev Ivan , Zaharieva Snezhinka , Dimov Ivan
Published: June 2023

In this study, we present the development of an advanced air pollution modeling approach, which incorporates cutting-edge stochastic techniques for large-scale simulations of long-range air pollutant transportation. The Unified Danish Eulerian Model (UNI-DEM) serves as a crucial mathematical framework with numerous applications in studies concerning the detrimental effects of heightened air pollution levels. We employ the UNI-DEM model in our research to obtain trustworthy insights into critical questions pertaining to environmental preservation. Our proposed methodology is a highly convergent quasi-Monte Carlo technique that relies on a unique symmetrization lattice rule. By fusing the concepts of special functions and optimal generating vectors, we create a novel algorithm grounded in the component-by-component construction method, which has been recently introduced. This amalgamation yields particularly impressive outcomes for lower-dimensional cases, substantially enhancing the performance of the most advanced existing methods for calculating the Sobol sensitivity indices of the UNI-DEM model. This improvement is vital, as these indices form an essential component of the digital ecosystem for environmental analysis.
An Evolutionary Game Analysis of Stakeholders’ Decision-Making Behavior in Medical Data Sharing
Authors: Gao Yi , Zhu Zhiling , Yang Jian
Published: June 2023

In the era of big data, medical data sharing has become an inevitable requirement to improve the quality and efficiency of medical services. To advance the progress of medical data sharing and expedite the circulation of data value, it becomes crucial to examine the decision-making behavior of stakeholders involved in the medical-data-sharing process. To this end, we construct a three-way evolutionary game model applicable to the medical sharing scenario, analyzing the evolutionary trends in the selection strategies of data providers, the medical-data-sharing platform and data demanders. Furthermore, through theoretical analysis and simulation experiments, we explore the game equilibrium point of the system and analyze key factors that affect stakeholder strategy selection. The results of the experiment show that, in addition to data security, platforms and regulators should pay attention to the regulation and governance of the quality of data flows, which involves reasonable incentives–feedback–rewards and penalties. By strengthening the security technology and data governance system construction of sharing platforms, as well as promoting regulatory authorities to implement reward and punishment measures, etc., a stable state can be achieved in such systems. In addition, this article also proposes relevant management suggestions for medical data sharing in order to provide useful references for scientific decision making by stakeholders.
Could You Understand Me? The Relationship among Method Complexity, Preprocessing Complexity, Interpretability, and Accuracy
Authors: Kelebercová Lívia , Munk Michal , Forgáč František
Published: June 2023

The need to train experts who will be able to apply machine learning methods for knowledge discovery is increasing. Building an effective machine learning model requires understanding the principle of operation of the individual methods and their requirements in terms of data pre-preparation, and it is also important to be able to interpret the acquired knowledge. This article presents an experiment comparing the opinion of the 42 students of the course called Introduction to Machine Learning on the complexity of the method, preprocessing, and interpretability of symbolic, subsymbolic and statistical methods with the correctness of individual methods expressed on the classification task. The methodology of the implemented experiment consists of the application of various techniques in order to search for optimal models, the accuracy of which is subsequently compared with the results of a knowledge test on machine learning methods and students’ opinions on their complexity. Based on the performed non-parametric and parametric statistic tests, the null hypothesis, which claims that there is no statistically significant difference in the evaluation of individual methods in terms of their complexity/demandingness, the complexity of data preprocessing, the comprehensibility of the acquired knowledge and the correctness of the classification, is rejected.
A Review of Representative Points of Statistical Distributions and Their Applications
Authors: Fang Kai-Tai , Pan Jianxin
Published: June 2023

Statistical modeling relies on a diverse range of statistical distributions, encompassing both univariate and multivariate distributions and/or discrete and continuous distributions. In the literature, numerous statistical methods have been proposed to approximate continuous distributions. The most commonly used approach is the use of the empirical distribution which is obtained from a random sample drawn from the distribution. However, it is very likely that the empirical distribution suffers from an accuracy problem when used to approximate the underlying distribution, especially if the sample size is not sufficient. In order to improve statistical inferences, various alternative forms of discrete approximation to the distribution were proposed in the literature. The choice of support points for the discrete approximation, known as Representative Points (RPs), becomes extremely important in terms of distribution approximations. In this paper we give a review of the three main methods for constructing RPs, namely based on the Monte Carlo method, the number-theoretic method (or quasi-Monte Carlo method), and the mean square error method, aiming to introduce such important methods to the statistical or mathematical community. Additional approaches for forming RPs are also briefly discussed. The review focuses on certain critical aspects such as theoretical properties and computational algorithms for constructing RPs. We also address the issue of the application of RPs through studying practical problems and provide evidence of RPs’ advantages over random samples in approximating the distribution.