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PurposeOwing to the excellent performance, giant magnetostrictive materials (GMMs) are widely used in many engineering fields. The dynamic Jiles–Atherton (J-A) model, derived from physical mechanism, is often used to describe the hysteresis characteristics of GMM. However, this model, despite cited by many different literature studies, seems not to possess unique expressions, which may cause great trouble to the subsequent application. This paper aims to provide the rational expressions of the dynamic J-A model and propose a numerical computation scheme to obtain the model results with high accuracy and fast speed.Design/methodology/approachThis paper analyzes different published papers and provides a reasonable form of the dynamic J-A model based on functional properties and physical explanations. Then, a numerical computation scheme, combining the Newton method and the explicit Adams method, is designed to solve the modified model. In addition, the error source and transmission path of the numerical solution are investigated, and the influence of model parameters on the calculation error is explored. Finally, some attempts are made to study the influence of numerical scheme parameters on the accuracy and time of the computation process. Subsequently, an optimization procedure is proposed.FindingsA rational form of the dynamic J-A model is concluded in this paper. Using the proposed numerical calculation scheme, the maximum calculation error, while computing the modified model, can remain below 2 A/m under different model parameter combinations, and the computation time is always less than 0.5 s. After optimization, the calculation speed can be enhanced with the computation accuracy guaranteed.Originality/valueTo the best of the authors’ knowledge, this paper is the first one trying to provide a rational form of the dynamic J-A model among different citations. No other research studies focus on designing a detailed computation scheme targeting the fast and accurate calculation of this model as well. And the performance of the proposed calculation method is validated in different conditions.

Osteogenesis is a complex physiologic process that occurs during bone regeneration. This process requires several growth factors that act on bone marrow-derived mesenchymal stem cells (BMSCs). Concentrated growth factor (CGF) is a new-generation platelet-rich derivative that is an appealing autologous material for application in tissue repair and bone regenerative medicine because it contains a variety of fibrin and growth factors. In this study, the effects of CGF on the proliferation and osteogenic differentiation of hBMSCs and human umbilical vein endothelial cells (HUVECs) were explored with in vitro cell co-culture experiments. HBMSCs and HUVECs were directly co-cultured at the ratio of 1:2 under different concentrations (0, 2, 5, 10, 20%) of CGF for 7 days. Alkaline phosphatase (ALP) staining and quantitative reverse transcription polymerase chain reaction were used to detect the effects of CGF on the expression of osteogenic genes (ALP, osteocalcin [OCN], type I collagen [COL-1], Runt-related transcription factor 2 [RUNX2]) and connexin 43 (CX43). RNA sequencing was used to explore potential regulated genes and signaling pathways that affect the osteogenesis of co-cultured hBMSCs exposed to CGF. The results showed higher expressions of ALP, COL-1, RUNX2, OCN, and CX43 in the direct co-culture group containing 10% CGF compared to the direct co-culture group without CGF and the indirect co-culture group. In summary, 10% CGF can significantly promote osteogenesis in hBMSCs directly co-cultured with HUVECs. Intercellular communication between the direct co-culture of hBMSCs and HUVECs through CX43 may be one of the main regulatory mechanisms.

Glycans are found across the tree of life with remarkable structural diversity enabling critical contributions to diverse biological processes, ranging from facilitating host-pathogen interactions to regulating mitosis & DNA damage repair. While functional motifs within glycan structures are largely responsible for mediating interactions, the contexts in which the motifs are presented can drastically impact these interactions and their downstream effects. Here, we demonstrate the first deep learning method to represent both local and global context in the study of glycan structure-function relationships. Our method, glyBERT, encodes glycans with a branched biochemical language and employs an attention-based deep language model to learn biologically relevant glycan representations focused on the most important components within their global structures. Applying glyBERT to a variety of prediction tasks confirms the value of capturing rich context-dependent patterns in this attention-based model: the same monosaccharides and glycan motifs are represented differently in different contexts and thereby enable improved predictive performance relative to the previous state-of-the-art approaches. Furthermore, glyBERT supports generative exploration of context-dependent glycan structure-function space, moving from one glycan to “nearby” glycans so as to maintain or alter predicted functional properties. In a case study application to altering glycan immunogenicity, this generative process reveals the learned contextual determinants of immunogenicity while yielding both known and novel, realistic glycan structures with altered predicted immunogenicity. In summary, modeling the context dependence of glycan motifs is critical for investigating overall glycan functionality and can enable further exploration of glycan structure-function space to inform new hypotheses and synthetic efforts.

Computational methods for predicting binding interfaces between antigens and antibodies (epitopes and paratopes) are faster and cheaper than traditional experimental structure determination methods. A sufficiently reliable computational predictor that could scale to large sets of available antibody sequence data could thus inform and expedite many biomedical pursuits, such as better understanding immune responses to vaccination and natural infection and developing better drugs and vaccines. However, current state-of-the-art predictors produce discontiguous predictions, e.g., predicting the epitope in many different spots on an antigen, even though in reality they typically comprise a single localized region. We seek to produce contiguous predicted epitopes, accounting for long-range spatial relationships between residues. We therefore build a novel Graph Convolution Network (GCN) that performs graph convolutions at multiple resolutions so as to represent and constrain long-range spatial dependencies. In evaluation on a standard epitope prediction benchmark, we see a significant boost with the multi-resolution approach compared to a previous state-of-the-art GCN predictor, with half of the test cases increasing in AUC-PR by an average of 0.15 and the other half decreasing by only 0.05. We further introduce a clustering algorithm that takes advantage of the contiguity yielded by our model, grouping the raw predictions into a small set of discrete potential epitopes. We show that within the top 3 clusters, 73% of test cases contain a cluster covering most of the actual epitope, demonstrating the utility of contiguous predictions for guiding experimental methods by yielding a small set of reasonable hypotheses for further investigation.

Motivation Protein–protein interactions drive wide-ranging molecular processes, and characterizing at the atomic level how proteins interact (beyond just the fact that they interact) can provide key insights into understanding and controlling this machinery. Unfortunately, experimental determination of three-dimensional protein complex structures remains difficult and does not scale to the increasingly large sets of proteins whose interactions are of interest. Computational methods are thus required to meet the demands of large-scale, high-throughput prediction of how proteins interact, but unfortunately, both physical modeling and machine learning methods suffer from poor precision and/or recall. Results In order to improve performance in predicting protein interaction interfaces, we leverage the best properties of both data- and physics-driven methods to develop a unified Geometric Deep Neural Network, ‘PInet’ (Protein Interface Network). PInet consumes pairs of point clouds encoding the structures of two partner proteins, in order to predict their structural regions mediating interaction. To make such predictions, PInet learns and utilizes models capturing both geometrical and physicochemical molecular surface complementarity. In application to a set of benchmarks, PInet simultaneously predicts the interface regions on both interacting proteins, achieving performance equivalent to or even much better than the state-of-the-art predictor for each dataset. Furthermore, since PInet is based on joint segmentation of a representation of a protein surfaces, its predictions are meaningful in terms of the underlying physical complementarity driving molecular recognition. Availability and implementation PInet scripts and models are available at https://github.com/FTD007/PInet. Supplementary information Supplementary data are available at Bioinformatics online.

Giant magnetostrictive materials (GMMs) have broad application prospects in the field of servo valves, but the giant magnetostrictive actuator (GMA) has problems such as large loss and severe heat generation, which affect the output effect and accuracy. To solve these problems, this paper designs a stacked giant magnetostrictive actuator (SGMA) and analyzes the magnetic circuit and magnetic field distribution of the SGMA. Based on the magnetic field analysis and the Jiles&ndash, Atherton model, we analyze the SGMA magnetization model, simplify the traditional model, and give a solution for the simplified model using the Runge&ndash, Kutta method. We analyze the eddy current loss of the SGMA, and according to Bessel&rsquo, s equation and the Kelvin function, we calculate the relationship among eddy current loss, GMM rod radius, and magnetic field frequency. By analyzing the inherent hysteresis of GMMs, a hysteresis loss model of the SGMA is established in this paper. We also calculate the coil impedance and obtain the coil loss model. Based on the loss model, the SGMA cooling system is designed. Based on the above analysis, we design a SGMA prototype, set-up the corresponding experimental platform, and conduct the necessary experiments. The experimental results show that the SGMA responds well to different signals, but as frequency increases, attenuation, deformation, and hysteresis become more pronounced, which verifies the amplitude and phase changes caused by various losses in the theoretical analysis. The experiment also observes the temperature rise of the oil-cooled SGMA at different frequencies, indicating that the cooling system can effectively control the temperature change of the SGMA, which validates the foregoing analysis.

The combustion behavior of bamboo char and its relationship with particle sizes were evaluated using thermo-gravimetric analysis. The results showed that the combustion properties of bamboo char were much better than those of the anthracite used as a coal injected for blast furnace ironmaking due to its porous structure, disordered microcrystalline and higher catalytic index of ash minerals. When the particle size increased from − 0.074 to 0.500–1.000 mm, the ignition temperature and burnout temperature of bamboo char increased, while the combustible index and comprehensive combustion characteristic index decreased slightly. The apparent activation energies of non-isothermal combustion of bamboo char and anthracite were calculated based on the distributed activation energy model. The results showed that the average activation energy was 162.86 kJ/mol for − 0.074 mm anthracite, while it ranged from 71.01 to 89.44 kJ/mol for bamboo chars of different sizes. It revealed that the combustion reactivity of bamboo char in the largest size (0.500–1.000 mm) was much better than that of − 0.074 mm anthracite; thus, the size of biomass char could be enlarged to the maximum size specified by the injection application of blast furnace.

The grain-size effects of the direct piezoelectric coefficient (d 33 ) and the converse piezoelectric coefficient (d 33 *) of BaTiO 3 ceramics with different Ba/Ti ratios were systematically explored. It was found that both d 33 and d 33 * exhibited strong grain size (g) dependences for BaTiO 3 ceramics with various Ba/Ti ratios. Although d 33 showed similar grain-size dependence for all the Ba/Ti ratios except a subtle shift of the critical grain size from 1 μm to 3 μm, two entirely different grain-size dependence of d 33 * were observed. By carefully examining the microstructure and ferroelectric properties of the ceramics, the variations of domain configurations and maximum polarization of BaTiO 3 ceramics with different Ba/Ti ratios were considered to be responsible for the different grain-size dependence of d 33 and d 33 *, respectively.

Effect of three iron ore types (limonite, hematite and oolitic hematite) on the thermal behaviour and reaction kinetics of coal-iron ore briquettes during coking was investigated using the thermal analysis method. The carbonized briquettes were characterized using the XRD and SEM. The results showed that all three iron ores were completely reduced to Fe at the final coking stage. The addition of iron ore to the coal briquette had little influence on the gas yield, but could significantly affect the reaction rate. A synergistic effect of iron ore and coal occurred in the later reaction stage, and the initial temperature of the synergistic effect varied with the type of iron ore in coal-iron ore briquettes. The type of iron ore hardly affected the devolatilization rate of coal-iron ore briquettes, but could greatly influence the reduction rate of iron ore, subsequently the gasification rate of coal char. In addition, the better reduction ability of iron ore could more easily lead to the cracking of coke. When the iron ore was blended into the coal briquette, the reaction kinetics at the first and third reaction stage changed. The three coal-iron ore briquettes had similar weighted average apparent activation energies of 30.67–35.52 kJ/mol.

In this paper, a simple image processing unit (IPU) structure for a general-purpose representation and association machine system is proposed. We immediately apply our IPU to a digit recognition and hyper-acuity test. The quality of the digit images has been severely degraded to mimic visual information variability experienced in human visual systems. The degraded images are then fed to the IPU, which consists of a randomly constructed low-density parity check (LDPC) code, an iterative decoder, a switch, and scaling, and decision devices. The results show that: 1) our IPU can reliably recognize digits despite the image quality being poor; 2) our IPU provides a hyper-acuity capability comparable to human visual systems; and 3) our IPU with the randomly constructed LDPC code can provide significantly improved recognition capability compared with the IPU without coding, even though the code is not optimized for our tasks.

The metallurgical properties and the microstructure of coke after gasification reaction with pure H2O and pure CO2 were investigated in this study. Moreover, the first principles calculation was conducted to study the reaction process of the carbon with pure H2O and pure CO2. The results show that the CRI (coke reaction index) increases sharply and the CSR (coke strength after reaction) decreases sharply, when the cokes are gasified with H2O as compared to CO2. The scanning electronic microscopy (SEM) images and the coke panoramagrams show that H2O more easily leads to the generation of large pore (>500μm) and destroys the coke structure than CO2. The X-ray diffraction (XRD) results indicate that the arrangement of carbon atoms of coke becomes regular and the ordered degree of coke increases after reaction with CO2 and H2O; however, after being gasified with H2O, the cokes have a higher ordered degree than with CO2. The results of the first principles calculation show that the H2O molecule is more likely ...

A two-step sintering method was employed to fabricate BiFeO3 ceramics and the influences of sintering conditions on the structural, dielectric, ferroelectric, and piezoelectric properties were investigated. It was found that high-density and pure-phase BiFeO3 ceramics could be successfully achieved through the two-step sintering method by optimizing the sintering conditions. Furthermore, ferroelectricity and piezoelectricity were also improved by the two-step sintering method. The pure-phase BiFeO3 ceramics obtained at T1=850 °C and T2=750 °C exhibited high resistivity (1.57×106 Ω.m), large remanent polarization (Pr=0.80μC/cm2) and strong piezoelectric activity (d33=42pC/N). All these results indicated that the two-step sintering method was an effective way to improve the properties of the BiFeO3 ceramics.

Two groups of barium titanate (BaTiO3) ceramics with high piezoelectric coefficient (d 33) have been successfully fabricated by the conventional solid-state reaction technique under different sintering atmospheres. The influences of sintering atmosphere on piezoelectric grain-size effects were systematically investigated. It was found that d 33 first increases then decreases with the increase of grain size (g) for both two groups of ceramics. However, the d 33 value reaches the maxima (501pC/N) at g = 1.13 µm for the samples sintered under the air sintering atmosphere (BaTiO3–Air). The samples sintered under the oxygen atmosphere (BaTiO3–O2) exhibit a large d 33 (>450pC/N) plateau at g from 0.98 to 7.30 µm. The experimental results indicated that the piezoelectric grain-size effects of BaTiO3 ceramics were strongly affected by the sintering atmosphere. Related mechanisms may be attributed to the variations of the domain configuration under different sintering atmospheres.

This paper presents a turbine load-sharing and load-shedding system for an islanded liquefied natural gas facility in Australia. The system includes three independent and redundant load-shedding schemes: process-based contingency load shedding with predefined load group and load pairs, high-speed underfrequency-based load shedding, and progressive overload shedding with system frequency supervision. In addition to the load-shedding schemes, the site includes a generation control system with frequency control, voltage control, automatic synchronization, and turbine load-sharing schemes. A breaker-and-a-half configuration complicates the fast load-shedding scheme. Results from hardware-in-the-loop testing are shared.

Carbon aerogels are among the most attractive porous carbon materials currently, but their real-world applications are greatly limited by their high cost, complicated preparation process and low mechanical properties. Herein, we report a very facile route to prepare lightweight but mechanically strong carbon aerogel monoliths (CAMs), through a sol-gel polymerization of linear phenolic resin and hexamethylenetetramine (HMTA), followed by ambient pressure drying and carbonization. The good capability of linear phenolic resin with ethanol could induce the formation of large polymer particle and good particle connectivity, affording robust network to suppress the collapse during the ambient drying. The synthesis is scalable and flexible, permitting a facile tailor of density, porous structure and mechanical strength by adjusting the ratio of phenolic resin to HMTA and phenolic resin concentration. The obtained CAMs possess macroporous/microporous hierarchical structure with low density as low as 0.07 g cm−3, high mechanical strength of 0.9–5.0 MPa and low thermal conductivity (0.032–0.069 W m−l K−1). Further CO2 activation can greatly develop the microporosity without sacrificing the monolithic structure. Moreover, as-prepared CAMs can be fabricated in large sizes, as well as being post-machined into many shapes and sizes for potential applications.

Lead-free piezoelectric ceramics Sr1.85Ca0.15Na1−xKxNb5O15 (0.00≤x≤0.40) were prepared using the conventional solid state reaction method. The structural, dielectric and piezoelectric properties were systematically studied. All the ceramics are single orthorhombic tungsten bronze phase at room temperature, and the lattice constants increase with K+ content. The dielectric spectra of each composition had two dielectric anomalies. The Curie temperature Tc gradually decreases from 291 °C to 266 °C as x increase from 0.00 to 0.40, and the transition temperature Ts from orthorhombic phase to tetragonal phase increases from 39 °C to 109 °C. With increasing K+ contents, the piezoelectric coefficient d33 increases rapidly initially, reaches a maximum and then gradually decreases. The highest piezoelectric performance was obtained at x=0.10, with piezoelectric coefficient d33=114 pC/N. Mechanisms that lead to the enhancement of d33 were discussed from the viewpoint of polarization and crystal structure.

This paper presents a centralized microgrid control system for effective operation of wind turbines and diesel engines coupled to a flywheel electrical storage component on Saint Paul Island. The wind turbines have sufficient capacity to support the entire island without using the diesel engines, allowing the formation of an islanded power system completely powered by renewables. The proposed strategy includes use of the flywheel, wind turbines, and diesel generators to attain survivability and resilience. The strategy is challenged and validated against different low to turbulent wind gust profiles and low to peak loading. Multiple permissive-based decoupling schemes, tie-flow controls, and heat load trading features are implemented. The tie-line flow control/heat load trading is operated in tandem with local diesel generators and wind turbines to maintain a minimum flow from the utility. The control system was tested using hardware-in-the-loop (HIL) with a simplified electrical model of Saint Paul Island.

More than 71% of the earth’s surface area is occupied by ocean, and the shipping has become one of the most common forms of transportation. There are many applications for rapid on-site detection in ships and marine engineering in general. However, owing to the limited space and environmental conditions, large-scale laboratory equipment cannot be utilized on ships and offline examination methods cannot meet the needs for rapid detection and analysis of problems. Microfluidic technologies provide an excellent platform where various biological and chemical reactions can be completed on very small microfluidic chips. The combination of microfluidic technologies and ship and marine engineering will have important theoretical significance and practical value. These applications mainly include ballast water analysis, lubricating oil analysis, monitoring oil spill, ship exhaust gas detection and ship sewage detection. Therefore, in this paper, we have summarized the current applications of microfluidic technologies in ships and marine engineering and suggested prospects for the potential research directions in the future.

In this letter, we analyze how to decode LDPC codes with non-equiprobable binary symbols. For such symbols, we need to modify the conventional Tanner graph, because the message passing from check nodes to information bits and to parity check bits are diverse. In other words, in conventional Tanner graph, the message passing along two directions are identical, while in our case, the message along the forward direction and backward direction are different. A method to optimize signaling constellation which maximizes the channel mutual information is presented as well. In the numerical section, symbols with prior probabilities (0.3,0.7) could gain 0.72 dB in performance if we replace equal space constellation with optimal constellation. Several cases of short LDPC codes (N, K =1024, 512) are explored and gain almost 0.4 dB. The simulation shows that additional gain of only 0.2 dB could be attainable, if optimal source coding is achievable.

The spread and invasion of many nonindigenous species in the ship’s ballast water around the world has been a hazard and threat to ecology, economy, and human health. The rapid and accurate detection of marine invasive species in ship’s ballast water is essential. This article is aimed at analysing ballast water quality by means of a changeable microfluidic chip detector thus comply with the D-2 standard of ship’s ballast water management and sediment convention. The detection system was designed through the integration of microfluidic chip technology, the impedance pulse sensing and LED light induced chlorophyll fluorescence (LED-LICF) detection. This system can measure the number, size, shape, and volume of targeted microorganisms, and it can also determine the chlorophyll fluorescence intensity, which is an important factor in analysing the activity of phytoplankton. The targeted samples were Chlorella volutis, Dunaliella salina, Platymonas subcordiformis, Chrysophytes, Escherichia coli, and Enterococci. The whole detection or operation can be accomplished through online detection in a few minutes with using micron volume of the sample solution. The valid data outputs are simultaneously displayed in terms of both impedance pulse amplitudes and fluorescent intensity signals. The detection system is designed for multi-sizes real time detection through changing the microchannel sizes on the microfluidic chip. Because it can successfully detect the label-free microorganisms, the system can be applicable to in-situ detections with some modifications to the system.

The dissolution behaviours of lumpy coal and coke used in COREX gasifier in molten iron were investigated. The time-dependent interfacial reaction products were observed and the microcrystalline structures of solid fuels were identified. The results showed that the rate of carbon dissolution in molten iron using lumpy coal was significantly less than that when the coke was used. The ordered carbon microcrystalline at the reaction interface would be a priority to dissolve. The interface thickness of the eroded coke was larger than that of coal char due to the uneven microtexture distribution and the irregular pore structure. The amount of attachments on the erosion interface was positively related to the dissolution time regardless of the type of solid fuel. Although the amount of ash phases on the coal char surface was less than that on the coke surface, the final carbon content in molten iron and dissolution rate of coal char were still less due to its microstructure of carbon matrix. This study contributes to understanding the dissolution mechanism of the solid fuels used in COREX gasifier and improving the fuel utilization.

The improved device of coke gasification reaction is employed to investigate the change rules of coke reactivity and strength after reaction, as well as coke microstructure, and pore size. Thermodynamic calculation is conducted to illustrate the imparity of the reaction between carbon with CO2 or H2O. The results show that H2O can promote the coke gasification reaction, and the coke reactivity (CRI) increases with the increasing φ(H2O), while the coke strength (CSR) has the opposite trend. The SEM observation results show that the interior and surface parts of cokes are all eroded at difference degrees after reaction, and the interior part of coke generates more large pores after reacted with pure CO2. While the interior part of coke that reacted with CO2 and H2O gas mixture generate more small pores, and the surface part is severely damaged. Moreover, the area percentage of oversized pores of coke gasified with gas mixture is larger than that of the coke gasified with pure CO2. The results of XRD indicate that the graphitization of coke increases after the reaction and reaches the highest when the reaction atmosphere is the CO2-H2O gas mixture, mainly due to the promotion of H2O to the consumption of isotropy.

In this paper, we illustrate how to use simple LDPC codes to build a GPRAM prototype. We overview the GPRAM system and design principles. We then map the design into a problem. We demonstrate an experimental solution. We further introduce a switch function in the system, which will allow us to perform revision in code structures in GPRAM prototype in future. In this study many interesting features begin to merge and some of them may have bio-implication which needs to be further explored.