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We present a physics-informed deep learning model for the transient heat transfer analysis of three-dimensional functionally graded materials (FGMs) employing a Runge–Kutta discrete time scheme. Firstly, the governing equation, associated boundary conditions and the initial condition for transient heat transfer analysis of FGMs with exponential material variations are presented. Then, the deep collocation method with the Runge–Kutta integration scheme for transient analysis is introduced. The prior physics that helps to generalize the physics-informed deep learning model is introduced by constraining the temperature variable with discrete time schemes and initial/boundary conditions. Further the fitted activation functions suitable for dynamic analysis are presented. Finally, we validate our approach through several numerical examples on FGMs with irregular shapes and a variety of boundary conditions. From numerical experiments, the predicted results with PIDL demonstrate well agreement with analytical solutions and other numerical methods in predicting of both temperature and flux distributions and can be adaptive to transient analysis of FGMs with different shapes, which can be the promising surrogate model in transient dynamic analysis.

Background The choice of mitral valve surgical approach has always been a difficult problem in patients with small left atrium. Case presentation We report a case of a patient with Marfan syndrome who underwent the David operation and mitral annuloplasty. The patient had a small left atrium, so we severed the superior vena cava and opened the interatrial groove and left atrial dome. This method allows for excellent exposure of the mitral valve and subvalvular apparatus, enabling a successful operation. Conclusion The interatrial groove-left atrial dome approach provides an option for patients with a small left atrium undergoing mitral valve surgery.

In order to maintain the aerodynamic shape of morphing wing, this paper focuses on studying the out-of-plane stiffness of Kevlar/carbon fiber hybrid composite skins for a shear variable-sweep wing. Based on the shear deformation theories, the nonlinear mathematical model is developed for the out-of-plane stiffness of composite skins with the in-plane shear loading, the aerodynamic loading and the thermal loading. The material properties of Kevlar/carbon fiber hybrid composite skins are estimated through a micromechanical model and are assumed to be contact coefficient-dependent between reinforcing fiber and rubber matrix. Based on the principle of virtual work and the fundamental lemma of calculus of variations, the motion equations are derived and the closed-form solutions are obtained for sutured composite skins on the framework. Displacement fields of three different shear deformation theories, namely, classical plate theory (CPT), parabolic shear deformation theory (PSDT), sinusoidal shear deformation theory (SSDT), have been presented and compared. A systematic comparison between the theoretical solutions and experimental results is carried out to validate the excellent accuracy and reliability of the numerical evaluations. The effects of geometric and material parameters on the out-of-plane stiffness of composite skins are systematically studied.

Vanadium-bearing titanomagnetite carbon composite briquette (VTM-CCB) was proposed as an innovative and promising blast furnace burden to realize low-carbon and high-efficiency ironmaking. To optimize the compositions of VTM-CCB based on its softening–melting–dripping characteristics, the evolution behavior and mechanisms of VTM-CCB in cohesive zone and dripping zone were investigated by conducting softening–melting tests under blast furnace conditions. The results show that the structure evolution of VTM-CCB in softening–melting process is correlated to the molten slag, metallic iron, liquid iron, and residual carbon. With the molar ratio of the fixed carbon to the reducible oxygen in iron oxides (FC/O ratio) ranging from 0.8 to 1.0, the VTM-CCB tends to form dense structure and accelerate the softening and melting. With increasing the FC/O ratio to 1.2 and 1.4, the VTM-CCB tends to form concentric circular structure, which could suppress the collapse of packed bed, shift down the location of core cohesive zone, and improve the gas permeability. Although the appropriate increase in FC/O ratio could improve the softening–melting performance of VTM-CCB, a higher FC/O ratio could also promote the precipitation of Ti(C,N), thereby thickening the molten mixtures and deteriorating the dripping behavior. Fully considering the softening–melting–dripping characteristics and permeability, the appropriate FC/O ratio of VTM-CCB should be controlled in the range of 1.0–1.2.

Aiming at the problem that the membrane structure is prone to creases in the process of folding and compaction, a proxy model is used to replace the creases to introduce initial defects for the folded membrane to realize the research of the deployment simulation of the membrane. Based on the finite-element method, the Z-folding and deploying process of the membrane is simulated and the elastic-plastic behavior of the crease is parameterized. The ABAQUS connector is used to replace the crease area of the membrane to simulate the characteristics of the crease and its effectiveness is verified. The deployment of Miura-ori membrane is simulated to explore the influence of force driving and constant-speed driving on the deploying process and deployment results of the membrane. In view of the self-contact phenomenon in the membrane deploying process when driven at a constant-speed, referring to the motion trajectory of the membrane loading corner of the force drive, a step-speed driving method is proposed. The research results show that using a step-speed to drive the deployment of folded membrane can reduce the curvature of the membrane surface, solve the problem of membrane self-contact, and eliminate the phenomenon of stress concentration of membrane surface. In addition, compared with other driving methods, the step-speed driving method has a significant advantage in improving the stability of the deploying process of a membrane.

For soil liquefaction prediction from multiple data sources, this study designs a hierarchical machine learning model based on deep feature extraction and Gaussian Process with integrated domain adaption techniques. The proposed model first combines deep fisher discriminant analysis (DDA) and Gaussian Process (GP) in a unified framework, so as to extract deep discriminant features and enhance the model performance for classification. To deliver fair evaluation, the classifier is validated in the approach of repeated stratified K-fold cross validation. Then, five different data resources are presented to further verify the model’s robustness and generality. To reuse the gained knowledge from the existing data sources and enhance the generality of the predictive model, a domain adaption approach is formulated by combing a deep Autoencoder with TrAdaboost, to achieve good performance over different data records from both the in-situ and laboratory observations. After comparing the proposed model with classical machine learning models, such as supported vector machine, as well as with the state-of-art ensemble learning models, it is found that, regarding seismic-induced liquefaction prediction, the predicted results of this model show high accuracy on all datasets both in the repeated cross validation and Wilcoxon signed rank test. Finally, a sensitivity analysis is made on the DDA-GP model to reveal the features that may significantly affect the liquefaction.

Space deployable mast, which is a supporting mechanism, especially for a space telescope, requires high repeatability. In this study, a deployed space tri-prism mast was taken as the research object, and the change of a tensional cable’s tension force was equivalent to an external load. Based on the accurate stiffness model of the mast, the repeatability of the tri-prism mast was calculated by using the Monte Carlo method. Then, the influences of the number of units, the change in the tension force, the thickness of the linkage, and the radius of the tensional cable on the repeatability of the tri-prism mast were studied. Moreover, the correctness of the analytical model was verified by the repeatability experiments. Results demonstrated that the proposed method could be used to analyze the repeatability of tri-prism mast. This study provided references and suggestions for the design of high-precision space deployable mast.

The carburization roasting treatment followed by the magnetic separation is an effective way to utilize low-grade siderite, in which the sodium sulfate additive plays an important role. In order to investigate the role of sodium sulfate additive, the present study fixes its particular attention on the function mechanism of sodium sulfate additive during the preheating treatment, carburization, and separation process. The results show that sodium sulfate additive can enhance the oxidation, reduction, and carburization reactions of siderite pellet, which dramatically increases the carburization rate and degree of siderite pellet. Besides, sodium sulfate additive can significantly improve the growth of iron carbide particle, transform the dense gangue into loose gangue, and produce the cracks inside pellet, which greatly promotes the separation of iron carbide and gangue. In the whole process, preheating treatment at high temperature is a necessary process to intensify and maintain the additive’s effects.

Small interfering RNAs (siRNAs) are essential for proper development and immunity in eukaryotes1. Plants produce siRNAs with lengths of 21, 22 or 24 nucleotides. The 21- and 24-nucleotide species mediate cleavage of messenger RNAs and DNA methylation2,3, respectively, but the biological functions of the 22-nucleotide siRNAs remain unknown. Here we report the identification and characterization of a group of endogenous 22-nucleotide siRNAs that are generated by the DICER-LIKE 2 (DCL2) protein in plants. When cytoplasmic RNA decay and DCL4 are deficient, the resulting massive accumulation of 22-nucleotide siRNAs causes pleiotropic growth disorders, including severe dwarfism, meristem defects and pigmentation. Notably, two genes that encode nitrate reductases—NIA1 and NIA2—produce nearly half of the 22-nucleotide siRNAs. Production of 22-nucleotide siRNAs triggers the amplification of gene silencing and induces translational repression both gene specifically and globally. Moreover, these 22-nucleotide siRNAs preferentially accumulate upon environmental stress, especially those siRNAs derived from NIA1/2, which act to restrain translation, inhibit plant growth and enhance stress responses. Thus, our research uncovers the unique properties of 22-nucleotide siRNAs, and reveals their importance in plant adaptation to environmental stresses. Characterization of 22-nucleotide short interfering RNAs in plants finds that they accumulate in response to environmental stress, causing translational repression, inhibition of plant growth and enhanced stress responses.

Background Data on the association of breakfast habits and changes in cardiometabolic markers in children are limited. Methods In total, 6964 children aged 6–13 years from Beijing, Shanghai, Chongqing, Jinan, Harbin, and Guangzhou were included in the final analysis. Daily consumption, consumption of ≥3 food groups, and at-home consumption were defined as healthy breakfast habits. Blood pressure, % fat mass, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, glucose, and 50-m × 8 shuttle run were measured at baseline (May 2009) and follow-up (May 2010). Clustered cardiometabolic risk score (CCRS) was computed by summing Z scores of five components: % fat mass, systolic blood pressure, glucose, TC to HDL-C ratio, and triglyceride. Results Children who ate breakfast daily had a higher decrease in TC to HDL-C ratio and a higher increase in HDL-C compared with breakfast skippers (both P values

The development of phononic crystals, especially their interaction with topological insulators, allows exploration of the anomalous properties of acoustic/elastic waves for various applications. However, rapidly and inversely exploring the geometry of specific targets remains a major challenge. In this work, we show how machine learning can address this challenge by studying phononic crystal beams using two different inverse design schemes. We first develop the theory of phononic beams using the transfer matrix method. Then, we use the reinforcement learning algorithm to effectively and inversely design the structural parameters to maximize the bandgap width. Furthermore, we employ the tandem-architecture neural network to solve the training-difficulty problem caused by inconsistent data and complete the task of inverse structure design with the targeted topological properties. The two inverse-design schemes have different adaptabilities, and both are characterized by high efficiency and stability. This work provides deep insights into the combination of machine learning, topological property, and phononic crystals and offers a reliable platform for rapidly and inversely designing complex material and structure properties.

A C-cross section thin-walled composite deployable boom (C boom) can be flattened and coiled elastically. Furthermore, C boom can be deployed by releasing stored strain energy. Finite element (FE) models of C booms are constructed based on a nonlinear explicit dynamics analysis. The full simulation is divided into six consecutive steps: flattening, end-compacting, releasing, coiling, holding, and deploying around a hub. An optimal design method for the coiling and deploying of the C boom is presented based on the response surface method (RSM). Twenty-seven sample points are obtained by using a full-factorial design of experiment method. Surrogate models of the maximum moment and stress during the fully simulated process, including the mass of the C boom, are created by the RSM. The maximum moment and mass are set as objectives, and the maximum stress is set as a constraint to increase deploying statue stiffness and enhance use times. A multi-objective optimization design of the C boom is performed by sequential quadratic programming algorithm. Lastly, FE models for the optimal design are built to validate the accuracy of the optimization and the response surface results.

This study explores the roles of Fe2O3 (3–5 wt%) and/or MgO (0.6–2.4 wt%) on the crystallization behaviour, microstructure, sinterability and mechanical properties of 17.02CaO-7.04Al2O3-58.84SiO2 (CAS, wt%) glass-ceramics. With increasing Fe2O3 and/or MgO contents, the peak temperature of glass crystallization decreased, and the main crystal phase (wollastonite) was suppressed, while the secondary phases of hardystonite and diopside were crystallized and promoted. Wollastonite crystals grew larger, and their distribution became scattered as Fe2O3 and/or MgO contents increased. The concentrations of elemental Fe and Zn in the glass matrix influence the formation of hardystonite (Ca2ZnSi2O7), and Mg2+ can participate in the formation of diopside and melilite-type solid solution Ca2ZnSi2O7-Ca2MgSi2O7. Vickers hardness was decreased by the increasing amount of glass matrix while density was increased. The optimum heat treatment temperature range of the CAS glass-ceramics was narrowed by the addition of Fe2O3 and/or MgO due to rapid crystallization and a degree of fusion or overburning.

Leaf senescence, the last stage of leaf development, is a type of postmitotic senescence and is characterized by the functional transition from nutrient assimilation to nutrient remobilization which is essential for plants’ fitness. The initiation and progression of leaf senescence are regulated by a variety of internal and external factors such as age, phytohormones, and environmental stresses. Significant breakthroughs in dissecting the molecular mechanisms underpinning leaf senescence have benefited from the identification of senescence-altered mutants through forward genetic screening and functional assessment of hundreds of senescence-associated genes (SAGs) via reverse genetic research in model plant Arabidopsis thaliana as well as in crop plants. Leaf senescence involves highly complex genetic programs that are tightly tuned by multiple layers of regulation, including chromatin and transcription regulation, post-transcriptional, translational and post-translational regulation. Due to the significant impact of leaf senescence on photosynthesis, nutrient remobilization, stress responses, and productivity, much effort has been made in devising strategies based on known senescence regulatory mechanisms to manipulate the initiation and progression of leaf senescence, aiming for higher yield, better quality, or improved horticultural performance in crop plants. This review aims to provide an overview of leaf senescence and discuss recent advances in multi-dimensional regulation of leaf senescence from genetic and molecular network perspectives. We also put forward the key issues that need to be addressed, including the nature of leaf age, functional stay-green trait, coordination between different regulatory pathways, source-sink relationship and nutrient remobilization, as well as translational researches on leaf senescence.

Background Acute type A aortic dissection with a dissection flap extending into the sinus segment often involves the commissures and the coronary ostia. In most cases, the intimal flap must be retained in order to restore aortic valve competence and reconstruct the coronary ostia. Residual dissection flap has the potential risks of proximal bleeding and adverse effects on long-term durability. We established a novel technique to reconstruct the aortic root using a pericardial autograft and significantly reduce remnant dissection tissues. Case presentation A 50-year-old female was admitted to our center with acute anterior chest pain and backache lasting about 10 h. Computed tomographic (CT) scans showed type A aortic dissection, with both coronary ostia being involved. Doppler echocardiography showed moderate aortic insufficiency. The dissection intimal flap was removed to the normal aorta wall near the annulus at the noncoronary sinus, leaving a 5 mm rim of intimal flap near the commissures and coronary ostia. Using a pericardial patch as a new aortic wall to reconstruct the root while preserving the aortic adventitia to fix and strengthen the new pericardial aortic wall. Ascending aorta and total arch replacement combined with frozen elephant trunk procedure was performed at the same time. The patient got an uneventful postoperative course. Conclusion Aortic root repair with a pericardial autograft is a safe and effective technique to treat acute type A dissection involving the sinus. Using this technique, residual dissection tissues could be significantly reduced, which subsequently decreases the risk of proximal bleeding and hence increases long-term durability.

Deployable composite triangle rollable and collapsible (TRAC) booms can be flattened and wrapped elastically, and then can be self-deployed by releasing stored strain energy around a hub. Composite ultra-thin TRAC booms have a higher potential application value for driving larger membrane antenna and solar sails. Wrapping and fully deploying status modal analysis are performed using nonlinear explicit dynamics analysis. The wrapping simulation is divided into three consecutive steps: flattening, end clamping, and wrapping around the hub. An optimal design method for the wrapping of the TRAC boom is presented based on the response surface theory. Then, sample points are created based on a three-level full factorial design of the experimental method. Surrogate models of the wrapping peak moment, maximum stress, and fully deploying fundamental frequency are constructed using quadratic polynomials. To enhance using times, the maximum stress is set as a constraint. Considering the high deploying stability and sufficient driving moment, the wrapping peak moment and deploying fundamental frequency are set as objectives to obtain the optimal design. Furthermore, a parametric study of the geometric parameters is performed to determine the effect on the wrapping behaviors and fully deploying stability.

Melatonin is a crucial neurohormone synthesized in the pineal gland that influences the physiology of animals. The molecular mechanism of norepinephrine control of the synthesis of melatonin is well documented; however, few reports have described the effects of epinephrine on the synthesis of melatonin. In this study, the effect of epinephrine on melatonin synthesis was investigated by adding different concentrations of epinephrine or norepinephrine to broiler pineal glands cultured in vitro. In addition, we investigated how epinephrine regulates the synthesis of melatonin and the transcription of the key melatonin synthesis enzyme AANAT. We determined the abundance of melatonin, norepinephrine, and epinephrine in broiler serum and the mRNA expression levels of key enzymes under different light conditions. The minimum concentrations of epinephrine and norepinephrine required to recover the melatonin synthesis rhythm in pineal cells were 10−13 and 10−11 mol/L, respectively. Under various light durations, epinephrine reached maximum levels two hours earlier than melatonin. These results demonstrate for the first time that epinephrine can increase the synthesis of melatonin by increasing the transcription of AANAT.

This study presents a process for recovering aluminum from aluminum dross (an industrial waste product) via an alkali roasting process and using it to synthesize mesoporous γ-alumina. The results show that the inherent chlorides in dross (KCl and NaCl) reduce Al extraction efficiency and should be removed first by water leaching. Use of salt-free dross increases the Al extraction rate (from 85 to 96 pct) within 90 minutes alkali roasting at 923 K (650 °C). In addition, an ammonium bicarbonate byproduct can be obtained from water leaching due to the hydrolysis of AlN, which can be used as a precipitating agent in the boehmite sol preparation. Synthesis of mesoporous γ-alumina was carried out by the sol-gel method with EO20PO70EO20 (P123) as a template. The prepared mesoporous γ-alumina was characterized as having a disordered mesostructure with a high pore volume of 1.02 cm3/g and surface area of 312 m2/g. Thus, we achieved highly efficient utilization of aluminum dross and yielded products with high added value. Mesoporous γ-alumina has potential applications in environmental remediation and catalysis.

The Sr doped Ta2O5 nanorods films were formed on pure tantalum by a facile two step hydrothermal method. The tantalum substrates were hydrothermally treated firstly in the mixed solution of HF and H2O2 and then in strontium acetate (SA) solution. The morphologies, phase components, surface chemical species and apatite-inducing ability of the Ta2O5 nanorods films before and after Sr doped were investigated. The obtained results demonstrate that Ta2O5 nanorods can be only formed on tantalum at the temperature higher than 220 °C when hydrothermally treated in 0.4 M HF and 2 M H2O2. By prolonging the HT time to 6, 9 and 24 h, the nanorods become longer and the diameter become coarser, and after 24 h of HT, the diameter of the nanorod is 24.9 ± 0.9 nm. The atom percent of Sr element is 0.00, 1.61, 4.08, 7.71 and 11.23% respectively when Ta2O5 nanorods films were hydrothermally treated in SA solution of 0.01, 0.05, 0.1, 0.2 and 0.3 M, and Ta2O5 nanorods films changes in morphology when hydrothermally treated in 0.2 and 0.3 M SA solution though with high amount of Sr doped. The Ta2O5 nanorods are grown along the [001] direction and Sr element is incorporated into the lattice as the chemical state of Sr2+. The Sr doped Ta2O5 nanorods film can induce apatite for less than 9 days while that without Sr doped can not induce apatite even after immersion in SBF for 17 days. The Sr doped Ta2O5 nanorods film can efficiently improve the apatite-inducing ability in SBF which is maybe attributed to the release of Sr ion.

Short-chain carboxylic acids and their derivatives are widely utilized in all aspects of our daily life. Given their specific functional groups, these molecules are also utilized in fine chemical synthesis. The traditional petroleum-based carboxylate production methods are restricted by petrol shortage and environmental pollution. Renowned for their more sustainable processes than traditional methods, biotechnological methods are preferred alternatives and have attracted increasing attention. However, the industrial application of biotechnological methods is currently limited by low factors: low productivity and low yield. Therefore, understanding the regulation of carboxylate accumulation will greatly enhance the industrial biotechnological production of short-chain carboxylate acids. The carboxylate transporter plays a crucial role in transmembrane uptake and secretion of carboxylate; therefore, regulating these transporters is of high academic and application relevance. This review concentrates on the physiological roles, regulation mechanisms, and harnessing strategies of Jen and AcpA orthologs in fungi, which provide potential clues for the biotechnological production of short-chain carboxylic acids with high efficiency.

Equal channel angular pressing (ECAP) was performed on extruded pure Mg, which was clad with a drilled pure Fe coat through an ECAP die to produce a pure Mg sample without obvious cracks at room temperature. After one-pass ECAP, the grain size decreased because of basal slip activation during the dynamic plastic deformation but the microstructure became inhomogeneous. The deformed texture was less scattered and inclined by ~20° from the normal direction toward the extruded direction, and low angle boundaries increased continuously. The mechanical properties decreased slightly as a result of the combined effect from a more refined microstructure and a weaker texture.

This study presents a new technique that uses high-temperature chloridizing -reduction-magnetic separation to recover iron from pyrite cinder containing non-ferrous metals. The effects of the reduction temperature, reduction time, and chlorinating agent dosage were investigated. The optimized process parameters were proposed as the following: CaCl2 dosage of 2 pct, chloridizing at 1398 K (1125 °C) for 10 minutes, reducing at 1323 K (1050 °C) for 80 minutes, grinding to a particle size of 78.8 pct less than 45 μm, and magnetic field intensity of 73 mT. Under the optimized conditions, the Cu, Pb, and Zn removal rates were 45.2, 99.2, and 89.1 pct, respectively. The iron content of the magnetic concentrate was 90.6 pct, and the iron recovery rate was 94.8 pct. Furthermore, the reduction behavior and separation mechanism were determined based on microstructure and phase change analyses using X-ray powder diffraction, scanning electron microscope, and optical microscopy.

Viscosity is considered to be a significant indicator of the metallurgical property of blast furnace (BF) slag. A model for viscosity prediction based on the partial least-squares regression of varietal quantity reference points is presented in this article. The present model proposes a dynamic regional algorithm for reference point selection. The study applied the partial least-squares regression to establish the dynamic regional viscosity prediction model on the basis of limited discrete points data. Then an actual prediction was carried out with a large amount of viscosity data of real and synthesized BF slags that was obtained from a certain steel plant in China. The results show that this advanced method turns out to be satisfactory in the viscosity prediction of BF slags with a low averaging error and mean value deviation.

Capture is a key component for on-orbit service and space debris clean. The current research of capture on-orbit focuses on using special capture devices or full-actuated space arms to capture cooperative targets. However, the structures of current capture devices are complex, and both space debris and abandoned spacecraft are non-cooperative targets. To capture non-cooperative targets in space, a lightweight, less driven under-actuated robotic hand is proposed in this paper, which composed by tendon-pulley transmission and double-stage mechanisms, and always driven by only one motor in process of closing finger. Because of the expandability, general grasping model is constructed. The equivalent joint driving forces and general grasping force are analyzed based on the model and the principle of virtual work. Which reveal the relationship among tendon driving force, joint driving forces and grasping force. In order to configure the number of knuckles of finger, a new analysis method which takes the maximum grasping space into account, is proposed. Supposing the maximum grasped object is an envelope circle with diameter of 2.5 m. In the condition, a finger grasping maximum envelope circle with different knuckles is modeled. And the finger lengths with corresponding knuckles are calculated out. The finger length which consists of three knuckles is the shortest among under-actuated fingers consists of not more than five knuckles. Finally, the principle prototype and prototype robotic hand which consists of two dingers are designed and assembled. Experiments indicate that the under-actuated robotic hand can satisfy the grasp requirements.

Because of the limited space of the launch rockets, deployable mechanisms are always used to solve the phenomenon. One dimensional deployable mast can deploy and support antenna, solar sail and space optical camera. Tape-spring hyperelastic hinges can be folded and extended into a rod like configuration. It utilizes the strain energy to realize self-deploying and drive the other structures. One kind of triangular prism mast with tape-spring hyperelastic hinges is proposed and developed. Stretching and compression stiffness theoretical model are established with considering the tape-spring hyperelastic hinges based on static theory. The finite element model of ten-module triangular prism mast is set up by ABAQUS with the tape-spring hyperelastic hinge and parameter study is performed to investigate the influence of thickness, section angle and radius. Two-module TPM is processed and tested the compression stiffness by the laser displacement sensor, deploying repeat accuracy by the high speed camera, modal shape and fundamental frequency at cantilever position by LMS multi-channel vibration test and analysis system, which are used to verify precision of the theoretical and finite element models of ten-module triangular prism mast with the tape-spring hyperelastic hinges. This research proposes an innovative one dimensional triangular prism with tape-spring hyperelastic hinge which has great application value to the space deployable mechanisms.

Multi-attribute group decision making is generally applied in the language environment, and how to obtain the attribute weights has also been the focus of attention recently. This paper proposes a new method based on the theory of linguistic operator and the entropy weight method to determine the attribute weights in the linguistic multi-attribute group decision making: the linguistic entropy weight method. At the same time, the missing values are completed. The method used to complete missing values not only shows the average of the evaluation values, but also avoids the impact of the value fluctuations, so it has the validity and accuracy. Finally we demonstrate its applicability through the evaluation example of the scenic spot order.

We investigated a control model of hypoglycemia-exposed brain tissues from a small series of patients with insulinoma, immediately dissect them, and perform a differential cold centrifugation to obtain gliosomes and examine alterations of glycogenolytic mechanisms. The BB as well as MM isoforms of glycogen phosphorylase enzymatic protein expression remained unaltered between insulinoma and control subjects within the gliosomes. However, the glycogen phosphorylase remained in a form that was potentially activated several folds on placing the gliosomes in a glucose-free medium. This was examined by its increased interaction with protein kinase A. Inhibitors of glycogen phosphorylase was used as controls. Furthermore, we demonstrated that glucose-depleted medium enhanced production of both ATP and lactate by the gliosomes. It is possible that a portion of glucose obtained from glycogen breakdown was circuited through glycolytic pathways to generate ATP. It has been reported earlier that ATP within gliosomes plays a major role in glutamate uptake, thus potentially preventing seizure during active bouts of hypoglycemia. Lactate shuttle from astrocytes is a potential mechanism to balance neuronal bioenergetics during events of hypoglycemia. Newer approaches to pharmacologically modulate glycogen phosphorylase may prove to be rational approach for neuroprotective therapy in this common clinical syndrome of hypoglycemia.

Both the friction caused by the preload in locked joints and the impact caused by clearance in unlocked joints cause energy dissipation in jointed deployable structures. The energy dissipation of locked joints is studied by analyzing the force on the infinitesimal body of the joint. The jointed beam with an unlocked joint is simplified into an impact mass-spring model with clearance, which considers the coefficient of restitution of impact. The energy dissipations of the joint caused by friction and clearance are transformed into damping ratios by Taylor expansion. Then, the effects of pressure, clearance and the dynamic parameters on the damping of joints are analyzed by utilizing the damping ratio formulation. The damping ratio increases with the preload and the clearance. To validate the damping ratio formulation of joints, experiments on a single jointed beam with preload and double jointed beams with clearance are conducted. Comparison between the experimental results and the model simulation results shows that the friction and impact damping models are accurate for the dynamic calculation of deployable structures. Furthermore, the damping ratio formulations can be directly introduced into the design and dynamic analysis of deployable structures.

One of the most striking properties of natural image statistics is the scale invariance. Some earlier studies have assumed that the kurtosis of marginal band pass filter response to be constant throughout scales for a natural image. In our study, this assumption is loosened by adaptively estimating an optimal filter computation whose response distributions through scales have the least Kullback---Leibler divergence. The adaptive filter and its responses characterize the scale-invariance property more accurately and effectively and are further utilized to model the statistics scale-invariance prior in this paper. Extensive experiments on image super-resolution and de-noising manifest that the explored natural images scale-invariance prior model achieves significant performance improvements over the current state-of-the-art schemes.

We present a self-powered, high-performance graphene-enhanced ultraviolet silicon Schottky photodetector. Different from traditional transparent electrodes, such as indium tin oxides or ultra-thin metals, the unique ultraviolet absorption property of graphene leads to long carrier life time of hot electrons that can contribute to the photocurrent or potential carrier-multiplication. Our proposed structure boosts the internal quantum efficiency over 100%, approaching the upper-limit of silicon-based ultraviolet photodetector. In the near-ultraviolet and mid-ultraviolet spectral region, the proposed ultraviolet photodetector exhibits high performance at zero-biasing (self-powered) mode, including high photo-responsivity (0.2 A W−1), fast time response (5 ns), high specific detectivity (1.6 × 1013 Jones), and internal quantum efficiency greater than 100%. Further, the photo-responsivity is larger than 0.14 A W−1 in wavelength range from 200 to 400 nm, comparable to that of state-of-the-art Si, GaN, SiC Schottky photodetectors. The photodetectors exhibit stable operations in the ambient condition even 2 years after fabrication, showing great potential in practical applications, such as wearable devices, communication, and “dissipation-less” remote sensor networks.

Flexible tape-spring hinges can be folded elastically and are able to self-deploy by releasing stored strain energy with fewer component parts and slight weights. This study presents a detailed investigation of the folding and deployment of single-layer tape-spring (SLTS) hinges and double-layer tape-spring (DLTS) hinges under pure bend loading. The material properties of tape-spring hinges are measured using an INSTRON machine. A DLTS hinge construction is created, and its moment-rotation relationship during quasi-static deployment is measured. An experiment is conducted to verify the validation of the numerical models for the DLTS hinges. The quasi-static deployment behavior of SLTS hinges and DLTS hinges is then analyzed using nonlinear finite element ABAQUS/Explicit solver, starting from the complete folded configuration. The DLTS hinge has good quasi-static deployment performances with regard to maximum stress (Sm), steady moment (M*) and the peak moment (Md) during the DLTS hinge quasi-static deployment. In addition, the sampling designs of the DLTS hinges are created based on a three-level full factorial design of experiments (DOE) method. The surrogate models of Sm, M* and Md of the DLTS hinges are derived using response surface method (RSM) to reduce the computational cost of quasi-static folding and deployment of numerical simulations. The Multiobjective optimization design (MOD) of the DLTS hinge is performed using modified non-dominated sorting genetic algorithm (NSGA-II) algorithm to achieve the optimal design. The finite element models for the optimal design based on numerical method are established to validate the optimization results.

Non-isothermal combustion kinetics of two kinds of low volatile pulverized coals (HL coal and RU coal) were investigated by thermogravimetric analysis. The results show that the combustibility of HL coal was better than that of RU coal, and with increasing heating rate, ignition and burnout characteristics of pulverized coal were improved. The volume model (VM), the random pore model (RPM), and the new model (NEWM) in which the whole combustion process is considered to be the overlapping process of volatile combustion and coal char combustion, were used to fit with the experimental data. The comparison of these three fitted results indicated that the combustion process of coal could be simulated by the NEWM with highest precision. When calculated by the NEWM, the activation energies of volatile combustion and coal char combustion are 130.5 and 95.7 kJ • mol−1 for HL coal, respectively, while they are 114.5 and 147.6 kJ • mol−1 for RU coal, respectively.

Viscosity is considered to be a significant indicator of the metallurgical property of blast furnace slag. An improved model for viscosity prediction based on the Chou model was presented in this article. The updated model has optimized the selection strategy of distance algorithm and negative weights at the reference points. Therefore, the extensionality prediction disadvantage in the original model was ameliorated by this approach. The model prediction was compared with viscosity data of slags of compositions typical to BF operations obtained from a domestic steel plant. The results show that the approach can predict the viscosity with average error of 9.23 pct and mean standard deviation of 0.046 Pa s.

The traditional artificial recognition methods for the blast furnace dust composition have several disadvantages, including a great deal of information to dispose, complex operation, and low working efficiency. In this article, a multifeature analysis method based on comprehensive image-processing techniques was proposed to automatically recognize the blast furnace dust composition. First, the artificial recognition and feature analysis, which included image preprocessing, Harris corner feature, Canny edge feature, and Ruffle feature analysis, was designed to build the template image, so that any unknown dust digital image could be tested. Second, the composition of coke, microvariation pulverized coal, vitric, ash, and iron from dust would be distinguished according to their different range of values based on the multifeature analysis. The method is valid for recognizing the blast furnace dust composition automatically, and it is fast and has a high recognition accuracy.

The high-temperature performance of iron ore fines is an important factor in optimizing ore blending in sintering. However, the application of linear regression analysis and the linear combination method in most other studies always leads to a large deviation from the desired results. In this study, the fuzzy membership functions of the assimilation ability temperature and the liquid fluidity were proposed based on the fuzzy mathematics theory to construct a model for predicting the high-temperature performance of mixed iron ore. Comparisons of the prediction model and experimental results were presented. The results illustrate that the prediction model is more accurate and effective than previously developed models. In addition, fuzzy constraints for the high-temperature performance of iron ore in this research make the results of ore blending more comparable. A solution for the quantitative calculation as well as the programming of fuzzy constraints is also introduced.

In order to increase the content of rare-earth oxides in magneto-optical glass and improve the Verdet constant, the rare-earth doped ternary Ga2O3-B2O3-SiO2(GBS) system magneto-optical glasses were prepared by the melt quenching technique. The influence of Tb3+ and Dy3+ ions on the structure of GBS glasses was investigated using FTIR, DSC and Faraday rotations. The experimental results showed that the content of rare-earth oxides in the glasses with the double incorporation of Tb2O3 and Dy2O3 was higher. The crystallization parameter β achieved the maximum 0.48 with Tb3+/Dy3+ content of 35mol%. Terbium oxide existed mainly in [TbO3] units in the glasses and [TbO4] units were converted into [TbO3] with increasing Tb2O3 content. As Ga3+ ion is larger than B3+ ion in radius, leading to an increasing of the glass network gap and improvement in the ability of accommodating rare earth ions, Verdet constant increased.

The structure of the burner nozzles in a blast furnace hot stove including their number, location, and angle has a vital effect on the flow field, temperature distribution, combustion efficiency, etc. In this article, simulation models were established for the hot stove located at Shougang Qianan. The $$ k{-}\varepsilon $$ model, eddy dissipation model, and P-1 model were used for the modeling of turbulence, combustion, and radiative heat transfer, respectively. The effect of different number of burner nozzles on the flow field and temperature distribution in the combustion chamber was investigated. The results indicated that 19 or 21 burner nozzles were preferred to obtain the optimum flow field and temperature distribution.

To provide theoretical basis for square honeycombs used as crashworthy structures, energy-absorption properties of metal square honeycombs and the size optimization were performed. Specific energy absorption (SEA) was defined as the energy absorbed by the honeycomb structure per unit volume. This parameter was often used for determining the crashworthiness of thin-walled structures. In order to find the most optimized metal square honeycomb structure with the maximum SEA and the lowest peak stress, the cell length and the foil thickness of the metal honeycombs were optimized, with a low peak stress and a high SEA set as the two primary objectives. The pre-processing software Patran was used to build FE models, and the explicit solver LS-DYNA was employed to perform the crashworthiness analyses. The results show that the square honeycomb exhibits good energy absorption performance in some cases. The geometry is effective using 16.8% less buffer structure volume than the hexagonal honeycombs with a peak stress limitation of 1.21 MPa.

The mechanism of improving compressive strength of magnetite pellet by adding boron-bearing iron concentrate was studied. Boron-bearing iron concentrate and magnetite were mixed, pelletized and roasted under different roasting conditions. Then, compressive strength of pellets was tested, and polished sections of the roasted pellets were analyzed from the perspective of mineralogy. Finally, the effects of different proportions, roasting temperatures and roasting time of boron-bearing iron concentrate on the compressive strength of magnetite pellets were investigated and explained.

The dynamic equivalent continuum modeling method of the mast which is based on energy equivalency principle was investigated. And three kinds of mast dynamic model were established, which were equivalent continuum model, finite element model and simulation model, respectively. The mast frequencies and mode shapes were calculated by these models and compared with each other. The error between the equivalent continuum model and the finite element model is less than 5% when the mast length is longer. Dynamic responses of the mast with different lengths are tested, the mode frequencies and mode shapes are compared with finite element model. The mode shapes match well with each other, while the frequencies tested by experiments are lower than the results of the finite element model, which reflects the joints lower the mast stiffness. The nonlinear dynamic characteristics are presented in the dynamic responses of the mast under different excitation force levels. The joint nonlinearities in the deployable mast are identified as nonlinear hysteresis contributed by the coulomb friction which soften the mast stiffness and lower the mast frequencies.

An updated approach to refining the core indicators of pulverized coal used for blast furnace injection based on principal component analysis is proposed in view of the disadvantages of the existing performance indicator system of pulverized coal used in blast furnaces. This presented method takes into account all the performance indicators of pulverized coal injection, including calorific value, igniting point, combustibility, reactivity, flowability, grindability, etc. Four core indicators of pulverized coal injection are selected and studied by using principal component analysis, namely, comprehensive combustibility, comprehensive reactivity, comprehensive flowability, and comprehensive grindability. The newly established core index system is not only beneficial to narrowing down current evaluation indices but also effective to avoid previous overlapping problems among indicators by mutually independent index design. Furthermore, a comprehensive property indicator is introduced on the basis of the four core indicators, and the injection properties of pulverized coal can be overall evaluated.

Activation of ethylene signaling is mediated by nuclear translocation of the cleaved EIN2 carboxyl terminus