Search

Phenolic compounds are a class of important plant secondary metabolites, which are regarded as prime constituents of nutraceuticals and functional foods due to their various bioactivities. Lycium barbarum L., an excellent tonic used for both medicinal and dietary purposes, is rich in phenolic compounds and their derivatives. This article aims to review recent progress in research on phenolic compounds and their derivatives in L. barbarum L. with respect to their extraction, separation, identification, and analysis methods as well as their bioactivities. Furthermore, it summarizes the current knowledge on the contribution of phenolic substances to the flavor and taste of L. barbarum L. along with their synthesis and metabolism and reviews recent progress in their deep processing and application. Finally, possible solutions to the problems existing in the research and development of phenolic compounds from L. barbarum L. and an outlook on future prospects are proposed. It is our expectation that this review will provide a reference for further exploration of phenolic compounds and derivatives in L. barbarum L., and offer theoretical guidance for the development and utilization of this specialty resource.

In the context of dual carbon goals， this paper proposes a multi-energy pricing and dispatch optimization strategy for integrated electricity-heat energy systems in an industrial park， based on the Stackelberg game to address low-carbon scheduling issues. Firstly， the paper introduces the transaction model between the park operator and the users. Secondly， a Stackelberg game model is developed， with the park operator acting as the leader and the user loads within the park acting as followers. The park operator model incorporates a tiered carbon trading mechanism， while the user load model considers the users’ electricity and heat demand response. Finally， the beetle antennae search-improved particle swarm optimization （BAS-PSO） algorithm and the CPLEX solver are utilized to determine the park operator’s pricing strategy and the users’ energy consumption strategies. Simulation results demonstrate that the proposed optimization strategy effectively balances the interests of all parties， resulting in a reduction in the peak-to-valley difference of user loads and a decrease in carbon emissions.

Meta-stable β titanium alloys that feature excellent mechanical properties are of great interest for a range of engineering applications. In particular, Fe containing titanium alloy is one of the most promising alloy systems because Fe is the most economic β stabilizer. However, Fe solute is highly prone to segregation during casting, which leads to the formation of “β flecks” in the subsequent thermo-mechanical treatment and deteriorates the fatigue properties. This paper aims to eliminate β flecks in Ti-3.5 wt%Fe alloy fabricated by Laser Directed Energy Deposition (L-DED), that utilises the high cooling rate during solidification and multiple thermal cycles after solidification. SEM and EDS analysis established that a large β-fleck free zone can be achieved in as-fabricated Ti-3.5 wt%Fe thin-walled samples. Combining the finite element temperature field simulation results and the one-dimensional dynamic diffusion model, the elimination of β flecks is well rationalized. The current work provides a paradigm to evaluate the segregation elimination in the additively manufactured alloy components.

We propose a programmable topological metasurface to integrate intelligent modulations of spatial and surface waves. A general design method is presented to design the programmable metasurface elements with PIN diodes. The surface waves can be controlled to propagate along the topological domain-wall interface by programming the C3-symmetry elements, while the spatial waves are modulated by the patterns of C6-symmetry elements. By independently controlling the bias voltages of meta-elements, the programmable topological metasurface can generate different coding patterns with distinct combinations of C3- and C6-symmetries in real time, respectively achieving the dynamical manipulation of the surface- and spatial-wave by using distinct element states in a time-division manner. To validate the modulation performance, we perform both near- and far-field tests with different coding patterns. Experimental results demonstrate good agreement with numerical simulations, thereby showcasing the flexible manipulations of surface waves and spatial waves by the topological metasurface. The proposed metasurface opens up new possibilities for multifunctional metadevices, which hold great potentials for future wireless communications and smart sensing systems.

The global demand for clean hydrogen energy is constantly increasing. However, the methane steam reforming process cannot satisfy the future social demand for clean hydrogen energy due to its high emission, while the development of water electrolysis technology via renewable energy is limited due to the high cost and the low efficiency. In response to the above issues, an electrified LNG steam reforming hydrogen production system was proposed by introducing the renewable electric heating into the methane steam reforming process, which efficiently integrates the carbon capture technology and the LNG cold energy recovery system. Meanwhile, a model of the electrified LNG steam reforming hydrogen production system was established, and its thermodynamic performance was analyzed. On this basis, investigation was conducted on the influence of the reforming temperature, water-to-carbon ratio and other key parameters on the exergy efficiency and electrical efficiency of the system. The research shows that the exergy efficiency and electrical efficiency of the novel hydrogen production system are as high as 83.2% and 89.5% respectively, and the electrical efficiency is 12.3% higher than the mainstream water electrolysis hydrogen production system. Generally, the novel hydrogen production system could achieve an efficient and clean hydrogen energy supply, providing a new idea and solution to achieve hydrogen production by renewable electricity.

An ideal metasurface design encompasses the control of all the degrees of freedom of electromagnetic (EM) waves. Here, we present a digital coding metasurface optimized for dual-band operations (in K and Ka band) for orthogonal polarizations. The proposed design allows for independent and the simultaneous control of the phases and amplitudes of cross-polarized transmitted waves in both (±z) direction. We employ the design to demonstrate distinct functionalities, which include single and multiple vortex beams carrying orbital angular momentum (OAM) of orders ‘l=+1’ and ‘l=−1’, and beam shaping with the feature of intensity modulations in distinct operating bands. We tested a prototype of the proposed design in the standard EM measurement environment, and the measured results agree well with the corresponding simulations. We remark that the digital coding metasurfaces presented here should improve the capacity of multiple-input multiple-output (MIMO) optical communication systems for power allocations in multi-band operations.

Natural silk fiber derived from the Bombyx mori (B. mori) silkworm has long been used as a luxury raw material in textile industry because of its shimmering appearance and durability, and as surgical suture for its high strength and flexibility. Regenerated silk fibroin, as the main protein extracted from the cocoons of the B. mori silkworm, recently has gained considerable attention due to its outstanding properties, including facile processability, superior biocompatibility, controllable biodegradation, and versatile functionalization. Tremendous effort has been made to fabricate silk fibroin into various promising materials with controlled structural and functional characteristics for advanced utilities in a multitude of biomedical applications, flexible optics, electronics devices, and filtration systems. Herein, reverse engineered silk fibroin extraction methods are reviewed, recent advances in extraction techniques are discussed. Fabrication methods of silk fibroin materials in various formats are also addressed in detail; in particular, progress in new fabrication technologies is presented. Attractive applications of silk fibroin-based materials are then summarized and highlighted. The challenges faced by current approaches in production of silk fibroin-based materials and future directions acquired for pushing these favorable materials further toward above mentioned applications are further elaborated.

In this paper, the image Gabor features extracted by Gabor wavelet are fused with the image grayscale map to construct the enhanced Gabor features, and then combined with the characteristics of Gabor wavelet and convolutional layer, the Gabor feature extraction module, parallel convolution module and spatial transformation pooling module are designed. The corresponding Gabor convolutional layer and Gabor convolutional neural network are constructed using the appropriate module in accordance with the image recognition task application scenario. The convex set projection image super-resolution reconstruction method is used in this paper to improve the resolution of images with low resolution. The construction of a computerized image recognition system involves combining a Gabor convolutional neural network and a convex set projection method. This system has been tested and found to have a recognition accuracy of 93.5% for object images. This system’s ability to accurately recognize low-resolution shadow-obscured face images is possible thanks to using the convex set projection method to reconstruct the image and recognize it accurately with an accuracy of up to 93.85%. This system’s recognition performance for complex images has been proven through experiments.

The stoichiometry of senesced leaves is pivotal in nutrient cycling and can be significantly influenced by soil salinization, a rising global issue threatening the functionality of ecosystems. However, the impacts of soil salinization on senesced leaf stoichiometry are not fully understood. In this study, we conducted a pot experiment with varying soil salt concentrations to examine their influence on the concentrations and stoichiometric ratios of nitrogen (N), phosphorus (P), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and zinc (Zn) in the senesced leaves of Suaeda glauca (Bunge). Compared to the control group, salt treatments significantly enhanced Na concentration while diminishing the concentrations of K, Ca, Mg, Zn, N, and P. Interestingly, as salinity levels escalated, N concentration maintained stability, whereas P concentration exhibited an increasing trend. Moreover, K, Ca, and Mg significantly declined as salt levels rose. Salt treatments brought about significant changes in stoichiometric ratios, with the N:P, K:Na, N:Na, N:Mg, and Ca : Mg ratios dropping and the N:Ca and N:K ratios rising, illustrating the varying nutrient coupling cycles under different salt conditions. These findings shed light on the plasticity of stoichiometric traits in S. glauca senesced leaves in response to soil salinization shifts, which could potentially offer insights into nutrient cycling reactions to soil salinization.

To cope with the demand for large amount of flexibility regulation caused by high penetration of intermittent renewable energy, it is necessary to classify and measure the demand capacity for different regulation performance, and to reasonably allocate flexibility resources for different regions and different regulation capacities. This study proposes a flexibility demand analysis and regulation capacity sharing decisions between interconnected power systems considering differences in regulation performance. Firstly, the empirical mode decomposition (EMD) method is used to decompose the historical operating load curves of each sub-region, and the demand capacities of different regulation performances are calculated based on the obtained decomposition results of trend components and fluctuation components. Then, the probability density and the regulation demand capacity interval at different confidence levels are calculated based on the regulation capacity statistics of the sample of historical operation days. Finally, the regulation capacity sharing decisions between the interconnected regions are made based on the cost of various regulation resources in different sub-regions and the confidence level requirements of internal resources in sub-regions to meet regulation demand. A scenario based on the interconnection operation of two regional grids and the self-sufficiency rate of regulation capacity in each sub-region is no less than 0.95 confidence level is used to verify the effectiveness and feasibility of the proposed method. The simulation results demonstrate that the regulation capacity demand considering the difference in regulation quality can provide a detailed basis for the cross-region deployment of different quality flexibility resources, and the total cost of regulation capacity of the regional grid after adopting the cross-region sharing decision model is reduced by about 4.51% compared with the system independent optimization model.

In this paper, a MMP algorithm is proposed. Compared with the classical algorithm, the proposed algorithm reduces the noise threshold of stably extractable parameters by 15 dB and reduces the computing time by ten or more. As an efficient way to interpret the measurements of high-frequency Inverse Synthetic Aperture Radar (ISAR), the Geometric Theory of Diffraction (GTD) model provides concise features of complex targets. However, the existing parameter extraction algorithms suffer from high computational complexity and poor ability against noise. To solve these challenges, a Maximum Matching Pursuit (MMP) algorithm is proposed in this paper. The proposed algorithm achieves parameter estimation by searching the maximum value of the dictionary matrix and observation signal matrix product. Compared to the classical OMP algorithm, the proposed algorithm significantly reduces the computational complexity by estimating params without cycles. To demonstrate the reconstruction efficiency of the improved algorithm, the Root-Mean-square-error (RMSE), and the computer time of the proposed algorithms are compared with the original algorithms, such as the OMP and the Estimating Signal Parameters via Rotational Invariance Techniques (ESPRIT) algorithm, under different Signal-to-Noise-Ratio (SNR). The simulation results show that the proposed algorithm reduces the noise threshold of stably extractable parameters by 15 dB, reducing the computing time by ten or more.

Solidification grain boundary migration (SGBM) occurs in metals and alloys manufactured by casting, welding, or 3D printing, and it affects material properties, but its mechanisms remain largely unknown. Here, the authors show how SGBM can be predicted in various alloys under different conditions.

Additive manufactured (AM) components are increasingly being applied to fatigue-limited applications and are often safety–critical, necessitating confidence in the predicted fatigue response. The fatigue failure mode is highly sensitive to variations in loading, materials and geometry; therefore, published AM fatigue data must be accompanied by robust supporting documentation for confident adoption. International standards provide robust guidance on these documentation requirements; however, there are currently no formal methods for quantifying the uncertainty within published AM fatigue test data. A set of documentation criteria are proposed based on the core requirements of recognised standards for fatigue and AM test reporting. These documentation criteria form the basis for applicability indices proposed to quantify the uncertainty of reported AM fatigue test data. The applicability indices offer a new way to evaluate the suitability of fatigue data for specific applications and are demonstrated for publicly available Powder Bed Fusion Ti-6Al-4V fatigue data. This large number of datasets are examined in terms of the influence of process variables on the observed fatigue response. These observations provide a reference for AM fatigue designers to be aware of the influence of relevant variables on fatigue response, as well as for AM fatigue researchers to identify strategic opportunities for novel contributions.

The mineralocorticoid receptor (MR) is a ligand-activated cytoplasmic receptor.Activation of MR in different cells can cause cardiovascular inflammation, oxidative stress, tissue remodeling ,and even function change the activity of ion channels resulting in incidence of arrhythmia through various mechanisms.MR antagonists are effective medicine to treat hypertension,coronary heart disease,and heart failure. In addition, the role of MR in arrhythmia and pulmonary hypertension also provides new perspectives for future clinical medication.

Among the different nanostructures that have been demonstrated as promising materials for various applications, three–dimensional (3D) nanostructures have attracted significant attention as building blocks for constructing high-performance nanodevices because of their unusual mechanical, electrical, thermal, optical, and magnetic properties arising from their novel size effects and abundant active catalytic/reactive sites due to the high specific surface area. Considerable research efforts have been devoted to designing, fabricating, and evaluating 3D nanostructures for applications, including structural composites, electronics, photonics, biomedical engineering, and energy. This review provides an overview of the nanofabrication strategies that have been developed to fabricate 3D functional architectures with exquisite control over their morphology at the nanoscale. The pros and cons of the typical synthetic methods and experimental protocols are reviewed and outlined. Future challenges of fabrication of 3D nanostructured materials are also discussed to further advance current nanoscience and nanotechnology.

Objective To explore the feasibility and effectiveness of an online service offering Traditional Chinese Medicine (TCM) physique conditioning under the normalization of epidemic prevention and control. Methods From March 1, 2020 to March 10, 2020, 190 subjects who were judged as "Qi deficiency" by "TCM constitution test" were recruited online. A research team was set up to develop physique conditioning plans, formulate "Ear Massage", construct a physique conditioning WeChat group and public account for Qi-deficiency subjects, and provided online physique conditioning services for 6 months. The conversion score of Qi-deficiency, the frequency of respiratory infection in 6 months and psychological status were compared before and after intervention. Results Compared with before intervention, the conversion score of Qi-deficiency, the frequency of respiratory infection in 6 months, the negative emotion score and total score of the five dimensions of depression, nervous decline, fear, compulsion-anxiety and hypochondria of the subjects decreased, with statistical significance(P

[Introduction] Control the exchanged power of the regional tie-lines within a reasonable range, which is an important factor to ensure the stability of the power network. However, under some extreme operation modes, the exchanged power of the tie-lines may exceed the limit, especially the large-scale of new energy sources into the power grid, the power of the tie-lines between regions may fluctuate greatly. Therefore, necessary power flow control measures should be taken. [Method] Compared the power flow control methods of several main types of tie-lines and their characteristics, a flexible power flow control method based on multi-stage rapid switching reactor was put forward, and the specific control strategy was studied. [Result] Finally, based on the application of a regional power grid Tie-lines, the function of multi-stage fast switching reactor in controlling the exchange power of regional power grid tie-line was verified. [Conclusion] The results show that the power flow of the tie-line can be controlled flexibly and quickly by using the multi-stage fast switching reactor, and the overall technical economy is better.

Due to the strong ability of recognizing electromagnetic (EM) environment and adaptively control of EM waves, the intelligent metasurfaces have received great attention recently. However, the intelligent metasurface with frequency recognition for adaptive manipulation of the EM waves has not been studied. Here, we propose a frequency-recognition intelligent metasurface to precisely control the spatial EM waves under the agile frequencies with the help of a real-time radio-frequency sensor and an adaptive feedback control system. An active meta-atom is presented to reach 2 bit phase coding and 1 bit amplitude coding capacities to control the amplitude and phase independently. Experimental results demonstrate that the metasurface can recognize different frequency of the incoming wave with very high resolution, and can adaptively realize the self-defined multiple frequency agilities to manipulate the reflected EM waves without any human participation. As example, the intelligent metasurface with frequency recognition can adaptively operate wave absorption at 5.36 GHz, reflection to normal direction at 5.38 GHz, deflection to −30° at 5.40 GHz, random diffusion at 5.42 GHz, and deflection to +33° at 5.44 GHz by detecting the incoming frequency at the resolution of 0.02 GHz.

C17H14N2O6S·C3H7NO, triclinic, P1‾ $P\overline{1}$ (no. 2), a = 5.4146(4) Å, b = 11.7925(8) Å, c = 16.9527(12) Å, α = 85.238(2)°, β = 86.674(4)°, γ = 78.959(2)°, V = 1057.77(13) Å3, Z = 2, R gt(F) = 0.0418, wR ref(F 2) = 0.1175, T = 296(2) K.

The thermodynamic behavior of 3-D orthogonal woven composite is studied to explore its structural heat transfer mechanism in a non-uniform heat load field based on finite element analysis (FEA). The temperature distribution characteristics of the resin matrix and the fabric reinforcement are observed to compare the heat absorption. Furthermore, the dynamic expansion and distribution characteristics of temperature in the 3-D orthogonal woven composite structure have also been quantitatively studied, together with simultaneously obtaining the path characteristics of the heat transfer in each system (i.e., warp yarns, weft yarns, and Z-yarns). In addition, the spatial temperature distribution characteristics of each yarn system in the fabric reinforcement are also explored. Thus, the structural mechanism of heat conduction for 3-D orthogonal woven composite is obtained.

Objective: This study aimed to improve the technological conditions of antioxidant activity of pumpkin polysaccharide. Methods: The effects of temperature, pumpkin powder/distilled water ratio of solid to liquid, inoculation amount and shaking speed on the extraction rate of bio-transformed pumpkin polysaccharide were investigated, and the scavenging ability of pumpkin polysaccharide on DPPH free radical was studied. Results: The optimal conditions were inoculation amount 1% and solid-liquid ratio 1∶30 (g/mL), with shaking speed of 100 r/min at 37 ℃. Under the control of these conditions, the scavenging rate of DPPH free radical was （54.61±1.58）%. The in vitro antioxidant activity of the bio-transformed pumpkin polysaccharide was significantly higher than that of the non-transformed one. Conclusion: Lactobacillus plantarum nbkBC299 could improve the antioxidant activity of pumpkin polysaccharide.

Applications involving strain rates in excess of 102 - 103s−1 are unique in both materials selection and design approaches and are of particular importance for protection of infrastructure and personnel in dynamic impact scenarios. Three broad categories of such applications, according to the impact type and configuration requirements, including material and design characteristics, can be identified: (i) ballistic protection against projectiles or fragments; (ii) protection against other types of high energy events (HEEs), such as a crash or a blast; and (iii) micrometeoroid and orbital debris (MMODs) mitigation. Prior studies have highlighted beneficial design features to enhance integrity under dynamic loading conditions, such as the ability to absorb the impact energy through cellular structural design or to deflect the impact. In these scenarios, the ability to optimise the three-dimensional (3D) geometry of the protection system can facilitate significant improvements in structural performance under high strain rate conditions, signifying the great potential of additive manufacturing (AM) methods in this field. However, to date, research on AM of materials and structures for dynamic impact applications has been relatively limited. In this article, we review the current state of knowledge in high strain rate engineering design and systematically assess the potential and emerging opportunities that can be realised via the AM approach.

Objective To investigate the effect of different temperature of intestinal liquid on the effect of colon cleansing under the guidance of syndrome differentiation and classification. Methods Totally 270 patients who underwent colonoscopy or treatment were selected as study subjects. According to the patient’s constitution of Traditional Chinese Medicine and intestinal fluid temperature, patients were divided into 9 groups: group A (Yang deficiency, 26 ~ 30 ℃), group B (Yang deficiency, 36 ~ 40℃), group C (Yang deficiency, 46 ~ 50℃), group D (Yin deficiency, 26 ~ 30℃), group E (Yin deficiency, 36 ~ 40℃), group F (Yin deficiency, 46 ~ 50℃), group G (balanced constitution, 26 ~ 30℃), group H (balanced constitution, 36 ~ 40℃), group I (balanced constitution, 46 ~ 50℃), with 30 cases in each group. The colon cleanliness, patient tolerance, time of onset of diarrhea and the frequency of diarrhea in 9 groups were observed. Results In patients with Yang-deficient constitution, group C had better colon cleanliness than group A and B (P

Three-dimensional angle-interlock woven composites (3DAWCs) are widely used for their excellent mechanical properties. The most significant feature is the existence of the undulated warp yarns along the thickness direction, which makes it interesting to study the mechanical properties in the warp direction. The quasi-static tensile behavior of a layer-to-layer 3DAWC along the undulated warp direction was studied by experimental and finite element analysis (FEA) methods. Based on the experimental results, the typical failure mode involving fibers, resin, and their interfaces was found. According to the FEA results, the stress concentration effect, key structural regions, and microstructural (yarn and resin) damage mechanism were obtained, which provided effective guidance for structural optimization design of the 3DAWC with stronger tensile resistance performance. In addition, the three-step progressive failure process of the 3DAWC under quasi-static tensile load was also described at the “yarn–resin” microstructural level.

The most attractive structural feature of the three-dimensional (3D) angle-interlock woven structure is that the straight weft yarns are bundled by the undulated warp yarns, which induces the overall good structural stability and a stable fabric structure. Thus the 3-D angle-interlock woven composite (3DAWC) prepared by the vacuum-assisted resin transfer molding (VARTM) curing process has excellent mechanical properties by using the fabric and epoxy resin as the reinforcement and matrix, respectively. The low-velocity impact damage properties of the composites under different drop-weight energies (70, 80, and 100 J) were tested experimentally. The load–displacement curves, energy–time curves, and the ultimate failure modes were obtained to analyze the performance of resistance to low-velocity impact, as well as the impact energy absorption effect and failure mechanism, especially the structural damage characteristics of the 3DAWC subjected to the low-velocity impact of drop weight. By analyzing the obtained experimental results, it is found that the fabric reinforcement is the primary energy absorption component and the impact energy mainly propagates along the longitudinal direction of the yarns, especially the weft yarn system, which is arranged in a straight way. In addition, as the impact energy increases, the energy absorbed and dissipated by the composite increases simultaneously. This phenomenon is manifested in the severity of deformation and damage of the material, i.e., the amount of deformation and size of the damaged area.

For the intelligence of metamaterials, the -sensing mechanism and programmable reaction units are two important components for self-recognition and -determination. However, their realization still face great challenges. Here, we propose a smart sensing metasurface to achieve self-defined functions in the framework of digital coding metamaterials. A sensing unit that can simultaneously process the sensing channel and realize phase-programmable capability is designed by integrating radio frequency (RF) power detector and PIN diodes. Four sensing units distributed on the metasurface aperture can detect the microwave incidences in the x- and y-polarizations, while the other elements can modulate the reflected phase patterns under the control of a field programmable gate array (FPGA). To validate the performance, three schemes containing six coding patterns are presented and simulated, after which two of them are measured, showing good agreements with designs. We envision that this work may motivate studies on smart metamaterials with high-level recognition and manipulation.

Reduction of greenhouse gas (GHG) emissions for mitigating climate changes is globally necessary. As a major GHG emitter, refinery sector is responsible for 14.1% of China’s CO2 emission in 2019. The flue gas associated with petroleum refining has high CO2 content, presenting potentials for methanol and electricity co-production when the methane and hydrogen in dry gas are considered. To unlock the green opportunity for refineries, in this study we employed Aspen Plus to develop the process of methanol synthesis by recovering CO2 in the flue gas of fluid catalytic cracking (FCC) unit and the methane and hydrogen in dry gas. The results show that the new co-production process increases the energy efficiency of the FCC unit by 2.4%. Compared with traditionally natural gas-based methanol production, the developed process enables annual CO2 mitigation of 1.3 million tons.

Mitigating greenhouse gas (GHG) emissions to curb climate change has become a consensus among international community. Refining is one of the major industries with high energy consumption and high emissions, which is responsible for 4-10% of global carbon dioxide (CO2) emissions and approximately 25% is generated by fluid catalytic cracking (FCC) units. The flue gas discharged from FCC units has a high CO2 content, presenting potential for methanol and electricity co-production production when the methane in the dry gas is considered. To unlock this green chance for enterprises, we designed a methanol production system that uses the CO2 recovered from the flue gas of fluid catalytic cracking (FCC) unit in a refinery and the CH4 separated from dry gas as feed stock (hydrogen to be added from an internal hydrogen production unit of the refinery). We analyzed economic feasibility of the process, the results show that the developed system is economically feasible for annual methanol yields of 1.0-2.5 Mt and the internal rate of return increases by 8.3%.

As one of the major energy-consuming and high-emission industries, the refineries account for 10% of global industrial carbon emissions, of which about 25% is emitted by fluid catalytic cracking (FCC) process. Therefore, CO2 capture from FCC flue gas create the possibility for low-carbon refineries. We developed a novel CO2 utilization process to methanol production modeling using Aspen Plus. Meanwhile, organic Rankine Cycle (ORC) power generation technology was coupled to recover the waste heat of the system. A five-million-ton FCC unit in China was selected as a case study. We conducted some analysis for the process, the results show that the developed system boosts the energy efficiency of the FCC unit by 2.8%. The annual capacity of the waste heat power generation unit is 4.8 GWh, with a thermal efficiency of 5.9%.

Additive Manufacturing (AM) technologies such as Laser-Based Powder Bed Fusion (LB-PBF) enables the manufacturing of high efficiency lattice structures. However, the LB-PBF processes inherently generate local geometric effects. The practical implications of these geometric effects on structural performance is of critical importance to effective AM design; however, these effects are poorly understood. In response to this uncertainty, this research compares predictive and experimental data for the structural response of LB-PBF lattice strut elements subject to compressive loading; this comparison is made for LB-PBF manufactured Ti-6Al-4V LB-PBF but is generally applicable to all AM systems and materials. This data provides insight into the influence of geometric design parameters, including: node and strut diameter, strut length, and manufacturing inclination angle. The effect of these geometric parameters on the associated critical buckling load, and the accuracy of predictive failure models is quantified. Furthermore, the eccentricity ratio, a classical measure of column efficiency widely used in civil engineering design, is applied for the first-time as a systematic metric to characterise the structural efficiency of as-manufactured AM strut element.

To overcome the difficulty of similarity expression and the effects of speckle noise in unsupervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images, a novel unsupervised PolSAR image terrain classification algorithm based on Tensor Product Graph (TPG) diffusion has been developed herein. Generally, TPG diffusion is usually utilized for optical image segmentation or image retrieval. In the present study, it can be used for PolSAR image terrain classification. TPG diffusion can robustly estimate geodesic distances; therefore, it can be used for mining the intrinsic affinity between data points. First, the PolSAR image is over-segmented into many superpixels. Second, seven features are extracted based on the segmented superpixels to form a feature vector and construct a similarity matrix by using the Gaussian kernel. Third, TPG diffusion is performed on this similarity matrix to obtain another similarity matrix with stronger discriminability by propagating affinity information along the mainfold structure of data to achieve the global affinity measure. Finally, spectral clustering based on the diffused similarity matrix is adopted to perform terrain classification. Extensive experiments conducted on both simulated and real-world PolSAR images demonstrate that our approach can effectively combine neighborhood information and achieve higher classification accuracy, compared to four other competitive state-of-the-art methods.

Objective To investigate the diagnostic value of rectal epithelial cells stability FH for the early screening of rectal cancer. Methods FH, CEA and CA19-9 were performed in 300 patients. We used pathological diagnostic results as the gold standard and electronic colonoscopy as an assistance to analyze the detection indicators of epithelial cells stability FH, CEA and CA19-9 test for screening rectal malignancy, such as sensitivity(Sen), specificity(Spe), false negative rate(missed diagnosis rate), false positive rate (the misdiagnosis rate), negative likelihood ratio (LR), positive likelihood ratio (LR+), diagnosis index (DI), Youden index, crude coincidence rate (CA), negative predictive value (PV-) and positive predictive value (PV+), etc. Results The positive rate of epithelial cell stability FH test for rectal malignant tumor was higher than those of CEA and CA19-9 (P=0.000). Among the 40 cases of rectal malignant tumor, 38 positive cases(95%) were detected by epithelial cell stability FH, 23 positive cases(57.5%) were detected by CEA, 10 positeve cases(25%) were detected by CA19-9. The sensitivity, positive likelihood ratio, diagnostic index, Youden index, negative predictive value and positive predictive value of FH were all higher than those of CEA and CA19-9, while the false negative rate and negative likelihood ratio were lower than CEA and CA19-9. Conclusion There are higher sensitivity, positive likelihood ratio, diagnostic index, Youden index, negative predictive value, positive predictive value, lower false negative rate and negative likelihood ratio of epithelial cells stability FH in rectal cancer screening.

The lithium-ion batteries retired from electric vehicles (EVs) and hybrid EVs have been exponentially utilized in battery energy storage systems (BESSs) for 2nd use due to their economic and environmentally friendly benefits. Therefore, research on their aging mechanism and state of health (SOH) has attracted increasing amounts of attention across the world. However, few studies focus on optimizing the economic operation of BESSs that are built by retired batteries with various SOHs. This paper proposes an economic operation optimization method for BESSs comprised of retired batteries with different SOHs, which provides a way for the BESS to operate with new and retired battery systems (BSs) together. An operation cost model is put forward that considers the cost increase caused by aging. This method aims to minimize the operating cost in a time step based on the particle swarm optimization method. To validate the feasibility of the economic operation optimization method, a case was studied using a BESS consisting of four BSs with different SOHs under peak load shifting. Compared with the traditional method, which allocated power according to the available peak power of each BS, the proposed method has advantages in the scheduled number and cost.

Under the goal of achieving “carbon neutrality”, increasing energy-saving and reducing emissions has become a long-term strategy to ensure the sustainable development of China’s social economy. The unrecycled waste heat leads to a high energy penalty in refinery. This paper presents an Organic Rankine Cycle (ORC) power generation technology, which through the thermodynamic cycle to recover the waste heat from the Aromatics Complex units. This process is simulated and analysed from the environmental point. The results indicate that the application of ORC in aromatics combined units can indirectly save 41040 tons of coal every year. The annual emission of CO2 is reduced by 94455 tons. The proposed ORC system provides technological route for refineries to achieve waste heat recovery, thus advancing the green transition of the petrochemical plants.

Triply Periodic Minimal Surface (TPMS) structures fabricated via Additive Manufacturing (AM) have recently emerged as being appropriate candidates for high-value engineered structures, including porous bio-implants and energy absorbing structures. Among the many TPMS designs, Gyroid structures have demonstrated merits in AM manufacturability, mechanical properties, and permeability in comparison to traditional lattice structures. Gyroid structures are mathematically formulated by geometric factors: surface thickness, sample size, number of surface periods, and the associated isovalue. These factors result in a continuous surface with a topology-specific structural response. Quantifying the effect of these factors on overall structural response requires substantial computational and experimental resources, and little systematic data exists in the literature. Using a numerical approach, cubic Gyroid structures of various designs were simulated under quasi-static compression, using a simulation model verified with experimental data for AM Ti-6Al-4V specimens fabricated by Selective Laser Melting (SLM). The influence of geometric factors on structural response was quantified with OFAT (One Factor At a Time) and Taguchi methods. The results identify the number of cells and surface thickness strongly influence both modulus and compressive strength. These findings were used to theoretically develop a Gyroid structure that imitates both elastic modulus and compressive strength of human cortical bone. Keywords: Finite element analysis, Triply periodic minimal surface, Cellular structure, Taguchi, Additive manufacture, 3D printing

Additive manufacturing (AM), particularly Selective Laser Melting (SLM) has enabled development of lattice structures with unique properties. Through control of various parameters lattice structures can produce unique mechanical, electrical, thermal and acoustic properties, and have received much research attention. Despite the increasing volume of published data on the mechanical response of specific SLM lattice structures, there exists no overarching analysis. This work addresses this identified deficiency by providing a comprehensive summary of the experimental data reported on the mechanical response of SLM lattice structures. The design, fabrication and performance of SLM lattice structures are reviewed and the quality of data reported is analysed to inform best-practice for future studies. This comprehensive data summary enables meta-analysis of the reported mechanical performance of SLM lattice structures, providing insight into the bounds of their technical capabilities. Correlations were identified between the relative density and mechanical properties of many unit cell topologies consistent with the predictions of the Gibson-Ashby model, indicating its usefulness in describing and predicting the behaviour of SLM lattice structures. This review provides designers with a compiled resource of experimental data and design for AM tools to inform future design applications of SLM lattice structures and facilitates their further commercial adoption. Keywords: Additive manufacturing, SLM, Selective laser melting, Lattice structures, DFAM, Mechanical properties

The quasi-static tensile damage behavior of one type of layer-to-layer 3-Dimensional Angle-interlock Woven Composite (3DAWC) was tested and analyzed in this paper. Incorporated with the acoustic emission (AE) events monitoring, the mechanical behavior of the 3DAWC under tensile loading condition was characterized. The Load-Extension curve, Load/AE events-Time curves occurred during the entire testing process and tensile damage modes were recorded to characterize and summarize the mechanical properties and damage mechanism of the 3DAWC subjected to tensile loading. It was found that the tensile damage of the 3DAWC could be summarized into 3 steps. And each step has a distinct primary damage mode. Moreover, the resin cracks, resin-yarn interface debonding and yarn breakages were the main damage modes for the 3DAWC.

Addition of manufacturing defects to computational models of 3D-printed lattice structures enable improved simulation accuracy. A computational model of a cellular structure based on finite element method (FEM) analysis, often starts from defect-free computer-aided design (CAD) geometries to generate discretised meshes. Such idealised CAD geometries neglect imperfections, which occur during the additive manufacturing process of lattice structures, resulting in model oversimplification. This research aims to incorporate manufacturing defects in the strut elements of a lattice structure, thereby enhancing predictive capabilities of models. In this work, a method of generating CAD AM representative strut models is proposed. The models are generated from micro-computer tomography (μCT) analysis of SLM fabricated struts. The proposed additive manufacturing (AM) representative strut FE model's axial stiffness and critical buckling load is compared to idealised- and μCT- based FE models, with significant error reduction over idealised strut models. The AM representative strut models are then used to generate full lattice FE models and compared with manufactured and idealised FE models. The AM representative FE lattice models show greater correlations toward experiment and more realistic deformation behaviours. Overall, the methodology used in this study demonstrates a novel approach to representing struts in FE models of AM fabricated lattice structures. Keywords: Selective laser melting (SLM), Lattice structures, Finite element analysis (FEA), Computer-aided design (CAD), Defect modelling