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Metal–CO2 batteries represent a potential new technology for environmental protection, as they can effectively reduce CO2 emissions while ensuring energy production. However, the design of active, selective, and cost-efficient electrocatalysts remains a challenge. Herein, we report two tubular cathodes (CNTs@Cu and CNTs@Ni, CNTs = carbon nanotubes) that are used to assemble two primary Zn–CO2 flow batteries with zinc wire and 1-ethyl-3-methylimidazolium tetrafluoroborate as the anode and electrolyte, respectively. Interestingly, CO2 conversion with quite high selectivity could be realized over the different cathodes in these two Zn–CO2 flow batteries. These two batteries exhibit the advantages of high operating voltages, excellent stability, and continuous and selective product outputs. The flow battery based on the tubular CNTs@Cu cathode can convert CO2 into CH4 with a faradaic efficiency of up to 93.3%. Concurrently, electricity is generated at an energy density of 376 Wh kg−1. This battery remains stable for more than 18 days. Surprisingly, the flow battery with a tubular CNTs@Ni cathode can reduce CO2 to syngas (CO and H2, faradaic efficiencies for CO and H2 of up to 50% and 48%, respectively) while generating electricity at an energy density of 208.7 Wh kg−1, and it is stable for up to 9 days. These excellent performances are attributed to a synergistic effect involving CNTs and the metal substrate, and the differences between these two batteries are mainly ascribed to metal substrate effects. Excitingly, low concentrations of CO2 released by humans and simulated vehicle emissions could also be converted. This work demonstrates that Zn–CO2 flow batteries are green, selective, efficient, and promising devices for producing value-added chemicals, and they are worthy of further theoretical studies and practical application.

The tension of cables and motion response significantly affect safety of an immersed tunnel element in the immersion process. To investigate those, a hydrodynamic scale-model test was carried out and the model experiments was conducted under wind, current and wave loads simultaneously. The immersion standby (the process that the position of the immersed tunnel element should be located before the immersion process) and immersion process conditions have been conducted and illustrated. At the immersion standby conditions, the maximum force of the cables and motion is much larger at the side of incoming wind, wave and current, the maximum force of Element-6 (6 cables directly tie on the element) is larger than for Pontoon-8 (8 cables tie on pontoon of the element), and the flexible connection can reduce the maximum force of the mooring cables and motion of element (i.e. sway is expecting to decrease approximate 40%). The maximum force of the mooring cables increases with the increase of current speed, wave height, and water depth. The motion of immersed tunnel element increases with increase of wave height and water depth, and the current speed had little effect on it. At the immersion process condition, the maximum force of the cables decrease with the increase of immersion depth, and dramatically increase with the increase of wave height (i.e. the tension of cable F4 of pontoons at wave height of 1.5m (83.3t) is approximately four times that at wave height of 0.8m). The current speed has no much effect on the maximum force of the cables. The weight has little effect on the maximum force of the mooring cables, and the maximum force of hoisting cables increase with the increase of weight. The maximum value of six-freedom motion amplitude of the immersed tunnel element decreases with the increase of immersion depth, increase with the increase of current speed and wave height (i.e. the roll motion at wave height of 1.5m is two times that at wave height of 0.8m). The weight has little effect on the maximum motion amplitude of the immersed tunnel element. The results are significant for the immersion safety of element in engineering practical construction process.

This work focuses on the impact of explosion puffing drying with different pretreatment on the processability and physical-functional properties in purple sweet potato powder. Compared to the powder by hot air drying, the explosion puffing drying whatever cooked or uncooked pretreatment had a significant beneficial effect in purple sweet potato powder physical-functional properties, which presents bright color, protection of anthocyanin, strong water absorption capacity and oil absorption capacity, and has small effect on granule structure. The uncooked pretreatment powder by explosion puffing drying yielded highest anthocyanin content (1.49 mg/g dry matter) which was about 3 times higher than the hot air drying sample (0.51 mg/g dry matter). Obviously, the explosion puffing drying may offer better processability and nutritional quality than hot air drying. This drying method can be used as a method for preserving functional properties to suit functionality and processability in specific food product for widening the application range of purple sweet potato powder.

This work reviews the ultimate compressive strength of aluminium plates and stiffened panels. The effect of boundary condition, initial imperfection, welding-induced residual stress and heat-affected zone are discussed. As the effect of manufacturing technology lacks in the literature, this effect is analysed employing the finite element method, considering the technology of welding and integrated extrusion. The numerical analyses have shown that the ultimate strength of the integrated extruded stiffened panel is relatively higher than the one of the traditional welded panel.

The origin traceability of edible oil is an effective way to protect the legitimate rights and interests of producers and consumers. This review briefly summarizes research progress on origin traceability technologies for edible oils including stable isotope ratio mass spectrometry, mineral element fingerprint analysis, organic component fingerprint analysis, near-infrared spectroscopy, nuclear magnetic resonance technology and biochemical analysis. Moreover, the development trends in edible oil origin traceability technology were proposed.

The design trade-offs of transceiver hardware are crucial to the performance of wireless systems. In this paper, we present an in-depth study to characterize the surprisingly notable systemic impacts of low-pass filter (LPF) design, which is a small yet indispensable component used for shaping spectrum and rejecting interference. Using a bottom-up approach, we examine how signal-level distortions caused by the trade-off of LPF design propagate to the upper-layers of wireless communication, reshaping bit error patterns and degrading link performance of today’s 802.11 systems. Moreover, we propose a novel algorithm that harnesses LPF defects for improving video streaming, which substantially enhances video quality in mobile environments.

In this work, a memristive circuit with affective multi-associative learning function is proposed, which mimics the process of human affective formation. It mainly contains three modules: affective associative learning, affective formation, affective expression. The first module is composed of several affective single-associative learning circuits consisting of memristive neurons and synapses. Memristive neuron will be activated and output pulses if its input exceeds the threshold. After it is activated, memristive neuron can automatically return to the inactive state. Memristive synapse can realize learning and forgetting functions based on the signals from pre- and post-neurons. The learning rule is pre-neuron activated lags behind post-neuron for a short time; the forgetting rule is to repeatedly activate pre-neuron after the emotion is learned. The process of learning or forgetting corresponds to facilitating or inhibiting synaptic weight, that is, decreasing or increasing memristance continuously. Different voltage signals applied to memristors and different parameters of memristors would lead to different synaptic weights which indicate different affective association. The second module can convert affective signals to corresponding emotions. The formed emotions can be shown in a face by the third module. The simulation results in PSPICE show that the proposed circuit system can learn, forget and form emotions like human. If the proposed circuit is further used on a humanoid robot platform through further research, the robot will have the ability of affective interaction with human so that it can be effectively used in affective company and other aspects.

Based on the Precise Transfer Matrix Method (PTMM), the dynamic model is constructed to observe the vibration behaviour of cylindrical shells with variable thickness by solving a set of first-order differential equations. The free vibration of stiffened cylindrical shells with variable thickness can be obtained to compare with the exact solution and FEM results. The reliability of the present method of free vibration is well proved. Furthermore, the effect of thickness on the vibration responses of the cylindrical shell is also discussed. The acoustic response of immersed cylindrical shells is analyzed by a Pluralized Wave Superposition Method (PWSM). The sound pressure coefficient can be gained by collocating points along the meridian line to satisfy the Neumann boundary condition. The mode convergence analysis of the cylindrical shell is carried out to guarantee calculation precision. Also, the reliability of the present method on sound radiation is verified by comparing with experimental results and numerical results.

As the main tool to realize data mining and efficient knowledge acquisition in the era of big data, machine learning is widely used in data center energy-saving research. The temperature prediction model based on machine learning predicts the state of the data center according to the upcoming tasks. It can adjust the refrigeration equipment in advance to avoid temperature regulation lag and set the air conditioning temperature according to the actual demand to avoid excessive refrigeration. Task scheduling and migration algorithm based on temperature prediction can effectively avoid hot spots. However, the choice of hyperparameter of machine learning model has a great impact on its performance. In this study, a hyperparameter optimization algorithm based on MLP is proposed. On the basis of trying certain hyperparameters, the MLP model is used to predict the value of all hyperparameters’ space, and then, a certain number of high-quality hyperparameters are selected to train the model repeatedly. In each iteration, the amount of training data decreases gradually, while the accuracy of the model improves rapidly, and finally, the appropriate hyperparameter are obtained. We use the idea of mutation in the genetic algorithm to improve the probability of high-quality solutions and the loss function weighting method to select the solution with the best stability. Experiments are carried out on two representative machine learning models, LSTM and Random Forest, and compared with the standard Gaussian Bayes and Random Search method. The results show that the method proposed in this study can obtain high-precision and high-stability hyperparameter through one run and can greatly improve the operation efficiency. This algorithm is not only effective for LSTM but also suitable for other machine learning models.

Authentication is an important requirement for the security of edge computing applications. The existing authentication schemes either frequently rely on third-party trusted authorities, leading to the security risk of user information disclosure, or have high authentication overhead, causing certain pressure on the computation and communication of lightweight terminal equipment in the edge environment. In this paper, we proposed a blockchain-based anonymous authentication scheme for edge computing environments. We first designed a blockchain-based authentication architecture to store a small number of authentication elements in the blockchain network, and provide a decentralized and trusted authentication environment to ensure device anonymity and improve the security of authentication processes. Then, an elliptic cryptographic curve-based authentication scheme is proposed. It uses the chameleon hash function to dynamically generate the authentication data according to the elements stored in the blockchain and negotiate the session key, which effectively reduces the computational overhead in the authentication process. The experimental results show that the proposed scheme achieves a secure authentication process and effectively reduces the authentication overhead by up to 43.16% compared to three state-of-the-art schemes.

Missing data is a major problem in data-driven intelligent transportation systems. This study presents an imputation method, called TrafficMosaic, for effective imputation of lost traffic flow data. If we consider traffic data as a image, then the missing data in it can be regarded as a mosaic. The design of TrafficMosaic is inspired by super resolution techniques. First, a deep neural network (DNN) is employed to recover the lost data by a suite of techniques inspired from image super resolution. This DNN method combines the temporal relevance of historical flow with spatial correlation of current fragmented flow data, and uses the imputation result as input for recursive calculation. Second, a data-driven road network matrixing algorithm is proposed to mine location relations from trajectory data and reconstruct a road network flow into matrixes of road network flow pictures. Convolutional local calculation in a convolutional neural network is introduced to extract local spatial features of the road network, thereby reducing the computational complexity and improving the generalization ability. The final step is to extract the local temporal features of the flow data. Traffic flows at adjacent moments have strong temporal characteristics, and we splice several historical road network traffic pictures in chronological order so that our model can capture temporal information from the sequence. The experimental evaluation used a real automatic number plate recognition dataset for experiments, and the results show the effectiveness of TrafficMosaic for lost data imputation.

Objective: To investigate the diagnostic value of ERCP combined with CRP, CEA and IL-6 in serum in Occult Common bile duct stones (CBDS). Methods: 80 cases of patients with occult CBDS treated in our hospital were selected as the research subjects, and the diagnosis rates of ERCP alone or ERCP combined with CRP, CEA and IL-6 in serum were compared. Results: Versus ERCP alone, the diagnosis rate of combined diagnosis was clearly higher (P < 0.05). Versus patients without CBDS, the levels of CRP, CEA and IL-6 in serum in CBDS patients were apparently elevated (P < 0.05). The levels of CRP, CEA and IL-6 in serum were of high value in the diagnosis of CBDS in patients with occult CBDS (P < 0.05). Conclusion: ERCP combined with CRP, CEA and IL-6 in serum is of high value in re-diagnosis of Occult CBDS.

Based on the equivalent mechanics model of wire rope, a kinetics modeling method of rope-driven unit for robot rotary joint is proposed, and the kinetics equation of rope-driven unit is derived. The impact resistance of rope-driven unit is analyzed theoretically, including passive compliance and active compliance. The active compliance control is introduced on the basis of tension feedback and position closed-loop controller of joint. According to the signals of tension sensor to judge the impact force, the change of output joint angle of rope-driven unit which the impact force may cause is calculated. Then, it will be substituted into the system kinetics equation to obtain the compensation angle needed by motor, so that rope-driven unit makes the corresponding retrograde motion to achieve the effect of unloading force when it is impacted by the external. Taking FDU-II rope-driven unit developed independently by our laboratory as an example, the system kinetics modeling and impact experimental research are carried out by using the above method. The results show that the active–passive compliance control can effectively improve the impact resistance of FDU-II rope-driven unit. At present, FDU-II rope-driven unit can withstand 3 times of the impact force of the load gravity and achieve 20% of the buffer ability. Compared with the impact experimental results only relying on passive compliance, it has greatly improved and also effectively reduced the period of shock caused by the impact, which provides a theoretical and experimental basis for the future research of biped robot stable walking experiment.

The numerical hydroelastic method is used to study the structural response of a hexagon enclosed platform (HEP) of flexible module rigid connector (FMRC) structure that can provide life accommodation, ship berthing and marine supply for ships sailing in the deep ocean. Six trapezoidal floating structures constitute the HEP structure so that it is a symmetrical very large floating structure (VLFS). The HEP has the characteristics of large area and small depth, so its hydroelastic response is significant. Therefore, this paper studies the structural responses of a hexagon enclosed platform of FMRC structure in waves by means of a 3D potential-flow hydroelastic method based on modal superposition. Numerical models, including the hydrodynamic model, wet surface model and finite element method (FEM) model, are established, a rigid connection is simulated by many-point-contraction (MPC) and the number of wave cases is determined. The load and structural response of HEP are obtained and analyzed in all wave cases, and frequency-domain hydroelastic calculation and time-domain hydroelastic calculation are carried out. After obtaining a number of response amplitude operators (RAOs) for stress and time-domain stress histories, the mechanism of the HEP structure is compared and analyzed. This study is used to guide engineering design for enclosed-type ocean platforms.

Drug-induced changes in urine color induced by drugs may have clinical significance. Pink urine syndrome (PUS), which has been associated with urinary uric acid (UA) disorders, is most frequently reported in patients with morbid obesity undergoing gastric bypass surgery and/or from propofol anesthesia use in those who potentially have preexisting UA metabolism disorders. However, PUS has rarely occurred following exposure to propofol in non-obese patients, and literature on long-term follow-up after PUS is scarce. We report a case of PUS induced by propofol in a previously healthy non-obese woman after undergoing thoracoscopic wedge resection of pulmonary nodules under general anesthesia using propofol. The patient suddenly developed pink urine 4 h after surgery. A pink sediment rapidly precipitated at the bottom of the test tube following centrifugation of the urine. Amorphous, colorless UA-like crystals were identified under a polarizing microscope. The diagnosis of PUS was confirmed by examining the urinary UA concentration. The patient recovered and as followed-up for 1 month, during which she did not experience any urinary complications. To our knowledge, this is the first report to describe in detail a case of PUS caused by propofol in a non-obese patient with follow-up. PUS is usually benign and can resolve by rapidly on administering lactated Ringer’s solution; however, the potential risk of urinary complications, particularly UA lithiasis, should be fully realized.

Despite the shortcomings of the MPI/OpenMP hybrid parallel model that is extensively employed in massively parallel CFD solvers, this paper creates a set of MPI/OpenMP coarse-grained hybrid communication mapping rules for a structured mesh and establishes a mapping relationship among the geometric topology, the boundary communication topology, the topology of processes and threads groups, and the communication buffer. Based on the key technologies of the nonblocking asynchronous message communication and fine-grained mutex synchronization with a double-buffer mechanism for shared memory communication, an MPI/OpenMP coarse-grained hybrid parallel CFD solver framework for a structured mesh is designed. The experimental results show that the framework has high parallel performance and excellent scalability.

Complex starch is gaining research attention due to its unique physicochemical and functional properties. Lotus seed starch (LS) suspensions (6.7%, w/v) with added green tea polyphenols (GTPs) (10%, w/w) were subjected to ultrasound (200–1000 W)-microwave (150–225 W) (UM) treatment for 15 min. The effects of UM treatment on the physicochemical properties of the LS-GTP system were investigated and exceeded that of microwave or ultrasound alone. The properties (morphology, X-ray diffraction pattern and so on) were affected by GTPs to various extents, depending on ultrasonic power. These influences may be explained by the non-covalent interactions between GTPs and LS. V-type LS-GTP inclusion complex and non-inclusive complex formation were observed. Their morphology and the distribution of GTPs molecules within them were estimated using scanning electron microscopy and confocal laser scanning microscopy. Furthermore, the digestion of LS-GTP complex was investigated by a dynamic in vitro rat stomach-duodenum (DIVRSD) model, lower digestion efficiency of LS has been achieved and the residues showed gradual improvement in morphology. These all experimental results do provide new insight into the complex starch production.

DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front parallelism by loop transformations. However, previous work almost statically performs iterations in parallel threads, thus causing a waste of computing resources in thread synchronization. This paper proposes a brand-new parallel strategy for DOACROSS loops that provides a dynamic task assignment with reduced dependences to achieve wave-front parallelism through loop tiling. The proposed strategy uses a master-slave parallel mode and some customized structures to realize dynamic and flexible parallelization, which effectively avoids threads from waiting in communication. An efficient tile size selection (TSS) approach is also proposed to preserve data reuse in cache for tiled codes. The experimental results show that the proposed parallel strategy obtains good and stable speedups over six typical benchmarks with different problem sizes and different numbers of threads on an Intel® Xeon® 32-core server. And it outperforms two static strategies, a barrier-based strategy and a post/wait-based strategy, by 32% and 20% in average performance, respectively. This strategy also yields a better performance than a mutex-based dynamic strategy. Besides, it has been demonstrated that the proposed TSS approach can achieve a near-optimal performance and is comparable with a state-of-the-art TSS approach.

The gel properties and structural changes of sweet potato starch induced by heat-moisture treatment (HMT) were investigated, and its vermicelli textural properties were revealed. HMT increased the relative crystallinity, and the crystallinity reduced with increasing moisture content, which was consistent with the results of DSC. RVA results revealed that the HMT starches showed an increased setback viscosity and a reduced breakdown viscosity, indicating that the HMT starches gel lead a stronger retrogradation tendency. Rheometer results indicated that the HMT starches had a stronger elasticity behavior. The content of amylose of starch and the possible amylose fine molecular change during HMT at different water content were hypothesized, and this caused the gel properties of starch. Consequently, the HMT starch vermicelli exhibited higher hardness, springiness, and chewiness. These mechanistic relations among starch structure, gel properties, and vermicelli quality during HMT will provide useful information for the starch vermicelli industry.

Grading of glioma is crucial for treatment decision making as well as prognostic assessments. In clinical routines, radiologists grade gliomas with multiple complementary magnetic resonance imaging (MRI) sequences, which is yet challenging for glioma prediction models. In this paper, we take full advantages of four commonly used MRI sequences to propose non-invasive grading of glioma based on a variant of maximum entropy discrimination (MED) and decision tree. First, radiomics features calculation is, respectively, performed on T1-weighted imaging, T2-weighted imaging, fluid attenuation inversion recovery imaging, and contrast-enhanced T1-weighted imaging. Then, radiomics features are integrated to build a glioma prediction model named four-sequence MED (FSMED) according to the assumption that the classification margin of different sequences is consistent. Finally, we propose a multi-MED decision tree (MMEDT) model to obtain the grading of gliomas based on the output of FSMED and the results of MED on each sequence. Validation experiments are conducted on a data set collected from Henan Provincial People's Hospital (GliomaHPPH2018) and Multimodal Brain Tumor Image Segmentation Benchmark 2017 (BraTS2017). The results of these two data sets demonstrate the high-prediction performance of our method. The average areas under the curve (AUC) of MMEDT are 0.9119, 0.8184, and 0.9084 for GliomaHPPH2018, BraTS2017, and their merged set, respectively, with the corresponding average sensitivities of 92.55%, 87.85%, and 87.91%, and average specificities of 92.57%, 81.36%, and 87.39%.

Lotus seed is well known as traditional food and medicine, but its skin is usually discarded. Recent studies have shown that lotus seed skin contains a high concentration of proanthocyanidins that have multi-functions, such as antioxidation, anti-inflammation, and anti-cancer effects. In the present study, we aimed to isolate and purify the proanthocyanidins from lotus seed skin by acetone extraction and rotary evaporation, identify their chemical structures by HPLC-MS-MS and NMR, and further investigate the antioxidant properties of the extract purified by macroporous resin (PMR) from lotus seed skin both in vitro and in vivo. The results showed that PMR mainly contained oligomeric proanthocyanidins, especially dimeric procyanidin B1 (PB1), procyanidin B2 and procyanidin B4. Although it had limited ability to directly scavenge radicals in vitro, PMR could significantly enhance the expressions of antioxidant proteins via activation of nuclear factor-E2-related factor 2 (Nrf2)-antioxidant response element (ARE) pathway in HepG2 cells. Molecular data revealed that PB1, a major component in PMR, stabilized Nrf2 by inhibiting the ubiquitination of Nrf2, which led to subsequent activation of the Nrf2-ARE pathway, including the enhancements of Nrf2 nuclear translocation, Nrf2-ARE binding and ARE transcriptional activity. Moreover, the in vivo results in high fat diet-induced mice further verified the powerful antioxidant property of PMR. These results revealed that lotus seed skin is a promising resource for functional food development.

The external loads and structural ultimate strength are two important aspects for the safety of ship hull girder. It may collapse in case the structural capacity is less than the external forces in extreme seas. In the present research, progressive collapse test is performed to investigate the collapse mechanism of ship structure in waves. External load with time history and corresponding structural collapse behavior are measured and discussed to demonstrate the interaction of fluid and structures.

Test on a small scaled model is an effective approach to predict the dynamic response of full scale structure under blast loadings. However, the geometric dimensions of specimens cannot simply comply with complete geometrical similarity due to manufacture or test restrictions. It would result in the difference structural performance between the full and small scaled models. This paper proposed a corrected similarity relationship of the dynamic behaviour between prototype and replica of stiffened plates subjected to blast load, in which both the thickness of the plate and the configuration (cross-sectional shape) of stiffeners are distortedly scaled-down (double distorted geometric scaling factors). Firstly, based on the mesh convergence study and comparing with results from experimental tests, a numerical method in predicting the confined blast load and dynamic response of structure was verified, which provides a reliable means to determine the dynamic behaviour of stiffened plate designed by the corrected similarity criterion of this paper. Then, the influence of altering the stiffener configuration on the dynamic response of stiffened plates was analysed and on the basis of it, a criterion for scaling the stiffener is proposed to help design a stiffener-distorted model from prototype structure. In addition, a method for scaling the double-parameter distortedly small scaled model is proposed to predict the dynamic response of the prototype. Finally, two sets of examples of both the small size and prototype stiffened structures subjected to blast load were analysed by using the presented method. It is shown that the replica developed by applying the present method is able to accurately predict the behaviour of the full-size stiffened plates, even when the thickness of the plate and the configuration of the stiffeners are distortedly scaling down with different factors.

espanolEl presente estudio empleo herramientas quimiometricas y GC-MS para detectar la adulteracion del aceite de semilla de camelia. Con este objetivo, en el conjunto de entrenamiento se formularon 65 muestras, en las que se mezclo aceite de semilla de camelia puro con concentraciones variables de aceite de soya [soja], cacahuate [mani] y colza, utilizandose sus contenidos de acidos grasos para realizar el analisis quimiometrico. El analisis de componentes principales permitio identificar los patrones de distribucion de las muestras. Estas mostraron una clara aglomeracion estratiforme de acuerdo con la cantidad variable de aceite de semilla de camelia que poseian. Asimismo, para establecer los modelos de clasificacion, se realizo el analisis discriminante de Fisher (FDA), mediante el cual se constato que la tasa de clasificacion correcta del modelo de validacion cruzada y del modelo original alcanzo 92.5% y 82.5%, respectivamente. A fin de comprobar la calidad del modelo se preparo un nuevo conjunto de pruebas, constatandose una alta precision en los resultados, de 88%. El conjunto de resultados hizo posible comprobar que el modelo de discriminacion desarrollado, establecido por PCA mas FDA, es eficiente para determinar la presencia de aceites comestibles de bajo precio en los aceites de semilla de camelia. EnglishChemometric tools and GC-MS were employed to detect the adulteration of camellia seed oil. In the training set, 65 samples were formulated by blending pure camellia seed oil with varying concentrations of soybean, peanut and rapeseed oil and their fatty acid contents were used in chemometric analysis. Principal Component analysis revealed the distribution patterns of samples that showed a clear stratiform agglomeration according to varying amount of camellia seed oil. Fisher Discriminant Analysis (FDA) was combined to establish the classification models and the correct classification rate of cross-validation model and original model reached 92.5% and 82.5%, respectively. To test the quality of the model, a new test set was prepared and the results showed a high accuracy of 88%. This was indicated that the developed discrimination model established by PCA plus FDA was efficient in predicting the presence of other low-price edible oils in camellia seed oils.

Load balancing is essential for a render farm on a supercomputer platform, according to the architecture characteristics of Sunway Blue Light and rendering applications, the design of a rendering cell is presented to mitigate the I/O load of storage nodes. A workload-aware load balancing algorithm for a rendering cluster system is proposed to solve the problem in which the traditional interframe equipartition method, based on the assumption that multiple frames of the same scene are similar in terms of rendering time, cannot achieve optimization of the load balance and minimize the job completion time for real animation scenes. The algorithm characterizes the workload depending on the number of frames to be rendered and the user-specific computational resource demand. For heavy workloads, an interleaved task distribution method is proposed to take advantage of frame-to-frame coherence. For light workloads, benefiting from the fine-grained intraframe scheduling in the aspect of load balance, a load balancing method using flexible task granularity is introduced. By four scene models of different computational requirements, experimental results and detailed comparisons with the traditional interframe scheduling method and intraframe scheduling method show that the proposed strategy not only achieves near-optimal load balancing but also reduces the rendering time of a rendering job.

The sparrow search algorithm (SSA) is a relatively new swarm intelligence heuristic algorithm. It has fast convergence speed, strong optimization ability and more extensive application scenarios compared with traditional heuristic search methods. And thus, the SSA is attracting the attention of researchers in different fields. However, there are deficiencies of initial population quality, search ability, and population diversity in the SSA. Therefore, this paper proposes an improved sparrow search algorithm (ISSA). The ISSA uses skew tent map-based chaotic method to produce initial population for a higher quality of convergence. For the location update of the producer sparrows during the iterations, the ISSA introduces a non-linear decreasing weight, promoting both exploration and exploitation of the search space, to improve the convergence and search precision. And the mutation strategy is employed to update the location of the scrounger sparrows with lower energy and the chaotic search is combined with the local exploitation for the scroungers with higher energy, which can enhance the diversity and avoid trapping in local optimum. Simulation experiments are carried out on 26 benchmark test functions. And the results show that the ISSA is superior to or at least competitive to the SSA in the convergence properties of accuracy, speed, and stability.

In Wireless Sensor Networks (WSNs), server clusters, and other systems requiring secure transmission, the overhead of data encryption and transmission is often not negligible. Unfortunately, a conflict exists between security and efficiency in processing data. Therefore, this paper proposes a strategy to overcome this conflict, called Client-Aware Negotiation for Secure and Efficient Data Transmission (CAN-SEAT). This strategy allows a client with different security transmission requirements to use the appropriate data security transmission without modifying the client. Two methods are designed for different clients. The first method is based on two-way authentication and renegotiation. After handshakes, the appropriate data security transmission scheme is selected according to the client requirements. Another method is based on redirection, which can be applied when the client does not support two-way authentication or renegotiation. For the characteristics of different architecture, this paper classifies and discusses symmetric key algorithms, asymmetric key algorithms, and hardware encryption instructions. In four application scenarios, the CAN-SEAT strategy is tested. Compared with the general transmission strategy, when only software encryption is used, the data processing and transmission cost can be reduced by 89.41% in the best case and by 15.40% in the worst case. When supporting hardware encryption, the cost can be reduced by 85.30% and 24.63%, respectively. A good effect was produced on the experimental platforms XiLinx, FT-2000+, and Intel processors. To the best of our knowledge, for Client-Aware Negotiation (CAN), this is the first method to be successfully deployed on a general system. CAN-SEAT can be easily combined with other energy-efficient strategies.

When penetrated by a high-velocity projectile, a fluid-filled container can be severely damaged and ruptured due to the intense impact loading from Hydrodynamic Ram (HRAM), which causes a primary shock wave, and then a subsequent loading phase when a cavity evolves in the fluid. In the design of fuel tanks for aircraft, and other transport vehicles, the HRAM pressure is a major concern for the reliability of the structure. In this paper, experiments of high-velocity projectiles impacting two different types of fluid-filled containers, including an aluminium wall and a composite aluminium/rubber wall, were performed to study the mitigation effect of the rubber layer on the damage of the structure and the impact loading from Hydrodynamic Ram. A high-speed camera was employed to record the formation process of the cavity, and the shock wave pressure-time histories in the fluid were also obtained by pressure transducers. By comparing and analysing the experimental results, it is shown that the rubber layer of the composite wall container was able to reduce the reflected shock pressure and the deformation of the structure.

Three novel low molecular weight polysaccharides (RLP-1a, RLP-2a, and RLP-3a) with 9004, 8761, and 7571 Da were first obtained by purifying the crude polysaccharides from the fruits of a traditional Chinese medicinal herb Rosae Laevigatae. The conditions for polysaccharides from the R. Laevigatae fruit (RLP) extraction were optimized by the response surface methodology, and the optimal conditions were as follows: extraction temperature, 93°C; extraction time, 2.8 h; water to raw material ratio, 22; extraction frequency, 3. Structural characterization showed that RLP-1a consisted of rhamnose, arabinose, xylose, glucose, and galactose with the ratio of 3.14 : 8.21 : 1 : 1.37 : 4.90, whereas RLP-2a was composed of rhamnose, mannose, glucose, and galactose with the ratio of 1.70 : 1 : 93.59 : 2.73, and RLP-3a was composed of rhamnose, arabinose, xylose, mannose, glucose, and galactose with the ratio of 6.04 : 26.51 : 2.05 : 1 : 3.17 : 31.77. The NMR analyses revealed that RLP-1a, RLP-2a, and RLP-3a contained 6, 4, and 6 types of glycosidic linkages, respectively. RLP-1a and RLP-3a exhibited distinct antioxidant abilities on the superoxide anions, 1,1-diphenyl-2-picrylhydrazyl (DPPH), and hydroxyl radicals in vitro. RLPs could decrease the serum lipid levels, elevate the serum high-density lipoprotein cholesterol levels, enhance the antioxidant enzymes levels, and upregulate of FADS2, ACOX3, and SCD-1 which involved in the lipid metabolic processes and oxidative stress in the high-fat diet-induced rats. These results suggested that RLPs ameliorated the high-fat diet- (HFD-) induced lipid metabolism disturbance in the rat liver through the peroxisome proliferator-activated receptor (PPAR) signaling pathway. Low molecular weight polysaccharides of RLP could be served as a novel potential functional food for improving hyperlipidemia and liver oxidative stress responses.

BackgroundTumor cells with a mesenchymal phenotype and/or cancer stem-like cells (CSCs) are known to contribute to metastasis and drug resistance. Circulating tumor cells (CTCs) undergoing epithelial-mesenchymal transition (EMT) and CTCs reflecting a dedifferentiated CSC phenotype may not be detected using only an anti-EpCAM antibody to capture them. We used an antibody-independent CTC enrichment platform, ApoStream®, which does not rely on any antibody, including anti-EpCAM, to capture EMT- and CSC-CTCs in breast cancer patients who received neoadjuvant chemotherapy and correlated them to pathological complete response (pCR).MethodsBlood samples from newly diagnosed breast cancer patients were prospectively collected before neoadjuvant chemotherapy (T0), after chemotherapy but before surgery (T1), and after surgery (T2) and processed using ApoStream. CTCs detected were stained with additional markers to define 3 CTC subsets with the following phenotypes: epithelial CTCs (CK+, EpCAM+ or E-cadherin+), EMT-CTCs (β-catenin+ or vimentin+), and CSC-CTCs (CD44+ and CD24low).ResultsWe enrolled 55 patients, 47 of which had data for analysis. EMT-CTCs were detected in 57%, 62%, and 72% and CSC-CTCs in 9%, 22%, and 19% at the T0, T1, and T2 time points, respectively. Counts of epithelial (P = 0.225) and EMT (P = 0.522) phenotypes of CTCs at T0 did not significantly predict pCR. Moreover, no correlation between CTC count change and pCR was demonstrated.ConclusionsApoStream was successful in detecting EMT-CTCs among patients after neoadjuvant chemotherapy. However, EMT-/CSC-CTC counts did not correlate with pCR. Due to the small sample size and heterogeneity of this patient population, further study in a larger cohort of molecularly homogeneous patients is warranted.

This paper studies the recovery of metals Pb, Zn, and Sb in antimony smelting slag by fuming furnace. The study focuses on volatile mechanism of Pb, Zn, and Sb, metal distribution, metal recovery, and fuel consumption in the process of slag fuming. It is concluded in this report that the Pb, Zn, and Sb from reduction reaction in the molten bath during the process of fuming will be oxidized in the offgas zone and collected by dust collection. When the antimony smelting slag contains Pb ~1.2%, Zn ~6.9%, and Sb ~1.4%, the metal recovery of Pb, Zn, and Sb after fuming and volatile process will be 95%, 88%, and 60%, respectively. Meanwhile, the coal consumption is ~0.3 t per ton antimony smelting slag, when the pulverized coal with 59.92% fixed carbon is utilized as reductant and fuel.