Search

As an important technology in artificial intelligence, Granular Computing has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Information granules forming an abstract and efficient characterization of large volumes of numeric data have been considered as the fundamental constructs of Granular Computing. By generating centroids (prototypes) and partition matrix, fuzzy clustering is a commonly encountered way of information granulation. As a reverse process of granulation, degranulation involves data reconstruction completed on a basis of the granular representatives (decoding information granules into numeric data). Previous studies have shown that there is a relationship between the reconstruction error and the performance of the granulation process. Typically, the lower the degranulation error is, the better performance of granulation process becomes. However, the existing methods of degranulation usually cannot restore the original numeric data, which is one of the important reasons behind the occurrence of the reconstruction error. To enhance the quality of reconstruction (degranulation), in this study, we develop an augmented scheme through modifying the partition matrix. By proposing the augmented scheme, we elaborate on a novel collection of granulation-degranulation mechanisms. In the constructed approach, the prototypes can be expressed as the product of the dataset matrix and the partition matrix. Then, in the degranulation process, the reconstructed numeric data can be decomposed into the product of the partition matrix and the matrix of prototypes. By modifying the partition matrix, the new partition matrix is constructed through a series of matrix operations. We offer a thorough analysis of the developed scheme. The experimental results are in agreement with the underlying conceptual framework. The results obtained on both synthetic and publicly available datasets are reported to show the enhancement of the data reconstruction performance thanks to the proposed method. It is pointed out that by using the proposed approach in some cases the reconstruction errors can be reduced close to zero by using the proposed approach.

This study focuses on linguistic information operational realization through information granulation in group decision-making (GDM) scenarios where the preference information offered by decision-makers over alternatives is described using distributed linguistic preference relations (DLPRs). First, an information granulation model is proposed to arrive at the operational realization of linguistic information in the GDM with DLPRs. The information granulation is formulated as a certain optimization problem where a combination of consistency degree of individual DLPRs and consensus degree among individuals is regarded as the underlying performance index. Then, considering that the proposed model is a constrained optimization problem (COP) with an adjustable parameter, which is difficult to be effectively solved using general optimization methods, we develop a novel approach towards achieving the optimal solution, referred to as penalty function-based co-evolutionary particle swarm optimization (PFCPSO). Within the PFCPSO setting, the designed penalty function is used to transform the COPs into unconstrained ones. Besides, the penalty factors and the adjustable parameter, as well as the decision variables of the optimization problems, are simultaneously optimized through the co-evolutionary mechanism of two populations in co-evolutionary particle swarm optimization (CPSO). Finally, a comprehensive evaluation problem about car brands is studied using the proposed model and the newly developed PFCPSO approach, which demonstrates their applicability. Two comparative studies are also conducted to show the effectiveness of the proposals. Overall, this study exhibits two facets of originality: the presentation of the linguistic information granulation model, and the development of the PFCPSO approach for solving the proposed model.

Double noncovalent network chitosan/hyperbranched polyethylenimine/Fe3+ films.

In this article, an augmented subspace-based algorithm for detecting the direction of arrival (DOA) of signals is presented. In the developed scheme, a uniform circular antenna array with a full range of lateral capacity is first transformed into a uniform linear antenna array in which the steering matrix has a Vandermonde form. This kind of structure can be exploited to formulate computationally efficient search-free estimation methods. In the process of virtual transformation, a novel DOA unit matrix of an assumed sector where the signals to be detected are located is built and optimized to find response matrices of the real and virtual antenna arrays to signals from the sector. By utilizing singular value decomposition (SVD) of the response matrix of the real antenna array to possible signals from the sector, a stable virtual transformation matrix between the real and virtual antenna arrays is obtained. Meanwhile, the aperture of the original array is also expanded during this process. Then, a virtual cyclic optimization algorithm is introduced to thoroughly mine information from the correlation matrices of the virtual antenna array receiving data and to optimize the signal subspace. Subsequently, the DOA can be efficiently determined through the reconstruction of the steering matrix. In the experimental part of the study, root-mean-square errors and probability of success are used to evaluate the performance of the algorithms. In particular, simulation results demonstrate that the proposed methods provide significant accuracy improvements, especially for low signal-to-noise ratio thresholds.

Chitosan-based composite films with good biodegradability, biocompatibility, and sustainability are extensively employed in the field of food packaging. In this study, novel chitosan/tannic acid (CTA) and chitosan/oxidized tannic acid (COTA) composite films with excellent mechanical and antibacterial properties were prepared using a tape casting method. The results showed that, when 20% tannic acid (TA) was added, the tensile strength of the CTA composite film was 80.7 MPa, which was 89.4% higher than that of the pure chitosan (CS) film. TA was oxidized to oxidized tannic acid (OTA) with laccase, and the phenolic hydroxyl groups were oxidized to an o-quinone structure. With the addition of OTA, a Schiff base reaction between the OTA and CS occurred, and a dual network structure consisting of a chemical bond and hydrogen bond was constructed, which further improved the mechanical properties. The tensile strength of 3% COTA composite film was increased by 97.2% compared to that of pure CS film. Furthermore, these CTA films with significant antibacterial effects against Escherichia coli (E. coli) are likely to find uses in food packaging applications.

Soybean protein isolate (SPI) shows a broad application prospect in the food and packaging industry. However, its inferior mechanical properties and water resistance limit its application. In this work, a series of SPI-based composite films were prepared by combining with cellulose nanofiber (CNF), graphene oxide (GO), GO/CNF, ethylene glycol diglycidyl ether (EDGE) or GO/CNF/EGDE. The results show that by adding a small amount of reinforced materials (3%), the water resistance, hydrophilicity, mechanical properties and thermal stability of composite films were improved. The filling effect and hydrogen bonding of the reinforcing materials contribute to the formation of film structure. EGDE cross-link SPI with CNF and GO build a chemical network to improve the properties of the film. In addition, they could make a synergistic effect to better enhance the performance of a protein film. Therefore, the tensile strength and elastic modulus of the SGCE film reached 469.21% and 367.58%, respectively.

Key message Wheat blast resistance in Caninde#1 is controlled by a major QTL on 2NS/2AS translocation and multiple minor QTL in an additive mode. Abstract Wheat blast (WB) is a devastating disease in South America, and it recently also emerged in Bangladesh. Host resistance to WB has relied heavily on the 2NS/2AS translocation, but the responsible QTL has not been mapped and its phenotypic effects in different environments have not been reported. In the current study, a recombinant inbred line population with 298 progenies was generated, with the female and male parents being Caninde#1 (with 2NS) and Alondra (without 2NS), respectively. Phenotyping was carried out in two locations in Bolivia, namely Quirusillas and Okinawa, and one location in Bangladesh, Jashore, with two sowing dates in each of the two cropping seasons in each location, during the years 2017–2019. Genotyping was performed with the DArTseq® technology along with five previously reported STS markers in the 2NS region. QTL mapping identified a major and consistent QTL on 2NS/2AS region, explaining between 22.4 and 50.1% of the phenotypic variation in different environments. Additional QTL were detected on chromosomes 1AS, 2BL, 3AL, 4BS, 4DL and 7BS, all additive to the 2NS QTL and showing phenotypic effects less than 10%. Two codominant STS markers, WGGB156 and WGGB159, were linked proximally to the 2NS/2AS QTL with a genetic distance of 0.9 cM, being potentially useful in marker-assisted selection.

The application of pure chitosan films is significantly limited due to their poor mechanical properties. In this study, a novel type of chitosan/hyperbranched polyethylenimine (CHP) and chitosan/hyperbranched polyethylenimine/Fe

This study investigated the AQI (air quality index) and atmospheric pollutants including PM2.5, PM10, CO, SO2, NO2 and O3 in Chongqing, Luzhou and Chengdu from 2017 to 2019. In addition, the impacts of the COVID-19 event on the air quality in the three cities in 2020 were compared and discussed. For the combined AQIs for the three cities, in spring, the daily AQIs ranged between 25 and 182 and averaged 72.1. In summer, the daily AQIs ranged between 24 and 206 and averaged 77.5. In autumn, the daily AQIs ranged between 22 and 170 and averaged 61.1, and in winter, the daily AQIs ranged between 28 and 375 and averaged 99.6. The distributions of the six AQI classes in spring were 3%, 94%, 3%, 0%, 0%, and 0%; in summer, they were 11%, 74%, 15%, 0%, 0% and 0%; in autumn, they were 29%, 70%, 1%, 0%, 0%, and 0%, and in winter, they were 1%, 52%, 44%, 3%, 0%, and 0%, respectively. The average AQIs, in order, were Chengdu (85.4) > Chongqing (73.8) > Luzhou (73.2). Both the highest AQIs and PM2.5 (as the major indicatory air pollutant) occurred mainly in the low temperature season (January, December, and February), while O3 was the main air pollutant in June and August when the weather was hot. In February 2020, during the epidemic prevention and control actions taken in response to COVID-19 for the three cities, the combined AQIs for the top five days with the highest AQIs in February 2020 was 79.4, which was 23.6% lower than that from 2017–2019 (AQI = 100.7), and the average concentrations of PM2.5, PM10, SO2, CO, and NO2 were 89.4 µg m–3, 106 µg m–3, 2.31 ppb, 0.72 ppm, and 12.3 ppb, respectively, and were 17.9%, 30.8%, 83.8%, 19.8%, and 62.1%, lower than those in February 2017–2019. However, the average O3 concentration (31.8 ppb) in February 2020 rather than decreasing, increased by 6.2%. This is because a lower NO2 concentration hindered the NO + O3 reaction and led to increase O3 concentration in the ambient air.

Both the air quality index (AQI) and indicatory air pollutants of Anqing, Hefei, and Suzhou near central China from 2017 to 2019, and the impact of COVID-19 epidemic prevention and control actions on air quality were investigated. The combined data for the three cities from 2017 to 2019 indicated that the lowest AQI (averaged 78.1) occurred in the summer season, for which the AQI proportions for classes I, II, III, IV, V, and VI were 25.6%, 49.9%, 21.9%, 2.7%, 0%, and 0%, respectively. The highest (AQI average of 112.6) was in winter, for which the proportions were 7.4%, 39.5%, 33.3%, 12.5%, 7.2%, and 0.1%, respectively. PM2.5, PM10, and NO2 in order were the most important indicatory air pollutants for AQI classes IV, V, and VI, which all prevailed in winter and spring, while O3 was the indicatory air pollutant that occurred most in summer. The COVID-19 event, which triggered global attention, broke out at the end of 2019. This study also investigated and compared the air quality levels in the three cities from January to March 2017–2019 with those in 2020. The results showed that during February 2020, in the three cities, the average ambient air concentrations of PM2.5, PM10, SO2, CO, and NO2 were 41.9 µg m–3, 50.1 µg m–3, 2.18 ppb, 0.48 ppm, and 8.97 ppb, and were 46.5%, 48.9%, 52.5%, 36.2%, and 52.8%, respectively, lower than those in the same month in 2017–2019, respectively. However, the O3 average concentration (80.6 ppb) did not show significant fluctuations and even slightly increased by 3.6%. This is because a lower concentration of NO2 resulted in constraints on the reaction of NO + O3, so the O3 level could not be effectively further reduced. In addition, this study also analyzed and compared the five highest daily AQIs from February 2017–2019 with those of 2020 for the three cities. The mean AQI for the 5 days with the highest daily AQI (averaged 122.6) in February 2020 was 45.1% lower than that for February 2017–2019 (averaging 223.2), and the indicatory air pollutant was always PM2.5, which decreased by 46.7% (from 173.6 to 92.6 µg m–3). It is clear that during the COVID-19 epidemic prevention and control action periods, the air quality near central China improved significantly.

In early 2020, the COVID-19 epidemic spread globally. This study investigated the air quality of three cities in Hubei Province, Wuhan, Jingmen, and Enshi, central China, from January to March 2017–2020 to analyze the impact of the epidemic prevention and control actions on air quality. The results indicated that in the three cities, during February 2020, when the epidemic prevention and control actions were taken, the average concentrations of atmospheric PM2.5, PM10, SO2, CO, and NO2 in the three cities were 46.1 µg m–3, 50.8 µg m–3, 2.56 ppb, 0.60 ppm, and 6.70 ppb, and were 30.1%, 40.5%, 33.4%, 27.9%, and 61.4% lower than the levels in February 2017–2019, respectively. However, the average O3 concentration (23.1, 32.4, and 40.2 ppb) in 2020 did not show a significant decrease, and even increased by 12.7%, 14.3%, and 11.6% in January, February, and March, respectively. This is because a lower concentration of NO2 resulted in constraints on the NO + O3 reaction, and the O3 could not be effectively further depleted. In addition, the average air quality index (AQI) for the three cities in January, February, and March 2020 were 32.2%, 27.7%, and 14.9% lower than the levels in 2017–2019, respectively. Based on the AQIs for the three cities, the combined proportions of Class I and Class Ⅱ in January, February, and March 2020 increased by 27.9%, 24.8%, and 4.3%, respectively, while the combined proportion of AQI Classes III, IV, V, and VI was reduced from 34.8% to 15.8%. In addition, in the first three months of 2020, the indicatory air pollutants in the three cities for the AQIs were predominant in the following order: PM2.5 (72.0%), O3 (16.4%), PM10 (8.3%), NO2 (2.9%), and CO (0.4%). This study provides useful information for establishing a scientific air pollution control strategy and is a valuable reference for future research on improving urban air quality.

The COVID-19 epidemic discovered and reported at the end of December 2019 and began spreading rapidly around the world. The impact of the COVID-19 event on the trip intensity, AQI (air quality index), and air pollutants, including PM2.5, PM10, SO2, CO, NO2, and O3 in Shenzhen, Guangzhou, and Foshan (the so-called ‘three cities’) from January 12 to March 27, in 2019 and 2020, are compared and discussed. In 2020, the combined trip intensity in the three cities ranged between 0.73 and 5.54 and averaged 2.57, which was 28.4% lower than that in 2019. In terms of the combined AQIs for the three cities, from January 12 to March 26, 2020, the daily AQIs ranged between 21.0 and 121.3 and averaged 56.4, which was 16.0% lower than that in 2019. The average AQIs in order were Guangzhou (57.5) > Foshan (54.1) > Shenzhen (44.1). In 2019, the distribution proportions of the six AQI classes were 45.2%, 50.4%, 4.40%, 0%, 0%, and 0%, respectively, while those in 2020 were 62.7%, 37.3%, 0%, 0%, 0% and 0%, respectively. For the combined data for the three cities, on the top five days with the highest AQIs during the epidemic period, the average concentrations of PM2.5, PM10, SO2, CO, NO2, and O3 were 76.4 μg m–3, 113.4 μg m–3, 5.14 ppb, 0.88 ppm, 36.5 ppb and 55.5 ppb, which were 55.2%, 49.4%, 55.1%, 30.0%, 45.1% and 15.5% lower than those during the non-epidemic period (from January 12 to March 27, 2017–2019). The above results revealed that the comprehensive strict epidemic prevention and control actions reduced trip intensity and improved the air quality significantly.

The weak rate capability and cyclic stability are stubborn issues limiting the application of intriguing lithium-rich layered oxide in the lithium-ion batteries. In this work, a glucose-based treatment was proposed to modify the microstructure and electrochemical properties of the lithium-rich layered oxide. A newly formed layered-spinel surface and chemically activated Li2MnO3 component were acquired through the glucose-based procedure. Notably increased initial coulombic efficiencies, discharge capacities, rate performance, and cyclic stability were observed in the modified samples. Typically, the discharge capacity and central voltage retentions after 100 cycles grow from 73.4% and 78.7% for the pristine to 84.1% and 86.2% for the treated sample. This improvement in electrochemical properties of the treated sample results from the co-contribution of the significantly promoted redox reaction at cathode surface, accelerated Li+ bulk diffusion rate, and tuned electrochemical evolution behavior of the lithium-rich layered oxide. This work provides a green and cost-efficient way for promoting the electrochemical properties of the lithium-rich layered oxide.

Wheat blast (WB) caused by Magnaporthe oryzae pathotype Triticum (MoT) is an important fungal disease in tropical and subtropical wheat production regions. The disease was initially identified in Brazil in 1985, and it subsequently spread to some major wheat-producing areas of the country as well as several South American countries such as Bolivia, Paraguay, and Argentina. In recent years, WB has been introduced to Bangladesh and Zambia via international wheat trade, threatening wheat production in South Asia and Southern Africa with the possible further spreading in these two continents. Resistance source is mostly limited to 2NS carriers, which are being eroded by newly emerged MoT isolates, demonstrating an urgent need for identification and utilization of non-2NS resistance sources. Fungicides are also being heavily relied on to manage WB that resulted in increasing fungal resistance, which should be addressed by utilization of new fungicides or rotating different fungicides. Additionally, quarantine measures, cultural practices, non-fungicidal chemical treatment, disease forecasting, biocontrol etc., are also effective components of integrated WB management, which could be used in combination with varietal resistance and fungicides to obtain reasonable management of this disease.

Spatial spectrum estimation, also known as direction of arrival (DOA) detection, is a popular issue in many fields, including remote sensing, radar, communication, sonar, seismic exploration, radio astronomy, and biomedical engineering. MUltiple SIgnal Classification (MUSIC) and Estimation Signal Parameter via Rotational Invariance Technique (ESPRIT), which are well-known for their high-resolution capability for detecting DOA, are two examples of an eigen-subspace algorithm. However, missed detection and estimation accuracy reduction often occur due to the low signal-to-noise ratio (SNR) and snapshot deficiency (small time-domain samples of the observed signal), especially for sources with different SNRs. To avoid the above problems, in this study, we develop a DOA detection approach through signal subspace reconstruction using Quantum-Behaved Particle Swarm Optimization (QPSO). In the developed scheme, according to received data, a noise subspace is established through performing an eigen-decomposition operation on a sampling covariance matrix. Then, a collection of angles randomly selected from the observation space are used to build a potential signal subspace on the basis of the steering matrix of the array. Afterwards, making use of the fact that the signal space is orthogonal to the noise subspace, a cost function, which contains the desired DOA information, is designed. Thus, the problem of capturing the DOA information can be transformed into the optimization of the already constructed cost function. In this respect, the DOA finding of multiple signal sources—that is, the multi-objective optimization problem—can be regarded as a single objective optimization problem, which can effectively reduce the probability of missed detection of the signals. Subsequently, the QPSO is employed to determine an optimal signal subspace by minimizing the orthogonality error so as to obtain the DOA. Ultimately, the performance of DOA detection is improved. An explicit analysis and derivation of the developed scheme are provided. The results of computer simulation show that the proposed scheme has superior estimation performance when detecting signals with very different SNR levels and small snapshots.

Soybean protein isolate (SPI) shows a broad application prospect in the food and packaging industry. However, its inferior mechanical properties and water resistance limit its application. In this work, a series of SPI-based composite films were prepared by combining with cellulose nanofiber (CNF), graphene oxide (GO), GO/CNF, ethylene glycol diglycidyl ether (EDGE) or GO/CNF/EGDE. The results show that by adding a small amount of reinforced materials (3%), the water resistance, hydrophilicity, mechanical properties and thermal stability of composite films were improved. The filling effect and hydrogen bonding of the reinforcing materials contribute to the formation of film structure. EGDE cross-link SPI with CNF and GO build a chemical network to improve the properties of the film. In addition, they could make a synergistic effect to better enhance the performance of a protein film. Therefore, the tensile strength and elastic modulus of the SGCE film reached 469.21% and 367.58%, respectively.

The separation of signal-and-noise subspaces is a crucial step in many array signal processing applications, since the performance of most high-resolution methods mainly depends on the accuracy of separated signal-and-noise subspaces. If the resulting signal subspace is inaccurately estimated, high-resolution subspace-based algorithms would most likely fail. In this paper, we propose a high-accuracy method to complete the separation of signal-and-noise subspaces. In the developed scheme, eigenvalues of the covariance matrix of the data received by the uniform linear array are first employed to construct an ideal sample space using the Schur product of matrices. Then, the Gaussian kernel is introduced to map the sample space into a new high-dimensional feature space, where the resulting structure becomes linearly separable. In the sequel, we propose two fuzzy set-based methods to divide the feature space into two subspaces, which correspond to the signal-and-noise subspaces. In this way, the signal subspace becomes separated. Experimental results show that, compared with the results produced by five other commonly used algorithms, the proposed method yields much higher accuracy, especially for low signal-to-noise ratio thresholds and small snapshots.

Li-rich layered oxides are promising cathode materials for advanced Li-ion batteries because of their high specific capacity and operating potential. In this work, the Li-rich layered oxide Li 1·2 Mn 0·54 Ni 0·13 Co 0·13 O 2 (LMNC), is modified via a carbonization-reduction process (yielding the corresponding reduced compound denoted LMNC-R). Compared to the pristine oxide, LMNC-R delivers significantly enhanced initial discharge capacity/columbic efficiency, remarkably improved rate performance with an accelerated Li + diffusion rate, and significantly increased capacity/voltage retention. The specific energy density and energy retention after 100 cycles increase from 378.2 Wh kg −1 and 47.7% for LMNC to 572.0 Wh kg −1 and 71.3%, respectively, for LMNC-R. The enhancement in the electrochemical performance of LMNC-R can be attributed to the synchronous formation of the oxygen non-stoichiometric Li 2 MnO 3-δ component and to the carbon/spinel double coating layer in the material that resulted from the post-treatment process. Thus, the carbonization-reduction modification process can be used to tailor the structural evolution procedure and to suppress the metal ion dissolution of the Li-rich layered oxide during cycling.

Additional file 2.

Additional file 1.

Background: An appropriate diet is an important determinant of kidney health. However, the association between vegetarian diets and renal function is unclear. We aimed to study the association between vegetarian diets and renal function in healthy adults. Methods: A total of 269 vegetarians and 269 sex- and age-matched nonvegetarian omnivores were enrolled in this cross-sectional study. Basic characteristics and daily dietary intakes were assessed by face-to-face interviews. Blood samples were collected, and renal function was assessed by measuring blood urea nitrogen (BUN), serum creatinine (SCr), uric acid (UA) and the estimated glomerular filtration rate (eGFR). Blood pressure, fasting blood glucose and blood lipid profiles were also assessed.Results: The average age of the vegetarians was 35.4±8.6 years, 82.2% of whom were female. We evaluated the association between vegetarian diets and renal function using multivariate analysis. Compared with omnivores, vegetarians had lower BUN [β= -0.63, 95% confidence interval (CI): (-0.88 , -0.38)], SCr [β= -2.04, 95% CI:(-4.10, 0.02)], and UA levels [β= -15.15, 95% CI: (-27.81, -2.50)] and higher eGFRs [β= 4.04, 95% CI: (0.30, 7.78)] after adjusting for sex, age, body mass index (BMI), physical activity, alcohol consumption, smoking status, low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), systolic pressure and fasting blood glucose. Further analysis of food composition and renal function showed that dietary fiber intake was significantly negatively associated with BUN [β= -0.02, 95% CI: (-0.03, 0.00)], SCr [β= -0.14, 95% CI: (-0.25, 0.04)], and UA levels [β= -0.72, 95% CI: (-1.36, 0.07)] and positively associated with the eGFR [β= 0.20, 95% CI: (0.00, 0.40)]. Conclusions: Healthy adult vegetarians have better renal function than omnivores, and the higher dietary fiber intake associated with vegetarian diets may contribute to the protective effect on renal function.

Information granules have been considered as the fundamental constructs of Granular Computing. As a useful unsupervised learning technique, Fuzzy C-Means (FCM) is one of the most frequently used methods to construct information granules. The FCM-based granulation–degranulation mechanism plays a pivotal role in Granular Computing. In this paper, to enhance the quality of the degranulation (reconstruction) process, we augment the FCM-based degranulation mechanism by introducing a vector of fuzzification factors (fuzzification factor vector) and setting up an adjustment mechanism to modify the prototypes and the partition matrix. The design is regarded as an optimization problem, which is guided by a reconstruction criterion. In the proposed scheme, the initial partition matrix and prototypes are generated by the FCM. Then a fuzzification factor vector is introduced to form an appropriate fuzzification factor for each cluster to build up an adjustment scheme of modifying the prototypes and the partition matrix. With the supervised learning mode of the granulation–degranulation​ process, we construct a composite objective function of the fuzzification factor vector, the prototypes and the partition matrix. Subsequently, the particle swarm optimization is employed to optimize the fuzzification factor vector to refine the prototypes and develop the optimal partition matrix. Finally, the reconstruction performance of the FCM algorithm is enhanced. Overall, we show that the enhanced version of the degranulation process is beneficial to reduce the deterioration of the reconstruction results and improve the performance of the mechanism of granulation–degranulation, which is also meaningful for transforming data between numeric form and granular format. We offer a thorough analysis of the developed scheme. In particular, we show that the classical FCM algorithm forms a special case of the proposed scheme. Experiments completed for both synthetic and publicly available datasets demonstrate that the proposed approach outperforms the generic data reconstruction approach.

Cobalt-free perovskites, Ln 0.5 Sr 0·5 Fe 0·8 Cu 0·2 O 3−δ (Ln = La, Pr, and Nd), are systematically evaluated as the cathode materials for intermediate-temperature solid oxide fuel cells (IT-SOFCs) using Gd 0.1 Ce 0·9 O 1.95 as the electrolyte. The samples exhibit an orthorhombic perovskite structures, and their cell volumes decrease as the ionic radius of Ln decreases. Both the oxygen vacancy content and the magnitude of lattice oxygen release per formula unit increase in the temperature range from 370 °C to 850 °C as the ionic radius of Ln decreases. Ln 0.5 Sr 0.5 Fe 0.8 Cu 0.2 O 3−δ is chemically and thermally compatible with the Gd 0.1 Ce 0·9 O 1.95 electrolyte. In the temperature range of 600 °C-750 °C, Nd 0.5 Sr 0·5 Fe 0·8 Cu 0·2 O 3−δ possesses the highest catalytic activity for the oxygen reduction reaction with area specific resistance values of 0.071 Ω cm 2 and 0.141 Ω cm 2 at 750 °C and 700 °C, respectively. The maximum power densities of the anode-supported single cells at 800 °C and 700 °C are 1003.7 mW cm −2 and 516.7 mW cm −2 for Pr 0.5 Sr 0·5 Fe 0·8 Cu 0·2 O 3−δ and 944.5 mW cm −2 and 530.2 mW cm −2 for Nd 0.5 Sr 0·5 Fe 0·8 Cu 0·2 O 3−δ , respectively. Ln 0.5 Sr 0.5 Fe 0.8 Cu 0.2 O 3−δ is shown to be a promising cathode material for IT-SOFCs.

Switchgrass (Panicum virgatum L.; family Poaceae) is a warm-season C4 perennial grass. Tillering plays an important role in determining the morphology of aboveground parts and the final biomass yield of switchgrass. Auxin distribution in plants can affect a variety of important growth and developmental processes, including the regulation of shoot and root branching, plant resistance and biological yield. Auxin transport and gradients in plants are mediated by influx and efflux carriers. PvPIN1, a switchgrass PIN1-like gene that is involved in regulating polar transport, is a putative auxin efflux carrier. Neighbor-joining analysis using sequences deposited in NCBI databases showed that the PvPIN1gene belongs to the PIN1 family and is evolutionarily closer to the Oryza sativa japonica group. Tiller emergence and development was significantly promoted in plants subjected toPvPIN1 RNA interference (RNAi), which yielded a phenotype similar to that of wild-type plants treated with the auxin transport inhibitor TIBA (2,3,5-triiodobenzoic acid). A transgenic approach that inducedPvPIN1 gene overexpression or suppression altered tiller number and the shoot/root ratio. These data suggest that PvPIN1plays an important role in auxin-dependent adventitious root emergence and tillering.

Dust agglomeration in an electrostatic precipitator (EP) during the sintering process taking place in an ironmaking plant was investigated. The dust agglomeration in the high sulfur flue gas dust hopper of the EP was very serious and did affect the removal of the dust from the hopper. The size of the agglomerate ranged from approximately 30–50 cm and was found to exhibit strong magnetic behavior. After combining actual operational observations and the physical and chemical test results, it was determined that the main factor resulting in the dust agglomeration in the EP was the unburned carbon, which was between 0.025% and 4.45% in the four samples of EP dust taken from different locations in the EP. In order to prevent fire accidents and dust agglomeration in the EP during the sintering process, the percentage of fine fuel particles (sized smaller than 1 mm) should be minimized; the average fuel particle size for the sintering process should be controlled at 2.5–3.0 mm, where the mass fraction accounts for approximately 80% of the fuel. In addition, strict sealing of the air box flue, the import and export flange, the expansion joint connection, the manhole door, and EP body should be carried out and maintained. Finally, the thickness of the bedding material should be more than 30 mm to ensure full combustion of the fuel used in the sintering process. This study provides useful information for the prevention of dust agglomeration in the EP during the sintering process.

During recent years, the development of mechanically robust epoxy resins from natural abundant plant oils is gaining more and more attention. Herein, two strategies were developed to precisely tune the microstructure of plant oil-derived epoxy polymers and mechanical properties of their thermosets. In strategy 1, plant oil-derived epoxy polymers (EPs) with varied densities of epoxy groups were prepared and epoxy resins with tunable mechanical properties were obtained. Tensile test revealed that the mechanical strength, Young's modulus, and toughness increased with the increase of epoxy group density. In strategy 2, the mechanical performanceof plant oil-derived epoxy resins were greatly improved by introducing vanillin as rigid segments. Moreover, the mechanical properties of plant oil-based epoxy resins could be precisely tuned via either strategy 1 or strategy 2, and thermosets from soft elastomers to rigid plastics were obtained. Due to the existence of well-defined chemical networks, plant oil-based epoxy resins exhibit excellent thermally induced shape memory properties.