Investigation of the Cofiring Process of Raw or Torrefied Bamboo and Masson Pine by Using a Cone Calorimeter

Cofiring characteristics of raw or torrefied bamboo and masson pine blends with different blend ratios were investigated by cone calorimetry, and its ash performance from cofiring was also determined by a YX-HRD testing instrument, X-ray fluorescence, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Results showed that bamboo and masson pine had the different physicochemical properties. Torrefaction improved fuel performances, resulting in a more stable cofiring process. It also decreased the heat release rate, total heat release, and total suspended particulates of fuels, especially CO2 and CO release. Masson pine ash mainly included CaO, SiO2, Fe2O3, K2O, and Al2O3. Bamboo ash was mainly composed of K2O, SiO2, MgO, and SO3. There were different melting temperatures and trends between different samples. The synergistic reaction of ash components was found during the cofiring process. The surface morphology of blend ash changed with the variation of bamboo or masson pine content

Incoherent Dictionary Learning Method Based on Unit Norm Tight Frame and Manifold Optimization for Sparse Representation

Optimizing the mutual coherence of a learned dictionary plays an important role in sparse representation and compressed sensing. In this paper, a efficient framework is developed to learn an incoherent dictionary for sparse representation. In particular, the coherence of a previous dictionary (or Gram matrix) is reduced sequentially by finding a new dictionary (or Gram matrix), which is closest to the reference unit norm tight frame of the previous dictionary (or Gram matrix). The optimization problem can be solved by restricting the tightness and coherence alternately at each iteration of the algorithm. The significant and different aspect of our proposed framework is that the learned dictionary can approximate an equiangular tight frame. Furthermore, manifold optimization is used to avoid the degeneracy of sparse representation while only reducing the coherence of the learned dictionary. This can be performed after the dictionary update process rather than during the dictionary update process. Experiments on synthetic and real audio data show that our proposed methods give notable improvements in lower coherence, have faster running times, and are extremely robust compared to several existing methods

Nitrogen Self-Doped Activated Carbons Derived from Bamboo Shoots as Adsorbent for Methylene Blue Adsorption

Bamboo shoots, a promising renewable biomass, mainly consist of carbohydrates and other nitrogen-related compounds, such as proteins, amino acids and nucleotides. In this work, nitrogen self-doped activated carbons derived from bamboo shoots were prepared via a simultaneous carbonization and activation process. The adsorption properties of the prepared samples were evaluated by removing methylene blue from waste water. The factors that affect the adsorption process were examined, including initial concentration, contact time and pH of methylene blue solution. The resulting that BSNC-800-4 performed better in methylene blue removal from waste water, due to its high specific surface area (2270.9 m2 g−1), proper pore size (2.19 nm) and relatively high nitrogen content (1.06%). Its equilibrium data were well fitted to Langmuir isotherm model with a maximum monolayer adsorption capacity of 458 mg g−1 and a removal efficiency of 91.7% at methylene blue concentration of 500 mg L−1. The pseudo-second-order kinetic model could be used to accurately estimate the carbon material’s (BSNC-800-4) adsorption process. The adsorption mechanism between methylene blue solution and BSNC-800-4 was controlled by film diffusion. This study provides an alternative way to develop nitrogen self-doped activated carbons to better meet the needs of the adsorption applications

Fisetin Inhibited Growth and Metastasis of Triple-Negative Breast Cancer by Reversing Epithelial-to-Mesenchymal Transition via PTEN/Akt/GSK3β Signal Pathway

Triple negative breast cancer (TNBC), characterized by its highly aggressive and metastatic features, is associated with poor prognosis and high mortality partly due to lack of effective treatment. Fisetin, a natural flavonoid compound, has been demonstrated to possess anti-cancer effects in various cancers. However, the effects and mechanisms of fisetin on metastasis of TNBC remain uncovered. In this study, we found that fisetin dose-dependently inhibited cell proliferation, migration and invasion in TNBC cell lines MDA-MB-231 and BT549 cells. In addition, fisetin reversed epithelial to mesenchymal transition (EMT) as evaluated by cell morphology and EMT markers in MDA-MB-231 and BT549 cells. Furthermore, fisetin suppressed phosphoinositol 3-kinase (PI3K)-Akt-GSK-3β signaling pathway but upregulated the expression of PTEN mRNA and protein in a concentration-dependent manner. Further, silence of PTEN by siRNA abolished these benefits of fisetin on proliferation and metastasis of TNBCs. In vivo, using the metastatic breast cancer xenograft model bearing MDA-MB-231 cells, we found that fisetin dramatically inhibited growth of primary breast tumor and reduced lung metastasis, meanwhile, the expression of EMT molecules and PTEN/Akt/GSK-3β in primary and metastatic tissues changed in the same way as those in vitro experiments. In conclusion, all these results indicated that fisetin could effectively suppress proliferation and metastasis of TNBC and reverse EMT process, which might be mediated by PTEN/Akt/GSK-3β signaling pathway

Incoherent Dictionary Learning Method Based on Unit Norm Tight Frame and Manifold Optimization for Sparse Representation

Optimizing the mutual coherence of a learned dictionary plays an important role in sparse representation and compressed sensing. In this paper, a efficient framework is developed to learn an incoherent dictionary for sparse representation. In particular, the coherence of a previous dictionary (or Gram matrix) is reduced sequentially by finding a new dictionary (or Gram matrix), which is closest to the reference unit norm tight frame of the previous dictionary (or Gram matrix). The optimization problem can be solved by restricting the tightness and coherence alternately at each iteration of the algorithm. The significant and different aspect of our proposed framework is that the learned dictionary can approximate an equiangular tight frame. Furthermore, manifold optimization is used to avoid the degeneracy of sparse representation while only reducing the coherence of the learned dictionary. This can be performed after the dictionary update process rather than during the dictionary update process. Experiments on synthetic and real audio data show that our proposed methods give notable improvements in lower coherence, have faster running times, and are extremely robust compared to several existing methods

Environment‐adaptive coassembly/self‐sorting and stimulus‐responsiveness transfer based on cholesterol building blocks

Manipulating the property transfer in nanosystems is a challenging task since it requires switchable molecular packing such as separate aggregation (self‐sorting) or synergistic aggregation (coassembly). Herein, a unique manipulation of self‐sorting/coassembly aggregation and the observation of switchable stimulus‐responsiveness transfer in a two component self‐assembly system are reported. Two building blocks bearing the same cholesterol group give versatile topological structures in polar and nonpolar solvents. One building block (cholesterol conjugated cynanostilbene, CCS) consists of cholesterol conjugated with a cynanostilbene unit, and the other one (C10CN) is comprised of cholesterol connected with a naphthalimide group having a flexible long alkyl chain. Their assemblies including gel, crystalline plates, and vesicles are obtained. In gel and crystalline plate phases, the self‐sorting behavior dominates, while synergistic coassembly occurs in vesicle phase. Since CCS having the cyanostilbene group can respond to the light irradiation, it undergoes light‐induced chiral amplification. C10CN is thermally responsive, whereby its supramolecular chirality is inversed upon heating. In coassembled vesicles, it is interestingly observed that their responsiveness can be transferred by each other, i.e., the C10CN segment is sensitive to the light irradiation, while CCS is thermoresponsive. This unprecedented behavior of the property transfer may shine a light to the precise fabrication of smart materials.Published versio

Cr(VI) Adsorption from Aqueous Solution by UiO-66 Modified Corncob

To adsorb hexavalent chromium (Cr(VI)) in polluted water, this paper prepared a UiO-66 (Zr6O4(OH)4(BDC)12) modified granular corncob composite adsorbent by hydrothermal method with in situ loading of UiO-66 on pretreated corncob particles. The physicochemical properties of the synthesized samples were characterized. Batch adsorption experiments were conducted to investigate the adsorption process of aqueous Cr(VI) under various conditions (different ionic strength, pH and co-existing anions). The results showed that UiO-66 was successfully loaded on the modified corncob particles. The isothermal adsorption data of Cr(VI) adsorption by the UiO-66 modified corncob fit well with the Langmuir model with the maximum adsorption capacity of Cr(VI) on UiO-66@Corn+ being 90.04 mg/g. UiO-66 loading could increase Cr(VI) adsorption capacity of Corn+. The kinetic study showed that the equilibrium time for Cr(VI) adsorption on UiO-66 modified corncob was about 180 min and the kinetic data followed the pseudo-secondary kinetic model. The Cr(VI) adsorption capacity on UiO-66@Corn+ decreased with the increasing solution pH, and the optimum pH range was 4–6. The ionic strength has little effect on the Cr(VI) adsorption capacity, but the coexistence of CO32−, SO42− and PO43− in the solution could significantly decrease the equilibrium adsorption capacity of Cr(VI). The adsorption mechanism analysis showed that Cr(VI) was adsorbed on the surface of adsorbents through electrostatic attraction and was reduced further to the less toxic Cr(III) by the electron donor on the surface of adsorbent. The electrostatic interaction was the main force affecting the adsorption of Cr(VI) by UiO-66. UiO-66@Corn+ had an excellent removal efficiency of Cr(VI) and excellent reusability. UiO-66@Corn+ could effectively remove Cr(VI) from water and have a promising application

Self-assembled Aza-boron-dipyrromethene for ferroptosis-boosted sonodynamic therapy

The presence of apoptosis inhibition proteins renders the cancer cells resistant to apoptosis, severely compromising the antitumor efficacy of sonodynamic therapy (SDT). Here, an intelligent anticancer nanoplatform based on an Aza-boron-dipyrromethene dye (denoted as Aza-BDY) is elaborately established for ferroptosis augmented SDT through cysteine (Cys) starvation. After endocytosis by tumor cells, Aza-BDY serves as both a ferroptosis inducing agent and a sonosensitizer for tumor treatment. The specific Cys response facilitates the disruption of redox homeostasis and initiation of cellular ferroptosis. Meanwhile, the released sonosensitizer causes efficient SDT and augments ferroptosis under ultrasound irradiation. Detailed in vitro and in vivo investigations demonstrate that the synergistic effect of Cys depletion and singlet oxygen (1 O2 ) generation significantly induces cancer-cell death and suppresses tumor proliferation with a high inhibition rate of 97.5 %.Agency for Science, Technology and Research (A*STAR)National Research Foundation (NRF)We greatly acknowledge the financial support from the National Natural Science Foundation of China (32171391 and 51902336), the Shanghai Science and Technology Program (21010500100), the Basic Research Program of Shanghai Municipal Government (21JC1406002), the Shanghai Rising-Star Program (22QA1403600), the Singapore National Research Foundation Investigatorship (NRF-NRFI2018-03), and the Singapore Agency for Science, Technology and Research (A*STAR) AME IRG grant (A20E5c0081)