Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Design,synthesis and evaluation of novel dehydroabietic acid-dithiocarbamate hybrids as potential multi-targeted compounds for tumor cytotoxicity

In the present study, novel representatives of the important group of biologically-active, dehydroabietic acid-bearing dithiocarbamate moiety, were synthesized and characterized by ¹H NMR, ¹³C NMR, HR-MS. The in vitro antiproliferative activity evaluation (MTT) indicated that these compounds exhibited potent inhibitory activities in various cancer cell lines (HepG-2, MCF-7, HeLa, T-24, MGC-803). Particularly, compound III-b possessed extraordinary cytotoxicity with low micromolar IC₅₀ values ranging from 4.07 to 38.84 µM against tested cancer cell lines, while displayed weak cytotoxicity on two normal cell lines (LO-2 and HEK 293 T). Subsequently, the potential mechanisms of representative compound III-b were elementarily investigated by Transwell experiment, which showed III-b can inhibit cancer cells migration. Annexin-V/PI dual staining showed that the compound can induce HepG-2 cells apoptosis in a dose-dependent manner. Meanwhile this apoptosis may be related to the upregulated protein expression of cleaved-caspase 3, cleaved-caspase 9, Bax and downregulated of Bcl-2 indicated by Western Blot. Later study further confirmed that ROS levels in HepG-2 cells increased significantly with the rise of concentrations. In addition, through the network pharmacology data analyzing, the core targets and signaling pathways of compound III-b for treatment of liver neoplasms were forecasted. Molecular docking model showed that compound III-b had high affinity with hub targets (CASP3, EGFR, HSP90AA1, MAPK1, ERBB2, MDM2), suggesting that compound III-b might target the hub protein to modulate signaling activity. Taken together, these data indicated that dehydroabietic acid structural modification following the “Molecular hybridization” principle is a feasible way to discover the potential multi-targeted antitumor compounds.     

Theoretical study of (e,2e) triple differential cross sections of pyrimidine and tetrahydrofurfuryl alcohol molecules using multi-center distorted-wave method

We report theoretical studies of electron impact triple differential cross sections of two bio-molecules,pyrimidine and tetrahydrofurfuryl alcohol,in the coplanar asymmetric kinematic conditions with the impact energy of 250 eV and ejected electron energy of 20 eV at three scattering angles of-5°,-10°,and-15°.Present multi-center distorted-wave method well describes the experimental data,which was obtained by performing(e,2e)experiment.The calculations show that the secondary electron produced by the primary impact electron is strongly influenced by the molecular ionic multi-center potential,which must be considered when the low energy electron interacts with DNA analogues.     

Solid-state luminescence of Au(I) complexes with external stimuli-responsive properties

In the last decade, the field of stimuli-responsive luminescent materials have been intensely emerged because of the high potential application to functional sensors or photoelectronic devices. In particular, luminescent molecular crystals constructed from Au(I) complexes have produced a wide range of examples of luminescent alterations when some external stimulations, such as heat, mechanical stress, vapor (or solvents), were applied to the solid samples. In this review, we describe the recent progress through a summary of the reported Au(I) complexes based on their utilized stimuli-responsive mechanisms, which are categorized in crystal phase transitions (“crystal-to-amorphous”, “crystal-to-crystal” and “single-crystal-to-single-crystal” transitions) and molecular rotation in crystalline media, respectively.     

基于TOPSIS模型的机场网络节点重要度评估

在机场网络中单个机场节点的失效往往会对其他的节点产生影响,特别是关键节点的失效会波及整个网络.准确客观的识别重要节点机场关乎整个机场网络的安全运营.本文分析了机场网络拓扑特性中的度、集聚系数和接近度指标,考虑了机场旅客吞吐量和所在城市人口等交通经济特性指标,使用熵权法确定权重的基础上,应用TOPSIS法构建综合评价体系模型,最后以华东地区机场网络为例进行节点重要度排序.结果表明与单一指标的评估结果相比,该方法更加全面客观的确定不同属性指标的权重,避免了不同指标取值的差异性,使评价更加全面,更符合机场网络实际运营情况.     

p-Adic函数空间上Hardy型算子的多线性交换子估计

在p-adic域上研究分数次Hardy型算子与CMO(Q_p~n)函数生成的多线性交换子,建立了交换子在Lebesgue空间和Herz空间上的有界性.对Hardy算子的多线性交换子也得到了相应的结果.     

1,3,5-三(羧基甲氧基)苯镍配位聚合物的合成、晶体结构及性质研究

采用溶剂热法,1,3,5-三(羧基甲氧基)苯为定向配体和乙酸镍反应构筑了一个新型的金属配位聚合物[Ni(TB)₂(H₂O)₂]_n·2H₂O,其中H₃TB=1,3,5-三(羧基甲氧基)苯,通过元素分析、IR及X射线单晶衍射对配合物结构进行表征,并研究其荧光性质、热稳定性及Hirshfeld表面作用力。单晶结构分析表明,该配合物属于三斜晶系,空间群$P \overline{1}$,配合物中心离子Ni(Ⅱ)分别与来自两个水分子上的氧原子及四个不同1,3,5-三(羧基甲氧基)苯配体的羧酸氧原子配位,形成六配位的NiO₆八面体构型,并通过与1,3,5-三(羧基甲氧基)苯配体的氧原子配位不断延伸形成具有孔洞结构的一维链状构型。配合物具有良好的荧光性能和热稳定性。Hirshfeld表面作用分析表明配合物分子中O…H/H…O作用占主导且占比为39.0%,而H…H的作用力占比为25.9%,O…O的作用力占比为13.6%。     

Terahertz generation in quantum cascade structures by two-color deriving fields: An approach to reach inversion population via optical pumping

In this paper, a quantum cascade laser (QCL) design is proposed based on GaAs/AlGaAs material system, which simultaneously operates at three widely separated wavelengths (${\lambda }_1=11.1\mu m,{\lambda }_2=14.1\mu m$ and ${\lambda }_{THz}=60\mu m$). In the design, all the wavelength radiations are achieved by the engineering of the electronic spectrum via the quantum-well widths and the applied electric field in a single active region within a same waveguide. The mid-infrared (mid-IR) wavelengths are obtained by adoption a dual-upper-state active region, and the proposed design aims to use both the mid-IR radiations as the coherent deriving fields to populate the upper THz lasing state to aid the THz-laser population inversion via optical pumping instead of direct electrical injection. A detailed analysis of electronic transport in the structure is carried out using a multi-level rate-equation model. The results show that the proposed structure offers an alternative approach to room temperature THz generation in QCLs.     

Acidity Modification of ZSM-5 for Methane Conversion in Co-feeding Method with MTA Reaction

Acidity plays a vital role in methane conversion by co-feeding method, which is one of the best strategies to improve the utilization and gentle the reaction conditions of methane. In this work, Zn, Ni, Mo, La, Ga, Fe and Co-impregnated ZSM-5 zeolites have been prepared with the same substitutions to variate the acidities and tested in co-aromatization of methanol with methane. It is demonstrated that the new medium-strong acid sites formed by metal and strong acid sites are the key role to activate methane in co-reaction. Zn-modified ZSM-5 catalyst is preferred to exhibit the best methane conversion of 12%, whose aromatic selectivity increases from 27.2% to 52.2% compared with that of HZSM-5. Besides, the addition of methane further improves the production of high-valued aromatics compared with methanol to aromatics (MTA) reaction.