Bejan flow visualization of free convection in a Jeffrey fluid from a semi-infinite vertical cylinder

Journal of Thermal Analysis and Calorimetry - This article studies the pattern of heat lines in free convection non-Newtonian flow from a semi-infinite vertical cylinder via Bejan’s heat...     

Prediction of drug-target interaction by integrating diverse heterogeneous information source with multiple kernel learning and clustering methods

BackgroundIdentification of potential drug-target interaction pairs is very important for pharmaceutical innovation and drug discovery. Numerous machine learning-based and network-based algorithms have been developed for predicting drug-target interactions. However, large-scale pharmacological, genomic and chemical datum emerged recently provide new opportunity for further heightening the accuracy of drug-target interactions prediction.ResultsIn this work, based on the assumption that similar drugs tend to interact with similar proteins and vice versa, we developed a novel computational method (namely MKLC-BiRW) to predict new drug-target interactions. MKLC-BiRW integrates diverse drug-related and target-related heterogeneous information source by using the multiple kernel learning and clustering methods to generate the drug and target similarity matrices, in which the low similarity elements are set to zero to build the drug and target similarity correction networks. By incorporating these drug and target similarity correction networks with known drug-target interaction bipartite graph, MKLC-BiRW constructs the heterogeneous network on which Bi-random walk algorithm is adopted to infer the potential drug-target interactions.ConclusionsCompared with other existing state-of-the-art methods, MKLC-BiRW achieves the best performance in terms of AUC and AUPR. MKLC-BiRW can effectively predict the potential drug-target interactions.     

Pozzolanic activity of natural pozzolan–lime pastes and physicomechanical characteristics

Journal of Thermal Analysis and Calorimetry - In order to evaluate the pozzolanic activity of a natural pozzolan (NP) of rhyolitic composition, several pastes were prepared by mixing the pozzolan...     

Chirped-probe-pulse femtosecond CARS thermometry in turbulent spray flames

This paper presents temperature measurements in turbulent dilute and dense spray flames using single-laser-shot chirped-probe-pulse femtosecond coherent anti-Stokes Raman spectroscopy (CPP-fs-CARS). This ultrafast technique, with a repetition rate of 5 kHz, is applied to the piloted Sydney Needle Spray Burner (SYNSBURN^TM). The burner system features air-blast atomization of liquid injected from a needle that can be translated within a co-flowing air stream. The pilot-stabilized spray flames can range between the two extremes of dense and dilute by physically translating the needle tip relative to the burner's exit plane. The CPP-fs-CARS set-up has achieved integration times of 3 picoseconds (ps) as well as spatial resolution of approximately 800 µm along beam propagation and 60 µm in the transverse dimension. Brief details of the technique, calibration, correction of interferences, and spectral fitting processes are presented along with estimates of the associated error. The measurements are compared against well-established, line Raman–Rayleigh data for temperature collected in a turbulent CH₄/air jet diffusion flame, which is largely non-sooting. At peak gaseous flame temperatures of up to 2512 K, the relative accuracy and precision were 2.8% and ±3.4%, respectively. Measurements in turbulent spray flames are shown after applying the relevant corrections based on non-resonant background (NRB) behavior and camera saturation effects on the shape of the CARS signal spectrum. Preliminary mapping of the temperature fields demonstrates the wealth of information available in this dataset which will provide insights into the spatio-temporal structure of spray flames once relevant statistical analysis is applied.     

Synthesis,computational quantum chemical study,in silico ADMET and molecular docking analysis,in vitro biological evaluation of a novel sulfur heterocyclic thiophene derivative containing 1,2,3-triazole and pyridine moieties as a potential human topoisomerase IIα inhibiting anticancer agent

Computational quantum chemical study and biological evaluation of a synthesized novel sulfur heterocyclic thiophene derivative containing 1,2,3-triazole and pyridine moieties namely BTPT [2-(1-benzyl-5-methyl-1H-1,2,3-triazol-4-yl)-6-methoxy-4-(thiophen-2-yl) pyridine] was presented in this study. The crystal structure was determined by SCXRD method. For the title compound BTPT, spectroscopic characterization like ¹H NMR, ¹³C NMR, FTIR, UV–vis were carried out theoretically by computational DFT method and compared with experimental data. Druglikeness parameters of BTPT were found through in silico pharmacological ADMET properties estimation. The molecular docking investigation was performed with human topoisomerase IIα (PDB ID:1ZXM) targeting ATP binding site. In vitro cytotoxicity activity of BTPT/doxorubicin were examined by MTT assay procedure against three human cancer cell lines A549, PC-3, MDAMB-231 with IC50 values of 0.68/0.70, 1.03/0.77 and 0.88/0.98 μM, respectively. Our title compound BTPT reveals notable cytotoxicity against breast cancer cell (MDAMB-231), moderate activity with human lung cancer cell (A-549) and less inhibition with human prostate cancer cell (PC-3) compared to familiar cancer medicine doxorubicin. From the results, BTPT could be observed as a potential candidate for novel anticancer drug development process.     

First principles investigations of Fe,Co, Ni in model honeycomb carbon networks

The behaviors of ferromagnetic transition metals of the first period: Fe, Co and Ni are examined within density functional theory calculations in two dimensional carbon extended networks using model structure LiC₆. Around geometry optimized structures, the energy-volume equations of states considering non magnetic and spin polarized configurations established ferromagnetic ground states with magnetizations –reduced with respect to the metals’– of 2 μ_B for FeC₆ and 1 μ_B for CoC₆ while no magnetic solution could be identified for NiC₆. In the D_6h point group of the P6/mmm space group l_m decomposition of the d states results with increasing energy into doublet state E_1g with d(x²-y²) and d(xy); singlet state A_1g d(z²) and doublet state E_2g d(xz) and d(yz) lying on E_F and responsible of the onset of magnetic moments. This was mirrored via molecular orbital approach with a construct of Fe embedded between two extended carbon networks thus validating the model structure proposed for TC₆ compounds. The 100% polarization in one spin channel allows proposing potential uses in spintronics applications.     

Insight into room-temperature catalytic oxidation of NO by CrO2(110): A DFT study

The first-principles DFT calculations together with microkinetic analysis reveal the complex catalytic mechanism of low-content NO oxidation on CrO₂(110) at room temperature. It quantitatively makes clear that CrO₂(110) can exhibit considerable activity with the Mars-van-Krevelen mechanism preferred, and the nitrate species serves as the key poisoning species.     

Event-triggered based $$\pmb {L_{2}-L_{\infty }}$$L2-L∞ filtering for multiagent systems with Markovian jumping topologies under time-varying delays

Nonlinear Dynamics - In this article, we analyze the $$L_{2}-L_{\infty }$$ filtering of multiagent systems for Markovian switch topologies under time-varying delays with an influence of...     

输电铁塔四地脚螺栓塔脚板抗拉承载力试验与计算方法研究

针对架空输电线路铁塔中常用的四地脚螺栓塔脚板进行了抗拉承载力试验和理论计算方法研究。首先,选取8个试件进行塔脚板抗拉承载力试验研究,分析塔脚底板板厚及有无加劲板对塔脚板抗拉承载力的影响;其次,通过有限元模拟塔脚板的应力分布情况,并结合“塑性分析,弹性设计”的思想,提出了一种基于屈服线理论的四地脚螺栓塔脚板抗拉承载力计算公式;最后,与试验结果、有限元仿真结果、已有技术规定中的计算结果进行了对比。结果表明:建议公式与试验结果和仿真结果较为吻合,相关技术规定中的计算结果偏于保守,验证了本文建议公式的精确性;底板厚度和加劲板的作用对塔脚板承载力影响较大。研究结果可为输电铁塔四地脚螺栓塔脚板结构设计提供参考。