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75/0.87, exhibit significant enhancements in amplitude, 2.4/24 times as large as that (-29 × 105 au) at intermediate yS = 0.59 as is often the case in DTDA2. Using the 1D 3s-2e valence-bond configuration interaction model, these sign inversions and drastic increase in the amplitude of γ are found to originate in the differences in Coulomb interactions between valence electrons, between valence and core electrons, and between valence electrons and nuclei. These results contribute to pave the way for the construction of novel control guidelines for the amplitude and sign of γ for one-hole-doped diradicaloids.Drug repositioning is the identification of interactions between drugs and target proteins in pharmaceutical sciences. Traditional large-scale validation through chemical experiments is time-consuming and expensive, while drug repositioning can drastically decrease the cost and duration taken by traditional drug development. With the rapid advancement of high-throughput technologies and the explosion of various biological and medical data, computational drug repositioning methods have been used to systematically identify potential drug-target interactions. Some of them are based on a particular class of machine learning algorithms called kernel methods. Acalabrutinib mw In this paper, we propose a new machine learning prediction method combining multiple kernels into a tripartite heterogeneous drug-target-disease interaction spaces in order to integrate multiple sources of biological information simultaneously. This novel network algorithm extends the traditional drug-target interaction bipartite graph to the third disease layer. Meanwhile, Gaussian kernel functions on heterogeneous networks and the regularized least square method of the Kronecker product are used to predict new drug-target interactions. The values of AUPR (area under the precision-recall curve) and AUC (the area under the receiver operating characteristic curve) of the proposed algorithm are significantly improved. Especially, the AUC values are improved to 0.99, 0.99, 0.97, and 0.96 on four benchmark data sets. These experimental results substantiate that the network topology can be used for predicting drug-target interactions.A supramolecular cucurbit[6]uril (CB[6])-enriched magnetic montmorillonite (CBCM) nanocomposite was prepared and characterized. CB[6] played a prominent role as a capping agent, helping in better distribution of the nanoparticles, and as a binder between nanoparticles. Montmorillonite provided structural stability and fortified ultrafast adsorption toward dyes. Its application in the removal of cationic dyes from wastewater was systematically assessed. Process parameters such as pH, initial dye concentration, dosage, temperature, and time were optimized. Kinetics and isotherms of the process were described using pseudo-second-order kinetics and the Langmuir isotherm, respectively. CBCM exhibited rapid dye removal capacity in short reaction times with qmax of 199.20, 78.31, and 55.62 mg g-1 and K2 of 0.0281, 0.0.0823, and 0.0953 L mg-1 min-1 for crystal violet, methylene blue, and rhodamine B, respectively. Benefiting from the synergetic effects of montmorillonite surface hydrophobicity, abundant carbonyl groups of CB[6], and magnetic properties of copper ferrite, CBCM demonstrated outstanding dye removal capacity, negligible leaching at saturation, and high tolerance toward harsh conditions. This intrinsic nature is expedient in prolonged industrial operations. To demonstrate industrial viability, syringe filtration and continuous flow fixed-bed column operations were validated. The CBCM fixed-bed column demonstrated stable dye removal efficiency with 10-100 mg mL-1 dye at 10-50 mL min-1 flow rates. Utilizing the magnetic and catalytic activities of the copper ferrite nanoparticles, CBCM was recycled using a magnet, regenerated, and reused for several cycles. CB[6] remarkably improved the performance of the nanocomposite and made it suitable for different effluent treatment techniques. This may pave a sustainable way toward the efficient onsite treatment of effluent at the industrial scale.In order to solve the problem of pipeline erosion-corrosion under acidic conditions with different CO2 contents of natural gas hydrate (NGH), the influence of different pH values on the erosion corrosion of X80 steel under dynamic conditions was studied. The erosion and corrosion behavior of X80 pipeline steel in multiphase flow (0.5% sand + 3% NaCl aqueous solution) at different pH was studied by rotating a cylindrical electrode apparatus combined with the electrochemical method in this paper. By analyzing the electrochemical impedance spectroscopy of the Tafel curve, the results showed that under dynamic solid-liquid two-phase conditions, with the decrease of the pH value, the self-corrosion potential of X80 steel samples was positively shifted, and the corrosion current density showed a trend of gradually increase. When the pH value is 2.0-3.0, the ac impedance spectrum of X80 steel samples shows a reactance arc in the high-frequency region and an inductive reactance arc in the low-frequency region. With the increase of the pH value, the radius of the capacitance and resistance arc of the impedance spectrogram increases gradually, and the time of the Bode spectrogram is “half peak” in the low-frequency region. As the time constant increases, the impedance decreases and the phase angle decreases; the overall polarization resistance Rp on the surface increased gradually and the corrosion rate decreased significantly. Therefore, the pH value of the content of NGH with different CO2 contents has obvious influence on the solid-liquid two-phase erosion corrosion of X80 steel. With the increase of the pH value, the corrosion resistance of X80 steel increases, the corrosion rate decreases, and the corrosion strength decreases.Hydrodeoxygenation (HDO) of bio-oil derived from liquefaction of a palm empty fruit bunch (EFB) in glycerol was investigated. To enhance the heating value and reduce the oxygen content of upgraded bio-oil, hydrodeoxygenation of light bio-oil over Ni- and Co-based catalysts on an Al2O3 support was performed in a rotating-bed reactor. Two consecutive steps were conducted to produce bio-oil from EFB including (1) microwave-assisted wet torrefaction of EFB and (2) solvothermolysis liquefaction of treated EFB in a Na2CO3/glycerol system. The HDO of as-prepared bio-oil was subsequently performed in a unique design reactor possessing a rotating catalyst bed for efficient interaction of a catalyst with bio-oil and facile separation of the catalyst from upgraded bio-oil after the reaction. The reaction was carried out in the presence of each mono- or bimetallic catalyst, namely, Co/Al2O3, Ni/Al2O3, NiMo/Al2O3, and CoMo/Al2O3, packed in the rotating-mesh host with a rotation speed of 250 rpm and kept at 300 and 350 °C, 2 MPa hydrogen for 1 h.