Screening for frequently detected quaternary ammonium mixture systems in waters based on frequent itemset mining and prediction of their toxicity.

Screening and prioritizing research on frequently detected mixture systems in the environment is of great significance, as conducting toxicity testing on all mixtures is impractical. Therefore, the frequent itemset mining (FIM) was introduced and applied in this paper to identify variables that commonly co-occur in a dataset. Based on the dataset of the quaternary ammonium compounds (QACs) in the water environment, the four frequent QAC mixture systems with detection rate ≥ 35 % were found, including [BDMM]+Cl--[BTMM]+Cl- (M1), [BDMM]+Cl--[BHMM]+Cl- (M2), [BTMM]+Cl- -[BHMM]+Cl- (M3), and [BDMM]+Cl--[BTMM]+Cl--[BHMM]+Cl- (M4). [BDMM]+Cl-, [BTMM]+Cl-, and [BHMM]+Cl- are benzyl dodecyl dimethyl ammonium chloride, benzyl tetradecyl dimethyl ammonium chloride, and benzyl hexadecyl dimethyl ammonium chloride, respectively. Then, the toxicity of the representative mixture rays and components for the four frequently detected mixture systems was tested using Vibrio qinghaiensis sp.-Q67 (Q67) as a luminescent indicator organism at 0.25 and 12 h. The toxicity of the mixtures was predicted using concentration addition (CA) and independent action (IA) models. It was shown that both the components and the representative mixture rays for the four frequently detected mixture systems exhibited obvious acute and chronic toxicity to Q67, and their median effective concentrations (EC50) were below 7 mg/L. Both CA and IA models predicted the toxicity of the four mixture systems well. However, the CA model had a better predictive ability for the toxicity of the M3 and M4 mixtures than IA at 12 h.

Quadrotors' double-loop controller design with tensor product model transformation and partial fully actuated method.

In the existing work of tensor product (TP) model transformation, the TP model transformation-based work on the quadrotor's control system design is scarce, the direct TP model transformation control strategy that applied to the quadrotor fails due to the calculation complexity, infeasibility of the huge amount of linear matrix inequalities, and the complexity of solving the linear matrix inequalities. To solve this problem, a partial TP model transformation-based double loop fuzzy controller has been studied in this work, the double-loop hybrid control scheme combines the fully actuated control method and the TP model transformation, while the fully actuated control method is used to the position subsystem control loop, and the TP model transformation based fuzzy controller is applied to the attitude control of the quadrotor. Moreover, for comparison purpose, a varying-input method based on TP model transformation is extended to the quadrotor's system control. The double-loop hybrid control scheme could also be extended with other TP model transformation based tensor sampling methods, such as, uniform sampling method and varying-input method. At last, the proposed algorithms are evaluated and compared on Parrot Mambo Minidrone, MFP450 and CUAV V5+ based hexarotor.

Effect of different conditions on the germination of coix seed and its characteristics analysis.

Coix seed (CS) has high nutritional value, but the deep processing of CS is relatively limited. Sprouting can significantly improve nutritional value, laying the foundation for efficient consumption or further processing. The optimal conditions for the germination of CS are a soaking temperature of 36 °C for 10 h and a germination temperature of 29 °C for 24 h. Under these conditions, the final germination rate of CS reached 90%. Additionally, the content of γ-aminobutyric acid was 21.205 mg/100 g; soluble protein, free amino acids, γ-aminobutyric acid, and other essential substances increased in CS. Especially after germination, the γ-aminobutyric acid (GABA) content increased by 7.8 times compared with the GABA content of ungerminated CS. Therefore, the nutritional value and flavor of germinated CS are better than those of ungerminated ones, which establishs a solid foundation for its application in developing various products such as compound health drinks, coix yogurt, and others.

Design, Manufacture, and Characterization of a Critical-Sized Gradient Porosity Dual-Material Tibial Defect Scaffold.

This study proposed a composite tibia defect scaffold with radial gradient porosity, utilizing finite element analysis to assess stress in the tibial region with significant critical-sized defects. Simulations for scaffolds with different porosities were conducted, designing an optimal tibia defect scaffold with radial gradient porosity for repairing and replacing critical bone defects. Radial gradient porosity scaffolds resulted in a more uniform stress distribution, reducing titanium alloy stiffness and alleviating stress shielding effects. The scaffold was manufactured using selective laser melting (SLM) technology with stress relief annealing to simplify porous structure fabrication. The study used New Zealand white rabbits' tibia defect sites as simulation parameters, reconstructing the 3D model and implanting the composite scaffold. Finite element analysis in ANSYS-Workbench simulated forces under high-activity conditions, analyzing stress distribution and strain. In the simulation, the titanium alloy scaffold bore a maximum stress of 122.8626 MPa, while the centrally encapsulated HAp material delivered 27.92 MPa. The design demonstrated superior structural strength, thereby reducing stress concentration. The scaffold was manufactured using SLM, and the uniform design method was used to determine a collection of optimum annealing parameters. Nanoindentation and compression tests were used to determine the influence of annealing on the elastic modulus, hardness, and strain energy of the scaffold.

Controllable acetylation of cellulose nanocrystal by uniform design and response surface methodology.

Acetylation of Cellulose nanocrystal (CNC) can reduce its surface polarity and therefore extends its application in biomedical and chemical fields. A method combining uniform design (UD) and response surface methodology (RSM) was developed to produce the acetylated CNC with arbitrary degree of substitution (DS) and crystallinity index (CrI). The effects of three factors (i.e., temperature, reaction time and the volume of acetic anhydride) on DS and CrI were investigated in their respective ranges (i.e., 60-90 oC, 1.0-5.0 h and 1.0-5.0 mL). Both mathematical models for DS and CrI were developed by multiple stepwise regression (MSR) based on UD data and their significances were evaluated by analysis of variance. The controllable acetylation of CNC was realized by using either UD alone or the combination of UD and RSM. Eight verification experiments show that the relative errors between the predicted and the measured results are less than 16.77 % and 6.08 % for DS and CrI, respectively, confirming the reliability and validity of the method. This developed methodology is ingenious and expected to be expanded to any other fields that controllable preparations are required.

Optimization of total flavonoids purification process in rose by uniform design method.

This study aims to establish a method for purifying total flavonoids in roses using macroporous resin columns, intending to leverage and harness their potential. We screened six macroporous resins to evaluate their capacity for their adsorption and desorption, ultimately identifying X5 macroporous resin as the most effective. To comprehensively understand the adsorption behavior, we analyzed it using various models, such as pseudo-first-order and pseudo-second-order kinetic models, particle diffusion models, and Langmuir, Freundlich, and Temkin isotherm models. Employing both single-factor and uniform design, approaches, the focus of this work was on maximizing the total flavonoid recovery rate. A 3-factor and 10-level uniform design table was utilized for optimizing the optimal process parameters and exploring the antioxidant properties of the purified flavonoids. The optimal process conditions for purifying total flavonoids from roses can be summarized as follows: a sample concentration of 2 mg/mL, pH at 2, 55 mL sample volume, eluent ethanol concentration of 75%, eluent volume of 5 BV, and the elution rate set at 1 mL/min. Following purification, the total flavonoid content peaked at 57.82%, achieving an 84.93% recovery rate, signifying substantial antioxidant potential. Consequently, the method established for purifying TFR using X5 macroporous resin in this study proves to be a dependable and reliable method consistent approach.

Preparation of Phosphorylated Auricularia cornea var. Li. Polysaccharide Liposome Gel and Analysis of Its In Vitro Antioxidant Activity.

In this study, Auricularia cornea var. Li. polysaccharides (ACP) were used as the research object to prepare liposome gel and determine its antioxidant activity in vitro. Phosphorylated Auricularia cornea var. Li. polysaccharides (P-ACP) were prepared via the phosphorylation of ACP by the phosphate method. Additionally, phosphorylated Auricularia cornea var. Li. polysaccharide liposomes (P-ACPL) were prepared using a reverse evaporation method. Finally, phosphorylated Auricularia cornea var. Li. polysaccharide liposome gel (P-ACPLG) was prepared by dispersing the P-ACPL in the gel matrix. The results show that the phosphorylation of the P-ACP was 15.51%, the containment rate of the P-ACPL was 84.50%, the average particle size was (192.2 ± 3.3) nm, and the particle size distribution map had a homogeneous peak, resulting in the particle dispersion being uniform and the polydispersion index (PDI) being 0.134 ± 0.021. The average Zeta potential was (-33.4 ± 0.57) mV. In addition, the in vitro antioxidant activity of the P-ACPL was slightly higher than that of the ACP and P-ACP. After the P-ACPL was emulsified into P-ACPLG, the DPPH, hydroxyl radical clearance, and reducing the ability of P-ACPL remained unchanged. In general, the P-ACPLG prepared in this study has good antioxidant activity in vitro and can retain the antioxidant activity of P-ACPL in vitro well.

A Uniform Design Method Can Optimize the Combinatorial Parameters of Antimicrobial Photodynamic Therapy, Including the Concentrations of Methylene Blue and Potassium Iodide, Light Dose, and Methylene Blue's Incubation Time, to Improve Fungicidal Effects on Candida Species.

The optimal combinatorial parameters of antimicrobial photodynamic therapy (aPDT) mediated by methylene blue (MB) with the addition of potassium iodide (KI) against Candida species have never been defined. This study aimed to optimize the combinatorial parameters of aPDT, including the concentrations of MB (X1, 0.1-1.0 mM) and KI (X2, 100-400 mM), light dose (X3, 10-70 J/cm2), and MB's incubation time (X4, 5-35 min) for three Candida species. The best MB + KI-aPDT fungicidal effects (Y) against Candida albicans ATCC 90028 (YCa), Candida parapsilosis ATCC 22019 (YCp), and Candida glabrata ATCC 2950 (YCg) were investigated using a uniform design method. The regression models deduced using this method were YCa = 7.126 + 1.199X1X3 - 1.742X12 + 0.206X22 - 0.361X32; YCp = 10.724 - 0.867X1 - 1.497X2 + 0.560X3 + 1.298X22; and YCg = 0.892 - 0.956X1 + 2.296X3 + 1.299X42 - 3.316X3X4. The optimal combinatorial parameters inferred from the regression equations were MB 0.1 mM, KI 400 mM, a light dose of 20 J/cm2, and a 5-minute incubation time of MB for Candida albicans; MB 0.1 mM, KI 400 mM, a light dose of 70 J/cm2, and a 5-minute incubation time of MB for Candida parapsilosis; MB 0.1 mM, KI 100 mM, a light dose of 10 J/cm2, and a 35-minute incubation time of MB for Candida glabrata. The uniform design method can optimize the combinatorial parameters of aPDT mediated by MB plus KI to obtain the best aPDT fungicidal effects on Candida species, providing a new method to optimize the combinatorial parameters of aPDT for different pathogens in the future.

Optimization of the proportions of advantageous components in the hypolipidemic "bioequivalent substance system" of Jiang-Zhi-Ning and its mechanism of action.

CONTEXT: Jiang-Zhi-Ning (JZN), a traditional Chinese medicinal formula, is used to treat hyperlipidemia in clinics. OBJECTIVE: To screen the hypolipidemic "bioequivalent substance system (BSS)" of JZN and elucidate the potential hypolipidemic mechanism. MATERIALS AND METHODS: In vitro, the TG content in HepG2 cells was determined after the intervention of the combination of advantageous components (CAC) by uniform design. In vivo, hyperlipidemia models were established by Triton WR-1339 (400 mg/kg; i.p.) in male ICR mice, and corresponding treatments were administered via oral administration once. The mice were divided into 12 groups (n = 5): control, hyperlipidemic model, simvastatin (positive control, 20 mg/kg), gradient doses of JZN granules (2, 4 and 8 g/kg) and the hypolipidemic effective extraction (HEE) of JZN (120, 240 and 480 mg/kg) and CAC groups (20, 40 and 160 mg/kg). Serum TC, TG, LDL-C and HDL-C were performed after 24 h. Transcriptomics and qRT-PCR technology were used to explore the mechanism of the "BSS" of JZN. RESULTS: In vitro, the ratio of CAC was determined. CAC could reduce the TG content in HepG2 cells (77.21%). Compared with the model group, the high dose of CAC could markedly decrease the levels of TC (61.86%), TG (105.54%) and LDL-C (39.38%) and increase the level of HDL-C (232.67%). CAC was proved to be the "BSS". Transcriptomics and qRT-PCR analysis revealed CAC regulated non-alcoholic fatty liver disease, bile secretion, PPAR and adipocytokine signalling pathway. DISCUSSION AND CONCLUSIONS: These findings provided new feasible ideas and methods for the elucidation of the pharmacodynamic material basis.

Isolation and Optimization of Aflatoxin B1 Degradation by Uniform Design and Complete Genome Sequencing of Novel Deep-Sea Kocuria rosea Strain 13.

Aflatoxin B1 is a natural carcinogenic mycotoxin. The biological detoxification of aflatoxin could result in less environmental pollution, more moderate conditions, and less impact on food and feed, and be more convenient than physical and chemical methods. In this study, strain 13 with aflatoxin B1 degradation activity (67.47 ± 1.44%) was isolated and identified as Kocuria rosea. A uniform design was applied to optimize the degradation activity using a software Data Processing System, and a quadratic polynomial stepwise regression model was selected to investigate the relationships between the degradation rate and five independent variables. Furthermore, the optimal degradation conditions (culture temperature of 30 °C, culture time of 4.2 days, seawater ratio of 100%, pH of 7.11, and inoculation dosage of 0.09%) were verified with a degradation rate of 88 ± 0.03%, which was well matched with the predicted value (92.97%) of the model. Complete genome sequencing of Kocuria rosea, conducted with a combination of Illumina and single-molecule real-time sequencing, was used to analyze the genomic features and functions of the strain, which were predicted by the annotation based on seven databases, and may provide insights into the potential of Kocuria rosea, as well as providing a reference for degradation gene and protein mining. These results indicate that Kocuria rosea strain 13 has the ability to degrade aflatoxin B1 efficiently, and it also has the potential to provide aflatoxin-degrading enzymes.

Optimization of Fermentation Conditions and Product Identification of a Saponin-Producing Endophytic Fungus.

BACKGROUND: Some fungal endophytes isolated from P. ginseng may present a new method of obtaining saponins. This experiment aimed to optimize the total saponin yield produced through in vitro fermentation by an endophytic fungus and analyze its saponin species in the fermented extract. METHODS: Fermentation protocols were optimized with a uniform design and verified through regression analysis to maximize the total saponin yield. The saponin types under optimal fermentation conditions were then identified and analyzed using Liquid Chromatography-Mass Spectrometry. RESULTS: The Trametes versicolor strain NSJ105 (gene accession number: OR144428) isolated from wild ginseng could produce total saponins. The total saponin yield could be increased more than two-fold through the optimization of fermentation conditions. The concentration of the total saponins achieved by the verified protocol 105-DP was close to the predicted value. The fermentation conditions of the 105-DP protocol were as follows: potato concentration 97.3 mg/mL, glucose concentration 20.6 mg/mL, inoculum volume 2.1%, fermentation broth pH 2.1, fermentation temperature 29.2 °C, and fermentation time 6 d. It was detected and analyzed that the fermented extract of 105-DP contained the ginsenosides Rf and Rb3. CONCLUSION: The endophytic fungus Trametes versicolor strain NSJ105 has potential application value in saponin production.

Multiple design and modelling approaches for the optimisation of carbon felt electro-Fenton treatment of dye laden wastewater.

This study utilizes artificial intelligence and statistical modelling to optimize the operating parameters of a carbon-based electro-Fenton process for purifying model dye (RB19)-contaminated wastewater. Multilevel experimental Box-Behnken and uniform deisgns (BBD, UD) with four variables were analysed using polynomial regression analysis (PRA) and artificial neural networks (ANN), while the process optimisation was done using desirability function. For the given testing range but different design matrices and runs, both designs predicted a maximum RB19 removal (RB19-RR) of 90 ± 2.1% at lowest energy consumption (EC) of 0.44 ± 2.5 Wh, when voltage, Na2SO4, FeSO4, and time were maintained as follows: 4-5.3 V, 7-11 mM, 0.4-0.6 mM, and 35-40 min, respectively. All the design-model combinations portrayed the similar senitivity analyses, revealing that RB19 degradation and EC are primarily influenced by electrolysis time and voltage. The performance assessment demonstrated that all the design-model combinations also excellently predicted for unseen conditions as the maximum root mean squared error (RMSE) value for RB19-RR was 4.07, while it was 0.072 for EC, however, BBD-ANN performance proved to be slightly better than others. Having ∼57% less experimentation, UD based models managed to accurately predict the results for unseen conditions as the statistical errors were quite insignificant, even in some cases, RMSE found to be less for UD compared to BBD, elucidating the potential of uniform design as an alternative of conventional factorial designs. Nevertheless, the prediction accuracy is also dependent on modelling approach, as in some cases ANN failed to predict the response precisely specially when dealing with small data. Furthermore, techno-economic evaluation results spell out the efficacy of carbon felt based enhanced electro-Fenton process as promising environmental remediation technology and highlight its practical implication from view of operational cost.

SAHmap: Synergistic-antagonistic heatmap to evaluate the combined synergistic effect of mixtures of three pesticides on multiple endpoints of Caenorhabditis elegans.

The environmental pollution caused by toxic chemicals such as pesticides has become a global problem. The mixture of dichlorvos (DIC), dimethoate (DIM), aldicarb (ALD) poses potential risks to the environment and human health. To fully explore the interaction of complex mixtures on Caenorhabditis elegans behavioral toxicity endpoint. This study created a synergistic-antagonistic heatmap (SAHmap) based on the combination index to systematically describe the toxicological interaction prospect of the mixture system. It was shown that the three pesticides and their binary as well as ternary mixture rays have significant concentration-response relationship on three behavioral endpoints of nematodes, From the perspective of synergistic-antagonistic heatmaps, all the mixture rays in the DIC-DIM mixture system showed strong synergism on the three behavioral and lethal endpoints. In the ternary mixture system, the five mixture rays showed different interaction between the behavioral endpoint and the lethal endpoint, and showed slight synergism to two behavioral endpoints as a whole. The emergence of synergism should arouse our attention to these hazardous chemicals. In addition, the use of SAHmap and the significant linear correlation among three behavioral endpoints further improved the efficiency of the study on the behavioral toxicity of pesticide mixtures to Caenorhabditis elegans.

Extraction of phenolics and anthocyanins from purple eggplant peels by multi-frequency ultrasound: Effects of different extraction factors and optimization using uniform design.

In this work, multi-frequency ultrasound (working modes for the single-, dual- and tri-frequency in simultaneous ways) was applied to extract bioactive compounds from purple eggplant peels. The single-factor experiments were performed by varying six independent variables. A six-level-five-factor uniform design (UD) was further employed to evaluate the interaction effects between different factors. It was found that extraction temperature and extraction time significantly affected the total phenolic content (TPC), whereas the total monomeric anthocyanins (TMA) was mainly influenced by ethanol concentration, extraction temperature and solid-liquid ratio. Based on partial least-squares (PLS) regression analysis, the optimal conditions for TPC extraction were: 53.6 % ethanol concentration, 0.336 mm particle size, 44.5 °C extraction temperature, 35.2 min extraction time, 1:43 g/mL solid-liquid ratio, and similar optimal conditions were also obtained for TMA. Furthermore, the TPC and TMA extraction were investigated by ultrasound in different frequencies and power levels. Compared with single-frequency (40 kHz) and dual-frequency ultrasound (25 + 40 kHz), the extraction yield of TPC and TMA with tri-frequency ultrasound (25 + 40 + 70 kHz) increased by 23.65 % and 18.76 % respectively, which suggested the use of multi-frequency ultrasound, especially tri-frequency ultrasound, is an efficient strategy to improve the TPC and TMA extracts in purple eggplant peels.

Optimization by uniform design U8 (83 ) approach for enhanced caffeine degradation in synthetic wastewater in bioreactor.

Coffee wastewater contains large amounts of caffeine which affects microflora and seed development to great extent. Although several physio-chemical methods available for caffeine degradation, they are not preferred for large-scale treatment. In this study, we optimized induced cell concentration, aeration and agitation rate for maximizing caffeine degradation rate in bioreactor using Uniform design. Maximum caffeine degradation rate of 23·59 mg L-1 h-1 was achieved. The reduction in chemical oxygen demand, biological oxygen demand and total organic carbon removal were found to be 72, 78 and 72% respectively. Mathematical model was developed through regression analysis and predicted maximum caffeine degradation rate of 24·2 mg L-1 h-1 under optimal conditions of 0·35 g L-1 biomass, 395 rev min-1 and 1·62 vvm. Experimental validation at optimum condition resulted in 22 mg L-1 h-1 of caffeine degradation rate. This is the first-ever bioreactor study showing highest caffeine degradation rate in synthetic coffee wastewater with limited experimental runs.

An Optimal Combination of Chemically Pure Compounds from Salvia miltiorrhiza for Inhibiting Cell Proliferation.

OBJECTIVE: Salvia miltiorrhiza (SM) is a traditional Chinese medicine used clinically to treat cardiovascular diseases, including atherosclerosis and myocardial infarction. Its therapeutic effect has been confirmed by many clinical and pharmacological studies. However, the optimal formulation of active ingredients in SM for treating cardiovascular diseases remains unclear. In this study, we determined the ratio of the optimal compatibility of SM ingredients DSS, Sal-A, Sal-B, and PAL (SABP)with a uniform and orthogonal optimized experimental design. In addition, we determined the anti-oxidation effect of SABP using Adventitial Fibroblasts (AFs). METHODS: By using a combination of uniform and orthogonal designs, we determined the optimal formulation of aqueous extract from SM. MTT assay was used to determine the inhibitory effects of these 4 components of SM on the AFs, which were isolated and cultured from the aorta. The reactive oxygen species (ROS) production in AFs was compared before and after SABP treatment. RESULTS: The optimal formulation of these 4 aqueous extracts from SM were 150 : 7 : 300 : 500, and their concentrations were S(1.5×10-4 mol/L), A(7×10-6 mol/L), B(3×10-4 mol/L), and P(5×10-4 mol/L). There were some synergies between these 4 components. Moreover, SABP decreased ROS production in AFs. CONCLUSION: These findings suggest that SABP inhibits the proliferation and oxidation stress in AFs. The present study provides new evidence that the efficacy and function generated from the optimal formulation of active ingredients in SM are better than lyophilized powder of SM.

Robust optimization of convolutional neural networks with a uniform experiment design method: a case of phonocardiogram testing in patients with heart diseases.

BACKGROUND: Heart sound measurement is crucial for analyzing and diagnosing patients with heart diseases. This study employed phonocardiogram signals as the input signal for heart disease analysis due to the accessibility of the respective method. This study referenced preprocessing techniques proposed by other researchers for the conversion of phonocardiogram signals into characteristic images composed using frequency subband. Image recognition was then conducted through the use of convolutional neural networks (CNNs), in order to classify the predicted of phonocardiogram signals as normal or abnormal. However, CNN requires the tuning of multiple hyperparameters, which entails an optimization problem for the hyperparameters in the model. To maximize CNN robustness, the uniform experiment design method and a science-based methodical experiment design were used to optimize CNN hyperparameters in this study. RESULTS: An artificial intelligence prediction model was constructed using CNN, and the uniform experiment design method was proposed to acquire hyperparameters for optimal CNN robustness. The results indicate Filters ([Formula: see text]), Stride ([Formula: see text]), Activation functions ([Formula: see text]), and Dropout ([Formula: see text]) to be significant factors considerably influencing the ability of CNN to distinguish among heart sound states. Finally, the confirmation experiment was conducted, and the hyperparameter combination for optimal model robustness was Filters ([Formula: see text]) = 32, Kernel Size ([Formula: see text] = 3 × 3, Stride ([Formula: see text]) = (1,1), Padding ([Formula: see text] as same, Optimizer ([Formula: see text] as the stochastic gradient descent, Activation functions ([Formula: see text]) as relu, and Dropout ([Formula: see text]) = 0.544. With this combination of parameters, the model had an average prediction accuracy rate of 0.787 and standard deviation of 0. CONCLUSION: In this study, phonocardiogram signals were used for the early prediction of heart diseases. The science-based and methodical uniform experiment design was used for the optimization of CNN hyperparameters to construct a CNN with optimal robustness. The results revealed that the constructed model exhibited robustness and an acceptable accuracy rate. Other literature has failed to address hyperparameter optimization problems in CNN; a method is subsequently proposed for robust CNN optimization, thereby solving this problem.

Synthesis of Fe3O4@mZrO2-Re (Re = Y/La/Ce) by Using Uniform Design, Surface Response Methodology, and Orthogonal Design & Its Application for As3+ and As5+ Removal.

In this study, iron oxide (Fe3O4) was coated with ZrO2, and doped with three rare earth elements((Y/La/Ce), and a multi-staged rare earth doped zirconia adsorbent was prepared by using uniform design U14, Response Surface methodology, and orthogonal design, to remove As3+ and As5+ from the aqueous solution. Based on the results of TEM, EDS, XRD, FTIR, and N2-adsorption desorption test, the best molar ratio of Fe3O4:TMAOH:Zirconium butoxide:Y:La:Ce was selected as 1:12:11:1:0.02:0.08. The specific surface area and porosity was 263 m2/g, and 0.156 cm3/g, respectively. The isothermal curves and fitting equation parameters show that Langmuir model, and Redlich Peterson model fitted well. As per calculations of the Langmuir model, the highest adsorption capacities for As3+ and As5+ ions were recorded as 68.33 mg/g, 84.23 mg/g, respectively. The fitting curves and equations of the kinetic models favors the quasi second order kinetic model. Material regeneration was very effective, and even in the last cycle the regeneration capacities of both As3+ and As5+ were 75.15%, and 77.59%, respectively. Adsorption and regeneration results suggest that adsorbent has easy synthesis method, and reusable, so it can be used as a potential adsorbent for the removal of arsenic from aqueous solution.

Synthesis of magnetic core-shell amino adsorbent by using uniform design and response surface analysis (RSM) and its application for the removal of Cu2+, Zn2+, and Pb2.

The magnetic Fe3O4 was synthesized by using a one-step solvothermal method. Then, anhydrous ethanol as a solvent, tetramethyl ammonium hydroxide (TMAOH) as an auxiliary agent, tetraethyl orthosilicate (TEOS) as a silicon source, and (3-aminopropyl) triethoxysilane (APTES) as amino source were used to prepare Fe3O4@mSiO2-NH2 by using the sol-gel method. Uniform design U14*(145) and the response surface method (RSM) were used to optimize the synthesis ratio. According to the results of TEM, SEM, N2 adsorption-desorption test, VSM, and XRD, it found that the best coating effect obtained when the relative molar ratio of TMAOH:TEOS:APTES:Fe3O4 was 5:4:6:0.45. The results of EDS and elemental analysis confirmed the success of amino group coating; VSM magnetization after surface modification was 32 emu/g; BET results show that specific surface area is 236 m2/g, size 5 nm, and the pore volume is 0.126 cm3/g. The removal of Cu2+, Zn2+, and Pb2+ by Fe3O4@mSiO2-NH2 was studied at the optimal initial pH value 6 of the adsorption test system. The isothermal adsorption results show that the Langmuir model and Redlich-Peterson model are more suitable than the Freundlich model to describe the adsorption behavior, and Cu2+, Zn2+, and Pb2+ adsorption is mainly single molecular layer. The maximum adsorption capacity qm of the Langmuir model for Cu2+, Zn2+, and Pb2+ removal was 48.04 mg/g, 41.31 mg/g, and 62.17 mg/g, respectively. The adsorption kinetic rates of Cu2+, Zn2+, and Pb2+ on Fe3O4@mSiO2-NH2 relatively more suitable for pseudo-second-order kinetic model, i.e., R2, were ranged between 0.995 and 0.999, and the suitable reaction time was 60 min. These results proved that Fe3O4@m-SiO2-NH2 prepared by using this method is easy to synthesize, has easy recovery, is ecofriendly, and can be potential adsorbent for Cu2+, Zn2+, and Pb2+ removal.

Prediction of the inhibitory concentrations of chloroquine derivatives using deep neural networks models.

In recent years, deep neural networks have begun to receive much attention, which has obvious advantages in feature extraction and modeling. However, in the using of deep neural networks for the QSAR modeling process, the selection of various parameters (number of neurons, hidden layers, transfer functions, data set partitioning, number of iterations, etc.) becomes difficult. Thus, we proposed a new and easy method for optimizing the model and selecting Deep Neural Networks (DNN) parameters through uniform design ideas and orthogonal design methods. By using this approach, 222 chloroquine (CQ) derivatives with half maximal inhibitory concentration values reported in different kinds of literature were selected to establish DNN models and a total number of 128,000 DNN models were built to determine the optimized parameters for selecting the better models. Comparing with linear and Artificial Neural Network (ANN) models, we found that DNN models showed better performance.Communicated by Ramaswamy H. Sarma.