Robust Visual Odometry Leveraging Mixture of Manhattan Frames in Indoor Environments.

We propose a robust RGB-Depth (RGB-D) Visual Odometry (VO) system to improve the localization performance of indoor scenes by using geometric features, including point and line features. Previous VO/Simultaneous Localization and Mapping (SLAM) algorithms estimate the low-drift camera poses with the Manhattan World (MW)/Atlanta World (AW) assumption, which limits the applications of such systems. In this paper, we divide the indoor environments into two different scenes: MW and non-MW scenes. The Manhattan scenes are modeled as a Mixture of Manhattan Frames, in which each Manhattan Frame in itself defines a Manhattan World of a specific orientation. Moreover, we provide a method to detect Manhattan Frames (MFs) using the dominant directions extracted from the parallel lines. Our approach is designed with lower computational complexity than existing techniques using planes to detect Manhattan Frame (MF). For MW scenes, we separately estimate rotational and translational motion. A novel method is proposed to estimate the drift-free rotation using MF observations, unit direction vectors of lines, and surface normal vectors. Then, the translation part is recovered from point-line tracking. In non-MW scenes, the tracked and matched dominant directions are combined with the point and line features to estimate the full 6 degree of freedom (DoF) camera poses. Additionally, we exploit the rotation constraints generated from the multi-view dominant directions observations. The constraints are combined with the reprojection errors of points and lines to refine the camera pose through local map bundle adjustment. Evaluations on both synthesized and real-world datasets demonstrate that our approach outperforms state-of-the-art methods. On synthesized datasets, average localization accuracy is 1.5 cm, which is equivalent to state-of-the-art methods. On real-world datasets, the average localization accuracy is 1.7 cm, which outperforms the state-of-the-art methods by 43%. Our time consumption is reduced by 36%.

Tetracycline catalytic photodegradation with mesoporous phosphated TiO2: characterization, process optimization and degradation pathway.

Concern about the effect of tetracycline (TC) on the ecosystem has been increasing due to its endurance and low decomposition. Photocatalysts have attracted extensive interest as alternatives to other ordinary wastewater treatment methods. A nanosized mesoporous phosphated TiO2 (P-TiO2) photocatalyst was fabricated to degrade TC under Xe lamp irradiation. The TC degradation and COD removal rate reached 98.97% and 79.16% within 30 min. Photocatalysts were characterized by SEM, HRTEM, BET, DRS, XRD, XPS and FT-IR techniques. 31 experiments were designed to identify the best conditions for photocatalytic degradation of TC by response surface methodology (RSM) based on a central composite design (CCD). 6 key operating parameters were selected to study their interrelationships by CCD design. Based on the experimental data and ANOVA, the coefficient of determination (R 2), the values of "Prob > F" and F-value were determined to be 0.9692, 0.002 and 7.87, respectively, which demonstrated that the model is significant. And the excellent correlation between the predicted and actual values also provided good confidence in the model. To achieve a higher removal rate of TC under appropriate and more economical experimental conditions, the optimum values of P-loading on TiO2, concentration of P-TiO2, irradiation time, photo intensity, pH and concentration of TC should be set to 17.45 wt%, 1.00 g L-1, 40.39 min, 5 A, 7, 29.93 mg L-1, respectively, in which the degradation of TC can reach 99.16%. Furthermore, the intermediates of TC verified by GC-MS analysis were mainly chains and rings. A possible pathway of photodegradation was also proposed.

Photocatalytic degradation of sulfamonomethoxine by mesoporous phosphorus-doped titania under simulated solar light irradiation.

Photocatalytic degradation of sulfamonomethoxine (SMM) by mesoporous phosphorus-doped TiO2 (P-TiO2) was studied under simulated solar light irradiation. The morphological structure and chemical composition of P-TiO2 were analyzed by XRD, SEM, HRTEM, BET, XPS and FTIR. Using the central composite design (CCD) of response surface methodology (RSM), the degradation of SMM was investigated with a range of antibiotic concentrations (4-8 mg L-1), catalyst dosages (400-900 mg L-1), P doping amounts (5-15 wt %) and irradiation time (90-150 min). The Ti-O-P bond formed during the calcination of TiO2, thereby generating plate-like P-TiO2, where P was uniformly distributed. Phosphorus doping can stabilize anatase TiO2, which has a larger specific surface area and a lower average particle and pore size than bare TiO2. The result obtained from the RSM model showed a significant correlation between the predicted values and the experimental results of SMM degradation (P < 0.05). Under the optimal experimental conditions (antibiotic concentration = 6 mg/L, catalyst dosage = 800 mg/L, P doping = 5 wt% and irradiation time = 90 min), the degradation rate of SMM was 99.51%, and the TOC was 50%. Toxicity showed a considerable reduction towards Vibrio-qinghaiensis sp.-Q67 after SMM photocatalytic degradation. Through free radical capture experiments, LC-MS detection and DFT calculations, the possible photocatalytic degradation mechanism of SMM using P-TiO2 as the catalyst was revealed.

Catalytic liquefaction of sewage sludge to small molecular weight chemicals.

The catalytic hydrotreatment of sewage sludge, the wet solid byproducts from wastewater treatment plants, using supported Ir, Pt, Pd, Ru catalysts had been investigated with different solvent conditions. Reactions were carried out in a batch set-up at elevated temperatures (400 °C) using a hydrogen donor (formic acid (FA) in isopropanol (IPA) or hydrogen gas), with sewage sludge obtained from different sampling places. Sewage sludge conversions of up to 83.72% were achieved using Pt/C, whereas the performance for the others catalysts is different and solvent had a strong effect on the conversion rate and product constitution. The sewage sludge oils were characterised using a range of analytical techniques (GC, GC-MS, GCxGC, GPC) and were shown to consist of monomers, mainly alkanes and higher oligomers.