Construction and application of highly efficient waste cooking oil degrading bacteria consortium in oily wastewater.

The treatment of cooking oil wastewater is an urgent issue need to be solved. We aimed to screen for efficient oil-degrading bacteria and develop a new microbial agent for degrading waste cooking oil in oily wastewater. Three extremely effective oil-degrading bacteria, known as YZQ-1, YZQ-3, and YZQ-4, were found by the enrichment and acclimation of samples from various sources and separation using oil degradation plates. The 16S rRNA sequencing analysis and phylogenetic tree construction showed that the three strains were Bacillus tropicus, Pseudomonas multiresinivorans, and Raoultella terrigena. Under optimal degradation conditions, the maximal degradation rates were 67.30 ± 3.69%, 89.65 ± 1.08%, and 79.60 ± 5.30%, respectively, for YZQ-1, YZQ-3, and YZQ-4. Lipase activity was highest for YZQ-3, reaching 94.82 ± 12.89 U/L. The best bacterial alliance was obtained by adding equal numbers of microbial cells from the three strains. Moreover, when this bacterial alliance was applied to oily wastewater, the degradation rate of waste cooking oil was 61.13 ± 7.30% (3.67% ± 2.13% in the control group), and COD removal was 62.4% ± 5.65% (55.60% ± 0.71% in the control group) in 72 h. Microbial community analysis results showed YZQ-1 and YZQ-3 were adaptable to wastewater and could coexist with local bacteria, whereas YZQ-4 could not survive in wastewater. Therefore, the combination of YZQ-1 and YZQ-3 can efficiently degrade oil and shows great potential for oily wastewater treatment.

Application of oil-degrading agents consisted of thermophilic Bacillus subtilis and Bacillus glycinifermentans in food waste.

This work aims to investigate the effective removal of oil in food waste (FW). Two bacteria, Bacillus subtilis and Bacillus glycinifermentans, were obtained under high temperature conditions and named YZQ-2 and YZQ-5, respectively. The oil degradation rate of two bacteria was explored under different pH value, temperature, and NaCl concentration. In addition, the lipase and emulsifying activity were evaluated. The maximum oil degradation rate was 83.41 ± 0.86% and the maximum lipase activity reached 89.73 ± 20.89 U L-1 with YZQ-2. The fermentation broth of YZQ-2 displayed exceptional emulsification activity. Subsequently, YZQ-2 and YZQ-5 were added to aerobic FW composting. The moisture content of the compost treated with inoculated strains decreased at a faster rate during the first three days of composting. The microbial quantity increased rapidly in the first three days, and the oil degradation rate reached 39.96% after five days. Due to the excellent adaptability to high temperature and ability to degrade oil, strains YZQ-2 and YZQ-5 exhibit superior potential for various applications.

Design of A Finite-Time Adaptive Controller for Image-Based Uncalibrated Visual Servo Systems with Uncertainties in Robot and Camera Models.

Aiming at the time-varying uncertainties of robot and camera models in IBUVS (image-based uncalibrated visual servo) systems, a finite-time adaptive controller is proposed based on the depth-independent Jacobian matrix. Firstly, the adaptive law of depth parameters, kinematic parameters, and dynamic parameters is proposed for the uncertainty of a robot model and a camera model. Secondly, a finite-time adaptive controller is designed by using a nonlinear proportional differential plus a dynamic feedforward compensation structure. By applying a continuous non-smooth nonlinear function to the feedback error, the control quality of the closed-loop system is improved, and the desired trajectory of the image is tracked in finite time. Finally, using the Lyapunov stability theory and the finite-time stability theory, the global finite-time stability of the closed-loop system is proven. The experimental results show that the proposed controller can not only adapt to the changes in the EIH and ETH visual configurations but also adapt to the changes in the relative pose of feature points and the camera's relative pose parameters. At the same time, the convergence rate near the equilibrium point is improved, and the controller has good dynamic stability.

Research on Apple Recognition Algorithm in Complex Orchard Environment Based on Deep Learning.

In the complex environment of orchards, in view of low fruit recognition accuracy, poor real-time and robustness of traditional recognition algorithms, this paper propose an improved fruit recognition algorithm based on deep learning. Firstly, the residual module was assembled with the cross stage parity network (CSP Net) to optimize recognition performance and reduce the computing burden of the network. Secondly, the spatial pyramid pool (SPP) module is integrated into the recognition network of the YOLOv5 to blend the local and global features of the fruit, thus improving the recall rate of the minimum fruit target. Meanwhile, the NMS algorithm was replaced by the Soft NMS algorithm to enhance the ability of identifying overlapped fruits. Finally, a joint loss function was constructed based on focal and CIoU loss to optimize the algorithm, and the recognition accuracy was significantly improved. The test results show that the MAP value of the improved model after dataset training reaches 96.3% in the test set, which is 3.8% higher than the original model. F1 value reaches 91.8%, which is 3.8% higher than the original model. The average detection speed under GPU reaches 27.8 frames/s, which is 5.6 frames/s higher than the original model. Compared with current advanced detection methods such as Faster RCNN and RetinaNet, among others, the test results show that this method has excellent detection accuracy, good robustness and real-time performance, and has important reference value for solving the problem of accurate recognition of fruit in complex environment.

Evaluation of a data-driven intelligent waste classification system for scientific management of garbage recycling in a Chinese community.

Waste classification management is effective in addressing the increasing waste output and continuous deterioration of environmental conditions. The waste classification behaviour of resident is an important basis for managers to collect and allocate resources. Traditional analysis methods, such as questionnaire, have limitations considering the complexity of individual behaviour. An intelligent waste classification system (IWCS) was applied and studied in a community for 1 year. Time-based data analysis framework was constructed to describe the residents' waste sorting behaviour and evaluate the IWCS. The results showed that residents preferred to use face recognition than other modes of identification. The ratio of waste delivery frequency was 18.34% in the morning and 81.66% in the evening, respectively. The optimal time windows of disposing wastes were from 6:55 to 9:05 in the morning and from 18:05 to 20:55 in the evening which can avoid crowding. The percentage of accuracy of waste disposal increased gradually in a year. The amount of waste disposal was largest on every Sunday. The average accuracy was more than 94% based on monthly data, but the number of participating residents decreased gradually. Therefore, the study demonstrates that IWCS is a potential platform for increasing the accuracy and efficiency of waste disposal and can promote regulations implementation.

A dual bacterial alliance removed erythromycin residues by immobilizing on activated carbon.

Removing erythromycin from the environment is a major challenge. In this study, a dual microbial consortium (Delftia acidovorans ERY-6A and Chryseobacterium indologenes ERY-6B) capable of degrading erythromycin was isolated, and the erythromycin biodegradation products were studied. Coconut shell activated carbon was modified and its adsorption characteristics and erythromycin removal efficiency of the immobilized cells were studied. It was indicated that alkali-modified and water-modified coconut shell activated carbon and the dual bacterial system had excellent erythromycin removal ability. The dual bacterial system follows a new biodegradation pathway to degrade erythromycin. The immobilized cells removed 95% of erythromycin at a concentration of 100 mg L-1 within 24 h through pore adsorption, surface complexation, hydrogen bonding, and biodegradation. This study provides a new erythromycin removal agent and for the first time describes the genomic information of erythromycin-degrading bacteria, providing new clues regarding bacterial cooperation and efficient erythromycin removal.

Reuse of composted food waste from rural China as vermicomposting substrate: effects on earthworms, associated microorganisms, and economic benefits.

ABSTRACTAerobic composting of food waste (FW) from rural China using a composting device results in a substantial financial burden on the government. This study aimed to assess the feasibility of mitigating this cost using vermicomposting of composted FW. The specific aims were to elucidate the effects of composted FW on earthworm growth and reproduction, reveal the changes in the physical and chemical properties of earthworm casts during vermicomposting, identify the microbial community structure associated with vermicomposting, and perform a financial analysis based on the yield of earthworms and earthworm casts. Mixing composted FW and mature cow dung in an equal ratio achieved the highest earthworm reproduction rate, where 100 adult earthworms produced 567 juvenile earthworms and 252 cocoons in 40 d. Earthworms reduce salt content of vermicomposting substrates by assimilating Na+ and promoting humification by transforming humin into humic and fulvic acid, thus producing earthworm casts with a high generation index > 80%. When composted FW was added to a vermicomposting substrate, a distinctive microbial community structure with alkaliphilic, halophilic, and lignocellulolytic microorganisms dominated the microflora. The dominant bacterial species was Saccharopolyspora rectivirgula, and the dominant fungal species changed from Kernia nitida to Coprinopsis scobicola. Furthermore, microbial genes for refractory organic matter and fat degradation were observed in Vibrio cholerae, Kernia nitida, and Coprinopsis scobicola. Financial analysis showed that vermicomposting has the potential to reduce the cost associated with FW disposal from $ 57 to $ 18/t.

Biodegradation of tylosin in swine wastewater by Providencia stuartii TYL-Y13: Performance, pathway, genetic background, and risk assessment.

Microbial bioremediation offers a solution to the problem of residual antibiotics in wastewater associated with animal farms. Efficient degradation of antibiotic residues depends upon the genetic make-up of microbial degraders, which requires a comprehensive understanding of the degradation mechanisms. In this study, a novel, efficient tylosin (TYL)-degrading bacterium, Providencia stuartii TYL-Y13 (Y13) was isolated, which could completely degrade 100 mg/L TYL within 15 h under optimal operating conditions at 40 â„ƒ, pH 7.0 %, and 1 % (v/v) bacterial inoculation rate. Whole genome sequencing revealed that strain Y13 consists of a circular chromosome and two plasmids. A new biodegradation pathway of TYL including desugarification, hydrolysis, and reduction reactions was proposed through the analysis of biodegradation products. It was demonstrated that strain Y13 gradually decreased the biotoxicity of TYL and its metabolites based on the results of the ecological structural activity relationships (ECOSAR) model analysis and toxicity assessment. Moreover, Y13 promoted the reduction of the target macrolide resistance genes in wastewater and disappeared within 84 h. These results shed new light on the mechanism of TYL biodegradation and better utilization of microbes to remediate TYL contamination.

Efficient degradation of tylosin by Klebsiella oxytoca TYL-T1.

Tylosin is widely used in livestock; however, the release of tylosin through animal manure can cause serious environmental problems. In this study, a new tylosin-degrading strain, TYL-T1, was isolated. Its phylogenetic similarity to Klebsiella oxytoca was found to be 99.17 %. TYL-T1 maintained good growth at 40 °C over a broad pH range (4.0-10). TYL-T1 degraded 99.34 % of tylosin in 36 h under optimal conditions (tylosin initial concentration: 25 mg/L, pH: 7.0, and temperature: 35 °C). After LC-MS-MS analysis, a new degradation pathway for tylosin was proposed, including ester bond breaking of the macrolide lactone ring, redox reaction, and loss of mycinose and mycarose. Based on a transcriptome analysis, 164 genes essential for degradation were upregulated through hydrolysis and redox of tylosin. Among various transferases, lipopolysaccharide methyltransferase, glycogen glucosyltransferase, and fructotransferase were responsible for tylosin degradation. The present study revealed the degradation mechanism of tylosin and highlighted the potential of Klebsiella oxytoca TYL-T1 to remove tylosin from the environment.

Mechanisms underlying operational energy consumption of buildings for low carbon city construction: A review.

With rapid urbanization, the increasing building stock, building operation energy consumption and the corresponding carbon emissions have become the important factors restricting the sustainable development of cities. To reduce energy consuming, it is necessary to explore the mechanisms underlying building's operational energy consumption and carbon emission. Although previous studies have analyzed the influencing factors and driving mechanism of urban building carbon emission from different perspectives, a systematical review of the relevant studies which could provide comprehensive guidance for building energy conservation and consumption reduction is fairly scarce. Following the Social-Economic-Natural Complex Ecosystem theory, we comprehensively discussed the driving mechanisms of the building's operational energy consumption and carbon emission. We further analyzed the various single-source driving mechanisms from the perspective of socio-economic, building feature, regional climate and microclimate conditions. Finally, we tackled the weaknesses of current researches and addressed the prospect for future development. The driving mechanism summarized in this work would contribute to the development of related research and support low carbon city construction.

4.0 Gbps visible light communication in a foggy environment based on a blue laser diode.

Fog has a strong attenuation effect on the optical channel, which will greatly degrade the performance of visible light communication (VLC). Studying the effect of the fog on communication performance is crucial to realize outdoor VLC for next generation networks, but there is little research on this topic. In this work, the transmission characteristics of visible light band in the foggy channel were measured and a high-speed VLC system based on a 450 nm blue laser diode (LD) and 16-ary quadrature amplitude modulation orthogonal frequency division multiplexing (16-QAM-OFDM) in the artificial fog environment was demonstrated experimentally. Through a foggy channel of 60 cm, a maximum data rate of up to 4 Gbps was achieved at the pass loss of 13.06 dB with a bit error rate (BER) of 3.5 × 10-3 below the forward error correction (FEC) limit (3.8 × 10-3), which was the highest data rate ever reported for VLC in the foggy channel. Even at a higher pass loss of 17.32 dB, the proposed system still could achieve a data rate of 2.84 Gbps with a BER of 2.8 × 10-3. Further extending the distance to 16.9 m for a more practical application, a data rate of 2.0 Gbps was also demonstrated successfully.