Traditional aquaculture provides food for humans, but produces a large amount of wastewater, threatening global sustainability. The antibiotics abuse and the water replacement or treatment causes ...safety problems and increases the aquaculture cost. To overcome environmental and economic problems in the aquaculture industry, a lot of efforts have been devoted into the application of microalgae for wastewater remediation, biomass production, and water quality control. In this review, the systematic description of the technologies required for microalgae-assisted aquaculture and the recent progress were discussed. It deeply reviews the problems caused by the discharge of aquaculture wastewater and introduces the principles of microalgae-assisted aquaculture. Some interesting aspects, including nutrients assimilation mechanisms, algae cultivation systems (raceway pond and revolving algal biofilm), wastewater pretreatment, algal-bacterial cooperation, harvesting technologies (fungi-assisted harvesting and flotation), selection of algal species, and exploitation of value-added microalgae as aquaculture feed, were reviewed in this work. In view of the limitations of recent studies, to further reduce the negative effects of aquaculture wastewater on global sustainability, the future directions of microalgae-assisted aquaculture for industrial applications were suggested.
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•The co-pyrolysis of lignin and waste cooking oil yielded up to 82.6% mono-aromatics.•The highest synergistic extent for mono-aromatic production was 52.1%.•Lignin-derived model ...compounds were selected for co-pyrolysis to study the mechanism.•Guaiacol was more active to be converted to aromatics than o-cresol and phenol.•The mechanism of catalytic co-pyrolysis of lignin and waste cooking oil was proposed.
Lignin and waste cooking oil are wastes from paper and food industries, respectively. In this work, the catalytic fast co-pyrolysis of lignin and waste cooking oil for the production of aromatics in a pyroprobe was investigated with an aim to improve the utilization of lignin waste and waste cooking oil. Furthermore, lignin-derived monomers, including phenol, o-cresol, and guaiacol, were also used as model feedstock for the catalytic co-pyrolysis in order to study the mechanism underlying aromatic formation. The mechanistic study helped lay theoretical foundation for the industrial application of the co-pyrolysis process. The effects of catalyst and waste cooking oil addition on co-pyrolysis product fractional yield and selectivity were studied. High amount of waste cooking oil in the feedstock with appropriate catalyst-to-feedstock ratio (3:1) contributed to high peak-area yields of the total detected compounds and aromatics. The alkylation and demethoxylation of phenols were enhanced at high ratios of catalyst to feedstock and waste cooking oil to lignin. When the ratio of waste cooking oil to lignin was 1:1, the highest mono-aromatic selectivity (82.6%) and synergistic extent (52.1%) for mono-aromatic production were obtained. The catalytic co-pyrolysis of the lignin-derived monomers and waste cooking oil showed that guaiacol was the most active compound to be converted to aromatics, followed by o-cresol, and phenol. The reaction mechanism underlying the formation of aromatics from the synergistic conversion of aliphatics and phenolics was elaborated.
► Mass cultivation of microalgae for biofuel production using municipal wastewater. ► Multi-step screening and acclimation to select high-lipid producing algal strains. ► Examination of 60 algae-like ...microorganisms collected in Minnesota. ► Twenty-seven strains proved to be able to perform facultative heterotrophic growth. ► Seventeen strains examined capable of growing in concentrated municipal wastewater.
Mass cultivation of microalgae for biofuel production depends heavily on the performance of the microalgae strains used. In this study, 60 algae-like microorganisms collected from different sampling sites in Minnesota were examined using multi-step screening and acclimation procedures to select high-lipid producing facultative heterotrophic microalgae strains capable of growing on concentrated municipal wastewater (CMW) for simultaneous energy crop production and wastewater treatment. Twenty-seven facultative heterotrophic microalgae strains were found, among which 17 strains were proved to be tolerant to CMW. These 17 top-performing strains were identified through morphological observation and DNA sequencing as
Chlorella sp.,
Heynigia sp.,
Hindakia sp.,
Micractinium sp., and
Scenedesmus sp. Five strains were chosen for other studies because of their ability to adapt to CMW, high growth rates (0.455–0.498
d
−1) and higher lipid productivities (74.5–77.8
mg
L
−1
d
−1). These strains are considered highly promising compared with other strains reported in the literature.
The feasibility of growing Chlorella sp. in the centrate, a highly concentrated municipal wastewater stream generated from activated sludge thickening process, for simultaneous wastewater treatment ...and energy production was tested. The characteristics of algal growth, biodiesel production, wastewater nutrient removal and the viability of scale-up and the stability of continuous operation were examined. Two culture media, namely autoclaved centrate (AC) and raw centrate (RC) were used for comparison. The results showed that by the end of a 14-day batch culture, algae could remove ammonia, total nitrogen, total phosphorus, and chemical oxygen demand (COD) by 93.9%, 89.1%, 80.9%, and 90.8%, respectively from raw centrate, and the fatty acid methyl ester (FAME) content was 11.04% of dry biomass providing a biodiesel yield of 0.12g-biodiesel/L-algae culture solution. The system could be successfully scaled up, and continuously operated at 50% daily harvesting rate, providing a net biomass productivity of 0.92g-algae/(L day).
Objective
To systematically evaluate the evidence relating to acupuncture on the sleep quality of patients with Parkinson's disease.
Data sources
Six English-language (PubMed, Cochrane Library, ...EBSCOhost, Embase, OVID MEDLINE, and Web of Science) and four Chinese-language (China National Knowledge Infrastructure, SinoMed, China Scientific Journals Database, and Wanfang) databases were searched for pertinent studies published from database inception to 11 October 2023.
Methods
Two researchers independently screened eligible studies and extracted relevant data using custom data extraction tables. Methodological quality assessment of the included studies was performed using Cochrane Handbook 5.1.0. Meta-analysis was performed using Cochrane Review Manager version 5.4.
Results
Twenty-four studies (1701 participants) met inclusion criteria. The meta-analysis showed that acupuncture improved the Parkinson's Disease Sleep Scale, Pittsburgh Sleep Quality Index, Hamilton Anxiety Scale, Hamilton Depression Scale, Self-Rating Depression Scale, and Parkinson's Disease Questionnaire 39 scores compared with controls (all P < 0.05).
Conclusion
This review showed that acupuncture improved sleep quality, anxiety and depressive symptoms, and quality of life of patients with Parkinson's disease relative to controls.
► Integration of algae based biodiesel production and wastewater treatment. ► All tested 14 algae strains were able to grow on centrate wastewater stream. ► Top-performing strains were capable of ...mixotrophic growth on centrate. ► Environmental factors had significant effect on biomass and biodiesel production. ► Environmental factors had important effect on wastewater nutrient removal by algae.
The objectives of this study are to find the robust strains for the centrate cultivation system and to evaluate the effect of environmental factors including light intensity, light–dark cycle, and exogenous CO2 concentration on biomass accumulation, wastewater nutrient removal and biodiesel production. The results showed that all 14 algae strains from the genus of Chlorella, Haematococcus, Scenedesmus, Chlamydomonas, and Chloroccum were able to grow on centrate. The highest net biomass accumulation (2.01g/L) was observed with Chlorella kessleri followed by Chlorella protothecoides (1.31g/L), and both of them were proved to be capable of mixotrophic growth when cultivated on centrate. Environmental factors had significant effect on algal biomass accumulation, wastewater nutrients removal and biodiesel production. Higher light intensity and exogenous CO2 concentration with longer lighting period promote biomass accumulation, biodiesel production, as well as the removal of chemical oxygen demand and nitrogen, while, lower exogenous CO2 concentration promotes phosphorus removal.
•Municipal wastewater-based algae cultivation system was used in this study.•Mutual compound relationship between algae and centrate-borne bacteria was found.•Low initial algal concentration was more ...favorable for bacterial growth.•The initial algal inoculum of 0.1g/L was optimal to obtain maximal algal biomass.•There was a synergistic effect of algae and bacteria for nutrition removal.
Centrate, a type of nutrient-rich municipal wastewater was used to determine the effect of wastewater-borne bacteria on algal growth and nutrients removal efficiency in this study. The characteristics of algal and bacterial growth profiles, wastewater nutrient removal and effect of initial algal inoculums were systematically examined. The results showed that initial algal concentration had apparent effect on bacterial growth, and the presence of bacteria had a significant influence on algal growth pattern, suggesting symbiotic relationship between algae and bacteria at the initial stage of algae cultivation. The maximum algal biomass of 2.01g/L with 0.1g/L initial algal inoculums concentration can be obtained during algae cultivation in raw centrate medium. The synergistic effect of centrate-borne bacteria and microalgae on algae growth and nutrient removal performance at initial fast growth stage has great potential to be applied to pilot-scale wastewater-based algae wastewater system cultivated in continuous or semi-continuous mode.
Abstract
Due to the high‐risk working environment of high‐voltage transmission lines, defect samples of strain clamps cannot be fully and completely collected. As a result, the deep learning method ...based on defect sample tags cannot effectively identify all abnormalities. To solve this problem, an unsupervised anomaly detection method based on knowledge distillation is proposed, which only requires a small number of normal samples to drive the model for anomaly detection. ResNet is the framework of the teacherstudent model, and the feature activation layer after ResBlock is used for knowledge transfer. Residual‐assisted attention and pyramid‐splitting attention were used to enhance the spatial perception and multi‐scale information utilization ability of the model. This model only transmits the information of normal samples and is sensitive to abnormal samples. The proposed model outperformed the baseline by 23% and individual categories by 78% on the MVTec AD (Anomaly Detection Dataset) and outperformed the baseline by 45% and individual categories by 10% on the CIFAR10 and is also reliable for Mnist and Fashion Mnist. This method performs best (82.71%) over the existing method on the self‐built data set.
In aircraft feature detection, the difficulty of acquiring Synthetic Aperture Radar (SAR) images leads to the scarcity of some types of aircraft samples, and the high privacy makes the personal ...sample set have the characteristics of data silos. Existing data enhancement methods can alleviate the problem of data scarcity through feature reuse, but they are still powerless for data that are not involved in local training. To solve this problem, a new federated learning framework was proposed to solve the problem of data scarcity and data silos through multi-client joint training and model aggregation. The commonly used federal average algorithm is not effective for aircraft detection with unbalanced samples, so a federal distribution average deviation (FedDAD) algorithm, which is more suitable for aircraft detection in SAR images, was designed. Based on label distribution and client model quality, the contribution ratio of each client parameter is adaptively adjusted to optimize the global model. Client models trained through federated cooperation have an advantage in detecting aircraft with unknown scenarios or attitudes while remaining sensitive to local datasets. Based on the YOLOv5s algorithm, the feasibility of federated learning was verified on SAR image aircraft detection datasets and the portability of the FedDAD algorithm on public datasets. In tests based on the YOLOv5s algorithm, FedDAD outperformed FedAvg’s mAP0.5–0.95 on the total test set of two SAR image aircraft detection and far outperformed the local centralized training model.
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