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This study systematically examined the effect of nitrogen and phosphorous stress on the formation of linoleic acid (LA), arachidonic acid (ARA), and eicosapentaenoic acid (EPA) in Porphyridium cruentum gy-h56. P. cruentum was cultivated in six different media conferring different conditions of nitrogen (N) sufficiency/deprivation and phosphorous (P) sufficiency/limitation/deprivation. Over a 16-day cultivation process, the dry-weight content, proportion of total fatty acids (TFAs), and the concentration in the medium of linoleic acid (LA) were greatly improved by a maximum of 2.5-, 1.6-, and 1.1-fold, respectively, under conditions of N or P deprivation compared with N and P sufficiency. In contrast, levels of EPA or ARA were not enhanced under N or P stress conditions. Additionally, the results showed that N deprivation weakened the impact of P deficiency on the content and proportions of LA and EPA, while P deprivation enhanced the impact of N starvation on the content and proportions of LA and EPA. The conditions of N sufficiency and P deprivation (N+P−) were the optimal conditions for the production of LA, while the optimal conditions for EPA, ARA, and TFAs production were N sufficiency and P limitation (N+P−lim). This study suggests the potential application of combining N removal from saline wastewater with the production of LA, ARA, EPA, and biodiesel.

Although coagulation can enhance sludge dewatering performance, it often leads to dense flocs, hindered water release, and secondary pollution of the sludge cake. In this study, three types of biochar-based skeleton materials, tea waste-derived biochar (TB), PAC sludge-derived biochar (PB), and their mixture (MB), were employed in combination with polyaluminum chloride (PAC) to improve sludge permeability and water release capacity. The results showed that PAC alone reduced the water content (Wc) and capillary suction time (CST) of raw sludge (RS) from 79.07% and 97.45 s to 69.45% and 42.30 s, respectively. In contrast, biochar–PAC composite conditioning achieved further enhancement. Among them, the TBP group (10% DS TB + 4% DS PAC) exhibited the best performance, with Wc and CST reduced to 58.73% and 55.65 s, reaching the threshold for deep dewatering (Wc < 60%). Low-field nuclear magnetic resonance (LF-NMR) analysis revealed an enhanced transformation from bound to free water, improving water mobility. Zeta potential and particle size analysis indicated that biochar promoted electrostatic neutralization and adsorption bridging. Rheological and EPS measurements demonstrated significant reductions in yield stress and apparent viscosity, alongside the enhanced release of proteins and polysaccharides into soluble EPS (S-EPS). Scanning electron microscopy and pore structure analysis further confirmed that biochar formed a stable porous skeleton (pore diameter up to 1.365 μm), improving sludge cake permeability. In summary, biochar synergizes with PAC through a “skeleton support–charge neutralization–adsorption bridging” mechanism, reconstructing sludge microstructure and significantly improving deep dewatering performance.

Aspect category detection is one challenging subtask of aspect based sentiment analysis, which categorizes a review sentence into a set of predefined aspect categories. Most existing methods regard the aspect category detection as a flat classification problem. However, aspect categories are inter-related, and they are usually organized with a hierarchical tree structure. To leverage the structure information, this paper proposes a hierarchical multi-label classification model to detect aspect categories and uses a graph enhanced transformer network to integrate label dependency information into prediction features. Experiments have been conducted on four widely-used benchmark datasets, showing that the proposed model outperforms all strong baselines.

In this study, Tisochrysis lutea was cultivated in mixotrophic and heterotrophic cultures with glycerol as a carbon source and with glucose and acetate for comparison; autotrophic cultivation was the control group without a carbon source. It was found that T. lutea used glycerol and did not use glucose and acetate under mixotrophy. Mixotrophy slightly elevated the docosahexaenoic acid (DHA) and total fatty acids (TFA) content in the dry-weight and enhanced the DHA and TFA production in medium (41.3 and 31.9% respectively) at the end of a 16-day cultivation, while heterotrophy reduced the DHA content and TFA production. Under the mixotrophy, the glycerol contribution to the DHA production (16.19 mg/L) and the TFA production (97.8 mg/L) was not very high and the DHA yield [2.63% chemical oxygen demand (COD)] and TFA yield (13.1% COD) were also very low. Furthermore, T. lutea using glycerol had a period of adaptation, indicating that T. lutea was not an ideal microalga for organic carbon utilization.

In this study, a novel process for phosphorus (P) recovery without excess sludge production from granular sludge in simultaneous nitrification-denitrification and P removal (SNDPR) system is presented. Aerobic microbial granules were successfully cultivated in an alternating aerobic–anaerobic sequencing batch reactor (SBR) for removing P and nitrogen (N). Dense and stable granular sludge was created, and the SBR system showed good performance in terms of P and N removal. The removal efficiency was approximately 65.22 % for N, and P was completely removed under stable operating conditions. Afterward, new operating conditions were applied in order to enhance P recovering without excess sludge production. The initial SBR system was equipped with a batch reactor and a non-woven cloth filter, and 1.37 g of CH 3 COONa·3H 2 O was added to the batch reactor after mixing it with 1 L of sludge derived from the SBR reactor to enhance P release in the liquid fraction, this comprises the new system configuration. Under the new operating conditions, 93.19 % of the P contained in wastewater was released in the liquid fraction as concentrated orthophosphate from part of granular sludge. This amount of P could be efficiently recovered in the form of struvite. Meanwhile, a deterioration of the denitrification efficiency was observed and the granules were disintegrated into smaller particles. The biomass concentration in the system increased firstly and then maintained at 4.0 ± 0.15 gVSS/L afterward. These results indicate that this P recovery operating (PRO) mode is a promising method to recover P in a SNDPR system with granular sludge. In addition, new insights into the granule transformation when confronted with high chemical oxygen demand (COD) load were provided.

In Chinese, phrases and named entities play a central role in information retrieval. Abbreviations, however, make keyword-based approaches less effective. This paper presents an empirical learning approach to Chinese abbreviation prediction. In this study, each abbreviation is taken as a reduced form of the corresponding definition (expanded form), and the abbreviation prediction is formalized as a scoring and ranking problem among abbreviation candidates, which are automatically generated from the corresponding definition. By employing Support Vector Regression (SVR) for scoring, we can obtain multiple abbreviation candidates together with their SVR values, which are used for candidate ranking. Experimental results show that the SVR method performs better than the popular heuristic rule of abbreviation prediction. In addition, in abbreviation prediction, the SVR method outperforms the hidden Markov model (HMM).

Recycling of iron and steelmaking dusts is a key issue in environmental protection efforts and to ensure efficient utilization. In this investigation, we developed a novel recovery process that uses a dispersed in-situ phase induced by an explosive reaction of composite balls of iron and steelmaking dusts. We designed and prepared composite balls for this function using a laboratory model batch-type balling disc (at 12 r/min) and optimized the feeding modes in 180-t and 260-t basic oxygen furnace (BOF) converters. The results indicate that feeding composite balls into BOF converters is an effective novel technology for recovering iron and steelmaking dusts. The period after hot metal charging and prior to the oxygen-blowing process is the most reasonable time to feed composite balls. Composite ball treatment is not appropriate for steel production with sulfur requirements lower than 80 ppm. The maximum composite ball feeding amount is 40 kg/t and the iron yield rate is better than 95%. Compared with the conventional recycling process of sludge and dust, this novel technology is more convenient and efficient, saving up to 309 RMB per ton of steel. Further investigation of this novel recycling technology is merited.

Recycling of iron and steelmaking dusts is a key issue in environmental protection efforts and to ensure efficient utilization. In this investigation, we developed a novel recovery process that uses a dispersed in-situ phase induced by an explosive reaction of composite balls of iron and steelmaking dusts. We designed and prepared composite balls for this function using a laboratory model batch-type balling disc(at 12 r/min) and optimized the feeding modes in 180-t and 260-t basic oxygen furnace(BOF) converters. The results indicate that feeding composite balls into BOF converters is an effective novel technology for recovering iron and steelmaking dusts. The period after hot metal charging and prior to the oxygen-blowing process is the most reasonable time to feed composite balls. Composite ball treatment is not appropriate for steel production with sulfur requirements lower than 80 ppm. The maximum composite ball feeding amount is 40 kg/t and the iron yield rate is better than 95%. Compared with the conventional recycling process of sludge and dust, this novel technology is more convenient and efficient, saving up to 309 RMB per ton of steel. Further investigation of this novel recycling technology is merited.

Twelve years have passed since the advent of grammatical evolution （GE） in 1998, but such issues as vast search space, genotypic readability, and the inherent relationship among grammatical concepts, production rules and derivations have remained untouched in almost all existing GE researches. Model-based approach is an attractive method to achieve different objectives of software engineering. In this paper, we make the first attempt to model syntactically usable information of GE using an automaton, coming up with a novel solution called model-based grammatical evolution （MGE） to these problems. In MGE, the search space is reduced dramatically through the use of concepts from building blocks, but the functionality and expressiveness are still the same as that of classical GE. Besides, complex evolutionary process can visually be analyzed in the context of transition diagrams.

ZnTixFe2-xO4 and ZnTi0.6Fe1.4O4/Carbon nanotubes （ZT0.6F1.4/CNTs） composites were prepared by chemical co-precipitation method. The composition, microstructure, magnetic property, adsorption and photocatalytic activity of the prepared samples were characterized by means of modem analytical techniques. The results indicated that ZT0.6F1.4CNTs composites not only held the original special structure and excellent adsorption properties of CNTs, but also had suitable magnetic property and excellent photocatalytic activity. The removal rate of the samples on Rhodamine B （RhB） depended on the adsorption of CNTs and the photocatalytic degradation of ZTo.6F1.4 in the composites. The maximum adsorption amount （qm） of ZT0.6F1.4/CNTs with the mass ratios of ZT0.6F1.4 to CNTs （mz/c）=l was up to 17.153 mg g-t for RhB, its adsorption behavior was in accord with Langmuir model, and its photocatalytic degradation activity on RhB had a positive correlation with the content of ZT0.6F1.4 in the sample. The experimental results indicate that the total removal rate of composite with rnz/c=l on RhB was more than 95% and the composite had good decontamination capability on industrial dye wastewater. In addition, the samples can be recovered conveniently, activated easily and had good performance for recycling.