Biochar Adsorption Treatment for Typical Pollutants Removal in Livestock Wastewater: A Review

Biochar, as an high efficiency, environmental friendly, and low-cost adsorbent, is usually used as soil conditioner, bio-fuel, and carbon sequestration regent. Recently, biochar has attracted much attention in wastewater treatment field. There are plenty of studies about application of biochar to adsorb pollutants in wastewater, because of its low-cost preparation, high surface area, large pore volume, plentiful functional groups, and environmental stability. Furthermore, it can be reused due to their high treatment efficiency and resource recovery potential. As biochar can be used for adsorption of typical pollutants in livestock wastewater, it becomes a promising method to treat livestock wastewater. The preparation methods, including pyrolysis, hydrothermal carbonization, and gasification, were introduced. The applications of biochar to adsorb typical pollutants, such as organic pollutants, heavy metals, and nutrients, in livestock wastewater were present. The organic structures, surface functional groups, surface electricity, and mineral component of biochar were investigated to explain the adsorption mechanism of organic pollutants, heavy metals, and nutrients in wastewater. Finally, outlooks were made for the better use of biochar in future. The relationship of preparation parameters, structures, and adsorption performance of biochar should be discussed. The quantitative analysis for the adsorption of organic structures, surface functional groups, surface electricity, and mineral component should be performed. The disposal of post-sorption biochar should be investigated

Experiments of Main Parameters Affecting the Erosive Behavior of Self-Excited Oscillating Abrasive Water Jets: Length of Self-Oscillation Chamber, Jet Pressure, Abrasive Fluid Velocity, and Abrasive Grain Size.

To enhance the erosion efficiency in traditional abrasive water jet processing, an abrasive water jet processing method based on self-excited fluid oscillation is proposed. Traditional abrasive water jet methods suffer from reduced jet kinetic energy due to the presence of a stagnation layer, which hinders efficient material removal. By integrating a self-oscillation chamber into the conventional abrasive water jet nozzle, the continuous jet is transformed into a pulsed jet, thereby increasing the jet velocity and enhancing the kinetic energy of the process. This modification aims to improve material removal efficiency. Using Ansys Fluent, we simulated the material removal efficiency on workpiece surfaces with varying lengths of self-oscillation chambers. The simulation results reveal that the optimal length of the self-oscillation chamber for maximum erosion is 4 mm. SiC materials were used to evaluate the impact of self-oscillation chamber length (L), jet pressure (P), abrasive flow rate (M), and abrasive grain size (D) on erosion. Experimental results show that the self-oscillation chamber increases erosion depth by 33 μm. The maximum erosion depths recorded were 167 μm when L = 4 mm, 223 μm when P = 16 MPa, 193 μm when M = 80 g/min, and 268 μm when D = 2000 μm. Overall, the self-excited oscillation effect enhances the erosion efficiency of the waterjet by 14%. This study further elucidates the factors influencing erosion behaviors in oscillating abrasive water jet processing

Multi-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation

Combining deep learning with symbolic logic reasoning aims to capitalize on the success of both fields and is drawing increasing attention. Inspired by DeepLogic, an end-to-end model trained to perform inference on logic programs, we introduce IMA-GloVe-GA, an iterative neural inference network for multi-step reasoning expressed in natural language. In our model, reasoning is performed using an iterative memory neural network based on RNN with a gated attention mechanism. We evaluate IMA-GloVe-GA on three datasets: PARARULES, CONCEPTRULES V1 and CONCEPTRULES V2. Experimental results show DeepLogic with gated attention can achieve higher test accuracy than DeepLogic and other RNN baseline models. Our model achieves better out-of-distribution generalisation than RoBERTa-Large when the rules have been shuffled. Furthermore, to address the issue of unbalanced distribution of reasoning depths in the current multi-step reasoning datasets, we develop PARARULE-Plus, a large dataset with more examples that require deeper reasoning steps. Experimental results show that the addition of PARARULE-Plus can increase the model's performance on examples requiring deeper reasoning depths. The source code and data are available at https://github.com/Strong-AI-Lab/Multi-Step-Deductive-Reasoning-Over-Natural-Language.Comment: 10 pages, 3 figures, The 2nd International Joint Conference on Learning & Reasoning and 16th International Workshop on Neural-Symbolic Learning and Reasoning (IJCLR-NeSy 2022

Recovery of Phosphorus From Swine Manure by Ultrasound/H2O2 Digestion, Struvite Crystallization, and Ferric Oxide Hydrate/Biochar Adsorption

Swine manure is potentially harmful to the environment but is also a readily accessible local source of phosphorus (P) for agricultural use. Decreasing the environmental impact of swine manure and recovering P from swine manure have been a challenge for a long time. In this study, an integrated process involving ultrasound/H2O2 digestion, struvite crystallization, and ferric oxide hydrate (HFO)/biochar adsorption was used to recover P from swine manure. The ultrasound/H2O2 treatment effectively solubilized the swine manure and converted organic P and other sparingly soluble P species into soluble phosphate. The struvite crystallization process allowed 85% of the available P to be recovered at pH 10.0 using a Mg:P molar ratio of 1.4 and a stirring rate of 150 rpm. HFO was loaded onto biochar synthesized by pyrolyzing ground corncob. The mechanism through which P was adsorbed was investigated by X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy. The adsorption of P by the HFO/biochar followed pseudo-second-order kinetics and was primarily controlled by chemical processes. The maximum amounts of P adsorbed were 225.08–242.21 mg/g. Thermodynamic calculations indicated that the adsorption of P was endothermic and spontaneous and increased the degree of disorder in the overall system. P mass balance calculations indicated that 90.4% of the total P was recovered as struvite and P-saturated HFO/biochar

Enhancing Logical Reasoning of Large Language Models through Logic-Driven Data Augmentation

Combining large language models with logical reasoning enhance their capacity to address problems in a robust and reliable manner. Nevertheless, the intricate nature of logical reasoning poses challenges to gathering reliable data from web for building comprehensive training datasets, subsequently affecting the performance on downstream tasks. To address this, we introduce a novel logic-driven data augmentation approach, AMR-LDA. AMR-LDA converts the original text into an Abstract Meaning Representation (AMR) graph, a structured semantic representation that encapsulates the logic structure of the sentence, upon which operations are performed to generate logically modified AMR graphs. The modified AMR graphs are subsequently converted back into texts to create augmented data. Notably, our methodology is architecture-agnostic and enhances generative large language models, such as GPT-3.5 and GPT-4, through prompt augmentation, and fine-tuning discriminative large language models through contrastive learning with logic-driven data augmentation. Empirical evidence underscores the efficacy of our proposed method with improvement in performance across seven downstream tasks, such as logical reasoning reading comprehension, textual entailment, and natural language inference. Furthermore, our method ranked first on the ReClor leaderboard \url{https://eval.ai/web/challenges/challenge-page/503/leaderboard/1347}. The source code and data are publicly available \url{https://github.com/Strong-AI-Lab/Logical-Equivalence-driven-AMR-Data-Augmentation-for-Representation-Learning}.Comment: Accepted for oral presentation at the LLM@IJCAI 2023 non-archival symposiu

A two-step lineage reprogramming strategy to generate functionally competent human hepatocytes from fibroblasts

Terminally differentiated cells can be generated by lineage reprogramming, which is, however, hindered by incomplete conversion with residual initial cell identity and partial functionality. Here, we demonstrate a new reprogramming strategy by mimicking the natural regeneration route, which permits generating expandable hepatic progenitor cells and functionally competent human hepatocytes. Fibroblasts were first induced into human hepatic progenitor-like cells (hHPLCs), which could robustly expand in vitro and efficiently engraft in vivo. Moreover, hHPLCs could be efficiently induced into mature human hepatocytes (hiHeps) in vitro, whose molecular identity highly resembles primary human hepatocytes (PHHs). Most importantly, hiHeps could be generated in large quantity and were functionally competent to replace PHHs for drug-metabolism estimation, toxicity prediction and hepatitis B virus infection modeling. Our results highlight the advantages of the progenitor stage for successful lineage reprogramming. This strategy is promising for generating other mature human cell types by lineage reprogramming.</p

The genome of broomcorn millet

Broomcorn millet (Panicum miliaceum L.) is the most water-efficient cereal and one of the earliest domesticated plants. Here we report its high-quality, chromosome-scale genome assembly using a combination of short-read sequencing, single-molecule real-time sequencing, Hi-C, and a high-density genetic map. Phylogenetic analyses reveal two sets of homologous chromosomes that may have merged ~5.6 million years ago, both of which exhibit strong synteny with other grass species. Broomcorn millet contains 55,930 proteincoding genes and 339 microRNA genes. We find Paniceae-specific expansion in several subfamilies of the BTB (broad complex/tramtrack/bric-a-brac) subunit of ubiquitin E3 ligases, suggesting enhanced regulation of protein dynamics may have contributed to the evolution of broomcorn millet. In addition, we identify the coexistence of all three C4 subtypes of carbon fixation candidate genes. The genome sequence is a valuable resource for breeders and will provide the foundation for studying the exceptional stress tolerance as well as C4 biology

Polycomb CBX7 Directly Controls Trimethylation of Histone H3 at Lysine 9 at the p16 Locus

BACKGROUND: H3K9 trimethylation (H3K9me3) and binding of PcG repressor complex-1 (PRC1) may play crucial roles in the epigenetic silencing of the p16 gene. However, the mechanism of the initiation of this trimethylation is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we found that upregulating the expression of PRC1 component Cbx7 in gastric cancer cell lines MGC803 and BGC823 led to significantly suppress the expression of genes within the p16-Arf-p15 locus. H3K9me3 formation was observed at the p16 promoter and Regulatory Domain (RD). CBX7 and SUV39H2 binding to these regions were also detectable in the CBX7-stably upregulated cells. CBX7-SUV39H2 complexes were observed within nucleus in bimolecular fluorescence complementation assay (BiFC). Mutations of the chromodomain or deletion of Pc-box abolished the CBX7-binding and H3K9me3 formation, and thus partially repressed the function of CBX7. SiRNA-knockdown of Suv39h2 blocked the repressive effect of CBX7 on p16 transcription. Moreover, we found that expression of CBX7 in gastric carcinoma tissues with p16 methylation was significantly lower than that in their corresponding normal tissues, which showed a negative correlation with transcription of p16 in gastric mucosa. CONCLUSION/SIGNIFICANCE: These results demonstrated for the first time, to our knowledge, that CBX7 could initiate H3K9me3 formation at the p16 promoter

Identification of Genome-Wide Variations among Three Elite Restorer Lines for Hybrid-Rice

Rice restorer lines play an important role in three-line hybrid rice production. Previous research based on molecular tagging has suggested that the restorer lines used widely today have narrow genetic backgrounds. However, patterns of genetic variation at a genome-wide scale in these restorer lines remain largely unknown. The present study performed re-sequencing and genome-wide variation analysis of three important representative restorer lines, namely, IR24, MH63, and SH527, using the Solexa sequencing technology. With the genomic sequence of the Indica cultivar 9311 as the reference, the following genetic features were identified: 267,383 single-nucleotide polymorphisms (SNPs), 52,847 insertion/deletion polymorphisms (InDels), and 3,286 structural variations (SVs) in the genome of IR24; 288,764 SNPs, 59,658 InDels, and 3,226 SVs in MH63; and 259,862 SNPs, 55,500 InDels, and 3,127 SVs in SH527. Variations between samples were also determined by comparative analysis of authentic collections of SNPs, InDels, and SVs, and were functionally annotated. Furthermore, variations in several important genes were also surveyed by alignment analysis in these lines. Our results suggest that genetic variations among these lines, although far lower than those reported in the landrace population, are greater than expected, indicating a complicated genetic basis for the phenotypic diversity of the restorer lines. Identification of genome-wide variation and pattern analysis among the restorer lines will facilitate future genetic studies and the molecular improvement of hybrid rice

Transaction Cost Analysis of PPP Risk Share

PPP (Public Private Partnerships) is a new operation mode of infrastructure projects, which usually undergo long periods and have various kinds of risks in technology, market, politics, policy, finance, society, natural conditions and cooperation. So the government and the private agency should establish the risk-sharing mechanism to ensure the successful implementation of the project. As an important branch of the new institutional economics, transaction cost economics and its analysis method have been proved to be beneficial to the proper allocation of risks between the two parts in PPP projects and the improvement of operation efficiency of PPP risk-sharing mechanism. This paper analyzed the transaction cost of the projects risk-sharing method and the both risk carriers. It pointed out that the risk-sharing method of PPP projects not only reflected the spirit of cooperation between public sector and private agency, but also minimized the total transaction cost of the risk sharing mechanism itself. Meanwhile, the risk takers had to strike a balance between the beforehand cost and the afterwards cost so as to control the cost of risk management. The paper finally suggested three ways which might be useful to reduce the transaction cost: to choose appropriate type of contract of PPP risk-sharing mechanism, to prevent information asymmetry and to establish mutual trust between the two participants