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GNNs (Graph Neural Networks) have attracted increasing attention for their strong power on dealing with the graph structures. However, it remains a challenge to design an ideal GNN suitable for various downstream tasks. By revisiting the framework of MPNN (Message Passing Neural Network), we argue that an ideal GNN should satisfy following two conditions. First, the node embedding can absorb the knowledge from a wide range of neighbors while maintaining locality. Second, the first-order information aggregation can adapt to unknown graphs. In this paper, we first extend S 2 GC to GMGC (Generalized Markov Graph Convolution), which can maintain the node locality regardless the type of the embedded diffusion kernel. Next, we embed the improved self-gating mechanism into the GMGC framework and propose a novel model named AMGC (Attention-enabled Adaptive Markov Graph Convolution), which well satisfies the above conditions. Moreover, the advantages of AMGC can be explained in the frequency domain. First, the frequency of the first-order diffusion kernel is adaptive and no longer limited to low-pass as S 2 GC . Second, the multi-order diffusion kernel can retain more components around the core frequency compared with FAGCN. To verify the ability of AMGC, extensive experiments are conducted, including graph regression, graph classification and semi-supervised node classification. The results show that AMGC can achieve comparable performance in all graph tasks. [ABSTRACT FROM AUTHOR]

Background: Sepsis is a high mortality disease which seriously threatens human life and health, for which the pathogenetic mechanism still unclear. There is increasing evidence showed that immune and inflammation responses are key players in the development of sepsis pathology. LncRNAs, which act as ceRNAs, have critical roles in various diseases. However, the regulatory roles of ceRNA in the immunopathogenesis of sepsis have not yet been elucidated. Results: In this study, we aimed to identify immune biomarkers associated with sepsis. We first generated a global immune-associated ceRNA (IMCE) network based on data describing interactions pairs of gene–miRNA and miRNA–lncRNA. Afterward, we excavated a dysregulated sepsis immune-associated ceRNA (SPIMC) network from the global IMCE network by means of a multi-step computational approach. Functional enrichment indicated that lncRNAs in SPIMC network have pivotal roles in the immune mechanism underlying sepsis. Subsequently, we identified module and hub genes (CD4 and STAT4) via construction of a sepsis immune-related PPI network. Then, we identified hub genes based on the modular structure of PPI network and generated a ceRNA subnetwork to analyze key lncRNAs associated with sepsis. Finally, 6 lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) that identified as immune biomarkers of sepsis. Moreover, the CIBERSORT algorithm and the infiltration of circulating immune cells types were performed to identify the inflammatory state of sepsis. Correlation analyses between immune cells and sepsis immune biomarkers showed that the LINC00265 was strongly positive correlated with the macrophages M2 (r = 0.77). Conclusion: Collectively, these results may suggest that these lncRNAs (LINC00265, LINC00893, NDUFA6-AS1, NOP14-AS1, PRKCQ-AS1 and ZNF674-AS1) played important roles in the immune pathogenesis of sepsis and provide potential therapeutic targets for further researches on immune therapy treatment in patients with sepsis. [ABSTRACT FROM AUTHOR]

Implementing the transformer for global fusion is a novel and efficient method for pose estimation. Although the computational complexity of modeling dense attention can be significantly reduced by pruning possible human tokens, the accuracy of pose estimation still suffers from the problem of high overlap of candidate regions and severe background noise. Moreover, the undifferentiated fusion of features from different views also leads to a sizeable effective information loss. To address these challenges, we propose a Gated Region-Refine Pose Transformer (GRRPT) for human pose estimation. The proposed GRRPT can obtain the general area of the human body from the coarse-grained tokens and then embed it into the fine-grained ones to extract more details of the joints. Experimental results on COCO demonstrate that performing the Multi-Resolution Attention mechanism learns more refined candidate regions and improves accuracy. Furthermore, we design a Fusion Gate module consisting of two gates to pixel-wise select valid information from the auxiliary views, which significantly alleviates information redundancy. Finally, we evaluate the effectiveness of our method on Human3.6M and our dataset FDU-Motion and achieve state-of-the-art performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Four different NBWs were added to the sludge anaerobic digestion. • The hydrolysis of sludge anaerobic digestion can be enhanced by the addition of NBW. • Addition of NBW increased methane production by 9.0–27.8% compared with control. • Addition of NBW (Air, CO 2 , He, and N 2) improved the dewaterability of digestate. • Air-NBW was the most cost-effective additive for sludge anaerobic digestion. The subsequence anaerobic digestion (AD) of dewatered sludge (DWS) from wastewater treatment plants necessitates an emphasis on enhancing methane production and dewaterability. The effect of different nanobubble water (NBW) on AD of DWS was investigated under mesophilic conditions. Cumulative methane production was improved by 9.0–27.8% with the addition of different NBW (Air, CO 2 , He, and N 2). NBW improved methanogenic performance by significantly enhancing the hydrolysis of sludge AD. Results from the digestate, the capillary suction time, specific resistance to filtration, and moisture content could be decreased by 14.6–18.2%, 18.8–29.6%, and 13.6–19.5%, respectively. The addition of NBW can improve the dewaterability of digestate by reducing the digestate particle size and increasing the zeta potential of digestate. The addition of NBW significantly increased methane production and improved dewaterability in AD; Air-NBW showed the best improvement. [ABSTRACT FROM AUTHOR]

Optical motion capture systems have been used intensively to obtain human body poses. However, there still exist several problems. First is the dislocation problem caused by joints being too close together. The second is the joint lost problem. Restricted by severe self-occlusions, cameras may not capture the target joints. Given this observation, we investigate the high-level constraints over human poses to solve these two problems. In this work, we present a Simplified-attention Enhanced Graph Convolutional Network (SaEGC-Net) to extract both spatial and temporal features from monocular videos flexibly. The SaEGC-Net for 3D human pose estimation is U-shaped and involves the Cascaded Spatial-Temporal Graph Convolutional (CST-GC) blocks and the Simplified Spatial-Temporal Attention (SST-Att) blocks, allowing for drawing long-range dependencies between unconnected joints by graph topologies and attention mechanism, respectively. Specifically, the CST-GC block embeds two predefined graph structures into a convolutional network, incorporating discriminative features from distant joints. The proposed SST-Att block disregards redundant information by sharing part of the attention map, which is highly lightweight. It also considers dimension-expanded joint relationships to maintain the diversity of dependence. To evaluate the effectiveness of our method, we conduct extensive experiments on two datasets: Human3.6M and our own dataset FDU-Motion. Results demonstrate that our model achieves excellent performance and can competently handle the above two problems. Also, ablation studies show that our network's submodules can better exploit the motion information of the human body. [ABSTRACT FROM AUTHOR]

Objective: The goal of this study is to investigate the efficacy, safety, and mechanism of ABL for inactivating Candida albicans (C. albicans), and to determine the best wavelength for treating candida infected disease, by experimental measurements and dynamic modeling. Methods: The changes in reactive oxygen species (ROS) in C. albicans and human host cells under the irradiation of 385, 405, and 415 nm wavelengths light with irradiance of 50 $mW/cm^2$ were measured. Moreover, a kernel-based nonlinear dynamic model, i.e., nonlinear autoregressive with exogenous inputs (NARX), was developed and applied to predict the concentration of light-induced ROS, whose kernels were selected by a newly developed algorithm based on particle swarm optimization (PSO). Results: The ROS concentration was increased respectively about 10-12 times in C. albicans and about 3-6 times in human epithelial cells by the ABL treatment with the same fluence of 90 $J/cm^2$. The NARX models were respectively fitted to the data from the experiments on both types of cells. Besides, four different kernel functions, including Gaussian, Laplace, linear and polynomial kernels, were compared in their fitting accuracies. The errors with the Laplace kernel turned out to be only 0.2704 and 0.0593, as respectively fitted to the experimental data of the C. albicans and human host cells. Conclusion: The results demonstrated the effectiveness of the NARX modeling approach, and revealed that the 415 nm light was more effective as an anti-fungal treatment with less damage to the host cells than the 405 or 385 nm light. Significance: The kernel-based NARX model identification algorithm offers opportunities for determining the effective and safe light dosages in treating various fungal infection diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] • Microbial electrolysis cell was integrated in different phases of different TPAD. • Thermophilic conditions enhanced hydrolysis more than microbial electrolysis cell. • TPAD integrated microbial electrolysis cell improved the methane yield. • Microbial electrolysis cell was more effective in mesophilic-mesophilic TPAD. Temperature-phased anaerobic digestion (TPAD) and microbial electrolysis cell (MEC) are both able to improve hydrolysis and methane yield during anaerobic digestion (AD) of dewatered sludge. However, the effect of TPAD and MEC integration at different temperatures and different phases is unclear. This study investigated the effect of the integration of intermittent energization MEC in different phases of TPAD on the digestion of dewatered sludge. Thermophilic and MEC hydrolysis could release higher total ammonia nitrogen of 186.0% and 10.3% than control, mesophilic methanogenesis phase integrated with MEC relieved the ammonia inhibition and accelerated the acid utilization leading to the relief of acid accumulation. The ultimate methane yield of the TPAD integrated with MEC was increased by 118.9%, in which the relative abundance of Methanothermobacteria and Methanosarcina was increased. Therefore, intermittent energization MEC integrated TPAD synchronously improved the hydrolysis and methane yield. [ABSTRACT FROM AUTHOR]

Myasthenia gravis (MG) is a complex neurological autoimmune disease with a pathogenetic mechanism that has yet to be elucidated. Emerging evidence has revealed that genes, non-coding RNAs and genetic variants play significant roles in the pathogenesis of MG. However, the molecular mechanisms of single nucleotide polymorphisms (SNPs) located on lncRNAs could disturb lncRNA-mediated ceRNA regulatory functions still unclear in MG. In this study, we collated 276 experimentally confirmed MG risk genes and 192 MG risk miRNAs. We then constructed a lncRNA-mediated ceRNA network for MG based on multi-step computational strategies. Next, we systematically integrated risk pathways and identified candidate SNPs in lncRNAs for MG based on data acquired from public databases. In addition, we constructed a pathway-based lncRNA-SNP mediated network (LSPN) that contained 128 lncRNAs targeting 8 MG risk pathways. By analyzing network, we propose a latent mechanism for how the "lncRNA-SNP-mRNA-pathway" axis affects the pathogenesis of MG. Moreover, 25 lncRNAs and 51 SNPs on lncRNAs were extracted from the "lncRNA-SNP-mRNA-pathway" axis. Finally, functional analyses demonstrated lncRNA-SNPs mediated ceRNA regulation pairs associated with MG participated in the MAPK signaling pathway. In summary, we constructed MG-specific lncRNA-SNPs mediated ceRNA regulatory networks based on pathway in the present study, which was helpful to elucidate the roles of lncRNA-SNPs in the pathogenesis of MG and provide novel insights into mechanism of lncRNA-SNPs as potential genetic risk biomarkers of MG. [ABSTRACT FROM AUTHOR]

Determining the extreme values of wind loads is crucial for wind-resistant design of structures. The Hermite polynomial model (HPM)- based translation method, which uses the first four moments of wind load, is the most recognized and widely used method for extreme wind load estimations. In this study, a quartic HPM-based translation method for estimating extreme wind loads is proposed. A strategy for solving the shape coefficients is suggested for better practical use. The monotonic increasing condition required for the translation between non-Gaussian wind load and standard Gaussian process is discussed, based on which the constraint of shape coefficients governing the applicability of the quartic HPM is derived. From the validation study, it is found that the applicability of the quartic HPM is satisfactory. Compared with the cubic and improved HPMs, the quartic HPM stands out for yielding more accurate estimates of extreme wind loads. Comparative analysis with the XIMIS, an observed-maxima method, reveals the quartic HPM's consistency in estimating extreme wind loads from data with shorter periods, while the performance of XIMIS deteriorates with decreasing periods. Furthermore, the quartic HPM exhibits robustness in addressing strong non-Gaussian wind loads, outperforming the other methods under such conditions. • A quartic HPM-based translation method for estimating extreme values of wind loads is proposed. • Constraint of shape coefficients in quartic HPM that governs requirement of monotonic increasing condition is derived. • Intensity of non-Gaussianity is quantitatively defined and successfully associated to tail characteristic of parent distribution of wind loads. • Quartic HPM outperforms cubic and improved HPMs, as well as XIMIS, in estimating extreme values of wind loads with strong non-Gaussianity. [ABSTRACT FROM AUTHOR]

This paper focuses on the self-supervised learning issue on heterogeneous graph. Currently, contrastive learning has become the dominant approach on various heterogeneous graph tasks. Its performance is highly dependent on the elaborate selection strategy of negative samples. However, it is difficult to design such an ideal strategy giving sufficient consideration to the characteristics of graph, such as structural similarity and feature similarity. To circumvent this problem, we propose a novel negative sample-free self-supervised framework named HGISD (H eterogeneous G raph learning based on I terative S imilarity D istillation), where the student improves itself by imitating the teacher's behavior and the teacher updates itself as a slow-moving average of the student. Moreover, metapath-based HGNN is employed as the built-in information encoder. We argue that previous metapath-based HGNNs neglect the correlation among metapaths and the locality within metapaths. To tackle these issues, we respectively propose IMCD (I nter- M etapath C orrelation D istillation) and IMSD (I ntra- M etapath S imilarity D istillation) within the self-distillation framework. Both IMCD and IMSD treat the embeddings in the shallow layers as the knowledge source, which well preserves the inter-metapath correlation and the intra-metapath locality. Finally, we conduct extensive experiments on several real-world heterogeneous graph datasets. The results show that the proposed HGISD achieves superior performance compared with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

With the growing scale of pre-trained language models (PLMs), full parameter fine-tuning becomes prohibitively expensive and practically infeasible. Therefore, parameter-efficient adaptation techniques for PLMs have been proposed to learn through incremental updates of pre-trained weights, such as in low-rank adaptation (LoRA). However, LoRA relies on heuristics to select the modules and layers to which it is applied, and assigns them the same rank. As a consequence, any fine-tuning that ignores the structural information between modules and layers is suboptimal. In this work, we propose structure-aware low-rank adaptation (SaLoRA), which adaptively learns the intrinsic rank of each incremental matrix by removing rank-0 components during training. We conduct comprehensive experiments using pre-trained models of different scales in both task-oriented (GLUE) and task-agnostic (Yelp and GYAFC) settings. The experimental results show that SaLoRA effectively captures the structure-aware intrinsic rank. Moreover, our method consistently outperforms LoRA without significantly compromising training efficiency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Methane yield of thermophilic digester is greater than that of mesophilic digester. • Bacterial and archaeal diversity of mesophilic digesters is more abundant. • Plant growth promotion of mesophilic biogas slurry is more prominent. • Potassium in biogas slurry is the key factor to promote plant growth. The objective of this study was to investigate the effects of mixing ratios of Chinese cabbage waste (CCW) and cow manure (CM) on methane yields, microbial community, and biogas slurry fertility during anaerobic co-digestion. Batch experiments were conducted at mesophilic and thermophilic temperatures with five different CCW/CM mixing ratios. Methane yields at mesophilic and thermophilic temperatures were 4.2–184.4 mL g−1 Volatile solids added (mL g−1 VS added) and 11.8–321.7 mL g−1 VS added , respectively. The richness and diversity of bacteria and archaea at mesophilic temperatures were higher than those at thermophilic temperatures. Compared with the unfertilized control, the dry weight of corn seedlings with the follow-up application of mesophilic or thermophilic biogas slurry increased by 12.3 %-73.4 % or 16.8 %-43.3 %, respectively. This study demonstrates that thermophilic temperatures are conducive to increasing methane yields, but mesophilic temperatures are conducive to improving the biogas slurry fertility. [ABSTRACT FROM AUTHOR]

Phosphorus deficiency severely limits crop yields and hinders sustainable agricultural development. Phosphate-solubilizing bacteria (PSB) are beneficial for crop growth because they enhance the uptake and utilization of phosphorus. This study explored the phosphorus-solubilizing, IAA-producing, nitrogen-fixing, potassium-solubilizing, and siderophore-producing abilities of three bacterial strains (Pantoea sp. J-1, Burkholderia cepacia Z-7, and Acinetobacter baumannii B-6) screened from the maize rhizosphere. A pot experiment was also conducted to explore the role of screened PSB in the growth of maize. Finally, the effects of the PSB on the physicochemical properties, enzyme activities, and microbial community structure of maize rhizosphere soil were analyzed. The results showed that strain Z-7 had the strongest abilities phosphorus solubilization, nitrogen fixation, potassium solubilization, and siderophore production, while strain J-1 exhibited the highest yield of IAA. The application of PSB promoted the growth of maize plants to different extents. Among the different treatments, the mixed bacterial treatment (J-1 + Z-7 + B-6) had the most potent growth promotion effect, and the consortium treatment significantly enhanced the activity of soil phosphatase. Soil pH, total phosphorus (TP), total potassium (TK), available phosphorus (AP), NH4+-N, and NO3−-N are key factors for the growth of maize plants. In addition, PSB significantly altered the microbial community structure in the maize rhizosphere soil, and the relative abundance of Proteobacteria increased by 16.07–69.10% compared to the control. These PSB have obvious growth-promoting abilities, with the potential to enhance crop productivity as excellent candidate strains for the development of biological fertilizers. [ABSTRACT FROM AUTHOR]

Background: Long non-coding RNAs (lncRNAs), functioning as competing endogenous RNAs (ceRNAs), have been reported to play important roles in the pathogenesis of autoimmune diseases. However, little is known about the regulatory roles of lncRNAs underlying the mechanism of myasthenia gravis (MG). The aim of the present study was to explore the roles of lncRNAs as ceRNAs associated with the progression of MG.Methods: MG risk genes and miRNAs were obtained from public databases. Protein-protein interaction (PPI) network analysis and module analysis were performed. A lncRNA-mediated module-associated ceRNA (LMMAC) network, which integrated risk genes in modules, risk miRNAs and predicted lncRNAs, was constructed to systematically explore the regulatory roles of lncRNAs in MG. Through performing random walk with restart on the network, HCG18/miR-145-5p/CD28 ceRNA axis was found to play important roles in MG, potentially. The expression of HCG18 in MG patients was detected using RT-PCR. The effects of HCG18 knockdown on cell proliferation and apoptosis were determined by CCK-8 assay and flow cytometry. The interactions among HCG18, miR-145-5p and CD28 were explored by luciferase assay, RT-PCR and western blot assay.Results: Based on PPI network, we identified 9 modules. Functional enrichment analyses revealed these modules were enriched in immune-related signaling pathways. We then constructed LMMAC network, containing 25 genes, 50 miRNAs, and 64 lncRNAs. Through bioinformatics algorithm, we found lncRNA HCG18 as a ceRNA, might play important roles in MG. Further experiments indicated that HCG18 was overexpressed in MG patients and was a target of miR-145-5p. Functional assays illustrated that HCG18 suppressed Jurkat cell apoptosis and promoted cell proliferation. Mechanistically, knockdown of HCG18 inhibited the CD28 mRNA and protein expression levels in Jurkat cells, while miR-145-5p inhibitor blocked the reduction of CD28 expression induced by HCG18 suppression.Conclusion: We have reported a novel HCG18/miR-145-5p/CD28 ceRNA axis in MG. Our findings will contribute to a deeper understanding of the molecular mechanism of and provide a novel potential therapeutic target for MG. [ABSTRACT FROM AUTHOR]

Conventional high-power wireless power transfer (WPT) systems that are required to deliver power over a wide operating range suffer from issues like hard switching, poor current sharing, and unwanted cross-coupling issues. This article proposes a new resonant inductor integrated-transformer-based multi-inverter to improve the WPT power rating without compromising performance. Viable modulation schemes of the proposed system are analyzed, and a hybrid modulation scheme is proposed for wide-range power regulation. To further investigate the feasibility of the proposed system, the power transfer capacity, current sharing among multiple inverters, and the soft switching regions are studied. A 14-kW LCC–LCC WPT experimental system with three parallel inverters is built, which achieves 93.5% efficiency, demonstrating the high performance of the proposed system. This article is accompanied by a video demonstrating these experiments. [ABSTRACT FROM AUTHOR]

The gradual increase in cattle farming has led to a huge production of cattle manure (CM), but the conventional treatment methods are less efficient. In this study, the treatment method of anaerobic digestion (AD) of high-solids CM by combining nanobubble water (NBW) with different gases was proposed to present a new idea for the reduction, harmlessness, and resourcefulness of CM. It was found that the performance of the digester with added NBW was better than the control. Among them, the cumulative methane yield T-Air: 227.09 mL g−1 VS added and T-CO 2 : 226.12 mL g−1 VS added increased by 17.72 % and 17.22 %, respectively, compared with the control T: 192.90 mL g−1 VS added under thermophilic conditions. Under mesophilic conditions, M-Air: 162.39 mL g−1 VS added increased by 9.68 % compared with control M: 148.05 mL g−1 VS added. Microbial communities analyzed at the genus level revealed that the relative abundance of bacteria favorable to hydrolysis and acid-producing processes, such as Defluviitalea , Haloplasma , and Bacillus , increased to varying degrees. Moreover, the relative abundance of archaea favorable for methanogenesis, such as Methanoculleus , Methanobrevibacter , and Methanosarcina , also increased to varying degrees. Therefore, the addition of NBW promoted the hydrolysis of high-solids CM, enhanced the stability of the reaction, improved the methanogenic performance, and increased the RA of favorable genera, which ultimately led to a better performance of the AD of high-solids CM. [Display omitted] • Compared with control, NBW increased CH 4 production by 5–17 %. • Compared with control, NBW contributes to the production/transformation of VFAs. • Incorporation of NBW improves stability of high solids anaerobic digestion. • Compared with control, NBW increased the RA of hydrolytic acidification-associated bacteria. • Compared with control, NBW increased the RA of methanogenic-associated archaea. [ABSTRACT FROM AUTHOR]

The prognostic and therapeutic implications in diffuse gliomas are still challenging. In this study, we first performed an integrative framework to infer the clonal status of mutations in glioblastomas (GBMs) and low-grade gliomas (LGGs) by using exome sequencing data from TCGA and observed both clonal and subclonal mutations for most mutant genes. Based on the clonal status of a given gene, we systematically investigated its prognostic value in GBM and LGG, respectively. Focusing on the subclonal mutations, our results showed that they were more likely to contribute to the poor prognosis, which could be hardly figured out without considering clonal status. These risk subclonal mutations were associated with some specific genomic features, such as genomic instability and intratumor heterogeneity, and their accumulation could enhance the prognostic value. By analyzing the regulatory mechanisms underlying the risk subclonal mutations, we found that the subclonal mutations of AHNAK and AHNAK2 in GBM and those of NF1 and PTEN in LGG could influence some important molecules and functions associated with glioma progression. Furthermore, we dissected the role of risk subclonal mutations in tumor evolution and found that advanced subclonal mutations showed poorer overall survival. Our study revealed the importance of clonal status in prognosis analysis, highlighting the role of the subclonal mutation in glioma prognosis. [ABSTRACT FROM AUTHOR]

To enhance the dewaterability of anaerobic digested sludge and to make full use of the biogas slurry. This study set up five sludge conditioning methods: polymeric ferric sulfate, polymeric aluminum chloride, cationic polyacrylamide, chitosan, and chitosan combined with rice husk powder. Their effects on the dewaterability of thermal hydrolysis-anaerobic digested sludge, bacterial community, and biogas slurry fertility were studied to find a non-toxic and non-risk dewatering technology for the environment and biogas slurry. Compared with that of the control group, moisture content, normalization capillary suction time, and specific resistance to filtration were reduced by 12.8%, 97.7%, and 82.9%, respectively. Chitosan enlarges the sludge flocs and forms complexes with proteins, disrupting the structure of the extracellular polymeric substances, thereby exposing more hydrophobic groups and reducing the hydrophilicity of the sludge. The subsequent addition of rice husk powder enhances the adsorption of hydrophilic substances and provides a stronger drainage channel for the sludge. In addition, the biogas slurry obtained by this conditioning method used as a fertilizer increased the dry weight and fresh weight of corn seedlings by 59.3% and 91.0%, respectively. And the total chlorophyll content increased by 84.6%. Pearson's correlation analysis showed that chitosan and rice husk meal had no toxic effect on the biogas slurry compared to the other three flocculants. The results showed that the combined treatment of chitosan and rice husk powder resulted in the best dewaterability. Overall, chitosan combined with rice husk powder is a green dewatering technology with great potential for anaerobic digested sludge dewatering and biogas slurry recycling. [Display omitted] • Compared with control, CS+RHP reduced SRF and NCST of sludge by 82.9% and 97.7%. • Compared with PFS, PAC, and CPAM, CS is better for plant growth promotion. • Compared with control, dry weight of corn seedling in CS+RHP increased by 59.3%. • Compared with control, total chlorophyll of seedling in CS+RHP increased by 84.6%. [ABSTRACT FROM AUTHOR]

[Display omitted] • Co-digestion improved methane yield 31.3%-68.0% at thermophilic temperature. • Co-digestion improved methane yield 83.0%-136.5% at mesophilic temperature. • The highest methane yield of anaerobic co-digestion obtained at P/S = 2:1. • NCST and TS of sediment increased with increasing initial TS of substrate. • NCST has a strong negative correlation with the water removal efficiency. The objective of this study is to assess the effects of the mixing ratio on the methane production and digestate dewaterability of co-digestion of pig manure (P) and sludge (S). Batch experiments were carried out at five different P/S mixing ratios at mesophilic and thermophilic temperatures. Compared to sludge anaerobic digestion, co-digestion of pig manure with sludge increased methane yield 83.0%-136.5% at mesophilic temperature and 31.3%-68.0% at thermophilic temperature. The normalized capillary suction time (NCST) and total solids (TS) of sediment (centrifugal dewatering) increased when pig manure proportion of substrate increased. The NCST at thermophilic temperatures (4.87–17.58 s g−1-TSS) was higher than that at mesophilic temperatures (1.89–10.95 s g−1-TSS). However, the TS of sediment was close at thermophilic and mesophilic temperatures. The results indicated that anaerobic co-digestion of pig manure and sludge at a proper mixing ratio (P/S = 2:1) provides a good choice for energy recovery and land utilization. [ABSTRACT FROM AUTHOR]