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Let A be a complete and cocomplete abelian category with the additional assumption that any direct sum and product of short exact sequences are exact. We explore the relation between balanced pairs and TTF triples in A. The main results are: (1) every balanced pair in A induces a TTF triple; (2) if A has projective covers and injective envelopes, then every TTF triple in A gives rise to a balanced pair, and hence there is a bijection between the equivalence classes of balanced pairs and TTF triples in A ; (3) a balanced pair in A is quasi admissible if and only if its induced TTF triple is centrally splitting. Our first application of these results provide abundant rings over which every balanced pair is quasi admissible, including local rings, commutative semiperfect rings, and commutative Noetherian rings. Another application is the classification of equivalence classes of cohereditary balanced pairs over arbitrary rings. We also present counterexamples to [15, Open questions 3 and 5]. Finally, we prove that the answers to [15, Open questions 2 and 4] are positive for coherent rings with weak global dimension at most one. [ABSTRACT FROM AUTHOR]

γ-Glutamyltranspeptidase (GGT) is an ectoenzyme anchored on the surface of the cell membrane, and it is closely associated with many diseases. Abnormal expression (>36 U/L) of GGT is involved in the progression of tumors and can act as a biomarker for tumor diagnosis. Here, we presented a series of GGT-activatable fluorescent probes, the P1, the P2 and the P3. By investigating the in vitro properties of the probes, P3 demonstrated the most sensitivity and better water solubility, which benefited from the introduction of the self-elimination moiety of p-aminobenzyl alcohol and the propanesulfonic acid moiety. Importantly, P3 was able to clearly delineate tumor boundaries in live tumor-bearing mice and clinical human liver tissue specimens by spraying in situ, which facilitated accurate resection of tumors under fluorescence guidance. The proposed enzyme-activated fluorescent probe has potential as a surgical resection tool in image-guided surgery. GGT-activatable fluorescent probe P3 was designed to clearly delineate tumor.boundaries via spraying in situ [Display omitted] • A series of near-infrared fluorescent probes responsive to GGT were synthesized. • Overexpression of GGT in cells has been successfully monitored by the probe P3. • The P3 was applied to discriminate cancer tissues from normal tissues accurately. • The P3 could be employed as a visual tool in image-guided tumor resection. [ABSTRACT FROM AUTHOR]

[Display omitted] • The grain size and major element composition in sedimentary sequences of the Yellow River Basin are presented. • The provenance, transport dynamics and sedimentary characteristics of sediments of the Yellow River is disclosed. • The processes and geomorphological effects of aeolian-fluvial interactions in the Yellow River Basin are identified. • The intensity of aeolian-fluvial interactions is related to sediment erosion and transport. Understanding environmental changes requires the characterization of potential interactions between aeolian and fluvial systems. This study aimed to identify the sedimentary characteristics, provenance, and transport of sediments of the Yellow River Basin, as well as the processes and geomorphological effects of aeolian-fluvial interactions using end-member modelling analysis (EMMA), multidimensional scaling (MDS), and principal component analysis (PCA). Samples (n = 107) collected from sedimentary sequences in the source area, upper, middle, and lower reaches were analyzed for grain size and major element contents. The results showed that sediments in the source area of the Yellow River mainly originated from the Tibetan Plateau, whereas the input of materials from the Chinese Loess Plateau (CLP) gradually increased from the upper to lower reaches. The sediment transport was jointly controlled by simultaneous or alternating aeolian and fluvial processes. Asynchronism in aeolian activity and rainfall and the non-uniformity of runoff and sediment sources resulted in a concentration of aeolian-fluvial interactions in the river reaches traversing through the deserts and CLP. Fluvial sediments in the upper reaches consisted of wash loads deposited in slow-moving water, whereas rapid replenishment of sediment from the CLP in the middle reaches increased sediment transport capacity, thereby enhancing the uniformity of sedimentary characteristics from the upper to lower reaches. Moreover, numerous gullies in the CLP resulted in increased intensities of aeolian-fluvial interactions, thereby accelerating severe sedimentation in the lower reaches. This study can act as a reference for paleoclimatic reconstruction and for soil and water conservation in large-scale watersheds across a range of climatic zones. [ABSTRACT FROM AUTHOR]

[Display omitted] • · The spatial characteristics of grain size and elemental composition in surface sediment of the Yellow River are investigated. • · The weathering nature, recycling characteristics and rock compositions are identified. • · The influence of climate condition and tectonic setting on erosion, weathering, and sedimentary recycling is elucidated. • · The provenance of surface sediment of the Yellow River is disclosed. Geochemical investigations of fluvial sediment help understand the provenance of sediment and surface processes taking place on the Earth at the watershed scale. This study is aimed at identifying the weathering and sedimentary recycling of the surface sediment of the Yellow River using the Chemical Index of Alteration (CIA), Weathering Index of Parker (WIP), Index of Compositional Variability (ICV), Mafic-Felsic-Weathering (MFW) ternary diagram, and Al-Ti-Zr ternary diagram. Source rocks compositions were clarified using Al 2 O 3 -CaO⁎+Na 2 O-K 2 O (A-CN-K), MFW, discriminant function, and Cr/V vs Y/Ni diagrams. The results demonstrated that the surface sediment of the Yellow River has experienced an overall low intensity of weathering and recycling. However, significant differences were observed in the characteristics of weathering and recycling among the upper, middle, and lower reaches, which is in turn associated with the differences in climatic conditions and tectonic settings. Source rocks manifested a typically mixed type composition, including felsic igneous rocks, intermediate igneous rocks, quartzose sedimentary rocks, and mafic components. Moreover, the sediment in the source area of the Yellow River may have originated from the clastics produced by the abrading of mountain glaciers. Sediment in the area in which the Yellow River flows through the Chinese Loess Plateau primarily originates from loess in the desert in Northwestern China. Sediment in the lower reaches does not only include the sorted sediment flowing down from the upper and middle reaches, but also that imported from regional rivers. This study can furnish a sound scientific basis for the reconstruction of the paleoclimatic and paleoenvironmental changes that affected large watersheds in arid and semi-arid areas. [ABSTRACT FROM AUTHOR]

[Display omitted] • The spatial distribution of heavy metals in surface sediments of the Yellow River mainstream are investigated. • The contamination degree, ecological risk, and source of heavy metals are explored. • The applicability of risk assessment indices of heavy metals in sediments is elucidated. • The reliability of multivariate statistical analyses for source identification of heavy metals is confirmed. Heavy metals in river sediments pose major threats to aquatic ecological environments and public health. This study investigated the characteristics, sources, and risks of heavy metals in surface sediments from the mainstream of the Yellow River. The grain size, loss on ignition (LOI), and content of Mn, Zn, V, Ni, Pb, and Cr in 61 samples were measured. The contamination level was evaluated using six indices, namely sediment quality guidelines (SQGs), contamination factor (C f), geo-accumulation index (I geo), modified degree of contamination (mC d), potential ecological risk index (RI), and pollution load index (PLI), and their spatial distribution was determined through Kriging interpolation. The sources of heavy metals were defined using multivariate statistical analyses, namely Pearson's correlation analysis (P'CA), principal component analysis (PCA), and cluster analysis (CA). The results show that Pb has the highest ecological risk, followed by Cr, Ni, and V, whereas Mn and Zn pose no risk. Mn and Zn mainly originate from natural processes, while Cr from anthropogenic process. V, Pb, and Ni are most likely from mixed sources. The ecological risk of heavy metals increases significantly when the Yellow River passes through the Loess Plateau. Furthermore, compared with SQGs and C f , the assessments of heavy metal contamination by I geo , RI, mC d and PLI are more objective and accurate. This study provides a powerful reference for contamination control and ecological security in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

• The prediction bias is mainly caused by data imbalance. • Curriculum coefficients are useful for mining hard samples and improving model generalization. • Teacher-student network ensures unbiased glaucoma diagnoses and evidence map predictions. • The evidence map output by the student network can provide more detailed information. Glaucoma is a disease that causes irreversible damage to the optic nerve. Research on accurate automatic screening algorithms is essential for the prevention and treatment of glaucoma. However, due to the imbalance of existing datasets and the existence of some hard samples that accompany other diverse and complex fundus diseases, the performance of current glaucoma screening algorithms is limited. In addition, the lack of interpretability also makes it difficult for the current algorithms to meet the requirements of clinical applications. In this paper, we propose a new multitask curriculum learning framework (MTCLF) for unbiased glaucoma screenings and visualizations of model decision-making areas. MTCLF is a teacher-student framework. The teacher network is used to generate the label evidence map. The student network can diagnose glaucoma and predict the evidence map at the same time with the well-designed dual-branch CNN structure and collaborative learning module. We design two curriculum coefficients θ and σ to guide the training process of the student network in the sample space so that the student network can adaptively balance the sample contribution, reduce the prediction bias and mine hard samples. The experimental results show that the accuracy, sensitivity, specificity, AUC and F 2 -score of MTCLF based on the LAG dataset for glaucoma diagnoses are 0.967, 0.961, 0.970, 0.996, and 0.958, respectively. These results are superior to those of the state-of-the-art methods. MTCLF not only achieves the best performance for unbiased glaucoma diagnoses but also generates a reliable evidence map to help clinicians explore fine lesion areas. [ABSTRACT FROM AUTHOR]

Osteoporosis, which manifests as reduced bone mass and deteriorated bone quality, is common in the elderly population. It is characterized by persistent elevation of macrophage-associated inflammation and active osteoclast bone resorption. Currently, the roles of intracellular metabolism in regulating these processes remain unclear. In this study, we initially performed bioinformatics analysis and observed a significant increase in the proportion of M1 macrophages in bone marrow with aging. Further metabolomics analysis demonstrated a notable reduction in the expression of carnitine metabolites in aged macrophages, while carnitine was not detected in osteoclasts. During the differentiation process, osteoclasts took up carnitine synthesized by macrophages to regulate their own activity. Mechanistically, carnitine enhanced the function of Nrf2 by inhibiting the Keap1-Nrf2 interaction, reducing the proteasome-dependent ubiquitination and degradation of Nrf2. In silico molecular ligand docking analysis of the interaction between carnitine and Keap1 showed that carnitine binds to Keap1 to stabilize Nrf2 and enhance its function. In this study, we found that the decrease in carnitine levels in aging macrophages causes overactivation of osteoclasts, ultimately leading to osteoporosis. A decrease in serum carnitine levels in patients with osteoporosis was found to have good diagnostic and predictive value. Moreover, supplementation with carnitine was shown to be effective in the treatment of osteoporosis. Carnitine activates Nrf2 in macrophage by inhibiting Keap1-Nrf2 protein-protein interaction (PPI), which further exerts anti-osteoporosis effects. In addition, carnitine serves a diagnostic indicator for osteoporosis. [Display omitted] [ABSTRACT FROM AUTHOR]

• The K sat of Zn-contaminated loess increases with time, while a decreasing trend for Cu-contaminated loess. • The hydrolysis of Zn2+ and the DDL effect are beneficial to the development of water passage. • The Cu 2 O precipitation in the Cu-contaminated loess is the main controlling factor for the weakening of pore connectivity. • The relationship among geochemical action, microstructure evolution, and seepage behavior of heavy-metal contaminated loess is revealed. Heavy metal contamination in soils can pose severe challenges to the safety of geotechnical engineering projects. Loess, which is widely distributed in Northwest China, is a preferred engineering construction material for anti-fouling barriers. Therefore, research on the influence of heavy metal ions on its seepage performance is urgently required. To obtain new insights into the seepage behavior of heavy metal-contaminated loess and its underlying geochemical mechanism, laboratory investigations were performed on the saturated hydraulic conductivity (K sat), leaching, and microstructural characteristics of loess contaminated with Cu2+ and Zn2+. The results indicate that the hydrolysis of Zn2+ creates an acidic environment, which promotes the dissolution of carbonate minerals in loess, enhances the leaching capacity, and leads to the quantitative transformation of small pores (2–8 μm) to mesopores (8–32 μm). Meanwhile, the alternating adsorption of Zn2+ and its diffuse double-layer effect compresses the diffusion layer, increasing the abundance of free water channels. Thus, the K sat of Zn-contaminated loess increases by 81.2% during the seepage period. As for Cu-contaminated loess, its seepage behavior is the opposite of that of Zn-contaminated loess, with a K sat decrease of nearly 50%. The primary factor controlling this phenomenon is the formation and enrichment of Cu 2 O in the lower part of the soil, which inhibits the enlargement of pores and reduces the effective connectivity of pores. The findings of this work provide insight into the seepage behavior of saturated loess under erosion by heavy metals and the underlying geochemical mechanism thereof. [ABSTRACT FROM AUTHOR]

In this paper, a marine dual fuel diesel engine fueled with the natural gas (NG: 60%, 70% and 80%) ignited by the biodiesel-diesel blended fuel (25%, 50% and 75% biodiesel by volume) was studied under different conditions. Based on the experiment, a computational fluid dynamics (CFD) model was established, and an improved chemical kinetic mechanism was developed to simulate the fuel spray process and combustion process. The ignition, combustion and emission characteristics of diesel engine fueled with different blended fuels were investigated under different load conditions. In addition, the temperature sensitivity of methane mole fraction with different NG energy fractions was analyzed at the 800 K and 1000 K. The results showed that the additions of NG and biodiesel in the blended fuel had a significant effect on the combustion and emission characteristics of the diesel engine. The starting of combustion (SOC) of the dual fuel engine lagged with the increases of NG and biodiesel content. The maximum enhancement of SOC reached 0.72°CA. The biggest influence on temperature was R122, which was the main reason for the shorter ignition delay during the combustion process. In all cases, NO x , CO and soot emissions decreased with increasing NG energy fraction. The maximum values of NO x , CO and soot emissions reached 1590 ppm, 461 ppm and 1.42 E−07 kg. Considering the combustion and emission characteristics of the engine, the best fuel blending ratio was EF80-B25. • A marine dual fuel diesel engine fueled with the natural gas ignited by the biodiesel-diesel blended fuel is investigated. • An improved 3D model and chemical kinetics mechanism are developed. • The optimum fuel mixture ratio of diesel engine is obtained. • The temperature sensitivity of methane mole fraction with different NG energy fractions is analyzed. [ABSTRACT FROM AUTHOR]

Extracellular ATP plays a key role in regulating plants stress responses. Here, we aimed to determine whether ATP can alleviate the glyphosate toxicity in maize seedlings under high temperature by regulating antioxidant responses. Foliar spraying with 100 μM glyphosate inhibited the growth of maize seedlings at room temperature (25 °C), leading to an increase in shikimic acid accumulation and oxidative stress (evaluated via lipid peroxidation, free proline, and H 2 O 2 content) in the leaves, all of which were further exacerbated by high temperature (35 °C). The growth inhibition and oxidative stress caused by glyphosate were both alleviated by exogenous ATP. Moreover, the glyphosate-induced antioxidant enzyme activity and antioxidant accumulation were attenuated by high temperature, while ATP treatment reversed this inhibitory effect. Similarly, qPCR data showed that the relative expression levels of antioxidant enzyme-related genes (CAT1 , GR1 , and γ-ECS) in maize leaves were upregulated by ATP before exposure to GLY. Moreover, high temperature-enhanced GLY residue accumulation in maize leaves was reduced by ATP. ATP-induced detoxification was attenuated through NADPH oxidase (NOX) inhibition. Higher NOX activities and O 2 •− production were noted in ATP-treated maize leaves compared to controls prior to GLY treatment, indicating that the extracellular ATP-induced alleviation of GLY toxicity was closely associated with NOX-dependent reactive oxygen species signalling. The current findings present a new approach for reducing herbicide toxicity in crops exposed to high temperatures. [Display omitted] • High temperatures aggravate glyphosate toxicity in maize seedlings. • ATP treatment alleviates glyphosate toxicity in maize seedlings. • ATP triggers the detoxification system in maize leaves. • ATP promotes glyphosate degradation in maize leaves. [ABSTRACT FROM AUTHOR]

• Dilated convolutions ensure better feature transfer and accurate classification that result in a sensitivity boost. • Dilated convolutions serve as the main constituents of decoder, encoder blocks and skip connections. • Dilated convolutions of different rates are more effective at capturing dynamically complex blood vessels. • Proposed Weighted multi-output fusion retrieves high fidelity vascular map by extracting critical features from each output block. Retinal image segmentation can help clinicians detect pathological disorders by studying changes in retinal blood vessels. This early detection can help prevent blindness and many other vision impairments. So far, several supervised and unsupervised methods have been proposed for the task of automatic blood vessel segmentation. However, the sensitivity and the robustness of these methods can be improved by correctly classifying more vessel pixels. We proposed an automatic, retinal blood vessel segmentation method based on the U-net architecture. This end-to-end framework utilizes preprocessing and a data augmentation pipeline for training. The architecture utilizes multiscale input and multioutput modules with improved skip connections and the correct use of dilated convolutions for effective feature extraction. In multiscale input, the input image is scaled down and concatenated with the output of convolutional blocks at different points in the encoder path to ensure the feature transfer of the original image. The multioutput module obtains upsampled outputs from each decoder block that are combined to obtain the final output. Skip paths connect each encoder block with the corresponding decoder block, and the whole architecture utilizes different dilation rates to improve the overall feature extraction. The proposed method achieved an accuracy: of 0.9680, 0.9694, and 0.9701; sensitivity of 0.8837, 0.8263, and 0.8713; and Intersection Over Union (IOU) of 0.8698, 0.7951, and 0.8184 with three publicly available datasets: DRIVE, STARE, and CHASE, respectively. An ablation study is performed to show the contribution of each proposed module and technique. The evaluation metrics revealed that the performance of the proposed method is higher than that of the original U-net and other U-net-based architectures, as well as many other state-of-the-art segmentation techniques, and that the proposed method is robust to noise. [ABSTRACT FROM AUTHOR]

Real-world point cloud objects pose great challenges in point cloud classification as objects acquired by scanning devices from real-world scans are often cluttered with background, and are partial due to occlusions as well as reconstruction errors. In the literature, few works tackle the problem of real-world point cloud classification while existing methods require fully point-level annotated training samples. However, large-scale dense point-level foreground–background labeling for real-world point clouds is a labor-intensive and time-consuming job. Leveraging two auxiliary modules, called semi-supervised point-level pseudo labels generation and noise-robust multi-task loss, the framework can integrate well with existing supervised point cloud classification network. A relational graph convolutional network on the local and non-local graph (PointRGCN) is first proposed to predict point-level foreground–background pseudo labels for each object with sparse ground-truth point-level foreground–background labels in training datasets. Then, a weakly supervised classification network, which combines with an auxiliary foreground–background segmentation branch, is employed to classify real-world point clouds. To cope with noise-containing point-level foreground–background labels generated above, a noise-robust multi-task loss is proposed to train the network accurately. Experimental results show that the performance of the proposed framework which is trained with only 1% point-level labels is comparable with many popular or state-of-the-art fully supervised methods. The source code will be available at http://zhiyongsu.github.io. [Display omitted] • A novel weakly supervised framework for real-world point cloud classification. • A local and non-local graph based relational graph convolutional network (PointRGCN). • A noise-robust multi-task loss combining classification and segmentation losses. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a chronic degenerative joint disease characterized by cartilage degeneration and subchondral bone remodelling. Currently, conservative treatment strategies cannot effectively alleviate the progression of OA. In this study, we used computer network analysis to show that Nitisinone (NTBC) is closely related to extracellular matrix degradation in OA and mainly interferes with the TNF-α signaling pathway. NTBC is an orphan drug used to treat hereditary type I tyrosinemia by altering phenylalanine/tyrosine metabolic flow. In this study, we found that NTBC effectively reduced chondrocyte inflammation and extracellular matrix degradation induced by TNF-α. Mechanistically, NTBC inhibited the cGAS/STING signaling pathway and reduced activation of the STING-dependent NF-κB pathway to alleviate inflammation. In addition, NTBC inhibited osteoclastogenesis and delayed the occurrence of subchondral bone remodelling. In mice with ACLT-induced osteoarthritis, intra-articular injection of NTBC significantly reduced cartilage degradation and subchondral bone remodelling. NTBC showed impressive therapeutic efficacy as a potential pharmaceutical intervention for the treatment of OA. [ABSTRACT FROM AUTHOR]

The problem of sugarcane top anti-tangling in the silage industry is based on mechanical properties, but there have been no studies on variables and models that can be used to predict them. The aim of this study was to examine how the physical properties, microstructure, and chemical composition of sugarcane top stems, leaves, and veins impact their mechanical properties and evaluate their role in entanglement within the silage industry. This study was carried out by using Grey Relational Analysis (GRA) and Multiple Linear Regression (MLR) to analyze the relationship and the influence level between the influencing factors (number of segments, diameter (width), segment distance, density, water content, hemicellulose content, cellulose content, and lignin content) and the mechanical property (tensile strength) of sugarcane tops. The results showed that the determination coefficients of tensile strength on stems, leaves, and veins were 0.9498, 0.9503, and 0.9457 by regression fitting, respectively. The RPD of the prediction model was greater than 3 and the RSEP was all less than 5%, which indicated that the model had a high prediction accuracy. It showed that the influencing factors and the mathematical model can be used to build the mechanical model of sugarcane tops, which was the basis for obtaining the data needed to study the anti-tangling of mechanical equipment. • Anti-tangling problems in the sugarcane top silage industry were analyzed. • Sugarcane tops were studied in a multi-scale and multi-faceted manner. • The factors rank influence the tensile properties of sugarcane tops were obtained. • The determination coefficients were 0.9498, 0.9503, and 0.9457, respectively. • The RPD of the prediction model was greater than 3 and the RSEP was less than 5%. [ABSTRACT FROM AUTHOR]

[Display omitted] • 3D porous graphene (3DPG) as reinforced additive was investigated in SBS/crumb rubber blend-modified asphalt. • 3DPG can significantly improve high and low-temperature performance and fatigue life of SBS/crumb rubber blend-modified asphalts. • The nanopores in 3DPG can effectively enhance the compatibility of SBS and crumb rubber in asphalt system by virtue of its unique amphiphilicity. • 3DPG as a new synergist presents a promising solution for the critical issue of wide adoption of crumb rubber modified asphalt for high-performance pavement. Styrene-butadiene-styrene (SBS)/crumb rubber (CR) blend-modified asphalt is a desirable binder for pavement engineering with both environmental and economic benefits. However, the inherent incompatibility of SBS and CR in asphalt is still a critical issue. Herein, 3D porous graphene (3DPG) with high surface area and rich micropores as reinforced additive was investigated in SBS/CR blend-modified asphalt for the first time. The experimental results demonstrate that incorporating 3DPG can effectively improve the compatibility of SBS and CR in asphalt and thus significantly enhance the high and low temperature performance and fatigue resistance of the modified asphalt, compared with that without 3DPG. Theoretical calculations further reveal that the nanopores in graphene can endow graphene with electrophilic property, providing a capability of absorbing nonpolar molecules in asphalt while the non-pore part in graphene can interact with polar molecules by conventional π − π stacking. The two forces within graphene can break the original colloidal structures of asphalt, which is conductive to the homogenous formation of SBS network and swelling of CR in asphalt, significantly promoting the pavement performance of the modified asphalt. This work presents the great potential of 3DPG as new additive to solve the inherent incompatibility of SBS/CR blend-modified asphalt for high-grade pavement engineering. [ABSTRACT FROM AUTHOR]

• The development of higher alcohols of modern automobile engines is listed. • The improvements of higher alcohols characteristic are discussed. • Optimization applications in diesel engine are investigated. • Improvement suggestions for performance enhancement of diesel engine are proposed. The application of oxygenated alternative fuels in diesel engines is an effective way to solve the energy crisis and environmental pollution. Higher alcohols (butanol and pentanol), as oxygenated and renewable fuels, are considered as new promising alternative fuels for diesel engine due to their good physicochemical properties and excellent combustion and emission characteristics in engines. The combustion is a complex process and has a significant impact on performance and emission characteristics of compression ignition (CI) engines. There are complicated relationships among CI engine, environment and fuel physicochemical properties, which interacts with each other. Therefore, it is important to investigate the synergistic effects of alternative fuels and their additives on CI engines. In recent years, the research on the advanced alcohols and its additives had made great progress. However, few people have reviewed the synergistic effect of higher alcohols and its additives on diesel engines. Therefore, this paper takes the combustion, performance and emission aspects of higher alcohols and its additives on the diesel engine as a starting point. Firstly, the physicochemical properties and preparations of higher alcohols are described, and their advantages are highlighted. Then, the effects of higher alcohols and its additives on the combustion, performance and emission characteristics of CI engines are summarized in terms of neat fuel, dual-fuel injection and multi-fuel blends, exhaust gas recirculation (EGR), injection strategy and advanced combustion mode. Finally, some important conclusions and discussions on the future development and experimental research direction are put forward, which will be helpful for the research on the use of higher alcohol in CI engines. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-crosslinked Flexible CNC/PVAGMA/TA nanocomposite hydrogel fibers was prepared. • The CNC/PVAGMA/TA nanocomposite hydrogels exhibited excellent tensile strengths as well as high-water content of 70 %. • The hydrogel fibers can be easily knitted into various complex geometries or integral textiles. Hydrogel fibers with excellent mechanical properties are requested for biomedical applications, especially for flexible and wearable devices. However, it remains a challenge to fabricate hydrogel fibers with both enough strength and high water content. Herein, we prepare cellulose nanocrystal/polyvinyl alcohol nanocomposite hydrogels by rapid covalent crosslinking and the subsequent strong hydrogen bonding interaction derived from tannic acid. The multi-crosslinked skeletal structure endows the hydrogels with excellent tensile strengths as well as high water content, compared to the polyvinyl alcohol-glycidylmethacrylate hydrogels. Notably, P10C5T15 hydrogel can lift loads to 4.375 kg, which is approximately 2353 times its weight. Subsequently, the flexible and mechanically stable hydrogel fibers are fabricated with a tensile strength of 7.3 MPa and a breaking elongation of 123.8 %. Furthermore, the fabricated hydrogel fibers can be easily knitted into various complex geometries or integral textiles, suggesting their great potential for woven smart devices. [ABSTRACT FROM AUTHOR]

• The K sat characteristics of remolded loess under CaCl 2 solutions are presented. • The response of EDL effect to CaCl 2 concentrations is evaluated. • Microstructure evolution of loess induced by CaCl 2 solutions is revealed. • The mechanism of K sat change in seepage process is disclosed. • The findings in this study have broad application value to other soils. Loess has been widely used in site remediation engineering projects in the Chinese Loess Plateau. With the interaction between CaCl 2 solution and cutoff wall, how does its permeability change, is the response pattern consistent for different concentrations, and what is the mechanism? To address this series of problems, the effects of CaCl 2 solutions of varying concentrations on the permeability of remolded loess were investigated by saturated permeability test, and the mechanisms underlying these effects were explored through free swelling ratio, zeta potential, thermogravimetric analysis (TGA), grain-size tests, as well as SEM and MIP tests. The results indicate that K sat values of the samples permeated with both deionized water (DW) and 0.001 mol/L CaCl 2 solution increase with time, with a greater increase observed in the latter. This is mainly due to that the electrical double layer (EDL) effect induced by Ca2+, as the dominant factor, controls particle flocculation and pore structure development. Under seepage of a 0.010 mol/L CaCl 2 solution, the EDL effect plays a dominant role during the initial stage. However, chemical weathering causes the disintegration of loess particles, and the dissolution of carbonates is inhibited by Ca2+. These are not conducive to pore development; thus, K sat first increases and then decreases significantly. The K sat of samples permeated with a 0.005 mol/L CaCl 2 solution first increases and then stabilizes, which represents the transitional stage of the two aforementioned change trends. This is mainly because the effective pores are increased by leaching and cation exchange, and then the porosity is in dynamic equilibrium under the combined action of the EDL effect, geochemical action, and microstructural evolution. Thus, the saturated hydraulic conductivity (K sat) of remolded loess is sensitive to the concentrations of CaCl 2 solutions, with different response modes. [ABSTRACT FROM AUTHOR]

Point cloud denoising is a crucial and fundamental step in geometry processing, which has achieved significant progress in the last two decades. Denoising real-world noisy point clouds is a very challenging problem since it is hard to describe the complex real-world noise by simple distributions such as Gaussian distribution. Furthermore, existing methods may suffer from performance degradation when dealing with real-world noisy point clouds with complex structures, which contain not only sharp features (sharp edges, sharp corners, etc.) but also smooth features, fine features, etc. To solve the above-mentioned problems, we propose a novel structure-aware denoising approach by exploiting the prior information in both external clean point clouds and the given noisy point cloud. We first group nonlocal self-similarity (NSS) patches from a set of external clean point clouds. Then, we employ the Gaussian Mixture Model (GMM) learning algorithm to learn external NSS priors over patch groups. Next, the internal priors are learned from the given noisy point cloud in the same way to refine the prior model. We integrate both the learned external and internal priors into a set of orthogonal dictionaries to efficiently estimate point normals. Finally, we propose a feature-aware point updating method through adaptive neighborhood selection to reposition points to match the estimated normals. Extensive experiments show that our approach achieves favorable comprehensive performance compared with many popular or state-of-the-art methods in terms of both objective and visual perception. The source code can be found at https://zhiyongsu.github.io. • A structure-aware denoising method is proposed for real-world noisy point clouds. • The proposed method jointly learns external and internal priors for denoising. • A feature-aware point updating method is proposed. [ABSTRACT FROM AUTHOR]