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Cosserat continuum models are motivated by modeling size effects in materials with micro-structure. While elastic Cosserat continuum models can reproduce size effects in deformation stiffness, inelastic models are often used to capture localization and post failure behavior of materials. In application of inelastic Cosserat models, parameter determination is a difficult issue not fully addressed. The purpose of this paper is to discuss parameter-related characteristic lengths in Cosserat continuum modeling of granular materials.

Based on a Cosserat continuum extension of a hypoplastic model for granular media, interpretation of additional parameters are sought through analysis of simple one-dimensional shear. Governing equations are obtained, respectively, for small strain shear formation and for stead flow state in localized zone.

Two characteristic lengths are obtained analytically for granular materials: one governs the size effect near boundaries in shear deformation, the other scales the thickness of shear band in failure. While both characteristic lengths are proportional to the micro-structure length (the mean grain diameter), the former is related to the micro-stiffness parameter, and the latter depends on the micro-strength parameter. The results reveal a connection between size effects, the micro-structure length and the material properties. The work also provides a new perspective to inelastic Cosserat continuum models, as well as a possible way for determination micro-deformation and strength parameters.

The results reveal a connection between size effects, the micro-structure length and the material properties. The work provides a new perspective and an interpretation to the micro-deformation and strength parameters of inelastic Cosserat continuum models, as well as a possible way for determination of these parameters.

The purpose of this paper is to explore the possibility of an enhanced continuous liquid interface production (CLIP) with a porous track-etched membrane as the oxygen-permeable window, which is prepared by irradiating polyethylene terephthalate membranes with accelerated heavy ions.

Experimental approaches are carried out to characterize printing parameters of resins with different photo-initiator concentrations by a photo-polymerization matrix, to experimentally observe and theoretically fit the oxygen inhibition layer thickness during printing under conditions of pure oxygen and air, respectively, and to demonstrate the enhanced CLIP processes by using pure oxygen and air, respectively.

Owing to the high permeability of track-etched membrane, CLIP process is demonstrated with printing speed up to 800 mm/h in the condition of pure oxygen, which matches well with the theoretically predicted maximum printing speed at difference light expose. Making a trade-off between printing speed and surface quality, maximum printing speed of 470 mm/h is also obtained even using air. As the oxygen inhibition layer created by air is thinner than that by pure oxygen, maximum speed cannot be simply increased by intensifying the light exposure as the case with pure oxygen.

CLIP process is capable of building objects continuously instead of the traditional layer-by-layer manner, which enables tens of times improvement in printing speed. This work presents an enhanced CLIP process by first using a porous track-etched membrane to serve as the oxygen permeable window, in which a record printing speed up to 800 mm/h using pure oxygen is demonstrated. Owing to the high permeability of track-etched membrane, continuous process at a speed of 470 mm/h is also achieved even using air instead of pure oxygen, which is of significance for a compact robust high-speed 3D printer.

Effective farmer participation in the rural land consolidation process has become increasingly important because it improves results in rural land consolidation and land use efficiency. The purpose of this paper is to examine the mechanism of farmers’ effective participation in Chinese rural land consolidation.

The authors empirically assess farmers’ effective participation in the rural land consolidation process in ten counties of China’s Hubei province. Focusing on an effective decision-making model, the authors comprehensively evaluated farmer participation using surveys that incorporated an index system and analyzed survey results using a structural equation model to examine factors that influenced farmer’s effective participation.

The results of the study suggest that the correlations between farmers’ effective participation and the impacting factors the authors proposed were particularly strong. In addition, participation ability, participation opportunity and participation incentive are strongly associated with effective farmer participation. Thus, the authors highlight that incentives should be provided to encourage farmers’ effective participation in rural land consolidation.

Because of the chosen approach and the set of the research object, the geographic context of the empirical survey work was limited; furthermore, the authors only studied the influencing factors at the individual level, leaving the interaction effects between governmental factors and farmer individual factors inadequately explained.

Despite those limitations, these results serve as an important reference for government agencies and stakeholder groups in rural land consolidation decision making.

Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises.

Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users.

Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different models such as random forest, fully-connected layer network, SVM and XGBOST, and the proposed method is comprehensively evaluated. Experimental results show that in the best case, our method can improve the F1-score of traditional models by 55.37%.

This paper investigates the relative importance of static information and dynamic behavior characteristics of users in predicting underground industry users, and whether the absence of features of these categories affects the prediction results. This investigation can go a long way in aiding further research on this subject and found the features which improved the accuracy of predicting underground industry users.