Almost Optimal Algorithms for Token Collision in Anonymous Networks

In distributed systems, situations often arise where some nodes each holds a collection of tokens, and all nodes collectively need to determine whether all tokens are distinct. For example, if each token represents a logged-in user, the problem corresponds to checking whether there are duplicate logins. Similarly, if each token represents a data object or a timestamp, the problem corresponds to checking whether there are conflicting operations in distributed databases. In distributed computing theory, unique identifiers generation is also related to this problem: each node generates one token, which is its identifier, then a verification phase is needed to ensure that all identifiers are unique. In this paper, we formalize and initiate the study of token collision. In this problem, a collection of k tokens, each represented by some length-L bit string, are distributed to n nodes of an anonymous CONGEST network in an arbitrary manner. The nodes need to determine whether there are tokens with an identical value. We present near optimal deterministic algorithms for the token collision problem with Õ(D+k⋅L/log n) round complexity, where D denotes the network diameter. Besides high efficiency, the prior knowledge required by our algorithms is also limited. For completeness, we further present a near optimal randomized algorithm for token collision

Multiscale Superpixel Structured Difference Graph Convolutional Network for VL Representation

Within the multimodal field, the key to integrating vision and language lies in establishing a good alignment strategy. Recently, benefiting from the success of self-supervised learning, significant progress has been made in multimodal semantic representation based on pre-trained models for vision and language. However, there is still room for improvement in visual semantic representation. The lack of spatial semantic coherence and vulnerability to noise makes it challenging for current pixel or patch-based methods to accurately extract complex scene boundaries. To this end, this paper develops superpixel as a comprehensive compact representation of learnable image data, which effectively reduces the number of visual primitives for subsequent processing by clustering perceptually similar pixels. To mine more precise topological relations, we propose a Multiscale Difference Graph Convolutional Network (MDGCN). It parses the entire image as a fine-to-coarse hierarchical structure of constituent visual patterns, and captures multiscale features by progressively merging adjacent superpixels as graph nodes. Moreover, we predict the differences between adjacent nodes through the graph structure, facilitating key information aggregation of graph nodes to reason actual semantic relations. Afterward, we design a multi-level fusion rule in a bottom-up manner to avoid understanding deviation by learning complementary spatial information at different regional scales. Our proposed method can be well applied to multiple downstream task learning. Extensive experiments demonstrate that our method is competitive with other state-of-the-art methods in visual reasoning. Our code will be released upon publication

Almost Optimal Algorithms for Token Collision in Anonymous Networks

In distributed systems, situations often arise where some nodes each holds a collection of tokens, and all nodes collectively need to determine whether all tokens are distinct. For example, if each token represents a logged-in user, the problem corresponds to checking whether there are duplicate logins. Similarly, if each token represents a data object or a timestamp, the problem corresponds to checking whether there are conflicting operations in distributed databases. In distributed computing theory, unique identifiers generation is also related to this problem: each node generates one token, which is its identifier, then a verification phase is needed to ensure all identifiers are unique. In this paper, we formalize and initiate the study of token collision. In this problem, a collection of $k$ tokens, each represented by some length-$L$ bit string, are distributed to $n$ nodes of an anonymous CONGEST network in an arbitrary manner. The nodes need to determine whether there are tokens with an identical value. We present near optimal deterministic algorithms for the token collision problem with $\tilde{O}(D+k\cdot L/\log{n})$ round complexity, where $D$ denotes the network diameter. Besides high efficiency, the prior knowledge required by our algorithms is also limited. For completeness, we further present a near optimal randomized algorithm for token collision

Molecular dynamics studies of interfacial crystallization behaviors in polyethylene/carbon nanotube composites

The interfacial crystallization of polyethylene can be greatly affected by the SWCNT surface topography and pre-orientation of the polyethylene chains.</p

Numerical Simulation and Multi-Objective Parameter Optimization of Inconel718 Coating Laser Cladding

Aiming at the difficulty of temperature control in the laser cladding process of high-temperature nickel-based alloys, the influence of cladding parameters on the temperature of the molten pool, and the quality of the cladding layer were explored. Firstly, through the analysis of the finite element method, the Inconel718 single-pass cladding model was established on the surface of 45 steel by using parametric language and life–death element technology, the influence of different laser power and scanning speed on the temperature of the molten pool center was explored, and reasonable process parameters scope were selected. Secondly, taking the cladding parameters as independent variables, and taking the dilution rate and forming coefficient of the cladding layer as the response variables, using BBD (Box–Behnken Design) to design experiments the response surface analysis method was used to establish the regression prediction model of the cladding process parameters and response indicators, and the genetic algorithm was used to carry out multi-objective optimization to obtain the best results. The optimal parameter combination is a laser power of 1756 W, a scanning speed of 19.43 mm/s, and a powder feeding rate of 19.878 g/min. Finally, a multi-pass lap joint experiment was carried out with the optimal parameters, and it was found that the cladding layer has a dense and fine structure and a good metallurgical bond with the matrix, which can effectively guide the actual production.</jats:p

Accelerating the Improvement of Human Well-Being in China through Economic Growth and Policy Adjustment

Human well-being in many countries lags behind the gross domestic product (GDP) due to the rapid changes in the socio-economic environment that have occurred for decades. However, the mechanisms behind this complex phenomenon are still unclear. This study revealed the changes in human well-being in China from 1995 to 2017 by revising the genuine progress indicator (GPI) at the national level and further quantified the contribution of interfering factors that have driven the increase in the GPI. The results indicated that: (1) The per capita GPI of China showed an increasing trend with an annual growth rate of 12.43%. The changes in the GPI followed the same pattern as economic development, rather than presenting the phenomenon of economic growth combined with a decline in welfare that has been recorded in some countries and regions. (2) The increase in human well-being was mainly driven by economic growth, but it was most sensitive to social factors. (3) Increasing income inequality and the cost of lost leisure time contributed obvious negative impacts (24.69% and 23.35%, respectively) to the per capita GPI. However, the increase in personal consumption expenditures, the value of domestic labor, ecosystem service value, and net capital growth accelerated the rise in the GPI, with positive contribution rates of 30.69%, 23%, 20.54%, and 20.02%, respectively. (4) The continuous increase in economic investment and the strengthening of social management due to policy adjustments completely counteracted the negative impacts on human well-being, thus leading to a great increase in the per capita GPI. Such insights could provide theoretical support for decision making and policy implementation to improve global human well-being