TDGVRPSTW of Fresh Agricultural Products Distribution: Considering Both Economic Cost and Environmental Cost

The time-dependent vehicle routing problem of time windows of fresh agricultural products distribution have been studied by considering both economic cost and environmental cost. A calculation method for road travel time across time periods is designed in this study. A freshness measure function of agricultural products and a measure function of carbon emission rate are employed by considering time-varying vehicle speeds, fuel consumptions, carbon emissions, perishable agricultural products, customers’ time windows, and minimum freshness. A time-dependent green vehicle routing problem with soft time windows (TDGVRPSTW) model is formulated. The object of the TDGVRPSTW model is to minimize the sum of economic cost and environmental cost. According to the characteristics of the model, a new variable neighborhood adaptive genetic algorithm is designed, which integrates the global search ability of the genetic algorithm and the local search ability of the variable neighborhood descent algorithm. Finally, the experimental data show that the proposed approaches effectively avoid traffic congestions, reduce total distribution costs, and promote energy conservation and emission reduction.

Challenges of Rabies Serology: Defining Context of Interpretation

The case fatality rate of rabies, nearly 100%, is one of the most unique characteristic of this ancient virus infection. The crucial role rabies virus neutralizing antibody plays in protection is both well established and explanation of why rabies serology is important. Various laboratory methods can and have been used but serum neutralization methods have long been the gold standard due to the ability to measure function (neutralization), however these methods can be difficult to perform for several reasons. Assays such as enzyme linked absorbance assays (ELISA), indirect fluorescence antibody (IFA) and more recently lateral flow methods are in use. Interpretation of results can be problematic, not only between methods but also due to modifications of the same method that can lead to misinterpretations. A common assumption in review of laboratory test results is that different methods for the same component produce comparable results under all conditions or circumstances. Assumptions and misinterpretations provide the potential for detrimental decisions, ranging from regulatory to clinically related, and most importantly what ‘level’ is protective. Review of the common challenges in performance and interpretation of rabies serology and specific examples illuminate critical issues to consider when reviewing and applying results of rabies serological testing.

The Efficient Proportional Myerson Values for Hypergraph Games

This study deals with a class of efficient extensions of Myerson value for games with hypergraph communication situations in which the surplus is allocated proportionally. We introduce w -fairness of surplus and provide axiomatic characterizations of the new allocation rule. Furthermore, we give an example of research fund distribution amongst researchers, compare the numerical results with several values, and realize other efficient extensions of Myerson value can be obtained depending on the different measure function w on the hypergraph.

A Modified PRP-CG Type Derivative-Free Algorithm with Optimal Choices for Solving Large-Scale Nonlinear Symmetric Equations

Inspired by the large number of applications for symmetric nonlinear equations, this article will suggest two optimal choices for the modified Polak–Ribiére–Polyak (PRP) conjugate gradient (CG) method by minimizing the measure function of the search direction matrix and combining the proposed direction with the default Newton direction. In addition, the corresponding PRP parameters are incorporated with the Li and Fukushima approximate gradient to propose two robust CG-type algorithms for finding solutions for large-scale systems of symmetric nonlinear equations. We have also demonstrated the global convergence of the suggested algorithms using some classical assumptions. Finally, we demonstrated the numerical advantages of the proposed algorithms compared to some of the existing methods for nonlinear symmetric equations.

Asymmetric Distribution Measure for Few-shot Learning

The core idea of metric-based few-shot image classification is to directly measure the relations between query images and support classes to learn transferable feature embeddings. Previous work mainly focuses on image-level feature representations, which actually cannot effectively estimate a class's distribution due to the scarcity of samples. Some recent work shows that local descriptor based representations can achieve richer representations than image-level based representations. However, such works are still based on a less effective instance-level metric, especially a symmetric metric, to measure the relation between a query image and a support class. Given the natural asymmetric relation between a query image and a support class, we argue that an asymmetric measure is more suitable for metric-based few-shot learning. To that end, we propose a novel Asymmetric Distribution Measure (ADM) network for few-shot learning by calculating a joint local and global asymmetric measure between two multivariate local distributions of a query and a class. Moreover, a task-aware Contrastive Measure Strategy (CMS) is proposed to further enhance the measure function. On popular miniImageNet and tieredImageNet, ADM can achieve the state-of-the-art results, validating our innovative design of asymmetric distribution measures for few-shot learning. The source code can be downloaded from https://github.com/WenbinLee/ADM.git.

Measuring stuff and process

This chapter begins the book’s survey of non-canonical comparatives, and suggests a degree-based interpretation of the expression “much” which occurs implicitly as a morphosyntactic part of “more”, and explicitly in phrases like “as much” and “too much”. Focusing on comparatives targeting mass nouns like “mud” and atelic verb phrases like “run (in the park)”, a primary goal of this analysis is to capture both the variability and constraints (especially a hypothesized “monotonicity constraint”) on measure function selection in such cases. In line with the central thesis of the book, this chapter emphasizes the role that the order-theoretic properties (when present) of a predicate plays in fixing the available dimension(s) for comparison in a given nominal or verbal comparative. The success of this analysis suggests considering whether it can apply to the canonical comparatives, which is explored in the subsequent chapter.