From Canteen Food to Daily Meals: Generalizing Food Recognition to More Practical Scenarios

The precise recognition of food categories plays a pivotal role for intelligent health management, attracting significant research attention in recent years. Prominent benchmarks, such as Food-101 and VIREO Food-172, provide abundant food image resources that catalyze the prosperity of research in this field. Nevertheless, these datasets are well-curated from canteen scenarios and thus deviate from food appearances in daily life. This discrepancy poses great challenges in effectively transferring classifiers trained on these canteen datasets to broader daily-life scenarios encountered by humans. Toward this end, we present two new benchmarks, namely DailyFood-172 and DailyFood-16, specifically designed to curate food images from everyday meals. These two datasets are used to evaluate the transferability of approaches from the well-curated food image domain to the everyday-life food image domain. In addition, we also propose a simple yet effective baseline method named Multi-Cluster Reference Learning (MCRL) to tackle the aforementioned domain gap. MCRL is motivated by the observation that food images in daily-life scenarios exhibit greater intra-class appearance variance compared with those in well-curated benchmarks. Notably, MCRL can be seamlessly coupled with existing approaches, yielding non-trivial performance enhancements. We hope our new benchmarks can inspire the community to explore the transferability of food recognition models trained on well-curated datasets toward practical real-life applications

Preconditioning with Physiological Levels of Ethanol Protect Kidney against Ischemia/Reperfusion Injury by Modulating Oxidative Stress

Oxidative stress due to excessive production of reactive oxygen species (ROS) and subsequent lipid peroxidation plays a critical role in renal ischemia/reperfusion (IR) injury. The purpose of current study is to demonstrate the effect of antecedent ethanol exposure on IR-induced renal injury by modulation of oxidative stress.Bilateral renal warm IR was induced in male C57BL/6 mice after ethanol or saline administration. Blood ethanol concentration, kidney function, histological damage, inflammatory infiltration, cytokine production, oxidative stress, antioxidant capacity and Aldehyde dehydrogenase (ALDH) enzymatic activity were assessed to evaluate the impact of antecedent ethanol exposure on IR-induced renal injury.After bilateral kidney ischemia, mice preconditioned with physiological levels of ethanol displayed significantly preserved renal function along with less histological tubular damage as manifested by the reduced inflammatory infiltration and cytokine production. Mechanistic studies revealed that precondition of mice with physiological levels of ethanol 3 h before IR induction enhanced antioxidant capacity characterized by significantly higher superoxidase dismutase (SOD) activities. Our studies further demonstrated that ethanol pretreatment specifically increased ALDH2 activity, which then suppressed lipid peroxidation by promoting the detoxification of Malondialdehyde (MDA) and 4-hydroxynonenal (HNE).Our results provide first line of evidence indicating that antecedent ethanol exposure can provide protection for kidneys against IR-induced injury by enhancing antioxidant capacity and preventing lipid peroxidation. Therefore, ethanol precondition and ectopic ALDH2 activation could be potential therapeutic approaches to prevent renal IR injury relevant to various clinical conditions

Multiperiod supply chain network equilibrium model with electronic commerce and multicriteria decision-making

In this paper, we develop a supply chain network equilibrium model in which electronic commerce in the presence of both B2B (business-to-business) and B2C (business-to-consumer) transactions, multiperiod decision-making and multicriteria decision-making are integrated. The model consists of three tiers of decision-makers (manufacturers, retailers and consumers at demand markets) who compete within a tier but may cooperate between tiers. Both manufacturers and retailers are concerned with maximization of profit as well as minimization of risk, whereas consumers take both the prices charged by manufacturers and retailers, along with the corresponding costs of transacting, in making their consumption decisions. Increasing relationship levels are assumed to decrease costs of transacting as well as risk costs. Establishing and maintaining these relationship levels incur some costs that have to be borne by the various decision-makers. We study the interaction among different tiers of decision-makers, describe their multicriteria decision-making behavior and derive the optimality conditions as well as the equilibrium conditions which are then shown to satisfy a finite-dimensional variational inequality problem. We then establish qualitative properties of the equilibrium model under some reasonable assumptions and illustrate the model with several numerical examples

Linear quadratic optimal control via using dynamic compensator

The linear-quadratic (LQ) optimal problem based on dynamic compensation is considered for a general quadratic performance index in this paper. First, it is shown that there exists a dynamic compensator with a proper dynamic order such that the closed- loop system is asymptotically stable and its associated Lyapunov equation has a symmetric positive-definite solution. Then, the quadratic performance index is derived to be a simple expression related to the symmetric positive-definite solution and the initial value of the closed-loop system. In order to solve the optimal control problem for the system, the proposed Lyapunov equation is transformed into a Bilinear Matrix Inequality (BMI) and a corresponding path-following algorithm to minimize the quadratic performance index is proposed in which an optimal dynamic compensator can be obtained. Finally, several numerical examples are provided to demonstrate the effectiveness and feasibility of the proposed approach

Canonical duality theory for solving non-monotone variational inequality problems

This paper presents a canonical dual approach for solving a class of non-monotone variational inequality problems. It shows that by using the canonical dual transformation, these challenging problems can be reformulated as a canonical dual problem, which is equivalent to the primal problems in the sense that they have the same set of KKT points. Existence theorem for global optimal solutions is obtained. Based on the canonical duality theory, this dual problem can be solved via well-developed convex programming methods. Applications are illustrated with several examples

The nonlinear complementarity model of industrial symbiosis network equilibrium problem

In this paper, we propose an industrial symbiosis network equilibrium model by using nonlinear complementarity theory. The industrial symbiosis network consists of industrial producers, industrial consumers, industrial decomposers and demand markets, which imitates natural ecosystem by means of exchanging by-products and recycling useful materials exacted from wastes. The industrial producers and industrial consumers are assumed to be concerned with maximization of economic profits as well as minimization of emissions. We describe the optimizing behavior, derive optimality conditions of the various decision-makers along with respective economic interpretations and establish the nonlinear complementarity model in accordance with the industrial symbiosis network equilibrium conditions. Based on the existence proof of the corresponding nonlinear complementarity model under reasonable assumptions, two groups of numerical examples are given to illustrate the rationality as well as the effectiveness of the model