Capacity Allocation and Pricing of High Occupancy Toll Lane Systems with Heterogeneous Travelers

In this article, we study the optimal design of High Occupancy Toll (HOT) lanes. In our setup, the traffic authority determines the road capacity allocation between HOT lanes and ordinary lanes, as well as the toll price charged for travelers who use the HOT lanes but do not meet the high-occupancy eligibility criteria. We build a game-theoretic model to analyze the decisions made by travelers with heterogeneous values of time and carpool disutilities, who choose between paying or forming carpools to take the HOT lanes, or taking the ordinary lanes. Travelers' payoffs depend on the congestion cost of the lane that they take, the payment and the carpool disutilities. We provide a complete characterization of travelers' equilibrium strategies and resulting travel times for any capacity allocation and toll price. We also calibrate our model on the California Interstate highway 880 and compute the optimal capacity allocation and toll design

Challenges in Representation Learning: A report on three machine learning contests

The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions.Comment: 8 pages, 2 figure

Constitutive modeling for the flow stress behaviors of alloys based on variable order fractional derivatives

During hot working, alloys may experience three kinds of flow stress behaviors, including strain hardening, strain softening, or steady flow, because of the competition of work hardening and thermal softening. Modelling the flow stress behaviors plays an essential role in understanding the mechanical properties of alloys. In this paper, the variable order fractional model is provided to describe the flow stress behaviors of alloys. The variation of the fractional order between 0 and 1 can reflect the mechanical property changing between solids and fluids. By assuming that the fractional order varies linearly with time, the proposed model can describe both the strain softening and strain hardening behaviors of alloys. The model fitting results are compared to the experimental data of A356 alloy for strain softening and Cu-Cr-Mg alloy for strain hardening under different temperatures and strain rates. It is validated that the variable order fractional model can accurately describe the flow stress behaviors of alloys. Furthermore, the rule of the variable order is also discussed to analyze its overall values and the changes before and after the yield point. It is concluded that the variation of the fractional order can intuitively reveal the changes in mechanical properties in the flow stress behaviors of alloys, including both strain softening and strain hardening

Recent Advances in Ionic Liquids—MOF Hybrid Electrolytes for Solid-State Electrolyte of Lithium Battery

Li-ion batteries are currently considered promising energy storage devices for the future. However, the use of liquid electrolytes poses certain challenges, including lithium dendrite penetration and flammable liquid leakage. Encouragingly, solid electrolytes endowed with high stability and safety appear to be a potential solution to these problems. Among them, ionic liquids (ILs) packed in metal organic frameworks (MOFs), known as ILs@MOFs, have emerged as a hybrid solid-state material that possesses high conductivity, low flammability, and strong mechanical stability. ILs@MOFs plays a crucial role in forming a continuous interfacial conduction network, as well as providing internal ion conduction pathways through the ionic liquid. Hence, ILs@MOFs can not only act as a suitable ionic conduct main body, but also be used as an active filler in composite polymer electrolytes (CPEs) to meet the demand for higher conductivity and lower cost. This review focuses on the characteristic properties and the ion transport mechanism behind ILs@MOFs, highlighting the main problems of its applications. Moreover, this review presents an introduction of the advantages and applications of Ils@MOFs as fillers and the improvement directions are also discussed. In the conclusion, the challenges and suggestions for the future improvement of ILs@MOFs hybrid electrolytes are also prospected. Overall, this review demonstrates the application potential of ILs@MOFs as a hybrid electrolyte material in energy storage systems

Protective effect of resveratrol against light-induced retinal degeneration in aged SAMP8 mice

Purpose The purpose of this study was to determine the protective effects of Resveratrol (RESV) on acute bright light-induced retinal degeneration in aged senescence accelerated mouse strain. Methods: Ten three-month-old male SAMP8 mice (prone to aging) were randomly assigned to two experimental dietary groups: one untreated group and one RESV treatment group (n=20 eyes for each group). After 30 days of treatment, mice were exposed to intense bright light. Ten male SAMR1 mice (resistant to aging) served as control (n=20 eyes). The protective effects of RESV administration on light-induced retinal degeneration in SAMP8 strain as well as the effect of bright light damage in the retinas of SAMP8 mice were analyzed by electroretinography (ERG), retinal histology, mRNA, protein and lipid profile. Results: 68%-85% of a-wave amplitude and 72%-92% of b-wave amplitude were persevered by RESV in SAMP8 mice that were exposed to light damage. Also, RESV preserved their photoreceptor nuclei. mRNA expression of neuroprotective factors leukemia inhibitory factor (LIF), brain derived neurotrophic factor (BDNF), oncostatin M (OSM), cardiotrophin 1(CT-1) and cardiotrophin-like cytokine (CLC) were up-regulated 28, 8, 7, 5 and 9-fold in SAMP8 mice after RESV treatment. In addition, RESV could suppress the NF-κB pathway by down-regulating the expression of pIκB. Light damage led to increase of saturated FA, monoenoic FA, n6 PUFA and n6/n3 ratio and decrease of Docosahexaenoic acid (DHA). There was no significant difference on DHA and the ratio of n6/n3-FA between the untreated and RESV treated SAMP8 mice. Conclusions: Collectively, our study provides evidence that RESV prevents light-induced retinal damage associated with aging

Optimal Design of Multimissile Formation Based on an Adaptive SA-PSO Algorithm

In an effort to maximize the combat effectiveness of multimissile groups, this paper proposes an adaptive simulated annealing–particle swarm optimization (SA-PSO) algorithm to enhance the design parameters of multimissile formations based on the concept of missile cooperative engagement. Firstly, considering actual battlefield circumstances, we establish an effectiveness evaluation index system for the cooperative engagement of missile formations based on the analytic hierarchy process (AHP). In doing so, we adopt a partial triangular fuzzy number method based on authoritative assessments by experts to ascertain the weight of each index. Then, considering given constraints on missile performance, by selecting the relative distances and angles of the leader and follower missiles as formation parameters, we design a fitness function corresponding to the established index system. Finally, we introduce an adaptive capability into the traditional particle swarm optimization (PSO) algorithm and propose an adaptive SA-PSO algorithm based on the simulated annealing (SA) algorithm to calculate the optimal formation parameters. A simulation example is presented for the scenario of optimizing the formation parameters of three missiles, and comparative experiments conducted with the traditional and adaptive PSO algorithms are reported. The simulation results indicate that the proposed adaptive SA-PSO algorithm converges faster than both the traditional and adaptive PSO algorithms and can quickly and effectively solve the multimissile formation optimization problem while ensuring that the optimized formation satisfies the given performance constraints

Optimal Design of Multimissile Formation Based on an Adaptive SA-PSO Algorithm

In an effort to maximize the combat effectiveness of multimissile groups, this paper proposes an adaptive simulated annealing–particle swarm optimization (SA-PSO) algorithm to enhance the design parameters of multimissile formations based on the concept of missile cooperative engagement. Firstly, considering actual battlefield circumstances, we establish an effectiveness evaluation index system for the cooperative engagement of missile formations based on the analytic hierarchy process (AHP). In doing so, we adopt a partial triangular fuzzy number method based on authoritative assessments by experts to ascertain the weight of each index. Then, considering given constraints on missile performance, by selecting the relative distances and angles of the leader and follower missiles as formation parameters, we design a fitness function corresponding to the established index system. Finally, we introduce an adaptive capability into the traditional particle swarm optimization (PSO) algorithm and propose an adaptive SA-PSO algorithm based on the simulated annealing (SA) algorithm to calculate the optimal formation parameters. A simulation example is presented for the scenario of optimizing the formation parameters of three missiles, and comparative experiments conducted with the traditional and adaptive PSO algorithms are reported. The simulation results indicate that the proposed adaptive SA-PSO algorithm converges faster than both the traditional and adaptive PSO algorithms and can quickly and effectively solve the multimissile formation optimization problem while ensuring that the optimized formation satisfies the given performance constraints

Research on the Spatial-Temporal Differentiation and Path Analysis of China’s Provincial Regions’ High-Quality Economic Development

High-quality economic development is an important approach for achieving sustainable economic development, and it is an essential condition for coordinated development between economic systems and ecosystems. This paper starts from five key points, namely, “innovation, coordination, opening-up, sharing and greenness”, to construct an evaluation system for the index of high-quality economic development, using the AHP and EVM methods to measure the level of high-quality economic development of 30 regions in China from 2004 to 2019. It uses the kernel density estimation model (hereinafter referred to briefly as KDE) and clustering method to analyze time evolution trends and spatial variation characteristics. Moreover, the LSE model is adopted to explore and analyze the factors influencing high-quality economic development in different regions. Additionally, the driving forces of China’s high-quality economic development are analyzed by means of path analysis combined with the average value of each index. The results show the following: (1) The high-quality economic development of 30 regions in China (excluding Hong Kong, Macao, Taiwan and Tibet) is spatially clustered, with obviously different development levels, characterized by the eastern region being better developed than the central and western regions. (2) With the passage of time, the polarization of China’s 30 regions has been alleviated, but they are still facing challenging development situations; (3) The factors affecting the high-quality economic development of these 30 regions in China can be divided into four types: three-factors, four-factors-I, four-factors-II and five-factors. Contributing regional factors show different distribution characteristics. The above conclusion provides a reference and scientific basis for the government to formulate policies of high-quality economic development and to solve problems facing coordinated sustainable development among regional societies, their economies and the environment

Genome-Wide Association Study of the Reproductive Traits of the Dazu Black Goat (<i>Capra hircus</i>) Using Whole-Genome Resequencing

Reproductive traits are the basic economic traits of goats and important indicators in goat breeding. In this study, Dazu black goats (DBGs; n = 150), an important Chinese local goat breed with excellent reproductive performance, were used to screen for important variation loci and genes of reproductive traits. Through genome-wide association studies (GWAS), 18 SNPs were found to be associated with kidding traits (average litter size, average litter size in the first three parity, and average litter size in the first six parity), and 10 SNPs were associated with udder traits (udder depth, teat diameter, teat length, and supernumerary teat). After gene annotation of the associated SNPs and in combination with relevant references, the candidate genes, namely ATP1A1, LRRC4C, SPCS2, XRRA1, CELF4, NTM, TMEM45B, ATE1, and FGFR2, were associated with udder traits, while the ENSCHIG00000017110, SLC9A8, GLRB, GRIA2, GASK1B, and ENSCHIG00000026285 genes were associated with litter size. These SNPs and candidate genes can provide useful biological information for improvement of the reproductive traits of goats