Design of zero-determinant strategies and its application to networked repeated games

Using semi-tensor product (STP) of matrices, the profile evolutionary equation (PEE) for repeated finite games is obtained. By virtue of PEE, the zero-determinant (ZD) strategies are developed for general finite games. A formula is then obtained to design ZD strategies for general finite games with multi-player and asymmetric strategies. A necessary and sufficient condition is obtained to ensure the availability of the designed ZD strategies. It follows that player $i$ is able to unilaterally design $k_i-1$ (one less than the number of her strategies) dominating linear relations about the expected payoffs of all players. Finally, the fictitious opponent player is proposed for networked repeated games (NRGs). A technique is proposed to simplify the model by reducing the number of frontier strategies.Comment: arXiv admin note: substantial text overlap with arXiv:2107.0325

AirCode: Unobtrusive Physical Tags for Digital Fabrication

We present AirCode, a technique that allows the user to tag physically fabricated objects with given information. An AirCode tag consists of a group of carefully designed air pockets placed beneath the object surface. These air pockets are easily produced during the fabrication process of the object, without any additional material or postprocessing. Meanwhile, the air pockets affect only the scattering light transport under the surface, and thus are hard to notice to our naked eyes. But, by using a computational imaging method, the tags become detectable. We present a tool that automates the design of air pockets for the user to encode information. AirCode system also allows the user to retrieve the information from captured images via a robust decoding algorithm. We demonstrate our tagging technique with applications for metadata embedding, robotic grasping, as well as conveying object affordances.Comment: ACM UIST 2017 Technical Paper

Transcriptome analyses reveal reduced hepatic lipid synthesis and accumulation in more feed efficient beef cattle

peer-reviewedThe genetic mechanisms controlling residual feed intake (RFI) in beef cattle are still largely unknown. Here we performed whole transcriptome analyses to identify differentially expressed (DE) genes and their functional roles in liver tissues between six extreme high and six extreme low RFI steers from three beef breed populations including Angus, Charolais, and Kinsella Composite (KC). On average, the next generation sequencing yielded 34 million single-end reads per sample, of which 87% were uniquely mapped to the bovine reference genome. At false discovery rate (FDR)  2, 72, 41, and 175 DE genes were identified in Angus, Charolais, and KC, respectively. Most of the DE genes were breed-specific, while five genes including TP53INP1, LURAP1L, SCD, LPIN1, and ENSBTAG00000047029 were common across the three breeds, with TP53INP1, LURAP1L, SCD, and LPIN1 being downregulated in low RFI steers of all three breeds. The DE genes are mainly involved in lipid, amino acid and carbohydrate metabolism, energy production, molecular transport, small molecule biochemistry, cellular development, and cell death and survival. Furthermore, our differential gene expression results suggest reduced hepatic lipid synthesis and accumulation processes in more feed efficient beef cattle of all three studied breeds

Identification of candidate genes and enriched biological functions for feed efficiency traits by integrating plasma metabolites and imputed whole genome sequence variants in beef cattle

Abstract Background Feed efficiency is one of the key determinants of beef industry profitability and sustainability. However, the cellular and molecular background behind feed efficiency is largely unknown. This study combines imputed whole genome DNA variants and 31 plasma metabolites to dissect genes and biological functions/processes that are associated with residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) in beef cattle. Results Regression analyses between feed efficiency traits and plasma metabolites in a population of 493 crossbred beef cattle identified 5 (L-valine, lysine, L-tyrosine, L-isoleucine, and L-leucine), 4 (lysine, L-lactic acid, L-tyrosine, and choline), 1 (citric acid), and 4 (L-glutamine, glycine, citric acid, and dimethyl sulfone) plasma metabolites associated with RFI, DMI, ADG, and MWT (P-value < 0.1), respectively. Combining the results of metabolome-genome wide association studies using 10,488,742 imputed SNPs, 40, 66, 15, and 40 unique candidate genes were identified as associated with RFI, DMI, ADG, and MWT (P-value < 1 × 10−5), respectively. These candidate genes were found to be involved in some key metabolic processes including metabolism of lipids, molecular transportation, cellular function and maintenance, cell morphology and biochemistry of small molecules. Conclusions This study identified metabolites, candidate genes and enriched biological functions/processes associated with RFI and its component traits through the integrative analyses of metabolites with phenotypic traits and DNA variants. Our findings could enhance the understanding of biochemical mechanisms of feed efficiency traits and could lead to improvement of genomic prediction accuracy via incorporating metabolite data

Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization

Artificial bee colony (ABC) algorithm has good performance in discovering the optimal solutions to difficult optimization problems, but it has weak local search ability and easily plunges into local optimum. In this paper, we introduce the chemotactic behavior of Bacterial Foraging Optimization into employed bees and adopt the principle of moving the particles toward the best solutions in the particle swarm optimization to improve the global search ability of onlooker bees and gain a hybrid artificial bee colony (HABC) algorithm. To obtain a global optimal solution efficiently, we make HABC algorithm converge rapidly in the early stages of the search process, and the search range contracts dynamically during the late stages. Our experimental results on 16 benchmark functions of CEC 2014 show that HABC achieves significant improvement at accuracy and convergence rate, compared with the standard ABC, best-so-far ABC, directed ABC, Gaussian ABC, improved ABC, and memetic ABC algorithms