In this paper, we investigate the allocation of resource in D2D-aided Fog computing system with multiple mobile user equipments (MUEs). We consider each MUE has a request for task from a task library and needs to make a decision on task performing with a selection of three processing modes which include local mode, fog offloading mode, and cloud offloading mode. Two scenarios are considered in this paper, which mean task caching and its optimization in off-peak time, task offloading, and its optimization in immediate time. In particular, task caching refers to cache the completed task application and its related data. In the first scenario, to maximize the average utility of MUEs, a task caching optimization problem is formulated with stochastic theory and is solved by a GA-based task caching algorithm. In the second scenario, to maximize the total utility of system, the task offloading and resource optimization problem is formulated as a mixed integer nonlinear programming problem (MINLP) with a joint consideration of the MUE allocation policy, task offloading policy, and computational resource allocation policy. Due to the nonconvex of the problem, we transform it into multi-MUEs association problem (MMAP) and mixed Fog/Cloud task offloading optimization problem (MFCOOP). The former problem is solved by a Gini coefficient-based MUEs allocation algorithm which can select the most proper MUEs who contribute more to the total utility. The task offloading optimization problem is proved as a potential game and solved by a distributed algorithm with Lagrange multiplier. At last, the simulations show the effectiveness of the proposed scheme with the comparison of other baseline schemes.

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Melanocortin 4 receptor (MC4R), which is associated with inherited human obesity, is involoved in food intake and body weight of mammals. To study the relationships between MC4R gene polymorphism and body weight in Beagle dogs, we detected and compared the nucleotide sequence of the whole coding region and 3′- and 5′- flanking regions of the dog MC4R gene (1214 bp). In 120 Beagle dogs, two SNPs (A420C, C895T) were identified and their relation with body weight was analyzed with RFLP-PCR method. The results showed that the SNP at A420C was significantly associated with canine body weight trait when it changed amino acid 101 of the MC4R protein from asparagine to threonine,while canine body weight variations were significant in female dogs when MC4R nonsense mutation at C895T. It suggested that the two SNPs might affect the MC4R gene’s function which was relative to body weight in Beagle dogs. Therefore, MC4R was a candidate gene for selecting different size dogs with the MC4R SNPs (A420C, C895T) being potentially valuable as a genetic marker.

BACKGROUND: In 2017 Tuta absoluta was identified as an invasive species in China. Due to its rapid geographic expansion and the severe crop damage it causes, T. absoluta poses a serious threat to China's tomato production industry. To determine its geographic distribution and host range, intensive surveys and routine monitoring were conducted across the Chinese mainland between 2018 and 2019. The population colonization coefficient (PCC; ratio of colonized sites and prefectures) and population occurrence index (POI; ratio of infested host species and PCCs) were calculated.RESULTS: In northwestern China, T. absoluta populations established in Xinjiang exhibited a medium PCC value (∼0.03). In southwestern China, populations in Yunnan and its five neighboring provinces exhibited high (∼0.50 in Yunnan and Guizhou), or low (<0.02 in Guangxi, Sichuan, Hunan, and Chongqing) PCC values. In the Chinese mainland, infestations of four crop plant species (tomato, eggplant, potato, and Chinese lantern) and two wild plant species (black nightshade and Dutch eggplant) were identified; tomatoes were infested in every colonized province. Chinese lantern and Dutch eggplant are potentially novel hosts. Yunnan, Guizhou, and Xinjiang experienced the most serious damage (POI). In southwestern China, observed damage significantly decreased with increased distance from the first discovery site of T. absoluta to the farthest county of an infested province increased. CONCLUSION: T. absoluta populations are well-established and could potentially spread to other regions of China. The present study helps to inform the establishment of better pest management guidelines and strategies in China and tomato-producing regions worldwide.