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An automated storage and retrieval system (AS/RS) is a key component of enterprise logistics. Its performance metrics include, e.g., order fulfillment time and energy consumption. A crane-based automated storage and retrieval system (CB-AS/RS) is used as the study subject in this paper to build a location allocation model with the goal of minimizing order fulfillment time and minimizing energy consumption. The two-objective problem is transformed into a single-objective problem by the weight method. A genetic algorithm (GA) is used to optimize and simulate the model using spatial mapping coding. A permutation-combination heuristics (PCH) is proposed that follows the coding method and cross-operation of the GA and conducts both arrange-operation and change-operation. During the simulation, the influence of different storage utilization rates and different output and input instruction quantities in a batch of orders on the results is considered. Experimental results show that the results of the PCH algorithm are better than the GA and the optimization results are more stable. In this paper, we provide an optimization idea for the CB-AS/RS researchers and managers.

To improve the throughput performance of the autonomous guide vehicle (AGV) unmanned storage system, a two-stage mathematical model was established. The model also considers the equipment configuration of the AGV unmanned storage system and the AGV- picking stations dual resource coordination scheduling problem. In the equipment-task scheduling phase, the model aims at the shortest order completion time, while the equipment configuration and layout model aims at the minimum equipment configuration and operating cost. To solve the two-stage model, a two-layer genetic algorithm was designed. The inner layer algorithm was used to optimize the task scheduling order of AGVs and picking stations. The results of the inner layer algorithm are fed back to the outer model to optimize configuration of the equipment and the picking station’s layout. The inner and outer loops are combined to obtain the optimal equipment configuration scheme. Through the simulation study of an enterprise AGV unmanned storage case, the optimal equipment configuration combination and picking stations layout scheme are obtained. Compared with the equipment configuration scheme based on the principle the task scheduling in operation is another key link that affects the picking efficiency of an unmanned warehouse of random task scheduling and the principle of shortest job time first; The model can improve the efficiency of warehouse retrieval and minimize the number of equipment configurations. Finally, the improved genetic algorithm is used to solve the model, and the performance is compared with that of LINGO to verify the effectiveness of the improved algorithm.

Despite the fact that point cloud registration under noisy conditions has recently begun to be tackled by several non-correspondence algorithms, they neither struggle to fuse the global features nor abandon early state estimation during the iterative alignment. To solve the problem, we propose a novel method named R-PCR (recurrent point cloud registration). R-PCR employs a lightweight cross-concatenation module and large receptive network to improve global feature performance. More importantly, it treats the point registration procedure as a high-order Markov decision process and introduces a recurrent neural network for end-to-end optimization. The experiments on indoor and outdoor benchmarks show that R-PCR outperforms state-of-the-art counterparts. The mean average error of rotation and translation of the aligned point cloud pairs are, respectively, reduced by 75% and 66% on the indoor benchmark (ScanObjectNN), and simultaneously by 50% and 37.5% on the outdoor benchmark (AirLoc).

Background: This study was designed initially to explore the effect of chemoradiotherapy on patients diagnosed with head and neck cancer (HNC) with respect to the alteration of systematic immunity. Methods: We did a retrospective study enrolling patients received concurrent chemoradiotherapy (CCRT), with or without induction chemotherapy (IC). Blood tests were performed before IC, before and after CCRT. Flow cytometric analysis and turbidimetric inhibition immunoassay were used for detection. Results: A total number of 58 patients were included from April 1, 2018, to March 31, 2019. Levels of immunoglobulins (Ig), including IgA, IgG, and IgM, declined after 2 to 3 cycles of IC and CCRT, respectively. Serum level of total hemolytic complement (CH50) increased ( P < .001) after IC, but kept stably post-CCRT. Natural killer (NK) cells decreased ( P < .01) after IC and enhanced ( P < .001) post-CCRT. The number of CD3 + CD4 + T cells got increased ( P < .01) after IC and decreased ( P < .001) post-CCRT. Consistently, both IC and CCRT induced the increase in CD3 + CD8 + T cells significantly ( P < .001 vs P < .01). Conclusion: Both radiotherapy (RT) and chemotherapy (CT) induced dual effect of immune response. Concurrent chemoradiotherapy created an active immune response based on the effect induced by IC, suggesting that RT exerted a potential function on mobilizing immune system.

Abstract Background Pathogens dependent upon vectors for transmission to new hosts undergo environment specific changes in gene transcription dependent on whether they are replicating in the vector or the mammalian host. Differential gene transcription, especially of potential vaccine candidates, is of interest in Anaplasma marginale, the tick-borne causative agent of bovine anaplasmosis. Methods RNA-seq technology allowed a comprehensive analysis of the transcriptional status of A. marginale genes in two conditions: bovine host blood and tick derived cell culture, a model for the tick vector. Quantitative PCR was used to assess transcription of a set of genes in A. marginale infected tick midguts and salivary glands at two time points during the transmission cycle. Results Genes belonging to fourteen pathways or component groups were found to be differentially transcribed in A. marginale in the bovine host versus the tick vector. One of the most significantly altered groups was composed of surface proteins. Of the 56 genes included in the surface protein group, eight were up regulated and 26 were down regulated. The down regulated surface protein encoding genes include several that are well studied due to their immunogenicity and function. Quantitative PCR of a set of genes demonstrated that transcription in tick cell culture most closely approximates transcription in salivary glands of recently infected ticks. Conclusions The ISE6 tick cell culture line is an acceptable model for early infection in tick salivary glands, and reveals disproportionate down regulation of surface protein genes in the tick. Transcriptional profiling in other cell lines may help us simulate additional microenvironments. Understanding vector-specific alteration of gene transcription, especially of surface protein encoding genes, may aid in the development of vaccines or transmission blocking therapies.