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Abstract This paper investigates Regional Integrated Energy Systems (RIES), emphasizing the connection of diverse energy supply subsystems to address varied user needs and enhance operational efficiency. A novel low-carbon economic dispatch method, utilizing the multi-objective chaotic artificial hummingbird algorithm, is introduced. The method not only optimizes economic and environmental benefits but also aligns with "carbon peak and carbon neutrality" objectives. The study begins by presenting a comprehensive low-carbon economic dispatch model, followed by the proposal of the multi-objective chaotic artificial hummingbird algorithm, crucial for deriving the Pareto frontier of the low-carbon economic dispatch model. Additionally, we introduce a TOPSIS approach based on combined subjective and objective weights, this approach harnesses the objective data from the Pareto solution set deftly, curbs the subjective biases of dispatchers effectively and facilitates the selection of an optimal system operation plan from the Pareto frontier. Finally, the simulation results highlight the outstanding performance of our method in terms of optimization outcomes, convergence efficiency, and solution diversity. Noteworthy among these results is an 8.8% decrease in system operational economic costs and a 14.2% reduction in carbon emissions.

Abstract IN the trend of energy revolution, power data becomes one of the key elements of the power grid. And an advance power system with "electric power + computing power" as the core has become an inevitable choice. However, the traditional search approach based on directory query is commonly used for power grid operation data in domestic and international. The approach fails to effectively meet the user's need for fast, accurate and personalized retrieval of useful information from the vast amount of power grid data. It seriously affects the real-time availability of data and the efficiency of business-critical analytical decisions. For this reason, an intelligent retrieval approach for power grid operation data based on improved SimHash and multi-attribute decision making is proposed in this paper. This method elaborates the properties of SimHash and multi-attribute decision making algorithms. And an intelligent parallel retrieval algorithm MR-ST based on MapReduce model is designed. Finally, real time grid operation data from multiple sources are analyzed on the cloud platform for example. The experimental results show the effectiveness and precision of the method. Compared with traditional methods, the search accuracy rate, search completion rate and search time are significantly improved. Experiments show that the method can be applied to intelligent retrieval of power grid operation data.

Abstract HIV subtypes convey important epidemiological information and possibly influence the rate of disease progression. In this study, HIV disease progression in patients infected with CRF01_AE, CRF07_BC, and subtype B was compared in the largest HIV molecular epidemiology study ever done in China. A national data set of HIV pol sequences was assembled by pooling sequences from public databases and the Beijing HIV laboratory network. Logistic regression was used to assess factors associated with the risk of AIDS at diagnosis ([AIDSAD], defined as a CD4 count

Abstract Temperature tolerance is an important trait from both an economic and evolutionary perspective in fish. Because of difficulties with measurements, genome-wide selection using quantitative trait loci (QTLs) affecting Upper temperature tolerance may be an alternative for genetic improvement. Turbot Scophthalmus maximus (L.) is a cold-water marine fish with high economic value in Europe and Asia. The genetic bases of upper temperature tolerance (UTTs) traits have been rarely studied. In this study, we constructed a genetic linkage map of turbot using simple sequence repeats (SSRs) and single nucleotide polymorphism (SNP) markers. A total of 190 SSR and 8,123 SNP were assigned to 22 linkage groups (LGs) of a consensus map, which spanned 3,648.29 cM of the turbot genome, with an average interval of 0.44 cM. Moreover, we re-anchored genome sequences, allowing 93.8% physical sequences to be clustered into 22 turbot pseudo-chromosomes. A high synteny was observed between two assemblies from the literature. QTL mapping and validation analysis identified thirteen QLTs which are major effect QTLs, of these, 206 linked SNP loci, and two linked SSR loci were considered to have significant QTL effects. Association analysis for UTTs with 129 QTL markers was performed for different families, results showed that eight SNP loci were significantly correlated with UTT, which markers could be helpful in selecting thermal tolerant breeds of turbot. 1,363 gene sequences were genomically annotated, and 26 QTL markers were annotated. We believe these genes could be valuable candidates affecting high temperatures, providing valuable genomic resources for the study of genetic mechanisms regulating thermal stress. Similarly, they may be used in marker-assisted selection (MAS) programs to improve turbot performance.

Abstract Upland cotton (Gossypium hirsutum L.) is an important economic crop for renewable textile fibers. However, the simultaneous improvement of yield and fiber quality in cotton is difficult as the linkage drag. Compared with breaking the linkage drag, identification of the favorable pleiotropic loci on the genome level by genome-wide association study (GWAS) provides a new way to improve the yield and fiber quality simultaneously. In our study restriction-site-associated DNA sequencing (RAD-seq) was used to genotype 316 cotton accessions. Eight major traits in three categories including yield, fiber quality and maturation were investigated in nine environments (3 sites × 3 years). 231 SNPs associated with these eight traits (− log10(P) > 5.27) were identified, located in 27 genomic regions respectively by linkage disequilibrium analysis. Further analysis showed that four genomic regions (the region 1, 6, 8 and 23) held favorable pleiotropic loci and 6 candidate genes were identified. Through genotyping, 14 elite accessions carrying the favorable loci on four pleiotropic regions were identified. These favorable pleiotropic loci and elite genotypes identified in this study will be utilized to improve the yield and fiber quality simultaneously in future cotton breeding.

Abstract Chronic disease, mental health symptoms and poor social relations are reported common causes for poor self-rated health in older people. To assess the co-occurrence rate of chronic diseases, poor mental health and poor social relationships in older people, and determine their association with self-rated health. 6,551 older people in Zhongshan, China, participated a large health surveillance program were randomly selected and questioned about their SRH, chronic conditions, mental health symptoms and social relationships. The association between self-rated health and chronic conditions, poor mental health, social relationships, and their co-occurrence were analyzed. 56.4% of participants reported poor self-rated health. 39.1% experienced at least one chronic disease. 29.0% experienced one or more mental health symptoms; 19.5% experienced at least one poor social relationship. 7.8% had co-occurrence of chronic diseases, mental health problems, and poor social relationships. Logistic regressions showed that poor self-rated health was associated with chronic diseases, poor mental health, poor social relationships and their co-occurrence. The findings indicate the importance of managing chronic disease, poor mental health and poor social relationships for older people.

Abstract Working memory (WM) is a fundamental cognitive function that typically declines with age. Previous studies have shown that targeted WM training has the potential to improve WM performance in older adults. In the present study, we investigated whether a multi-domain cognitive training program that was not designed to specifically target WM could improve the behavioral performance and affect the neural activity during WM retrieval in healthy older adults. We assigned healthy older participants (70–78 years old) from a local community into a training group who completed a 3-month multi-domain cognitive training and a control group who only attended health education lectures during the same period. Behavioral and electroencephalography (EEG) data were recorded from participants while performing an untrained delayed match or non-match to category task and a control task at a pre-training baseline session and a post-training follow-up session. Behaviorally, we found that participants in the training group showed a trend toward greater WM performance gains than participants in the control group. Event-related potential (ERP) results suggest that the task-related modulation of P3 during WM retrieval was significantly enhanced at the follow-up session compared with the baseline session, and importantly, this enhancement of P3 modulation was only significant in the training group. Furthermore, no training-related effects were observed for the P2 or N2 component during WM retrieval. These results suggest that the multi-domain cognitive training program that was not designed to specifically target WM is a promising approach to improve WM performance in older adults, and that training-related gains in performance are likely mediated by an enhanced modulation of P3 which might reflect the process of WM updating.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.