308 research outputs found
On constructing benchmark quantum circuits with known near-optimal transformation cost
Current quantum devices impose strict connectivity constraints on quantum
circuits, making circuit transformation necessary before running logical
circuits on real quantum devices. Many quantum circuit transformation (QCT)
algorithms have been proposed in the past several years. This paper proposes a
novel method for constructing benchmark circuits and uses these benchmark
circuits to evaluate state-of-the-art QCT algorithms, including TKET from
Cambridge Quantum Computing, Qiskit from IBM, and three academic algorithms
SABRE, SAHS, and MCTS. These benchmarks have known near-optimal transformation
costs and thus are called QUEKNO (for quantum examples with known
near-optimality). Compared with QUEKO benchmarks designed by Tan and Cong
(2021), which all have zero optimal transformation costs, QUEKNO benchmarks are
more general and can provide a more faithful evaluation for QCT algorithms
(like TKET) which use subgraph isomorphism to find the initial mapping. Our
evaluation results show that SABRE can generate transformations with
conspicuously low average costs on the 53-qubit IBM Q Rochester and Google's
Sycamore in both gate size and depth objectives.Comment: 14 pages, 7 figures, code and benchmarks available at https:
//github.com/ebony72/quekn
Association of MTHFR A1298C polymorphism with breast cancer and/or ovarian cancer risk: an updated meta-analysis
Background: Recent years have witnessed the discovery of similar gene variations between breast cancer and ovarian cancer, inherited breast and ovarian cancer in particular. A large number of case-control studies have been conducted to explore the association of Methylenetetrahydrofolate Reductase (MTHFR) A1298C polymorphism with breast cancer and/or ovarian cancer risk. However, the results are still inconsistent and inconclusive. Consequently, we performed a meta-analysis to evaluate the association between MTHFR A1298C polymorphism and breast, ovarian cancer risk.Materials and Methods: A comprehensive retrieval was conducted in the electronic database of PubMed, Web of Science and Chinese National Knowledge Infrastructure (CNKI) until June 2015 to identify eligible studies. A total of 35 studies which examined the association of MTHFR A1298C polymorphism with breast cancer and/or ovarian cancer were identified. The pooled odds ratios (ORs) with 95 % confidence intervals (CIs) were used to assess the effect of gene polymorphism. And allele model, homozygous model, co-dominant model, dominant model, recessive model were applied.Result: In the overall analysis, significantly increased breast cancer and/or ovarian cancer risk was found (for allele model A VS C OR = 1.05, CI: 1.02-1.08, P = 4Ă10-3; for homozygous model AA VS CC OR = 1.11, CI: 1.03-1.19, P = 5Ă10-3; for recessive model (AC +AA) VS CC: OR = 1.10, CI: 1.03-1.18, P = 7Ă10-3).Conclusion: In the subgroup analysis, significantly increased breast cancer risk was identified among Caucasians. MTHFR A1298C polymorphism might contribute to an increased risk of breast cancer and/or ovarian cancer susceptibility. In addition, MTHFR A1298C polymorphism had a significant association with breast cancer in Caucasians.Keywords: Breast cancer, Ovarian cancer, MTHFR A1298C, Polymorphism, Meta analysi
Analysis of the control strategy of range extender system on the vehicle NVH performance
With focus on NVH performance, this paper studies the range extender system control strategy such as the initial start speed, operating points, speed up and down control method between operating points of the range extender, etc. At the same time, the confirmation of the operating points of the range extender based on the full vehicle frequency distribution and vibration and noise level of key points (seat rail, driverâs inner ear) was performed. Finally, we conducted objective test and compared the test data with benchmark vehicles
Microorganism-regulated mechanisms of temperature effects on the performance of anaerobic digestion
Additional file 2. Additional tables
Mixture of tree species enhances stability of soil bacterial community through phylogenetic diversity
The composition of tree species might influence microbial diversity considerably, yet investigation of the consequences of changes in diversity on stability of the microbial community is still in its early stages. Understanding how diversity governs community stability is vital for predicting the response of an ecosystem to environmental changes. Phylogenetic diversity (PD) describes the distinct evolution of species in a community, and might be useful for estimating the effects of biodiversity on ecosystem function and stability. Highâthroughput 16S rRNA gene sequencing was used to examine soil bacterial phylogenetic distances, phylogenetic diversity and interactions between individuals in five singleâspecies plantations and three mixedâspecies plantations. The plantations were established on the same initial substrate, and sampling was at 68 relatively spatially independent sites. Our results showed that mixed tree species enhanced soil bacterial phylogenetic diversity and community stability, and that phylogenetic diversity had a positive effect on stability of the soil microbial community. We also found evidence that microbial communities characterized by distantly related species with weak interactions were more stable in mixed plantations than communities with strong interactions in singleâspecies plantations. These results may be explained by the âinsurance hypothesisâ, that large phylogenetic diversity of microbial communities which share different ecological niches insures them against decline in their stability. This is because, even if some microbial species fail to deal with environmental change, others might not necessarily be affected similarly. Our findings demonstrate that phylogenetic diversity is the main controlling factor of the variation in stability across sites and requires more attention in sustainable forest management
Variation of Helicoverpa armigera symbionts across developmental stages and geographic locations
Cotton bollworm (Helicoverpa armigera) poses a global problem, causing substantial economic and ecological losses. Endosymbionts in insects play crucial roles in multiple insect biological processes. However, the interactions between H. armigera and its symbionts have not been well characterized to date. We investigated the symbionts of H. armigera in the whole life cycle from different geographical locations. In the whole life cycle of H. armigera, Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria were the dominant bacteria at the phylum level, while Enterococcus, Enterobacter, Glutamicibacter, and Bacillus were the four dominant bacteria at the genus level. Furthermore, high similarity in symbiotic bacterial community was observed in different stages of H. armigera, which were dominated by Enterococcus and Enterobacter. In fields, the dominant bacteria were Proteobacteria and Bacteroidetes, whereas, in the laboratory, the dominant bacteria were Proteobacteria. At the genus level, the dominant bacteria in cotton bollworm eggs of wild populations were Enterobacter, Morganella, Lactococcus, Asaia, Apibacter, and Enterococcus, and the subdominant bacteria were Bartonella, Pseudomonas, and Orbus. Moreover, the symbionts varied with geographical locations, and the closer the geographical distance, the more similar the microbial composition. Taken together, our study identifies and compares the symbiont variation along with geographical gradients and host development dynamic and reveals the high flexibility of microbiome communities in H. armigera, which probably benefits for the successful survival in a complicated changing environment
Divergence of Fecal Microbiota and Their Associations With Host Phylogeny in Cervinae
Gastrointestinal microbiota may shape the adaptation of their hosts to different habitats and lifestyles, thereby driving their evolutionary diversification. It remains unknown if gastrointestinal microbiota diverge in congruence with the phylogenetic relationships of their hosts. To evaluate the phylosymbiotic relationships, here we analyzed the compositions of fecal microbiota of seven Cervinae species raised in the Chengdu Zoo. All sampled animals were kept in the same environmental condition and fed identical fodder for years. Results showed that Firmicutes and Bacteroidetes were dominant in their fecal microbiota. Even though some bacteria (e.g., Ruminococcaceae) were found to be common in the feces of all investigated species, some genera (e.g., Sharpea and Succinivibrio) were only observed in animals with particular digestive systems. As for the intraspecies variations of microbial communities, only a few operational taxonomic units (OTUs) were shared among replicates of the same host species although they accounted for most of the total abundance. Correlation was observed between the fecal microbiota divergence and host phylogeny, but they were not congruent completely. This may shed new light on the coevolution of host species and their microbiota
ASSOCIATION OF MTHFR A1298C POLYMORPHISMWITH BREAST CANCER AND/OR OVARIAN CANCER RISK: AN UPDATED META-ANALYSIS
Background: Recent years have witnessed the discovery of similar gene variations between breast cancer and ovarian cancer, inherited breast
and ovarian cancer in particular. A large number of case-control studies have been conducted to explore the association of
Methylenetetrahydrofolate Reductase (MTHFR) A1298C polymorphism with breast cancer and/or ovarian cancer risk. However, the results are
still inconsistent and inconclusive. Consequently, we performed a meta-analysis to evaluate the association between MTHFR A1298C
polymorphism and breast, ovarian cancer risk.
Materials and Methods: A comprehensive retrieval was conducted in the electronic database of PubMed, Web of Science and Chinese National
Knowledge Infrastructure (CNKI) until June 2015 to identify eligible studies. A total of 35 studies which examined the association of MTHFR
A1298C polymorphism with breast cancer and/or ovarian cancer were identified. The pooled odds ratios (ORs) with 95 % confidence intervals
(CIs) were used to assess the effect of gene polymorphism. And allele model, homozygous model, co-dominant model, dominant model,
recessive model were applied.
Result: In the overall analysis, significantly increased breast cancer and/or ovarian cancer risk was found (for allele model A VS C OR = 1.05,
CI: 1.02-1.08, P = 4Ă10-3; for homozygous model AA VS CC OR = 1.11, CI: 1.03-1.19, P = 5Ă10-3; for recessive model (AC +AA) VS CC: OR
= 1.10, CI: 1.03-1.18, P = 7Ă10-3).
Conclusion: In the subgroup analysis, significantly increased breast cancer risk was identified among Caucasians. MTHFR A1298C
polymorphism might contribute to an increased risk of breast cancer and/or ovarian cancer susceptibility. In addition, MTHFR A1298C
polymorphism had a significant association with breast cancer in Caucasians
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