An optimization model of the acceptable consensus and its economic significance

Purpose – The purpose of this paper is to construct an optimal resource reallocation model of the limited resource by a moderator for reaching the greatest consensus, and show how to reallocate the limited resources by using optimization methodology once the consensus opinion is reached. Moreover, this paper also devotes to theoretically exploring when or what is the condition that the group decision-making (GDM) system is stable; and when new opinions enter into the GDM, how the level of consensus changes. Design/methodology/approach – By minimizing the differences between the individuals’ opinions and the collective consensus opinion, this paper constructs a consensus optimization model and shows that the objective weights of the individuals are actually the optimal solution to this model. Findings – If all individual deviations of the decision makers (DMs) from the consensus balance each other out, the information entropy theorem shows this GDM is most stable, and economically each individual DM gets the same optimal unit of compensation. Once the consensus opinion is determined and each individual opinion of the DMs is under an acceptable consensus level, the consensus is still acceptable even if additional DMs are added, and the moderator’s cost is still no more than a fixed upper limitation. Originality/value – The optimization model based on acceptable consensus is constructed in this paper, and its economic significance, including the theoretical and practical significance, is emphatically analyzed: it is shown that the weight information of the optimization model carries important economic significance. Besides, some properties of the proposed model are discussed by analyzing its particular solutions: the stability of the consensus system is explored by introducing information entropy theory and variance distribution; in addition, the effect of adding new DMs on the stability of the acceptable consensus system is discussed by analyzing the convergence of consensus level: it is also built up the condition that once the consensus opinion is determined, the consensus degree will not decrease even when additional DMs are added to the GDM

A prediction method for plasma concentration by using a nonlinear grey Bernoulli combined model based on a self-memory algorithm

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The goal of this work is to present and explore the application of a novel nonlinear grey Bernoulli combined model based on a self-memory algorithm, abbreviated as SA-NGBM, for modeling single-peaked sequences of time samples of acetylsalicylate plasma concentration following oral dosing. The self-memorization SA-NGBM routine reduces the dependence on a solitary initial value, as the initial state of the model utilizes multiple time samples. To test its forecasting performance, the SA-NGBM was used to extrapolate the plasma concentration predicted data, in comparison with the later time samples. The results were contrasted with those of the traditional optimized NGBM (ONGBM), exponential smoothing (ES) and simple moving average (SMA) using four popular accuracy and significance tests. That comparison showed that the SA-NGBM was much more accurate and efficient for matching the individual, nonlinear-system stochastic fluctuations than the existing ONGBM, ES and SMA models. The findings have potential applications for signal matching to similar small sample size, single-peaked, plasma concentration series

Using a novel multi-variable grey model to forecast the electricity consumption of Shandong Province in China

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The electricity consumption forecasting problem is especially important for policy making in developing region. To properly formulate policies, it is necessary to have reliable forecasts. Electricity consumption forecasting is influenced by some factors, such as economic, population and so on. Considering all factors is a difficult task since it requires much detailed study in which many factors significantly influence on electricity forecasting whereas too many data are unavailable. Grey convex relational analysis is used to describe the relationship between the electricity consumption and its related factors. A novel multi-variable grey forecasting model which considered the total population is developed to forecast the electricity consumption in Shandong Province. The GMC(1,N) model with fractional order accumulation is optimized by changing the order number and the effectiveness of the first pair of original data by the model is proven. The results of practical numerical examples demonstrate that the model provides remarkable prediction performances compared with the traditional grey forecasting model. The forecasted results showed that the increase of electricity consumption will speed up in Shandong Province

Grey Self-memory Combined Model for Complex Equipment Cost Estimation

The file attached to this record is the author's final peer reviewed version.To improve the using rationality of complex equipment cost, this paper presents a novel grey self-memory combined model for predicting the equipment cost. The proposed model can improve the modeling accuracy by means of the self-memory prediction technique. The combined model combines the advantages of the self-memory principle and traditional grey model through coupling of the above two prediction methods. The weakness of the traditional grey prediction model, i.e., being sensitive to initial value, can be overcome by using multi-time-point initial field instead of only single-time-point initial field in the system's self-memorization equation. As shown in the two case studies of complex equipment cost estimation, the novel grey self-memory combined model can take full advantage of the system's multi-time historical monitoring data and accurately predict the system's evolutionary trend. Three popular accuracy test criteria are adopted to test and verify the reliability and robustness of the combined model, and its superior predictive performance over other traditional grey prediction models. The results show that the proposed combined model enriches equipment cost estimation methods, and can be applied to other similar complex equipment cost estimation problems

Generation of tooth profile for roots rotor based on virtual linkage associated with Assur group

This article, for the first time, presents the generation of Roots rotor tooth profiles based on an Assur-group-associated virtual linkage method. Taking the original Roots rotor as an example, structure and geometry of the Roots rotor are introduced, and based on the principle of inversion, an equivalent virtual linkage is identified for generating dedendum tooth profile of the rotor. Using linkage decomposition associated with elemental Assur groups, algorithm for computing the tooth curve is constructed leading to the explicit expression of rotor profile and the corresponding numerical simulation, verifying the validity of the proposed approach. For demonstration purpose, the virtual linkage method is then extended to the generation of tooth profiles for the variants of Roots rotors with arc-cycloidal curves and arc-involute curves. Integrated with computer-aided design, computer-aided engineering and computer-aided manufacturing software platforms, as well as the three-dimensional printing technology, this article provides an efficient and intuitive approach for Roots rotor system design, analysis and development

Electronic Origin of High-Tc Maximization and Persistence in Trilayer Cuprate Superconductors

In high temperature cuprate superconductors, it was found that the superconducting transition temperature Tc depends on the number of CuO2 planes (n) in the structural unit and the maximum Tc is realized in the trilayer system (n=3). It was also found that the trilayer superconductors exhibit an unusual phase diagram that Tc keeps nearly constant in the overdoped region which is in strong contrast to the Tc decrease usually found in other cuprate superconductors. The electronic origin of the Tc maximization in the trilayer superconductors and its high Tc persistence in the overdoped region remains unclear. By taking high resolution laser-based angle resolved photoemission (ARPES) measurements, here we report our revelation of the microscopic origin of the unusual superconducting properties in the trilayer superconductors. For the first time we have observed the trilayer splitting in Bi2Sr2Ca2Cu3O10+d (Bi2223) superconductor. The observed Fermi surface, band structures, superconducting gap and the selective Bogoliubov band hybridizations can be well described by a three-layer interaction model. Quantitative information of the microscopic processes involving intra- and interlayer hoppings and pairings are extracted. The electronic origin of the maximum Tc in Bi2223 and the persistence of the high Tc in the overdoped region is revealed. These results provide key insights in understanding high Tc superconductivity and pave a way to further enhance Tc in the cuprate superconductors

van Hove Singularity-Driven Emergence of Multiple Flat Bands in Kagome Superconductors

The newly discovered Kagome superconductors AV$_3$Sb$_5$ (A=K, Rb and Cs) continue to bring surprises in generating unusual phenomena and physical properties, including anomalous Hall effect, unconventional charge density wave, electronic nematicity and time-reversal symmetry breaking. Here we report an unexpected emergence of multiple flat bands in the AV$_3$Sb$_5$ superconductors. By performing high-resolution angle-resolved photoemission (ARPES) measurements, we observed four branches of flat bands that span over the entire momentum space. The appearance of the flat bands is not anticipated from the band structure calculations and cannot be accounted for by the known mechanisms of flat band generation. It is intimately related to the evolution of van Hove singularities. It is for the first time to observe such emergence of multiple flat bands in solid materials. Our findings provide new insights in revealing the underlying mechanism that governs the unusual behaviors in the Kagome superconductors. They also provide a new pathway in producing flat bands and set a platform to study the flat bands related physics.Comment: 20 pages, 4 figure

HFR1 Is Crucial for Transcriptome Regulation in the Cryptochrome 1-Mediated Early Response to Blue Light in Arabidopsis thaliana

Cryptochromes are blue light photoreceptors involved in development and circadian clock regulation. They are found in both eukaryotes and prokaryotes as light sensors. Long Hypocotyl in Far-Red 1 (HFR1) has been identified as a positive regulator and a possible transcription factor in both blue and far-red light signaling in plants. However, the gene targets that are regulated by HFR1 in cryptochrome 1 (cry1)-mediated blue light signaling have not been globally addressed. We examined the transcriptome profiles in a cry1- and HFR1-dependent manner in response to 1 hour of blue light. Strikingly, more than 70% of the genes induced by blue light in an HFR1-dependent manner were dependent on cry1, and vice versa. High overrepresentation of W-boxes and OCS elements were found in these genes, indicating that this strong cry1 and HFR1 co-regulation on gene expression is possibly through these two cis-elements. We also found that cry1 was required for maintaining the HFR1 protein level in blue light, and that the HFR1 protein level is strongly correlated with the global gene expression pattern. In summary, HFR1, which is fine-tuned by cry1, is crucial for regulating global gene expression in cry1-mediated early blue light signaling, especially for the function of genes containing W-boxes and OCS elements

In Vitro Effects of Pirfenidone on Cardiac Fibroblasts: Proliferation, Myofibroblast Differentiation, Migration and Cytokine Secretion

Cardiac fibroblasts (CFs) are the primary cell type responsible for cardiac fibrosis during pathological myocardial remodeling. Several studies have illustrated that pirfenidone (5-methyl-1-phenyl-2-[1H]-pyridone) attenuates cardiac fibrosis in different animal models. However, the effects of pirfenidone on cardiac fibroblast behavior have not been examined. In this study, we investigated whether pirfenidone directly modulates cardiac fibroblast behavior that is important in myocardial remodeling such as proliferation, myofibroblast differentiation, migration and cytokine secretion. Fibroblasts were isolated from neonatal rat hearts and bioassays were performed to determine the effects of pirfenidone on fibroblast function. We demonstrated that treatment of CFs with pirfenidone resulted in decreased proliferation, and attenuated fibroblast α-smooth muscle actin expression and collagen contractility. Boyden chamber assay illustrated that pirfenidone inhibited fibroblast migration ability, probably by decreasing the ratio of matrix metalloproteinase-9 to tissue inhibitor of metalloproteinase-1. Furthermore, pirfenidone attenuated the synthesis and secretion of transforming growth factor-β1 but elevated that of interleukin-10. These direct and pleiotropic effects of pirfenidone on cardiac fibroblasts point to its potential use in the treatment of adverse myocardial remodeling

HPV and cervical cancer related knowledge, awareness and testing behaviors in a community sample of female sex workers in China

BACKGROUND: Limited data suggested that the prevalence of Human Papillomavirus (HPV) among female sex workers (FSW) is much higher than in the general female population. The current study aimed to examine the HPV and cervical cancer related awareness, knowledge, and behaviors among FSW in China. METHODS: A total of 360 FSW recruited from entertainment establishments in Beijing completed a self-administered survey including demographics, HPV related knowledge, and health-seeking and cervical cancer preventive behaviors. RESULTS: Approximately 70.8% of the participants ever heard of cervical cancer, and as few as 22.1% and 13.3% ever heard of HPV and HPV vaccine, respectively. The mean score on a 7-item knowledge scale was 2.2 (SD = 2.4). Less than 10% of FSW perceived any risk of cervical cancer, and only 15.3% ever had a Pap smear. About 40.8% of FSW would accept HPV vaccine if it is free, and 21.8% would accept it even with a charge. Multivariate regression suggested that women with better knowledge of cervical cancer were more likely to have a Pap smear (aOR = 1.35); women who had tested for HIV were 11 times more likely to have a Pap smear, and women who had worked longer in commercial sex (aOR = 1.01) and had regular health check-ups (aOR = 1.95) were more likely to accept HPV vaccine. CONCLUSIONS: Our study underscores the needs for effective cervical cancer prevention programs for FSW in China and other resource-limited countries. We specifically call for cervical cancer and HPV knowledge and awareness programs and regular screening as well as HPV risk-reduction programs for these vulnerable women