•Introduce a new framework of additively normalized interval priorities (ANIPs).•Build two eigenvector problems from an interval paired comparison matrix (IPCM).•Develop a procedure to obtain ...eigenvector based ANIPs from IPCMs.•Propose a novel eigenvector problem based acceptability checking method for IPCMs.•Present an eigenvector driven hierarchical MCDM model with interval assessments.
Priority derivation and acceptability checking play crucial roles in multi-criteria decision making (MCDM) with pairwise comparison matrices. However, the existing eigenvector based interval priority derivation methods often fail to obtain a reasonable and logical solution from an interval multiplicative pairwise comparison matrix (IMPCM). The obtained maximal eigenvalues are frequently unable to be used to check the quality of interval evaluations in an IMPCM. To get over these challenges, this paper introduces a new framework to additively normalize interval priorities from the viewpoint of producing an identical and consistent IMPCM. By analyzing the approximation relationship between original evaluations and interval priorities of IMPCMs, two positive real matrices and their corresponding eigenvector problems are established from an IMPCM and a procedure is developed to obtain eigenvector based additively normalized interval priorities from IMPCMs. A maximal eigenvalue based consistency index and its corresponding consistency ratio are defined and a method is presented to check the acceptability of an IMPCM by taking its inconsistency and its eigenvector based interval priority uncertainty into consideration. Afterwards, an approach is proposed to obtain global importance weights of the criteria at the bottom level and a procedure is devised to tackle hierarchical MCDM problems with interval assessments. The proposed interval priority derivation method and acceptability checking model are illustrated by two numerical examples and comparative studies are conducted to show their performance and superiority. Meanwhile, a renewable energy supply selection problem is utilized to demonstrate the applicability of the presented interval MCDM method.
We propose a new unsupervised learning method for clustering a large number of time series based on a latent factor structure. Each cluster is characterized by its own cluster-specific factors in ...addition to some common factors which impact on all the time series concerned. Our setting also offers the flexibility that some time series may not belong to any clusters. The consistency with explicit convergence rates is established for the estimation of the common factors, the cluster-specific factors, and the latent clusters. Numerical illustration with both simulated data as well as a real data example is also reported. As a spin-off, the proposed new approach also advances significantly the statistical inference for the factor model of Lam and Yao.
Supplementary materials
for this article are available online.
We propose a novel algorithm to detect visual saliency from video signals by combining both spatial and temporal information and statistical uncertainty measures. The main novelty of the proposed ...method is twofold. First, separate spatial and temporal saliency maps are generated, where the computation of temporal saliency incorporates a recent psychological study of human visual speed perception. Second, the spatial and temporal saliency maps are merged into one using a spatiotemporally adaptive entropy-based uncertainty weighting approach. The spatial uncertainty weighing incorporates the characteristics of proximity and continuity of spatial saliency, while the temporal uncertainty weighting takes into account the variations of background motion and local contrast. Experimental results show that the proposed spatiotemporal uncertainty weighting algorithm significantly outperforms state-of-the-art video saliency detection models.
This study aims to explore the effect of miR‐330 targeting VAV1 on amyloid β‐protein (Aβ) production, oxidative stress (OS), and mitochondrial dysfunction in Alzheimer's disease (AD) mice through the ...MAPK signaling pathway. Putative targeted gene of miR‐330 was performed by a miRNA target prediction website and dual‐luciferase reporter gene assay. AD mouse model was successfully established. Fourteen C57 mice were randomized into AD and control groups. The positive protein expression rate of VAV1 was measured by immunohistochemistry. Neuron cells were assigned into control, blank, negative control (NC), miR‐330 mimics, miR‐330 inhibitors, siRNA‐VAV1, and miR‐330 inhibitors + siRNA‐VAV1 groups. Expression of miR‐330, VAV1, ERK1, JNK1, P38MAPK, Aβ, COX, and lipoprotein receptor‐related protein‐1 (LRP‐1) were determined using RT‐qPCR and Western blotting. Colorimetry was applied to measure the levels of OS parameters of superoxide dismutase (SOD) and malondialdehyde (MDA). Aβ production in brain tissue was detected using ELISA, while that in neuron cell was measured by radioimmunoassay. MiR‐330 was down‐regulated in neuron cells of AD mice and VAV1 was negatively regulated by miR‐330. Compared with the control group, the positive protein expression rate of VAV1 was significantly elevated in the AD group. Overexpression of miR‐330 decreased the expression of VAV1, ERK1, JNK1, P38MAPK, and Aβ, but increased the expression of COX and LRP‐1. AD mice revealed elevated Aβ production and MDA with decreased SOD level. The result indicates that overexpressed miR‐330 targeting VAV1 through the MAPK signaling pathway reduces Aβ production and alleviates OS and mitochondrial dysfunction in AD.
The result indicates that overexpressed miR‐330 targeting VAV1 through the MAPK signaling pathway reduces Aβ production and alleviates oxidative stress and mitochondrial dysfunction in AD mice.
•Obtain uncertainty constraints among assessments in an additively consistent IVFPR.•Acquire an analytical solution of interval fuzzy utility vectors from IVFPRs.•Propose a novel acceptability ...checking method for IVFPRs.•Develop MCDM with highlighting individual characteristics of alternatives.
Acquiring an analytical solution of interval fuzzy utility vectors (IFUVs) from interval-valued fuzzy preference relations (IVFPRs) plays a key role in improving the efficiency and performance of decision making with IVFPRs. This study devises formulas to compute uncertainty indices of interval-valued fuzzy assessments and IVFPRs, and builds uncertainty constraints among fuzzy assessments in an additively consistent IVFPR. By dividing all IVFPRs with the same size into two categories, least square models with constraints of uncertainty indices are set up and their analytical solutions are found to respectively acquire normalized IFUVs from the two categories of IVFPRs. The analytical solutions are then integrated into unified computational formulas acquiring normalized IFUVs from IVFPRs. On the basis of analytical-solution-based IFUVs, a distance based additive consistency index is devised and a novel acceptability concept is presented by taking both additive inconsistency acceptability and uncertainty acceptability into account. Subsequently, this paper proposes a multi-criteria decision making method with highlighting individual characteristics of alternatives. An illustration with one consistent IVFPR and three inconsistent IVFPRs is offered and a comparative study is implemented to validate the models presented. An annual-performance-evaluation-based outstanding teacher recommendation problem is utilized to show the practicality of the decision method proposed.
We propose a high-sensitive Sagnac-interferometer biosensor based on theVernier effect (VE) with a high-birefringence microfiber. The sensitivity enhancement is achieved by utilizing two cascaded ...Sagnac interferometers. One of the two interference loops consists of a panda polarization-maintaining fiber as a filter, whilst the other is comprised of high-birefringent microfiber coated Graphene oxide (GO) as a sensing channel. We theoretically analyzed the sensitivity of the sensor and verified it with experiments. The results of the simulation show that the refractive index sensitivity is more than five times that of the fiber sensor based on a single Sagnac loop. The sensitivity of the refractive index in the experiments can reach 2429 nm/refractive index unit (RIU), which is basically in accordance with the simulation. We also use electrostatic adsorption to coat GO on the surface of the sensing channel. GO is employed to adsorb bovine serum albumin (BSA) molecules to achieve the desired detection results, which has good biocompatibility and large specific surface area. The sensitivity to detect BSA can reach 9.097 nm/(mg×mL
).
The possible advantages of laparoscopic radical hysterectomy (LRH) versus open radical hysterectomy (RH) have not been well reviewed systematically. The aim of this study was to systematically review ...the comparative effectiveness between LRH and RH in the treatment of cervical cancer based on the evaluation of the Perioperative outcomes, oncological clearance, complications and long-term outcomes.
The systematic review was conducted by searching PubMed, MEDLINE, EMBASE, the Cochrane Library and BIOSIS databases. All original studies that compared LRH with RH were included for critical appraisal. Data were pooled and analyzed.
A total of twelve original studies that compared LRH (n = 754) with RH (n = 785) in patients with cervical cancer fulfilled quality criteria were selected for review and meta-analysis. LRH compared with RH was associated with a significant reduction of intraoperative blood loss (weighted mean difference = -268.4 mL (95 % CI -361.6, -175.1; p < 0.01), a reduced risk of postoperative complications (OR = 0.46; 95 % CI 0.34-0.63) and shorter hospital stay (weighted mean difference = -3.22 days; 95 % CI-4.21, -2.23 days; p < 0.01). These benefits were at the cost of longer operative time (weighted mean difference = 26.9 min (95 % CI 8.08-45.82). The rate of intraoperative complications was similar in the two groups. Lymph nodes yield and positive resection margins were similar between the two groups. There were no significant differences in 5-year overall survival (HR 0.91, 95 % CI 0.48-1.71; p = 0.76) and 5-year disease-free survival (hazard ratio HR 0.97, 95 % CI 0.56-1.68; p = 0.91).
LRH shows better short term outcomes compared with RH in patients with cervical cancer. The oncologic outcome and 5-year survival were similar between the two groups.
Information security has gained increasing attention in the past decade, leading to the development of advanced materials for anti‐counterfeiting, encryption and instantaneous information display. ...However, it remains challenging to achieve high information security with simple encryption procedures and low‐energy stimuli. Herein, a series of strain/temperature‐responsive liquid crystal elastomers (LCEs) are developed to achieve dual‐modal, multi‐level information encryption and real‐time, rewritable transient information display. The as‐prepared polydomain LCEs can change from an opaque state to a transparent state under strain or temperature stimuli, with the transition strains or temperatures highly dependent on the concentration of long‐chain flexible spacers. Information encrypted by different LCE inks can be decrypted under specific strains or temperatures, leading to multi‐level protection of information security. Furthermore, with the combination of the phase transition of polydomain LCEs and the photothermal effect of multi‐walled carbon nanotubes (MWCNTs), we achieved a repeatable transient information display by using near‐infrared (NIR) light as a pen for writing. This study provides new insight into the development of advanced encryption materials with versatility and high security for broad applications.
A series of dual‐responsive polydomain liquid crystal elastomers (LCEs) are developed, which can change from opaque to transparent states under strain or temperature stimuli. The as‐prepared LCEs can achieve multi‐level information encryption based on strain response and real‐time, rewritable transient information display upon incorporating photothermal multi‐walled carbon nanotubes.
We propose a simple yet effective structural patch decomposition approach for multi-exposure image fusion (MEF) that is robust to ghosting effect. We decompose an image patch into three conceptually ...independent components: signal strength, signal structure, and mean intensity. Upon fusing these three components separately, we reconstruct a desired patch and place it back into the fused image. This novel patch decomposition approach benefits MEF in many aspects. First, as opposed to most pixel-wise MEF methods, the proposed algorithm does not require post-processing steps to improve visual quality or to reduce spatial artifacts. Second, it handles RGB color channels jointly, and thus produces fused images with more vivid color appearance. Third and most importantly, the direction of the signal structure component in the patch vector space provides ideal information for ghost removal. It allows us to reliably and efficiently reject inconsistent object motions with respect to a chosen reference image without performing computationally expensive motion estimation. We compare the proposed algorithm with 12 MEF methods on 21 static scenes and 12 deghosting schemes on 19 dynamic scenes (with camera and object motion). Extensive experimental results demonstrate that the proposed algorithm not only outperforms previous MEF algorithms on static scenes but also consistently produces high quality fused images with little ghosting artifacts for dynamic scenes. Moreover, it maintains a lower computational cost compared with the state-of-the-art deghosting schemes.
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