An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment

The aim of this paper is to develop an interactive approach for multiple attribute decision making with incomplete weight information under linguistic environment. Some of the concepts are defined, such as the distance between two 2-tuple linguistic variables, the expectation level of alternative, the achievement scale, the alternative comprehensive scale under linguistic environment. Based on these concepts, we establish some linear programming models, through which the decision maker interacts with the analyst. Furthermore, we establish a practical interactive approach for selecting the most desirable alternative(s). The interactive process can be realized by giving and revising the achievement scale and comprehensive scale of alternatives till the achievement scale and the comprehensive scale are achieved to the decision maker’s request. Finally, an illustrative example is also given.The author is very grateful to the associated editor and two anonymous referees for their insightful and constructive comments and suggestions that have led to an improved version of this paper. This work was partly supported by the National Natural Science Foundation of China (No. 90924027, No. 71101043), National Basic Research Program of China (973 Program, No. 2010C B951104), Key Program of National Social Science Foundation of China (No. 10AJY005), College Philosophy and Social Science Research Project of Jiangsu Province under Grant 2011SJD630007.Xu, Y.; Wang, H.; Palacios Marqués, D. (2013). An Interactive Approach Based on Alternative Achievement Scale and Alternative Comprehensive Scale for Multiple Attribute Decision Making under Linguistic Environment. International Journal of Computational Intelligence Systems. 6(1):87-95. https://doi.org/10.1080/18756891.2013.756226S87956

Two-year results after combined phacoemulsification and iris-fixated phakic intraocular lens removal

Purpose To describe and present results after a technique for cataract surgery combined with explantation of an iris-fixated phakic intraocular lens (IF-pIOL).Methods The medical records of all patients, who had undergone cataract surgery combined with IF-pIOL explantation and subsequent implantation of a posterior chamber IOL by the Single Incision Technique (SIT), were reviewed. Data collection included preoperative and postoperative corrected distance visual acuity (CDVA), manifest refraction, and endothelial cell density (ECD) up to a follow-up time of 24 months.Results Fifty myopic eyes (34 patients) and 9 hyperopic eyes (6 patients) had undergone a SIT procedure mainly because of cataract (67%). Postoperative CDVA improved in both the myopic eyes to 0.16 +/- 0.37 logMAR, as in the hyperopic eyes to - 0.10 +/- 0.55 logMAR with no eyes having loss of Snellen lines. Mean postoperative spherical equivalent was - 0.34 +/- 0.72 D and - 0.10 +/- 0.55 D, respectively. ECD loss 6 months after surgery was 5% and remained stable thereafter.Conclusion SIT for combined phacoemulsification and IF-pIOL removal yields good visual and refractive results and is a safe procedure in regard to ECD loss. The technique has advantages over the conventional procedure and is easy to perform.Neuro Imaging Researc

Implantation of an iris-fixated phakic intraocular lens for the correction of hyperopia: 15-year follow-up

Purpose: To assess the predictability, efficacy, stability, and safety of implantation of an Artisan iris-fixated phakic intraocular lens (IF-pIOL) for the correction of hyperopia with a follow-up of up to 15 years.Setting: Leiden University Medical Center, the Netherlands.Methods: Patients operated by a single surgeon up to 2007 were identified, and data on refraction, corrected distance visual acuity (CDVA), uncorrected distance visual acuity, endothelial cell (EC) density, and complications were collected.Results: A total of 61 eyes (32 patients) were analysed. The mean spherical equivalent decreased from +6.43 +/- 1.78 diopters (D) preimplantation to -0.22 +/- 0.57 D at 1 year postimplantation and remained stable throughout follow-up. A stable CDVA with safety indices ranging from 0.91 to 1.10 and efficacy indices between 0.43 and 0.86 were observed. Follow-up time had a significant effect on EC density with an estimated annual decline of 58 cells/mm(2) after IF-pIOL implantation. IF-pIOL explantation was performed in a 10 eyes (16.4%) after 8.13 +/- 5.11 years. The main reason for IF-pIOL explantation was EC loss (4 eyes [6.6%]). Pigment dispersion was the most encountered complication, observed in 9 eyes ( 14.8%).Conclusions: Visual and refractive results after implantation of an IF- pIOL to correct hyperopia show favorable and stable results with long-term follow- up. Lifelong monitoring of EC counts is mandatory. Pigment dispersion might be a problem in hyperopic eyes implanted with an IF-pIOL; a shallower anterior chamber depth and a convex iris configuration might be predisposing factors. Copyright (C) 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of ASCRS and ESCRSNeuro Imaging Researc

Predicting high-risk patients using the International IGA Nephropathy risk prediction tool: a preliminary single-centre analysis

Introduction The International IgA Nephropathy Risk Prediction Tool (IgAN- RPT) has been utilized to predict renal progression up to 5 or 7 years after biopsy via histological and clinical risk factors. We reported the preliminary analysis of the renal outcome of IgAN patients in relation to their predicted risk based on the IgAN-RPT at biopsy. Methods We included 29 biopsy-proven adult IgAN patients diagnosed between 2010 and 2017. The IgAN-RPT predicted risk score at 5 years was calculated for each patient. The primary outcome was the risk of developing a 50% decline in the estimated glomerular filtration rate (eGFR) or end stage renal disease (ESRD) at 5 years after biopsy. Independent Student T-test and chi-square analysis were used to compare the clinical data between groups, while Kaplan-Meier survival analysis was done to compare the predicted and observed outcomes within risk groups using SPSS 26 (2020; IBM Corp., Armonk, NY, USA). Results Our cohort consisted of 13 Chinese, 12 Malay and 4 Indian patients with a mean eGFR of 68.2 (±5.7) at biopsy. The median 5-year IgAN-RPT risk score was 13.12% (IQR: 6.02 to 28.00). 20.7% (n=6) reached the primary outcome. Statistically significant; lower mean serum albumin level [30.5 ± 3.3 versus 38.0 ± 6.9, t=2.571 (27), p= 0.016], higher proportion of not using RAS blocker [100.0% versus 11.5%, χ2 = 10.9 (2), p=0.004] and higher proportion of using immunosuppression at biopsy [36.4% versus 5.9%, χ2 =7.54 (2), p=0.023] were noted among these patients. At this preliminary point, none of the other clinical data was significant, thus no further multivariate analyses were performed. To compare the predicted and observed outcomes within the risk group, a cut-off point of 30% for the predicted risk was determined by calculating the Youden Index of a receiving operating curve plotted between the predicted outcome versus observed outcome at 5 years. Results showed well-separated curves between the two risk groups, indicating a good discriminant ability of the tool among our patients. Conclusions Our study demonstrated the median 5-year 1gAN-RPT risk score among our patients was 13.12% with 20.7% of them reaching the primary outcome. Moreover, a cut-off of 30% IgAN- RPT predicted score could discriminate between high-risk versus low-risk patients to develop ESRD or a 50% decline in eGFR in this population. No conflict of interes

Clustering Algorithms: Their Application to Gene Expression Data

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and iden-tify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure

Search for leptophobic Z ' bosons decaying into four-lepton final states in proton-proton collisions at root s=8 TeV

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Search for black holes and other new phenomena in high-multiplicity final states in proton-proton collisions at root s=13 TeV

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Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

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Search for high-mass diphoton resonances in proton-proton collisions at 13 TeV and combination with 8 TeV search

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