Relations between multidimensional interval-valued variational problems and variational inequalities

summary:In this paper, we introduce a new class of variational inequality with its weak and split forms to obtain an $LU$-optimal solution to the multi-dimensional interval-valued variational problem, which is a wider class of interval-valued programming problem in operations research. Using the concept of (strict) $LU$-convexity over the involved interval-valued functionals, we establish equivalence relationships between the solutions of variational inequalities and the (strong) $LU$-optimal solutions of the multi-dimensional interval-valued variational problem. In addition, some applications are constructed to illustrate the established results

Improving Kidney Tumor Detection Accuracy Using Hybrid U-Net Segmentation

Kidney cancer stands as a significant factor in cancer-related mortality, highlighting the critical importance of early and precise tumor detection This study introduces a computer-aided approach using the KiTS19 dataset and a hybrid U-Net architecture. Manual tumor segmentation is resource-intensive and prone to errors. Leveraging the hybrid U-Net, known for its proficiency in medical image analysis, we achieve precise tumor identification. Our method involves initial kidney and tumor segmentation in high-resolution CT images, followed by region of interest (ROI) generation and benign/malignant tumor classification. The assessment conducted on the KiTS19 dataset demonstrates encouraging outcomes, with Dice coefficients of 0.974 for kidney segmentation and 0.818 for tumor segmentation, accompanied by a tumor classification accuracy rate of 94.3%.The hybrid U-Net’s advanced feature extraction and spatial context awareness contribute to these outcomes. By streamlining diagnosis, our approach has the potential to significantly improve patient outcomes. The use of the KiTS19 dataset ensures robustness across various clinical cases and imaging modalities. This method represents a valuable advancement in computer-aided kidney tumor detection, promising to enhance patient care

Well-posedness for generalized mixed vector variational-like inequality problems in Banach space

In this article, we focus to study about well-posedness of a generalized mixed vector variational-like inequality and optimization problems with aforesaid inequality as constraint. We establish the metric characterization of well-posedness in terms of approximate solution set.Thereafter, we prove the sufficient conditions of generalized well-posedness by assuming the boundedness of approximate solution set. We also prove that the well-posedness of considered optimization problems is closely related to that of generalized mixed vector variational-like inequality problems. Moreover, we present some examples to investigate the results established in this paper

Research Publications on Tourism Education: A Bibliometric Analysis of Dimensions (2010 – 2022)

The purpose of this paper is to examine the trends in published research articles on tourism education from 2010 to 2022. A total of 1210 articles indexed in Dimensions AI database were analyzed for the number of authors, journals, citations, collaborating institutions and source countries. The research publications in scholarly articles on tourism education shows a gradual increase with higher growth observed in the years 2017, 2020, and 2021. Prominent authors include Deale, Cynthia S., and Ateljevic, Irena, and, prominent institutions include Hong Kong Polytechnic University, China and the United States appeared to be the most productive country in terms of articles and citations. “Learning”, “Curriculum”, “Career”, “Internship program” and “Competencies & skills” were the most research topics. The paper offers valuable insights for researchers, identifying productive authors, institutions, and popular keywords used in tourism education

On nonsmooth multiobjective fractional programming problems involving (p, r)− ρ −(η ,θ)- invex functions

A class of multiobjective fractional programming problems (MFP) is considered where the involved functions are locally Lipschitz. In order to deduce our main results, we introduce the definition of (p,r)−ρ −(η,θ)-invex class about the Clarke generalized gradient. Under the above invexity assumption, sufficient conditions for optimality are given. Finally, three types of dual problems corresponding to (MFP) are formulated, and appropriate dual theorems are proved

A Modified Approach of OPTICS Algorithm for Data Streams

Data are continuously evolving from a huge variety of applications in huge volume and size. They are fast changing, temporally ordered and thus data mining has become a field of major interest. A mining technique such as clustering is implemented in order to process data streams and generate a set of similar objects as an individual group. Outliers generated in this process are the noisy data points that shows abnormal behavior compared to the normal data points. In order to obtain the clusters of pure quality outliers should be efficiently discovered and discarded. In this paper, a concept of pruning is applied on the stream optics algorithm along with the identification of real outliers, which reduces memory consumption and increases the speed for identifying potential clusters

The Effect of Dietary Nitrate and Vitamin C on Endothelial Function, Oxidative Stress and Blood Lipids in Untreated Hypercholesterolemic Subjects: A Randomized Double-Blind Crossover Study

BACKGROUND: Vitamin C may enhance nitric oxide (NO) production through stepwise reduction of dietary nitrate (NO3) to nitrite (NO2) to NO. The combined effect of vitamin C and NO3 supplementation is relatively unexplored in untreated hypercholesterolemia. AIMS: We aimed to examine whether co-administration of vitamin C and nitrate for 4-weeks would improve endothelial function (primary outcome), plasma NO metabolites, oxidative stress, and blood lipids (secondary outcomes). METHODS: Subjects 50–70 years of age with low density lipoprotein (LDL) \u3e 130 mg/dL and RHI ≤ 2 were enrolled in this randomized double-blind crossover study. Subjects were assigned to two 4-week supplementation treatments starting with 70 ml of concentrated beetroot juice (CBJ) with 1000 mg of vitamin C (NC) or CBJ with matched placebo (N), then switched to alternate treatment following 2-week washout. The change in reactive hyperemia index (RHI), sum of plasma NO metabolites (NO2 + NO3 (NOx)), oxidized LDL (oxLDL), and serum lipids were assessed at baseline and at 4-weeks of each treatment period. RESULTS: Eighteen subjects (11M:7F) completed all study visits. No significant treatment differences were observed in RHI change (N: 0.21 ± 0.12; NC: 0.20 ± 0.17; p = 0.99). Secondary analysis revealed that a subgroup of NC subjects who started with a baseline RHI of \u3c 1.67 (threshold value for ED) had greater improvements in RHI compared to subjects with RHI \u3e 1.67 (1.23 ± 0.15 to 1.96 ± 0.19; n = 8 vs. 1.75 ± 0.11 to 1.43 ± 0.10; n = 8; p = 0.02). Compared to N, NC experienced a significant increase in plasma NOx (N: 94.2 ± 15.5 μmol/L; NC: 128.7 ± 29.1 μmol/L; p = 0.01). Although there was no significant difference in oxLDL change between treatments (N: −1.08 ± 9.8 U/L; NC: −6.07 ± 9.14 U/L; p = 0.19), NC elicited significant reductions in LDL (N: 2.2 ± 2; NC: −10.7 ± 23; p = 0.049), triglycerides (N: 14.6 ± 43; NC: −43.7 ± 45; p = 0.03), and no change in serum high density lipoprotein. Within treatment group comparisons showed that only NC reduced oxLDL significantly from baseline to 4 weeks (p = 0.01). CONCLUSIONS: No between intervention differences were observed in RHI. RHI only improved in NC subjects with ED at intervention baseline. Four weeks of NC enriched the NO pool and promoted reduction of blood lipids and oxidative stress in subjects with hypercholesterolemia. These preliminary findings highlight a supplementation strategy that may reduce the progression of atherosclerotic disease and deserves further attention in studies using flow mediated dilation methods. CLINICAL TRIAL REGISTRATION: www.clinicaltrials.gov (NCT04283630)