Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Objective: To develop a screening system for more rapid and sensitive mutation detection of autosomal dominant polycystic kidney disease (ADPKD) gene 1 (PKD1) by using denaturing high-performance liquid chromatography (DHPLC) protocol.... more
Objective: To develop a screening system for more rapid and sensitive mutation detection of autosomal dominant polycystic kidney disease (ADPKD) gene 1 (PKD1) by using denaturing high-performance liquid chromatography (DHPLC) protocol. Methods: Using genomic DNA as templates extracted from blood samples of 19 Han pedigrees with 67 family members, the complete codon areas were amplified by long-range PCR and nested PCR in succession, and then the PCR products were analyzed by DHPLC. The mutations from screened abnormal PCR products were confirmed by DNA sequencing, and then compared with the mutations identified by single strand conformation polymorphism (SSCP) before. Results: There were 14 mutations found in this study, including 10 missense, 1 insertion, 1 deletion and 2 nonsense mutations. Besides 12 mutations identified before, mutations nt32819G>A and nt37137T>C were the novel mutations found. The mutation detection ratio was 73.7%. Conclusion: This developed system via DHPLC can be used as a more effective approach for mutation detection of autosomal dominant polycystic kidney disease PKD1 in Hans.
Research Interests: Genetics, Molecular Biology, Biology, China, Medicine, and 15 moreHumans, Mutation, Female, Male, Pedigree, Middle Aged, Family Health, PKD, Genomic DNA, Adult, Asian Continental Ancestry Group, Base Sequence, Nonsense Mutation, DNA mutational analysis, and Autosomal Dominant Polycystic Kidney Disease
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This paper expands the work on distributionally robust newsvendor to incorporate moment constraints. The use of Wasserstein distance as the ambiguity measure is preserved. The infinite dimensional primal problem is formulated; problem of... more
This paper expands the work on distributionally robust newsvendor to incorporate moment constraints. The use of Wasserstein distance as the ambiguity measure is preserved. The infinite dimensional primal problem is formulated; problem of moments duality is invoked to derive the simpler finite dimensional dual problem. An important research question is: How does distributional ambiguity affect the optimal order quantity and the corresponding profits/costs? To investigate this, some theory is developed and a case study in auto sales is performed. We conclude with some comments on directions for further research.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve... more
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population....
Research Interests:
The distribution network voltage level is directly related to residents' normal use of electricity, in order to correctly predict the low-voltage distribution network voltage quality, to take timely and effective means to prevent... more
The distribution network voltage level is directly related to residents' normal use of electricity, in order to correctly predict the low-voltage distribution network voltage quality, to take timely and effective means to prevent low-voltage phenomenon, the article collects nine indicators to reflect the characteristics of low-voltage distribution network voltage quality which are mainline diameter, mainline type, branch line diameter, branch line type, power supply radius, distribution transformer capacity -load ratio, the three-phase load unbalance rate, single-phase-home number, reactive power compensation rate. Then the article establishes a self-organizing competitive neural network model to automatic cluster the samples into three kinds which are normal, existing low voltage risk and existing severe low voltage risk. Using the known practical result to compare with the calculation results will indicate that the network model has high accuracy and feasibility.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a... more
We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a mathematical programming model that decomposes the network into origin-destination pairs so that each pair can be treated as a single flight-leg problem. We first discuss that the proposed framework is quite generic in the sense that not only several well-known models from the literature fit into this framework, but also many single flight-leg models can be easily extended to a network setting through the prescribed construction. Then, we analyze the structure of the overall mathematical programming model and establish its relationship with other models frequently used in practice. The application of the proposed framework is illustrated through two examples based on static and dynamic single-leg models, respectively. These illustrative examples are then ben...
Research Interests:
Research Interests: Finance, Mathematics, Applied Mathematics, Computer Science, Economics, and 10 moreSemidefinite Programming, Iterated Function Systems, Numerical Analysis and Computational Mathematics, Interior Point Method, LINEAR PROGRAM, Optimal Solution, Interior Point Algorithm, quadratic convergence, Duality gap, and Path following
In this paper we present two algorithms for a machine allocation problem occurring in manufacturing systems. For the two algorithms presented we prove worst-case performance ratios of 2 and 3/2, respectively. The machine allocation... more
In this paper we present two algorithms for a machine allocation problem occurring in manufacturing systems. For the two algorithms presented we prove worst-case performance ratios of 2 and 3/2, respectively. The machine allocation problem we consider is a general convex resource allocation problem, which makes the algorithms applicable to a variety of resource allocation problems. Numerical results are presented for two real-life manufacturing systems.
Research Interests:
Research Interests: Mathematics, Applied Mathematics, Computer Science, Mathematical Programming, Economic Theory, and 11 moreAlgorithm, Location theory, Convex Programming, Large classes, Location, Economic Model, Numerical Analysis and Computational Mathematics, Location Problem, Ellipsoid Method, Ellipsoid, and Rate of Convergence
Research Interests: Mathematics, Applied Mathematics, Computer Science, Mathematical Programming, Stochastic Programming, and 10 morePortfolio Management, Decision Making Under Uncertainty, Mathematical Optimization, High performance, Convex Programming, Path Following Methods, Numerical Analysis and Computational Mathematics, Interior Point Method, Decomposition Algorithm, and Path following
In this paper, we introduce robust versions of the classical static and dynamic single-leg seat allocation models. These robust models take into account the inaccurate estimates of the underlying probability distributions. As observed by... more
In this paper, we introduce robust versions of the classical static and dynamic single-leg seat allocation models. These robust models take into account the inaccurate estimates of the underlying probability distributions. As observed by simulation experiments, it turns out that for these robust versions the variability compared to their classical counterparts is considerably reduced with a negligible decrease in average revenue.