The Power of Simple Menus in Robust Selling Mechanisms

We study a robust selling problem where a seller attempts to sell one item to a buyer but is uncertain about the buyer's valuation distribution. Existing literature indicates that robust mechanism design provides a stronger theoretical guarantee than robust deterministic pricing. Meanwhile, the superior performance of robust mechanism design comes at the expense of implementation complexity given that the seller offers a menu with an infinite number of options, each coupled with a lottery and a payment for the buyer's selection. In view of this, the primary focus of our research is to find simple selling mechanisms that can effectively hedge against market ambiguity. We show that a selling mechanism with a small menu size (or limited randomization across a finite number of prices) is already capable of deriving significant benefits achieved by the optimal robust mechanism with infinite options. In particular, we develop a general framework to study the robust selling mechanism problem where the seller only offers a finite number of options in the menu. Then we propose a tractable reformulation that addresses a variety of ambiguity sets of the buyer's valuation distribution. Our formulation further enables us to characterize the optimal selling mechanisms and the corresponding competitive ratio for different menu sizes and various ambiguity sets, including support, mean, and quantile information. In light of the closed-form competitive ratios associated with different menu sizes, we provide managerial implications that incorporating a modest menu size already yields a competitive ratio comparable to the optimal robust mechanism with infinite options, which establishes a favorable trade-off between theoretical performance and implementation simplicity. Remarkably, a menu size of merely two can significantly enhance the competitive ratio, compared to the deterministic pricing scheme

Using Shallow Platform Drilling Technology to Tap the Reserves of the Below Constructed Area of Fuyu Oilfield: Taking Chengping Block 12 as an Example

The special geographical conditions in the below constructed area of the surface have caused the poor oil-water well condition, incomplete well patterns, difficult measures for tapping potential, and no effective development of reserves, which have affected the comprehensive adjustment of Fuyu oilfield. In order to solve this problem, the shallow large platform horizontal well technology was studied in Fuyu oilfield by taking Chengping 12 reservoir as an example. This technology has been successfully applied under limited ground conditions, and underground reserves have been fully utilized. This study has laid a solid foundation for fuyu oilfield to increase recoverable reserves and achieve stable production during the 12th Five-year plan

Identification of Apo-A1 as a biomarker for early diagnosis of bladder transitional cell carcinoma

<p>Abstract</p> <p>Background</p> <p>Bladder transitional cell carcinoma (BTCC) is the fourth most frequent neoplasia in men, clinically characterized by high recurrent rates and poor prognosis. Availability of urinary tumor biomarkers represents a convenient alternative for early detection and disease surveillance because of its direct contact with the tumor and sample accessibility.</p> <p>Results</p> <p>We tested urine samples from healthy volunteers and patients with low malignant or aggressive BTCC to identify potential biomarkers for early detection of BTCC by two-dimensional electrophoresis (2-DE) coupled with mass spectrometry (MS) and bioinformatics analysis. We observed increased expression of five proteins, including fibrinogen (Fb), lactate dehydrogenase B (LDHB), apolipoprotein-A1 (Apo-A1), clusterin (CLU) and haptoglobin (Hp), which were increased in urine samples of patients with low malignant or aggressive bladder cancer. Further analysis of urine samples of aggressive BTCC showed significant increase in Apo-A1 expression compared to low malignant BTCC. Apo-A1 level was measured quantitatively using enzyme-linked immunosorbent assay (ELISA) and was suggested to provide diagnostic utility to distinguish patients with bladder cancer from controls at 18.22 ng/ml, and distinguish patients with low malignant BTCC from patients with aggressive BTCC in two-tie grading system at 29.86 ng/ml respectively. Further validation assay showed that Apo-A1 could be used as a biomarker to diagnosis BTCC with a sensitivity and specificity of 91.6% and 85.7% respectively, and classify BTCC in two-tie grading system with a sensitivity and specificity of 83.7% and 89.7% respectively.</p> <p>Conclusion</p> <p>Taken together, our findings suggest Apo-A1 could be a potential biomarker related with early diagnosis and classification in two-tie grading system for bladder cancer.</p

Mlsp : A bioinformatics tool for predicting molecular subtypes and prognosis in patients with breast cancer

The molecular landscape in breast cancer is characterized by large biological heterogeneity and variable clinical outcomes. Here, we performed an integrative multi-omics analysis of patients diagnosed with breast cancer. Using transcriptomic analysis, we identified three subtypes (cluster A, cluster B and cluster C) of breast cancer with distinct prognosis, clinical features, and genomic alterations: Cluster A was asso-ciated with higher genomic instability, immune suppression and worst prognosis outcome; cluster B was associated with high activation of immune-pathway, increased mutations and middle prognosis out-come; cluster C was linked to Luminal A subtype patients, moderate immune cell infiltration and best prognosis outcome. Combination of the three newly identified clusters with PAM50 subtypes, we pro-posed potential new precision strategies for 15 subtypes using L1000 database. Then, we developed a robust gene pair (RGP) score for prognosis outcome prediction of patients with breast cancer. The RGP score is based on a novel gene-pairing approach to eliminate batch effects caused by differences in heterogeneous patient cohorts and transcriptomic data distributions, and it was validated in ten cohorts of patients with breast cancer. Finally, we developed a user-friendly web-tool (https://sujiezhulab.shi-nyapps.io/BRCA/) to predict subtype, treatment strategies and prognosis states for patients with breast cancer.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).Peer reviewe

Multivariate analysis and optimal configuration of wind-photovoltaic complementary power generation system

Advantages of wind-solar complementary power generation system to utilize solar and wind energy in the aspect of resource and technical economy have been reviewed tersely. Convenience of entering and exiting generating equipment and load from DC as well as AC bus are interpreted briefly. The factors that affect the electrical power output of the system were analyzed and studied. Based on the law of energy conservation, the energetic matching algorithm was proposed which forms the foundation of optimal configuration of system. Finally, the intelligent control and on-line monitoring of wind-solar complementary power generation system were discussed

Research on Teaching Satisfaction under the Application of Social Media Tools from the Perspective of Multiple Incentives

Education big data has risen to China's national strategy, and the construction of education big data has ushered in major historical development opportunities (Zhang Wei, 2017). Social media, as the collector of the most micro-level education big data, supports the entire data ecology. Social media-based mixed teaching is changing the traditional classroom, but we still know very little about the current status of social media teaching, especially the internal and external environment of social media teaching for college teachers. In this study, a questionnaire survey was used to systematically investigate the satisfaction of college students with mixed teaching based on social media. The study found that in the mixed teaching process, teachers can have an impact on teaching results through multiple incentive modes; among them, spiritual and interactive incentives can have a significant impact on teaching satisfaction; this will provide a useful reference for college social media teaching. Promoting the transformation of the role of teachers in colleges and universities helps to promote the high development of education