Zero-Regret Performative Prediction Under Inequality Constraints

Performative prediction is a recently proposed framework where predictions guide decision-making and hence influence future data distributions. Such performative phenomena are ubiquitous in various areas, such as transportation, finance, public policy, and recommendation systems. To date, work on performative prediction has only focused on unconstrained scenarios, neglecting the fact that many real-world learning problems are subject to constraints. This paper bridges this gap by studying performative prediction under inequality constraints. Unlike most existing work that provides only performative stable points, we aim to find the optimal solutions. Anticipating performative gradients is a challenging task, due to the agnostic performative effect on data distributions. To address this issue, we first develop a robust primal-dual framework that requires only approximate gradients up to a certain accuracy, yet delivers the same order of performance as the stochastic primal-dual algorithm without performativity. Based on this framework, we then propose an adaptive primal-dual algorithm for location families. Our analysis demonstrates that the proposed adaptive primal-dual algorithm attains \ca{O}(\sqrt{T}) regret and constraint violations, using only $\sqrt{T} + 2T$ samples, where $T$ is the time horizon. To our best knowledge, this is the first study and analysis on the optimality of the performative prediction problem under inequality constraints. Finally, we validate the effectiveness of our algorithm and theoretical results through numerical simulations

Empirical approximation to invariant measures of non-degenerate McKean--Vlasov dynamics

This paper studies the approximation of invariant measures of McKean--Vlasov dynamics with non-degenerate additive noise. While prior findings necessitated a strong monotonicity condition on the McKean--Vlasov process, we expand these results to encompass dissipative and weak interaction scenarios. Utilizing a reflection coupling technique, we prove that the empirical measures of the McKean--Vlasov process and its path-dependent counterpart can converge to the invariant measure in the Wasserstein metric. The Curie--Weiss mean-field lattice model serves as a numerical example to illustrate empirical approximation.Comment: 21 pages, 1 figur

Investigating Determinants of Voting for the “Helpfulness” of Online Consumer Reviews: A Text Mining Approach

The “helpfulness” feature of online user reviews helps consumers cope with information overloads and facilitates decision making. However, many online user reviews lack sufficient helpfulness votes for other users to evaluate their true helpfulness level. This study empirically examines the impact of the various features, that is, basic, stylistic, and semantic, of online user reviews on the number of helpfulness votes those reviews receive. Text mining techniques are employed to extract semantic characteristics from review texts. Our findings show that the semantic characteristics are more influential than other characteristics in affecting how many helpfulness votes reviews receive. Our findings also suggest that reviews with extreme opinions receive more helpfulness votes than those with mixed or neutral opinions. This paper sheds light on the understanding of online users’ helpfulness voting behavior and the design of a better helpfulness voting mechanism for online user review systems

Dupilumab for the treatment of prurigo nodularis: A systematic review

BackgroundConventional treatment techniques have limited efficacy and more side effects in the treatment of prurigo nodularis. The better alternative treatment option for better outcomes of the disease is dupilumab.ObjectiveThe objective of this study was to systematically review dupilumab-related treatment outcomes in prurigo nodularis.MethodsSeveral databases like Embase, PubMed, Web of Science, and Cochrane library were searched for data acquisition on October 8, 2022. Based on Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, 24 publications were included in this study.ResultsAfter 4,12,16 and more than 16 weeks of dupilumab treatment, 8.3% (n=5/60), 34.4% (n=11/32), 3.6% (n=2/56), and 45.3% (n=29/64) of patients had complete remission, respectively. In addition, 85.0% (n=51/60), 59.4% (n=19/32), 83.9% (n=47/56), and 43.8% (n=28/64) had partial remission, respectively. Moreover, 6.7% (n=4/60), 6.3% (n=2/32), 12.5% (n=7/56), and 10.9% (n=7/64) showed no remission, respectively, and significant reduction of numeric rating scale itch intensity (from 9.0 to 4.9, 2.1, 2.8, 0.9) was attained. There were no serious adverse events observed during treatment, but the most common event observed was conjunctivitis (12.6%, n=15/119).ConclusionsDupilumab has definite effectiveness and safety in prurigo nodularis treatment.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier (CRD42022365802)

Current Status of the Chinese National Twin Registry

The Chinese National Twin Registry is the first and largest population-based twin registry in China. It was established in 2001. The primary goal of this program is the establishment of a population-based twin registry of 45,000 twin pairs from several regions representing north, south, urban, and rural areas in China. A secondary goal is to study genetic contributions to complex diseases, and to test associations of candidate genes with related phenotypes. Seven thousand, four hundred and twenty-three twin pairs have been enrolled in the registry in which 1613 pairs have undergone detailed questionnaire assessments and physical examination. Based on the baseline registry, a twin cohort was established. Continued research includes studies on intermediate phenotypes of cardiovascular and cerebrovascular diseases and psychological studies in adult twins, studies on growth and development in adolescent twins, and so forth. The current state and future plans for the Chinese National Twin Registry will be discussed in this article.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000243216600009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Genetics & HeredityObstetrics & GynecologySCI(E)PubMed17ARTICLE6747-752

Enabling Efficient Fuzzy Keyword Search over Encrypted Data in Cloud Computing

As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. For the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only \emph{exact} keyword search. That is, there is no tolerance of minor typos and format inconsistencies which, on the other hand, are typical user searching behavior and happen very frequently. This significant drawback makes existing techniques unsuitable in Cloud Computing as it greatly affects system usability, rendering user searching experiences very frustrating and system efficacy very low. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users\u27 searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop two advanced techniques on constructing fuzzy keyword sets, which achieve optimized storage and representation overheads. We further propose a brand new symbol-based trie-traverse searching scheme, where a multi-way tree structure is built up using symbols transformed from the resulted fuzzy keyword sets. Through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution

Expression and Clinical Significance of MIS18BP1 in Bladder Cancer Tissues

Objective To explore the expression, correlation with clinicopathologic parameters, and clinical significance of MIS18 binding protein 1 (MIS18BP1) in bladder cancer. Methods TCGA and GEO databases were used to analyze the mRNA expression of MIS18BP1 in tumors and controls, and the results were verified via qRT-PCR. UALCAN online database was utilized in the analysis of the expression of MIS18BP1 and its correlation with clinicopathological parameters and the degree of immune cell infiltration. Immunohistochemistry was employed to analyze the expression of MIS18BP1 in bladder cancer and its relationship with clinicopathological features. The ROC curve was applied to evaluate the diagnostic value of MIS18BP1 mRNA in bladder cancer. Results Bioinformatics analysis and qRT-PCR results revealed the increased expression of MIS18BP1 mRNA in bladder cancer compared with that in the control group (P<0.05). Immunohistochemistry unveiled the significantly high positive rate of MIS18BP1 protein in bladder cancer (P<0.05) and its correlation with the clinical stage of tumors, depth of invasion, and lymph node metastasis (P<0.05). The immune infiltration analysis showed the association of MIS18BP1 with immune cell infiltration in bladder cancer. Conclusion The increased expression level of MIS18BP1 gene and protein in bladder cancer may regulate the development of bladder cancer by influencing immune cell infiltration

Identification and Functional Characterization of Squamosa Promoter Binding Protein-Like Gene TaSPL16 in Wheat (Triticum aestivum L.)

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Squamosa promoter binding protein-like (SPL) proteins are plant-specific transcript factors and play critical roles in plant growth and development. The functions of many SPL gene family members were well characterized in Arabidopsis and rice, in contrast, research on wheat SPL genes is lagging behind. In this study, we cloned and characterized TaSPL16, an orthologous gene of rice OsSPL16, in wheat. Three TaSPL16 homoeologs are located on the short arms of chromosome 7A, 7B, and 7D, and share more than 96% sequence identity with each other. All the TaSPL16 homoeologs have three exons and two introns, with a miR156 binding site in their last exons. They encode putative proteins of 407, 409, and 414 amino acid residues, respectively. Subcellular localization showed TaSPL16 distribution in the cell nucleus, and transcription activity of TaSPL16 was validated in yeast. Analysis of the spatiotemporal expression profile showed that TaSPL16 is highly expressed in young developing panicles, lowly expressed in developing seeds and almost undetectable in vegetative tissues. Ectopic expression of TaSPL16 in Arabidopsis causes a delay in the emergence of vegetative leaves (3–4 days late), promotes early flowering (5–7 days early), increases organ size, and affects yield-related traits. These results demonstrated the regulatory roles of TaSPL16 in plant growth and development as well as seed yield. Our findings enrich the existing knowledge on SPL genes in wheat and provide valuable information for further investigating the effects of TaSPL16 on plant architecture and yield-related traits of wheat