プライバシーを考慮したデータ取引に関する研究

京都大学新制・課程博士博士(情報学)甲第24933号情博第844号京都大学大学院情報学研究科社会情報学専攻(主査)教授 伊藤 孝行, 教授 鹿島 久嗣, 教授 岡部 寿男, 阿部 正幸(NTT社会情報研究所)学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDGA

Secure Shapley Value for Cross-Silo Federated Learning

The Shapley value (SV) is a fair and principled metric for contribution evaluation in cross-silo federated learning (cross-silo FL), wherein organizations, i.e., clients, collaboratively train prediction models with the coordination of a parameter server. However, existing SV calculation methods for FL assume that the server can access the raw FL models and public test data. This may not be a valid assumption in practice considering the emerging privacy attacks on FL models and the fact that test data might be clients' private assets. Hence, we investigate the problem of secure SV calculation for cross-silo FL. We first propose HESV, a one-server solution based solely on homomorphic encryption (HE) for privacy protection, which has limitations in efficiency. To overcome these limitations, we propose SecSV, an efficient two-server protocol with the following novel features. First, SecSV utilizes a hybrid privacy protection scheme to avoid ciphertext--ciphertext multiplications between test data and models, which are extremely expensive under HE. Second, an efficient secure matrix multiplication method is proposed for SecSV. Third, SecSV strategically identifies and skips some test samples without significantly affecting the evaluation accuracy. Our experiments demonstrate that SecSV is 7.2-36.6 times as fast as HESV, with a limited loss in the accuracy of calculated SVs.Comment: Extened report for our VLDB 2023 pape

Higher superconducting transition temperature by breaking the universal pressure relation

By investigating the bulk superconducting state via dc magnetization measurements, we have discovered a common resurgence of the superconductive transition temperatures (Tcs) of the monolayer Bi2Sr2CuO6+{\delta} (Bi2201) and bilayer Bi2Sr2CaCu2O8+{\delta} (Bi2212) to beyond the maximum Tcs (Tc-maxs) predicted by the universal relation between Tc and doping (p) or pressure (P) at higher pressures. The Tc of under-doped Bi2201 initially increases from 9.6 K at ambient to a peak at ~ 23 K at ~ 26 GPa and then drops as expected from the universal Tc-P relation. However, at pressures above ~ 40 GPa, Tc rises rapidly without any sign of saturation up to ~ 30 K at ~ 51 GPa. Similarly, the Tc for the slightly overdoped Bi2212 increases after passing a broad valley between 20-36 GPa and reaches ~ 90 K without any sign of saturation at ~ 56 GPa. We have therefore attributed this Tc-resurgence to a possible pressure-induced electronic transition in the cuprate compounds due to a charge transfer between the Cu 3d_(x^2-y^2 ) and the O 2p bands projected from a hybrid bonding state, leading to an increase of the density of states at the Fermi level, in agreement with our density functional theory calculations. Similar Tc-P behavior has also been reported in the trilayer Br2Sr2Ca2Cu3O10+{\delta} (Bi2223). These observations suggest that higher Tcs than those previously reported for the layered cuprate high temperature superconductors can be achieved by breaking away from the universal Tc-P relation through the application of higher pressures.Comment: 13 pages, including 5 figure

Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations

Computer simulations offer a robust toolset for exploring complex systems across various disciplines. A particularly impactful approach within this realm is Agent-Based Modeling (ABM), which harnesses the interactions of individual agents to emulate intricate system dynamics. ABM's strength lies in its bottom-up methodology, illuminating emergent phenomena by modeling the behaviors of individual components of a system. Yet, ABM has its own set of challenges, notably its struggle with modeling natural language instructions and common sense in mathematical equations or rules. This paper seeks to transcend these boundaries by integrating Large Language Models (LLMs) like GPT into ABM. This amalgamation gives birth to a novel framework, Smart Agent-Based Modeling (SABM). Building upon the concept of smart agents -- entities characterized by their intelligence, adaptability, and computation ability -- we explore in the direction of utilizing LLM-powered agents to simulate real-world scenarios with increased nuance and realism. In this comprehensive exploration, we elucidate the state of the art of ABM, introduce SABM's potential and methodology, and present three case studies (source codes available at https://github.com/Roihn/SABM), demonstrating the SABM methodology and validating its effectiveness in modeling real-world systems. Furthermore, we cast a vision towards several aspects of the future of SABM, anticipating a broader horizon for its applications. Through this endeavor, we aspire to redefine the boundaries of computer simulations, enabling a more profound understanding of complex systems.Comment: Source codes are available at https://github.com/Roihn/SAB

Transcription Factor NFAT5 Promotes Glioblastoma Cell-driven Angiogenesis via SBF2-AS1/miR-338-3p-Mediated EGFL7 Expression Change

Glioblastoma (GBM) is the most aggressive primary intracranial tumor of adults and confers a poor prognosis due to high vascularization. Hence anti-angiogenic therapy has become a promising strategy for GBM treatment. In this study, the transcription factor nuclear factor of activated T-cells 5 (NFAT5) was significantly elevated in glioma samples and GBM cell lines, and positively correlated with glioma WHO grades. Knockdown of NFAT5 inhibited GBM cell-driven angiogenesis. Furthermore, long non-coding RNA SBF2 antisense RNA 1 (SBF2-AS1) was upregulated in glioma samples and knockdown of SBF2-AS1 impaired GBM-induced angiogenesis. Downregulation of NFAT5 decreased SBF2-AS1 expression at transcriptional level. In addition, knockdown of SBF2-AS1 repressed GBM cell-driven angiogenesis via enhancing the inhibitory effect of miR-338-3p on EGF like domain multiple 7 (EGFL7). In vivo study demonstrated that the combination of NFAT5 knockdown and SBF2-AS1 knockdown produced the smallest xenograft volume and the lowest microvessel density. NFAT5/SBF2-AS1/miR-338-3p/EGFL7 pathway may provide novel targets for glioma anti-angiogenic treatment

Anxiety mediates association between sex and jaw function limitation in temporomandibular disorder patients from China

AimThe objective of this study is to explore the relationship between sex and jaw function and to test whether anxiety mediates the causal relationship between sex and jaw function in temporomandibular disorders (TMDs) patients.MethodsA total of 488 participants with TMD were included in the analysis. Demographic data were collected. Generalized anxiety symptoms and anxiety severity were initially assessed using the GAD-7 questionnaire. And jaw function limitation was measured using the JFLS-8 scale. A directed acyclic graph (DAG) was used in this study to evaluate the hypotheses. Mediation analysis was conducted to explore causality and to calculate the total effect, natural direct effect (NDE) and natural indirect effect (NIE).ResultsIn TMD patients, there was a significant association between female and jaw function (r = 0.17, p < 0.001), female and anxiety (r = 0.15, p = 0.002), anxiety and jaw function (r = 0.35, p < 0.001). In addition, sex can directly lead to differences in impaired jaw function (NDE: 3.719, 95% CI: 1.619–5.828, p < 0.001), and can also be causally related to jaw function through anxiety (NIE: 1.146, 95% CI: 0.267–2.024, p = 0.011). And the total effect was 4.865 (95% CI, 2.709–7.029, p < 0.001).ConclusionA causal mechanism was found that anxiety acts as a mediator of sex effects on jaw function. Therefore, psychological factors need to be taken into account in the treatment of female TMD patients. Further clinical trials are needed to explore whether psychotherapy is more beneficial to improve jaw function in female TMD patients

EXAMINING HETEROGENEITY OF CELLULAR SENESCENCE WITH MULTIPLEXING IMMUNOLABELING

Aging has become an arising prominent problem that has received more and more attention. Cellular senescence is thought to be a key contributor to the aging process. A deeper understanding of cellular senescence could lead to the development of novel therapies to promote healthy aging and prevent or treat age-related diseases. However, cellular senescence is a heterogeneous phenomenon that can vary in terms of its triggers, phenotypes, and functional consequences, which poses a challenge to the development of therapies targeting senescence. Here, we try to reveal the heterogeneity with the single-cell imaging analysis platform and figure out some different subpopulations of senescent cells with morphological characteristics and protein expressions