Study on settlement prediction of soft ground considering multiple feature parameters based on ISSA-RF model.

By collecting a large amount of data from various preloading engineering projects, a settlement prediction database was established including up to 15 feature parameters, such as final measured time, magnitude of surcharge loading, porosity ratio, internal friction angle, and others. Furthermore, a settlement prediction model of soft foundation based on random forest (RF) model was also developed. To enhance the accuracy of settlement prediction, the improved sparrow search algorithm (ISSA), which incorporates several enhancements such as the use of Logistic-tent chaotic mapping, adaptive nonlinear inertia-decreasing weight parameters, and Levy flight strategy, was proposed to optimize the hyperparameters of the RF model. The optimization results of various algorithms on benchmark functions revealed that the ISSA algorithm excelled in terms of accuracy and stability when compared to conventional algorithms such as particle swarm optimization and butterfly optimization. The ISSA-RF settlement prediction model was subsequently constructed and applied to practical projects. The results demonstrated that the ISSA-RF model exhibited superior prediction accuracy and applicability compared to the RF model. It can therefore provide valuable guidance for the planning and implementation of preloading engineering projects.

Copine 7 promotes colorectal cancer proliferation through PKM2 interaction and MAPK signaling pathway.

Introduction: Colorectal cancer (CRC) is currently the third most common cancer in the world, and its prevalence and mortality rate continue to increase. Methods: Based on an analysis of The Cancer Genome Atlas database, Tumor Immune Estimation Resource and Gene Expression Profiling Interactive Analysis, we explored the expression of CPNE7 in tumors. Immunohistochemistry and quantitative polymerase chain reaction analysis the expression of CPNE7 in colorectal cancer. Our study explored how CPNE7 promotes CRC cell proliferation and migration in vitro and in vivo. Transcriptome sequencing and Co-IP assay explored the underlying mechinaism of CPNE7 founction. Results: We found the CPNE7 was overexpressed in CRC by database and IHC. CPNE7 promoted CRC cells proliferstion and migration in vitro and in vivo. Comparing and analyzing transcriptome sequencing between exogenous up-/downregulated CPNE7 CRC cells and the controls, we found that CPNE7 activates mitogen-activated protein kinase (MAPK) signaling pathway stimulating cancer cell proliferation. Coimmunoprecipitation experiments revealed an interaction between CPNE7 and pyruvate kinase muscle protein (PKM2). We also found the activity of MAPK signaling is regulated by exogenous CPNE7 expression. Discussion: These results imply that CPNE7 may promote the progression of CRC by interacting with PKM2 and initiating the MAPK signaling pathway.

Performance Analysis of Motion-Sensor Behavior for User Authentication on Smartphones.

The growing trend of using smartphones as personal computing platforms to access and store private information has stressed the demand for secure and usable authentication mechanisms. This paper investigates the feasibility and applicability of using motion-sensor behavior data for user authentication on smartphones. For each sample of the passcode, sensory data from motion sensors are analyzed to extract descriptive and intensive features for accurate and fine-grained characterization of users' passcode-input actions. One-class learning methods are applied to the feature space for performing user authentication. Analyses are conducted using data from 48 participants with 129,621 passcode samples across various operational scenarios and different types of smartphones. Extensive experiments are included to examine the efficacy of the proposed approach, which achieves a false-rejection rate of 6.85% and a false-acceptance rate of 5.01%. Additional experiments on usability with respect to passcode length, sensitivity with respect to training sample size, scalability with respect to number of users, and flexibility with respect to screen size were provided to further explore the effectiveness and practicability. The results suggest that sensory data could provide useful authentication information, and this level of performance approaches sufficiency for two-factor authentication on smartphones. Our dataset is publicly available to facilitate future research.