MYC-SEPT11 Axis Promotes osteoblast differentiation and bone formation via PI3K/AKT and RhoA/ROCK signaling pathways - Yiwen Zhao; Zhenghuan Zhu; Haining Chen; Yu Song; Feng Wang; Zhihui Huang; Wenming Ma; Wenge Ding; Jinbo Liu (Functional & Integrative Genomics, 2026)

Design and fully coupled dynamic performance analysis of a novel wave-focusing-enhanced hybrid wind-wave energy system - Fang He; Haining Ding; Shunhang Lu; Chizhong Wang (Ocean Engineering, 2026)

Effects of freeze-thaw cycle on soil greenhouse gas emissions depend on freezing duration: A meta-analysis - Ying Wang; Haining Zhang; Liming Yin; Junxia Ding; Ruiqiang Liu; Yanghui He; Xuhui Zhou (Pedobiologia, 2026)

ESPNP promotes cell migration and invasion in gastric cancer cells via regulation of epithelial-mesenchymal transition/Twist1 - Weibing Li; Haiyang Zhang; Xiangyuan Ding; Haining Ma (Journal of Molecular Histology, 2026)

Hybrid framework combining machine learning with mechanism models for enhanced forecasting of biomass gasification products - Jiaming Song; Zongqi Chen; Haining Tang; Hong Ding; Shiliang Wu; Zhou Liu; Feng Gong (Bioresource Technology, 2026)

Characterization of intestinal microbiota in patients with psoriasis combined with metabolic syndrome - Yiyue Yuan; Linna Zhao; Haining Ding; Yinshuang Hua; Hongmei Wang; Manlin Zhao (Molecular and Cellular Biochemistry, 2025)

Mechanical properties of CFRP grid reinforced 3D printed concrete arch structures - Tao Ding; Zechen Peng; Haining Dong (Engineering Structures, 2025)

Efficiency and mechanism of a novel La-based hydrogel designed for controlling lake eutrophication: Insight from phosphorus release characteristics of sediment, sulfur-driven autotrophic denitrification and cyanobacterial bloom response - Qinyi Chen; Zhicong Wang; Bingjie Zhao; Haining Huang; Yuchen Geng; Yuang Ding; Dunhai Li (Water Research, 2025)

New insights into odor release from sediments in Lake Chaohu and the potential role of sediment microbial communities - Haining Huang; Qinyi Chen; Yuang Ding; Bingjie Zhao; Zhicong Wang; Dunhai Li (Journal of Hazardous Materials, 2025)

Derivation and genetic-screening of human haploid trophoblast stem cells - Wenhao Zhang; Qing Wang; Shengyi Sun; Yan Liu; Yiding Zhao; Haining Luo; Chunmeng Yao; Yun Sun; Dan Ding; Ying Chang; Qian Gao; Ling Shuai (Science Bulletin, 2025)

Fabrication of a disposable aptasensing chip for simultaneous label-free detection of four common coexisting mycotoxins - Jing Qian; Yue Liu; Haining Cui; Huiyuan Yang; Mustafa Hussain; Kun Wang; Jie Wei; Lingliang Long; Lijun Ding; Chengquan Wang (Analytica Chimica Acta, 2023)

Variational Bayesian Inference Time Delay Estimation for Passive Sonars - Feilong Ding; Cheng Chi; Yu Li; Haining Huang (Journal of Marine Science and Engineering, 2023)
In passive sonars, distance and depth estimation of underwater targets is often limited by the accuracy of time delay estimations. The estimation accuracy of the existing methods of time delay estimation is limited by the uniform discrete grid (signal sampling rate). When a true time delay is out of the grid, the estimation accuracy deteriorates due to the mismatch between the real-time delay and the discrete grid. This paper proposes a new method for time delay estimation, which realizes the time delay estimation under the framework of variational Bayesian inference. The proposed method is grid-less, that is, continuous in the time domain. Unlike the popular grid-less compressive time delay estimation method, this method does not require parameter adjustment, and can automatically estimate the number of time delays, noise variance, and amplitude variance. The simulation results showed that the performance of the proposed method was superior to the reference state-of-the-art time delay estimation methods.

Parametric Knocking Performance Investigation of Spark Ignition Natural Gas Engines and Dual Fuel Engines - La Xiang; Gerasimos Theotokatos; Haining Cui; Keda Xu; Hongkai Ben; Yu Ding (Journal of Marine Science and Engineering, 2020)
Both spark ignition (SI) natural gas engines and compression ignition (CI) dual fuel (DF) engines suffer from knocking when the unburnt mixture ignites spontaneously prior to the flame front arrival. In this study, a parametric investigation is performed on the knocking performance of these two engine types by using the GT-Power software. An SI natural gas engine and a DF engine are modelled by employing a two-zone zero-dimensional combustion model, which uses Wiebe function to determine the combustion rate and provides adequate prediction of the unburnt zone temperature, which is crucial for the knocking prediction. The developed models are validated against experimentally measured parameters and are subsequently used for performing parametric investigations. The derived results are analysed to quantify the effect of the compression ratio, air-fuel equivalence ratio and ignition timing on both engines as well as the effect of pilot fuel energy proportion on the DF engine. The results demonstrate that the compression ratio of the investigated SI and DF engines must be limited to 11 and 16.5, respectively, for avoiding knocking occurrence. The ignition timing for the SI and the DF engines must be controlled after −38°CA and 3°CA, respectively. A higher pilot fuel energy proportion between 5% and 15% results in increasing the knocking tendency and intensity for the DF Engine at high loads. This study results in better insights on the impacts of the investigated engine design and operating settings for natural gas (NG)-fuelled engines, thus it can provide useful support for obtaining the optimal settings targeting a desired combustion behaviour and engine performance while attenuating the knocking tendency.