Dye-based fluorescent organic nanoparticles made from polar and polarizable chromophores for bioimaging purposes: a bottom-up approach by Daniel, Jonathan, Dal Pra, Ophélie, Kurek, Eleonore, Grazon, Chloé, Blanchard-Desce, Mireille

“…Their luminescence can be tuned in the whole visible region down to the Near Infra-Red I (NIR-I) region while their nonlinear optical responses can be enhanced thanks to cooperative effects. …”
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Vertical distribution and variability of soil organic carbon and CaCO3 in deep Colluvisols modeled by hyperspectral imaging by Jessica Reyes-Rojas, Julien Guigue, Daniel Žížala, Vít Penížek, Tomáš Hrdlička, Petra Vokurková, Aleš Vaněk, Tereza Zádorová

“…In this study, we investigated the effectiveness of hyperspectral imaging in visible and near-infrared range to assess the detailed variability (both vertical and within each colluvial layer and in-situ soil horizon) of soil organic carbon (SOC) and CaCO3 concentrations in three deep Colluvisols developed on loess and located at different slope positions in southeast Czechia, and evaluate whether this in-detail mapped microvariability can be used as a proxy to assess the dynamics and history of colluvial sedimentation. A variety of nonlinear machine learning techniques such as cubist regression tree (Cubist), random forest (RF), support vector machine regression (SVMR) and one linear technique partial least square regression (PLSR) were compared to determine the most suitable model for the prediction of SOC and CaCO3 content in each profile. …”
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Risk factors affecting polygenic score performance across diverse cohorts by Daniel Hui, Scott Dudek, Krzysztof Kiryluk, Theresa L Walunas, Iftikhar J Kullo, Wei-Qi Wei, Hemant Tiwari, Josh F Peterson, Wendy K Chung, Brittney H Davis, Atlas Khan, Leah C Kottyan, Nita A Limdi, Qiping Feng, Megan J Puckelwartz, Chunhua Weng, Johanna L Smith, Elizabeth W Karlson, Regeneron Genetics Center, Penn Medicine BioBank, Gail P Jarvik, Marylyn D Ritchie

“…Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account nonlinear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. …”
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Prediction of coal dust particle size after spraying dust reduction in roadway based on orthogonal experiment and regression analysis by Bingyou JIANG, Yuqian ZHANG, Changfei YU, Ben JI, Haoyu WANG, Zhuang LIU

“…On this basis, combined with the weights of each influencing factor, a weighted-based multivariate nonlinear regression prediction model of coal dust D90 after spraying dust reduction was constructed, and its prediction results were compared and analyzed with those of the multivariate linear regression model. …”
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Long-term exposure to PM2.5 and its constituents and visual impairment in schoolchildren: A population-based survey in Guangdong province, China by Jia-Hui Li, Hui-Xian Zeng, Jing Wei, Qi-Zhen Wu, Shuang-Jian Qin, Qing-Guo Zeng, Bin Zhao, Guang-Hui Dong, Ji-Chuan Shen, Xiao-Wen Zeng

“…Results: The observed associations typically displayed a nonlinear pattern. Compared to the lowest quartile of PM2.5 and its constituents, the fourth quartile was associated with higher odds of visual impairment in schoolchildren (e.g., the adjusted odds ratio (OR) was 1.23 (95% CI: 1.13, 1.33) for PM2.5, 1.53 (95% CI: 1.40, 1.67) for OM, and 1.35 (95% CI: 1.27, 1.44) for BC), respectively. …”
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Stock price prediction with attentive temporal convolution-based generative adversarial network by Ying Liu, Xiaohua Huang, Liwei Xiong, Ruyu Chang, Wenjing Wang, Long Chen

“…Stock price prediction presents significant challenges owing to the highly volatile and nonlinear nature of financial markets, which are influenced by various factors including macroeconomic conditions, policy changes, and market sentiment. …”
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Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells by Tian Xu, Qin Xu, Ran Lu, David N. Oakland, Song Li, Liwu Li, Christopher M. Reilly, Xin M. Luo

“…However, advanced deep learning models such as Single Cell Variational Inference (scVI) have the capability to capture nonlinear gene expression patterns in the sequencing data. …”
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Characterisation of cardiovascular disease (CVD) incidence and machine learning risk prediction in middle-aged and elderly populations: data from the China health and retirement lo... by Qing Huang, Zihao Jiang, Bo Shi, Jiaxu Meng, Li Shu, Fuyong Hu, Jing Mi

“…Shapley additive explanations (SHAP) analyses revealed the importance of key features, such as night sleep duration, TG levels, and waist circumference, in predicting outcomes, and highlighted the nonlinear relationships between these features and CVD risk. …”
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Sex-biased prevalence in infections with heterosexual, direct, and vector-mediated transmission: a theoretical analysis by Andrea Pugliese, Abba B. Gumel, Fabio A. Milner, Jorge X. Velasco-Hernandez

“…In the first model, where the other two transmission modes are not considered, the attack ratios (fractions of the population of each sex that will eventually be infected) can be obtained as solutions of a system of two nonlinear equations, that has a unique solution if the net reproduction number exceeds unity. …”
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Shock reaction model for impact energy release behavior of Al/PTFE reactive material by Bao-yue Guo, Ke-rong Ren, Xia-yin Ma, Gan Li, Cai-min Huang, Zhi-bin Li, Rong Chen

“…At the same time, the shock reaction model is embedded into the material library of the LS-DYNA nonlinear dynamic simulation software as a secondary development. …”
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Dynamic analysis and optimal control of a hybrid fractional monkeypox disease model in terms of external factors by Saima Rashid, Abdul Bariq, Ilyas Ali, Sobia Sultana, Ayesha Siddiqa, Sayed K. Elagan

“…Through the application of nonlinear least squares, we determine the parameter values applying actual cases collected from Canada. …”
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Association of serum chloride levels with all-cause mortality among patients in surgical intensive care units: a retrospective analysis of the MIMIC-IV database by Quan Ma, Wei Tian, Kaifeng Wang, Bin Xu, Tianyu Lou

“…RCS analysis depicted an L-shaped curve demonstrating the dynamics between serum chloride concentrations and the risk of all-cause mortality across the 30-day, 90-day, and 180-day periods.Starting at a concentration of 104 mmol/L, a decrease in serum chloride levels was associated with an increased risk of mortality.These findings elucidate a marked nonlinear association between serum chloride levels and all-cause mortality in SICU patients, enhancing our comprehension of serum chloride’s impact on clinical outcomes in this setting.…”
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A case-crossover study of air pollution exposure during pregnancy and the risk of stillbirth in Tehran, Iran by Nadia Mohammadi Dashtaki, Mohammad Fararouei, Alireza Mirahmadizadeh, Mohammad Hoseini, Mohammad Heidarzadeh

“…Using a quasi-Poisson regression model and distributed lag nonlinear models (DLNM), we estimated the effect of exposure to air pollutants measured as lags (0 to 7 days) and cumulative average days (0–2, 0–6, and 0–14-day lag) before delivery on stillbirth. …”
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Age-stratified analysis of the BMI-kidney stone relationship: findings from a national cross-sectional study by Liuliu Zhou, Wei Gu, Yufeng Jiang, Haimin Zhang

“…BackgroundThe association between body mass index (BMI) and kidney stone formation may vary across different age groups and follow nonlinear patterns.MethodsThis study analyzed data from NHANES 2009–2018, including 14,880 participants aged ≥20 years, to evaluate the association between BMI and the risk of kidney stones. …”
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Associations of PM2.5 and its components with term preterm rupture of membranes: a retrospective study by Jiangxia Qin, Weiling Liu, Haidong Zou, Chong Zeng, Cifeng Gao, Weiqi Liu

“…Specifically, the interquartile range (IQR) 3 (IQR3) and IQR4 of ${\mathrm{SO}}_{4}^{2-}$ SO 4 2 − exposure during the third trimester increased the risk of TPROM by 18% (95% CIs [1.01–1.39]) and 18% (95% CIs [1.01–1.39]), respectively. A nonlinear relationship was observed between exposure to PM2.5, ${\mathrm{SO}}_{4}^{2-}$ SO 4 2 − , ${\mathrm{NH}}_{4}^{+}$ NH 4 + , and OM during the second trimester and the risk of TPROM. …”
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Mathematical Modelling and Analysis of Transmission Dynamics of Lassa Fever by E. A. Bakare, E. B. Are, O. E. Abolarin, S. A. Osanyinlusi, Benitho Ngwu, Obiaderi N. Ubaka

“…In this work, a periodically forced seasonal nonautonomous system of a nonlinear ordinary differential equation is developed that captures the dynamics of Lassa fever transmission and seasonal variation in the birth of Mastomys rodents where time was measured in days to capture seasonality. …”
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Classification and Recognition Method for Bearing Fault based on IFOA-SVM by Wei Zhang, Zhihua Ma

“…In order to identify the nonlinear classification of bearing fault features more accurately， a fault identification method based on IFOA-SVM is proposed. …”
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Association between the triglyceride-glucose index and liver fibrosis in adults with metabolism-related fatty liver disease in the United States: a cross-sectional study of NHANES... by Yuou Ying, Yuan Ji, Ruyi Ju, Jinhan Chen, Mingxian Chen

“…A restricted cubic spline (RCS) model was used to explore nonlinear effects, and receiver operating characteristic (ROC) curves were applied to evaluate the effectiveness in predicting. …”
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Construction and Optimization of Integrated Yield Prediction Model Based on Phenotypic Characteristics of Rice Grown in Small–Scale Plantations by Jihong Sun, Peng Tian, Zhaowen Li, Xinrui Wang, Haokai Zhang, Jiangquan Chen, Ye Qian

“…Although machine learning can handle complex nonlinear problems to enhance prediction accuracy, further improvements in models are still needed to accurately predict rice yields in small areas facing complex planting environments, thereby enhancing model performance. …”
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The Relationship Between Novel Inflammatory Markers and Serum 25‐Hydroxyvitamin D Among US Adults by Hang Zhao, Yangyang Zhao, Yini Fang, Weibang Zhou, Wenjing Zhang, Jiecheng Peng

“…To further explore the relationship between the two, we applied smooth curve fittings and generalized additive models. Upon detecting nonlinear relationships, we used a recursive algorithm to pinpoint the inflection point. …”
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