Shuchang Liu

中国龙卷的稳定但重叠热力—动力环境配置及其多层背景

Xu Yan, Zhengyang Zhang, Shuchang Liu, 韩艳 et autres

Initial submission release of the reproducibility package for the study of stable but overlapping thermodynamic–kinematic environmental configurations of tornadoes in China. This release contains the frozen analysis code, derived aggregate data, figure/table source data, manuscript-supporting documentation, software environment information, and integrity manifests …

中国龙卷的稳定但重叠热力—动力环境配置及其多层背景

Xu Yan, Zhengyang Zhang, Shuchang Liu, 韩艳 et autres

Initial submission release of the reproducibility package for the study of stable but overlapping thermodynamic–kinematic environmental configurations of tornadoes in China. This release contains the frozen analysis code, derived aggregate data, figure/table source data, manuscript-supporting documentation, software environment information, and integrity manifests …

Data and code for 'CERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates'

Shuchang Liu

CERA_paper.tar.gz contains data for plots in the paper.CERA_trained_model.tar.gz contains trained model.CERA_code.zip contains code for the model. For figure 2,4,5,6: reweightFalseqv_Ftrest_baseline_bs1024_norh_noBMSE (baseline), reweightFalseqv_Ftrest_baseline_bs1024_rh_BMSE (RH+B baseline), Together_reweightFalse_sepa1_gt0.003warmup4000_std0_latent0.0001_CNN_0.003AE0.99_bs4096_noRH (CERA), Together_reweightFalse_sepa1_gt0.003warmup4000_std0_latent0_CNN_0.003AE0.99_bs4096_noRH (CERA_noAlign). For figure 7: run_MLP_72x180x48(baseline), run_CERA_72x180x48(CERA). For figure 8: run_MLP_mean_up_to_1800000_TABS_QV (baseline), run_CERA_mean_up_to_1800000_TABS_QV (CERA). For figure …

CERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates

Shuchang Liu, Paul A. O’Gorman

Abstract Robust generalization under climate change remains a major challenge for machine learning applications in climate science. Most existing approaches struggle to extrapolate beyond the climate they were trained on, leading to a strong dependence on training data from model simulations of …

us (code pays fourni par la source)

Railway carbon emission scenario prediction in four regions of China based on machine learning

Yintao Lu, Shuchang Liu, Yuechao Wang, Shengming Qiu et autres

Understanding carbon emissions of the railway transportation industry in China is critical for effective climate action. This study applied machine learning models to analyze railway operational conditions and socio-economic driving factors of carbon emissions across four railway operational regions with different terrain, …

cn (code pays fourni par la source)

Functional Foods in Health Promotion and Disease Prevention: Innovations, Evidence and Challenges

Zheng Feei, Shuchang Liu, Caili Fu, Shaobo Zhou et autres

Functional foods have attracted increasing scientific and commercial interest due to their potential roles in health promotion and the prevention of non-communicable diseases such as diabetes and cardiovascular diseases. In this review, we will critically examine the current evidence on functional foods …

gb, cn, my (code pays fourni par la source)

Correction: Advanced progress of adipose-derived stem cells-related biomaterials in maxillofacial regeneration

Lijun Zhang, Zihang Yu, Shuchang Liu, Fan Liu et autres

cn (code pays fourni par la source)

CERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates

Shuchang Liu, Paul A. O’Gorman

Robust generalization under climate change remains a major challenge for machine learning applications in climate science. Most existing approaches struggle to extrapolate beyond the climate they were trained on, leading to a strong dependence on training data from model simulations of warm …

Acoustic manipulations of droplets with high-speed automatic route planning and navigation

Shuchang Liu, Luyao Li, Shuying Wang, Bohan Liang et autres

cn (code pays fourni par la source)

Assessing Cloud Feedbacks Over the Atlantic With Bias‐Corrected Downscaling

Shuchang Liu, Christian Zeman, Christoph Schär

Abstract Clouds exert a significant impact on global temperatures and climate change. Cloud‐radiative feedback (CRF) is one of the major sources of climate change uncertainty. Understanding CRF is therefore crucial for accurate climate projections. Biases like the double‐ITCZ problem in Global Climate …

ch, us (code pays fourni par la source)

Driving Mechanism and Energy Conservation Strategy for China’s Railway Passenger Stations Towards Carbon Neutrality

Yintao Lu, Shengming Qiu, Shuchang Liu, Jiayan Wang et autres

As critical hubs for long-distance transportation, railway passenger stations (RPSs) significantly influence energy conservation and CO2 mitigation. This study investigates the spatiotemporal patterns and driving factors of CO2 emissions across 247 Chinese RPSs (2014–2023), proposing region-specific decarbonization strategies. The key findings include: …

cn (code pays fourni par la source)

Explicit Uncertainty Modeling for Video Watch Time Prediction

Shanshan Wu, Shuchang Liu, Shuai Zhang, Xiaoyu Yang et autres

In video recommendation, a critical component that determines the system's recommendation accuracy is the watch-time prediction module, since how long a user watches a video directly reflects personalized preferences. One of the key challenges of this problem is the user's stochastic watch-time …