| 1. |
- Wen, Wanqing, et al.
(författare)
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Genome-wide association studies in East Asians identify new loci for waist-hip ratio and waist circumference
- 2016
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- Sixty genetic loci associated with abdominal obesity, measured by waist circumference (WC) and waist-hip ratio (WHR), have been previously identified, primarily from studies conducted in Europeanancestry populations. We conducted a meta-analysis of associations of abdominal obesity with approximately 2.5 million single nucleotide polymorphisms (SNPs) among 53,052 (for WC) and 48,312 (for WHR) individuals of Asian descent, and replicated 33 selected SNPs among 3,762 to 17,110 additional individuals. We identified four novel loci near the EFEMP1, ADAMTSL3, CNPY2, and GNAS genes that were associated with WC after adjustment for body mass index (BMI); two loci near the NID2 and HLA-DRB5 genes associated with WHR after adjustment for BMI, and three loci near the CEP120, TSC22D2, and SLC22A2 genes associated with WC without adjustment for BMI. Functional enrichment analyses revealed enrichment of corticotropin-releasing hormone signaling, GNRH signaling, and/or CDK5 signaling pathways for those newly-identified loci. Our study provides additional insight on genetic contribution to abdominal obesity.
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| 2. |
- Gao, Hongkai, et al.
(författare)
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Assessing glacier retreat and its impact on water resources in a headwater of Yangtze River based on CMIP6 projections
- 2021
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 765
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Tidskriftsartikel (refereegranskat)abstract
- Glacier retreat caused by global warming alters the hydrological regime and poses far-reaching challenges to water resources and nature conservation of the headwater of Yangtze River, and its vast downstream regions with dense population. However, there is still lack of a robust modeling framework of the “climate-glacier-streamflow” in this water tower region, to project the future changes of glacier mass balance, glacier geometry, and the consequent impacts on runoff. Moreover, it is imperative to use the state-of-the-art sixth phase Coupled Model Intercomparison Project (CMIP6) to assess glacio-hydrology variations in future. In this study, we coupled a glacio-hydrological model (FLEXG) with a glacier retreat method (Δh-parameterization) to simulate glacio-hydrological processes in the Dongkemadi Glacier (over 5155 m.a.s.l), which has the longest continuous glacio-hydrology observation on the headwater of Yangtze River. The FLEXG-Δh model was forced with in-situ observed meteorological data, radar ice thickness, remote sensing topography and land cover data, and validated by measured runoff. The results showed that the model was capable to simulate hydrological processes in this glacierized basin, with Kling-Gupta efficiency (IKGE) of daily runoff simulation 0.88 in calibration and 0.70 in validation. Then, forcing by the bias-corrected meteorological forcing from the eight latest CMIP6 Earth system models under two climate scenarios (RCP2.6 and RCP8.5), we assessed the impact of future climate change on glacier response and its hydrological effects. The results showed that, to the end of simulation in 2100, the volume of the Dongkemadi Glacier would continuously retreat. For the RCP2.6 and RCP8.5 scenarios, the glacier volume will decrease by 8.7 × 108 m3 (74%) and 10.8 × 108 m3 (92%) respectively in 2100. The glacier runoff will increase and reach to peak water around 2060 to 2085, after this tipping point water resources will likely decrease.
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| 3. |
- He, Yixu, et al.
(författare)
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Exploring the design of reward functions in deep reinforcement learning-based vehicle velocity control algorithms
- 2024
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Ingår i: Transportation Letters. - 1942-7867 .- 1942-7875. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- The application of deep reinforcement learning (DRL) techniques in intelligent transportation systems garners significant attention. In this field, reward function design is a crucial factor for DRL performance. Current research predominantly relies on a trial-and-error approach for designing reward functions, lacking mathematical support and necessitating extensive empirical experimentation. Our research uses vehicle velocity control as a case study, build training and test sets, and develop a DRL framework for speed control. This framework examines both single-objective and multi-objective optimization in reward function designs. In single-objective optimization, we introduce “expected optimal velocity” as an optimization objective and analyze how different reward functions affect performance, providing a mathematical perspective on optimizing reward functions. In multi-objective optimization, we propose a reward function design paradigm and validate its effectiveness. Our findings offer a versatile framework and theoretical guidance for developing and optimizing reward functions in DRL, particularly for intelligent transportation systems.
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| 4. |
- Jin, Yunzhe, et al.
(författare)
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Effects of in-situ stress on heat transfer in fracture networks
- 2024
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Ingår i: Geomechanics for Energy and the Environment. - : Elsevier BV. - 2352-3808. ; 37
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Tidskriftsartikel (refereegranskat)abstract
- Stress-induced fracture deformation is the principal cause for permeability change in geothermal systems. This study focuses on the influence of the nonlinear deformation and dilation effect of fractures on the geothermal system under the action of in-situ stress. By adopting a nonlinear constitutive model of rock fractures and embedding discrete fracture networks, numerical studies are first conducted to investigate the effects of different in-situ stress schemes on fracture aperture evolution using a rigid-body spring method. Based on the anisotropic aperture field of the fracture network caused by the in-situ stress, a finite element method is then used to study the flow and heat transfer process. The effects of different stress schemes on the heat flow transfer process are analyzed. Numerical simulation results show that when the ratio of horizontal to vertical stresses is not sufficient to cause shear dilation effects, the nonlinear normal deformation is the main factor affecting flow and heat transfer. In this case, the heat extraction efficiency is reduced. As the stress ratio increases, the shear dilation gradually becomes the dominant mechanism, and the heat extraction performance is improved. The obtained results provide a practical guide for geothermal site siting and optimizing heat extraction efficiency in geothermal reservoirs.
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| 5. |
- Jin, Yunzhe, et al.
(författare)
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Experimental and numerical simulation study on the evolution of mechanical properties of granite after thermal treatment
- 2024
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Ingår i: Computers and geotechnics. - : Elsevier BV. - 0266-352X .- 1873-7633. ; 172
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Tidskriftsartikel (refereegranskat)abstract
- High temperature significantly influences the mechanical properties of granite, which is relevant to various engineering applications, including geothermal energy extraction. The objective of this study is to investigate the meso-mechanics of granite, specifically focusing on the formation of thermal cracks and the temperature-dependent mechanical properties in heterogeneous rock. Firstly, we heat the granite to 25–1000 ℃ by muffle furnace. Following this, we conduct triaxial compression tests with 0–20 MPa confining pressures on the heated-specimens cooled by cold water. Subsequently, we combine the grain-based model (GBM) and the finite-discrete element method (FDEM) to simulate the heat treatment process and the triaxial experiments. We calibrate the micromechanical parameters of granite by experimental results. Results show that the mechanism behind the formation of thermal cracks in granite subjected to high-temperature is the differential thermal expansion coefficients of mineral particles in granites, leading to the degradation of mechanical properties in thermal-treated granite. The temperature threshold for the formation of thermal cracks is between 500 °C and 550 °C. Particularly, the stress-strain curve of granite exhibits ideal elastic-plastic characteristics under temperature is 1000 °C. These results can help to demonstrate the temperature-dependent evolution of mechanical properties of crystalline rocks, providing a theoretical basis for the utilization of engineering applications.
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| 6. |
- Li, Jian, et al.
(författare)
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A 3D extra-large-pore zeolite enabled by 1D-to-3D topotactic condensation of a chain silicate
- 2023
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 379:6629, s. 283-287
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Tidskriftsartikel (refereegranskat)abstract
- Zeolites are microporous silicates with a large variety of applications as catalysts, adsorbents, and cation exchangers. Stable silica-based zeolites with increased porosity are in demand to allow adsorption and processing of large molecules but challenge our synthetic ability. We report a new, highly stable pure silica zeolite called ZEO-3, which has a multidimensional, interconnected system of extra-large pores open through windows made by 16 and 14 silicate tetrahedra, the least dense polymorph of silica known so far. This zeolite was formed by an unprecedented one-dimensional to three-dimensional (1D-to-3D) topotactic condensation of a chain silicate. With a specific surface area of more than 1000 square meters per gram, ZEO-3 showed a high performance for volatile organic compound abatement and recovery compared with other zeolites and metal-organic frameworks.
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| 7. |
- Li, Zongbao, et al.
(författare)
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High throughput trapping and arrangement of biological cells using self-assembled optical tweezer
- 2018
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Ingår i: Optics Express. - : OPTICAL SOC AMER. - 1094-4087. ; 26:26, s. 34665-34674
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Tidskriftsartikel (refereegranskat)abstract
- Lately, a fiber-based optical tweezer that traps and arranges the micro/nanoparticles is crucial in practical applications, because such a device can trap the biological samples and drive them to the designated position in a microfluidic system or vessel without harming them. Here, we report a new type of fiber optical tweezer, which can trap and arrange erythrocytes. It is prepared by coating graphene on the cross section of a microfiber. Our results demonstrate that thermal-gradient-induced natural convection flow and thermophoresis can trap the erythrocytes under low incident power, and the optical scattering force can arrange them precisely under higher incident power. The proposed optical tweezer has high flexibility, easy fabrication, and high integration with lab-on-a-chip, and shows considerable potential for application in various fields, such as biophysics, biochemistry, and life sciences.
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| 8. |
- Li, Zongbao, et al.
(författare)
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Upconversion Luminescence of Graphene Oxide through Hybrid Waveguide
- 2018
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Ingår i: The Journal of Physical Chemistry C. - : AMER CHEMICAL SOC. - 1932-7447 .- 1932-7455. ; 122:29, s. 16866-16871
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Tidskriftsartikel (refereegranskat)abstract
- Phonon-assisted upconversion is a promising way to generate short-wavelength emissions under excitation of long wavelength based on unique anti-Stokes luminescence properties. Graphene oxide nanosheets (GONs) exhibit excellent optical properties owing to quantum confinement and edge effects, which have driven research into fundamental principles and potential applications. Here, we experimentally demonstrate upconversion emission by exciting an easily fabricated GON hybrid waveguide (GHVV) with enhanced photothermal effects. The results reveal different origins of short-wavelength range and long-wavelength range in the upconversion spectra, whereas the emissive surface defects of GONs and GHW structure play significant roles in the behavior of photoluminescence. Introducing other upconversion materials to promote emission efficiency, the hybrid waveguide system might readily provide the possibility for the construction of upconversion fiber lasers and remote control of the upconversion luminescence.
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| 9. |
- Lin, Hongyi, et al.
(författare)
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Deep Demand Prediction: An Enhanced Conformer Model With Cold-Start Adaptation for Origin–Destination Ride-Hailing Demand Prediction
- 2024
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Ingår i: IEEE Intelligent Transportation Systems Magazine. - 1939-1390 .- 1941-1197. ; 16:3, s. 111-124
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Tidskriftsartikel (refereegranskat)abstract
- In intelligent transportation systems, one key challenge for managing ride-hailing services is the balancing of traffic supply and demand while meeting passenger needs within vehicle availability constraints. Accurate origin–destination (OD) demand predictions can empower platforms to execute timely reallocation of cruising vehicles and improve ride-sharing services. Nonetheless, the complexity of OD-based demand prediction arises from intricate spatiotemporal dependencies and a higher need for precision compared to zone-based predictions, which leads to many unprecedented OD pairs. To tackle this issue, we design a comprehensive set of 102 features, including travel demand, passenger count, travel volume, liveliness, weather, and cross features. We also introduce an enhanced conformer model, which is composed of a single conformer block that integrates feedforward layers, multihead self-attention mechanisms, and depth-wise separable convolution layers. To address the cold-start problem and manage large values, we design a specific algorithm for OD pairs lacking training data and apply a technique to handle larger values. Our approach demonstrates a marked improvement in prediction performance, with an 18% decrease in the total travel demand error and up to a 47% reduction for certain larger values in some cases. Through extensive experiments on a dataset collected from a city, provided by a ride-hailing platform, our proposed methods significantly outperform the most advanced models.
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| 10. |
- Lin, Hongyi, et al.
(författare)
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Enhancing State Representation in Multi-Agent Reinforcement Learning for Platoon-Following Models
- 2024
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Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- With the growing prevalence of autonomous vehicles and the integration of intelligent and connected technologies, the demand for effective and reliable vehicle speed control algorithms has become increasingly critical. Traditional car-following models, which primarily focus on individual vehicle pairs, exhibit limitations in complex traffic environments. To this end, this paper proposes an enhanced state representation for the application of multi-agent reinforcement learning (MARL) in platoon-following scenarios. Specifically, the proposed representation, influenced by feature engineering techniques in time series prediction tasks, thoroughly accounts for the intricate relative relationships between different vehicles within a platoon and can offer a distinctive perspective on traffic conditions to help improve the performance of MARL models. Experimental results show that the proposed method demonstrates superior performance in platoon-following scenarios across key metrics such as the time gap, distance gap, and speed, even reducing the time gap by 63%, compared with traditional state representation methods. These enhancements represent a significant step forward in ensuring the safety, efficiency, and reliability of platoon-following models within the context of autonomous vehicles.
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