Comprehensive understanding of new particle formation in China through advanced modeling
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Shen, Jiewen↗
Engineering topics
Zhang, Ying
Publications and source records attributed to Zhang, Ying.
Core Model Proposal 401: Ukraine as an independent region in GCAM
The goal of this core model proposal (CMP) is to break out Ukraine from the Europe_Eastern region. This work aims to establish Ukraine as an independent region in the GCAM core (region 14) while moving Belarus and Moldova to region 15 (Europe_Non_EU). We have: 1) Updated several mappings to recode region 14 (formerly Europe_Eastern) as Ukraine and moved Belarus and Moldova to region 15 (Europe_Non_EU); 2) Updated several assumptions in the raw data files which provide information by region to reframe Ukraine as the 14th region, including coefficients, base year values, share weight interpolation values and rules, pipeline networks for gas trade, elasticities, shares, etc. 3) Changed documentation and in-code comments at several places referring to fixed 32 regions in GCAM to indicate that GCAM can have any number of regions; 4) Updated code base in gcamdata to dynamically process data for Ukraine given special cases.
Global Change Analysis Model (GCAM)↗
The impact of climate change on Korea’s agricultural sector under the national self-sufficiency policy
Evolving environmental conditions due to climate change have brought about changes in agriculture, which is required for human life as both a source of food and income. International trade can act as a buffer against potential negative impacts of climate change on crop yields, but recent years have seen breakdowns in global trade, including export bans to improve domestic food security. For countries that rely heavily on imported food, governments may institute policies to protect their agricultural industry from changes in climate-induced crop yield changes and other countries’ potential trade restrictions. This study assesses the individual and combined effects of climate impacts and food self-sufficiency policies in Korea, which is highly dependent on imports. We use the Global Change Analysis Model (GCAM), a global integrated assessment model, to explore (1) the direct impact of climate change on Korea’s agricultural yields, (2) the full impacts of global climate change on agricultural production, including trade-induced changes due to yield changes in other regions, (3) the impacts of food self-sufficiency policy, and (4) the interactive impact of climate change and self-sufficiency policies. We find that, in Korea, the direct impact of climate change on agricultural yields would be overshadowed by the impact of global climate change due to changing trade patterns. Second, global climate change leads to a rise (rice and wheat) or a decline (soybeans) in Korean producer revenues, while simultaneously raising consumer expenditures on both staples and non-staples. Third, implementing self-sufficiency policies for wheat and soybeans in Korea boosts the nation’s producer revenues, in conjunction with the effects of climate change, at the cost of additional increases in consumer expenditures for both staples and non-staples.
Science & Technology - Other Topics↗
Convergence of Energy and IT Sectors
Today there has never been a more profound codependence and synergetic convergence, such as the one between the energy and IT sectors, and the industries will need to work together more closely to meet today’s growing data center power demands.
AI↗
A Target Class Ligandability Evaluation of WD40 Repeat-Containing Proteins
Not provided.
Pharmacology & Pharmacy↗
Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method
Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (ders). to address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines taylor series expansion knowledge with a data-driven regression technique. the proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified taylor expansion. to mitigate the approximation loss that surges due to the der integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. comparative analysis in the 13-bus and 123-bus ieee unbalanced feeders shows that the proposed hybrid algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.
data-driven↗
Small-Scale Irrigation: Improving Food Security under Changing Climate and Water Resource Conditions in Ethiopia
We develop a new systems modeling tool that integrates knowledge from hydrology, agriculture, and economics to understand the effect of small-scale irrigation on food security and groundwater sustainability in Ethiopia. Irrigation is an effective tool to mitigate climate impacts and improve agricultural yields. Small-scale irrigation, such as decentralized groundwater irrigation, is well suited for developing countries where smallholder farming communities are widely dispersed and can only afford small infrastructure investment. We study the underlying interdependencies between food and water systems in Ethiopia, where small-holder agriculture is the foundation of the nation’s economy and climate variability has led to great challenges to its food security. Our coupled market and crop model with groundwater module captures the interdependencies of climate, water availability (including irrigation), crop yield, farmland allocation, crop production, transport and consumption based on a system approach across multiple spatial scales. We study the implication of small-scale irrigation to Ethiopia’s food security and water resource conditions as a “what-if” question by comparing an irrigation scenario to the calibrated baseline in 2015, a year of significant drought and crop failure over a large portion of Ethiopia. Our model offers fresh insights into geographic disparities in outcomes that are driven by baseline climate variability, soil fertility, and market conditions. In general, we find that small-scale irrigation can potentially improve food security through increases in food consumption, but it requires policy support to direct the increases of production to domestic consumption while maintaining a sustainable groundwater condition. By using Ethiopia as an example, we show the strength of our model to study how water infrastructure resources support critical functions and service in water and food systems.
Zhang, Ying↗
Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets
Climate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial–temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy markets and emission reduction scenarios. We find that under SSP5, a “fossil-fueled development” scenario, the effects of sea-ice loss are larger for Arctic offshore oil production than gas. Under SSP5, future extraction of Arctic offshore oil and gas through 2100 adds roughly 0.8–2.6 EJ/year to oil and gas markets but does not have large impacts on global oil and gas markets. Surprisingly, a low-carbon scenario results in greater Arctic offshore oil production to offset the more emissions-intensive unconventional oil production.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Pharmacokinetics and relative bioavailability study of two cefquinome sulfate intramammary infusions in cow milk
In this study, two intramammary infusions of cefquinome sulfate were investigated for pharmacokinetics and bioavailability. Twelve lactating cows for each group were administered an effective dose of 75 mg/gland for cefquinome, with milk samples collected at various time intervals. The concentrations of cefquinome in milk at different times were determined by the UPLC-MS/MS method. Analyses of noncompartmental pharmacokinetics were conducted on the concentration of cefquinome in milk. Mean pharmacokinetic parameters of group A and group B following intramammary administration were as follows: AUC last 300558.57 ± 25052.78 ng/mL and 266551.3 ± 50654.85 ng/mL, C max 51786.35 ± 11948.4 ng/mL and 59763.7 ± 8403.2 ng/mL, T 1/2 5.69 ± 0.62 h and 5.25 ± 1.62 h, MRT 7.43 ± 0.79 h and 4.8 ± 0.78 h, respectively. Pharmacokinetic experiments showed that the relative bioavailability of group B was 88.69% that of group A. From our findings, group B (3 g: 75 mg) shows a quicker drug elimination process than group A (8 g: 75 mg), which suggests that the withdrawal period for the new formulation may be shorter.
Li, Shuang↗
Electron‐Assisted Generation and Straight Movement of Skyrmion Bubble in Kagome TbMn 6 Sn 6
Abstract Topological magnetic textures are promising candidates as binary data units for the next‐generation memory device. The precise generation and convenient control of nontrivial spin topology at zero field near room temperature endows the critical advantages in skyrmionic devices but is not simultaneously integrated into one material. Here, in the Kagome plane of quantum TbMn 6 Sn 6 , the expedient generation of the skyrmion bubbles in versatile forms of lattice, chain, and isolated one by converging the electron beam, where the electron intensity gradient contributes to the dynamic generation from local anisotropy variation near spin reorientation transition (SRT) is reported. Encouragingly, by utilizing the dynamic shift of the SRT domain interface, the straight movement is actualized with the skyrmion bubble slave to the SRT domain interface forming an elastic composite object, avoiding the usual deflection from the skyrmion Hall effect. The critical contribution of the SRT domain interface via conveniently electron‐assisted heating is further theoretically validated in micromagnetic simulation, highlighting the compatible application possibility in advanced devices.
Li, Zhuolin↗
Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control
Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. Here, we develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Hydropower expansion in eco-sensitive river basins under global energy-economic change
Vast hydropower resources remain untapped globally, the deployment of which could provide energy-economic benefits but impact riverine ecosystems. Across eco-sensitive river basins, it is unclear how drivers of hydropower expansion, such as rapid economic growth and a low-carbon energy transition, could interact with countervailing forces, such as increasingly cost-competitive variable renewable energy (VRE). Using an integrated energy-water-economy model, we explore the effects of these forces on long-term hydropower expansion in the world’s 20 most eco-sensitive basins, which have high ecological richness and untapped hydropower potential. Here, we find that a low-carbon transition exerts the strongest development pressure, causing deployment exceeding 80% of exploitable potential in more than 72% of eco-sensitive basins by 2050, most of which have limited deployment today. Rapid economic growth induces such extensive deployment in only 44% of eco-sensitive basins. Enhanced integration of VRE reduces deployment, alleviating the impacts of rapid economic growth but not the low-carbon transition.
13 HYDRO ENERGY↗
Discovery of a First-in-Class Small-Molecule Ligand for WDR91 Using DNA-Encoded Chemical Library Selection Followed by Machine Learning
Not provided.
Pharmacology & Pharmacy↗
Insight into the structures of unusual base pairs in RNA complexes containing a primer/template/adenosine ligand
RNA self-copying using an activated adenosine substrate is challenging. Our structure studies reveal the binding motifs of adenosine substrates. The obtained structures explain the disfavorable conformations for nucleophilic reactions.
Dantsu, Yuliya↗
NBS1 knockdown by small interfering RNA increases ionizing radiation mutagenesis and telomere association in human cells
Hypomorphic mutations which lead to decreased function of the NBS1 gene are responsible for Nijmegen breakage syndrome, a rare autosomal recessive hereditary disorder that imparts an increased predisposition to development of malignancy. The NBS1 protein is a component of the MRE11/RAD50/NBS1 complex that plays a critical role in cellular responses to DNA damage and the maintenance of chromosomal integrity. Using small interfering RNA transfection, we have knocked down NBS1 protein levels and analyzed relevant phenotypes in two closely related human lymphoblastoid cell lines with different p53 status, namely wild-type TK6 and mutated WTK1. Both TK6 and WTK1 cells showed an increased level of ionizing radiation-induced mutation at the TK and HPRT loci, impaired phosphorylation of H2AX (gamma-H2AX), and impaired activation of the cell cycle checkpoint regulating kinase, Chk2. In TK6 cells, ionizing radiation-induced accumulation of p53/p21 and apoptosis were reduced. There was a differential response to ionizing radiation-induced cell killing between TK6 and WTK1 cells after NBS1 knockdown; TK6 cells were more resistant to killing, whereas WTK1 cells were more sensitive. NBS1 deficiency also resulted in a significant increase in telomere association that was independent of radiation exposure and p53 status. Our results provide the first experimental evidence that NBS1 deficiency in human cells leads to hypermutability and telomere associations, phenotypes that may contribute to the cancer predisposition seen among patients with this disease.
Non-NASA Center↗