The EXO70 inhibitor Endosidin2 alters plasma membrane protein composition in Arabidopsis roots

To sustain normal growth and allow rapid responses to environmental cues, plants alter the plasma membrane protein composition under different conditions presumably by regulation of delivery, stability, and internalization. Exocytosis is a conserved cellular process that delivers proteins and lipids to the plasma membrane or extracellular space in eukaryotes. The octameric exocyst complex contributes to exocytosis by tethering secretory vesicles to the correct site for membrane fusion; however, whether the exocyst complex acts universally for all secretory vesicle cargo or just for specialized subsets used during polarized growth and trafficking is currently unknown. In addition to its role in exocytosis, the exocyst complex is also known to participate in membrane recycling and autophagy. Using a previously identified small molecule inhibitor of the plant exocyst complex subunit EXO70A1, Endosidin2 (ES2), combined with a plasma membrane enrichment method and quantitative proteomic analysis, we examined the composition of plasma membrane proteins in the root of Arabidopsis seedlings, after inhibition of the ES2-targetted exocyst complex, and verified our findings by live imaging of GFP-tagged plasma membrane proteins in root epidermal cells. The abundance of 145 plasma membrane proteins was significantly reduced following short-term ES2 treatments and these likely represent candidate cargo proteins of exocyst-mediated trafficking. Gene Ontology analysis showed that these proteins play diverse functions in cell growth, cell wall biosynthesis, hormone signaling, stress response, membrane transport, and nutrient uptake. Additionally, we quantified the effect of ES2 on the spatial distribution of EXO70A1 with live-cell imaging. Our results indicate that the plant exocyst complex mediates constitutive dynamic transport of subsets of plasma membrane proteins during normal root growth

GraphScope Flex: LEGO-like Graph Computing Stack

Graph computing has become increasingly crucial in processing large-scale graph data, with numerous systems developed for this purpose. Two years ago, we introduced GraphScope as a system addressing a wide array of graph computing needs, including graph traversal, analytics, and learning in one system. Since its inception, GraphScope has achieved significant technological advancements and gained widespread adoption across various industries. However, one key lesson from this journey has been understanding the limitations of a "one-size-fits-all" approach, especially when dealing with the diversity of programming interfaces, applications, and data storage formats in graph computing. In response to these challenges, we present GraphScope Flex, the next iteration of GraphScope. GraphScope Flex is designed to be both resource-efficient and cost-effective, while also providing flexibility and user-friendliness through its LEGO-like modularity. This paper explores the architectural innovations and fundamental design principles of GraphScope Flex, all of which are direct outcomes of the lessons learned during our ongoing development process. We validate the adaptability and efficiency of GraphScope Flex with extensive evaluations on synthetic and real-world datasets. The results show that GraphScope Flex achieves 2.4X throughput and up to 55.7X speedup over other systems on the LDBC Social Network and Graphalytics benchmarks, respectively. Furthermore, GraphScope Flex accomplishes up to a 2,400X performance gain in real-world applications, demonstrating its proficiency across a wide range of graph computing scenarios with increased effectiveness

Historic evolution of population exposure to heatwaves in Xinjiang Uygur Autonomous Region, China

Abstract Heatwaves have pronounced impacts on human health and the environment on a global scale. Although the characteristics of heatwaves has been well documented, there still remains a lack of dynamic studies of population exposure to heatwaves (PEH), particularly in the arid regions. In this study, we analyzed the spatio-temporal evolution characteristics of heatwaves and PEH in Xinjiang using the daily maximum temperature (Tmax), relative humidity (RH), and high-resolution gridded population datasets. The results revealed that the heatwaves in Xinjiang occur more continually and intensely from 1961 to 2020. Furthermore, there is substantial spatial heterogeneity of heatwaves with eastern part of the Tarim Basin, Turpan, and Hami been the most prone areas. The PEH in Xinjiang showed an increasing trend with high areas mainly in Kashgar, Aksu, Turpan, and Hotan. The increase in PEH is mainly contributed from population growth, climate change and their interaction. From 2001 to 2020, the climate effect contribution decreased by 8.5%, the contribution rate of population and interaction effects increased by 3.3% and 5.2%, respectively. This work provides a scientific basis for the development of policies to improve the resilience against hazards in arid regions

Projected population exposure to heatwaves in Xinjiang Uygur autonomous region, China

Abstract The intensification of heatwaves dues to climate change is a significant concern, with substantial impacts on ecosystems and human health, particularly in developing countries. This study utilizes NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) and projected population data accounting for China’s population policies to project changes in various grades of heatwaves (light, moderate, and severe) and the population exposure to heatwaves (PEH) in Xinjiang under three shared socioeconomic pathways (SSP1–2.6, SSP2-4.5, and SSP5-8.5). The results show that the number of days and intensity of heatwaves in Xinjiang are projected to increase. Heatwaves occurring in Xinjiang will predominantly be severe heatwaves (SHW) in the long-term under the SSP5-8.5 scenario, and the number of SHW days projected to increase by 62 ± 18.4 days compared to the reference period. Changes in heatwaves are anticipated to influence PEH, estimating population exposure to light, moderate, and severe heatwaves (LPEH, MPEH, and SPEH) at 534.6 ± 64 million, 496.2 ± 43.5 million, and 1602.4 ± 562.5 million person-days, respectively, in the long-term under the SSP5-8.5 scenario. The spatial distribution of PEH is projected to be consistent with that of the reference period, with high values persisting in Urumqi, Kashgar and Hotan. Changes in PEH are primarily driven by climate effects, followed by interactive effects, while population effects contribute the least. Therefore, mitigating climate change is crucial to reduce the PEH in Xinjiang

Species Distribution Modeling of Sassafras Tzumu and Implications for Forest Management

Sassafras tzumu (Chinese sassafras) is an economically and ecologically important deciduous tree species. Over the past few decades, increasing market demands and unprecedented human activity in its natural habitat have created new threats to this species. Nonetheless, the distribution of its habitat and the crucial environmental parameters that determine the habitat suitability remain largely unclear. The present study modeled the current and future geographical distribution of S. tzumu by maximum entropy (MAXENT) and genetic algorithm for rule set prediction (GARP). The value of area under the receiver operating characteristic curve (AUC), Kappa, and true skill statistic (TSS) of MAXENT was significantly higher than that of GARP, indicating that MAXENT performed better. Temperate and subtropical regions of eastern China where the species had been recorded was suitable for growth of S. tzumu. Relative humidity (26.2% of permutation importance), average temperature during the driest quarter (16.6%), annual precipitation (12.6%), and mean diurnal temperature range (10.3%) were identified as the primary factors that accounted for the present distribution of S. tzumu in China. Under the climate change scenario, both algorithms predicted that range of suitable habitat will expand geographically to northwest. Our results may be adopted for guiding the preservation of S. tzumu through identifying the habitats susceptible to climate change

Suppression of Power Angle Oscillation Among Synchronous Generators by Optimizing Steady–State Power of High-Voltage DC

In the power systems with high-voltage DC (HVDC) transmission, the angular oscillations among the synchronous generators (SGs) endanger the system security. The pre-fault power of the HVDC changes the power flow and affects the system dynamics, hence may be optimized to improve the system stability. However, the HVDC power does not appear in the system matrix, thus it is difficult to derive the analytical expression of the trajectory sensitivity (TS) for parameter optimization. Based on the power flow equations, the initial value of the TS is newly introduced in the sensitivities of the power angles of the SGs with respect to the intermediate variables and then to the DC powers. The imbalanced matrix of the TS is derived during the time-domain simulation. By setting the objective function as the integral of the square of the relative value of the SGs’ power angle deviation with time, and summing the trajectory sensitivity for all time steps, the gradient information of the objective function to the DC powers is newly derived. The optimization model is solved with the interior point method to adjust the steady-state HVDC powers. The effect of the power optimization on the angular oscillation is verified with the time-domain simulation. The numerical results show that the objective function is reduced by 37.92%, and the oscillation amplitude is reduced by 35%

Suppression to Angular Oscillation among Synchronous Generators by Optimizing Parameters and Set-Points of Synchronous Condenser and High-Voltage DC

After losing one or two poles of the high-voltage DC (HVDC) line, power systems may experience angular oscillations among the synchronous generators (SGs), possibly followed by tripping of the SGs and blackouts of the loads. To suppress the oscillations, the difficulty lies in the optimization methods and the countermeasures. For the former, parameter optimization based on the eigen-analysis for a given scenario is not suitable for angular oscillation after a large disturbance lasting for several seconds or longer. For the latter, adjusting the active power of the SGs is effective but responds slowly. Adjusting the excitation system of the synchronous condensers (SCs) is seldom studied since the relation of the power angle with the reactive power is not clearly described. Adjusting the control parameters of the remaining HVDC has limited effect and is not enough. The set-points for the controller of the HVDC are adjusted to suppress the oscillation but are to be restored after the oscillation, which is different from optimization of the control parameters. In this paper, coordinated optimization of the control parameters and the set-points of the SC and the HVDC is proposed to suppress the angular oscillations among the SGs. At first, the relation of the reactive power of the SC with the power angles is validated to provide the basis for optimizing the control parameters and the set-points of the SC. Since the analytical expression between the power angle and the control parameters or the set-points related to the reactive power is not explicit and the optimization periods of different parameters are different, an improved analytical model of the trajectory sensitivity (TS) is proposed. Based on the indication indices, the control parameters and the set-points of the constant current controller and the excitation system to be optimized are decided. The gradients of the objective function are extended to derive a coordinated multiparameter optimization model to suppress the angular oscillation among the SGs. The numerical results validate the accuracy of the improved TS by comparing it with the perturbation method. The time-domain analysis in different scenarios shows that the angular oscillations in the AC/HVDC system are effectively suppressed with the proposed optimization model