Implication of Climate Change Induced Variation in Wind Extremes on Wind Farm in Mountainous Area of Central China—A Case Study of Hengshan

AbstractWind load is critical to the safety of wind turbines. Wind turbines are designed according to the referrence wind speed of 50-year recurrence interval. The climate change induced variation in extremes of wind could impact safety of wind turbines. Meteorological data from Hengshan weather station in central China is investigated. The wind data of 1973–1992 and 1992–2011 are utilized to estimate the extreme wind of 50-year recurrence interval using method of independent storm and generalized pareto distribution model. It is uncovered that although extreme wind of 50-year recurrence interval escalate a little during the two time spans, it will not affect the safety of wind turbines over there notably

Transforming growth factor-β1 protects mechanically injured cortical murine neurons by reducing trauma-induced autophagy and apoptosis

Transforming growth factor β1 (TGF-β1) has a neuroprotective function in traumatic brain injury (TBI) through its anti-inflammatory and immunomodulatory properties. However, the precise mechanisms underlying the neuroprotective actions of TGF-β1 on the cortex require further investigation. In this study, we were aimed to investigate the regulatory function of TGF-β1 on neuronal autophagy and apoptosis using an in vitro primary cortical neuron trauma-injury model. LDH activity was assayed to measure cell viability, and intracellular [Ca2+] was measured using Fluo-4-AM in an in vitro primary cortical neuron trauma-injury model. RNA-sequencing (RNAseq), immunofluorescent staining, transmission electron microscopy (TEM), western blot and CTSD activity detection were employed. We observed significant enrichment of DEGs related to autophagy, apoptosis, and the lysosome pathway in trauma-injured cortical neurons. TEM confirmed the presence of autophagosomes as well as autophagolysosomes. Western blot revealed upregulation of autophagy-related protein light chain 3 (LC3-II/LC3-I), sequestosome 1 (SQSTM1/p62), along with apoptosis-related protein cleaved-caspase 3 in trauma-injured primary cortical neurons. Furthermore, trauma-injured cortical neurons showed an upregulation of lysosomal marker protein (LAMP1) and lysosomal enzyme mature cathepsin D (mCTSD), but a decrease in the activity of CTSD enzyme. These results indicated that apoptosis was up-regulated in trauma- injured cortical neurons at 24 h, accompanied by lysosomal dysfunction and impaired autophagic flux. Notably, TGF-β1 significantly reversed these changes. Our results suggested that TGF-β1 exerted neuroprotective effects on trauma- injured cortical neurons by reducing lysosomal dysfunction, decreasing the accumulation of autophagosomes and autophagolysosomes, and enhancing autophagic flux

Multifaceted oncostatin M: novel roles and therapeutic potential of the oncostatin M signaling in rheumatoid arthritis

Rheumatoid arthritis (RA) is a self-immune inflammatory disease characterized by joint damage. A series of cytokines are involved in the development of RA. Oncostatin M (OSM) is a pleiotropic cytokine that primarily activates the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling pathway, the mitogen-activated protein kinase (MAPK) signaling pathway, and other physiological processes such as cell proliferation, inflammatory response, immune response, and hematopoiesis through its receptor complex. In this review, we first describe the characteristics of OSM and its receptor, and the biological functions of OSM signaling. Subsequently, we discuss the possible roles of OSM in the development of RA from clinical and basic research perspectives. Finally, we summarize the progress of clinical studies targeting OSM for the treatment of RA. This review provides researchers with a systematic understanding of the role of OSM signaling in RA, which can guide the development of drugs targeting OSM for the treatment of RA

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Impervious Surfaces Alter Soil Bacterial Communities in Urban Areas: A Case Study in Beijing, China

The rapid expansion of urbanization has caused land cover change, especially the increasing area of impervious surfaces. Such alterations have significant effects on the soil ecosystem by impeding the exchange of gasses, water, and materials between soil and the atmosphere. It is unclear whether impervious surfaces have any effects on soil bacterial diversity and community composition. In the present study, we conducted an investigation of bacterial communities across five typical land cover types, including impervious surfaces (concrete), permeable pavement (bricks with round holes), shrub coverage (Buxus megistophylla Levl.), lawns (Festuca elata Keng ex E. Alexeev), and roadside trees (Sophora japonica Linn.) in Beijing, to explore the response of bacteria to impervious surfaces. The soil bacterial communities were addressed by high-throughput sequencing of the bacterial 16S rRNA gene. We found that Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, Chloroflexi, and Firmicutes were the predominant phyla in urban soils. Soil from impervious surfaces presented a lower bacterial diversity, and differed greatly from other types of land cover. Soil bacterial diversity was predominantly affected by Zn, dissolved organic carbon (DOC), and soil moisture content (SMC). The composition of the bacterial community was similar under shrub coverage, roadside trees, and lawns, but different from beneath impervious surfaces and permeable pavement. Variance partitioning analysis showed that edaphic properties contributed to 12% of the bacterial community variation, heavy metal pollution explained 3.6% of the variation, and interaction between the two explained 33% of the variance. Together, our data indicate that impervious surfaces induced changes in bacterial community composition and decrease of bacterial diversity. Interactions between edaphic properties and heavy metals were here found to change the composition of the bacterial community and diversity across areas with different types of land cover, and soil properties play a more important role than heavy metals

Impervious Surfaces Alter Soil Bacterial Communities in Urban Areas: A Case Study in Beijing, China

The rapid expansion of urbanization has caused land cover change, especially the increasing area of impervious surfaces. Such alterations have significant effects on the soil ecosystem by impeding the exchange of gasses, water, and materials between soil and the atmosphere. It is unclear whether impervious surfaces have any effects on soil bacterial diversity and community composition. In the present study, we conducted an investigation of bacterial communities across five typical land cover types, including impervious surfaces (concrete), permeable pavement (bricks with round holes), shrub coverage (Buxus megistophylla Levl.), lawns (Festuca elata Keng ex E. Alexeev), and roadside trees (Sophora japonica Linn.) in Beijing, to explore the response of bacteria to impervious surfaces. The soil bacterial communities were addressed by high-throughput sequencing of the bacterial 16S rRNA gene. We found that Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, Chloroflexi, and Firmicutes were the predominant phyla in urban soils. Soil from impervious surfaces presented a lower bacterial diversity, and differed greatly from other types of land cover. Soil bacterial diversity was predominantly affected by Zn, dissolved organic carbon (DOC), and soil moisture content (SMC). The composition of the bacterial community was similar under shrub coverage, roadside trees, and lawns, but different from beneath impervious surfaces and permeable pavement. Variance partitioning analysis showed that edaphic properties contributed to 12% of the bacterial community variation, heavy metal pollution explained 3.6% of the variation, and interaction between the two explained 33% of the variance. Together, our data indicate that impervious surfaces induced changes in bacterial community composition and decrease of bacterial diversity. Interactions between edaphic properties and heavy metals were here found to change the composition of the bacterial community and diversity across areas with different types of land cover, and soil properties play a more important role than heavy metals

Simultaneous Robust Coordinated Damping Control of Power System Stabilizers (PSSs), Static Var Compensator (SVC) and Doubly-Fed Induction Generator Power Oscillation Dampers (DFIG PODs) in Multimachine Power Systems

The potential of utilizing doubly-fed induction generator (DFIG)-based wind farms to improve power system damping performance and to enhance small signal stability has been proposed by many researchers. However, the simultaneous coordinated tuning of a DFIG power oscillation damper (POD) with other damping controllers is rarely involved. A simultaneous robust coordinated multiple damping controller design strategy for a power system incorporating power system stabilizer (PSS), static var compensator (SVC) POD and DFIG POD is presented in this paper. This coordinated damping control design strategy is addressed as an eigenvalue-based optimization problem to increase the damping ratios of oscillation modes. Both local and inter-area electromechanical oscillation modes are intended in the optimization design process. Wide-area phasor measurement unit (PMU) signals, selected by the joint modal controllability/ observability index, are utilized as SVC and DFIG POD feedback modulation signals to suppress inter-area oscillation modes. The robustness of the proposed coordinated design strategy is achieved by simultaneously considering multiple power flow situations and operating conditions. The recently proposed Grey Wolf optimizer (GWO) algorithm is adopted to efficiently optimize the parameter values of multiple damping controllers. The feasibility and effectiveness of the proposed coordinated design strategy are demonstrated through frequency-domain eigenvalue analysis and nonlinear time-domain simulation studies in two modified benchmark test systems. Moreover, the dynamic response simulation results also validate the robustness of the recommended coordinated multiple damping controllers under various system operating conditions