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This study examines the role of the Indonesian Throughflow (ITF) variations on the El Nino/La Nina events simulated by a coupled ocean-atmosphere model of the tropical Pacific.
Since its discovery as an eclipsing binary with a white dwarf companion by Nelson and Young (1970), V471 Tau (BD + 16 deg 516) has been an object of considerable importance. The K dwarf companion has been the subject of intensive studies because it demonstrates many of the properties normally attributed to classical RS CVn stars. In the present investigation, it is demonstrated that the K dwarf companion exhibits also flaring properties which characterize the BY Dra stars. In a sense, V471 Tau may be the critical link by providing information that the distinctions between RS CVn phenomena and BY Dra phenomena are artificial and misleading, arising entirely from historical processes. Observations in the optical and the X-ray wavelength regions are reported. A study of the occurrence times of flare events in terms of the ephemeris of the photometric wave which is known to migrate through the light curve of V471 Tau reveals a strong correlation, suggesting that the flares occur near regions of the K dwarf where spot groups are inferred.
Disastrous events have been drastically increasing – both in frequency and destructive capacity – over the past few years. While advance-notice events have received a great deal of attention in the literature of disaster management, not much attention so far has been given to the no-notice events mainly because of the scarcity of data. As an attempt to address this critical gap, the current study proposes a disaggregate evacuation demand framework to understand evacuees’ travel behavior in case of no-notice emergency events. Here, the proposed framework comprises four main steps of evacuation decision, evacuation planning, tour formation, and activity schedule update. This article is dedicated to the introduction of the framework structure and elaboration on the tour formation step. In this step, we first estimate the total number of intermediate stops, travel time, and distance of the evacuation tours for those who decide to evacuate through a joint modeling structure and then, determine the type of each intermediate stop (if any). It is found that a broad range of factors including evacuees’ demographic profiles, built-environment attributes, and characteristics of the disastrous event plays a significant role in people’s evacuation behavior during no-notice emergency events. The findings of this study can assist responsible agencies in understanding evacuees’ complex behavior, and consequently, in devising effective strategies to alleviate economic damages and casualties resulted by such events.
Organization, equipment, and the current status of the Joint Airport Weather Studies project initiated in relation to the microburst phenomenon are summarized. Some data collection techniques and preliminary statistics on microburst events recorded by Doppler radar are discussed as well. Radar studies show that microbursts occur much more often than expected, with majority of the events being potentially dangerous to landing or departing aircraft. Seventy events were registered, with the differential velocities ranging from 10 to 48 m/s; headwind/tailwind velocity differentials over 20 m/s are considered seriously hazardous. It is noted that a correlation is yet to be established between the velocity differential and incoherent radar reflectivity.
Preliminary results of observations performed using two different lidar systems during the EASOE (European Arctic Stratospheric Ozone Experiment), which has taken place in the winter of 1991-1992 in the northern hemisphere lattitude regions, are presented. The first system is a ground based multiwavelength lidar intended to perform measurements of the ozone vertical distribution in the 5 km to 40 km altitude range. It was located in Sodankyla (67 degrees N, 27 degrees E) as part of the ELSA experiment. The objectives of the ELSA cooperative project is to study the relation between polar stratospheric cloud events and ozone depletion with high vertical resolution and temporal continuity, and the evolution of the ozone distribution in relation to the position of the polar vortex. The second system is an airborne backscatter lidar (Leandre) which allows for the study of the 3-D structure and the optical properties of polar stratospheric clouds. The Leandre instrument is a dual-polarization lidar system, emitting at 532 nm, which allows for the determination of the type of clouds observed, according to the usual classification of polar stratospheric clouds. More than 60 hours of flight were performed in Dec. 1991, and Jan. and Feb. 1992 in Kiruna, Sweden. The operation of the Leandre instrument has led to the observation of the short scale variability of the Pinatubo volcanic cloud in the high latitude regions and to several episodes of polar stratospheric clouds. Preliminary analysis of the data is presented.
This paper presents a study of the dynamics for a single-stage, axial-flow, high speed compressor core, specifically, the NASA Lewis rotor stage 37. Due to the overall blading design for this advanced core compressor, each stage has considerable tip loading and higher speed than most compressor designs, thus, the compressor operates closer to the stall margin. The onset of rotating stall is explained as bifurcations in the dynamics of axial compressors. Data taken from the compressor during a rotating stall event is analyzed. Through the use of a box-assisted correlation dimension methodology, the attractor dimension is determined during the bifurcations leading to rotating stall. The intent of this study is to examine the behavior of precursive stall events so as to predict the entrance into rotating stall. This information may provide a better means to identify, avoid or control the undesirable event of rotating stall formation in high speed compressor cores.
The National Air Quality Forecast Capability (NAQFC) operated in U.S.’s National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matters with aerodynamic diameters less than 2.5μm (PM2.5) over the contiguous 48 U.S. states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions ( CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to the CMAQ’s Carbon Bond 5 (CB05)-Aero6 species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015.The simulated PM2.5 was improved from 0.18 to 0.37 and the mean bias was reduced from -6.74 μg/m3 to -2.96 μg/m3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study, and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the global model CLBCs, such as GEOS CLBCs, are not available.
For nearly a century, studying cosmic-ray air showers has driven progress in our understanding of elementary particle physics. In this work, we revisit the production of millicharged particles in these atmospheric showers and provide new constraints for XENON1T and Super-Kamiokande and new sensitivity estimates of current and future detectors, such as JUNO. We discuss distinct search strategies, specifically studies of single-energy-deposition events, where one electron in the detector receives a relatively large energy transfer, as well as multiple-scattering events consisting of (at least) two relatively small energy depositions. We demonstrate that these atmospheric search strategies — especially the multiple-scattering signature — provide significant room for improvement beyond existing searches, in a way that is complementary to anthropogenic, beam-based searches for MeV-GeV millicharged particles. Finally, we also discuss the implementation of a Monte Carlo simulation for millicharged particle detection in large-volume neutrino detectors, such as IceCube.
This review presents a comprehensive overview of key phenomenological opportunities at the future Electron–Ion Collider (EIC), synthesizing discussions and collaborative research efforts developed within the Korean EIC community and the EICφ collaboration. We explore a diverse range of physics topics central to the EIC scientific program, including the multidimensional tomography of nucleon and nuclear structure, precision Quantum Chromodynamics studies through jet physics and event-shape observables, heavy quarkonium production as a probe of partonic dynamics, and the spectroscopy of exotic hadrons. Furthermore, we discuss the transformative potential of emerging technologies—specifically Machine Learning and Quantum Computing—as essential tools for addressing the computational challenges and maximizing the scientific discovery potential of the EIC era.
For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.
Guidance on Sensor Placement was identified as the top research priority for hydrogen sensors at the 2018 HySafe Research Priority Workshop on hydrogen safety in the category Mitigation, Sensors, Hazard Prevention, and Risk Reduction. This paper discusses the initial steps (Phase 1) to develop such guidance for mechanically ventilated enclosures. This work was initiated as an international collaborative effort to respond to emerging market needs related to the design and deployment equipment for hydrogen infrastructure that is often installed in individual equipment cabinets or ventilated enclosures. The ultimate objective of this effort is to develop guidance for an optimal sensor placement such that, when integrated into a facility design and operation, will allow earlier detection at lower levels of incipient leaks, leading to significant hazard reduction. Reliable and consistent early warning of hydrogen leaks will allow for the risk mitigation by reducing or even eliminating the probability of escalation of small leaks into large and uncontrolled events. To address this issue, a study of a real-world mechanically ventilated enclosure containing GH2 equipment was conducted, where CFD modeling of the hydrogen dispersion (performed by AVT and UQTR, and independently by the JRC) was validated by the NREL Sensor laboratory using a Hydrogen Wide Area Monitor (HyWAM) consisting of a 10-point gas and temperature measurement analyzer. In the release test, helium was used as a hydrogen surrogate. Expansion of indoor releases to other larger facilities (including parking structures, vehicle maintenance facilities and potentially tunnels) and incorporation into QRA tools, such as HyRAM is planned for Phase 2. It is anticipated that results of this work will be used to inform national and international standards such as NFPA 2 Hydrogen Technologies Code, Canadian Hydrogen Installation Code (CHIC) and relevant ISO/TC 197 and CEN documents.
Low-lying coastal cities, exemplified by Norfolk, Virginia, face the challenge of street flooding caused by rainfall and tides, which strain transportation and sewer systems and can lead to personal and property damage. While high-fidelity, physics-based simulations provide accurate predictions of urban pluvial flooding, their computational complexity renders them unsuitable for real-time applications. Using data from Norfolk rainfall events between 2016 and 2018, this study compares the performance of a previous surrogate model based on a random forest algorithm with two deep learning models: Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The comparison of deep learning to the random forest algorithm is motivated by the desire to utilize a machine learning architecture that allows for the future inclusion of common uncertainty quantification techniques and the effective integration of relevant, multi-modal features.
The top quark mass is one of the most intriguing parameters of the standard model (SM). Its value indicates a Yukawa coupling close to unity, and the resulting strong ties to Higgs physics make the top quark mass a crucial ingredient for understanding essential aspects of the electroweak sector of the SM. This review offers the first comprehensive overview of the top quark mass measurements performed by the CMS Collaboration using the data collected at centre-of-mass energies of 7, 8, and 13 TeV. Moreover, a detailed description of the top quark event reconstruction is provided and dedicated studies of the dominant uncertainties in the modelling of the signal processes are discussed. The interpretation of the experimental results on the top quark mass in terms of the SM Lagrangian parameter is challenging and is a focus of an ongoing discussion in the theory community. The CMS Collaboration has performed two main types of top quark mass measurements, addressing this challenge from different perspectives: highly precise ‘direct’ measurements, based on reconstructed top quark decay products and relying exclusively on Monte-Carlo simulations, as well as ‘indirect’ measurements, where the simulations are employed to determine parton-level cross sections that are compared to fixed-order perturbative calculations. Recent mass extractions using Lorentz-boosted top quarks open a new avenue of measurements based on top quark decay products contained in a single particle jet, with promising prospects for accurate theoretical interpretations.
Highlights: • Normal-density and low-density neutrophils from patients with hypertension influx more Na{sup +} compared to normotensive individuals. • Normal-density neutrophils from patients with hypertension generate low levels of reactive oxygen species. • Normal-density and low-density neutrophils from patients with hypertension exhibit lower levels of apoptosis. • Normal-density neutrophils from patients with hypertension maintain an activated and degranulated phenotype. • Low-density neutrophils from patients with hypertension show atypical mitochondrial morphology. Cellular heterogeneity and diversity are recognized to contribute to the functions of neutrophils under homeostatic and pathological conditions. We previously suggested that the chronic inflammatory responses associated with hypertension (HTN) are related to the participation of different subpopulations of neutrophils. Two populations of neutrophils can be obtained by density gradient centrifugation: normal-density neutrophils (NDN) and low-density neutrophils (LDN). However, the lack of standardized functional protocols has limited phenotypic characterization and functional comparisons of LDN and NDN. Based on their capability to incorporate Na{sup +}, maturity and activation stage, we characterized NDN and LDN in blood samples from ten patients with HTN and ten healthy individuals (HI) using flow cytometry. We compared the levels of reactive oxygen species (ROS), generation of neutrophil extracellular traps (NETs) and levels of apoptosis in NDN and LDN. In general, the NDN and LDN subpopulations from patients with HTN exhibited higher levels of sodium influx and ROS, and lower levels of apoptosis than the corresponding NDN and LDN subsets from HI. Transmission electron microscopy revealed NDN and LDN from patients with HTN exhibited alterations to mitochondrial morphology and fewer cytoplasmic granules than the corresponding HI subpopulations. Our results indicate both the NDN and LDN subpopulations enhance the effects of inflammation that contribute to the pathophysiology of HTN. Further detailed studies are required to characterize the events during ontogeny of the myeloid lineage that result in the diverse phenotypic characteristics of each subpopulation of LDN and NDN.
The Long Island Sound (LIS) Tropospheric Ozone Study was a multi-agency collaborative field campaign conducted during the summer of 2018 to improve the understanding of ozone chemistry and transport from New York City to areas downstream, especially the LIS and adjacent Connecticut coastline. Measurements made during this campaign were leveraged to test and evaluate the coupled WRF-CMAQ model at 12 km, 4 and 1.33 km horizontal grid spacing. Special attention was placed on the model's representation of sea breeze circulations, low level jets, and boundary layer evolution. The evaluation suggests using higher resolutions resulted in improved surface meteorology statistics throughout the whole summer, with temperature biases seeing the biggest statistical improvements when using 1.33-km grid spacing, going from –0.12 to 0.08 K. Additionally, 4-km grid spacing provided the biggest advantage when simulating ozone over the region of interest, with biases being reduced from 2.40 to 0.57 to 0.37 ppbV with increased resolution. Case studies of two high ozone concentration events (July 10 and August 6) revealed that sound breezes and low-level jets had a critical role in transporting pollutant-rich, shallow marine air masses from the LIS inland over the Connecticut coast. Modifications were made to the representation of sea surface temperatures, which subsequently improved the simulation of surface ozone predictions.
Understanding potential response of forest carbon (C) and nutrient storage to warming is important for climate mitigation policies. Unfortunately, those responses are difficult to predict in seasonally dry forests, in part, because ecosystem processes are highly sensitive to both changes in temperature and precipitation. We investigated how warming might alter stocks of C, nitrogen (N), and phosphorus (P) in vegetation and the entire regolith (soil + weathered bedrock or “saprock”) using a space-for-time substitution along a bioclimatic gradient in the Sierra Nevada, California. The pine-oak and mixed-conifer forests between 1,160–2,015 m elevation have more optimal climates (not too dry or hot) for ecosystem productivity, soil weathering, and cycling of essential elements than the oak savannah (405 m) and subalpine forest (2,700 m). We found decreases in overstory vegetation nutrient stocks with decreasing elevation because of enhanced water limitation and greater occurrence of disturbances. Stocks of C, N, and P in the entire regolith peaked at the pine-oak and mixed-conifer forests across the bioclimatic gradient, driven by thicker regolith profiles and greater nutrient input rates. These observations suggest long-term warming will decrease ecosystem nutrient storage at the warmer, transitional pine-oak zone, but will increase nutrient storage at the colder, subalpine zone. Assuming steady-state conditions, we found the mean residence time of ecosystem C decreased with projected rising air temperatures and increased following a major drought event across the bioclimatic gradient. Our study emphasizes potentially elevation-dependent changes in nutrient storage and C persistence with warming in seasonally dry forests.
Protein tyrosine phosphatases regulate a myriad of essential subcellular signaling events, yet they remain difficult to study in their native biophysical context. Here we develop a minimally disruptive optical approach to control protein tyrosine phosphatase 1B (PTP1B)—an important regulator of receptor tyrosine kinases and a therapeutic target for the treatment of diabetes, obesity, and cancer—and we use that approach to probe the intracellular function of this enzyme. Our conservative architecture for photocontrol, which consists of a protein-based light switch fused to an allosteric regulatory element, preserves the native structure, activity, and subcellular localization of PTP1B, affords changes in activity that match those elicited by post-translational modifications inside the cell, and permits experimental analyses of the molecular basis of optical modulation. Findings indicate, most strikingly, that small changes in the activity of PTP1B can cause large shifts in the phosphorylation states of its regulatory targets.
Hyperdiverse tropical rainforests, such as the aseasonal forests in Southeast Asia, are supported by high annual rainfall. Its canopy is dominated by the species-rich tree family of Dipterocarpaceae (Asian dipterocarps), which has both ecological (e.g., supports flora and fauna) and economical (e.g., timber production) importance. Recent ecological studies suggested that rare irregular drought events may be an environmental stress and signal for the tropical trees. We assembled the genome of a widespread but near threatened dipterocarp, Shorea leprosula, and analyzed the transcriptome sequences of ten dipterocarp species representing seven genera. Comparative genomic and molecular dating analyses suggested a whole-genome duplication close to the Cretaceous-Paleogene extinction event followed by the diversification of major dipterocarp lineages (i.e. Dipterocarpoideae). Interestingly, the retained duplicated genes were enriched for genes upregulated by no-irrigation treatment. These findings provide molecular support for the relevance of drought for tropical trees despite the lack of an annual dry season.