A survey of smart grid architectures, applications, benefits and standardization

The successful transformation of conventional power grids into Smart Grids (SG) will require robust and scalable communication network infrastructure. The SGs will facilitate bidirectional electricity flow, advanced load management, a self-healing protection mechanism and advanced monitoring capabilities to make the power system more energy efficient and reliable. In this paper SG communication network architectures, standardization efforts and details of potential SG applications are identified. The future deployment of real-time or near-real-time SG applications is dependent on the introduction of a SG compatible communication system that includes a communication protocol for cross-domain traffic flows within the SG. This paper identifies the challenges within the cross-functional domains of the power and communication systems that current research aims to overcome. The status of SG related machine to machine communication system design is described and recommendations are provided for diverse new and innovative traffic features

Software defined neighborhood area network for smart grid applications

Information gathered from the Smart Grid (SG) devices located in end user premises provides a valuable resource that can be used to modify the behavior of SG applications. Decentralized and distributed deployment of neighborhood area network (NAN) devices makes it a challenge to manage SG efficiently. The NAN communication network architecture should be designed to aggregate and disseminate information among different SG domains. In this paper, we present a communication framework for NAN based on wireless sensor networks using the software defined networking paradigm. The data plane devices, such as smart meters, intelligent electronic devices, sensors, and switches are controlled via an optimized controller hierarchy deployed using a separate control plane. An analytical model is developed to determine the number of switches and controllers required for the NAN and the results of several test scenarios are presented. A Castalia based simulation model was used to analyze the performance of modified NAN performance

Treatment of Gaucher disease with an enzyme inhibitor

The hypothesis is offered predicting that Caucher patients could be treated with a drug that slows the synthesis of glucosylceramide, the lipid that accumulates in this disorder. The present therapeutic approach involves augmenting the defective enzyme, glucosylceramide β-glucosidase, with exogenous β-glucosidase isolated from human tissue. This spectacularly expensive mode of treatment should be replaceable with a suitable enzyme inhibitor that simply slows formation of the lipid and matches the rate of synthesis with the rate of the defective, slowly working β-glucosidase. Several drugs that possess this ability are available, the best known of which is 1-phenyl-2-decanoylamino-3-morpholino-1-propanol (PDMP), a designer inhibitor that resembles the synthase's substrate and product. PDMP has been found to be effective in mice, rats, fish, and a wide variety of cultured cells. Its use, at suitable dosages, seems to be harmless, although long-term tests have not been made. The lack of suitable animal models of Gaucher disease has made it difficult to test the hypothesis adequately, but PDMP does rapidly lower the levels of glucosylceramide in normal animal tissues and the animals evidently do well with the lowered levels of glucosylceramide and its more complex glycolipid metabolites.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45689/1/10719_2004_Article_BF00731489.pd

Electrical detection of magnetic skyrmions by non-collinear magnetoresistance

Magnetic skyrmions are localised non-collinear spin textures with high potential for future spintronic applications. Skyrmion phases have been discovered in a number of materials and a focus of current research is the preparation, detection, and manipulation of individual skyrmions for an implementation in devices. Local experimental characterization of skyrmions has been performed by, e.g., Lorentz microscopy or atomic-scale tunnel magnetoresistance measurements using spin-polarised scanning tunneling microscopy. Here, we report on a drastic change of the differential tunnel conductance for magnetic skyrmions arising from their non-collinearity: mixing between the spin channels locally alters the electronic structure, making a skyrmion electronically distinct from its ferromagnetic environment. We propose this non-collinear magnetoresistance (NCMR) as a reliable all-electrical detection scheme for skyrmions with an easy implementation into device architectures

Multiparticle azimuthal correlations for extracting event-by-event elliptic and triangular flow in Au + Au collisions at sNN =200 GeV

We present measurements of elliptic and triangular azimuthal anisotropy of charged particles detected at forward rapidity 1<|η|<3 in Au + Au collisions at sNN=200 GeV, as a function of centrality. The multiparticle cumulant technique is used to obtain the elliptic flow coefficients v2{2},v2{4},v2{6}, and v2{8}, and triangular flow coefficients v3{2} and v3{4}. Using the small-variance limit, we estimate the mean and variance of the event-by-event v2 distribution from v2{2} and v2{4}. In a complementary analysis, we also use a folding procedure to study the distributions of v2 and v3 directly, extracting both the mean and variance. Implications for initial geometrical fluctuations and their translation into the final-state momentum distributions are discussed

Pseudorapidity Dependence of Particle Production and Elliptic Flow in Asymmetric Nuclear Collisions of p+Al, p+Au, d+Au, and ^{3}He+Au at sqrt[s_{NN}]=200 GeV.

Asymmetric nuclear collisions of p+Al, p+Au, d+Au, and ^{3}He+Au at sqrt[s_{NN}]=200  GeV provide an excellent laboratory for understanding particle production, as well as exploring interactions among these particles after their initial creation in the collision. We present measurements of charged hadron production dN_{ch}/dη in all such collision systems over a broad pseudorapidity range and as a function of collision multiplicity. A simple wounded quark model is remarkably successful at describing the full data set. We also measure the elliptic flow v_{2} over a similarly broad pseudorapidity range. These measurements provide key constraints on models of particle emission and their translation into flow

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources

Studies of the action of ceramide-like substances ( d - and l -PDMP) on sphingolipid glycosyltransferases and purified lactosylceramide synthase

We have studied the effects of D -threo-1-phenyl-2-decanoylamino-3-morpholino-1-propanol ( D -PDMP) and its L -enantiomer on glycosphingolipids in cultured normal human kidney proximal tubular cells. We found that D -PDMP exerted a concentration-dependent reduction in the metabolic labelling and cellular levels of glucosylceramide (GlcCer), lactosylceramide (LacCer), and the globo-series glycosphingolipids, GbOse 3 Cer and GbOse 4 Cer. It also directly inhibited the activity of UDP-glucose:ceramide β1 → 4-glucosyltransferase (GlcT-1) and UDP-galactose: GlcCer β1 → 4 galactosyltransferase (GalT-2). In contrast, L -PDMP had opposite effects on the metabolic labelling of GlcCer, LacCer, and GbOse 3 Cer. The levels of GlcCer and LacCer were increased, while the labelling and level of GbOse 4 Cer were strongly reduced. Purified GalT-2 from human kidney was inhibited by D -PDMP and stimulated by L -PDMP. It appears likely that the different glycosphingolipid glycosyltransferases possess similar binding sites for the ceramide moiety, which are blocked by binding to D -PDMP and, in the case of GbOse 4 Cer synthase, by L -PDMP as well. The stimulatory effects of L -PDMP on GlcCer and LacCer synthases may be the result of binding to a modulatory site on the glycosyltransferases; in intact cells, the enzyme-analog complex may afford protection against the normal catabolic inactivation of the enzymes.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45706/1/10719_2004_Article_BF00731481.pd

Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron

We study the underlying event in proton-antiproton collisions by examining the behavior of charged particles (transverse momentum pT > 0.5 GeV/c, pseudorapidity |\eta| < 1) produced in association with large transverse momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan production) or the leading jet (in high-pT jet production) in each event to define three regions of \eta-\phi space; toward, away, and transverse, where \phi is the azimuthal scattering angle. For Drell-Yan production (excluding the leptons) both the toward and transverse regions are very sensitive to the underlying event. In high-pT jet production the transverse region is very sensitive to the underlying event and is separated into a MAX and MIN transverse region, which helps separate the hard component (initial and final-state radiation) from the beam-beam remnant and multiple parton interaction components of the scattering. The data are corrected to the particle level to remove detector effects and are then compared with several QCD Monte-Carlo models. The goal of this analysis is to provide data that can be used to test and improve the QCD Monte-Carlo models of the underlying event that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.

Sheldon Spectrum and the Plankton Paradox: Two Sides of the Same Coin : A trait-based plankton size-spectrum model

The Sheldon spectrum describes a remarkable regularity in aquatic ecosystems: the biomass density as a function of logarithmic body mass is approximately constant over many orders of magnitude. While size-spectrum models have explained this phenomenon for assemblages of multicellular organisms, this paper introduces a species-resolved size-spectrum model to explain the phenomenon in unicellular plankton. A Sheldon spectrum spanning the cell-size range of unicellular plankton necessarily consists of a large number of coexisting species covering a wide range of characteristic sizes. The coexistence of many phytoplankton species feeding on a small number of resources is known as the Paradox of the Plankton. Our model resolves the paradox by showing that coexistence is facilitated by the allometric scaling of four physiological rates. Two of the allometries have empirical support, the remaining two emerge from predator-prey interactions exactly when the abundances follow a Sheldon spectrum. Our plankton model is a scale-invariant trait-based size-spectrum model: it describes the abundance of phyto- and zooplankton cells as a function of both size and species trait (the maximal size before cell division). It incorporates growth due to resource consumption and predation on smaller cells, death due to predation, and a flexible cell division process. We give analytic solutions at steady state for both the within-species size distributions and the relative abundances across species