Socioeconomic vulnerability and differential impact of severe weather-induced power outages.

In response to concerns about increasingly intense Atlantic hurricanes, new federal climate and environmental justice policies aim to mitigate the unequal impact of environmental disasters on economically and socially vulnerable communities. Recent research emphasizes that standard procedures for restoring power following extreme weather could be one significant contributor to these divergent outcomes. Our paper evaluates the hypothesis that more economically and socially vulnerable communities experience longer-duration power outages following hurricanes than less vulnerable communities do, conditional on the severity of the impact of the storm itself. Using data from eight major Atlantic hurricanes that made landfall between January 2017 and October 2020 and induced power outages for over 15 million customers in 588 counties in the Southeast, we demonstrate a significant relationship between socioeconomic vulnerability and the duration of time that elapses before power is restored for 95% of customers in a county. Specifically, a one-decile change in the socioeconomic status theme in the Social Vulnerability Index, a measure of vulnerability produced by the Centers for Disease Control and Prevention and the Agency for Toxic Substances and Disease Registry, produces a 6.1% change in expected outage duration in a focal county. This is equivalent to a 170-min average change in the period of time prior to power restoration.

Homogenization of diffusion in multicomponent liquids.

Diffusion is a key kinetic factor determining chemical mixing and phase formation in liquids. In multicomponent systems, the presence of different elements makes it experimentally challenging to measure diffusivities and understand their mechanisms. Using a molecular dynamics simulation, we obtain the diffusion constants and the atomic process of a model Cantor alloy liquid made of five equimolar components. We show that the diffusivities conform remarkably well to the Arrhenius law in a wide range of temperature covering both the equilibrium and undercooled liquid regions. The activation energies for all the alloy elements with different bonding energies and atomic sizes are close to each other. The results suggest that the diffusivity in the multicomponent liquid tends to be homogenized by the components with marginal differences. This finding allows us to treat the different elements as a single type of atom, the pseudo-atom, for diffusional and maybe structural and physical properties in multicomponent liquids.

Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria.

A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island's settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community.

Regulation of FcRγ function by site-specific serine phosphorylation.

The common FcRγ, an immunoreceptor tyrosine-based activation motif (ITAM)- containing adaptor protein, associates with multiple leukocyte receptor complexes and mediates signal transduction through the ITAM in the cytoplasmic domain. The presence of multiple serine and threonine residues within this motif suggests the potential for serine/threonine phosphorylation in modulating signaling events. Single-site mutational analysis of these residues in RBL-2H3 cells indicates that each may contribute to net FcRγ-mediated signaling, and mass spectrometry of WT human FcRγ from receptor-stimulated cells shows consistent preferential phosphorylation of the serine residue at position 51. Immunoblot analysis, mass spectrometry, and mutational analyses showed that phosphorylation of serine 51 in the 7-residue spacer between the 2 YxxL sequences regulates FcRγ signaling by inhibiting tyrosine phosphorylation at the membrane proximal Y47 position of the ITAM, but not phosphorylation at position Y58. This inhibition results in reduced Syk recruitment and activation. With in vitro kinase assays, PKC-δ and PKA show preferential phosphorylation of S51. Serine/threonine phosphorylation of the FcRγ ITAM, which functions as an integrator of multiple signaling elements, may explain in part the contribution of variants in PKC-δ and other PKC isoforms to some autoimmune phenotypes.

Learning geotemporal nonstationary failure and recovery of power distribution.

Smart energy grid is an emerging area for new applications of machine learning in a nonstationary environment. Such a nonstationary environment emerges when large-scale failures occur at power networks because of external disruptions such as hurricanes and severe storms. Power distribution networks lie at the edge of the grid, and are especially vulnerable to external disruptions. Quantifiable approaches are lacking and needed to learn nonstationary behaviors of large-scale failure and recovery of power distribution. This paper studies such nonstationary behaviors in three aspects. First, a novel formulation is derived for an entire life cycle of large-scale failure and recovery of power distribution. Second, spatial-temporal models of failure and recovery of power distribution are developed as geolocation-based multivariate nonstationary GI(t)/G(t)/∞ queues. Third, the nonstationary spatial-temporal models identify a small number of parameters to be learned. Learning is applied to two real-life examples of large-scale disruptions. One is from Hurricane Ike, where data from an operational network is exact on failures and recoveries. The other is from Hurricane Sandy, where aggregated data is used for inferring failure and recovery processes at one of the impacted areas. Model parameters are learned using real data. Two findings emerge as results of learning: 1) failure rates behave similarly at the two different provider networks for two different hurricanes but differently at the geographical regions and 2) both the rapid and slow-recovery are present for Hurricane Ike but only slow recovery is shown for a regional distribution network from Hurricane Sandy.

The unique cytoplasmic domain of human FcγRIIIA regulates receptor-mediated function.

Ligand specificity characterizes receptors for Abs and many other immune receptors, but the common use of the FcR γ-chain as their signaling subunit challenges the concept that these receptors are functionally distinct. We hypothesized that elements for specificity might be determined by the unique cytoplasmic domain (CY) sequences of the ligand-binding α-chains of γ-chain-associated receptors. Among Fcγ receptors, a protein kinase C (PKC) phosphorylation consensus motif [RSSTR], identified within the FcγRIIIa (CD16A) CY by in silico analysis, is specifically phosphorylated by PKCs, unlike other FcRs. Phosphorylated CD16A mediates a more robust calcium flux, tyrosine phosphorylation of Syk, and proinflammatory cytokine production, whereas nonphosphorylatable CD16A is more effective at activation of the Gab2/PI3K pathway, leading to enhanced degranulation. S100A4, a specific protein-binding partner for CD16A-CY newly identified by yeast two-hybrid analysis, inhibits phosphorylation of CD16A-CY by PKC in vitro, and reduction of S100A4 levels in vivo enhances receptor phosphorylation upon cross-linking. Taken together, PKC-mediated phosphorylation of CD16A modulates distinct signaling pathways engaged by the receptor. Calcium-activated binding of S100A4 to CD16A, promoted by the initial calcium flux, attenuates the phosphorylation of CY, and, acting as a molecular switch, may both serve as a negative feedback on cytokine production pathways during sustained receptor engagement and favor a shift to degranulation, consistent with the importance of granule release following conjugate formation between CD16A(+) effector cells and target cells. This switch mechanism points to new therapeutic targets and provides a framework for understanding novel receptor polymorphisms.

IgA and IgG antineutrophil cytoplasmic antibody engagement of Fc receptor genetic variants influences granulomatosis with polyangiitis.

Granulomatosis with polyangiitis (Wegener's) is a rare autoimmune neutrophil-mediated vasculitis that can cause renal disease and mucosal manifestations. Antineutrophil cytoplasmic antibodies (ANCA) are present in many patients, vary in level over time, and induce neutrophil activation through engagement with Fc receptors (FcRs). Given roles for FcRs in ANCA-mediated neutrophil activation and IgA antibodies in mucosal immunity, we hypothesized that FcR genetics and previously unappreciated IgA ANCA affect clinical presentation. We assembled a total of 673 patients and 413 controls from two multicenter cohorts, performed ELISA and immunofluorescence assays to determine IgA and IgG ANCA positivity, and used Illumina, TaqMan, or Pyrosequencing to genotype eight haplotype-tagging SNPs in the IgA FcR (FCAR) and to determine NA1/NA2 genotype of FCGR3B, the most prevalent neutrophil IgG FcR. We evaluated neutrophil activation by measuring degranulation marker CD11b with flow cytometry or neutrophil extracellcular trap formation with confocal microscopy. Functional polymorphisms in FCGR3B and FCAR differed between patient groups stratified by renal involvement. IgA ANCA were found in ∼30% of patients and were less common in patients with severe renal disease. Neutrophil stimulation by IgA or IgG ANCA led to degranulation and neutrophil extracellcular trap formation in a FcR allele-specific manner (IgA:FCAR P = 0.008; IgG:FCGR3B P = 0.003). When stimulated with IgA and IgG ANCA together, IgG ANCA induced neutrophil activation was reduced (P = 0.0001). FcR genotypes, IgA ANCA, and IgG ANCA are potential prognostic and therapeutic targets for understanding the pathogenesis and presentation of granulomatosis with polyangiitis (Wegener's).

Immune opsonins modulate BLyS/BAFF release in a receptor-specific fashion.

TNF ligand superfamily member 13B (B lymphocyte stimulator (BLyS), B cell activating factor (BAFF)) promotes primary B cell proliferation and Ig production. While the soluble form of BLyS/BAFF is thought to be the primary biologically active form, little is known about the regulation of its cleavage and processing. We provide evidence that Fcgamma receptor cross-linking triggers a rapid release of soluble, biologically active BLyS/BAFF from myeloid cells. Surprisingly, this function is primarily mediated by FcgammaRI, but not FcgammaRIIa as defined by specific mAb, and can be initiated by both IgG and C reactive protein as ligands. The generation of a B cell proliferation and survival factor by both innate and adaptive immune opsonins through engagement of an Fcgamma receptor, which can also enhance Ag uptake and presentation, provides a unique opportunity to facilitate Ab production. These results provide a mechanism by which Fcgamma receptors can elevate circulating BLyS levels and promote autoantibody production in immune complex-mediated autoimmune diseases.

FcalphaRI (CD89) alleles determine the proinflammatory potential of serum IgA.

The human IgA FcR (FcalphaRI; CD89) mediates a variety of immune system functions including degranulation, endocytosis, phagocytosis, cytokine synthesis, and cytokine release. We have identified a common, nonsynonymous, single nucleotide polymorphism (SNP) in the coding region of CD89 (844A-->G) (rs16986050), which changes codon 248 from AGC (Ser(248)) to GGC (Gly(248)) in the cytoplasmic domain of the receptor. The two different alleles demonstrate significantly different FcalphaRI-mediated intracellular calcium mobilization and degranulation in rat basophilic leukemia cells and cytokine production (IL-6 and TNF-alpha) in murine macrophage P388D1 cells. In the absence of FcR gamma-chain association in P388D1 cells, the Ser(248)-FcalphaRI allele does not mediate cytokine production, but the Gly(248)-FcalphaRI allele retains the capacity to mediate a robust production of proinflammatory cytokine. This allele-dependent difference is also seen with FcalphaRI-mediated IL-6 cytokine release by human neutrophils ex vivo. These findings and the enrichment of the proinflammatory Gly(248)-FcalphaRI allele in systemic lupus erythematosus populations in two ethnic groups compared with their respective non-systemic lupus erythematosus controls suggest that FcalphaRI (CD89) alpha-chain alleles may affect receptor-mediated signaling and play an important role in the modulation of immune responses in inflammatory diseases.

Spatial-temporal modeling of malware propagation in networks.

Network security is an important task of network management. One threat to network security is malware (malicious software) propagation. One type of malware is called topological scanning that spreads based on topology information. The focus of this work is on modeling the spread of topological malwares, which is important for understanding their potential damages, and for developing countermeasures to protect the network infrastructure. Our model is motivated by probabilistic graphs, which have been widely investigated in machine learning. We first use a graphical representation to abstract the propagation of malwares that employ different scanning methods. We then use a spatial-temporal random process to describe the statistical dependence of malware propagation in arbitrary topologies. As the spatial dependence is particularly difficult to characterize, the problem becomes how to use simple (i.e., biased) models to approximate the spatially dependent process. In particular, we propose the independent model and the Markov model as simple approximations. We conduct both theoretical analysis and extensive simulations on large networks using both real measurements and synthesized topologies to test the performance of the proposed models. Our results show that the independent model can capture temporal dependence and detailed topology information and, thus, outperforms the previous models, whereas the Markov model incorporates a certain spatial dependence and, thus, achieves a greater accuracy in characterizing both transient and equilibrium behaviors of malware propagation.

[Experiment on the sexual virility of immature mice immunized with LHRH fusion protein vaccine].

OBJECTIVE: To observe the sexual virility of immature immature male mice were divided into a pre-ablactation group (n 10). The first two groups were immunized with the LHRH fusion proportion of pregnant female mice, the morphological and histological examined to conform the emasculating effect of the vaccine. When ted with testosterone (1.0 ml each) , the post-ablactation ones were rameters. RESULTS: The sexual virility of the immature mice immunized in 3 -4 months. CONCLUSION: The LHRH fusion protein vaccine mice after ablactation, and the sexual virility can recover in the pre-ablactation decrease.

A pattern recognition serine proteinase triggers the prophenoloxidase activation cascade in the tobacco hornworm, Manduca sexta.

A serine proteinase cascade in insect hemolymph mediates prophenoloxidase activation, a defense mechanism against pathogen or parasite infection. Little is known regarding its initiating proteinase or how this enzyme is activated in response to invading microorganisms. We have isolated from the tobacco hornworm, Manduca sexta, a cDNA encoding a modular protein designated hemolymph proteinase 14 (HP14). It contains five low density lipoprotein receptor class A repeats, a Sushi domain, a unique Cys-rich region, and a proteinase-catalytic domain. The HP14 mRNA exists in fat body and hemocytes of the naive larvae, and its level increases significantly at 24 h after a bacterial challenge. We expressed proHP14 with a carboxyl-terminal hexahistidine tag in a baculovirus/insect cell system and detected the recombinant protein in two forms. The 87-kDa protein was primarily intracellular, whereas the 75-kDa form was present in the medium. Interaction with peptidoglycan resulted in proteolytic processing of the purified zymogen and generation of an amidase activity. Supplementation of hemolymph with proHP14 greatly enhanced prophenoloxidase activation in response to Micrococcus luteus. These data suggest that proHP14 is a pattern recognition protein that binds to bacteria and autoactivates and triggers the prophenoloxidase activation system in the hemolymph of M. sexta.

Expression and in vitro activation of Manduca sexta prophenoloxidase-activating proteinase-2 precursor (proPAP-2) from baculovirus-infected insect cells.

Prophenoloxidase activation is a component of the immune system in insects and crustaceans. We recently purified and cloned a new prophenoloxidase-activating proteinase (PAP-2) from hemolymph of the tobacco hornworm Manduca sexta [J. Biol. Chem. 278, 3552-3561]. As the terminal component of a putative serine proteinase cascade, this enzyme activates prophenoloxidase (proPO) via limited proteolysis. To purify and study the activating proteinase for PAP-2 from this insect, we expressed the zymogen of PAP-2 (proPAP-2) in insect cells infected by a recombinant baculovirus that harbors the cDNA. To facilitate the purification of proPAP-2, we modified a commercial vector (pFastBac1) by inserting a synthetic DNA fragment encoding a hexahistidine sequence, allowing fusion of the affinity tag to the carboxyl terminus of a protein. After Spodoptera frugiperda Sf21 cells were infected by the virus, recombinant proPAP-2 was efficiently secreted into the media at a concentration of 5.9 microg/ml under the optimal conditions. After ammonium sulfate precipitation, the proenzyme was purified to near homogeneity by affinity chromatography on Ni(2+)-NTA agarose. Western blot analysis indicated that the recombinant proPAP-2 has a mobility slightly lower than that of the zymogen from M. sexta hemolymph. The molecular mass and isoelectric point of proPAP-2 were determined to be 47,573+/-11Da and 6.6, respectively. After the purified proenzyme was added to hemolymph from induced M. sexta larvae, it was rapidly activated by an unknown proteinase in the presence of peptidoglycan.

A serpin mutant links Toll activation to melanization in the host defence of Drosophila.

A prominent response during the Drosophila host defence is the induction of proteolytic cascades, some of which lead to localized melanization of pathogen surfaces, while others activate one of the major players in the systemic antimicrobial response, the Toll pathway. Despite the fact that gain-of-function mutations in the Toll receptor gene result in melanization, a clear link between Toll activation and the melanization reaction has not been firmly established. Here, we present evidence for the coordination of hemolymph-borne melanization with activation of the Toll pathway in the Drosophila host defence. The melanization reaction requires Toll pathway activation and depends on the removal of the Drosophila serine protease inhibitor Serpin27A. Flies deficient for this serpin exhibit spontaneous melanization in larvae and adults. Microbial challenge induces its removal from the hemolymph through Toll-dependent transcription of an acute phase immune reaction component.

Network Synthesis through Data-Driven Growth and Decay.

AN ALGORITHM FOR ADDITION AND DELETION (ADDEL) OF RESOURCES DURING LEARNING IS DEVELOPED TO ACHIEVE TWO GOALS: (1) to find feed-forward multilayer networks that are as small as possible, (2) to find an appropriate structure for such small networks. These goals are accomplished by operating alternately between an adding phase and a deleting phase while learning the given input-output associations. The adding phase develops a crude structure by filling in resources (connections, units and layers) at a virtual multilayer network with a maximum of L possible layers. The deleting phase then removes any unnecessary connections to obtain a refined structure. The additions and deletions are done based on a sensitivity measure and a corresponding probability rule so that only the synapses which are most effective in reducing the output error are preserved. A generalization error estimated from a validation set is used to control the alternation between the two learning phases and the termination of learning. Simulations, including handwritten digit recognition, demonstrate that the algorithm is effective in finding an appropriate network structure for a small network which can generalize well. The algorithm is used to investigate when the size of a network is important for generalization. Copyright 1997 Elsevier Science Ltd.

An Efficient EM-based Training Algorithm for Feedforward Neural Networks.

A fast training algorithm is developed for two-layer feedforward neural networks based on a probabilistic model for hidden representations and the EM algorithm. The algorithm decomposes training the original two-layer networks into training a set of single neurons. The individual neurons are then trained via a linear weighted regression algorithm. Significant improvement on training speed has been made using this algorithm for several bench-mark problems. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.