Distributed Optimal Frequency Control Considering a Nonlinear Network-Preserving Model

This paper addresses the distributed optimal frequency control of power systems considering a network-preserving model with nonlinear power flows and excitation voltage dynamics. Salient features of the proposed distributed control strategy are fourfold: i) nonlinearity is considered to cope with large disturbances; ii) only a part of generators are controllable; iii) no load measurement is required; iv) communication connectivity is required only for the controllable generators. To this end, benefiting from the concept of 'virtual load demand', we first design the distributed controller for the controllable generators by leveraging the primal-dual decomposition technique. We then propose a method to estimate the virtual load demand of each controllable generator based on local frequencies. We derive incremental passivity conditions for the uncontrollable generators. Finally, we prove that the closed-loop system is asymptotically stable and its equilibrium attains the optimal solution to the associated economic dispatch problem. Simulations, including small and large-disturbance scenarios, are carried on the New England system, demonstrating the effectiveness of our design

Online Station Assignment for Electric Vehicle Battery Swapping

This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that request battery swapping from a central operator, i.e., in the absence of future information a battery swapping service station has to be assigned instantly to each EV upon its request. Based on EVs' locations, the availability of fully-charged batteries at service stations in the system, as well as traffic conditions, the assignment aims to minimize cost to EVs and congestion at service stations. Inspired by a polynomial-time offline solution via a bipartite matching approach, we develop an efficient and implementable online station assignment algorithm that provably achieves the tight (optimal) competitive ratio under mild conditions. Monte Carlo experiments on a real transportation network by Baidu Maps show that our algorithm performs reasonably well on realistic inputs, even with a certain amount of estimation error in parameters

Online Station Assignment for Electric Vehicle Battery Swapping

This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that request battery swapping from a central operator, i.e., in the absence of future information a battery swapping service station has to be assigned instantly to each EV upon its request. Based on EVs' locations, the availability of fully-charged batteries at service stations in the system, as well as traffic conditions, the assignment aims to minimize cost to EVs and congestion at service stations. Inspired by a polynomial-time offline solution via a bipartite matching approach, we develop an efficient and implementable online station assignment algorithm that provably achieves the tight (optimal) competitive ratio under mild conditions. Monte Carlo experiments on a real transportation network by Baidu Maps show that our algorithm performs reasonably well on realistic inputs, even with a certain amount of estimation error in parameters

Networked Cournot Competition in Platform Markets: Access Control and Efficiency Loss

This paper studies network design and efficiency loss in open and discriminatory access platforms under networked Cournot competition. In open platforms, every firm connects to every market, while discriminatory platforms limit connections between firms and markets to improve social welfare. We provide tight bounds on the efficiency loss of both platforms; (i) that the efficiency loss at a Nash equilibrium under open access is bounded by 3/2, and (ii) for discriminatory access platforms, we provide a greedy algorithm for optimizing network connections that guarantees efficiency loss at a Nash equilibrium is bounded by 4/3, under an assumption on the linearity of cost functions

Differential expression of microRNAs during fiber development between fuzzless- lintless mutant and its wild-type allotetraploid cotton

Cotton is one of the most important textile crops but little is known how microRNAs regulate cotton fiber development. Using a well-studied cotton fiberless mutant Xu-142-fl, we compared 54 miRNAs for their expression between fiberless mutant and its wildtype. In wildtype Xu-142, 26 miRNAs are involved in cotton fiber initiation and 48 miRNAs are related to primary wall synthesis and secondary wall thickening. Thirty three miRNAs showed different expression in fiber initiation between Xu-142 and Xu- 142-fl. These miRNAs potentially target 723 protein-coding genes, including transcription factors, such as MYB, ARF, and LRR. ARF18 was newly predicted targets of miR160a, and miR160a was expressed at higher level in −2DPA of Xu-142-fl compared with Xu-142. Furthermore, the result of Gene Ontology- based term classification (GO), EuKaryotic Orthologous Groups (KOG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis shows that miRNA targets were classified to 222 biological processes, 64 cellular component and 42 molecular functions, enriched in 22 KOG groups, and classified into 28 pathways. Together, our study provides evidence for better understanding of miRNA regulatory roles in the process of fiber development, which is helpful to increase fiber yield and improve fiber quality

Circuit dissection of the role of somatostatin in itch and pain

Stimuli that elicit itch are detected by sensory neurons that innervate the skin. This information is processed by the spinal cord; however, the way in which this occurs is still poorly understood. Here we investigated the neuronal pathways for itch neurotransmission, particularly the contribution of the neuropeptide somatostatin. We find that in the periphery, somatostatin is exclusively expressed in Nppb+ neurons, and we demonstrate that Nppb+somatostatin+ cells function as pruriceptors. Employing chemogenetics, pharmacology and cell-specific ablation methods, we demonstrate that somatostatin potentiates itch by inhibiting inhibitory dynorphin neurons, which results in disinhibition of GRPR+ neurons. Furthermore, elimination of somatostatin from primary afferents and/or from spinal interneurons demonstrates differential involvement of the peptide released from these sources in itch and pain. Our results define the neural circuit underlying somatostatin-induced itch and characterize a contrasting antinociceptive role for the peptide

Human macrophages differentiated in the presence of vitamin D3 restrict dengue virus infection and innate responses by downregulating mannose receptor expression

ABSTARCT: Severe dengue disease is associated with high viral loads and overproduction of pro-inflammatory cytokines, suggesting impairment in the control of dengue virus (DENV) and the mechanisms that regulate cytokine production. Vitamin D3 has been described as an important modulator of immune responses to several pathogens. Interestingly, increasing evidence has associated vitamin D with decreased DENV infection and early disease recovery, yet the molecular mechanisms whereby vitamin D reduces DENV infection are not well understood. METHODS AND PRINCIPAL FINDINGS: Macrophages represent important cell targets for DENV replication and consequently, they are key drivers of dengue disease. In this study we evaluated the effect of vitamin D3 on the differentiation of monocyte-derived macrophages (MDM) and their susceptibility and cytokine response to DENV. Our data demonstrate that MDM differentiated in the presence of vitamin D3 (D3-MDM) restrict DENV infection and moderate the classical inflammatory cytokine response. Mechanistically, vitamin D3-driven differentiation led to reduced surface expression of C-type lectins including the mannose receptor (MR, CD206) that is known to act as primary receptor for DENV attachment on macrophages and to trigger of immune signaling. Consequently, DENV bound less efficiently to vitamin D3-differentiated macrophages, leading to lower infection. Interestingly, IL-4 enhanced infection was reduced in D3-MDM by restriction of MR expression. Moreover, we detected moderate secretion of TNF-α, IL-1β, and IL-10 in D3-MDM, likely due to less MR engagement during DENV infection. CONCLUSIONS/SIGNIFICANCE: Our findings reveal a molecular mechanism by which vitamin D counteracts DENV infection and progression of severe disease, and indicates its potential relevance as a preventive or therapeutic candidate