Voltage dip immunity aspects of power-electronic equipment : recommendations from CIGRE/CIRED/UIE JWG C4.110

This paper presents some of the results from an international working group on voltage-dip immunity. The working group has made a number of recommendations to reduce the adverse impact of voltage dips. Specific recommendations to researchers and manufacturers of powerelectronic equipment are considering all voltage dip characteristics early in the design of equipment; characterize performance of equipment by means of voltage-dip immunity curves; and made equipment with different immunity available

Voltage dip immunity of equipment and installations : messages to stakeholders

This paper presents the messages to the stakeholders on voltage-dip immunity as extracted by UIE WG2 from CIGRE TB412 [1]. The paper summarizes the main recommendations from this technical brochure in the form of messages towards regulators, standard-settingorganizations, network operators, industrial customers, equipment manufacturers, and power quality monitor manufacturers, researchers

Do mutual funds have consistency in their performance?

Using a comprehensive data set of 714 Chinese mutual funds from 2004 to 2015, the study investigates these funds’ performance persistence by using the Capital Asset Pricing model, the Fama-French three-factor model and the Carhart Four-factor model. For persistence analysis, we categorize mutual funds into eight octiles based on their one year lagged performance and then observe their performance for the subsequent 12 months. We also apply Cross-Product Ratio technique to assess the performance persistence in these Chinese funds. The study finds no significant evidence of persis- tence in the performance of the mutual funds. Winner (loser) funds do not continue to be winner (loser) funds in the subsequent time period. These findings suggest that future performance of funds cannot be predicted based on their past performance.info:eu-repo/semantics/publishedVersio

Tick size and price diffusion

A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties of prices. The second part presents original results obtained by investigating the tick size changes occurring at the New York Stock Exchange (NYSE). We show that tick size change has three effects on price diffusion. First, as already shown in the literature, tick size affects price return distribution at an aggregate time scale. Second, reducing the tick size typically leads to an increase of volatility clustering. We give a possible mechanistic explanation for this effect, but clearly more investigation is needed to understand the origin of this relation. Third, we explicitly show that the ability of the subordination hypothesis in explaining fat tails of returns and volatility clustering is strongly dependent on tick size. While for large tick sizes the subordination hypothesis has significant explanatory power, for small tick sizes we show that subordination is not the main driver of these two important stylized facts of financial market.Comment: To be published in the "Proceedings of Econophys-Kolkata V International Workshop on "Econophysics of Order-driven Markets" March 9-13, 2010, The New Economic Windows series of Springer-Verlag Italia

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 201

The Effects of Twitter Sentiment on Stock Price Returns

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-know micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events

Mass Measurement of 27^{27}P for Improved Type-I X-ray Burst Modeling

Light curves are the primary observable of type-I x-ray bursts. Computational x-ray burst models must match simulations to observed light curves. Most of the error in simulated curves comes from uncertainties in $rp$ process reaction rates, which can be reduced via precision mass measurements of neutron-deficient isotopes in the $rp$ process path. We perform a precise atomic mass measurement of $^{27}$P and use this new measurement to update existing type-I x-ray burst models to produce an improved light curve. High-precision Penning trap mass spectrometry was used to determine the atomic mass of $^{27}$P. Modules for Experiments in Stellar Astrophysics (MESA) was then used to simulate x-ray bursts using a 1D multi-zone model to produce updated light curves. The mass excess of $^{27}$P was measured to be -670.7$\pm$ 0.6 keV, a fourteen-fold precision increase over the mass reported in AME2020. The $^{26}$Si($p, \gamma$)$^{27}$P and reverse photodisintegration reaction rates have been determined to a higher precision based on the new, high precision mass measurement of $^{27}$P, and MESA light curves generated using these rates. Changes in the mass of $^{27}$P seem to have minimal effect on XRB light curves, even in burster systems tailored to maximize impact. The mass of $^{27}$P does not play a significant role in x-ray burst light curves. It is important to understand that more advanced models don't just provide more precise results, but often qualitatively different ones. This result brings us a step closer to being able to extract stellar parameters from individual x-ray burst observations. In addition, the Isobaric Multiplet Mass Equation (IMME) has been validated for the $A=27, T=3/2$ quartet, but only after including a small, theoretically predicted cubic term and utilizing an updated excitation energy for the $T=3/2$ isobaric analogue state of $^{27}$Si.Comment: 8 pages, 7 figure

Voltage-dip immunity: statistics and need for further work

Abstract. This paper presents the main results from CIGRE/CIRED/UIE working group JWG C4.110 and an overview of the need for further work identified by this working group. The paper goes into more details of the voltage-dip statistics collected by the working group and on methods to present the results from voltage-dip surveys

Protein Phosphatase-1 Activates CDK9 by Dephosphorylating Ser175

The cyclin-dependent kinase CDK9/cyclin T1 induces HIV-1 transcription by phosphorylating the carboxyterminal domain (CTD) of RNA polymerase II (RNAPII). CDK9 activity is regulated by protein phosphatase-1 (PP1) which was previously shown to dephosphorylate CDK9 Thr186. Here, we analyzed the effect of PP1 on RNAPII phosphorylation and CDK9 activity. The selective inhibition of PP1 by okadaic acid and by NIPP1 inhibited phosphorylation of RNAPII CTD in vitro and in vivo. Expression of the central domain of NIPP1 in cultured cells inhibited the enzymatic activity of CDK9 suggesting its activation by PP1. Comparison of dephosphorylation of CDK9 phosphorylated by (32P) in vivo and dephosphorylation of CDK9's Thr186 analyzed by Thr186 phospho-specific antibodies, indicated that a residue other than Thr186 might be dephosphorylated by PP1. Analysis of dephosphorylation of phosphorylated peptides derived from CDK9's T-loop suggested that PP1 dephosphorylates CDK9 Ser175. In cultured cells, CDK9 was found to be phosphorylated on Ser175 as determined by combination of Hunter 2D peptide mapping and LC-MS analysis. CDK9 S175A mutant was active and S175D – inactive, and dephosphorylation of CDK9's Ser175 upregulated HIV-1 transcription in PP1-dependent manner. Collectively, our results point to CDK9 Ser175 as novel PP1-regulatory site which dephosphorylation upregulates CDK9 activity and contribute to the activation of HIV-1 transcription