The performance of socially responsible mutual funds: the role of fees and management companies

In this paper, we shed light on the debate about the financial performance of socially responsible investment (SRI) mutual funds by separately analyzing the contributions of before-fee performance and fees to SRI funds' performance and by investigating the role played by fund management companies in the determination of those variables. We apply the matching estimator methodology to obtain our results and find that in the period 1997-2005, US SRI funds had significantly higher fees and better before- and after-fee performance than conventional funds with similar characteristics. Differences, however, were driven exclusively by SRI funds run by management companies specialized in socially responsible investment.Socially responsible investment, Mutual fund fees, Mutual fund performance, Matching estimators

Dynamical replica theoretic analysis of CDMA detection dynamics

We investigate the detection dynamics of the Gibbs sampler for code-division multiple access (CDMA) multiuser detection. Our approach is based upon dynamical replica theory which allows an analytic approximation to the dynamics. We use this tool to investigate the basins of attraction when phase coexistence occurs and examine its efficacy via comparison with Monte Carlo simulations.Comment: 18 pages, 2 figure

Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the operation of a smart grid, an example of which is energy demand forecasting. Short term energy forecasting can be used by utilities to assess if any forecasted peak energy demand would have an adverse effect on the power system transmission and distribution infrastructure. It can also help in load scheduling and demand side management. Many techniques have been proposed to forecast time series including Support Vector Machine, Artificial Neural Network and Deep Learning. In this work we use Long Short Term Memory architecture to forecast 3-day ahead energy demand across each month in the year. The results show that 3-day ahead demand can be accurately forecasted with a Mean Absolute Percentage Error of 3.15%. In addition to that, the paper proposes way to quantify the time as a feature to be used in the training phase which is shown to affect the network performance

Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices

Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in [arXiv:1109.4424] a strategy that allows compressed sensing to be performed at acquisition rates approaching to the theoretical optimal limits. In this paper, we give a more thorough presentation of our approach, and introduce many new results. We present the probabilistic approach to reconstruction and discuss its optimality and robustness. We detail the derivation of the message passing algorithm for reconstruction and expectation max- imization learning of signal-model parameters. We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distribution of signals, and discuss the best possible reconstruction performances regardless of the algorithm. We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically.Comment: 42 pages, 37 figures, 3 appendixe

FAK acts as a suppressor of RTK-MAP kinase signalling in Drosophila melanogaster epithelia and human cancer cells

Receptor Tyrosine Kinases (RTKs) and Focal Adhesion Kinase (FAK) regulate multiple signalling pathways, including mitogen-activated protein (MAP) kinase pathway. FAK interacts with several RTKs but little is known about how FAK regulates their downstream signalling. Here we investigated how FAK regulates signalling resulting from the overexpression of the RTKs RET and EGFR. FAK suppressed RTKs signalling in Drosophila melanogaster epithelia by impairing MAPK pathway. This regulation was also observed in MDA-MB-231 human breast cancer cells, suggesting it is a conserved phenomenon in humans. Mechanistically, FAK reduced receptor recycling into the plasma membrane, which resulted in lower MAPK activation. Conversely, increasing the membrane pool of the receptor increased MAPK pathway signalling. FAK is widely considered as a therapeutic target in cancer biology; however, it also has tumour suppressor properties in some contexts. Therefore, the FAK-mediated negative regulation of RTK/MAPK signalling described here may have potential implications in the designing of therapy strategies for RTK-driven tumours

Radio-frequency dressed state potentials for neutral atoms

Potentials for atoms can be created by external fields acting on properties like magnetic moment, charge, polarizability, or by oscillating fields which couple internal states. The most prominent realization of the latter is the optical dipole potential formed by coupling ground and electronically excited states of an atom with light. Here we present an experimental investigation of the remarkable properties of potentials derived from radio-frequency (RF) coupling between electronic ground states. The coupling is magnetic and the vector character allows to design state dependent potential landscapes. On atom chips this enables robust coherent atom manipulation on much smaller spatial scales than possible with static fields alone. We find no additional heating or collisional loss up to densities approaching $10^{15}$ atoms / cm$^3$ compared to static magnetic traps. We demonstrate the creation of Bose-Einstein condensates in RF potentials and investigate the difference in the interference between two independently created and two coherently split condensates in identical traps. All together this makes RF dressing a powerful new tool for micro manipulation of atomic and molecular systems

Triclinic modification of N-[(1,1-di­methyl­ethoxy)carbon­yl]-3-[(R)-prop-2-en-1-ylsulfin­yl]-(R)-alanine ethyl ester at 120 (1) K

There are two independent mol­ecules in the asymmetric unit of the title compound, C13H23NO5S. In the crystal structure, inter­molecular N—H⋯O hydrogen bonds link mol­ecules into two independent one-dimensional chains along [100]. The crystal studied was found to be a non-merohedral twin with a ratio of 0.615 (6):0.385 (1) for the refined components. At 200 (1) K [Singh et al. (2009 ▶). Acta Cryst. E65, o1385–o1386] the crystal structure of the title compound contains one disordered mol­ecule in the asymmetric unit of a monoclinic unit cell

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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