Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Hot Hands Exist Among Hedge Fund Managers? An Empirical Evaluation

We examine whether hot hands exist among hedge fund managers. In measuring performance persistence, we use hedge fund style benchmarks. This allows us to identify managers with valuable skills, and also to control for option-like features inherent in returns from hedge fund strategies. We take into account the possibility that reported asset values may be based on stale prices. We develop a statistical model that relates a hedge fund's performance to its decision to liquidate or close in order to infer the performance of a hedge fund that left the database. While we find significant performance persistence among superior funds we find little evidence of persistence among inferior funds. The Appendices for this paper are available at the following URL: <a href="http://ssrn.com/abstract=2278686">http://ssrn.com/abstract=2278686</a>
Starspots properties and stellar activity from planetary transits

Abstract Magnetic activity of stars manifests itself in the form of dark spots on the stellar surface. This in turn will cause variations of a few percent in the star light curve as it rotates. When an orbiting planet eclipses its host a star, it may cross in front of one of these spots. In this case, a “bump” will be detected in the transit lightcurve. By fitting these spot signatures with a model, it is possible to determine the spots physical properties such as size, temperature, location, magnetic field, and lifetime. Moreover, the monitoring of the spots longitude provides estimates of the stellar rotation and differential rotation. For long time series of transits during multiple years, magnetic cycles can also be determined. This model has been applied successfully to CoRoT-2, CoRoT-4, CoRot-5, CoRoT-6, CoRoT-8, CoRoT-18, Kepler-17, and Kepler-63.
The XMM Cluster Survey : evolution of the velocity dispersion-temperature relation over half a Hubble time

We measure the evolution of the velocity dispersion–temperature (σ v–TX) relation up to z = 1 using a sample of 38 galaxy clusters drawn from the XMM Cluster Survey. This work improves upon previous studies by the use of a homogeneous cluster sample and in terms of the number of high-redshift clusters included. We present here new redshift and velocity dispersion measurements for 12 z > 0.5 clusters observed with the Gemini Multi Object Spectographs instruments on the Gemini telescopes. Using an orthogonal regression method, we find that the slope of the relation is steeper than that expected if clusters were self-similar, and that the evolution of the normalization is slightly negative, but not significantly different from zero (σ v ∝ T0.86±0.14E(z)−0.37±0.33). We verify our results by applying our methods to cosmological hydrodynamical simulations. The lack of evolution seen in our data is consistent with simulations that include both feedback and radiative cooling.
Modeling of magnetic particle orientation in magnetic powder injection molding

The magnetic micro powder orientation under viscous shear flow has been analytically understood and characterized into a new analytical orientation model for a powder injection molding process. The effects of hydrodynamic force from the viscous flow, external magnetic force and internal dipole–dipole interaction were considered to predict the orientation under given process conditions. Comparative studies with a finite element method proved the calculation validity with a partial differential form of the model. The angular motion, agglomeration and magnetic chain formation have been simulated, which shows that the effect of dipole–dipole interaction among powders on the orientation state becomes negligible at a high Mason number condition and at a low λ condition (the ratio of external magnetic field strength and internal magnetic moment of powder). Our developed model can be very usefully employed in the process analysis and design of magnetic powder injection molding.
MAKING DO WITH LESS: FIRM GROWTH AND FINANCIAL PERFORMANCE UNDER RESOURCE CONSTRAINTS (SUMMARY)

This paper examines the financial resourcing behaviour of a sample of high growth firms. Firms growing faster than generated internally funds must finance this growth through external means or alternatively adopt bootstrapping measures aimed at increasing efficiency in working capital management. For a sample of manufacturing firms, we find that consistent with the pecking order theory; high growth firms have a preference for internal rather than external finance. More specifically, we find that the short term growth in sales to be largely financed through increased inventory turnover along with a reduction in gross margins. This raises questions about the longer term sustainability of this growth.
NBER WORKING PAPER SERIES CLIMATE AMENITIES, CLIMATE CHANGE, AND AMERICAN QUALITY OF LIFE

We present a hedonic framework to estimate U.S. households’ preferences over local climates, using detailed weather and 2000 Census data. We find that Americans favor an average daily temperature of 65 degrees Fahrenheit, will pay more on the margin to avoid excess heat than cold, and are not substantially more averse to extremes than to temperatures that are merely uncomfortable. These preferences vary by location due to sorting or adaptation. Changes in climate amenities under business-asusual predictions imply annual welfare losses of 1 to 3 percent of income by 2100, holding technology and preferences constant. David Albouy Department of Economics University of Illinois at Urbana-Champaign 214 David Kinley Hall Urbana, IL 61801-3606 and NBER albouy@illinois.edu Walter Graf Department of Agricultural and Resource Economics University of California, Berkeley 207 Giannini Hall, #3310 Berkeley, CA 94720-3310 walter.graf@berkeley.edu Ryan Kellogg Department of Economics University of Michigan 238 Lorch Hall 611 Tappan Street Ann Arbor, MI 48109-1220 and NBER kelloggr@umich.edu Hendrik Wolff Department of Economics University of Washington Box 353330 Savery 305 Seattle, WA 98195-3330 hendrik.wolff@gmail.com
Unity‐Order Nonlinear Optical Index Change in Epsilon‐Near‐Zero Composite Materials of Gain Media and Metal Nanoparticles

This work reports giant optical nonlinearity of active gain composites containing metal nanoparticles. In the epsilon‐near‐zero regime, the effective index of the composite strongly depends on the magnitude of host material's saturable gain and one can obtain unity‐order nonlinear optical index change for the pump with gain saturation intensity. For pump intensity of about 100 kW/cm2, the nonlinear refractive index (the refractive index change per unit pump intensity) reaches 10−5 cm2/W, which is 6–8 orders‐of‐magnitude larger than the records recently obtained in epsilon‐near‐zero bulk materials. If the gain value of the host medium is slightly larger than a critical value, such large optical nonlinearity can be obtained without loss or even accompanying with amplification. The proposed materials also have the advantage of wide tunability of operating wavelength range from visible to infrared by changing the gain value of the host and the shape parameters and filling factors of metal nanoparticles.
Influence of the Echo Time (TE) on Long-Range Autocorrelations in BOLD Noise

The sensitivity of functional magnetic resonance (MR) imaging sequences to the blood oxygenation level dependent (BOLD) contrast depends on the echo time (TE) with a maximum in the range 40–60 ms [1]. This study analyses BOLD signals at rest in terms of signal strength (or variance) σ, and the Hurst exponent H , to confirm the physiological origins of H . We expect that H is maximal if TE is 40–60 ms and that σ declines with TE.
Phytochemical and antimicrobial activity of Terminalia avicennioides extracts against some bacteria pathogens associated with patients suffering from complicated respiratory tract diseases

Ethanolic extracts of the stem bark, root bark and leaves of Terminalia avicennioides were assayed against Staphylococcus aureus, Escherichia coliand Pseudomonas aeruginosa obtained from patients suffering from complicated respiratory tract infections for their antimicrobial activity. Analysis of variance showed that the ethanolic extracts of the plant material exhibit a significant (P > 0.05) antimicrobial activity against S. aureus. The various zone of inhibitions onEscherichia coli was moderate (P < 0.05) at different concentrations, very low antimicrobial activity was observed against P. aeruginosa. Important bioactive agents like phenols, steroids, glycosides, flavonoids, tannins, ellagic acids were detected in the bark, leaves and root of T. avicennioides. Anthraquinone was not absent in all the plant parts tested. The bioactive constituents detected in T. avicennioides may be responsible for the observed antimicrobial activity of the plant and hence, its potential use as antimicrobial agent. Key words: Antimicrobial activity, bacterial pathogens, Phytochemical, respiratory tract diseases, Terminalia avicennioides.
Lapatinib plus chemotherapy or endocrine therapy (CET) versus CET alone in the treatment of HER-2-overexpressing locally advanced or metastatic breast cancer: systematic review and meta-analysis

Background: This paper reports a systematic review and meta-analysis of all randomized controlled trials comparing the efficacy of lapatinib plus chemotherapy or endocrine therapy (CET) versus CET alone in human epidermal growth factor receptor 2-overexpressing (HER-2 + ) locally advanced or metastatic breast cancer. Methods: Several databases were searched, including MEDLINE, EMBASE, LILACS, and CENTRAL. The primary endpoints were progression-free survival and overall survival. The side effects of each treatment were analyzed. The data extracted from the studies were combined by using the hazard ratio or risk ratio with their corresponding 95% confidence interval (CI). Results: A total of 113 references were identified and screened. The final analysis included four trials comprising 1,073 patients with HER-2 + . The overall response rate was higher in patients who received the combination of CET plus lapatinib (risk ratio 0.78; 95% CI 0.71–0.85; P , 0.00001) but with significant heterogeneity ( χ 2 = 15.61, df = 3; P = 0.001; I 2 = 81%). This result remained favorable to the use of lapatinib when a random-effects model analysis was performed (risk ratio 0.76; 95% CI 0.62–0.94; P = 0.01). Progression-free survival was also higher in patients who received CET plus lapatinib (hazard ratio 0.57; 95% CI 0.49–0.66; P , 0.00001) with no heterogeneity detected on this analysis ( χ 2 = 3.05; df = 3; P = 0.38; I 2 = 1%). Overall survival was significantly longer in patients who received CET plus lapatinib (hazard ratio 0.80; 95% CI 0.69–0.92; P = 0.002) without heterogeneity on this analysis ( χ 2 = 1.26; df = 3; P = 0.74; I 2 = 0%). Regarding adverse events and severe toxicities (grade $ 3), the group receiving CET plus lapatinib had higher rates of neutropenia (risk ratio 2.08; 95% CI 1.64–2.62; P , 0.00001), diarrhea (risk ratio 4.82; 95% CI 3.14–7.41; P , 0.00001), and rash (risk ratio 8.03; 95% CI 2.46–26.23; P = 0.0006). Conclusion: The combination of CET plus lapatinib increased the overall response rate, progression-free survival, and overall survival in patients with HER-2 + locally advanced or metastatic breast cancer. chemotherapy endocrine therapy; CI, confidence interval; SE, standard error; IV, inverse Evidence an international, peer-reviewed open-access the underlying the potential in therapy of drugs throughout their development lifecycle from preclinical to post- launch. each to evaluate the case for a in outcome terms in indications and
Greenwich Academic Literature Archive (GALA)

Mahallawi, Waleed H. , Kasbekar, Anand V. , McCormick, Maxwell S. , Hoschler, Katja, Temperton, Nigel, Leong, Samuel C. , Beer, Helen, Ferrara, Francesca, McNamara, Paul S. and Zhang, Qibo (2013) Infection with 2009 H1N1 influenza virus primes for immunological memory in human noseassociated lymphoid tissue, offering cross-reactive immunity to H1N1 and avian H5N1 viruses. Journal of Virology, 87 (10). pp. 5331-5339. ISSN 0022-538X (Print), 1098-5514 (Online) (doi:10.1128/JVI.03547-12)
Spatiotemporal Statistical Shape Model Construction for the Observation of Temporal Change in Human Brain Shape

This chapter introduces a spatiotemporal statistical shape model (stSSM) using brain MR image which will represent not only the statistical variability of shape but also a temporal change of the statistical variance with time. The proposed method applies expectation-maximization (EM)-based weighted principal component analysis (WPCA) using a temporal weight function, where E-step estimates Eigenvalues of every data using temporal Eigenvectors, and M-step updates Eigenvectors to maximize the variance. The method constructs stSSM whose Eigenvectors change with time. By assigning a predefined weight parameter for each subject according to subjects’ age, it calculates the weighted variance for time-specific stSSM. To validate the method, this study employed 105 adult subjects (age: 30–84 years old with mean ± SD = 60.61 ± 16.97) from OASIS database. stSSM constructed for time point 40–80 with a step of 2. The proposed method allows the characterization of typical deformation patterns and subject-specific shape changes in repeated time-series observations of several subjects where the modeling performance was observed by optimizing variance.
Detection and classification of faults in transmission lines using the maximum wavelet singular value and Euclidean norm

In this study, a novel algorithm for detecting and classifying faults in high-voltage transmission lines is proposed. The algorithm is based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). The DWT is used for extracting the currents’ high-frequency components under fault conditions. Signals under each fault condition are scaled in frequency, in order to build a wavelet matrix. By means of the SVD, the maximum singular value is calculated and employed in this proposal. The attained results exhibit that the maximum singular value represents a good indicator for the issue. This novel approach for detecting and classifying faults in power systems is called maximum wavelet singular value. Phase-to-ground, two-phase to ground, and three-phase faults’ simulations under different fault impedances are carried out by DIgSILENT Power Factory. The analysed fault conditions are evaluated demonstrating that the proposal reduces the computational burden and the time detection.
Application of Allura Red in the construction of a novel amperometric flow sensor for the automatic determination of hydroquinone and catechol using a two-line flow injection manifold with a single-sensor/double-pulse amperometric detection

A novel amperometric flow sensor was constructed by the successive voltammetric cycling of a glassy carbon electrode (GCE) in a basic solution of Allura Red. The performance of the constructed treated GCE sensor was characterized in the new flow injection amperometric manifold with a single-sensor/double-pulse amperometric simultaneous detection of hydroquinone (HQ) and catechol (CC). A programmed sequence of two potential steps with magnitudes of +0.18 (at the time of the first sample injection) and +0.26 V (at the time of the second injection) was applied. By designing a proper time delay between a sequence of two sample injections and potential steps, two separate flow injection amperometric peaks were recorded. The first peak corresponds to HQ and the second peak is related to the oxidation of both HQ and CC. The currents obtained from the subtraction of two recorded peaks is utilized to obtain the amount of CC. Under the optimized chemical and instrumental parameters, the relation between the concentration and response of the sensor has a good linearity in the ranges of 0.2–600.0 and 0.2–300.0 µmol l−1 for HQ and CC, respectively. The detection limit obtained for both was 0.15 µmol l−1 (signal-to-noise ratio = 3). The proposed flow sensor was employed for the determination of HQ and CC in the real samples with satisfying precision and accuracy.
An integrated 13 . 56-MHz RFID tag in a printed organic complementary TFT technology on flexible substrate

This paper presents the first printed organic 13-MHz RFID on flexible substrate. The proposed sol ution includes a planar near field antenna bonded to an R FID tag, which is printed on flexible foil using an organic complementary TFT technology. Thanks to an active envelope detect or, ASK modulation with modulation depth as low as 20% can be adopted to increase the available input power for the recti f er. The RFID functionality is demonstrated at the internally generated supply voltage of 24 V, for a reading range of 2-5 cm and a bit-rate up to 50 bit/s. With more than 250 transistors on the same foil, this work represents the most complex circuit ever publi shed in a printed organic complementary TFT technology.
Selection on Observed and Unobserved Variables : Assessing the E ff ectiveness of Catholic Schools 1

In this paper we measure the effect of Catholic high school attendance on educational attainment and test scores. Because we do not have a good instrumental variable for Catholic school attendance, we develop new estimation methods based on the idea that the amount of selection on the observed explanatory variables in a model provides a guide to the amount of selection on the unobservables. We also propose an informal way to assess selectivity bias based on measuring the ratio of selection on unobservables to selection on observables that would be required if one is to attribute the entire effect of Catholic school attendance to selection bias. We use our methods to estimate the effect of attending a Catholic high school on a variety of outcomes. Our main conclusion is that Catholic high schools substantially increase the probability of graduating from high school and, more tentatively, college attendance. We find little evidence of an effect on test scores.
SKIN DOSE MEASUREMENT FOR PATIENTS USING IMAGING PLATES IN INTERVENTIONAL RADIOLOGY PROCEDURES

A method using europium-doped BaFBr imaging plates (IPs) has been developed to estimate and map values of entrance skin doses during interventional radiology (IR). IPs offer many advantages for measuring the entrance skin dose because they have a wide dynamic range (up to 100 Gy), provide high spatial resolution as a detector of two-dimensional images, and can be used repeatedly. The entrance skin dose was measured by fitting a 40 × 40 cm IP sheet around a patient's back using a corset in clinical studies involving IR procedures at two hospitals. The corset can minimize a geometric discrepancy in dose estimates between the IP and the patient body. The entrance skin dose was measured by using photoluminescent glass dosimeters simultaneously, and both values were compared. The spatial relative dose profiles from both dose estimates showed generally good agreement; however, the doses obtained with glass dosimeter chips were often lower than those obtained with IPs. This discrepancy comes from a radiation shielding effect for x rays by IPs and a strong angular dependence of the glass dosimeter in low energy x-ray fields. Comprehensive results of this study demonstrated that IPs were able to measure entrance skin dose in even high dose regions with steep dose gradients and to determine the peak skin dose, without missing hot spots, over all ranges used during interventional radiology procedures. Use of the corset minimized variations associated with angular dependence.
Cloning, molecular characterization and heterologous expression of AMY1, an a -amylase gene from Cryptococcus£avus

A Cryptococcus ﬂavus gene ( AMY1 ) encoding an extracellular a -amylase has been cloned. The nucleotide sequence of the cDNA revealed an ORF of 1896 bp encoding for a 631 amino acid polypeptide with high sequence identity with a homologous protein isolated from Cryptococcus sp. S-2. The presence of four conserved signature regions, (I) 144 DVVVNH 149 , (II) 235 GLRIDSLQQ , placed the enzyme in the GH13 a -amylase family. Furthermore, sequence comparison suggests that the C. ﬂavus a -amylase has a C-terminal starch-binding domain characteristic of the CBM20 family. AMY1 was successfully expressed in Saccharomyces cerevisiae . The time course of amylase secretion in S. cerevisiae resulted in a maximal extracellular amylolytic activity (3.93 UmL (cid:1) 1 ) at 60 h of incubation. The recombinant protein had an apparent molecular mass similar to the native enzyme ( c . 67 kDa), part of which was due to N-glycosylation. present study describes the isolation of an a -amylase gene ( AMY1 ) from the yeast C. ﬂavus . This gene was successfully expressed in S. cerevisiae , showing that this system may be used in starch-conversion processes using Amy1 as a source of a -amylase activity.
Identifying Customer Needs from User-Generated Content

Firms traditionally rely on interviews and focus groups to identify customer needs for marketing strategy and product development. User-generated content (UGC) is a promising alternative source for identifying customer needs. However, established methods are neither efficient nor effective for large UGC corpora because much content is non-informative or repetitive. We propose a machine-learning approach to facilitate qualitative analysis by selecting content for efficient review. We use a convolutional neural network to filter out non-informative content and cluster dense sentence embeddings to avoid sampling repetitive content. We further address two key questions: Are UGC-based customer needs comparable to interview-based customer needs? Do the machine-learning methods improve customer-need identification? These comparisons are enabled by a custom dataset of customer needs for oral care products identified by professional analysts using industry-standard experiential interviews. The analysts also coded 12,000 UGC sentences to identify which previously identified customer needs and/or new customer needs were articulated in each sentence. We show that (1) UGC is at least as valuable as a source of customer needs for product development, likely more-valuable, than conventional methods, and (2) machine-learning methods improve efficiency of identifying customer needs from UGC (unique customer needs per unit of professional services cost).
Frontiers in Computational Neuroscience

account fi nite postsynaptic potentials where their effect is most prominent: our new treatment still describes the probability density evolution on a length scale σ determined by the fl uctuations in the input as a diffusion, but we take into account the discrete events near the absorbing boundary. With a different approach Sirovich et al. (2000) and Sirovich (2003) calculated the equilibrium solution for fi nite sized excitatory incoming events. De Kamps (2003) developed a stable numerical approach to solve the equilibrium and non-equilibrium population dynamics. Here we are interested in the case of excitatory and inhibitory inputs, as they occur in balanced neural networks (van Vreeswijk and Sompolinsky, 1996; Brunel, 2000). Secondly, unlike previous analytical treatments, we solve the problem in discrete time to incorporate the effect of the discretization on the equilibrium and response properties of the neuron. This is necessary to get a quantitative understanding of artifacts observed in simulation studies: in time-driven simulations, the state of the neuron is only updated in time steps of size h and the incoming synaptic impulses are accumulated over one such time step. However, modern time-driven simulators (Gewaltig and Diesmann, 2007; Morrison et al., 2007) are able to take into account exact spike timing and hence avoid discretization effects. These methods can be either slower or faster than traditional time-driven techniques depending on the required accuracy.