Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Momentum Traders Profit from Central Bank Intervention in Australia

A number of recent studies have attributed the success of technical trading strategies in foreign exchange markets to central bank intervention. Arguments advanced in favour of this hypothesis contend that intervention is conducted to maintain orderly market conditions - not to make money - and as such, central banks may be willing to take a loss on their intervention operations. This paper investigates the relationship between momentum based trading profits and intervention by the Reserve Bank of Australia (RBA) in the U.S. Dollar - Australian Dollar ($US/$A) market. As the RBA's intervention policy underwent several regime shifts throughout the course of the study, the analysis should provide better insights into this relationship than has been possible in similar studies involving other central banks. This paper demonstrates that whilst a simple momentum trading rule is largely unprofitable in the absence of RBA intervention, it generates very attractive returns when taking positions in the opposite direction to the RBA during periods of intervention. The most profitable opportunities occur when the RBA attempts to smooth or correct a strong trend in the $A (particularly an aggressive depreciation) over successive days. This suggests that on occasions where the RBA 'leans against the wind', public resources are lost to speculators following momentum trading strategies. As such, the results from this study have important implications for both monetary authorities and foreign exchange traders.
The local immunological microenvironment in colorectal cancer as a prognostic factor for treatment decisions in the clinic

Analysis of the local immunological microenvironment in colorectal cancer lesions yielded prognostic markers. Harnessing these insights for clinical application however requires the use of sophisticated technology and algorithms, especially the robust and reproducible quantification of immune cells. These technologies are available and will allow individualized treatment decisions beyond the current standard.
Margin Requirements and Stock Price Volatility When Agents' Beliefs are Heterogeneous

In a pure-exchange, continuous-time economy, agents, who have different subjective discount rates and heterogenous beliefs on the fundamentals, trade with each other motivated not only by the benefit of risk sharing but also by speculation. This aggressiveness in trading can increase stock price volatility under some conditions. Margin requirements limit agents' ability to speculate, thus they tend to reduce the stock price volatility in general, especially when agents' beliefs are more divergent. Furthermore, if the margins are binding, an increase in margins leads to a decrease in stock volatility in the case when the patient agent is relatively optimistic and lead to an increase in stock volatility when the patient agent is relatively pessimistic. Margin requirements also stabilize the redistribution of wealth caused by the trading (speculating) of stocks and alter the equilibrium interest rates. Some dynamic implications of margin requirements are also explored through a simulated example.
Reconsidering Single Failure Recovery in Clustered File Systems

How to improve the performance of single failure recovery has been an active research topic because of its prevalence in large-scale storage systems. We argue that when erasure coding is deployed in a cluster file system (CFS), existing single failure recovery designs are limited in different aspects: neglecting the bandwidth diversity property in a CFS architecture, targeting specific erasure code constructions, and no special treatment on load balancing during recovery. In this paper, we reconsider the single failure recovery problem in a CFS setting, and propose CAR, a cross-rack-aware recovery algorithm. For each stripe, CAR finds a recovery solution that retrieves data from the minimum number of racks. It also reduces the amount of cross-rack repair traffic by performing intra-rack data aggregation prior to cross-rack transmission. Furthermore, by considering multi-stripe recovery, CAR balances the amount of cross-rack repair traffic across multiple racks. Evaluation results show that CAR can effectively reduce the amount of cross-rack repair traffic and the resulting recovery time.
High temperature elastic anisotropy of the perovskite and post‐perovskite polymorphs of Al2O3

Finite temperature ab initio molecular dynamics calculations were performed to determine the high temperature elastic and seismic properties of the perovskite and post‐perovskite phases of pure end‐member Al2O3. The post‐perovskite phase exhibits very large degrees of shear‐wave splitting. The incorporation of a few mole percent of Al2O3 into MgSiO3 is predicted to have little effect on the perovskite to post‐perovskite phase transition pressure and seismic properties of the post‐perovskite phase; although a small difference in shear‐wave splitting may be observable.
Pion interferometry in Au plus Au and Cu plus Cu collisions at s(NN)=62.4 and 200 GeV

We present a systematic analysis of two-pion interferometry in Au+Au collisions at s(NN)=62.4 GeV and Cu+Cu collisions at s(NN)=62.4 and 200 GeV using the STAR detector at the Relativistic Heavy Ion Collider (RHIC). The multiplicity and transverse momentum dependences of the extracted correlation lengths (radii) are studied. The scaling with charged particle multiplicity of the apparent system volume at final interaction is studied for the RHIC energy domain. The multiplicity scaling of the measured correlation radii is found to be independent of colliding system and collision energy.
A Review of Related Work on Machine Learning in Semiconductor Manufacturing and Assembly Lines

This paper deals with applications of machine learning algorithms in manufacturing. Machine learning can be defined as a field of computer science that gives computers the ability to learn without explicitly developing the needed algorithms. Manufacturing is the production of merchandise by manual labour, machines and tools. The focus of this paper is on automatic production lines. The areas of interest of this paper are semiconductor manufacturing and production on assembly lines. The purpose of this paper is to review the relevant papers describing the applications of machine learning techniques in these fields of manufacturing thus creating a firm foundation for further research in the matter of machine learning in manufacturing.
The structure of dark matter haloes in hierarchical clustering models

We use a set of large cosmological N-body simulations to study the internal structure of dark matter haloes which form in scale-free hierarchical clustering models (initial power spectra P(k) ∞ kn with n = 0, −1 and −2) in an Ω = 1 universe. We find that the radius r178 in a halo corresponding to a mean interior overdensity of 178 accurately delineates the quasi-static halo interior from the surrounding infalling material, in agreement with the simple spherical collapse model. The interior velocity dispersion correlates with mass, again in good agreement with the spherical collapse model. Interior to the virial radius r178 the spherically averaged density, circular velocity and velocity dispersion profiles are well fitted by a simple two-parameter analytical model proposed by Navarro, Frenk & White. This model has ρ ∞ r−l at small radii, steepening to ρ ∞ r−3 at large radii, and fits our haloes to the resolution limit of the simulations. The two model parameters, scalelength and mass, are tightly correlated. Lower mass haloes are more centrally concentrated, and so have scalelengths which are a smaller fraction of their virial radius than those of their higher mass counterparts. This reflects the earlier formation times of low-mass haloes. The haloes are moderately aspherical, with typical axial ratios 1 : 0.8 : 0.65 at their virial radii, becoming gradually more spherical towards their centres. The haloes are generically triaxial, but with a slight preference for prolate over oblate configurations, at least for n = −1 and 0. These shapes are maintained by an anisotropic velocity dispersion tensor. The median value of the spin parameter is λ ≈ 0.04, with a weak trend for lower λ at higher halo mass. We also investigate how the halo properties depend on the algorithm used to identify them in the simulations, using both friends-of-friends and spherical overdensity methods. We find that, for groups selected at mean overdensities ∼ 100 – 400 by either method, the properties are insensitive to how the haloes are selected, if the halo centre is taken as the position of the most bound particle.
New Diabetes Diagnostic Threshold of Hemoglobin A1c and the 3-Year Incidence of Retinopathy

The new diagnostic threshold of hemoglobin A1c was made based on evidence from cross-sectional studies, and no longitudinal study supports its validity. To examine whether hemoglobin A1c of 6.5% or higher defines a threshold for elevated risk of incident retinopathy, we analyzed longitudinal data of 19,897 Japanese adults who underwent a health checkup in 2006 and were followed up 3 years later. We used logistic regression models and restricted cubic spline models to examine the relationship between baseline hemoglobin A1c levels and the prevalence and the 3-year incidence of retinopathy. The restricted cubic spline model indicated a possible threshold for the risk of incident retinopathy at hemoglobin A1c levels of 6.0–7.0%. Logistic regression analysis found that individuals with hemoglobin A1c levels of 6.5–6.9% were at significantly higher risk of developing retinopathy at 3 years compared with those with hemoglobin A1c levels of 5.0–5.4% (adjusted odds ratio, 2.35 [95% CI 1.08–5.11]). Those with hemoglobin A1c levels between 5.5 and 6.4% exhibited no evidence of elevated risks. We did not observe a threshold in the analysis of prevalent retinopathy. Our longitudinal results support the validity of the new hemoglobin A1c threshold of 6.5% or higher for diagnosing diabetes.
Selection, Investment, and Women&Apos;S Relative Wages Since 1975

In theory, growing wage inequality within gender should cause women to invest more in their market productivity and should differentially pull able women into the workforce, thereby closing the measured gender gap even though women's wages might have grown less than men's had their behavior been held constant. Using the CPS repeated cross-sections between 1975 and 2001, we use control function (Heckit) methods to correct married women's conditional mean wages for selectivity and investment biases. Our estimates suggest that selection of women into the labor market has changed sign, from negative to positive, or at least that positive selectivity bias has come to overwhelm investment bias. The estimates also explain why measured women's relative wage growth coincided with growth of wage inequality within-gender, and attribute the measured gender wage gap closure to changing selectivity and investment biases, rather than relative increases in women's earning potential. Using PSID waves 1975-93 to control for the changing female workforce with person-fixed effects, we also find little growth in women's mean log wages. Finally, we make a first attempt to gauge the relative importance of selection versus investment biases, by examining the family and cognitive backgrounds of members of the female workforce. PSID, NLS, and NLSY data sets show how the cross-section correlation between female employment and family/cognitive background has changed from "negative" to "positive" over the last thirty years, in amounts that might be large enough to attribute most of women's relative wage growth to changing selectivity bias.
Overdrive atrial pacing does not improve obstructive sleep apnoea syndrome

The aim of this study was to assess the ability of overdrive atrial pacing to reduce sleep apnoea severity. A total of 17 unselected patients (12 males; mean±sd age 71±10 yrs; body mass index 27±3 kg·m−2) who had received permanent atrial-synchronous ventricular pacemakers for symptomatic bradyarrhythmias and not known to have central or obstructive sleep apnoea syndrome (OSAS) were studied. Using a crossover study design, patients were or were not in pacing mode with atrial overdrive (15 beats·min−1 faster than mean baseline nocturnal cardiac frequency) for 1 month. Patients were paced only during sleep periods, identified by a specific algorithm included in the pacemaker. Patients underwent three overnight polysomnographic evaluations 1 month apart. The first was performed for baseline evaluation. The patients were then randomly assigned to either 1 night in spontaneous rhythm or to 1 night in pacing mode with atrial overdrive. Two patients refused to continue the study after the first polysomnographic evaluation. OSAS was highly prevalent in this population: 10 of the 15 (67%) patients exhibited an apnoea–hypopnoea index of >30 events·h−1. The nocturnal spontaneous rhythm was 59±7 beats·min−1 at baseline, compared to 75±10 beats·min−1 with atrial overdrive pacing. The apnoea–hypopnoea index was 46±29 events·h−1 in spontaneous rhythm, compared to 50±24 events·h−1 with atrial overdrive pacing. Overdrive pacing changed none of the respiratory indices, or sleep fragmentation or sleep structure parameters. In conclusion, atrial overdrive pacing has no significant effect on obstructive sleep apnoea.
Altered Cortical Synaptic Plasticity in Response to 5-Hz Repetitive Transcranial Magnetic Stimulation as a New Electrophysiological Finding in Amnestic Mild Cognitive Impairment Converting to Alzheimer’s Disease: Results from a 4-year Prospective Cohort Study

Introduction To investigate cortical excitability and synaptic plasticity in amnestic mild cognitive impairment (aMCI) using 5 Hz repetitive transcranial magnetic stimulation (5 Hz-rTMS) and to assess whether specific TMS parameters predict conversion time to Alzheimer’s disease (AD). Materials and methods Forty aMCI patients (single- and multi-domain) and 20 healthy controls underwent, at baseline, a neuropsychological examination and 5 Hz-rTMS delivered in trains of 10 stimuli and 120% of resting motor threshold (rMT) intensity over the dominant motor area. The rMT and the ratio between amplitude of the 1st and the 10th motor-evoked potential elicited by the train (X/I-MEP ratio) were calculated as measures of cortical excitability and synaptic plasticity, respectively. Patients were followed up annually over a period of 48 months. Analysis of variance for repeated measures was used to compare TMS parameters in patients with those in controls. Spearman’s correlation was performed by considering demographic variables, aMCI subtype, neuropsychological test scores, TMS parameters, and conversion time. Results Thirty-five aMCI subjects completed the study; 60% of these converted to AD. The baseline rMT and X/I-MEP ratio were significantly lower in patients than in controls (p = 0.04 and p = 0.01). Spearman’s analysis showed that conversion time correlated with the rMT (0.40) and X/I-MEP ratio (0.51). Discussion aMCI patients displayed cortical hyperexcitability and altered synaptic plasticity to 5 Hz-rTMS when compared with healthy subjects. The extent of these changes correlated with conversion time. These alterations, which have previously been observed in AD, are thus present in the early stages of disease and may be considered as potential neurophysiological markers of conversion from aMCI to AD.
Glutathione S-transferases and UDP-glycosyltransferases Are Involved in Response to Aluminum Stress in Flax

About 30% of the world's ice-free land area is occupied by acid soils. In soils with pH below 5, aluminum (Al) releases to the soil solution, and becomes highly toxic for plants. Therefore, breeding of varieties that are resistant to Al is needed. Flax (Linum usitatissimum L.) is grown worldwide for fiber and seed production. Al toxicity in acid soils is a serious problem for flax cultivation. However, very little is known about mechanisms of flax resistance to Al and the genetics of this resistance. In the present work, we sequenced 16 transcriptomes of flax cultivars resistant (Hermes and TMP1919) and sensitive (Lira and Orshanskiy) to Al, which were exposed to control conditions and aluminum treatment for 4, 12, and 24 h. In total, 44.9–63.3 million paired-end 100-nucleotide reads were generated for each sequencing library. Based on the obtained high-throughput sequencing data, genes with differential expression under aluminum exposure were revealed in flax. The majority of the top 50 up-regulated genes were involved in transmembrane transport and transporter activity in both the Al-resistant and Al-sensitive cultivars. However, genes encoding proteins with glutathione transferase and UDP-glycosyltransferase activity were in the top 50 up-regulated genes only in the flax cultivars resistant to aluminum. For qPCR analysis in extended sampling, two UDP-glycosyltransferases (UGTs), and three glutathione S-transferases (GSTs) were selected. The general trend of alterations in the expression of the examined genes was the up-regulation under Al stress, especially after 4 h of Al exposure. Moreover, in the flax cultivars resistant to aluminum, the increase in expression was more pronounced than that in the sensitive cultivars. We speculate that the defense against the Al toxicity via GST antioxidant activity is the probable mechanism of the response of flax plants to aluminum stress. We also suggest that UGTs could be involved in cell wall modification and protection from reactive oxygen species (ROS) in response to Al stress in L. usitatissimum. Thus, GSTs and UGTs, probably, play an important role in the response of flax to Al via detoxification of ROS and cell wall modification.
Highly parallel SNP genotyping.

genetic factors underlying common disease are largely unknown. Discovery of disease-causing genes will transform our knowledge of the genetic contribution to human disease, lead to new genetic screens, and underpin research into new cures and improved lifestyles. The se-quencing of the human genome has catalyzed efforts to search for disease genes by the strategy of associating sequence variants with measurable phenotypes. In particular , the Human Genome Project and follow-on efforts to characterize genetic variation have resulted in the discovery of millions of single-nucleotide polymorphisms (SNPs) (Patil et al. 2001; Sachidanandam et al. 2001; Reich et al. 2003). This represents a significant fraction of common genetic variation in the human genome and creates an unprecedented opportunity to associate genes with phenotypes via large-scale SNP genotyping studies. To make use of this information, efficient and accurate SNP genotyping technologies are needed. However, most methods were designed to analyze only one or a few SNPs per assay, and are costly to scale up (Kwok 2001; Syvanen 2001). To help enable genome-wide association studies and other large-scale genetic analysis projects, we have developed an integrated SNP genotyping system that combines a highly multiplexed assay with an accurate readout technology based on random arrays of DNA-coated beads (Michael et al. 1998; Oliphant et al. 2002; Gunderson et al. 2004). Our aim was to reduce costs and increase productivity by ~2 orders of magnitude. We chose a multiplexed approach because it is more easily scalable and is intrinsically cost-efficient (Wang et al. 1998). Although existing multiplexed approaches lacked the combination of accuracy, robustness, scalability, and cost-effectiveness needed for truly large-scale endeavors, we hypothesized that some of these limitations could be overcome by designing an assay specifically for multiplexing. To increase throughput and decrease costs by ~2 orders of magnitude, it was necessary to eliminate bottlenecks throughout the genotyping process. It was also desirable to minimize sources of variability and human error in order to ensure data quality and reproducibility. We therefore took a systems-level view to technology design, development , and integration. Although the focus of this paper is on a novel, highly multiplexed genotyping assay, the GoldenGate ™ assay, four other key technologies that were developed in parallel, as part of the complete BeadLab system (Oliphant et al. 2002), are briefly described below. BEADARRAY™ PLATFORM We developed an array technology based on random assembly of beads in micro-wells located at the end of an …
The Goldberg--Kerr Approach to Lorentz Covariant Gravity

The approach to asymptotic electromagnetic fields introduced by Goldberg and Kerr is used to study various aspects of Lorentz Covariant Gravity. Retarded multipole moments of the source, the central objects of this study, are defined, and a sequence of conservation equations for these are derived. These equations are used extensively throughout the paper. The solution of the linearized Einstein equation is obtained in terms of the retarded moments for a general bound source, correct to $O(r^{-4})$. This is used to obtain the peeling--off of the linearized field, and to study the geometric optics approximation for the field and for the energy-momentum pseudotensor of the field. It is shown that the energy-momentum 4-vector splits into the `total radiated 4-momentum' and the `bound 4-momentum of the source', similar to the case of the electromagnetic field. In the case of a source which has only retarded pole, dipole and quadrupole moments, a decomposition into arbitrary functions of a null coordinate is obtained which allows comparison with the solutions for linearized gravity obtained by other authors.
Current status of hemodilution in acute cerebral ischemia.

T 4 C r | ^ hinning the blood" is such an intuitively reasonable and understandable treatment for ischemic stroke that most clinicians have invoked this phrase to explain to families one of the ways of possibly treating their recently hemiplegic relative. The Scandinavian Stroke Study Group reports in this issue of Stroke, however, that hemodilution (or probably any treatment) does not work when applied by general physicians seeing patients several days after a stroke. This is a clinically important finding but it should not be a surprising one considering the conservative design of the study. In their thoughtful discussion, the authors address many of the questions raised by their results, but in addition, it should be emphasized that while it is necessary to validate any therapy in the "real world" and not in just the specialized confines of tertiary referral centers, the delay in treatment and relatively indiscriminate selection of patients characteristic of this study contradicts the emerging concept, based on modern studies of cerebral blood flow (CBF) and metabolism, that therapy of cerebral ischemia should be instituted early and tailored to subgroups of patients. The concept of hemodilution has been extensively reviewed in this journal and it is based on the close correlation of hematocrit and whole blood viscosity. Lowering hematocrit results in reduced viscosity and less resistance to blood flow, especially in regions of relative stasis. Arguments in favor of hemodilution therapy for cerebral ischemia are based on observations that hemodilution increases CBF and has improved clinical outcome in animal and preliminary human studies. "* Hypervolemic hemodilution is so popular for treating ischemic complications of vasospasm after subarachnoid hemorrhage that most clinicians dealing with this condition are reluctant to perform a controlled trial including untreated patients. Arguments against hemodilution are based on the poor correlation of CBF and outcome after stroke and the generally negative results obtained with other therapies aimed at raising CBF. Furthermore, improved