Reinforcement Learning for Systematic FX Trading

We explore online inductive transfer learning, with a feature representation transfer from a radial basis function network formed of Gaussian mixture model hidden processing units to a direct, recurrent reinforcement learning agent. This agent is put to work in an experiment, trading the major spot market currency pairs, where we accurately account for transaction and funding costs. These sources of profit and loss, including the price trends that occur in the currency markets, are made available to the agent via a quadratic utility, who learns to target a position directly. We improve upon earlier work by targeting a risk position in an online transfer learning context. Our agent achieves an annualised portfolio information ratio of 0.52 with a compound return of 9.3%, net of execution and funding cost, over a 7-year test set; this is despite forcing the model to trade at the close of the trading day at 5 pm EST when trading costs are statistically the most expensive

The potential of Λ and Ξ− studies with PANDA at FAIR

The antiproton experiment PANDA at FAIR is designed to bring hadron physics to a new level in terms of scope, precision and accuracy. In this work, its unique capability for studies of hyperons is outlined. We discuss ground-state hyperons as diagnostic tools to study non-perturbative aspects of the strong interaction, and fundamental symmetries. New simulation studies have been carried out for two benchmark hyperon-antihyperon production channels: p¯p→Λ¯Λ and p¯p→Ξ¯+Ξ−. The results, presented in detail in this paper, show that hyperon-antihyperon pairs from these reactions can be exclusively reconstructed with high efficiency and very low background contamination. In addition, the polarisation and spin correlations have been studied, exploiting the weak, self-analysing decay of hyperons and antihyperons. Two independent approaches to the finite efficiency have been applied and evaluated: one standard multidimensional efficiency correction approach, and one efficiency independent approach. The applicability of the latter was thoroughly evaluated for all channels, beam momenta and observables. The standard method yields good results in all cases, and shows that spin observables can be studied with high precision and accuracy already in the first phase of data taking with PANDA

DNA damage and repair following In vitro exposure to two different forms of titanium dioxide nanoparticles on trout erythrocyte

TiO(2) has been widely used to promote organic compounds degradation on waste aqueous solution, however, data on TiO(2) nanotoxicity to aquatic life are still limited. In this in vitro study, we compare the toxicity of two different families of TiO(2) nanoparticles on erythrocytes from Oncorhynchus mykiss trout. The crystal structure of the two TiO(2) nanoparticles was analyzed by XRD and the results indicated that one sample is composed of TiO(2) in the anatase crystal phase, while the other sample contains a mixture of both the anatase and the rutile forms of TiO(2) in a 2:8 ratio. Further characterization of the two families of TiO(2) nanoparticles was determined by SEM high resolution images and BET technique. The toxicity results indicate that both TiO(2) nanoparticles increase the hemolysis rate in a dose dependent way (1.6, 3.2, 4.8 μg mL(-1) ) but they do not influence superoxide anion production due to NADH addition measured by chemiluminescence. Moreover, TiO(2) nanoparticles (4.8 μg mL(-1) ) induce DNA damage and the entity of the damage is independent from the type of TiO(2) nanoparticles used. Modified comet assay (Endo III and Fpg) shows that TiO(2) oxidizes not only purine but also pyrimidine bases. In our experimental conditions, the exposure to TiO(2) nanoparticles does not affect the DNA repair system functionality. The data obtained contribute to better characterize the aqueous environmental risks linked to TiO(2) nanoparticles exposure. © 2011 Wiley Periodicals, Inc. Environ Toxicol, 2011

Glassy magnetic behavior and correlation length in nanogranular Fe-oxide and Au/Fe-oxide samples

In nanoscale magnetic systems, the possible coexistence of structural disorder and competing magnetic interactionsmay determine the appearance of a glassy magnetic behavior, implying the onset of a low-temperature disordered collective state of frozen magnetic moments. This phenomenology is the object of an intense research activity, stimulated by a fundamental scientific interest and by the need to clarify how disordered magnetism effects may affect the performance of magnetic devices (e.g., sensors and data storage media). We report the results of a magnetic study that aims to broaden the basic knowledge of glassy magnetic systems and concerns the comparison between two samples, prepared by a polyol method. The first can be described as a nanogranular spinel Fe-oxide phase composed of ultrafine nanocrystallites (size of the order of 1 nm); in the second, the Fe-oxide phase incorporated non-magnetic Au nanoparticles (10-20 nm in size). In both samples, the Fe-oxide phase exhibits a glassy magnetic behavior and the nanocrystallite moments undergo a very similar freezing process. However, in the frozen regime, the Au/Fe-oxide composite sample is magnetically softer. This effect is explained by considering that the Au nanoparticles constitute physical constraints that limit the length of magnetic correlation between the frozen Fe-oxide moments

Novel mixed precursor approach to prepare multiferroic nanocomposites with enhanced interfacial coupling

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Identifying clusters of anomalous payments in the salvadorian payment system

We develop an unsupervised methodology to group payments and identify possible anomalies. With our methodology, we identify clusters based on a set of network features, using transactional (unlabeled) information from a systemically important payment system of El Salvador. We first preprocess network features, such as degree and strength, through a principal components analysis we reduce the dimensionality of the newly defined data, then we place the main variables into clustering algorithms (k-means and DBSCAN) to analyze anomalous payments. We then analyze, these clusters using random forest to obtain the main network feature. Our results suggest that the proposed methodology works very well to detect anomalous payments, and it is very important to study the case of El Salvador, because of the recent restructuring of the Massive Payment System in El Salvador (promoted by the Transfer365 project), because the authorities want to increase financial inclusion. This change will make the SPM available to the public, to diversify services and incorporate more participants because, historically, it has operated with only three active participants. We expected that Transfer365 will interconnect the LBTR participants' systems with their banking core, the systems of the Ministry of Finance, and other authorized participants to channel large payment flows. Then, identifying possible anomalies through methodology will enhance risk monitoring and management by payment systems overseers

Influence of the thermomechanical characteristics of low-density polyethylene substrates on the thermoresistive properties of graphite nanoplatelet coatings

Morphological, structural, and thermoresistive properties of films deposited on low-density polyethylene (LDPE) substrates are investigated for possible application in flexible electronics. Scanning and transmission electron microscopy analyses, and X-ray diffraction measurements show that the films consist of overlapped graphite nanoplatelets (GNP) each composed on average of 41 graphene layers. Differential scanning calorimetry and dynamic-mechanical-thermal analysis indicate that irreversible phase transitions and large variations of mechanical parameters in the polymer substrates can be avoided by limiting the temperature variations between −40 and 40◦ C. Electrical measurements performed in such temperature range reveal that the resistance of GNP films on LDPE substrates increases as a function of the temperature, unlike the behavior of graphite-based materials in which the temperature coefficient of resistance is negative. The explanation is given by the strong influence of the thermal expansion properties of the LDPE substrates on the thermo-resistive features of GNP coating films. The results show that, narrowing the temperature range from 20 to 40◦ C, the GNP on LDPE samples can work as temperature sensors having linear temperature-resistance relationship, while keeping constant the temperature and applying mechanical strains in the 0–4.2 × 10−3 range, they can operate as strain gauges with a gauge factor of about 48

Biomedical Co-Cr-Mo Components Produced by Direct Metal Laser Sintering

Direct Metal Laser Sintering (DMLS) is an additive manufacturing technique based on a laser power source that sinters powdered materials using a 3D CAD model. The mechanical components produced by this procedure typically show higher residual porosity and poorer mechanical properties than those obtained by traditional manufacturing techniques. In this study, samples were produced by DMLS starting from a Co-Cr-Mo powder (in the \u3b3 phase) with a composition suitable for biomedical applications. Samples were submitted to hardness measurements and structural characterization. The samples showed a hardness value remarkably higher that those commonly obtained for the same cast or wrought alloys. In fact, the HRC value measured for the samples is 47 HRC, while the usual range for CAST Co-Cr-Mo is from 25 to 35 HRC. The samples microstructure was investigated by X-ray diffraction (XRD), electron microscopy (SEM and TEM) and energy dispersive microanalysis (EDX) in order to clarify the origin of this unexpected result. The laser treatment induced a melting of the metallic Co-Cr-Mo powder, generating a phase transformation from the \u3b3 (fcc) to the e (hcp) phase. The rapid cooling of the melted powder produced the formation of e (hcp) nano-lamellae inside the \u3b3 (fcc) phase. The nano-lamellae formed an intricate network responsible for the measured hardness increase. The results suggest possible innovative applications of the DMLS technique to the production of mechanical parts in the medical and dental fields, where a high degree of personalization is required

Solid-state phase transformations in thermally treated Ti-6Al-4V alloy fabricated via laser powder bed fusion

Laser Powder Bed Fusion (LPBF) technology was used to produce samples based on the Ti-6Al-4V alloy for biomedical applications. Solid-state phase transformations induced by thermal treatments were studied by neutron diffraction (ND), X-ray diffraction (XRD), scanning transmission electron microscopy (STEM) and energy-dispersive spectroscopy (EDS). Although, ND analysis is rather uncommon in such studies, this technique allowed evidencing the presence of retained \u3b2 in \u3b1' martensite of the as-produced (#AP) sample. The retained \u3b2 was not detectable byXRDanalysis, nor by STEM observations. Martensite contains a high number of defects, mainly dislocations, that anneal during the thermal treatment. Element diffusion and partitioning are the main mechanisms in the \u3b1 \u2194 \u3b2 transformation that causes lattice expansion during heating and determines the final shape and size of phases. The retained \u3b2 phase plays a key role in the \u3b1' \u2192 \u3b2 transformation kinetics