Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural breaks and financial volatility: Lessons from BRIC countries

Despite the fact that there is a substantial literature on the analysis of volatility spillovers between stock returns and domestic exchange rates, surprisingly, little empirical research has examined volatility spillovers between oil prices and emerging economies, where a clear gap of research have been found regarding to the BRIC financial markets and the effects of the 2007-2009 World economy crisis. This lack of research might appear as surprising given that energy markets are of particular interest as they are considered a fundamental reference for economic recovery and growth. Therefore, this work aims to address this gap on the literature by looking at the BRIC financial markets and their co-movements with regard to some energy markets (oil, natural gas and electricity) and also to the international pressures that may arise from fluctuations originated in the US stock markets. This research major findings show compelling evidence highlighting the weak integration levels that exist among the Chinese financial markets, energy markets and the US stock market. On the other hand, the Brazilian, Indian and Russian markets are found to be more sensitive to international shocks arisen from US markets and also to energy markets instability, especially with regard to oil market uncertainty.
Estimation of IMU orientation using linear Kalman Filter based on correntropy criterion

Human motion is an important issue in various medical analyses. In this paper, the application of interest is estimating the orientation of the wrist in indoor and outdoor activities using low cost Inertial Measurement Sensor IMU. We present an orientation estimation using Kalman Filter based on Correntropy Criterion (KFCC). The proposed method uses only the acceleration data in the aim to reduce the computing load with accurate orientation estimation. Optical measurement system has been used to benchmark the performance of the proposed method. Moreover, the KFCC is evaluated in indoor and outdoor activities with static and dynamic motion conditions. The proposed method proves its efficiency and reliability against existing methods.
An effective crossing minimisation heuristic based on star insertion

We present a new heuristic method for minimising crossings in a graph. The method is based upon repeatedly solving the so-called star insertion problem and has several desirable characteristics for practical use. We introduce the method, discuss some aspects of algorithm design for our implementation, and provide some experimental results. The results indicate that our method compares well to existing methods, particularly for dense graphs, and is able to obtain some of the best known heuristic solutions to well-known instances.
Primary Cutaneous Lymphomas and Interferon Treatment

Primary cutaneous lymphomas (PCLs) are the second most common group of extranodal non-Hodgkin lymphomas (NHL) with an estimated annual incidence of 1/100.000. Interferons (IFNs) are used in mono or combination therapy for cutaneous lymphomas especially for cutaneous T-cell lymphomas (CTCL) for years. IFN-α is the most widely-used type for cutaneous lymphomas. IFN-α has been shown to be a highly active agent in CTCL with response rates ranging from 40% to 80%. In this review, the current information about PCLs and IFNs treatment is summarized. Review Article
Diagnostic Accuracy of Natriuretic Peptides for Heart Failure in Patients with Pleural Effusion: A Systematic Review and Updated Meta-Analysis

Background Previous studies have reported that natriuretic peptides in the blood and pleural fluid (PF) are effective diagnostic markers for heart failure (HF). These natriuretic peptides include N-terminal pro-brain natriuretic peptide (NT-proBNP), brain natriuretic peptide (BNP), and midregion pro-atrial natriuretic peptide (MR-proANP). This systematic review and meta-analysis evaluates the diagnostic accuracy of blood and PF natriuretic peptides for HF in patients with pleural effusion. Methods PubMed and EMBASE databases were searched to identify articles published in English that investigated the diagnostic accuracy of BNP, NT-proBNP, and MR-proANP for HF. The last search was performed on 9 October 2014. The quality of the eligible studies was assessed using the revised Quality Assessment of Diagnostic Accuracy Studies tool. The diagnostic performance characteristics (sensitivity, specificity, and other measures of accuracy) were pooled and examined using a bivariate model. Results In total, 14 studies were included in the meta-analysis, including 12 studies reporting the diagnostic accuracy of PF NT-proBNP and 4 studies evaluating blood NT-proBNP. The summary estimates of PF NT-proBNP for HF had a diagnostic sensitivity of 0.94 (95% confidence interval [CI]: 0.90–0.96), specificity of 0.91 (95% CI: 0.86–0.95), positive likelihood ratio of 10.9 (95% CI: 6.4–18.6), negative likelihood ratio of 0.07 (95% CI: 0.04–0.12), and diagnostic odds ratio of 157 (95% CI: 57–430). The overall sensitivity of blood NT-proBNP for diagnosis of HF was 0.92 (95% CI: 0.86–0.95), with a specificity of 0.88 (95% CI: 0.77–0.94), positive likelihood ratio of 7.8 (95% CI: 3.7–16.3), negative likelihood ratio of 0.10 (95% CI: 0.06–0.16), and diagnostic odds ratio of 81 (95% CI: 27–241). The diagnostic accuracy of PF MR-proANP and blood and PF BNP was not analyzed due to the small number of related studies. Conclusions BNP, NT-proBNP, and MR-proANP, either in blood or PF, are effective tools for diagnosis of HF. Additional studies are needed to rigorously evaluate the diagnostic accuracy of PF and blood MR-proANP and BNP for the diagnosis of HF.
Structure of c-phycocyanin from the thermophilic cyanobacterium Synechococcus vulcanus at 2.5 A: structural implications for thermal stability in phycobilisome assembly.

The crystal structure of the light-harvesting phycobiliprotein, c-phycocyanin from the thermophilic cyanobacterium Synechochoccus vulcanus has been determined by molecular replacement to 2.5 A resolution. The crystal belongs to space group R32 with cell parameters a=b=188.43 A, c=61.28 A, alpha=beta=90 degrees, gamma=120 degrees, with one (alphabeta) monomer in the asymmetric unit. The structure has been refined to a crystallographic R factor of 20.2 % (R-free factor is 24.4 %), for all data to 2.5 A. The crystals were grown from phycocyanin (alphabeta)(3) trimers that form (alphabeta)(6) hexamers in the crystals, in a fashion similar to other phycocyanins. Comparison of the primary, tertiary and quaternary structures of the S. vulcanus phycocyanin structure with phycocyanins from both the mesophilic Fremyella diplsiphon and the thermophilic Mastigocladus laminosus were performed. We show that each level of assembly of oligomeric phycocyanin, which leads to the formation of the phycobilisome structure, can be stabilized in thermophilic organisms by amino acid residue substitutions. Each substitution can form additional ionic interactions at critical positions of each association interface. In addition, a significant shift in the position of ring D of the B155 phycocyanobilin cofactor in the S. vulcanus phycocyanin, enables the formation of important polar interactions at both the (alphabeta) monomer and (alphabeta)(6) hexamer association interfaces.
Boosting Robot Learning and Control with Domain Constraints

In this short paper, we exploit robotics domain knowledge, be it acquired from humans or self-organization, to alleviate learning and control challenges from directly dealing with raw demonstrations or sparse reward signals. We take a unified latent variable perspective in incorporating domain constraints. The latent variables are regarded as task parameters or representations, which rationalize task observations with a generative model. The constraints can thus be specified with structured latent variables. Different from many related works, we explore latent structures that are computationally feasible and robotics-oriented to facilitate both task learning and control synthesis. The paper will briefly discuss adopted structures ranging from parameter dependency, modality and dynamical associativity, extending imitation learning such as inverse optimal control and deep generative models. The framework is shown to be effective in a range of manipulation tasks, including 1) learning variable impedance controllers in robotic handwriting; 2) boosting motion synthesis for writing novel symbols; 3) reasoning an internal model to score a balltarget under malfunctioning visual input.
Measuring Practical Coil Array Performance with Respect to Ultimate Intrinsic SNR: A Tool for Array Design and Assessment

R. Lattanzi, A. K. Grant, M. A. Ohliger, D. K. Sodickson Division of Health Science and Technology, Harvard-MIT, Cambridge, MA, United States, Radiology, Beth Israel Deaconess Medical Center, Boston, MA, United States Introduction As the number of available receiver channels on modern MR systems increases, increasing attention will be paid to the design and performance of many-element RF coil arrays. Questions regarding the balance of coil-noise and sample-noise or the suitability of any particular array design for parallel imaging– already areas of great practical interest to coil designers – promise to take on new significance as the number of elements increases. In this context, it would be useful to have a concrete metric of coil performance, in order not only to compare different designs but also to determine how much room for improvement there may be in any particular design. Recent studies have shown that there is an inherent electrodynamic limitation to the achievable SNR for any physically realizable coil array (assuming sampledominated noise), and have modeled the behavior of ultimate intrinsic SNR either in the absence [1] or in the presence [2,3] of parallel acceleration. In [1], coil performance maps were also presented, in which the actual SNR of particular coils was compared with the appropriately scaled ultimate intrinsic SNR for a particular phantom and image plane geometry. In this work, we extend the computation of coil performance maps to include the effects of parallel imaging. We compute the ultimate SNR at each point within a central cross-section of a cylindrical phantom for a variety of acceleration factors, and express the actual SNR, measured with a particular eight-element coil array in a phantom with the same geometry, as a percentage of the ultimate achievable value. Such coil performance maps may of course be generated for arbitrary coil arrays and object/image geometries, and they may ultimately be used as absolute references for coil design optimization.
An Extreme Protocluster of Luminous Dusty Starbursts in the Early Universe

We report the identification of an extreme protocluster of galaxies in the early universe whose core (nicknamed Distant Red Core, DRC, because of its very red color in Herschel SPIRE bands) is formed by at least 10 dusty star-forming galaxies (DSFGs), spectroscopically confirmed to lie at z spec = 4.002 via detection of [C i](1–0), 12CO(6–5), 12CO(4–3), 12CO(2–1), and H 2 O ( 2 11 – 2 02 ) emission lines with ALMA and ATCA. These DSFGs are distributed over a 260 kpc × 310 kpc region and have a collective obscured star formation rate (SFR) of ∼ 6500 M ⊙ yr − 1 , considerably higher than those seen before in any protocluster at z ≳ 4 . Most of the star formation is taking place in luminous DSFGs since no Lyα emitters are detected in the protocluster core, apart from a Lyα blob located next to one of the DRC components, extending over 60 kpc . The total obscured SFR of the protocluster could rise to SFR ∼ 14,400 M ⊙ yr − 1 if all the members of an overdensity of bright DSFGs discovered around DRC in a wide-field Large APEX BOlometer CAmera 870 μm image are part of the same structure. [C i](1–0) emission reveals that DRC has a total molecular gas mass of at least M H 2 ∼ 6.6 × 10 11 M ⊙ , and its total halo mass could be as high as ∼ 4.4 × 10 13 M ⊙ , indicating that it is the likely progenitor of a cluster at least as massive as Coma at z = 0.
DPRA: Dynamic Power-Saving Resource Allocation for Cloud Data Center Using Particle Swarm Optimization

Cloud computing provides the scalable computation capability based on a virtualization technique. The energy conservation for green computing is one of the vital issues while allocating resources. To improve energy efficiency, the dynamic power-saving resource allocation (DPRA) mechanism based on a particle swarm optimization algorithm is proposed. The DPRA mechanism not only considers the energy consumption of physical machine (PM) and virtual machine (VM) but also newly tackles the energy efficiency ratio of air conditioner. Moreover, the least squares regression method is utilized to forecast PM's resource utilization for allocating VM and eliminating VM migrations. In simulation, the proposed DPRA mechanism is compared with three familiar allocation schemes and one previous solution. Simulation results show that in the presence of VM number, DPRA outperforms traditional schemes and previous solution in terms of total energy consumption (includes PMs and air conditioners), total electric bill, VM migration, and the number of shutdown PMs, chosen as objective performance metrics.
A Hardware Platform for Efficient Multi-Modal Sensing with Adaptive Approximation

We present Warp, a hardware platform to support research in approximate computing, sensor energy optimization, and energy-scavenged systems. Warp incorporates 11 state-of-the-art sensor integrated circuits, computation, and an energy-scavenged power supply, all within a miniature system that is just 3.6 cm x 3.3 cm x 0.5 cm. Warp's sensor integrated circuits together contain a total of 21 sensors with a range of precisions and accuracies for measuring eight sensing modalities of acceleration, angular rate, magnetic flux density (compass heading), humidity, atmospheric pressure (elevation), infrared radiation, ambient temperature, and color. Warp uses a combination of analog circuits and digital control to facilitate further tradeoffs between sensor and communication accuracy, energy efficiency, and performance. This article presents the design of Warp and presents an evaluation of our hardware implementation. The results show how Warp's design enables performance and energy efficiency versus ac- curacy tradeoffs.
IDENTIFICATION OF THE HUMAN RESPIRATORY SYSTEM DURING EXPERIMENT WITH NEGATIVE PRESSURE IMPULSE EXCITATION

This article describes an innovative measurement method enabling one to identify mechanical parameters of the respiratory tract. The method is compared with traditional techniques such as the forced oscillation technique (FOT), forced expiration technique, and the interrupter technique (IT). The developed characteristics of the method were examined by simulation and experiments. The results confirmed its specificity and sensitivity. The respiratory system along with the circulatory system constitute a basic system whose proper functioning determines an organism's survival. The basic respiratory system's function is to provide an organism with oxygen and to remove toxic carbon dioxide, which is a result of metabolism, from the organism. An acute failure of the respiratory system may have various reasons, but it always is an immediate threat to life. Hence, a lot of attention is paid to its diagnostics. The article describes a new method to identify mechanical parameters of the respiratory system. The method is based on the assumption that from the identification point of view the respiratory system is a pneumatic, dynamic system and its properties are determined by parameters such as elastance, inertance as well as pneumatic resistance. If a transient state is generated in such a system by proper stimulation, transients of the object measurable signals will contain data sufficient to evaluate its parameters that is, conduct parametrical identification of the respiratory system. The object identification may be formulated as a solution of the inverse problem (21). What is difficult in the process is to stimulate the object properly so that the data signals content is rich enough. The difficulty also lies in the fact that the data need be read and transformed into parameter estimates being the purpose of the research. The usefulness of the method is a derivative of the estimated parameter number and the uncertainty of the received estimates. The measurement method presented in this article consists in stimulating the respiratory system with a short pressure impulse of 50 ms, generated at the outlet of the respiratory tract and recording the transitional state generated in this way in the flow signal of the exhaled air. An advantage of the method is the fact that it requires little cooperation on the examined person's side, which facilitates conducting research and renders the method objective. Another advantage is the simplicity of the measurement system. The process of obtaining diagnostic data has been moved to the stage of algorithmic processing of the recorded
MPGM: Scalable and Accurate Multiple Network Alignment

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network motifs, and the reconstruction of species’ phylogenetic relationships. A good multiple-network alignment (MNA), by considering the data related to several species, provides a deep understanding of biological networks and system-level cellular processes. With the massive amounts of available PPI data and the increasing number of known PPI networks, the problem of MNA is gaining more attention in the systems-biology studies. In this paper, we introduce a new scalable and accurate algorithm, called <sc>MPGM</sc>, for aligning multiple networks. The <sc>MPGM</sc> algorithm has two main steps: (i) <sc>SeedGeneration</sc> and (ii) <sc>MultiplePercolation</sc>. In the first step, to generate an initial set of seed tuples, the <sc>SeedGeneration</sc> algorithm uses only protein sequence similarities. In the second step, to align remaining unmatched nodes, the <sc>MultiplePercolation</sc> algorithm uses network structures and the seed tuples generated from the first step. We show that, with respect to different evaluation criteria, <sc>MPGM</sc> outperforms the other state-of-the-art algorithms. In addition, we guarantee the performance of <sc>MPGM</sc> under certain classes of network models. We introduce a sampling-based stochastic model for generating <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="kazemi-ieq1-2914050.gif"/></alternatives></inline-formula> correlated networks. We prove that for this model if a sufficient number of seed tuples are available, the <sc>MultiplePercolation</sc> algorithm correctly aligns almost all the nodes. Our theoretical results are supported by experimental evaluations over synthetic networks.
Understanding the Role of Automated Response Actions in Improving AMI Resiliency

The smart grid promises better services and higher reliability but is exposed to new security threats. In particular, deployment of advanced metering infrastructures (AMIs) will vastly increase the attack surface because of the smart meters installed in customer homes. Managing the security of AMIs cannot be done manually because of their size and complexity. Thus, we propose a three-step plan to bring automated responses to AMIs. Considering the challenges of automated responses, we will develop a taxonomy of response actions in AMIs. Then, we will model the response actions in terms of their impact and cost for the different actors in the system: users, administrators, and attackers. Finally, we will discuss implementation and evaluation requirements for a practical automated response engine for AMIs.
Structure of chlorine isotopes populated by heavy ion transfer reactions

Neutron-rich chlorine isotopes were populated in the Ar-40 + Pb-208 multiple transfer reaction via the -1p channels in a fragment-gamma coincident measurement employing the Prisma-Clara setup. New gamma transitions have been identified and, together with already available data, level schemes have been revised and compared with the results of large-scale sd-pf shell-model calculations. The evolution of the energy splitting between the s(1/2) and d(3/2) orbitals and the increased mixing of different proton configurations in the populated Cl isotopic chain have been deduced by inspecting the shell-model wave functions.
Origins and History of Laboratory Insect Stocks in a Multispecies Insect Production Facility, With the Proposal of Standardized Nomenclature and Designation of Formal Standard Names

Abstract Laboratory insect colonies are an essential part of experimental insect science. Formalized naming of laboratory stocks is standard practice in model organisms such as mice and fruit flies, but crucial details such as colony origin and standard names are often lacking in nonmodel systems. For institutions involved in rearing multiple nonmodel species, effective monitoring requires standardized naming and nomenclature, from establishment to production, distribution, and publication. Insect rearing has been the cornerstone of the Insect Production and Quarantine Laboratories (IPQL) at the Great Lakes Forestry Centre for over 70 yr, but the histories of the insect colonies in this facility have not been adequately documented and formal, standardized names do not exist. We propose a standardized naming framework that we applied to the eight species reared at the IPQL to rectify these deficiencies. We also present the origin and history of each colony, essential information that is challenging to obtain post hoc. We suggest that other research institutions consider developing similar standards, so they can accurately document, communicate, and track laboratory insect their within the facilities and through the scientific literature.
Organ-ona-chip platforms for studying drug delivery systems

a Division of Biomedical Engineering, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, 02139, USA b Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, 02139, USA c Doctoral Programme in Experimental Biology and Biomedicine, Center for Neuroscience and Cell Biology, Institute for Interdisciplinary Research, University of Coimbra, 3030-789 Coimbra, Portugal d Biocant — Biotechnology Innovation Center, 3060-197 Cantanhede, Portugal e Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston 02115, USA f Department of Physics, King Abdulaziz University, Jeddah 21569, Saudi Arabia
Photospheric high-frequency acoustic power excess in sunspot umbra: signature of magneto-acoustic modes

Abstract. We present observational evidence for the presence of MHD (magnetohydrodynamic) waves in the solar photosphere deduced from SOHO/MDI (Solar and Heliospheric Observatory/Michelson Doppler Imager) Dopplergram velocity observations. The magneto-acoustic perturbations are observed as acoustic power enhancement in the sunspot umbra at high-frequency bands in the velocity component perpendicular to the magnetic field. We use numerical modelling of wave propagation through localised non-uniform magnetic field concentration along with the same filtering procedure as applied to the observations to identify the observed waves. Guided by the results of the numerical simulations we classify the observed oscillations as magneto-acoustic waves excited by the trapped sub-photospheric acoustic waves. We consider the potential application of the presented method as a diagnostic tool for magnetohelioseismology.