Miracle-dz/UniFAR-FTUs huggingface dataset:
Finite-size effects in fine particles: magnetic and transport properties

Some of the most relevant finite-size and surface effects in the magnetic and transport properties of magnetic fine particles and granular solids are reviewed. The stability of the particle magnetization, superparamagnetic regime and the magnetic relaxation are discussed. New phenomena appearing due to interparticle interactions, such as the collective state and non-equilibrium dynamics, are presented. Surface anisotropy and disorder, spin-wave excitations, as well as the enhancements of the coercive field and particle magnetization are also reviewed. The competition of surface and finite-size effects to settle the magnetic behaviour is addressed. Finally, two of the most relevant phenomena in the transport properties of granular solids are summarized namely, giant magnetoresistance in granular heterogeneous alloys and Coulomb gap in insulating granular solids.
Automatic case cluster detection using hospital electronic health record data

Abstract Case detection through contact tracing is a key intervention during an infectious disease outbreak. However, contact tracing is an intensive process where a given contact tracer must locate not only confirmed cases but also identify and interview known contacts. Often these data are manually recorded. During emerging outbreaks, the number of contacts could expand rapidly and beyond this, when focused on individual transmission chains, larger patterns may not be identified. Understanding if particular cases can be clustered and linked to a common source can help to prioritize contact tracing effects and understand underlying risk factors for large spreading events. Electronic health records systems are used by the vast majority of private healthcare systems across the USA, providing a potential way to automatically detect outbreaks and connect cases through already collected data. In this analysis, we propose an algorithm to identify case clusters within a community during an infectious disease outbreak using Bayesian probabilistic case linking and explore how this approach could supplement outbreak responses; especially when human contact tracing resources are limited.
The Infection Dynamics of Experimental Edwardsiella ictaluri and Flavobacterium covae Coinfection in Channel Catfish (Ictalurus punctatus)

Edwardsiella ictaluri and Flavobacterium covae are pervasive bacterial pathogens associated with significant losses in catfish aquaculture. Bacterial coinfections have the potential to increase outbreak severity and can worsen on-farm mortality. A preliminary assessment of in vivo bacterial coinfection with E. ictaluri (S97-773) and F. covae (ALG-00-530) was conducted using juvenile channel catfish (Ictalurus punctatus). Catfish were divided into five treatment groups: (1) mock control; (2) E. ictaluri full dose (immersion; 5.4 × 105 CFU mL−1); (3) F. covae full dose (immersion; 3.6 × 106 CFU mL−1); (4) E. ictaluri half dose (immersion; 2.7 × 105 CFU mL−1) followed by half dose F. covae (immersion; 1.8 × 106 CFU mL−1); and (5) F. covae half dose followed by half dose E. ictaluri. In the coinfection challenges, the second inoculum was delivered 48 h after the initial exposure. At 21 days post-challenge (DPC), the single dose E. ictaluri infection yielded a cumulative percent mortality (CPM) of 90.0 ± 4.1%, compared with 13.3 ± 5.9% in the F. covae group. Mortality patterns in coinfection challenges mimicked the single dose E. ictaluri challenge, with CPM of 93.3 ± 5.4% for fish initially challenged with E. ictaluri followed by F. covae, and 93.3 ± 2.7% for fish exposed to F. covae and subsequently challenged with E. ictaluri. Despite similarities in the final CPM within the coinfection groups, the onset of peak mortality was delayed in fish exposed to F. covae first but was congruent with mortality trends in the E. ictaluri challenge. Catfish exposed to E. ictaluri in both the single and coinfected treatments displayed increased serum lysozyme activity at 4-DPC (p < 0.001). Three pro-inflammatory cytokines (il8, tnfα, il1β) were evaluated for gene expression, revealing an increase in expression at 7-DPC in all E. ictaluri exposed treatments (p < 0.05). These data enhance our understanding of the dynamics of E. ictaluri and F. covae coinfections in US farm-raised catfish.
The Asymmetric Effect of Exchange Rate on the Household Consumption Expenditures

Previous literature on the exchange rate and household consumption failed to examine the effect of positive and negative changes in the exchange rate on household consumption expenditures. We extended the available literature by investigating the asymmetric impacts in African emerging economies (AEE). To attain this aim, we utilized the nonlinear ARDL model, which covers both negative and positive shocks in the exchange rate. Our results indicate that movements in the exchange rate have asymmetric impacts on household consumption in all the included emerging economies, excluding Nigeria. Our findings propose recommendations for the policymakers to ensure the alignment of the optimal exchange rate for countries of emerging African economies and propose relevant policies for the countries.JEL Classification: D12, D60, I30How to Cite:Gohar, R. , Chang, B. H. , Uche, E. , & Bhatty, K. (2023). The Asymmetric Effect of Exchange Rate on the Household Consumption Expenditures. Etikonomi, 22(1), 31–44. https://doi.org/10.15408/etk.v22i1. 23428.
Low power deformable mirror actuator controller

A deformable mirror may be used to improve the image quality of ground-based optical telescopes, by counteracting the distortions caused by atmospheric turbulence. Dedicated controller boards, carrying multiple FPGAs, are used to drive the actuators inside the deformable mirror. The power dissipation of the FPGAs causes additional distortions by heating the air surrounding the mirror. An attempt is made to reduce these distortions by optimizing the power usage of the FPGAs. The software in the FPGAs is migrated to a development board and methods for measuring power usage are developed. The power measurements have led to improved controller designs that use less power than the original designs.
Adding-weight local-region linear model of network traffic forecast based on degree of incidence

When the embedded dimension of reconstructive phase space increase,applying the traditional adding-weight local-region model,which the weight of neighbor phase points is generally determined by space distance to forecast the chaotic time series,is not so satisfied.In the paper,taking the incidence-degree impact on the dynamical behavior of forecast center point into account,a novel adding-weight local-region linear model for forecasting network traffic is created,with the weight of neighbor phase points defined by incidence-degree between neighbor phase points with forecast center point.The result of simulation shows the presented model can greatly improve precision of network traffic forecasting when the embedded dimension is high,compared with the traditional method.
Coronary Physiology: Modern Concepts for the Guidance of Percutaneous Coronary Interventions and Medical Therapy

Recent evidence on ischemia, rather than coronary artery disease (CAD), representing a major determinant of outcomes, has led to a progressive shift in the management of patients with ischemic heart disease. According to most recent guidelines, myocardial revascularization strategies based on anatomical findings should be progressively abandoned in favor of functional criteria for the guidance of PCI. Thus, emerging importance has been assigned to the assessment of coronary physiology in order to determine the ischemic significance of coronary stenoses. However, despite several indexes and tools that have been developed so far, the existence of technical and clinical conditions potentially biasing the functional evaluation of the coronary tree still cause debates regarding the strategy of choice. The present review provides an overview of the available methods and the most recent acquirements for the invasive assessment of ischemia, focusing on the most widely available indexes, fractional flow reserve (FFR) and instant-wave free ratio (iFR), in addition to emerging examples, as new approaches to coronary flow reserve (CFR) and microvascular resistance, aiming at promoting the knowledge and application of those “full physiology” principles, which are generally advocated to allow a tailored treatment and the achievement of the largest prognostic benefits.
Direct numerical simulation of dynamic three-fluid flow

Three-fluid flow is characterised by three different interfaces between fluids, which are among the most important issues in a three-fluid flow. The objective of this paper is to track the dynamic interfaces between fluids implicitly and then to computerise the flow hydrodynamics. We use the level-set method for the interface tracking and a high-order Navier-Stokes solver, called Cubic-Interpolated Pseudo-Particle (CIP) algorithm to solve the equation system. Firstly, a two-fluid situation is simulated to demonstrate the capability of the level-set method. Then, as an example, we simulate a drop which is covered by a layer of gas/vapour and is moving in a water pool. The dynamic processes, such as deformation of vapour layer and its detachment from the drop, are simulated.
Control: A -Dissipative Approach

This paper applies the chain-scattering approach for linear control to input affine nonlinear plants with general output structure. The nonlinear -control problem is reformu- lated in terms of the chain representation of a given plant. The state-space characterization of -dissipative ( -lossless) systems together with two special types of coprime factorizations are used to provide a class of controllers which solve locally the -control problem. The problems considered correspond to the general two- and four-block problems in the linear case. The results are given in terms of two uncoupled nonlinear partial differential inequalities with a coupling condition on their solutions.
An aggregation/disaggregation algorithm for computing the stationary distribution of a large markov chain

A new aggregation/disaggregation iterative procedure for computing the stationary distribution of a large Markov chain is proposed. In each iteration two steps are performed. In the first, one updates approximations to the limit of the conditional probabilities of states given the subset which the chain visits. This is done by rank-one modifications of stochastic matrices each of which approximates the transition probabilities of the Markov chain resulting from observing the original chain only while in the subset under consideration. This results in a computational improvement upon existing methods in which the modification is not rank-one. In the second step, one approximates the aggregate probabilities of the subsets themselves. We analyse the performance of the procedure when applied to nearly uncoupled stochastic matrices. In particular, we show that if the matrix has the degree of coupling ϵ between subsets, then there is a reduction of O(ϵ) in the error of the approximation at each iteration.
Hard X-rays from Coma Cluster region

A high-energy nonthermal component in the 18-130 keV energy band was detected by balloon-borne observations of the region containing the Coma Cluster of galaxies. The emitted photon spectrum is well-described by a single power law of photon index -1.77 and an intensity of 8.9 x 10 to the -5th photons/sq cm/s/KeV at 50 keV. The emission supports the presence of a hard tail, and could be due to the inverse Compton mechanism of relativistic electrons permeating the cluster off the 2.7 K background radiation or the presence in the field of an active galactic nucleus. 30 refs.
Reliability analysis in aperture synthesis interferometric radiometers: Application to L band Microwave Imaging Radiometer with Aperture Synthesis instrument

The Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) instrument will be the first radiometer using aperture synthesis techniques for Earth observation. It will be boarded in the Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission of the European Space Agency and launched in 2005. The configuration under study in the MIRAS Demonstrator Pilot Project is a Y‐shaped array with 27 dual‐polarization L band antennas in each arm, spaced 0.89 wavelengths. In addition to these 81 antennas there are 3 additional ones between the arms for phase restoration and redundancy purposes and an extra one at the center of the Y array that is connected to a noise injection radiometer. The digitized in‐phase and quadrature outputs of each receiver are multiplexed in groups of four and optically transmitted to the hub where the complex cross correlations are computed. In this configuration there are 85 antennas‐receiving channels and 21 multiplexers. The objectives of this paper are twofold: (1) the study of the performance degradation of Y‐shaped aperture synthesis interferometric radiometers in case of single or multiple subsystem failures and (2) a reliability analysis at subsystem level.
Association between maternal multimorbidity and preterm birth, low birth weight and small for gestational age: a prospective birth cohort study from the Japan Environment and Children’s Study

Objectives Multimorbidity is defined as the coexistence of two or more chronic physical or psychological conditions within an individual. The association between maternal multimorbidity and adverse perinatal outcomes such as preterm delivery and low birth weight has not been well studied. Therefore, this study aimed to investigate this association. Methods We conducted a prospective cohort study using data from the Japan Environment and Children’s Study of pregnant women between 2011 and 2014. Those with data on chronic maternal conditions were included in the study and categorised as having no chronic condition, one chronic condition or multimorbidities. The primary outcomes were the incidence of preterm birth (PTB), low birth weight (LBW) and small for gestational age (SGA). Adjusted logistic regression was performed to estimate ORs (aORs) and 95% CIs. Results Of the 104 062 fetal records, 86 885 singleton pregnant women were analysed. The median maternal age and body mass index were 31 years and 20.5 kg/m2, respectively. The prevalence of pregnant women with one or more chronic conditions was 40.2%. The prevalence of maternal multimorbidity was 6.3%, and that of PTB, LBW, and SGA were 4.6%, 8.1%, and 7.5%, respectively. Pre-pregnancy underweight women were the most common, observed in 15.6% of multimorbidity cases, followed by domestic violence from intimate partner in 13.0%. Maternal multimorbidity was significantly associated with PTB (aOR 1.50; 95% CI 1.33–1.69), LBW (aOR 1.49; 95% CI 1.35–1.63) and SGA (aOR 1.33; 95% CI 1.20–1.46). Conclusion Maternal multimorbidity was associated with adverse perinatal outcomes, including PTB, LBW and SGA. The risk of adverse perinatal outcomes tends to increase with a rise in the number of chronic maternal conditions. Multimorbidity becomes more prevalent among pregnant women, making our findings important for preconception counselling.
A Study on Centralised and Decentralised Swarm Robotics Architecture for Part Delivery System

Drones are also known as UAVs are originally designed for military purposes. With the technological advances, they can be seen in most of the aspects of life from filming to logistics. The increased use of drones made it sometimes essential to form a collaboration between them to perform the task efficiently in a defined process. This paper investigates the use of a combined centralised and decentralised architecture for the collaborative operation of drones in a parts delivery scenario to enable and expedite the operation of the factories of the future. The centralised and decentralised approaches were extensively researched, with experimentation being undertaken to determine the appropriateness of each approach for this use-case. Decentralised control was utilised to remove the need for excessive communication during the operation of the drones, resulting in smoother operations. Initial results suggested that the decentralised approach is more appropriate for this use-case. The individual functionalities necessary for the implementation of a decentralised architecture were proven and assessed, determining that a combination of multiple individual functionalities, namely VSLAM, dynamic collision avoidance and object tracking, would give an appropriate solution for use in an industrial setting. A final architecture for the parts delivery system was proposed for future work, using a combined centralised and decentralised approach to combat the limitations inherent in each architecture.
Affine Subspace Robust Low-Rank Self-Representation: From Matrix to Tensor

Low-rank self-representation based subspace learning has confirmed its great effectiveness in a broad range of applications. Nevertheless, existing studies mainly focus on exploring the global linear subspace structure, and cannot commendably handle the case where the samples approximately (i.e., the samples contain data errors) lie in several more general affine subspaces. To overcome this drawback, in this paper, we innovatively propose to introduce affine and nonnegative constraints into low-rank self-representation learning. While simple enough, we provide their underlying theoretical insight from a geometric perspective. The union of two constraints geometrically restricts each sample to be expressed as a convex combination of other samples in the same subspace. In this way, when exploring the global affine subspace structure, we can also consider the specific local distribution of data in each subspace. To comprehensively demonstrate the benefits of introducing two constraints, we instantiate three low-rank self-representation methods ranging from single-view low-rank matrix learning to multi-view low-rank tensor learning. We carefully design the solution algorithms to efficiently optimize the proposed three approaches. Extensive experiments are conducted on three typical tasks, including single-view subspace clustering, multi-view subspace clustering, and multi-view semi-supervised classification. The notably superior experimental results powerfully verify the effectiveness of our proposals.
The Josephson Effect in Atomic Contacts

The Josephson effect appears when a weak-link establishes phase coherence between two superconductors. A unifying theory of this effect emerged in the 90's within the framework of mesoscopic physics. Based on two cornerstone concepts, conduction channels and Andreev reflection, it predicts the current-phase relation for the most basic weak-link: a single conduction channel of arbitrary transmission. This thesis illustrates this mesoscopic point of view with experiments on superconducting atomic size contacts. In particular, we have focused on the supercurrent peak around zero voltage, put into evidence the ac Josephson currents in a contact under constant bias voltage (Shapiro resonances and photon assisted multiple Andreev reflections), and performed direct measurements of the current-phase relation.
A structure for laminar flow past a bluff body at high Reynolds number

The steady planar symmetric motion of an incompressible fluid, past a symmetric bluff body fixed in an otherwise uniform stream, is considered for large Reynolds numbers Re. A laminar-flow structure is proposed which consists primarily of (a) the large-scale flow and (b) the smaller, body-scale, flow. Here (a) involves a pair of massive, effectively inviscid, recirculating eddies set up behind the body and bounded by viscous shear layers. Each eddy has small constant vorticity and its length and width both increase linearly with Re, so that the large-scale potential flow outside the eddies is significantly disturbed from the oncoming stream. This reduces the effective free stream acting on (b). The latter has the Kirchhoff property of a parabolic growth in the eddy width downstream; but its eddy vorticity is non-uniform and substantial, contrary to the Kirchhoff and Prandtl–Batchelor models, and secondary separation is possible. The non-uniform vorticity is provoked by the thick return jet, which is forced back along the centreline in (a) from downstream. Buffer zones, e.g. of length ∝ Re½, are required to join (b) fully to (a). The resulting drag coefficient cD is believed to be O(1) generally, and is controlled, along with the eddy length and vorticity, by a combination of the viscous–inviscid flow problems posed in both (a) and (b). A special case of small cD is also covered. The structure seems self-consistent so far, and tends to compare reasonably well with recent numerical solutions of the Navier–Stokes equations at increased Re. An Appendix describes the inviscid parts of (a) for relatively thin eddies.
Characterization of a time-resolved spectral detector for spectral fluorescence lifetime imaging with the parallel 16-channel FastFLIM and the phasor analysis

Multiplexed fluorescence detection has become an indispensable tool in modern biosensing and imaging. Although a variety of excitation/detection optics designs and unmixing schemes have been proposed to achieve multiplexed detection, successful differentiation and quantification of multiple fluorophores at each imaging pixel is still challenging. Recently, fluorescence lifetime imaging microscopy (FLIM) in combination with the phasor plot analysis has shown many advantages over other multiplexed detection methods. Being an intrinsic property of a fluorescent molecule, fluorescence lifetime measured by FLIM is not biased by excitation power or probe abundance and can reveal information on the probe’s microenvironment (ions, pH, oxygen content, electrical signals, index of refractions, etc.). In addition, FLIM is one of the most robust ways of quantifying FRET for studying protein-protein interactions. Moreover, by combining lifetime information with a spectral reading at each pixel, spectral FLIM adds two more dimensions to the spatiotemporal information collected by a conventional confocal setup, resulting in a 6-dimenional (x, y, z, λ, τ, t) dataset. The major challenges to the spectral FLIM method lie in the data acquisition speed and the complexity in post processing and analysis. Here, we present a new time-resolved spectral detector with parallel 16-channel digital frequency domain FLIM (FastFLIM) readouts, for fast spectral FLIM data acquisition. The 16-channel FastFLIM can produce unbiased spectral FLIM data for phasor analysis that unambiguously discriminate and quantitate fluorescent species with unique spectral and lifetime features at each image pixel. Our spectral FastFLIM method offers new opportunities for monitoring multiple dynamic signaling events in live specimens, providing insights into complex biological systems.
Eigendecomposition of Images Correlated on S1, S2, and SO(3) Using Spectral Theory

Eigendecomposition represents one computationally efficient approach for dealing with object detection and pose estimation, as well as other vision-based problems, and has been applied to sets of correlated images for this purpose. The major drawback in using eigendecomposition is the off line computational expense incurred by computing the desired subspace. This off line expense increases drastically as the number of correlated images becomes large (which is the case when doing fully general 3-D pose estimation). Previous work has shown that for data correlated on S(1), Fourier analysis can help reduce the computational burden of this off line expense. This paper presents a method for extending this technique to data correlated on S(2) as well as SO3 by sampling the sphere appropriately. An algorithm is then developed for reducing the off line computational burden associated with computing the eigenspace by exploiting the spectral information of this spherical data set using spherical harmonics and Wigner-D functions. Experimental results are presented to compare the proposed algorithm to the true eigendecomposition, as well as assess the computational savings.