Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of COVID-19 Pandemic on Palliative Care Services as Perceived by Healthcare Professionals: A Systematic Review

Background: The Covid-19 pandemic stretched healthcare systems' capacity, imposed the reorganization and reprioritization of services under the burden of scarce resources, and altered the traditional way that care was provided. Palliative care, though designed to address complex needs such as relief from severe suffering, difficult decision making and complicated grief was not an exception;its holistic approach of care was seriously challenged due to infection spread restrictions. Objective: To review the impact on palliative care services from healthcare professionals' perspective. Methodology: A systematic review according to the Preferred Reporting Items for Systematic Review and MetaAnalysis (PRISMA) was conducted via PubMed in October 2022. Eligibility criteria included original studies that had used a qualitative, quantitative, or mixed design approach to evaluate the impact on services, delivery of care, and emotional status of palliative healthcare professionals. Results: Out of 2040 initial records, 32 studies were included in the review coming from various countries and settings with representative participation of multidisciplinary palliative care teams' members. Reported impacts concerned organizational aspects and provision of services, altered delivery of care, and implications for the mental health of involved staff. Increased workload, visiting restrictions, use of Personal Protective Equipment, and remote contact were perceived as factors compromising the quality of care provided and impeding palliative healthcare professionals from fulfilling their holistic care role. Moral distress was the most exacerbated emotional impact. Conclusions: Despite the important role that palliative care can play during a health crisis, this was not always adequately reflected on pandemic plans. In the era of the Covid-19, Palliative care entered a phase of change;whether this fact may compromise or accelerate its evolvement depends on how lessons learned will be used in future planning.
Artiﬁcial Intelligence (AI) Augmented Edge and Fog Computing: Trends and Challenges

—In recent years, the landscape of computing paradigms has witnessed a gradual yet remarkable shift from monolithic computing to distributed and decentralized paradigms such as Internet of Things (IoT), Edge, Fog, Cloud, and Server-less. The frontiers of these computing technologies have been boosted by shift from manually encoded algorithms to Artiﬁcial Intelligence (AI)-driven autonomous systems for optimum and reliable management of distributed computing resources. Prior work focuses on improving existing systems using AI across a wide range of domains, such as efﬁcient resource provisioning, application deployment, task placement, and service management. This survey reviews the evolution of data-driven AI-augmented technologies and their impact on computing systems. We demystify new techniques and draw key insights in Edge, Fog and Cloud resource management-related uses of AI methods and also look at how AI can innovate traditional applications for enhanced Quality of Service (QoS) in the presence of a continuum of resources. We present the latest trends and impact areas such as optimizing AI models that are deployed on or for computing systems. We layout a roadmap for future research directions in areas such as resource management for QoS optimization and service reliability. Finally, we discuss blue-sky ideas and envision this work as an anchor point for future research on AI-driven computing systems.
Charged-current Quasi-elastic-like neutrino interactions at the T2K experiment

T2K is a long-baseline neutrino oscillation experiment based in Japan. The experiment has already measured the appearance of ⌫e in a ⌫μ beam, and is hoping to measure the appearance of ⌫¯e in a ⌫¯μ beam, which would open the possibility of observing CP-violation in the lepton sector. The charged current quasi-elastic (CCQE) interaction (vμ + n -> μ− + p) is of great importance to T2K as it is expected to make up over 80% of the interactions at the oscillation peak (600 MeV). In recent years it has become clear that the most common model describing CCQE interactions on nuclei, the Relativistic Fermi Gas (RFG) model, is not able to describe low energy data on nuclear targets. An alternative model, the Spectral Function (SF) model, was implemented in the NEUT interaction generator. Relevant uncertainties in this model are identified and evaluated. The charged current quasi-elastic-like cross section is then measured using the T2K near detector, ND280, as a function of muon momentum and angle. This data is then critically compared to the predictions from two implementations of the RFG model, and also to the newly implemented SF model. The total integrated cross section is found to be (4.06 ± 0.757) x 10−39 cm2 nucleon−1. This value is currently in agreement with all three predictions.
On the Parameter Insensitivity of GMRES-Accelerated ADMM for Quadratic Objectives

In this paper, we show, using theoretical bounds and empirical results, that the convergence of the alternating direction method-of-multipliers (ADMM) for quadratic objectives is made remarkably insensitive to the parameter choice when it is accelerated using the generalized minimum residual method (GMRES). We prove that ADMM-GMRES can consistently converge, irrespective of the exact parameter choice, to an $\epsilon$-accurate solution of a $\kappa$-conditioned problem in $O(\kappa^{2/3}\log\epsilon^{-1})$ iterations. The accelerated method is applied to randomly generated problems, as well as the Newton direction computation for the interior-point solution of semidefinite programs in the SDPLIB test suite. The empirical results confirm this parameter insensitivity, and suggest a slightly improved iteration bound of $O(\sqrt{\kappa}\log\epsilon^{-1})$.
Friction induced vibrations in railway transportation

Controlling friction at the wheel-rail interface is indispensable for extending track life, minimising wheel-flange wear, improving fuel efficiency, reducing noise and lateral forces. A particular implementation of friction modifier system consists of a stick-tube assembly, attached through a bracket which is suspended from the railway bogie frame. Inside the tube, a set of interlocking solid sticks resides with one end pressed against the tread or flange of the wheel, and the other end against a constant force tape spring. Rubbing action at the stick-wheel interface and the action of the spring results in a gradual transfer of friction modifier film to the wheel and thence to the rail through the wheel-rail contact. This results in effective friction management between the wheel and the rail. Friction modifier systems can experience unstable friction-induced vibrations due to a complex set of in situ contact conditions. Stability prediction is important for efficient functioning of friction control systems. This dissertation contributes a stability analysis procedure in frequency domain based on Frequency Response Functions (FRFs) of the wheel and the applicator-bracket subsystems. The stability analysis yields stability maps delineating stable and unstable regions of operation in the design parameter space defined by speed of train, angle of applicator, and friction coefficient. Stability characteristics of three bracket designs are compared using experiments and finite element models. Results are summarised in the form of stability diagrams indicating the operating conditions that will lead to unstable vibrations. This methodology can easily incorporate design changes to the bracket and/or applicator, thus facilitating a rapid comparison of different designs for their stability characteristics even before they are built.
Ordering and Superconductivity: Scanning Tunneling Spectroscopy of Unconventional Superconductors

In this thesis I present scanning tunneling microscopy (STM) studies that probe the interplay between ordering phenomena and superconductivity in two classes of materials: heavy fermions (CeCoIn5 and URu2Si2) and cuprates (Bi2Sr2CaCu2O8+δ (Bi2212)). In CeCoIn5, these measurements detect the emergence of heavy quasiparticles with lowering of temperature, as well as their composite nature. Interference of these quasiparticles allow their energy-momentum structure to be resolved as a function of temperature. Analysis of the tunneling spectra reveal signatures of energytemperature scaling associated with a quantum critical point. In URu2Si2, spatially resolved spectroscopy is used to examine the electronic states that emerge from the uranium f -states. As the temperature is lowered, the spectrum develops into a Fano resonance which characterizes the onset of heavy-fermion coherence below≈ 120 K. At T = 17.5 K, URu2Si2 is known to undergo a second-order phase transition into a phase with a hidden order parameter. Tunneling spectroscopy identifies a bias-asymmetric energy gap with a mean-field temperature dependence that develops in the hidden order state. In Bi-2212, combined STM and resonant elastic x-ray scattering (REXS) measurements are used to establish the formation of charge ordering. Depending on the hole concentration, the ordering in Bi-2212 occurs with the same period as those found in Y-based or La-based cuprates. This charge ordering also displays the analogous competition with superconductivity found in the other compounds. Together these results indicate the universality of charge organization competing with superconductivity across different families of cuprates. Finally, investigations of the influence of anisotropic tip structures on STM conductance maps establish, with a model calculation, the presence of a tunneling interference effect within an STM junction that induces an artificial nematic signal. This effect is experimentally confirmed on different correlated electron systems, including Bi-2212, and is shown to be a sensitive probe of changes in the band structure of the sample. iii
Interpolation of positive operators on variable Lebesgue spaces

We prove an interpolation theorem for integral operators with positive kernel on the variable Lebesgue spaces. As an application we show that the set of exponents for spaces on which the Hardy-Littlewood maximal operator is bounded is convex. Mathematics subject classification (2010): 42B20, 42B25.
An Introduction to Rasch Measurement

JAM Press is pleased to announce that the new book, Introduction to Rasch Measurement: Theory, Models, and Applications, is now available. The book is available in soft cover ($47, ISBN 0-9755351-1-0) and hard cover ($59, ISBN 0-9755351-0-2). Postage and handling are additional. Information on ordering the book (689 pages) is found on the reverse of this announcement and also available at the website for the Journal of Applied Measurement, www.jampress. org. Please go to the JAM Press Books page on that website and scroll down to the new books section. A PDF of the JAM Press order form is also available for printing on that web page. Introduction to Rasch Measurement: Theory, Models, and Applications contains 24 chapters, written by the leading experts in Rasch measurement, which discuss all aspects of family of Rasch measurement models. A listing of the chapters can be found below.
Image thresholding segmentation based on two-dimensional minimum Tsallis-cross entropy

Image thresholding segmentation method based on two-dimensional minimum Tsallis-cross entropy is proposed by utilizing the non-extensive property of Tsallis entropy in the paper. Firstly, the two-dimensional Tsallis-cross entropy is given, then the particle swarm optimization is used to search the best two-dimensional threshold vector by minimizing the two-dimensional Tsallis-cross entropy. The proposed method not only considers the spatial information of pixels, but also the interaction between the object and the background. Its segmentation performance is superior to thresholding methods using Shannon entropy and minimum one-dimensional Tsallis-cross entropy. Experimental results show that the proposed method can give good segmentation results with less computation time.
Pair Matching: When bandits meet stochastic block model

The pair-matching problem appears in many applications where one wants to discover good matches between pairs of individuals. Formally, the set of individuals is represented by the nodes of a graph where the edges, unobserved at first, represent the good matches. The algorithm queries pairs of nodes and observes the presence/absence of edges. Its goal is to discover as many edges as possible with a fixed budget of queries. Pair-matching is a particular instance of multi-armed bandit problem in which the arms are pairs of individuals and the rewards are edges linking these pairs. This bandit problem is non-standard though, as each arm can only be played once. Given this last constraint, sublinear regret can be expected only if the graph presents some underlying structure. This paper shows that sublinear regret is achievable in the case where the graph is generated according to a Stochastic Block Model (SBM) with two communities. Optimal regret bounds are computed for this pair-matching problem. They exhibit a phase transition related to the Kesten-Stigund threshold for community detection in SBM. To avoid undesirable features of optimal solutions, the pair-matching problem is also considered in the case where each node is constrained to be sampled less than a given amount of times. We show how this constraint deteriorates optimal regret rates. The paper is concluded by a conjecture regarding the optimal regret when the number of communities is larger than $2$. Contrary to the two communities case, we believe that a statistical-computational gap would appear in this problem.
On the number of cells defined by a family of polynomials on a variety

Let R be a real closed field and a variety of real dimension k ′ which is the zero set of a polynomial Q ∈ R [ X 1 ,…, X k ] of degree at most d . Given a family of s polynomials = { P 1 ,…, P s }⊂ R [ X 1 ,…, X k ] where each polynomial in has degree at most d , we prove that the number of cells defined by over is ( O ( d )) k Note that the combinatorial part of the bound depends on the dimension of the variety rather than on the dimension of the ambient space.
Topics in ordinal logistic regression and its applications

Topics in Ordinal Logistic Regression and Its Applications. (August 2004) Hyun Sun Kim, B.S., Dongguk University, Seoul, Korea; M.S., Dongguk University, Seoul, Korea Chair of Advisory Committee: Dr. Suojin Wang Sample size calculation methods for ordinal logistic regression are proposed to test statistical hypotheses. The author was motivated to do this work by the need for statistical analysis of the red imported fire ants data. The proposed methods use the concept of approximation by the moment-generating function. Some correction methods are also suggested. When a prior data set is available, an empirical method is explored. Application of the proposed methodology to the fire ant mating flight data is demonstrated. The proposed sample size and power calculation methods are applied in the hypothesis testing problems. Simulation studies are also conducted to illustrate their performance and to compare them with existing methods.
Estimation of foreseeable and unforeseeable risks in motor insurance

This project works with the risk model developed by Li et al. (2015) and quests modelling, estimating and pricing insurance for risks brought in by innovative technologies, or other emerging or latent risks. The model considers two different risk streams that arise together, however not clearly separated or observed. Specifically, we consider a risk surplus process where premia are adjusted according to past claim frequencies, like in a Bonus-Malus (BM) system, when we consider a classical or historical risk stream and an unforeseeable risk one. These are unknown risks which can be of high uncertainty that, when pricing insurance (ratemaking and experience rating), suggest a sensitive premium adjustment strategy. It is not clear for the actuary to observe which claim comes from one or the other stream. When modelling such risks it is crucial to estimate the behaviour of such claims, occurrence and their severity. Premium calculation must fairly reflect the nature of these two kinds of risk streams. We start proposing a model, separating claim counts and severities, then propose a premium calculation method, and finally a parameter estimation procedure. In the modelling we assume a Bayesian approach as used in credibility theory, a credibility approach for premium calculation and the use of the Expectation-Maximization (EM) algorithm in the estimation procedure.
Optimal adaptive control with ΘLQG

This thesis introduces ΘLQG, the hyper extension of the Linear Quadratic Gaussian Regulator, for solving general purpose (locally optimal) nonlinear adaptive control on multiple-input multiple-output systems. This approach can be used to stabilize an under-actuated under-observed nonlinear dynamic system with noisy measurements while simultaneously identifying system parameters. It requires a parameterized dynamic model with operation about equilibrium points. Its general construction can also be used in disturbance rejection, gain scheduling and reference tracking. Specific case examples are introduced.
Analysis and Prediction of Wordle Dataset Based on ARIMA and Pearson's Correlation Coefficient

In this paper, a time series analysis was performed to ensure the parameters p, d, and q. Finally, the ARIMA (1,1,0) model was chosen to create a prediction interval for the number of outcomes to be reported in the future. The results of the precision test showed good confidence in the prediction with a goodness-of-fit of 98.2%. the prediction interval for March 1, 2023 was [10103,10523]. In addition, this paper used Pearson's correlation coefficient and chi-square test to verify the correlation between each attribute of the word and the percentage of scores in the hard model. In summary, this paper found that the attributes of words definitely affect the percentage of scores, and these scores are mainly the initials and lexicality of words.
Subclinical psychopathy and styles of intimate relationships

Different studies show the relationship between subclinical psychopathy and the strategies of distancing and avoidance that prevent the formation of stable and lasting emotional bonds in the couple. The study analyses subclinical psychopathy and the relationship style/love type in a sample of 1289 university students to determine its frequency, as well as the relationship between psychopathy and the relationship style/love type. The Integrated/Subclinical Psychopathy Questionnaire (CUPIS) and the Triangle of Love Scale (TLS) were used. It was found that a significant percentage of these students presents features that characterise subclinical psychopathy. In addition, it was found that the higher the score in psychopathy, the lower the intimacy, passion and commitment in their relationships. Furthermore, subclinical psychopathy was found to be a greater predictor of a lack of intimacy and commitment in intimate relationships between couples. In conclusion, we highlight that, in subclinical psychopathy, there are low patterns of intimacy and commitment in relationships; so these are unlikely to remain stable over time.
Super-resolution reconstruction of high dynamic range images in a perceptually uniform domain

Abstract. Super resolution is a signal processing method that utilizes information from multiple degraded images of the same scene in order to reconstruct an image with enhanced spatial resolution. The method is typically employed on similarly exposed pixel valued images, but it can be extended to differently exposed images with a high combined dynamic range. We propose a novel formulation of the joint super-resolution, high dynamic range image reconstruction problem, using an image domain in which the residual function of the inverse problem relates to the perception of the human visual system. Simulated results are presented, including a comparison with a conventional method, demonstrating that the proposed approach avoids some severe reconstruction artifacts.
Multi-frame Image Super-resolution by Total-variation Regularization

Multi-frame image Super-resolution (SR) reconstruction needs to deal with the recovery of a single high-resolution image from a set of low quality images. Recently, there has been a great deal of work developing multi-frame SR algorithms. In this study, we proposed an efficient SR regularization algorithm. This approach combines the ideas of bilateral filtering and the beyond-digital-total-variation model. A new regularization norm was presented, termed as locally digital bilateral-total-variation, to keep edges and more details. Experimental results were introduced to illustrate the effectiveness of the proposed algorithm. Performance analysis shows that our method is superior to similar existing methods, the peak signal-to-noise ratio improved about 0.1-1.0 dB.
Effects of an explicit rime-based phonics method on the phonological awareness outcomes of Ethiopian EFL children

Abstract The present study aimed to assess whether a training-based intervention using an explicit rime-based phonics method improves the phonological awareness outcomes of EFL children in Ethiopia. The participants were two sections of 3rd grade children (N = 70) from two public primary schools in Hawassa, Ethiopia. A quasi-experimental research design was used in which a section of the children (N = 35) were randomly assigned to the experimental group and the other section of the children (N = 35) to the control group. The experimental group was explicitly exposed to a training-based beginning reading intervention using an explicit rime-based phonics method. The control group stayed in their regular classroom with their regular beginning reading lessons with the conventional way. The phonological awareness test (PAT) was used to measure phonological awareness outcomes in the two groups before and after the intervention. The findings showed that the experimental group achieved significant improvement on the phonological awareness at post- test and that the magnitude of the intervention’s effect was very large for all sub-subtests and the total phonological awareness. The findings also indicated that brief and direct beginning reading instruction with an explicit rime-based phonics method helps children in a non-English language context with a first language (L1) significantly different from English to rapidly improve their phonological awareness performances. The findings further suggested that just knowledge of letters alone is not a sufficient condition for phonological awareness to develop.