Miracle-dz/UniFAR-FTUs huggingface dataset:
Barriers and facilitators to cross-sector workforce competency assessment in the care of older people residing in care homes

Background In recent years, transformation in care delivery towards cross-sector models has occurred with the aim of providing safe, efficient care for older people with complex needs, including those living in care homes. Effective workforce competency development and assessment across sectors is integral to these models. However, there is much evidence to suggest a distinct lack of cross-sector alignment with regard to competency development and assessment, which could lead to variations in practice and affect outcomes for older people. Methods This qualitative study explored the barriers and facilitators to cross-sector workforce competency assessment in the care of older people residing in care homes. Twenty nine staff with responsibility for staff learning and development participated. Data were analysed using Braun and Clarkes (2006) six phase thematic analysis approach. Findings Findings indicate that a significant challenge to the development of a competent workforce is evidencing competency, due to difficulties in finding appropriate assessors and inconsistencies in the assessment process. Findings also indicate potential solutions including: a system-wide, standardised framework and strategy for assessment of competence; policy for the sign-off of competencies that is recognised across organisational boundaries; and adopting practice-based approaches to competence development and assessment.
Reduction of brooding and more general depressive symptoms after fMRI neurofeedback targeting a melancholic functional-connectivity biomarker

Depressive disorders contribute heavily to global disease burden; This is possibly because patients are usually treated homogeneously, despite having heterogeneous symptoms with differing underlying neural mechanisms. On the contrary, treatment that directly influences the neural circuit relevant to an individual patient's subset of symptoms might more precisely and thus effectively aid in the alleviation of their specific symptoms. We tested this hypothesis, using fMRI functional connectivity neurofeedback to target a neural biomarker that objectively relates to a specific subset (melancholic) of depressive symptoms and that is generalizable across independent cohorts of patients. The targeted biomarker was the functional connectivity between the left dorsolateral prefrontal cortex and left precuneus, which has been shown in a data-driven manner to be less anticorrelated in patients with melancholic depression than in healthy controls. We found that the more a participant normalized this biomarker, the more related (brooding and more general depressive), but not unrelated (trait anxiety), symptoms were reduced. Thus, one-to-one correspondence between a normalized neural network and decreased depressive symptoms was demonstrated. These results were found in two experiments that took place several years apart by different experimenters, indicating their reproducibility. Indicative of their potential clinical utility, effects remained one-two months later.
Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data

Designing public health responses to outbreaks requires close monitoring of population-level health indicators in real-time. Thus an accurate estimation of the epidemic curve is critical. We propose an approach to reconstruct epidemic curves in near real time. We apply this approach to characterize the early SARS-CoV-2 outbreak in two Spanish regions between the months of March and April 2020. We address two data collection problems that affected the reliability of the available real-time epidemiological data, namely, the frequent missing information documenting when a patient first experienced symptoms, and the frequent retrospective revision of historical information (including right censoring). This is done by using a novel back-calculating procedure based on imputing patients dates of symptom onset from reported cases, according to a dynamically-estimated backward reporting delay conditional distribution, and adjusting for right censoring using an existing package, NobBS, to estimate in real time (nowcast) cases by date of symptom onset. This process allows us to obtain an approximation of the time-varying reproduction number (Rt) in real-time. At each step, we evaluate how different assumptions affect the recovered epidemiological events and compare the proposed approach to the alternative procedure of merely using curves of case counts, by report day, to characterize the time-evolution of the outbreak. Finally, we assess how these real-time estimates compare with subsequently documented epidemiological information that is considered more reliable and complete that became available weeks to months later in time. Our approach may help improve accuracy, quantify uncertainty, and evaluate frequently unstated assumptions when recovering the epidemic curves from limited data obtained from public health surveillance systems in other locations.
Convection heat transfer coefficients for axial flow gas quenching of a cylinder

During gas quenching of steel the local heat transfer rate is of major importance for the final hardness, its uniformity, and the distortion of the parts. The local heat transfer coefficient distributions on a two-diameter long cylinder (150 mm in diameter) was measured in axial flows of air, at Reynolds numbers ( ) of 8.9 to 6.17 (9 to 63 m/s). The measurements were performed at different upstream air flow conditions, which were set by varying the flow turbulence level ( ) using a turbulence generating grid, and by using flow modification inserts in front of the cylinder. The heat transfer coefficients were evaluated from the measured surface temperatures using a thermochromic liquid crystal (TLC) technique. The TLC was applied onto an electrically heated thin foil, which allowed for full surface heat transfer measurements including the cylinder ends. The turbulence-generating grid caused an increase in the heat transfer coefficient up to 22 % and when a flow modification insert was used the nonuniformity was reduced up to 35%. The heat transfer coefficient evaluated as a Nusselt number ( ) was found to increase with , and relations between and are presented. IN QUENCHING, the product hardness, uniformity of mechanical properties, and shape distortion depend on the rate and uniformity of the cooling. Gas quenching requires high gas speeds and pressures (typical values are 10 m/s and 10 bar, but they vary widely depending on the application), i.e. turbulent flows with Reynolds numbers typically between a few hundred thousand to a few million. The flows are thus highly turbulent, with separations and reattachments, which create significant convection heat transfer coefficient nonuniformities over the body surface. These coefficients must be controlled in magnitude and uniformity to obtain optimal quench products. A cylinder is a classical shape of interest to quenching, but despite a fair number of experimental studies that provide heat transfer coefficient distributions for single cylinders (cf. Lowery 1975 [1] , Achenbach 1975 [2], Zukauskas 1985 [3], Wiberg 2000 [4]) and multiple ones (cf. Achenbach 1989 [5]) in cross flows, little information is available for cylinders in axial flow, and none were measured for 5.5 . Specifically, heat transfer measurements at constant surface heat flux, were performed by Ota and Kon 1977 [6], for 2.52
Personalized and dynamic antibiograms-an exploration in seven infectious syndromes

To prevent antimicrobial resistance and inform better, antibiograms should distinguish different biomedical situations. It is also desirable that new antibiograms provide in vivo, temporal, and patient-specific immunological information. Here, the informative ability of a pattern recognition-based method was explored with data collected from patients that experienced seven infectious syndromes (pneumonia, endocarditis, tuberculosis, syphilis, as well as skin and soft tissue, intra-abdominal, and/or urinary tract infections associated with meningitis). Interactions among seven dimensions (7D) were investigated: (i) space, (ii) time, (iii) temporal data directionality, (iv) immunological multicellularity, (v) antibiotics, (vi) immunomodulation, and (vii) personalized data. Omissions and ambiguity (confounding different biological situations) occurred when static metrics were used in isolation, such as leukocyte percentages. In contrast, hidden information was uncovered when complexity and dynamics were assessed. The 7D approach grouped together observations that displayed similar immune profiles and identified antibiotics that modulated specific leukocytes. For instance, in tuberculosis, blood monocytes were modulated by isoniazid-related antimicrobials. In spite of the diverse syndromes analyzed, this proof-of-concept discriminated. It is suggested that the simultaneously exploration of numerous dimensions associated with complexity may be biologically interpretable, prevent ambiguity, promote research, expand machine learning-oriented methods, and support personalized medicine.
Quasi maximum likelihood , indirect inference and bias-corrected pooled least squares estimators for dynamic panels with short T ∗

This paper proposes new estimators for panel autoregressive (PAR) models with short time dimensions (T ) and large cross sections. These estimators are based on the cross-sectional regression model using the first time series observations as a regressor and the last as a dependent variable. The regressors and errors of this regression model are correlated. The first estimator is the quasi maximum likelihood estimator (QMLE). The second estimator is the indirect inference estimator (IIE) that attempts to remove the finite-sample bias of the QMLE. The third estimator is the bias-corrected pooled least squares estimator (BCPLSE) that eliminates the asymptotic bias of the pooled least squares estimator by using the QMLE. The QMLE, IIE and BCPLSE are extended to the PAR model with endogenous regressors. The QMLE, IIE and BCPLSE provide consistent estimates of the PAR coeffi cients for stationary, unit root and explosive PAR models, estimate the coeffi cients of endogenous regressors consistently and can be computed as long as T ≥ 2. Their finite sample properties are compared with those of some other estimators for the PAR model of order 1. The estimators of this paper are shown to perform quite well in finite samples.
Supported VPO Catalysts for Selective Oxidation of Butane. II. Characterization of VPO/SiO2 Catalysts

SiO2-supported VPO catalysts with different P/V ratios were prepared, used in selective oxidation of butane, and characterized by X-ray diffraction (XRD), laser Raman spectroscopy (LRS), near-edge X-ray absorption spectroscopy (XANES), and 31P magic angle spinning NMR. Similar to the SiO2-supported catalysts of lower metal loadings studied previously, the maleic anhydride selectivity increased with increasing P/V ratio, to greater than 50 mol % for P/V = 2. XRD and LRS detected predominantly α1-VOPO4 or a phase that is structurally very similar for both P/V = 1 and P/V = 2 samples. However, within the detection limit of the XANES experiment, the P/V = 1 catalyst contained mostly V5+ under reaction conditions, whereas the P/V = 2 catalyst contained 100% V4+.
Analysis of the optical properties of poly(3‐octylthiophene) partially dedoped

In this work, poly(3-octylthiophene) (P3OT) films were synthesized electrochemically in non-aqueous media through the oxidation of the monomer, (3-octylthiophene), using a standard three-electrode cell in acetonitrile with 0.05 mol L S1 LiClO4 or 0.05 mol L S1 Et4NBF4. The polymeric films were deposited on fluorine tin oxide (FTO). The partial dedoping was obtained in NH4OH solution, providing a good chemical stability of the formed material. The films obtained through this method have been characterized by Fourier-transform infrared spectroscopy (FT-IR), electron paramagnetic resonance (EPR), UV–Vis absorption, and photoluminescence (PL) spectroscopy. The FT-IR and EPR spectra together gave the results that led to characterization of two structures (pristine and non-pristine forms of thiophene rings) while forming the P3OT polymer chain. These results were associated with the stabilization of pristine chains and mixed chains (non-pristine structures) in the polymeric film. Their bands in the PL spectra are wide and asymmetric and their adjustments by Gaussian functions was necessary; this was the main indication that there are two distinct contributions to the emission spectra. These two contributions are attributed to the emission by mixed chains (Gaussian centered at higher energy) and by pristine chains (Gaussian of lower energy) present in the formed polymeric material. Copyright 2010 John Wiley & Sons, Ltd.
Differential Privacy for Industrial Internet of Things: Opportunities, Applications, and Challenges

The development of Internet of Things (IoT) brings new changes to various fields. Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more applications of IIoT, privacy protection issues are emerging. Especially, some common algorithms in IIoT technology, such as deep models, strongly rely on data collection, which leads to the risk of privacy disclosure. Recently, differential privacy has been used to protect user-terminal privacy in IIoT, so it is necessary to make in-depth research on this topic. In this article, we conduct a comprehensive survey on the opportunities, applications, and challenges of differential privacy in IIoT. We first review related papers on IIoT and privacy protection, respectively. Then, we focus on the metrics of industrial data privacy, and analyze the contradiction between data utilization for deep models and individual privacy protection. Several valuable problems are summarized and new research ideas are put forward. In conclusion, this survey is dedicated to complete comprehensive summary and lay foundation for the follow-up research on industrial differential privacy.
Biometric Verification Secure Against Malicious Adversaries

Biometric verification has been widely deployed in current authentication solutions as it proves the physical presence of individuals. To protect the sensitive biometric data in such systems, several solutions have been developed that provide security against honest-but-curious (semi-honest) attackers. However, in practice attackers typically do not act honestly and multiple studies have shown drastic biometric information leakage in such honest-but-curious solutions when considering dishonest, malicious attackers. In this paper, we propose a provably secure biometric verification protocol to withstand malicious attackers and prevent biometric data from any sort of leakage. The proposed protocol is based on a homomorphically encrypted log likelihood-ratio-based (HELR) classifier that supports any biometric modality (e.g. face, fingerprint, dynamic signature, etc.) encoded as a fixed-length real-valued feature vector and performs an accurate and fast biometric recognition. Our protocol, that is secure against malicious adversaries, is designed from a protocol secure against semi-honest adversaries enhanced by zero-knowledge proofs. We evaluate both protocols for various security levels and record a sub-second speed (between $0.37$s and $0.88$s) for the protocol against semi-honest adversaries and between $0.95$s and $2.50$s for the protocol secure against malicious adversaries.
Enhancing spin-photon coupling with a micromagnet

Hybrid quantum systems involving solid-state spins and superconducting microwave cavities play a crucial role in quantum science and technology, but improving the spin-photon coupling at the single quantum level remains challenging in such systems. Here, we propose a simple technique to strongly couple a single solid-state spin to the microwave photons in a superconducting coplanar waveguide (CPW) cavity via a magnetic microsphere. We show that, strong coupling at the single spin level can be realized by virtual magnonic excitations of a nearby micromagnet. The spin-photon coupling strength can be enhanced up to typically four orders of magnitude larger than that without the use of the micromagnet. This work can find applications in quantum information processing with strongly coupled solid-state spin-photonic systems.
A convolutional-neural-network estimator of CMB constraints on dark matter energy injection

We show that the impact of energy injection by dark matter annihilation on the cosmic microwave background power spectra can be apprehended via a residual likelihood map. By resorting to convolutional neural networks that can fully discover the underlying pattern of the map, we propose a novel way of constraining dark matter annihilation based on the Planck 2018 data. We demonstrate that the trained neural network can efficiently predict the likelihood and accurately place bounds on the annihilation cross-section in a model-independent fashion. The machinery will be made public in the near future.
I Beg to Differ: A study of constructive disagreement in online conversations

Disagreements are pervasive in human communication. In this paper we investigate what makes disagreement constructive. To this end, we construct WikiDisputes, a corpus of 7425 Wikipedia Talk page conversations that contain content disputes, and define the task of predicting whether disagreements will be escalated to mediation by a moderator. We evaluate feature-based models with linguistic markers from previous work, and demonstrate that their performance is improved by using features that capture changes in linguistic markers throughout the conversations, as opposed to averaged values. We develop a variety of neural models and show that taking into account the structure of the conversation improves predictive accuracy, exceeding that of feature-based models. We assess our best neural model in terms of both predictive accuracy and uncertainty by evaluating its behaviour when it is only exposed to the beginning of the conversation, finding that model accuracy improves and uncertainty reduces as models are exposed to more information.
Signatures of quenching in dwarf galaxies in local galaxy clusters

Context. The transformation of late-type galaxies has been suggested as the origin of early-type dwarf galaxies (typically M⋆ ≤ 109 M⊙) in galaxy clusters. Based on deep images, Venhola and colleagues analysed correlations between colour and surface brightness for galaxies in the Fornax cluster binned by luminosity or stellar mass. In the bins with M⋆ < 108 M⊙, the authors identified a correlation of redness with fainter surface brightness and interpreted it as a consequence of the quenching of star formation by ram pressure stripping in the dwarf galaxies. Aims. This study carries out a similar analysis for the Virgo cluster. The analysis for both clusters is then used to compare the Virgo and Fornax clusters, for which the ram pressure is expected to have different strengths. The purpose of this is to scrutinise the ram pressure interpretation from the other study and search for differences between the clusters that reflect the different ram pressure efficiencies, which would either support or weaken this interpretation. Ultimately, this could help weigh the importance of ram pressure stripping relative to other transformative processes in the shaping of the dominant early-type dwarf galaxy population. Methods. We extend the analysis of colour versus surface brightness binned by stellar mass to higher masses and a wider range of optical colours. The results, in particular at low stellar mass, are compared to predictions of stellar evolution models. Benefitting from larger sample sizes, we also analyse late- and early-type galaxies separately. This analysis is carried out for the Virgo and Fornax clusters, and the colour versus surface brightness relation, as well as other properties of the two clusters’ galaxy populations, are compared. Results. While the colour–surface brightness diagrams are remarkably similar for the two clusters, only the low-mass late-type galaxies are found to have slopes consistent with a fading and reddening following the quenching of star formation. For the early-type galaxies, there are no (or only weak) correlations between colour and surface brightness in all mass bins. Early- and late-type galaxies in both clusters have comparable sizes below a stellar mass of M⋆ ≲ 108 M⊙. The colour and size scaling relations are very similar for the Virgo and Fornax clusters. However, Virgo features a lower fraction of early-type or red galaxies despite its higher mass. Conclusions. The similarity of early-type dwarfs and low-mass late types in size at the masses M⋆ ≲ 108 M⊙ as well as the overall consistency of the colour–surface brightness correlation with fading stellar populations support a scenario of transformation via the quenching of star formation, for example by gas removal. However, the lack of this imprint of an ageing stellar population on the early-type dwarfs themselves calls for some additional explanation. Finally, the Virgo cluster is an atypical cluster with a comparably low fraction of quiescent early-type galaxies at all galaxy masses despite its large cluster mass.
Population-Based Methods: Particle Swarm Optimization - Development of a General-Purpose Optimizer and Applications

This thesis is concerned with continuous, static, and single-objective optimization problems subject to inequality constraints. Nevertheless, some methods to handle other kinds of problems are briefly reviewed. The particle swarm optimization paradigm was inspired by previous simulations of the cooperative behaviour observed in social beings. It is a bottom-up, randomly weighted, population-based method whose ability to optimize emerges from local, individual-to-individual interactions. As opposed to traditional methods, it can deal with different problems with few or no adaptation due to the fact that it does profit from problem-specific features of the problem at issue but performs a parallel, cooperative exploration of the search-space by means of a population of individuals. The main goal of this thesis consists of developing an optimizer that can perform reasonably well on most problems. Hence, the influence of the settings of the algorithm's parameters on the behaviour of the system is studied, some general-purpose settings are sought, and some variations to the canonical version are proposed aiming to turn it into a more general-purpose optimizer. Since no termination condition is included in the canonical version, this thesis is also concerned with the design of some stopping criteria which allow the iterative search to be terminated if further significant improvement is unlikely, or if a certain number of time-steps are reached. In addition, some constraint-handling techniques are incorporated into the canonical algorithm to handle inequality constraints. Finally, the capabilities of the proposed general-purpose optimizers are illustrated by optimizing a few benchmark problems.