Miracle-dz/UniFAR-FTUs huggingface dataset:
The added value of cognition-targeted exercise versus symptom-targeted exercise for multiple sclerosis fatigue: A randomized controlled pilot trial

Background Fatigue is considered one of the most common symptoms of multiple sclerosis (MS) and lacks a current standardized treatment. Therefore, the aim of this study was to examine the feasibility and effectiveness of a cognition-targeted exercise versus symptom-targeted exercise for MS fatigue. Methods In this Pilot, parallel-group, randomized controlled trial, sixty participants with multiple sclerosis, were randomly assigned to either a Cognition-Targeted Exercise (CTE) (N = 30, mean age 41) or a Symptom-Targeted Exercise (STE) (N = 30, mean age 42). The participants in the experimental group received eight, 50-minute sessions of weekly Cognitive Behavior Therapy (CBT) in addition to a CTE Program; whereas, participants in the control group received eight, 50-minute sessions of weekly CBT in addition to the standardized physiotherapy program (STE Program). Feasibility was assessed through recruitment rate, participant retention, adherence and safety, in addition to clinical outcome measures, including: (1) Modified Fatigue Impact Scale (MFIS), (2) Work and Social Adjustment Scale (WSAS), (3) Hospital Anxiety and Depression Scale (HADS), and Perceived Stress Scale (PSS). All outcome measures were assessed at baseline (pretreatment), following completion of the eight visit intervention protocol, and at 3-months follow-up. Results The recruitment rate was 60% and 93% of participants completed the entire study. The recruited participants complied with 98% of the required visits. No adverse events were recorded. A Generalized Estimation Equation Model revealed a significant difference over time as an interaction term during the post and follow up visit for all clinical outcome measures (p < .001). Conclusion The addition of CTE to CBT exhibited positive and more lasting influence on MS fatigue outcomes compared to Symptom-Targeted Exercise (STE). Feasibility and efficacy data from this pilot study provide support for a full-scale RCT of CTE as an integral component of Multiple Sclerosis fatigue management.
International Journal of Emerging Electric Power Systems Unit Commitment by Structure Based Solution and Efficient Lagrangian Relaxation

Lagrangian relaxation (LR) is one of the most promising approaches for solving power system unit commitment (UC) problems by means of decomposition. There are several technical challenges in developing an effective LR solution. The first is to devise an efficient dual optimization procedure. The second is to have a quick and reliable procedure for removing residual violations in the relaxed constraints. The third is to make the solution algorithm less dependent of problem domain knowledge to improve solution portability. This paper presents a general algorithm that depends only on the formal structure of the problem formulation and assumes no specific knowledge in the problem domain. The proposed algorithm has been tested on real unit commitment problems with as many as 50,000 integer variables and has consistently produced good solutions with very limited number of iterations. In addition to being very efficient, the proposed algorithm is also seen to be robust under parametric perturbations.
Concordance of HIV transmission risk factors elucidated using viral diversification rate and phylogenetic clustering

Abstract Background and objectives Although HIV sequence clustering is routinely used to identify subpopulations experiencing elevated transmission, it over-simplifies transmission dynamics and is sensitive to methodology. Complementarily, viral diversification rates can be used to approximate historical transmission rates. Here, we investigated the concordance and sensitivity of HIV transmission risk factors identified by phylogenetic clustering, viral diversification rate, changes in viral diversification rate and a combined approach. Methodology Viral sequences from 9848 people living with HIV in British Columbia, Canada, sampled between 1996 and February 2019, were used to infer phylogenetic trees, from which clusters were identified and viral diversification rates of each tip were calculated. Factors associated with heightened transmission risk were compared across models of cluster membership, viral diversification rate, changes in diversification rate, and viral diversification rate among clusters. Results Viruses within larger clusters had higher diversification rates and lower changes in diversification rate than those within smaller clusters; however, rates within individual clusters, independent of size, varied widely. Risk factors for both cluster membership and elevated viral diversification rate included being male, young, a resident of health authority E, previous injection drug use, previous hepatitis C virus infection or a high recent viral load. In a sensitivity analysis, models based on cluster membership had wider confidence intervals and lower concordance of significant effects than viral diversification rate for lower sampling rates. Conclusions and implications Viral diversification rate complements phylogenetic clustering, offering a means of evaluating transmission dynamics to guide provision of treatment and prevention services. Lay Summary Understanding HIV transmission dynamics within clusters can help prioritize public health resource allocation. We compared socio-demographic and clinical risk factors associated with phylogenetic cluster membership and viral diversification rate, a historical branching rate, in order to assess their relative concordance and sampling sensitivity.
The association of cardiovascular mortality with a first-degree family member history of different cardiovascular diseases

OBJECTIVE To investigate which history of cardiovascular disease [coronary heart disease (CHD), stroke, or peripheral arterial disease] in a first-degree family member predicts cardiovascular mortality. METHODS We studied a prospective cohort (the Lipid Research Clinics Prevalence Study) from ten primary care centers across North America. The primary outcome was cardiovascular mortality, assessed using Cox survival models. RESULTS There were 8,646 participants (mean age: 47.4 ± 12.1 years, 46% women, 52% of participants with hyperlipidemia) who were followed up for a mean duration of 19.4 ± 4.9 years. There were 1,851 deaths (21%), including 852 cardiovascular deaths. A paternal, maternal or sibling history of premature CHD (before 60 years) was present in 26% of participants, of stroke in 27% of participants, and of peripheral arterial disease in 24% of participants. After adjusting for risk factors (age, sex, systolic blood pressure, diastolic blood pressure, body mass index, smoking, fasting glucose, low-density lipoprotein cholesterol and triglycerides), only a paternal history of premature or any CHD, a maternal history of diabetes mellitus or premature or any CHD, and a sibling history of premature CHD, hypertension, or hyperlipidemia were individually predictive of cardiovascular mortality. After adjusting for risk factors and the mentioned familial factors, only paternal and maternal histories of CHD, especially before 60 years, remained predictive of cardiovascular mortality, with a somewhat higher association for a maternal history [adjusted hazard ratio (aHR) = 1.99, 95% CI: 1.36−2.92,P < 0.001 for maternal history of premature CHD; aHR = 1.52, 95% CI: 1.10−2.10, P = 0.011 for paternal history of premature CHD]. Family history of stroke or peripheral arterial disease did not predict cardiovascular mortality. Parental history of premature CHD predicted cardiovascular mortality independently of baseline age (< 60 years and ≥ 60 years), hypertension, or hyperlipidemia and carried more important prognostic value in men rather than women. CONCLUSIONS In this study, a parental history of CHD, especially before 60 years, best predicted cardiovascular mortality. This finding could help more accurately identify high-risk patients who would benefit from preventive strategies.
Exploring the effects of degraded vision on sensorimotor performance

Purpose Many people experience unilateral degraded vision, usually owing to a developmental or age-related disorder. There are unresolved questions regarding the extent to which such unilateral visual deficits impact on sensorimotor performance; an important issue as sensorimotor limitations can constrain quality of life by restricting ‘activities of daily living’. Examination of the relationship between visual deficit and sensorimotor performance is essential for determining the functional implications of ophthalmic conditions. This study attempts to explore the effect of unilaterally degraded vision on sensorimotor performance. Methods In Experiment 1 we simulated visual deficits in 30 participants using unilateral and bilateral Bangerter filters to explore whether motor performance was affected in water pouring, peg placing, and aiming tasks. Experiment 2 (n = 74) tested the hypothesis that kinematic measures are associated with visuomotor deficits by measuring the impact of small visual sensitivity decrements created by monocular viewing on sensorimotor interactions with targets presented on a planar surface in aiming, tracking and steering tasks. Results In Experiment 1, the filters caused decreased task performance—confirming that unilateral (and bilateral) visual loss has functional implications. In Experiment 2, kinematic measures were affected by monocular viewing in two of three tasks requiring rapid online visual feedback (aiming and steering). Conclusions Unilateral visual loss has a measurable impact on sensorimotor performance. The benefits of binocular vision may be particularly important for some groups (e.g. older adults) where an inability to complete sensorimotor tasks may necessitate assisted living. There is an urgent need to develop rigorous kinematic approaches to the quantification of the functional impact of unilaterally degraded vision and of the benefits associated with treatments for unilateral ophthalmic conditions to enable informed decisions around treatment.
Pairing dynamics and solitonic excitations in collisions of medium-mass, identical nuclei

We present results of collisions of $^{90}$Zr+$^{90}$Zr and $^{96}$Zr+$^{96}$Zr obtained within time-dependent density functional theory (TDDFT) extended to superfluid systems, known as time-dependent superfluid local density approximation (TDSLDA). We discuss qualitatively new features occurring in collisions of two superfluid nuclei at energies in the vicinity of the Coulomb barrier. We show that a \textit{solitonic excitation} -- an abrupt pairing phase distortion -- reported previously [P.~Magierski et al., Phys. Rev. Lett. \textbf{119}, 042501 (2017)], increases the barrier for capture generating effective repulsion between colliding nuclei. Moreover we demonstrate that pairing field leads to qualitatively different dynamics at the Coulomb barrier which manifests itself in a slower evolution of deformation towards a compact shape. Last but not least, we show that magnitude of pairing correlations can be dynamically enhanced after collision. We interpret it as a dynamically induced $U(1)$ symmetry breaking, which leads to large-amplitude oscillations of pairing field and bear similarity to the pairing Higgs mechanism.
Propagation time and nondipole contributions to intraband high-harmonic generation

Applying the semiclassical model, we identify two connected effects in intraband high-harmonic generation (HHG): (1) propagation time from the point of emission at the source to the point of detection, (2) beyond-electric-dipole corrections to the light-matter interaction. These effects inherit information regarding the dispersion and cause specific features in the spectra including even-ordered harmonics in systems with spaceand time-inversion symmetry. They can for certain experimental geometries be measured free of the dipole background.
The Second Earth Trojan 2020 XL5

The Earth Trojans are coorbitals librating around the Lagrange points L 4 or L 5 of the Sun–Earth system. Although many numerical studies suggest that they can maintain their dynamical status and be stable on timescales up to a few tens of thousands of years or even longer, they remain an elusive population. Thus far only one transient member (2010 TK7) has been discovered serendipitously. Here, we present a dynamical study of asteroid 2020 XL5. With our meticulous follow-up astrometric observations of the object, we confirmed that it is a new Earth Trojan. However, its eccentric orbit brings it close encounters with Venus on a frequent basis. Based on our N-body integration, we found that the asteroid was captured into the current Earth Trojan status in the fifteenth century, and then it has a likelihood of 99.5% to leave the L 4 region within the next ∼10 kyr. Therefore, it is most likely that 2020 XL5 is dynamically unstable over this timescale.
Multiply connected wandering domains of meromorphic functions: the pursuit of uniform internal dynamics

Recently, Benini et al showed that, in simply connected wandering domains of entire functions, all pairs of orbits behave in the same way relative to the hyperbolic metric, thus giving us our first insight into the general internal dynamics of such domains. The author proved in a recent paper [G. R. Ferreira. Multiply connected wandering domains of meromorphic functions: internal dynamics andconnectivity. J. Lond. Math. Soc. (2) 106 (2022), 1897–1919] that the same is not true for multiply connected wandering domains, a natural question is how inhomogeneous multiply connected wandering domains can be. We give an answer to this question, in that we show that uniform dynamics inside an open subset of the domain generalizes to the whole wandering domain. As an application of this result, we construct the first example of a meromorphic function with a semi-contracting infinitely connected wandering domain.
Unified Group Fairness on Federated Learning

Federated learning (FL) has emerged as an important machine learning paradigm where a global model is trained based on the private data from distributed clients. However, most of existing FL algorithms cannot guarantee the performance fairness towards different groups because of data distribution shift over groups. In this paper, we formulate the problem of unified group fairness on FL, where the groups can be formed by clients (including existing clients and newly added clients) and sensitive attribute(s). To solve this problem, we first propose a general fair federated framework. Then we construct a unified group fairness risk from the view of federated uncertainty set with theoretical analyses to guarantee unified group fairness on FL. We also develop an efficient federated optimization algorithm named Federated Mirror Descent Ascent with Momentum Acceleration (FMDA-M) with convergence guarantee. We validate the advantages of the FMDA-M algorithm with various kinds of distribution shift settings in experiments, and the results show that FMDA-M algorithm outperforms the existing fair FL algorithms on unified group fairness.
The Hölder continuity of the scaling limit of three-dimensional loop-erased random walk

Let β be the growth exponent of the loop-erased random walk (LERW) in three dimensions. We prove that the scaling limit of 3D LERW is almost surely h -Hölder continuous for all h < 1 /β , but not 1 /β -Hölder continuous.
Sectorised antenna array and measurement methodology for indoor ultra-wideband applications

A new sectorised antenna array (SAA) and measurement methodology are proposed for indoor ultra-wideband (UWB) applications. The proposed SAA comprises of one centre element and six side elements. The one centre element and six side elements are arranged in a semi-spherical antenna array configuration. The measurement system and methodology for the coverage of the SAA are developed. The measured bandwidth of the SAA for voltage standing wave ratio (VSWR) les2 is 37.5%, ranging from 3.06 to 4.47 GHz. The boresight gain is more than 5.2 dBi across the impedance bandwidth. The proposed SAA is able to provide omni-directional pattern with an average gain of 5.2 dBi over the angles (0-360deg). The discone reference antenna is used to measure the coverage of the proposed SAA. The proposed measurement study shows that the proposed SAA offers omni-directional coverage desirable in UWB indoor location and short-range communication systems.
Formation of orbital molecules on a pyrochlore lattice induced by A-O bond covalency

A. Krajewska, 2, 3 A. Yaresko, J. Nuss, A. S. Gibbs, S. Bette, M. Blankenhorn, 2 R. E. Dinnebier, D. P. Sari, 5 I. Watanabe, J. Bertinshaw, H. Gretarsson, 6 K. Ishii, D. Matsumura, T. Tsuji, M. Isobe, B. Keimer, H. Takagi, 2, 9 and T. Takayama 2 Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany Institute for Functional Matter and Quantum Technologies, University of Stuttgart, 70550 Stuttgart, Germany ISIS Neutron and Muon Source, STFC Rutherford Appleton Laboratory, Chilton, Didcot, Oxon OX11 0QX, United Kingdom Graduate School of Engineering and Science, Shibaura Institute of Technology Meson Science Laboratory, Nishina Center for Accelerator-Based Science, RIKEN, 2-1 Hirosawa, Wako 351-0198, Japan Deutsches Elektronen-Synchrotron DESY, Notkestr. 85, D-22607 Hamburg, Germany Synchrotron Radiation Research Center, National Institutes for Quantum Science and Technology, Hyogo 679-5148, Japan Materials Sciences Research Center, Japan Atomic Energy Agency, Hyogo 679-5148, Japan Department of Physics, University of Tokyo, Tokyo 113-0033, Japan
An Application of Quantum Machine Learning on Quantum Correlated Systems: Quantum Convolutional Neural Network as a Classifier for Many-Body Wavefunctions from the Quantum Variational Eigensolver

Machine learning has been applied on a wide variety of models, from classical statistical mechanics to quantum strongly correlated systems for the identification of phase transitions. The recently proposed quantum convolutional neural network (QCNN) provides a new framework for using quantum circuits instead of classical neural networks as the backbone of classification methods. We present here the results from training the QCNN by the wavefunctions of the variational quantum eigensolver for the one-dimensional transverse field Ising model (TFIM). We demonstrate that the QCNN identifies wavefunctions which correspond to the paramagnetic phase and the ferromagnetic phase of the TFIM with good accuracy. The QCNN can be trained to predict the corresponding phase of wavefunctions around the putative quantum critical point, even though it is trained by wavefunctions far away from it. This provides a basis for exploiting the QCNN to identify the quantum critical point.
Robot control for simultaneous impact tasks via QP based reference spreading

— With the aim of further enabling the exploitation of impacts in robotic manipulation, a control framework is presented that directly tackles the challenges posed by tracking control of robotic manipulators that are tasked to perform nominally simultaneous impacts associated to multiple contact points. To this end, we extend the framework of reference spreading, which uses an extended ante-and post-impact reference coherent with a rigid impact map, determined under the assumption of an inelastic simultaneous impact. In practice, the robot will not reside exactly on the reference at the impact moment; as a result a sequence of impacts at the different contact points will typically occur. Our new approach extends reference spreading in this context via the introduction of an additional intermediate control mode. In this mode, a torque command is still based on the ante-impact reference with the goal of reaching the target contact state, but velocity feedback is disabled as this can be potentially harmful due to rapid velocity changes. With an eye towards real implementation, the approach is formulated using a QP control framework and is validated using numerical simulations both on a rigid robot model and on a realistic robot model with ﬂexible joints.
Query-Augmented Active Metric Learning

Abstract In this article, we propose an active metric learning method for clustering with pairwise constraints. The proposed method actively queries the label of informative instance pairs, while estimating underlying metrics by incorporating unlabeled instance pairs, which leads to a more accurate and efficient clustering process. In particular, we augment the queried constraints by generating more pairwise labels to provide additional information in learning a metric to enhance clustering performance. Furthermore, we increase the robustness of metric learning by updating the learned metric sequentially and penalizing the irrelevant features adaptively. In addition, we propose a novel active query strategy that evaluates the information gain of instance pairs more accurately by incorporating the neighborhood structure, which improves clustering efficiency without extra labeling cost. In theory, we provide a tighter error bound of the proposed metric learning method using augmented queries compared with methods using existing constraints only. Furthermore, we also investigate the improvement using the active query strategy instead of random selection. Numerical studies on simulation settings and real datasets indicate that the proposed method is especially advantageous when the signal-to-noise ratio between significant features and irrelevant features is low.
QUDOS: quorum-based cloud-edge distributed DNNs for security enhanced industry 4.0

Distributed machine learning algorithms that employ Deep Neural Networks (DNNs) are widely used in Industry 4.0 applications, such as smart manufacturing. The layers of a DNN can be mapped onto different nodes located in the cloud, edge and shop floor for preserving privacy. The quality of the data that is fed into and processed through the DNN is of utmost importance for critical tasks, such as inspection and quality control. Distributed Data Validation Networks (DDVNs) are used to validate the quality of the data. However, they are prone to single points of failure when an attack occurs. This paper proposes QUDOS, an approach that enhances the security of a distributed DNN that is supported by DDVNs using quorums. The proposed approach allows individual nodes that are corrupted due to an attack to be detected or excluded when the DNN produces an output. Metrics such as corruption factor and success probability of an attack are considered for evaluating the security aspects of DNNs. A simulation study demonstrates that if the number of corrupted nodes is less than a given threshold for decision-making in a quorum, the QUDOS approach always prevents attacks. Furthermore, the study shows that increasing the size of the quorum has a better impact on security than increasing the number of layers. One merit of QUDOS is that it enhances the security of DNNs without requiring any modifications to the algorithm and can therefore be applied to other classes of problems.
A Sphere-Packing Error Exponent for Mismatched Decoding

We derive a sphere-packing error exponent for coded transmission over discrete memoryless channels with a fixed decoding metric. By studying the error probability of the code over an auxiliary channel, we find a lower bound to the probability of error of mismatched decoding. The bound is shown to decay exponentially for coding rates smaller than a new upper bound to the mismatch capacity which is established in this paper. For rates higher than the new upper bound, the error probability is shown to be bounded away from zero. The new upper bound is shown to improve over previous upper bounds to the mismatch capacity.