Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Telerehabilitation on Physical Fitness and Depression/Anxiety in Post-COVID-19 Patients: A Randomized Controlled Trial

Aim: The aim of this research was to evaluate the impact of a telerehabilitation program on physical fitness, muscle strength, and levels of depression and anxiety in post-COVID-19 patients. Methods: Thirty-two individuals recovered from COVID-19 (48.20±12.82 years) were allocated into either a telerehabilitation (TG n=16) or control (CG n=16) group. Physical fitness, handgrip strength, depression and anxiety levels were assessed before and after an 8-week intervention. Results: There was a significant improvement in muscle strength in both groups. Physical fitness significantly increased compared to the CG at the end of the intervention. Levels of anxiety and depression significantly decreased after the intervention when compared to the CG. Conclusion: Eight weeks of functional telerehabilitation training is a viable and efficient way to rehabilitate patients affected by COVID-19, as it improved physical conditioning and mental health.
Training of Support Vector Machines by the Steepest Ascent Method

Since the training of support vector machines needs to solve the dual problem with the number of variables equal to the number of training data, the training becomes slow when the number of training data is large. To speed up training the Sequential Minimal Optimization (SMO) technique has been proposed, in which two data are optimized simultaneously. In this paper, we propose to extend SMO so that more than two data are optimized simultaneously. Namely, we select a working set including variables, solve the equality constraint for one variable included in the working set, and substitute it into the objective function. Then we solve the subproblem related to the working set by calculating the inverse of the Hessian matrix. We evaluate our method for the five benchmark data sets and show the speed-up of training over SMO.
Determination of Ionosphere Gradient in Short Baselines by Using Single Frequency Measurements

This paper proposes a single frequency based ionosphere gradient detector. Since ionospheric delays can strongly change locally and rapidly due to ionospheric disturbances, the large differences in ionospheric delays between the receiver stations may arise. Therefore, it is necessary for the improvement of the positioning accuracy, availability and reliability to develop the detection method in such cases. In our proposed method, Kalman filter is applied to single difference (SD) code pseudorange and SD carrier phase measurements to estimate SD ionospheric delays, SD carrier phase ambiguities and SD receiver clock error. Further, we apply SD ionosphere-free combinations to determine absolute ionospheric delays in order to distinguish ionospheric delays from carrier phase ambiguities. The estimating performance of our proposed method is evaluated with ionospheric anomalous observable data.
Incommensurate Moiré overlayer with strong local binding: CoO(111) bilayer on Ir(100)

Incommensurate relaxed overlayer Moire structures are often interpreted as systems with weak lateral variations of the binding potential and thus no structural modulations in the overlayer material. We discuss here the example of a CoO(111) bilayer on Ir(100), which is a relaxed overlayer with strong structural response to the lateral modulation of interface properties but nevertheless is incommensurate. By means of density functional theory (DFT) calculations, we quantitatively reproduce all the structural parameters of the CoO(111) bilayer on Ir(100) as proposed by a recent low-energy electron diffraction analysis [Ebensperger et al., Phys. Rev. B 81, 235405 (2010)]. The calculations predict energetic degeneracies with respect to registry shifts of the CoO(111) film along [011]. Large-scale, low-temperature scanning tunneling microscopy topographies reveal that the true structure of the film is incommensurate in this direction, exhibiting a one-dimensional Moire pattern with a period of about 9.4 aIr. From DFT calculations for limiting (periodic) models, we can sample the potential landscape of the cobalt and oxygen atoms in the Moire structure across the Ir(100) unit cell. We find that despite the non-commensurability of the film, the binding to the substrate is site specific with strong attraction and repulsion points for both cobalt and oxygen atoms, leading to severe local distortions in the film. The lateral modulation of the structural elements within the oxide film can be understood as a combination of the lateral variation in the Co-Ir binding potential and additional O-Ir binding.
Bandit view on noisy optimization

This chapter deals with the problem of making the best use of a finite number of noisy evaluations to optimize an unknown function. We are primarily concerned with the case where the function is defined over a finite set. In this discrete setting, we discuss various objectives for the learner, from optimizing the allocation of a given budget of evaluations to optimal stopping time problems with ( , δ)-PAC guarantees. We also consider the so-called online optimization framework, where the result of an evaluation is associated to a reward, and the goal is to maximize the sum of obtained rewards. In this case, we extend the algorithms to continuous sets and (weakly) Lipschitzian functions (with respect to a prespecified metric).
Performance Boost of Si TFETs by Insertion of III–V Dipole Formation Layer: A First Principle Study

Silicon channel tunnel field-effect transistors (TFETs) are known to exhibit low ON-state current due to the wide indirect band gap. In this work, to achieve high ON-state current, we propose a Si TFET with an ultra-thin dipole formation layer (DFL) inserted at the source/channel junction. The inserted DFL forms charge transfer dipoles at the interface, resulting in a staggered band gap. As the consequence, the effective tunnel barrier for electrons is significantly lowered so that ON-state current increases by orders of magnitude. To analyze the characteristics of DFL-inserted Si TFETs, we have solved nonequilibrium Green’s function (NEGF) and Poisson’s equation using density functional theory (DFT) Hamiltonians. We demonstrate that DFL-inserted Si TFETs show boosted performance over conventional TFETs, exhibiting high ON-state current and steep subthreshold swing (SS).
A Population Search Algorithm for Clustered Multivariate Solutions: Application to EEG Connectivity

There is a need to efficiently identify time, frequency and spatial locations between which connectivity occurs within the brain. Therefore, a novel, population based, search algorithm is proposed based upon the behaviour of foraging animals. The method is evaluated on a simple grid search problem and on the identification of time-frequency locations of statistically significant phase synchronisation in both synthetic and real EEG. The method is shown to be comparable to a state-of-the-art phase synchronisation identification algorithm in terms of speed while identifying a large proportion of available solutions.
Techniques to distinguish between electron and photon induced events using segmented germanium detectors

Two techniques to distinguish between electron and photon induced events in germanium detectors were studied: (1) anti-coincidence requirements between the segments of segmented germanium detectors and (2) the analysis of the time structure of the detector response. An 18-fold segmented germanium prototype detector for the GERDA neutrinoless double beta-decay experiment was characterized. The rejection of photon induced events was measured for the strongest lines in Co-60, Eu-152 and Th-228. An accompanying Monte Carlo simulation was performed and the results were compared to data. The sensitivity of the GERDA experiment to neutrinoless double beta-decay was determined. Special statistical tools were developed to correctly treat the small number of events expected.
The search for the pair production of second-generation scalar leptoquarks and measurements of the differential cross sections of the W boson produced in association with jets with the CMS detector at the LHC

of Dissertation Since the formulation of the Standard Model of particle physics, numerous experiments have sought to observe the signatures of the subatomic particles by examining the outcomes of charged particle collisions. Over time, advances in detector technology and scientific computing have allowed for unprecedented precision measurements of Standard Model phenomena and particle properties. Although the Standard Model has displayed remarkable predictive power, extensions to the Standard Model have been formulated to account for unexplained phenomena, and these extensions often infer the existence of additional subatomic particles. Consequently, experiments at particle colliders often endeavor to search for signatures of physics beyond the Standard Model. These searches and measurements are often complementary pursuits, as searches are often limited by the precision of estimations of the Standard Model backgrounds. At the forefront of present-day collider experiments is the Large Hadron Collider at CERN, which delivers proton-proton collisions with unprecedented energy and luminosity. Collisions are recorded with detectors located at interaction points along the ring of the Large Hadron Collider. The CMS detector is one of two general-purpose detectors at the Large Hadron Collider, and the high-precision detection of particles from collision events in the CMS detector make the CMS detector a powerful tool for both Standard-Model measurements and searches for new physics. The Standard Model is characterized by three generation of quarks and leptons.
ALERGODATA: Sentinel registry of health outcomes in allergic patients treated with biological therapies from specialized allergology clinics in Spain.

1Servicio de Alergia, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain 2Servicio de Alergología, Hospital Clínico Universitario “Lozano Blesa”, Zaragoza, Instituto de Investigación Sanitaria de Aragón, Facultad de Medicina, Universidad de Zaragoza, Spain 3Hospital Universitario de Salamanca, Departamento de Ciencias Biomédicas y del Diagnóstico, IBSAL, Salamanca, Spain 4Rhinology & Asthma Unit, Hospital Universitario de Jerez, Cádiz, Spain 5Hospital Universitario Virgen Macarena, Sevilla, Spain 6Hospital Universitario La Paz, Instituto de Investigación (IDiPAZ), Madrid, Spain 7Hospital Universitario Cruces, Vizcaya, Spain 8Complejo Asistencial de Zamora, Zamora Spain 9Hospital de Llíria, Valencia, Spain 10Hospital Universitari Vall d'Hebron, Barcelona, Spain 11Hospital infantil Universitario Niño Jesús, Madrid, Spain 12Complexo Hospitalario Universitario A Coruña, Spain 13Hospital de Conxo de Santiago de Compostela, Spain 14Hospital Clínic de Barcelona, IDIBAPS, CIBERES, Barcelona, Spain
Mathematics Curriculum in Ireland: The Influence of PISA on the Development of Project Maths

This article interrogates the extent to which the Organization for Economic Cooperation and Development (OECD) through its Programme for International Student Assessment (PISA) influenced the development of Project Maths, a new second-level mathematics education policy in Ireland. It argues that the Irish government, in its revision of mathematics education policy, was strongly influenced by PISA and that concern with the country’s ‘average’ placement in the international assessment was instrumental in defining the direction of the revision. It traces the genetic imprint of PISA on the development of curriculum policy, the new mathematics syllabus, its content and assessment. It argues that Project Maths sets out to follow closely the PISA conceptual framework. However, the analysis finds that Project Maths is not a mini-PISA but that the programme is comprised of two distinct approaches, on the one hand retaining the abstract, symbolic mathematics of sections of the pre-existing curriculum, while on the other emphasizing a PISA-like approach to pedagogy and to real-life problem solving.
Evaluating Efficiency of a Provincial Telerehabilitation Service in Improving Access to Care During the COVID-19 Pandemic

Scope Early in the COVID-19 pandemic, community rehabilitation stakeholders from a provincial health system designed a novel telerehabilitation service. The service provided wayfinding and self-management advice to individuals with musculoskeletal concerns, neurological conditions, or post-COVID-19 recovery needs. This study evaluated the efficiency of the service in improving access to care. Methodology We used multiple methods including secondary data analyses of call metrics, narrative analyses of clinical notes using artificial intelligence (AI) and machine learning (ML), and qualitative interviews. Conclusions Interviews revealed that the telerehabilitation service had the potential to positively impact access to rehabilitation during the COVID-19 pandemic, for individuals living rurally, and for individuals on wait lists. Call metric analyses revealed that efficiency may be enhanced if call handling time was reduced. AI/ML analyses found that pain was the most frequently-mentioned keyword in clinical notes, suggesting an area for additional telerehabilitation resources to ensure efficiency.
Application Of The Random Choice Method To TheEstuarine Mass Transport

Performance comparisons of the Random Choice Method (RCM) with conventional advection schemes to compute simple cases of the Mass Transport Equation in estuaries are conducted. Test cases treated here include one-dimensional front propagation and advection of a rotary pulse. Both cases represent extreme conditions of the mass transport in estuaries, i.e., absence of physical diffusion. The RCM is capable of producing numerical solutions that are exactly equal to the analytical solutions, except for a displacement of coordinates which on the average is zero. All other numerical schemes compared introduce numerical diffusion and/or dispersion. The RCM therefore offers a very good alternative for modeling mass transport in estuaries.
Numerical modeling of heat transfer by radiation and convection in an atrium with thermal inertia

The thermal comfort and buoyancy-induced motion of air in a room are determined by the interaction of different types of heat transfer and of thermal storage in building components. Heat transfer includes energy transport by radiation, convection, and conduction (within air and the building fabric). The driving forces of buoyancy of air become more pronounced for tall spaces. Therefore, proper modeling of these interactions becomes more crucial in the design of large enclosures. In atria, in particular, solar and infrared radiation are important because of large-area glazing. The boundary conditions for airflow, surface-to-surface radiation, and building dynamics are linked by surface temperatures that may vary in time and space. Numerical methods for the direct coupling of computational fluid dynamics with thermal dynamics and radiation are proposed and demonstrated at a case study building of IEA Annex 26.
Observability Criteria and Null-Measurement Kalman Filter for Vision-Aided Inertial Navigation

This work presents a linear time-varying approach to real-time vision-aided inertial navigation. An exact measurement model is provided, which linearly depends on the state and is therefore suitable for Kalman filtering. Sufficient observability and nonobservability criteria are derived, which can be used to identify observable trajectories. Moreover, the paper proposes a filter able to determine the absolute scale of the camera motion without any need for estimating three-dimensional feature positions or a priori knowledge of the absolute attitude. The effectiveness of the filter on low-cost hardware is demonstrated in flight tests with a small fixed-wing unmanned aerial vehicle.
Maximum Kullback-Leibler Distance of Some Conventional Distributions

Based on the distance of Kullback-Leibler,this paper give the exact definition of the maximum Kullback-Leibler distance between two different distribution functions and prove that this one has analytic properties such as symmetry,triangle inequality which is the same as the Euclidean distance.By the definition, the maximum Kullback-Leibler distance between some conventional distributions, such as two different binomial distributions,two different normal distributions are obtianed. Farther,for multivariable distribution,this paper give the definition of the Kullback-Leibler distance, and to derive the Kullback-Leibler distance for two different matrix Γ-distribution. On the other hand,the conditions that a normal distribution approximate to a exponetial distribution is obtained under Kullback-Leibler distance.
Numerical Simulation Study on Field of Temperature During the Growth of Nd∶YAG Crystal

A numerical simulation study on field of temperature in crystal and melt by using FDM (Finite Differential Method) during the growth of Nd∶YAG crystal by Cz (Czochralski) method was reported. At first, the mathematical model of the growth of Nd∶YAG crystal was given, then the equations with no dimensions were given. Finally, the boundary condition was given and the equations were solved by FDM. The simulation program was given by above method, and then the change of field of temperature in crystal and melt was described by simulation program. The effect of technological conditions on field of temperature in crystal and melt was analyzed.
Chemical, Physical, and Toxicological Properties of V-Agents

V-agents are exceedingly toxic organophosphate nerve agents. The most widely known V-agents are the phosphonylated thiocholines VX and VR. Nonetheless, other V-subclasses have been synthesized. Here, a holistic overview of V-agents is provided, where these compounds have been categorized based on their structures to facilitate their study. A total of seven subclasses of V-agents have been identified, including phospho(n/r)ylated selenocholines and non-sulfur-containing agents, such as VP and EA-1576 (EA: Edgewood Arsenal). Certain V-agents have been designed through the conversion of phosphorylated pesticides to their respective phosphonylated analogs, such as EA-1576 derived from mevinphos. Further, this review provides a description of their production, physical properties, toxicity, and stability during storage. Importantly, V-agents constitute a percutaneous hazard, while their high stability ensures the contamination of the exposed area for weeks. The danger of V-agents was highlighted in the 1968 VX accident in Utah. Until now, VX has been used in limited cases of terrorist attacks and assassinations, but there is an increased concern about potential terrorist production and use. For this reason, studying the chemistry of VX and other less-studied V-agents is important to understand their properties and develop potential countermeasures.
DESIGN SPACE OPTIMIZATION FOR TOPOLOGY BASED ON FIXED GRID

Design space optimization for topology based on fixed grid is proposed and numerical verification for high probability to a global optimum is shown. In conventional optimization, only a portion of structural parameters are designated as design variables while the remaining set of other parameters related to the design space are often taken for granted. It is desirable to make the design space evolve into a better one during optimization process by increasing or decreasing the number of design variables, which is called design space optimization. To have this capability, it is needed to obtain sensitivities when design space expands. A method has been developed recently with the necessary mathematical background, but due to coupling effect between neighboring elements during implementation sensitivity results have not been satisfactory. To solve this problem, a new method of decoupling nearby elements based on FE model is proposed. Also, to avoid the deletion of newly created elements during the optimization process, mixed artificial material is proposed. Seeking optimal design space for topology is very tedious and time-consuming. To accelerate this process, new method for design space expansion is proposed and superior performance over conventional method illustrated. Although there are many local optimums in the usual formulations, this is hardly mentioned or studied in the past. Two kinds of numerical examples are taken to demonstrate that the proposed design space optimization can give higher probability of getting the global optimum. Nomenclature * , u u→ + ψ = sensitivity of a functional using directional derivative at the pivot phase
Handbook of 3D Machine Vision: Optical Metrology and Imaging, Series in Optics and Optoelectronics, edited by Song Zhang

approximated by MHD assumption and are the focus of the next chapter. The article discusses the fundamental dynamics of turbulence in dynamos (electrically conducting fluids without a significant mean magnetic field) and strong and weak turbulence in flows with significant magnetic field. The book closes with another interesting and intellectually stimulating phenomenon – quantum turbulence. The article revolves around the core theme of identification of similarities between quantum and classical turbulence by comparing the decaying isotropic turbulence with decay of vortex line density in QT. Overall, each chapter is exceptionally well written with topics arranged in a logical and streamlined fashion. The writing style differs from chapter to chapter; each review article being written by a different author(s). Since the book covers a wide variety of subject matter, it is quite natural that the contents are selective in nature. This fact is acknowledged in most of the chapters by their respective authors. This deficiency is compensated by the literature cited at the end of each chapter, which covers the majority of seminal research works conducted in the field of turbulent flows in the last century. While, the book is extremely insightful, it can be a challenge to read because of the rigorous and mathematical treatment of the subject matter – it is not an introductory textbook. Potential readers are expected to have a thorough understanding of fundamental turbulence theory (including the mathematical description) and familiarity with advanced topics in turbulent flows.
Mutations in the Vicinity of the IRAK3 Guanylate Cyclase Center Impact Its Subcellular Localization and Ability to Modulate Inflammatory Signaling in Immortalized Cell Lines

Interleukin-1 receptor-associated kinase 3 (IRAK3) modulates the magnitude of cellular responses to ligands perceived by interleukin-1 receptors (IL-1Rs) and Toll-like receptors (TLRs), leading to decreases in pro-inflammatory cytokines and suppressed inflammation. The molecular mechanism of IRAK3’s action remains unknown. IRAK3 functions as a guanylate cyclase, and its cGMP product suppresses lipopolysaccharide (LPS)-induced nuclear factor kappa-light-chain-enhancer of activated B cell (NFκB) activity. To understand the implications of this phenomenon, we expanded the structure–function analyses of IRAK3 through site-directed mutagenesis of amino acids known or predicted to impact different activities of IRAK3. We verified the capacity of the mutated IRAK3 variants to generate cGMP in vitro and revealed residues in and in the vicinity of its GC catalytic center that impact the LPS-induced NFκB activity in immortalized cell lines in the absence or presence of an exogenous membrane-permeable cGMP analog. Mutant IRAK3 variants with reduced cGMP generating capacity and differential regulation of NFκB activity influence subcellular localization of IRAK3 in HEK293T cells and fail to rescue IRAK3 function in IRAK3 knock-out THP-1 monocytes stimulated with LPS unless the cGMP analog is present. Together, our results shed new light on the mechanism by which IRAK3 and its enzymatic product control the downstream signaling, affecting inflammatory responses in immortalized cell lines.