Miracle-dz/UniFAR-FTUs huggingface dataset:
A quasi-conservative DG-ALE method for multi-component flows using the non-oscillatory kinetic flux

A high-order quasi-conservative discontinuous Galerkin (DG) method is proposed for the numerical simulation of compressible multi-component flows. A distinct feature of the method is a predictor-corrector strategy to define the grid velocity. A Lagrangian mesh is first computed based on the flow velocity and then used as an initial mesh in a moving mesh method (the moving mesh partial differential equation or MMPDE method ) to improve its quality. The fluid dynamic equations are discretized in the direct arbitrary Lagrangian-Eulerian framework using DG elements and the non-oscillatory kinetic flux while the species equation is discretized using a quasiconservative DG scheme to avoid numerical oscillations near material interfaces. A selection of oneand two-dimensional examples are presented to verify the convergence order and the constant-pressure-velocity preservation property of the method. They also demonstrate that the incorporation of the Lagrangian meshing with the MMPDE moving mesh method works well to concentrate mesh points in regions of shocks and material interfaces.
EventAnchor: Reducing Human Interactions in Event Annotation of Racket Sports Videos

The popularity of racket sports (e.g., tennis and table tennis) leads to high demands for data analysis, such as notational analysis, on player performance. While sports videos offer many benefits for such analysis, retrieving accurate information from sports videos could be challenging. In this paper, we propose EventAnchor, a data analysis framework to facilitate interactive annotation of racket sports video with the support of computer vision algorithms. Our approach uses machine learning models in computer vision to help users acquire essential events from videos (e.g., serve, the ball bouncing on the court) and offers users a set of interactive tools for data annotation. An evaluation study on a table tennis annotation system built on this framework shows significant improvement of user performances in simple annotation tasks on objects of interest and complex annotation tasks requiring domain knowledge.
Convergence analysis of some tent-based schemes for linear hyperbolic systems

Finite element methods for symmetric linear hyperbolic systems using unstructured advancing fronts (satisfying a causality condition) are considered in this work. Convergence results and error bounds are obtained for mapped tent pitching schemes made with standard discontinuous Galerkin discretizations for spatial approximation on mapped tents. Techniques to study semidiscretization on mapped tents, design fully discrete schemes, prove local error bounds, prove stability on spacetime fronts, and bound error propagated through unstructured layers are developed.
Computer Architecture-Aware Optimisation of DNA Analysis Systems

DNA sequencing is revolutionising the field of medicine. DNA sequencers, the machines which perform DNA sequencing, have evolved from the size of a fridge to that of a mobile phone over the last two decades. The cost of sequencing a human genome also has reduced from billions of dollars to hundreds of dollars. Despite these improvements, DNA sequencers output hundreds or thousands of gigabytes of data that must be analysed on computers to discover meaningful information with biological implications. Unfortunately, the analysis techniques have not kept the pace with rapidly improving sequencing technologies. Consequently, even today, the process of DNA analysis is performed on high-performance computers, just as it was a couple of decades ago. Such high-performance computers are not portable. Consequently, the full utility of an ultra-portable sequencer for sequencing in-the-field or at the point-of-care is limited by the lack of portable lightweight analytic techniques. This thesis proposes computer architecture-aware optimisation of DNA analysis software. DNA analysis software is inevitably convoluted due to the complexity associated with biological data. Modern computer architectures are also complex. Performing architecture-aware optimisations requires the synergistic use of knowledge from both domains, (i.e, DNA sequence analysis and computer architecture). This thesis aims to draw the two domains together. In this thesis, gold-standard DNA sequence analysis workflows are systematically examined for algorithmic components that cause performance bottlenecks. Identified bottlenecks are resolved through architecture-aware optimisations at different levels, i.e., memory, cache, register and processor. The optimised software tools are used in complete end-to-end analysis workflows and their efficacy is demonstrated by running on prototypical embedded systems.
DAEs for Linear Inverse Problems: Improved Recovery with Provable Guarantees

Generative priors have been shown to provide improved results over sparsity priors in linear inverse problems. However, current state of the art methods suffer from one or more of the following drawbacks: (a) speed of recovery is slow; (b) reconstruction quality is deficient; (c) reconstruction quality is contingent on a computationally expensive process of tuning hyperparameters. In this work, we address these issues by utilizing Denoising Auto Encoders (DAEs) as priors and a projected gradient descent algorithm for recovering the original signal. We provide rigorous theoretical guarantees for our method and experimentally demonstrate its superiority over existing state of the art methods in compressive sensing, inpainting, and super-resolution. We find that our algorithm speeds up recovery by two orders of magnitude (over 100x), improves quality of reconstruction by an order of magnitude (over 10x), and does not require tuning hyperparameters.
The structure of epitaxial layers of uranium

Epitaxial layers of uranium have been grown on a variety of buffer/seed layers on sapphire substrates by UHV magnetron sputtering and their structure determined using x-ray diffraction. The buffer layers were epitaxial layers of niobium, tungsten and niobium covered by a seed layer of hcp gadolinium, on which uranium layers were grown to a thickness of 600 Å. The x-ray diffraction results establish that the α-orthorhombic phase of uranium grows epitaxially in the (110) orientation on the niobium (110) buffer, while on the tungsten (110) buffer the growth planes of the α-uranium were (002) and for the growth on the gadolinium buffer the α-uranium was predominantly (021) oriented. These results show that epitaxial uranium films in selected orientations can be grown by using an appropriate buffer. To our knowledge this is the first report of epitaxial α-uranium films, and it is significant because of the difficulty of growing single crystals of α-uranium due to the occurrence of high temperature structural transformations.
No black holes from cosmic string cusps

Recent work by Jenkins and Sakellariadou claims that cusps on cosmic strings lead to black hole production. To derive this conclusion they use the hoop conjecture in the rest frame of the string loop, rather than in the rest frame of the proposed black hole. Most of the energy they include is the bulk motion of the string near the cusp. We redo the analysis taking this into account and find that cusps on cosmic strings with realistic energy scale do not produce black holes, unless the cusp parameters are extremely fine-tuned.
Fast and robust magnon transport in a spin chain

A protocol for fast and robust magnon transport in a one-dimensional spin chain is devised. Employing an approximate mapping between the chain and a single harmonically trapped particle, we exploit the known analytic control protocols for the latter and adopt them to achieve fast, high-fidelity transport in the chain. We compare the performance with finite time adiabatic protocols, showing that the designed scheme allows for significantly faster and more stable transport. Furthermore, we show that a sharp transition exists between regions in which the protocol is effective and when it breaks down, giving rise to a heuristic speed limit for the process.
Generation of electric charge associated with the formation of soft hail in thunderclouds

The electrical charging which results from collisions between ice crystals and a simulated hailstone is measured as a function of their temperature difference, and of the size and impact velocity of the crystals. It is found that the sign of the charging is governed by that of the temperature difference, the hailstone becoming negatively charged if it is warmer than the rebounding crystals. The magnitude of the charging is proportional to the temperature difference but rather insensitive to the size and impact velocity of the crystals. With a temperature difference of 5°C, a rebounding crystal of diameter about 50 μ produces, on average, a charge of 5 x 10-9 e. s. u. The electrification of an artificial pellet of soft hail growing by the accretion of supercooled water droplets (riming) is also investigated. Freezing of the droplets on the hailstone is accompanied by the ejection of positively charged ice splinters, the hailstone acquiring a negative charge. The manner in which the rates of charging and splinter production vary with the air temperature, drop diameter and impact velocity has been established. In a typical experiment, with the air temperature at -15°C, droplets of diameter 80μ impacting at 10 m s-1 freeze to produce, on average, 12 splinters and a charge of 4 x 10-6 e. s. u. per drop. Droplets of diameter less than 30 μ produce few splinters and little charging. The results of both sets of experiments are interpreted in terms of the authors’ theory of charge separation in ice under the influence of a temperature gradient, and are used to calculate probable rates of charge generation in thunderstorms. It appears that the electrification which accompanies the growth of pellets of soft hail through the freezing and splintering of supercooled droplets is capable of generating and separating charge at the required rate of about 1 C km-3 min-1 but, while rebounding ice crystals will usually charge the hailstones in the same (negative) sense, this mechanism will contribute only slightly to thunderstorm electrification.
Characterization of Thin-Film Lithium Batteries with Stable Thin-Film Li3PO4 Solid Electrolytes Fabricated by ArF Excimer Laser Deposition

High quality Li 3 PO 4 thin films have been prepared by pulsed laser deposition (PLD) as a solid electrolyte for thin-film batteries. The structure, composition, ionic conductivity, and electrochemical stability of the Li 3 PO 4 thin films have been characterized. The Li 3 PO 4 film exhibits a single lithium-ion conductor with an ionic conductivity of 4.0 × 10 -7 S cm -1 at 25°C and an activation energy of 0.58 eV. The Li 3 PO 4 film is electrochemically stable in the potential range from 0 to 4.7 V vs Li/Li + . All-solid-state thin-film batteries, Li/Li 3 PO 4 /LiCoO 2 , have been fabricated by using PLD-grown Li 3 PO 4 thin film. The thin-film battery shows excellent intercalation property and stability for long-term cycling in the potential range from 3.0 to 4.4 V.
Network Slicing for eMBB and mMTC with NOMA and Space Diversity Reception

In this work, we study the coexistence in the same Radio Access Network (RAN) of two use cases present in the Fifth Generation (5G) of wireless communication systems: enhanced Mobile BroadBand (eMBB) and massive Machine-Type Communications (mMTC). eMBB services are requested for applications that demand extremely high data rates and moderate requirements on latency and reliability, whereas mMTC enables applications for connecting a massive number of low-power and low-complexity devices. The coexistence of both services is enabled by means of network slicing and Non-Orthogonal Multiple Access (NOMA) with Successive Interference Cancellation (SIC) decoding. Under the orthogonal slicing, the radio resources are exclusively allocated to each service, while in the non-orthogonal slicing the traffics from both services overlap in the same radio resources. We evaluate the uplink performance of both services in a scenario with a multi-antenna Base Station (BS). Our simulation results show that the performance gains obtained through multiple receive antennas are more accentuated for the non-orthogonal slicing than for the orthogonal allocation of resources, such that the non-orthogonal slicing outperforms its orthogonal counterpart in terms of achievable data rates or number of connected devices as the number of receive antennas increases.
FUNCTIONAL CALCULI FOR SECTORIAL OPERATORS AND RELATED FUNCTION THEORY

Abstract We construct two bounded functional calculi for sectorial operators on Banach spaces, which enhance the functional calculus for analytic Besov functions, by extending the class of functions, generalising and sharpening estimates and adapting the calculus to the angle of sectoriality. The calculi are based on appropriate reproducing formulas, they are compatible with standard functional calculi and they admit appropriate convergence lemmas and spectral mapping theorems. To achieve this, we develop the theory of associated function spaces in ways that are interesting and significant. As consequences of our calculi, we derive several well-known operator norm estimates and provide generalisations of some of them.
HESS J1858+020: A GeV-TeV source possibly powered by cosmic rays from SNR G35.6-0.4

Context. The supernova remnant (SNR) G35.6−0.4 shows a non-thermal radio shell, however, no γ-ray or X-ray counterparts have been found for it thus far. One TeV source, HESS J1858+020, was found near the SNR and this source is spatially associated with some clouds at 3.6 kpc. Aims. To attain a better understanding of the origin of HESS J1858+020, we further investigate the association between SNR cosmic rays (CRs) and the clouds through the Fermi-LAT analysis and hadronic modeling. Methods. We performed the Fermi-LAT analysis to explore the GeV emission in and around the SNR. We explored the SNR physics with previously observed multi-wavelength data. We built a hadronic model using runaway CRs of the SNR to explain the GeV-TeV observation. Results. We found a hard GeV source (SrcX2) that is spatially coincident with both HESS J1858+020 and a molecular cloud complex at 3.6 kpc. In addition, a soft GeV source (SrcX1) was found at the northern edge of the SNR. The GeV spectrum of SrcX2 connects well with the TeV spectrum of HESS J1858+020. The entire γ-ray spectrum ranges from several GeV up to tens of TeV and it follows a power-law with an index of ~2.15. We discuss several pieces of observational evidence to support the middle-aged SNR argument. Using runaway CRs from the SNR, our hadronic model explains the GeV-TeV emission at HESS J1858+020, with a diffusion coefficient that is much lower than the Galactic value.
Plug-and-Play Algorithms for Video Snapshot Compressive Imaging

We consider the reconstruction problem of video snapshot compressive imaging (SCI), which captures high-speed videos using a low-speed 2D sensor (detector). The underlying principle of SCI is to modulate sequential high-speed frames with different masks and then these encoded frames are integrated into a snapshot on the sensor and thus the sensor can be of low-speed. On one hand, video SCI enjoys the advantages of low-bandwidth, low-power and low-cost. On the other hand, applying SCI to large-scale problems (HD or UHD videos) in our daily life is still challenging and one of the bottlenecks lies in the reconstruction algorithm. Existing algorithms are either too slow (iterative optimization algorithms) or not flexible to the encoding process (deep learning based end-to-end networks). In this paper, we develop fast and flexible algorithms for SCI based on the plug-and-play (PnP) framework. In addition to the PnP-ADMM method, we further propose the PnP-GAP (generalized alternating projection) algorithm with a lower computational workload. We first employ the image deep denoising priors to show that PnP can recover a UHD color video with 30 frames from a snapshot measurement. Since videos have strong temporal correlation, by employing the video deep denoising priors, we achieve a significant improvement in the results. Furthermore, we extend the proposed PnP algorithms to the color SCI system using mosaic sensors, where each pixel only captures the red, green or blue channels. A joint reconstruction and demosaicing paradigm is developed for flexible and high quality reconstruction of color video SCI systems. Extensive results on both simulation and real datasets verify the superiority of our proposed algorithm.
Electric dipole moment in storage ring experiments

The measurement of electric dipole moment (EDM) in storage rings can potentially exceed the sensitivity of tests with neutral systems. The spin dynamics under such conditions is described by the Bargmann-Michel-Telegdi equation. It can be derived in the semiclassical approximation under several assumptions one of which is the zero pseudoscalar bilinear. However, many promising extensions to the standard model consider scalar-pseudoscalar couplings which assume nonzero electron pseudoscalar. We re-derive the spin precession equation under conditions that do not assume that pseudoscalar is zero. It leads to a correction term that might be required for matching the storage ring measurements with quantum field evaluations. Since the goal of storage ring experiments is to achieve unprecedently high accuracy in measuring EDM, it is important to accurately describe the spin dynamics under conditions of CP-violating extensions.
Energy-Efficient Node Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

We study a heterogeneous wireless sensor network (WSN) where N heterogeneous access points (APs) gather data from densely deployed sensors and transmit their sensed information to M heterogeneous fusion centers (FCs) via multi-hop wireless communication. This heterogeneous node deployment problem is modeled as an optimization problem with total wireless communication power consumption of the network as its objective function. We consider both static WSNs, where nodes retain their deployed position, and mobile WSNs where nodes can move from their initial deployment to their optimal locations. Based on the derived necessary conditions for the optimal node deployment in static WSNs, we propose an iterative algorithm to deploy nodes. In addition, we study the necessary conditions of the optimal movement-efficient node deployment in mobile WSNs with constrained movement energy, and present iterative algorithms to find such deployments, accordingly. Simulation results show that our proposed node deployment algorithms outperform the existing methods in the literature, and achieves a lower total wireless communication power in both static and mobile WSNs, on average.
Calibration Methods of Touch-Point Ambiguity for Finger-Fitts Law

Finger-Fitts law (FFitts law) is a model to predict touch-pointing times that was modified from Fitts’ law. It considers the absolute touch-point precision, or a finger tremor factor 𝜎 a , to decrease the admissible target area and thus increase the task difficulty. Among choices such as running an independent task or performing parameter optimization, there is no consensus on the best methodology to measure 𝜎 a . By integrating the results of our 1D and 2D touch-pointing experiments and reanalyses of previous studies’ data, we examined the advantages and disadvantages of each approach to compute 𝜎 a , and we found that there is no optimal choice to maximize the prediction accuracy of FFitts law.
Memory-Efficient Modeling and Slicing of Large-Scale Adaptive Lattice Structures

Lattice structures have been widely used in various applications of additive manufacturing due to its superior physical properties. If modeled by triangular meshes, a lattice structure with huge number of struts would consume massive memory. This hinders the use of lattice structures in large-scale applications (e.g., to design the interior structure of a solid with spatially graded material properties). To solve this issue, we propose a memory-efficient method for the modeling and slicing of adaptive lattice structures. A lattice structure is represented by a weighted graph where the edge weights store the struts' radii. When slicing the structure, its solid model is locally evaluated through convolution surfaces and in a streaming manner. As such, only limited memory is needed to generate the toolpaths of fabrication. Also, the use of convolution surfaces leads to natural blending at intersections of struts, which can avoid the stress concentration at these regions. We also present a computational framework for optimizing supporting structures and adapting lattice structures with prescribed density distributions. The presented methods have been validated by a series of case studies with large number (up to 100M) of struts to demonstrate its applicability to large-scale lattice structures.
Automated determination of iron in seawater by chelating resin concentration and chemiluminescence detection

A new automated shipboard analytical method for determining iron(III) in seawater has been developed. The method is based on a combination of selective column extraction using chelating resin and improved chemiluminescence (CL) detection in a closed flowthrough system. In this method, Fe(III) in an acidified sample solution is selectively collected on 8-quinolinol immobilized chelating resin and then eluted with dilute hydrochloric acid. The resulting eluent is mixed with luminol solution, aqueous ammonia, and hydrogen peroxide solution successively, and then the mixture is introduced into the CL cell. The iron concentration is obtained from the CL intensity. The detection limit of iron(III) is 0.05 nmol L -1 when using an 18-mL seawater sample
Determinants of Non-Adherence to Treatment Among Patients with Type 2 Diabetes in Kenya: A Systematic Review

Introduction Non-adherence to the prescribed treatment regimen in patients with type 2 diabetes mellitus is quite high. Furthermore, it has been associated with higher rates of hospital admissions, suboptimal health outcomes, increased morbidity and mortality, and increased health care costs. The present systematic review study aimed to explore the determinants that contribute to non-adherence to treatment among patients with type 2 diabetes mellitus in Kenya. Methods A systematic review of studies conducted in Kenya on the present research problem published in English between December 2013 and May 2020. The databases included Scopus, Web of Science, Science Direct, Cochrane Library, PUBMED, OVID and Google Scholar. The following were the key words used in the search: “Non-adherence Diabetes Patients”, “Determinants of Non-adherence Diabetes Patients” AND “Health Facilities” AND “Kenya”. Qualitative analysis was used to present data under thematic domains. Results The search generated 17,094 articles of which only 15 met the inclusion criteria. The major determinants were presented under three thematic domains: 1) Cost – income, insurance, distance, bills of drugs and food; 2) Patient characteristics – perception of (efficacy, severity, effects of non-adherence), knowledge, co-morbidity, family support, self unfounded beliefs; and 3) Health system – health education, multiple drugs, evaluations and support, guidelines, poor perception of system. Conclusion A multitude of factors including unaffordable care, patient’s poor knowledge on the disease process, less family support in patient’s daily self-care management, complex drug regimen and unsatisfactory health messages from the health providers were observed to be associated with non-adherence. Implementing integrated care programs will help in reducing levels of non-adherence among type 2 diabetes mellitus patients.