Miracle-dz/UniFAR-FTUs huggingface dataset:
Fried deconvolution

In this paper we present a new approach to deblur the effect of atmospheric turbulence in the case of long range imaging. Our method is based on an analytical formulation, the Fried kernel, of the atmosphere modulation transfer function (MTF) and a framelet based deconvolution algorithm. An important parameter is the refractive index structure which requires specific measurements to be known. Then we propose a method which provides a good estimation of this parameter from the input blurred image. The final algorithms are very easy to implement and show very good results on both simulated blur and real images.
Grounded Theory: An Exploration of Process and Procedure

Grounded theory, as an evolving qualitative research method, is a product of its history as well as of its epistemology. Within the literature, there have been a number of discussions focusing on the differences between Glaser's (1978, 1992) and Strauss's (1987, 1990) versions of grounded theory. The purpose of this article is to add a level of depth and breadth to this discussion through specifically exploring the Glaser-Strauss debate by comparing the data analysis processes and procedures advocated by Glaser and by Strauss. To accomplish this task, the authors present the article in two sections. First, they provide relevant background information on grounded theory as a research method. Second, they pursue a more in-depth discussion of the positions of Glaser, using Glaser's work, and Strauss, using Strauss's and Strauss and Corbin's (1990) work, regarding the different phases of data analysis, specifically addressing the coding procedures, verification, and the issue of forcing versus emergence.
Erfahrungen mit synchronen und asynchronen Lernszenarien an der Universität Mannheim

ZUSAMMENFASSUNG An der Universität Mannheim werden seit 1996 TeleTeaching-Projekte durchgeführt. Der Schwerpunkt liegt dabei in synchronen Lernszenarien, worunter wir eine zeitgleiche (Internet-) Übertragung einer Veranstaltung an verschiedene Orte verstehen. Die Audio- und Videoströme des Dozenten werden zugleich aufgezeichnet und als Bestandteil eines Computer-Based-Trainings zeitunabhängig für asynchrone Lernszenarien zur Verfügung gestellt. Die implementierten synchronen und asynchronen Lernszenarien werden seit 1998 im Verbundprojekt VIROR der oberrheinischen Universitäten Freiburg, Heidelberg, Karlsruhe und Mannheim eingesetzt. Dieser Artikel beschreibt verschiedene Lernszenarien bei TeleVeranstaltungen, ihre Besonderheiten und spezifischen Anforderungen. Die zugrunde liegende Technologie wird kurz vorgestellt, einige selbst entwickelte Software Werkzeuge beschrieben und weitere, bislang nicht realisierte Anforderungen an die Technik formuliert. Das Hauptaugenmerk aber legen wir auf Erfahrungen, die wir in den nunmehr vier Jahren aktiven TeleTeachings gewonnen haben.
Automatic generation of component wrappers by composition of hardware library elements starting from communication service specification

A system-on-chip is composed of heterogeneous components interacting through a communication network. Wrappers are hardware components aimed to adapt these heterogeneous components to the network. Such an adaptation can be specified as a set of provided and required services, according to communication requirements and available resources. System-on-chip designers are required to quickly adapt to the fast changing system specifications, but the design of a wrapper can be time consuming. So this paper presents a new methodology for their automatic generation starting from a communication service specification. This specification, already used in the computer network community, is refined to an RTL model using a systematic library based approach. The effectiveness of the methodology is shown on an example.
SAR processing UWB VHF data without a motion measurement system

SAR processing usually requires very accurate navigation data, i.e. to form a focused image. The track must be measured within fractions of the centre wavelength. For high frequencies (e.g. X-band) this condition is too strict. Even with a cutting-edge motion measurement system, autofocus is a necessity. For low frequencies (e.g. VHF-band) a differential GPS (DGPS) is often an adequate solution (alone). However, for this case, it is actually conceivable to rely on autofocus capability over the motion measurement system. This paper describes how to form a SAR image without support from navigation data. That is within the scope of factorized geometrical autofocus (FGA). The FGA algorithm is a base-2 fast factorized back-projection realization with six free geometry parameters (per sub-aperture pair). These are tuned step-by-step until a sharp image is obtained. This procedure can compensate for an erroneous geometry (from a focus perspective). The FGA algorithm has been applied successfully on an ultra-wideband (UWB) data set, acquired at VHF-band by the CARABAS 3 system. The track is measured accurately by means of a DGPS. We however adopt and modify a basic geometry model. A linear equidistant flight path at fixed altitude is assumed and adjusted at several resolution levels. With this approach, we emulate a stand-alone processing chain without support from navigation data. The resulting FGA image is compared to a reference image and verified to be focused. This indicates that it is feasible to form a VHF-band SAR image without a motion measurement system.
GENO - GENeric Optimization for Classical Machine Learning

Although optimization is the longstanding algorithmic backbone of machine learning, new models still require the time-consuming implementation of new solvers. As a result, there are thousands of implementations of optimization algorithms for machine learning problems. A natural question is, if it is always necessary to implement a new solver, or if there is one algorithm that is sufficient for most models. Common belief suggests that such a one-algorithm-fits-all approach cannot work, because this algorithm cannot exploit model specific structure and thus cannot be efficient and robust on a wide variety of problems. Here, we challenge this common belief. We have designed and implemented the optimization framework GENO (GENeric Optimization) that combines a modeling language with a generic solver. GENO generates a solver from the declarative specification of an optimization problem class. The framework is flexible enough to encompass most of the classical machine learning problems. We show on a wide variety of classical but also some recently suggested problems that the automatically generated solvers are (1) as efficient as well-engineered specialized solvers, (2) more efficient by a decent margin than recent state-of-the-art solvers, and (3) orders of magnitude more efficient than classical modeling language plus solver approaches.
Protective effect of Aloe vera gel on the permeability transition pore in the inner membrane of rat liver mitochondria in vitro

Abstract Objective: Aloe vera is a perennial drought resisting, succulent plant belonging to the zanthorrhoeaceae family which historically has been used for a variety of medicinal purposes. This study seeks to determine the effect of varying concentrations of Aloe vera gel (50, 100, 150, 250, and 350 µg/ml) on mitochondrial permeability transition pore (MPTP) in rat liver mitochondria (RLM) (in vitro). Methods: Fresh Aloe gel was prepared daily from the Aloe vera leaf and the effect of the gel on mitochondrial membrane permeability transition pore opening was estimated in vitro using the spectrophotometric method of Lapidus and Sokolove. Results: Varying concentrations of Aloe vera gel (50, 100, 150, 250, and 350 µg/ml) induced (insignificantly at p < 0.05) the opening of the mitochondrial permeability transition pore in a concentration dependent manner in the absence of calcium (Δ540 nm as −0.020 ± 0.008, −0.021 ± 0.009, −0.031 ± 0.013, −0.031 ± 0.014, −0.034 ± 0.014 respectively) when compared with the control (−0.016 ± 0.009). In the presence of calcium, the various concentrations of Aloe vera gel further opened the MMPT pore with the highest effect noticed at 350 µg/ml concentration. Conclusions: These findings indicate that Aloe vera gel modulates the mitochondrial pore opening by further increasing the effect of calcium. This effect is needed in situations that requires tissue wastage such as in cancer treatment.
A survey of maneuvering target tracking, part VIc: approximate nonlinear density filtering in discrete time

This paper is Part VIc of a comprehensive survey of maneuvering target tracking without addressing the so-called measurement-origin uncertainty. It provides an in-depth coverage of various approximate density-based nonlinear filters in discrete time developed particularly for handling the uncertainties induced by potential target maneuvers as well as nonlinearities in the dynamical systems commonly encountered in target tracking. An emphasis is given to more recent results, especially those with good potential for tracking applications.
Lattice equations and dielectric function for optical lattice vibrations in monolayer transition metal dichalcogenides

Using a microscopic dipole lattice model including electronic polarization (EP) of ions and local field effects (LFEs) self-consistently, two sets of three equations are deduced for long wavelength in-plane and out-of-plane optical lattice vibrations in monolayer (ML) transition metal dichalcogenides (TMDs). Expressions for the lattice vibrational energy density are obtained for the two-dimensional (2D) crystals. The linear coefficients of the lattice equations can be determined by first-principles calculation, making these equations very useful for studying the lattice dynamical properties. The two pairs of equations describing the polar vibrations have the same forms as those for ML hexagonal BN and also resemble Huang's equations for bulk [Proc. Roy. Soc. A 208, 352 (1951)]. Each pair of the equations are solved simultaneously with the equation of electrostatics, and explicit expressions are obtained for the in-plane longitudinal and transverse optical (LO and TO) modes and out-of-plane optical (ZO) modes. The LO phonon dispersion relation is identical to the analytical expression of Sohier et al. [Nano Lett. 17, 3758 (2017)]. All the optical phonon branches except for LO are nondispersive at the long wavelengths. A 2D longitudinal lattice dielectric function $\epsilon(k,\omega)$ is deduced, allowing one to rederive the LO phonon dispersion simply from $\epsilon(k,\omega)=0$. A 2D Lyddane--Sachs--Teller relation and a frequency--susceptibility relation are obtained for in-plane and out-of-plane vibrations, respectively, through which the phonon frequencies are related to the 2D dielectric functions or susceptibilities. The explicit expressions are applied to calculate various dynamical properties when knowing three first-principles calculated parameters, and the ionic EP and LFEs are studied thoroughly.
Follow-up procedure for gravitational wave searches from isolated neutron stars using the time-domain F-statistic method

Among promising sources of gravitational waves are long-lived nearly periodic signals produced by rotating, asymmetric neutron stars. Depending on the astrophysical scenario, the sources of asymmetry may have thermal, viscous, elastic and/or magnetic origin. In this work we introduce a follow-up procedure for an all-sky search for gravitational wave signals from rotating neutron stars. The procedure denoted as Followup implements matched-filtering -statistic method. We describe data analysis methods and algorithms used in the procedure. We present tests of the Followup for artificial signals added to white, Gaussian noise. The tests show a good agreement with the theoretical predictions. The Followup will become part of the Time-Domain -statistic pipeline that is routinely used for all-sky searches of LIGO and Virgo detector data.
The cut metric for probability distributions

Guided by the theory of graph limits, we investigate a variant of the cut metric for limit objects of sequences of discrete probability distributions. Apart from establishing basic results, we introduce a natural operation called {\em pinning} on the space of limit objects and show how this operation yields a canonical cut metric approximation to a given probability distribution akin to the weak regularity lemma for graphons. We also establish the cut metric continuity of basic operations such as taking product measures.
[Analysis of the efficacy of reflexology in the complex treatment of chronic migraine].

AIM To evaluate the effect of different reflexology techniques on main clinical indices of patients with chronic migraine, the number of analgesics used and dynamics of chronic migraine comorbid disorders. MATERIAL AND METHODS The study included 84 patients (60 women (71.5%) and 24 men (28.5%)), aged from 18 to 63 years, with a diagnosis of chronic migraine. Patients were randomized in 4 groups - Su Jok (n=22), acupuncture (n=22), electroacupuncture (n=20), control (n=20). Topiramate was administered in all groups in dose of 100 mg daily. Patients were evaluated before treatment, after 4 and 16 weeks from randomization. RESULTS There was a marked regression in frequency of headache in reflexological groups in comparison with the control. The number of days with headache was 19±1.12 at baseline and 6.57±1.3 days after treatment in the Su Jok group; 21.6±1.688 and 7±1.786 days in the acupuncture group; 20.25±1.97 and 5.75±0.633 days in the electroacupuncture group. Each of the methods had an impact on various clinical aspects of chronic migraine and comorbid disorders: Su Jok was most effective in treatment of autonomic disorders, the use of acupuncture resulted in the significant reduction of headache intensity and regression of anxiety disorders. The electroacupuncture group showed a significant increase in pain threshold and the least number of days with headache per month. CONCLUSION Reflexotherapy is a method of choice in the complex treatment of patients with chronic migraine. Taking into account complex diagnosis, the individually oriented approach in prescribing of different reflexology techniques for successful treatment and subsequent rehabilitation of patients with chronic migraine is required.
Information Minimization In Emergent Languages

There is a growing interest in studying the languages emerging when neural agents are jointly trained to solve tasks that require communication through discrete messages. We investigate here the information-theoretic complexity of such languages, focusing on the most basic two-agent, one-symbol, one-exchange setup. We find that, under common training procedures, the emergent languages are subject to an information minimization pressure: The mutual information between the communicating agent's inputs and the messages is close to the minimum that still allows the task to be solved. After verifying this information minimization property, we perform experiments showing that a stronger discrete-channel-driven information minimization pressure leads to increased robustness to overfitting and to adversarial attacks. We conclude by discussing the implications of our findings for the studies of artificial and natural language emergence, and for representation learning.
Knee osteoarthritis in obese women with cardiometabolic clustering.

OBJECTIVE To assess the role of obesity and metabolic dysfunctionality with knee osteoarthritis (OA), knee joint pain, and physical functioning performance, adjusted for joint space width (JSW) asymmetry. METHODS Knee OA was defined as a Kellgren/Lawrence score > or =2 on weight-bearing radiographs. Obesity was defined as a body mass index > or =30 kg/m2. Cardiometabolic clustering classification was based on having > or =2 of the following factors: low levels of high-density lipoprotein cholesterol; elevated levels of low-density lipoprotein cholesterol, triglycerides, blood pressure, C-reactive protein, waist:hip ratio, or glucose; or diabetes mellitus. The difference between lateral and medial knee JSW was used to determine joint space asymmetry. RESULTS In a sample of women (n = 482, mean age 47 years), prevalences of knee OA and persistent knee pain were 11% and 30%, respectively. The knee OA prevalence in nonobese women without cardiometabolic clustering was 4.7%, compared with 12.8% in obese women without cardiometabolic clustering and 23.2% in obese women with cardiometabolic clustering. Nonobese women without cardiometabolic clustering were less likely to perceive themselves as limited compared with women in all other obesity/cardiometabolic groups (P < 0.05). Similar associations were seen with knee pain and physical functioning measures. The inclusion of a joint space asymmetry measure was associated with knee OA but not with knee pain or physical functioning. CONCLUSION Knee OA was twice as frequent in obese women with cardiometabolic clustering compared with those without, even when considering age and joint asymmetry. Obesity/cardiometabolic clustering was also associated with persistent knee pain and impaired physical functioning.
A comparison study of microarrays by fluorescence imaging and surface plasmon resonance imaging

In the past decade the analysis of microarrays which are rich in biology information has generated considerable interest. One of the conventional techniques in this area is to detect the biomolecules labeled with fluorescence agents. In recent years, the surface plasmon resonance (SPR) imaging plays an important role in the detection of microarrays. The intensity of fluorescence signal acquired from fluorescence imaging is proportional to the amount of biomolecules, while the refractive index obtained from SPR imaging is relative to the concentration of sample, a comparison study of microarrays by these two detection techniques may be of great value. We develop a quasi-confocal parallel scan fluorescence imaging system which has only one moving part and can produce wide-field confocal images. The bacterial 16s rDNA universal primer labeled with CY5 fluorescence agents are used as probes and prepared as a microarray. The DNA-array is detected by both the quasi-confocal parallel scan fluorescence imaging system and the parallel scan spectral SPR imaging system. The results from these two imaging systems were compared and discussed in resolving power, homogeneity, etc. The refractive index information from the SPR imaging system and the fluorescence intensity information from the fluorescence imaging system are linked by bio-array concentration. The measured results can be inter-referred for bio-array studies.
Mortality Among Rocketdyne Workers Who Tested Rocket Engines, 1948–1999

Objective: The objective of this study was to evaluate potential health risks associated with testing rocket engines. Methods: A retrospective cohort mortality study was conducted of 8372 Rocketdyne workers employed 1948 to 1999 at the Santa Susana Field Laboratory (SSFL). Standardized mortality ratios (SMRs) and 95% confidence intervals (CIs) were calculated for all workers, including those employed at specific test areas where particular fuels, solvents, and chemicals were used. Dose–response trends were evaluated using Cox proportional hazards models. Results: SMRs for all cancers were close to population expectations among SSFL workers overall (SMR = 0.89; CI = 0.82–0.96) and test stand mechanics in particular (n = 1651; SMR = 1.00; CI = 0.86–1.16), including those likely exposed to hydrazines (n = 315; SMR = 1.09; CI = 0.75–1.52) or trichloroethylene (TCE) (n = 1111; SMR = 1.00; CI = 0.83–1.19). Nonsignificant associations were seen between kidney cancer and TCE, lung cancer and hydrazines, and stomach cancer and years worked as a test stand mechanic. No trends over exposure categories were statistically significant. Conclusion: Work at the SSFL rocket engine test facility or as a test stand mechanic was not associated with a significant increase in cancer mortality overall or for any specific cancer.
On the Accuracy of Fiber Tractography

Invasive neurosurgical interventions bear the risk of damaging indispensable fiber pathways. Current fiber reconstruction techniques based on diffusion tensor imaging (DTI) do not determine the spatial extent of a fiber bundle in an accurate and reliable manner, due to errors and imprecisions in both the imaging and the algorithmic pipeline. In this thesis, we start by quantifying the errors of current fiber tracking algorithms by means of novel software phantoms which provide a realistic model of neural fiber bundles. This knowledge is used to locally analyze the quality of a patient's diffusion tensor dataset and to construct individual confidence hulls around the tracked fibers. In the following chapter, these ideas are developed further and we suggest an accurate approach to the segmentation of a patient's diffusion tensor image which combines connectivity and tensor clustering information. We then focus our attention on the sensitivity of streamline tractography to user-defined regions of interest. In order to reduce this sensitivity, we demonstrate the feasibility of mapping a fiber bundle from a fiber atlas onto the DTI dataset of a patient. In the last chapter of this thesis, we consider several alternatives to visualize fiber-tracking related uncertainties by means of color-coded streamlines and confidence hulls.
Enriching Bibliographic Data by Combining String Matching and the Wikidata Knowledge Graph to Improve the Measurement of International Research Collaboration

Measuring international research collaboration is necessary when evaluating, for example, the efficacy of policy meant to increase cooperation between countries, but is currently very difficult as bibliographic records contain only affiliation data from which there is no standard method to identify the relevant countries. In this paper we describe a method to address this difficulty, and evaluate it using both general and domain-specific data sets.
Resilient Distributed Parameter Estimation With Heterogeneous Data

This paper studies resilient distributed estimation under measurement attacks. A set of agents each makes successive local, linear, noisy measurements of an unknown vector field collected in a vector parameter. The local measurement models are heterogeneous across agents and may be locally unobservable for the unknown parameter. An adversary compromises some of the measurement streams and changes their values arbitrarily. The agents’ goal is to cooperate over a peer-to-peer communication network to process their (possibly compromised) local measurements and estimate the value of the unknown vector parameter. We present SAGE, the Saturating Adaptive Gain Estimator, a distributed, recursive, consensus + innovations estimator that is resilient to measurement attacks. We demonstrate that, as long as the number of compromised measurement streams is below a particular bound, then, SAGE guarantees that all of the agents’ local estimates converge almost surely to the value of the parameter. The resilience of the estimator – i.e., the number of compromised measurement streams it can tolerate – does not depend on the topology of the inter-agent communication network. Finally, we illustrate the performance of SAGE through numerical examples.