Miracle-dz/UniFAR-FTUs huggingface dataset:
Line of sight depth of the Large and Small Magellanic Clouds

Abstract We used the red clump stars from the Optical Gravitational Lensing Experiment (OGLE II) survey and the Magellanic Cloud Photometric Survey (MCPS), to estimate the line-of-sight depth. The observed dispersion in the magnitude and colour distribution of red clump stars is used to estimate the line-of-sight depth, after correcting for the contribution due to other effects. This dispersion due to depth, has a range from minimum dispersion that can be estimated, to 0.46 mag (a depth of 500 pc to 10.44 kpc), in the LMC. In the case of the SMC, the dispersion ranges from minimum dispersion to 0.35 magnitude (a depth of 665 pc to 9.53 kpc). The thickness profile of the LMC bar indicates that it is flared. The average depth in the bar region is 4.0 ± 1.4 kpc. The halo of the LMC (using RR Lyrae stars) is found to have larger depth compared to the disk/bar, which supports the presence of an inner halo for the LMC. The large depth estimated for the LMC bar and the disk suggests that the LMC might have had minor mergers. In the case of the SMC, the bar depth (4.90 ± 1.23 kpc) and the disk depth (4.23 ± 1.48 kpc) are found to be within the standard deviations. We find evidence for an increase in depth near the optical center (up to 9 kpc). On the other hand, the estimated depth for the halo (RR Lyrae stars) and disk (RC stars) for the bar region of the SMC is found to be similar. Thus, increased depth and enhanced stellar as well as H i density near the optical center suggests that the SMC may have a bulge.
Pre- and Post-Processing Sum-of-Squares Programs in Practice

Checking non-negativity of polynomials using sum-of-squares has recently been popularized and found many applications in control. Although the method is based on convex programming, the optimization problems rapidly grow and result in huge semidefinite programs. Additionally, they often become increasingly ill-conditioned. To alleviate these problems, it is important to exploit properties of the analyzed polynomial, and post-process the obtained solution. This technical note describes how the sum-of-squares module in the MATLAB toolbox YALMIP handles these issues.
Formation of alginate nanospheres

This chapter reviews available methods for the formation of alginate nano-aggregates, nanocapsules and nanospheres. Primarily, alginate nanoparticles are being prepared by two methods. In the “complexation method”, complex formation on the interface of an oil droplet is used to form alginate nanocapsules, and complex formation in an aqueous solution is used to form alginate nano-aggregates. In a second method w/o emulsification coupled with gelation of the alginate emulsion droplet can be used to form alginate nanospheres. We review advantages and disadvantages of these methods, and give an overview of the properties of the alginate particles produced with these methods. This chapter has been published with some modifications as: Jerome P. Paques, Erik van der Linden, Cees J. M. van Rijn, Leonard M.C. Sagis. Preparation methods of alginate nanoparticles. Adv. Colloid Interface Sci. 2014, 209, 163-171.
Capacity of Ultra-Wideband Power-Constrained Ad Hoc Networks

In this correspondence, we show that the uniform throughput capacity of an ultra-wideband (UWB) power-constrained ad hoc network is given by , where is the per-node power constraint, is the fading exponent of radio signal and is the number of nodes randomly distributed inside a disk of unit area. This is a stronger result than the upper bound and the lower bound previously shown by Negi and Rajeswaran. Our proof is simple given the prior work by Gupta and Kumar.
A Maximum-Likelihood Surface Estimator for Dense Range Data

Describes how to estimate 3D surface models from dense sets of noisy range data taken from different points of view, i.e., multiple range maps. The proposed method uses a sensor model to develop an expression for the likelihood of a 3D surface, conditional on a set of noisy range measurements. Optimizing this likelihood with respect to the model parameters provides an unbiased and efficient estimator. The proposed numerical algorithms make this estimation computationally practical for a wide variety of circumstances. The results from this method compare favorably with state-of-the-art approaches that rely on the closest-point or perpendicular distance metric, a convenient heuristic that produces biased solutions and fails completely when surfaces are not sufficiently smooth, as in the case of complex scenes or noisy range measurements. Empirical results on both simulated and real ladar data demonstrate the effectiveness of the proposed method for several different types of problems. Furthermore, the proposed method offers a general framework that can accommodate extensions to include surface priors, more sophisticated noise models, and other sensing modalities, such as sonar or synthetic aperture radar.
Globally Optimal Image Segmentation with an Elastic Shape Prior

So far global optimization techniques have been developed independently for the tasks of shape matching and image segmentation. In this paper we show that both tasks can in fact be solved simultaneously using global optimization. By computing cycles of minimal ratio in a large graph spanned by the product of the input image and a shape template, we are able to compute globally optimal segmentations of the image which are similar to a familiar shape and located in places of strong gradient. The presented approach is translation-invariant and robust to local and global scaling and rotation of the given shape. We show how it can be extended to incorporate invariance to similarity transformations. The particular structure of the graph allows for run-time and memory efficient implementations. Highly parallel implementations on graphics cards allow to produce globally optimal solutions in a few seconds only.
Process Integration, Assessment, and Online Monitoring of Biotechnological Itaconic Acid Production

With the gradual establishment of a biobased economy and the imminent switch from petrochemicals to products from renewable resources, the fermentative utilization of sugars and other feedstocks has gained importance within the last years. As one of the most promising value-added chemicals from biomass, itaconic acid has a vast potential in the production of versatile, biobased polymers and the replacement of petrochemical-based materials such as acrylic acid. With regard to biotechnological itaconic acid production, however, new, innovative processes are required to enhance profitability and competitiveness in future markets. Therefore, process integration, assessment, and online monitoring of itaconic acid production were addressed within this thesis. Prior to submerged itaconic acid production, the generation of suitable seed cultures for the cultivation of Aspergillus terreus was investigated. For the most commonly used Czapek-Dox agar medium, a modified formulation was proposed, which reliably induced sporulation without any variability in the observed phenotypes. Subsequently, the cultivation of A. terreus was established in unbaffled shake flasks as well as a laboratory scale bioreactor. Online measurement of the respiratory quotient was found to directly reflect itaconic acid formation. Hence, phases of strong itaconic acid production as well as conditions negatively affecting product formation such as product inhibition could be identified online. To alleviate the negative effect of product inhibition via process integration, the applicability of reactive extraction for in situ product removal was investigated. Initially, the biocompatibility of several solvents was assessed based on their influence on the respiratory activity of A. terreus. As a result, a mixture of the extractant trioctylamine and the diluent isopropyl myristate was chosen for further experiments. As expected, an increase in the amount of trioctylamine increased itaconic acid extraction efficiency. However, the simultaneous increase in pH due to the alkaline properties of trioctylamine attenuated this effect. In addition to reactive extraction, the feasibility of itaconic acid back-extraction into an aqueous trimethylamine solution was confirmed. Finally, reactive extraction was successfully integrated into the cultivation of A. terreus via solvent addition after 63 h. As a consequence of the elevated pH and the reduced amount of itaconic acid, glucose consumption and product
Topological expansion and boundary conditions

In this article, we compute the topological expansion of all possible mixed-traces in a hermitian two matrix model. In other words give a recipe to compute the number of discrete surfaces of given genus, carrying an Ising model, and with all possible given boundary conditions. The method is recursive, and amounts to recursively cutting surfaces along interfaces. The result is best represented in a diagrammatic way, and is thus rather simple to use.
Modern Focused-Ion-Beam-Based Site-Specific Specimen Preparation for Atom Probe Tomography

Abstract Approximately 30 years after the first use of focused ion beam (FIB) instruments to prepare atom probe tomography specimens, this technique has grown to be used by hundreds of researchers around the world. This past decade has seen tremendous advances in atom probe applications, enabled by the continued development of FIB-based specimen preparation methodologies. In this work, we provide a short review of the origin of the FIB method and the standard methods used today for lift-out and sharpening, using the annular milling method as applied to atom probe tomography specimens. Key steps for enabling correlative analysis with transmission electron-beam backscatter diffraction, transmission electron microscopy, and atom probe tomography are presented, and strategies for preparing specimens for modern microelectronic device structures are reviewed and discussed in detail. Examples are used for discussion of the steps for each of these methods. We conclude with examples of the challenges presented by complex topologies such as nanowires, nanoparticles, and organic materials.
Achieving Artificial General Intelligence Through Peewee Granularity

The general intelligence of any autonomous system must in large part be measured by its ability to automatically learn new skills and integrate these with prior skills. Cognitive architectures addressing these topics are few and far between ‐ possibly because of their difficulty. We argue that architectures capable of diverse skill acquisition and integration, and real-time management of these, require an approach of modularization that goes well beyond the current practices, leading to a class of architectures we refer to as peewee-granule systems. The building blocks (modules) in such systems have simple operational semantics and result in architectures that are heterogeneous at the cognitive level but homogeneous at the computational level.
Deep Parsing at the CLEF2014 IE Task

We present an information extraction system for patient records which has been submitted to the ShARe/CLEF eHealth Evaluation Lab 2014 Task 2. The task was information extraction from clinical text in terms of a disease/disorder template filling process. The system uses a lexicalized parser to annotate grammatical relations between diseases, disorders, and other constituents on a sentence level. Grammatical pattern matching rules are applied in order to annotate the specifics of individual disease/disorder cases. High accuracy is most important for clinical decision support; the comparative results suggest that a deep parsing approach is suitable for this task, as we achieved acc = 0.822 and acc = 0.804 for the two runs of the system.
Efficient image stitching of an image sequence by selecting dominate frames

This paper presents an efficient image stitching algorithm with better image quality and less processing time for stitching a continuous image sequence. In the beginning, the blurred image frame is filtered out by considering the variation of its edge amount under different scales. Stitching a lot of frames with similar scene is time-consuming and easily generates the inconsistency in the overlap region between frames. In order to decrease the stitching error and the computational time, the proposed image stitching strategy desires to stitch only several significant frames instead of aligning all frames. The dominant frame with most of the visual content dissimilar to that in the previously stitched result can contribute a lot of new information and is worthy to be stitched. The proposed stitching algorithm has been verified in the on-line experiment to present the efficiency of the overall system.
Performance of Three-Layered Organic Light-Emitting Diodes Using the Hole-Transport and Injection Layer of TPD and Teflon-AF, and the Electron-Injection Layer of Li2CO3 and LiF

The performance of three-layered organic light-emitting diodes (OLEDs) was investigated using TPD hole-transport and injection layers, Teflon-AF, and the electron-injection layer of Li 2 CO 3 and LiF. The OLEDs were manufactured in a structure of TPD/Alq 3 /LiF, TPD/Alq 3 /Li 2 CO 3 , and AF/Alq 3 /LiF using low-molecular organic materials. In three different three-layered OLEDs, it was found that the device with the TPD/Alq 3 /LiF structure shows higher performance in maximum luminance, and maximum external quantum efficiency compared to those of the device with TPD/Alq 3 / Li 2 CO 3 and TPD/Alq 3 /LiF by 35% and 17%, and 193% and 133%, respectively. It is thought that the combined LiF/ Al cathode contributes to a reduced work function and improves an electrical conduction mechanism due to the electron injection rather than the hole transport, which then increases a recombination rate of charge carriers.
A content-based image retrieval system for texture and color queries

A CONTENT-BASED IMAGE RETRIEVAL SYSTEM FOR TEXTURE AND COLOR QUERIES Eyup Sabri Konak M.S. in Computer Engineering Supervisors: Assist. Prof. Dr. Ugur Gudukbay and Assoc. Prof. Dr. Ozgur Ulusoy August, 2002 In recent years, very large collections of images and videos have grown rapidly. In parallel with this growth, content-based retrieval and querying the indexed collections are required to access visual information. Two of the main components of the visual information are texture and color. In this thesis, a content-based image retrieval system is presented that computes texture and color similarity among images. The underlying technique is based on the adaptation of a statistical approach to texture analysis. An optimal set of five second-order texture statistics are extracted from the Spatial Grey Level Dependency Matrix of each image, so as to render the feature vector for each image maximally informative, and yet to obtain a low vector dimensionality for efficiency in computation. The method for color analysis is the color histograms, and the information captured within histograms is extracted after a pre-processing phase that performs color transformation, quantization, and filtering. The features thus extracted and stored within feature vectors are later compared with an intersection-based method. The system is also extended for pre-processing images to segment regions with different textural quality, rather than operating globally over the whole image. The system also includes a framework for object-based color and texture querying, which might be useful for reducing the similarity error while comparing rectangular regions as objects. It is shown through experimental results and precision-recall analysis that the content-based retrieval system is effective in terms of retrieval and scalability.
Optimisation of imaging technique used in direct digital radiography

The purpose of the study was to optimise the technique employed for AP shoulder and lateral cervical spine examinations following an investigation into image quality, based on clinical assessment, and effective dose, calculated from patient entrance surface dose measurements. A study was therefore conducted in an attempt to determine whether the increased radiation dose to the patient following the introduction of an anti-scatter grid was justified by the level of improvement in image quality. The study, involving 100 patients, was able to demonstrate that the increase in radiation dose to the patient when using an anti-scatter grid for AP shoulder examinations is not justified by the improved image quality. A poor level of inter-rater reliability between the consultants scoring the lateral cervical spine images prevented a firm conclusion from being reached. The fact that all images were of diagnostic quality, however, suggested that the use of the anti-scatter grid was unnecessary. Following completion of the project the hospital involved was informed of all findings.
Joint symbol timing and channel estimation for OFDM based WLANs

The orthogonal frequency-division multiplexing access technique has been attracting considerable interest especially for wireless local area networks (WLANs). We consider the joint estimation of the symbol timing, the channel length and the channel-impulse response. A novel estimation algorithm based on maximum-likelihood principles and the generalized Akaike information criterion are proposed. We provide simulation results to illustrate the performance of our proposed algorithm.
Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution

Diluting a sample to obtain a measure within the analytical range is a common task in clinical laboratories. However, for urgent samples, it can cause delays in test reporting, which can put patients’ safety at risk. The aim of this work is to show a simple artificial neural network that can be used to make it unnecessary to predilute a sample using the information available through the laboratory information system. Particularly, the Multilayer Perceptron neural network built on a data set of 16,106 cardiac troponin I test records produced a correct inference rate of 100% for samples not requiring predilution and 86.2% for those requiring predilution. With respect to the inference reliability, the most relevant inputs were the presence of a cardiac event or surgery and the result of the previous assay. Therefore, such an artificial neural network can be easily implemented into a total automation framework to sensibly reduce the turnaround time of critical orders delayed by the operation required to retrieve, dilute, and retest the sample.
EGrid: supporting the control room operation of a utility company with multi-touch tables

This work presents eGrid, a software environment designed for utility companies to enable the collaboration of control center team members in their daily tasks of analyzing and managing the electrical grid of a city. Despite the recent advances in geospatial data analysis applications, the need still arises for the design of innovative applications which facilitate the collaboration of control center team members in discussing problems and finding solutions, eliminating the headache of synchronizing paper maps frequently to reflect the changes made daily in electricity circuits. eGrid utilizes multi-touch digital table-top hardware to allow multiple users to interact concurrently with domain specific geographic information system (GIS) using finger touches and natural hand gestures. It is an advanced prototype of an actual application of tabletop technology in a non-trivial domain. The development of eGrid shows strong buy-in from the intended end-user community.
Two Easy Theories Whose Combination is Hard

We restrict attention to the validity problem for unquantified disjunctions of literals (possibly negated atomic formulae) over the domain of integers, or what is just as good, the satisfiability problem for unquantified conjunctions. When = is the only predicate symbol and all function symbols are left uninterpreted, or when ≤ is the only predicate symbol (taking its standard interpretation on the integers) and the only terms are variables and integers, then satisfiability is decidable in polynomial time. However when ≤ and uninterpreted function symbols are allowed to appear together, satisfiability becomes an NPcomplete problem. This combination of the two theories can arise for example when reasoning about arrays (the uninterpreted function symbols) and subscript manipulation (where ≤ arises in considering subscript bounds). These results are unaffected by the presence of successor, which also arises commonly in reasoning about subscript manipulation.
The Role of Wall Shear Stress in the Assessment of Right Ventricle Hydraulic Workload

Pulmonary hypertension (PH) is a devastating disease affecting approximately 15–50 people per million, with a higher incidence in women. PH mortality is mostly attributed to right ventricle (RV) failure, which results from RV hypotrophy due to an overburdened hydraulic workload. The objective of this study is to correlate wall shear stress (WSS) with hemodynamic metrics that are generally accepted as clinical indicators of RV workload and are well correlated with disease outcome. Retrospective right heart catheterization data for 20 PH patients were analyzed to derive pulmonary vascular resistance (PVR), arterial compliance (C), and an index of wave reflections (Γ). Patient-specific contrast-enhanced computed tomography chest images were used to reconstruct the individual pulmonary arterial trees up to the seventh generation. Computational fluid dynamics analyses simulating blood flow at peak systole were conducted for each vascular model to calculate WSS distributions on the endothelial surface of the pulmonary arteries. WSS was found to be decreased proportionally with elevated PVR and reduced C. Spatially averaged WSS (SAWSS) was positively correlated with PVR (R 2 = 0.66), C (R 2 = 0.73), and Γ (R 2 = 0.5) and also showed promising preliminary correlations with RV geometric characteristics. Evaluating WSS at random cross sections in the proximal vasculature (main, right, and left pulmonary arteries), the type of data that can be acquired from phase-contrast magnetic resonance imaging, did not reveal the same correlations. In conclusion, we found that WSS has the potential to be a viable and clinically useful noninvasive metric of PH disease progression and RV health. Future work should be focused on evaluating whether SAWSS has prognostic value in the management of PH and whether it can be used as a rapid reactivity assessment tool, which would aid in selection of appropriate therapies.