Miracle-dz/UniFAR-FTUs huggingface dataset:
Unique Structural Modifications Are Present in the Lipopolysaccharide from Colistin-Resistant Strains of Acinetobacter baumannii

ABSTRACT Acinetobacter baumannii is a nosocomial opportunistic pathogen that can cause severe infections, including hospital-acquired pneumonia, wound infections, and sepsis. Multidrug-resistant (MDR) strains are prevalent, further complicating patient treatment. Due to the increase in MDR strains, the cationic antimicrobial peptide colistin has been used to treat A. baumannii infections. Colistin-resistant strains of A. baumannii with alterations to the lipid A component of lipopolysaccharide (LPS) have been reported; specifically, the lipid A structure was shown to be hepta-acylated with a phosphoethanolamine (pEtN) modification present on one of the terminal phosphate residues. Using a tandem mass spectrometry platform, we provide definitive evidence that the lipid A isolated from colistin-resistant A. baumannii MAC204 LPS contains a novel structure corresponding to a diphosphoryl hepta-acylated lipid A structure with both pEtN and galactosamine (GalN) modifications. To correlate our structural studies with clinically relevant samples, we characterized colistin-susceptible and -resistant isolates obtained from patients. These results demonstrated that the clinical colistin-resistant isolate had the same pEtN and GalN modifications as those seen in the laboratory-adapted A. baumannii strain MAC204. In summary, this work has shown complete structure characterization including the accurate assignment of acylation, phosphorylation, and glycosylation of lipid A from A. baumannii, which are important for resistance to colistin.
Coarse-to-Fine Segmentation with Shape-Tailored Continuum Scale Spaces

We formulate an energy for segmentation that is designed to have preference for segmenting the coarse over fine structure of the image, without smoothing across boundaries of regions. The energy is formulated by integrating a continuum of scales from a scale space computed from the heat equation within regions. We show that the energy can be optimized without computing a continuum of scales, but instead from a single scale. This makes the method computationally efficient in comparison to energies using a discrete set of scales. We apply our method to texture and motion segmentation. Experiments on benchmark datasets show that a continuum of scales leads to better segmentation accuracy over discrete scales and other competing methods.
Spam Mobile Apps

The increased popularity of smartphones has attracted a large number of developers to offer various applications for the different smartphone platforms via the respective app markets. One consequence of this popularity is that the app markets are also becoming populated with spam apps. These spam apps reduce the users’ quality of experience and increase the workload of app market operators to identify these apps and remove them. Spam apps can come in many forms such as apps not having a specific functionality, those having unrelated app descriptions or unrelated keywords, or similar apps being made available several times and across diverse categories. Market operators maintain antispam policies and apps are removed through continuous monitoring. Through a systematic crawl of a popular app market and by identifying apps that were removed over a period of time, we propose a method to detect spam apps solely using app metadata available at the time of publication. We first propose a methodology to manually label a sample of removed apps, according to a set of checkpoint heuristics that reveal the reasons behind removal. This analysis suggests that approximately 35% of the apps being removed are very likely to be spam apps. We then map the identified heuristics to several quantifiable features and show how distinguishing these features are for spam apps. We build an Adaptive Boost classifier for early identification of spam apps using only the metadata of the apps. Our classifier achieves an accuracy of over 95% with precision varying between 85% and 95% and recall varying between 38% and 98%. We further show that a limited number of features, in the range of 10--30, generated from app metadata is sufficient to achieve a satisfactory level of performance. On a set of 180,627 apps that were present at the app market during our crawl, our classifier predicts 2.7% of the apps as potential spam. Finally, we perform additional manual verification and show that human reviewers agree with 82% of our classifier predictions.
Morpheus: Variability-Aware Refactoring in the Wild

Today, many software systems are configurable with conditional compilation. Just like any software system, configurable systems need to be refactored in their evolution, but their inherent variability induces an additional dimension of complexity that is not addressed well by current academic and industrial refactoring engines. To improve the state of the art, we propose a variability-aware refactoring approach that relies on a canonical variability representation and recent work on variability-aware analysis. The goal is to preserve the behavior of all variants of a configurable system, without compromising general applicability and scalability. To demonstrate practicality, we developed Morpheus, a sound, variability-aware refactoring engine for C code with preprocessor directives. We applied Morpheus to three substantial real-world systems (Busybox, OpenSSL, and SQLite) showing that it scales reasonably well, despite of its heavy reliance on satisfiability solvers. By extending a standard approach of testing refactoring engines with support for variability, we provide evidence for the correctness of the refactorings implemented.
The Metabolic Syndrome and Risk of Sudden Cardiac Death: The Atherosclerosis Risk in Communities Study

Background Prior studies have demonstrated a link between the metabolic syndrome and increased risk of cardiovascular mortality. Whether the metabolic syndrome is associated with sudden cardiac death is uncertain. Methods and Results We characterized the relationship between sudden cardiac death and metabolic syndrome status among participants of the ARIC (Atherosclerosis Risk in Communities) Study (1987–2012) free of prevalent coronary heart disease or heart failure. Among 13 168 participants, 357 (2.7%) sudden cardiac deaths occurred during a median follow‐up of 23.6 years. Participants with the metabolic syndrome (n=4444) had a higher cumulative incidence of sudden cardiac death than those without it (n=8724) (4.1% versus 2.3%, P<0.001). After adjustment for participant demographics and clinical factors other than components of the metabolic syndrome, the metabolic syndrome was independently associated with sudden cardiac death (hazard ratio, 1.70, 95% confidence interval, 1.37–2.12, P<0.001). This relationship was not modified by sex (interaction P=0.10) or race (interaction P=0.62) and was mediated by the metabolic syndrome criteria components. The risk of sudden cardiac death varied according to the number of metabolic syndrome components (hazard ratio 1.31 per additional component of the metabolic syndrome, 95% confidence interval, 1.19–1.44, P<0.001). Of the 5 components, elevated blood pressure, impaired fasting glucose, and low high‐density lipoprotein were independently associated with sudden cardiac death. Conclusions We observed that the metabolic syndrome was associated with a significantly increased risk of sudden cardiac death irrespective of sex or race. The risk of sudden cardiac death was proportional to the number of metabolic syndrome components.
A Chain‐Code‐Based Map Matching Algorithm for Wheelchair Navigation

Accurate vehicle tracking is essential for navigation systems to function correctly. Unfortunately, GPS data is still plagued with errors that frequently produce inaccurate trajectories. Research in map matching algorithms focuses on how to efficiently match GPS tracking data to the underlying road network. This article presents an innovative map matching algorithm that considers the trajectory of the data rather than merely the current position as in the typical map matching case. Instead of computing the precise angle which is traditionally used, a discrete eight‐direction chain code, to represent a trend of movement, is used. Coupled with distance information, map matching decisions are made by comparing the differences between trajectories representing the road segments and GPS tracking data chain‐codes. Moreover, to contrast the performance of the chain‐code algorithm, two evaluation strategies, linear and non‐linear, are analyzed. The presented chain‐code map matching algorithm was evaluated for wheelchair navigation using university campus sidewalk data. The evaluation results indicate that the algorithm is efficient in terms of accuracy and computational time.
Influence of aging time and temperature on diffusion of alloyed copper

Purpose: The aim of this study is to determine the impact of aging time and temperature on the diffusion process of alloying elements inside alloyed copper CuCr0,7, CuFe2 and CuTi4. Design/methodology/approach: It was assumed the activation energy for diffusion of small interstitial atoms is smaller than for large substitute atoms. To determine the influence of aging time and temperature on diffusion of alloying elements in binary copper-based alloys CuCr0,7, CuFe2 and CuTi4 it has been necessary to develop a suitable mathematical model. It has been shown that with the increase of time t, the diffusion pathway L is increased, but the impact of time is not as large as the effect forced by altering temperature. In general, multiple increase of time is equivalent to increasing the temperature by a few degrees. Findings: The model should be used to estimate the average atom pathway of chromium, iron or titanium in copper matrix, caused by diffusion, and the diffusion path into the grain boundary without adsorption as a function of time and temperature aging Research limitations/implications: The model should be used to calculate the influence of temperature and time of aging on the atoms diffusion pathway of the alloying elements in the selected alloyed copper types. Practical implications: The results allow to calculate the average atom pathway L (with reasonable error level) for which the diffused atoms achieve the amount of free energy required to overcome the energetic barrier, on the basis of a combination of heat treatment parameters. Originality/value: This paper presents the impact of the aging temperature on diffusion in the alloyed copper CuCr0.7, CuFe2 and CuTi4.
Multi 3D camera mapping for predictive and reflexive robot manipulator trajectory estimation

With advancing technologies, robotic manipulators and visual environment sensors are becoming cheaper and more widespread. However, robot control can be still a limiting factor for better adaptation of these technologies. Robotic manipulators are performing very well in structured workspaces, but do not adapt well to unexpected changes, like people entering the workspace. We present a method combining 3D Camera based workspace mapping, and a predictive and reflexive robot manipulator trajectory estimation to allow more efficient and safer operation in dynamic workspaces. In experiments on a real UR5 robot our method has proven to provide shorter and smoother trajectories compared to a reactive trajectory planner in the same conditions. Furthermore, the robot has successfully avoided any contact by initialising the reflexive movement even when an obstacle got unexpectedly close to the robot. The main goal of our work is to make the operation more flexible in unstructured dynamic workspaces and not just avoid obstacles, but also adapt when performing collaborative tasks with humans in the near future.
Minimac2: Faster Genotype Imputation

UNLABELLED Genotype imputation is a key step in the analysis of genome-wide association studies. Upcoming very large reference panels, such as those from The 1000 Genomes Project and the Haplotype Consortium, will improve imputation quality of rare and less common variants, but will also increase the computational burden. Here, we demonstrate how the application of software engineering techniques can help to keep imputation broadly accessible. Overall, these improvements speed up imputation by an order of magnitude compared with our previous implementation. AVAILABILITY AND IMPLEMENTATION minimac2, including source code, documentation, and examples is available at http://genome.sph. umich.edu/wiki/Minimac2
Solving Poisson ’ s equation using dataflow computing

Student number: 4424093 Project duration: September, 2016 – September, 2017 Thesis committee Applied Mathematics: Prof. dr. ir. Kees Vuik, TU Delft Dr. rer nat. Matthias Möller, TU Delft, supervisor Prof. dr. ir. Georgi Gaydadjiev, TU Delft, Maxeler Prof. dr. ir. Hai Xiang Lin TU Delft Thesis committee Computer Engineering: Dr. ir. Arjan van Genderen, TU Delft Prof. dr. ir. Georgi Gaydadjiev, TU Delft, Maxeler, supervisor Dr. rer nat. Matthias Möller, TU Delft
Rolling Shutter Camera Synchronization with Sub-millisecond Accuracy

A simple method for synchronization of video streams with a precision better than one millisecond is proposed. The method is applicable to any number of rolling shutter cameras and when a few photographic flashes or other abrupt lighting changes are present in the video. The approach exploits the rolling shutter sensor property that every sensor row starts its exposure with a small delay after the onset of the previous row. The cameras may have different frame rates and resolutions, and need not have overlapping fields of view. The method was validated on five minutes of four streams from an ice hockey match. The found transformation maps events visible in all cameras to a reference time with a standard deviation of the temporal error in the range of 0.3 to 0.5 milliseconds. The quality of the synchronization is demonstrated on temporally and spatially overlapping images of a fast moving puck observed in two cameras.
Developmental differences in relations between parent-reported executive function and unitized and non-unitized memory representations during childhood

Previous research has documented an association between executive functioning (EF) and memory for bound details. However, it is unknown if this relation varies as a function of the type of bound information (i.e., unitized versus non-unitized) and whether this association changes as a function of age during childhood, when both EF and memory undergo rapid development. The current study sought to address these gaps by examining whether relations between parent-reported EF differed for unitized versus non-unitized memory representations and if these relations differed between children who were 4, 6, or 8 years of age. Results revealed that EF was selectively associated with non-unitized associative memory in 8-year-old children; no significant relations between EF and either memory condition were evident in 4- or 6-year-olds. These results suggest relations between EF and memory may be specific to non-unitized representations and that this association may emerge across childhood as both EF and memory abilities develop.
Determination of magnetic resonance imaging biomarkers for multiple sclerosis treatment effects

Identifying specific structures of the brain where pathology differs between groups of subjects may aid to develop imagingbased markers for disease diagnosis. We propose a new technique for doing multivariate statistical analysis on white matter tracts with sheet like shapes. Previous works assume tube-like shapes, not always suitable for modelling the white matter tracts of the brain. The tract-oriented technique aimed at group studies, integrates the usage of multivariate features and outputs a single value of significance indicating tract-specific differences. This is in contrast to voxel based analysis techniques which outputs a significance per voxel basis, and requires multiple comparison correction. We demonstrate our technique by comparing a group of controls with a group of Multiple Sclerosis subjects obtaining significant differences on 11 different fascicle structures.
Soft exfoliation of 2D SnO with size-dependent optical properties

Two-dimensional (2D) materials have recently gained unprecedented attention as potential candidates for next-generation (opto)electronic devices due to their fascinating optical and electrical properties. Tin monoxide, SnO, is an important p-type semiconductor with applications across photocatalysis (water splitting) and electronics (transistors). However, despite its potential in several important technological applications, SnO remains underexplored in its 2D form. Here we present a soft exfoliation strategy to produce 2D SnO nanosheets with tunable optical and electrical properties. Our approach involves the initial synthesis of layered SnO microspheres, which are readily exfoliated through a low-power sonication step to form high quality SnO nanosheets. We demonstrate that the properties of 2D SnO are strongly dependent on its dimensions. As verified through optical absorption and photoluminescence studies, a strong size-dependent quantum confinement effect in 2D SnO leads to substantial variation in its optical and electrical properties. This results in a remarkable (>1 eV) band gap widening in atomically thin SnO. Through photoconductivity measurements, we further validate a strong correlation between the quantum-confined properties of 2D SnO and the selective photoresponse of atomically thin sheets in the high energy UV light. Such tunable semiconducting properties of 2D SnO could be exploited for a variety of applications including photocatalysis, photovoltaics and optoelectronics in general.
A novel hardware logic encryption technique for thwarting illegal overproduction and Hardware Trojans

Hardware piracy is a threat that is becoming more and more serious these last years. The different types of threats include mask theft, illegal overproduction, as well as the insertion of malicious alterations to a circuit, referred to as Hardware Trojans. To protect circuits from overproduction, circuits can be encrypted so that only authorized users can use the circuits. In this paper, we propose an encryption technique that also helps thwarting Hardware Trojan insertion. Assuming that an attacker will attach a Hardware Trojan to signals with low controllability in order to make it stealthy, the principle of the encryption is to minimize the number of signals with low controllability.
Relative Abundance of and Composition within Fungal Orders Differ between Cheatgrass (Bromus tectorum) and Sagebrush (Artemisia tridentata)-Associated Soils

Nonnative Bromus tectorum (cheatgrass) is decimating sagebrush steppe, one of the largest ecosystems in the Western United States, and is causing regional-scale shifts in the predominant plant-fungal interactions. Sagebrush, a native perennial, hosts arbuscular mycorrhizal fungi (AMF), whereas cheatgrass, a winter annual, is a relatively poor host of AMF. This shift is likely intertwined with decreased carbon (C)-sequestration in cheatgrass-invaded soils and alterations in overall soil fungal community composition and structure, but the latter remain unresolved. We examined soil fungal communities using high throughput amplicon sequencing (ribosomal large subunit gene) in the 0–4 cm and 4–8 cm depth intervals of six cores from cheatgrass- and six cores from sagebrush-dominated soils. Sagebrush core surfaces (0–4 cm) contained higher nitrogen and total C than cheatgrass core surfaces; these differences mirrored the presence of glomalin related soil proteins (GRSP), which has been associated with AMF activity and increased C-sequestration. Fungal richness was not significantly affected by vegetation type, depth or an interaction of the two factors. However, the relative abundance of seven taxonomic orders was significantly affected by vegetation type or the interaction between vegetation type and depth. Teloschistales, Spizellomycetales, Pezizales and Cantharellales were more abundant in sagebrush libraries and contain mycorrhizal, lichenized and basal lineages of fungi. Only two orders (Coniochaetales and Sordariales), which contain numerous economically important pathogens and opportunistic saprotrophs, were more abundant in cheatgrass libraries. Pleosporales, Agaricales, Helotiales and Hypocreales were most abundant across all libraries, but the number of genera detected within these orders was as much as 29 times lower in cheatgrass relative to sagebrush libraries. These compositional differences between fungal communities associated with cheatgrass- and sagebrush-dominated soils warrant future research to examine soil fungal community composition across more sites and time points as well as in association with native grass species that also occupy cheatgrass- invaded ecosystems.
Detecting Turnarounds in Sentiment Analysis: Thwarting

Thwarting and sarcasm are two uncharted territories in sentiment analysis, the former because of the lack of training corpora and the latter because of the enormous amount of world knowledge it demands. In this paper, we propose a working definition of thwarting amenable to machine learning and create a system that detects if the document is thwarted or not. We focus on identifying thwarting in product reviews, especially in the camera domain. An ontology of the camera domain is created. Thwarting is looked upon as the phenomenon of polarity reversal at a higher level of ontology compared to the polarity expressed at the lower level. This notion of thwarting defined with respect to an ontology is novel, to the best of our knowledge. A rule based implementation building upon this idea forms our baseline. We show that machine learning with annotated corpora (thwarted/nonthwarted) is more effective than the rule based system. Because of the skewed distribution of thwarting, we adopt the Areaunder-the-Curve measure of performance. To the best of our knowledge, this is the first attempt at the difficult problem of thwarting detection, which we hope will at least provide a baseline system to compare against.
RecSys Challenge 2017: Offline and Online Evaluation

The ACM Recommender Systems Challenge 20171 focused on the problem of job recommendations: given a new job advertisement, the goal was to identify those users who are both (a) interested in getting notified about the job advertisement, and (b) appropriate candidates for the given job. Participating teams had to balance between user interests and requirements for the given job as well as dealing with the cold-start situation. For the first time in the history of the conference, the RecSys challenge offered an online evaluation: teams first had to compete as part of a traditional offline evaluation and the top 25 teams were then invited to evaluate their algorithms in an online setting, where they could submit recommendations to real users. Overall, 262 teams registered for the challenge, 103 teams actively participated and submitted together more than 6100 solutions as part of the offline evaluation. Finally, 18 teams participated and rolled out recommendations to more than 900,000 users on XING2.
Finite Element Modeling and Biomechanical Analysis of Eyeball and Extraocular Muscles

Finite element analysis (FEA) plays an important role in the biomechanical field. In this paper, we used FEA method in the area of ophthalmology. We generated an eyeball - extraocular muscles (EOMs) model and converted it to meet the need of FEA process. We exerted outside forces on the structure for nonlinear computation and achieved the distributions of displacement, stress and strain. The results corresponded with the basic theory of ophthalmology. We also put forward some related aspects for discussion and advanced studies