Miracle-dz/UniFAR-FTUs huggingface dataset:
Matching monocular lightweight features using N-gram techniques for topological location identification

SUMMARY In SLAM (simultaneous localization and mapping), the topological paradigm provides a more natural and compact solution that scales better with the size of the environment. Computer vision has always been regarded as the ideal sensor technology for topological feature extraction and description and several methods have been proposed in the literature, but they are either time-consuming, require plenty of different sensors, or are very sensitive to perceptual aliasing, all of which limit their application scope. This paper presents a fast-to-compute collection of features extracted from monocular images, and an adaptive matching procedure for location identification in structured indoor environments inspired by the natural language processing field. Although only dominant vertical lines, color histograms, and a reduced number of keypoints are employed in this paper, the matching framework introduced allows for the incorporation of almost any other type of feature. The results of the experiments carried out in a home and an office environment suggest that the proposed method could be used for real-time topological scene recognition even if the environment changes moderately over time. Due to the combination of complementary features, high precision can be achieved within reasonable computation time by using weaker but faster descriptors.
Comparison of health behaviors among women brothel workers to those of the general population of women in Denmark

ABSTRACT Previous research on behavioral risk factors for illness among sex workers has been limited and based on mixed, poorly defined groups of sex workers. The aim of the present study was to compare the health behaviors and weight of women brothel workers with women in the general population in Denmark. Logistic regression analyses were used to compare data from eighty-eight women working in brothels in 2010 with data from 3,225 women of similar age from the nationally representative Danish Health Survey 2010. Compared to Danish women, the prevalence of daily and heavy smoking was higher among brothel workers, but the prevalence of wanting to quit smoking was lower. The prevalence rates of exceeding the Danish high-risk level of alcohol consumption, binge drinking, and illicit drug use were higher among women brothel workers compared to Danish women. The prevalence of underweight was higher and overweight and obesity lower among brothel workers compared to Danish women. These differences were significant when adjusted for age and educational level. Few differences were noted regarding dietary habits and no differences regarding physical activity. Findings suggest the need for health-promotion initiatives, particularly for smoking, alcohol consumption, and drug use, targeted at women brothel workers.
Toward Developer-like Automated Program Repair — Modification Comparisons between GenProg and Developers

Automated program repair is a way to reduce costs on program debuggingto a large extent. Repair techniques using genetic programming havebeen attracting much attention. They were applied to actual softwaresystems and they were able to fix several dozen of actual faults. However, programs generated by such techniques often include some sourcecode changes not related to fixing a given fault even if they pass allgiven test cases. Furthermore, some researchers found that suchtechniques occasionally induce new faults which are not covered byexisting test cases. The reason why those problems arise is that suchtechniques consider only given test cases. On the other hand, developers consider program behaviors not covered by test cases. Thus, those problems arise less frequently in programs modified by developers. Consequently, the authors suppose that if we make automated programmodifications close to developers' ones, we may be able to relieve thoseproblems. At this moment, there is no research study investigatingdifferences between automated modifications and developers' ones. Inthis paper, we compare GenProg's modifications with developers'ones for the same faults. As a result, we found that developers tend to(1) change more different functions, (2) change control flows in sourcecode, and (3) add/delete more code lines.
sEMG-Based Hand-Gesture Classification Using a Generative Flow Model

Conventional pattern-recognition algorithms for surface electromyography (sEMG)-based hand-gesture classification have difficulties in capturing the complexity and variability of sEMG. The deep structures of deep learning enable the method to learn high-level features of data to improve both accuracy and robustness of a classification. However, the features learned through deep learning are incomprehensible, and this issue has precluded the use of deep learning in clinical applications where model comprehension is required. In this paper, a generative flow model (GFM), which is a recent flourishing branch of deep learning, is used with a SoftMax classifier for hand-gesture classification. The proposed approach achieves 63.86±5.12% accuracy in classifying 53 different hand gestures from the NinaPro database 5. The distribution of all 53 hand gestures is modelled by the GFM, and each dimension of the feature learned by the GFM is comprehensible using the reverse flow of the GFM. Moreover, the feature appears to be related to muscle synergy to some extent.
A trajectory splicing approach to concretizing counterexamples for hybrid systems

This paper examines techniques for finding falsifying trajectories of hybrid systems using an approach that we call trajectory splicing. Many formal verification techniques for hybrid systems, including flowpipe construction, can identify plausible abstract counterexamples for property violations. However, there is often a gap between the reported abstract counterexamples and the concrete system trajectories. Our approach starts with a candidate sequence of disconnected trajectory segments, each segment lying inside a discrete mode. However, such disconnected segments do not form concrete violations due to the gaps that exist between the ending state of one segment and the starting state of the subsequent segment. Therefore, trajectory splicing uses local optimization to minimize the gap between these segments, effectively splicing them together to form a concrete trajectory. We demonstrate the use of our approach for falsifying safety properties of hybrid systems using standard optimization techniques. As such, our approach is not restricted to linear systems. We compare our approach with other falsification approaches including uniform random sampling and a robustness guided falsification approach used in the tool S-Taliro. Our preliminary evaluation clearly shows the potential of our approach to search for candidate trajectory segments and use them to find concrete property violations.
Adaptive finite difference schemes based on interpolating wavelets for solving 2D Maxwell’s equations

This paper describes a 2D application of interpolating wavelets and recursive interpolation schemes with thresholding, aiming the representation of the electric and magnetic fields in nonuniform, adaptive grids. Applied to Maxwell's equations, the method leads to sparse grids that adapt in space to the local smoothness of the fields, and at the same time track the evolution of the fields over time. In general, the number of points in the grid, Ns, is below the maximum number of points, N. It is possible to control Ns, by trading off representation accuracy and data compression, and therefore speed. A numerical example is presented showing the propagation of a Gaussian pulse within a 2D horn.
MadT: A Memory Access Detection Tool for Symbolic Memory Profiling

Tools for memory access detection are widely used, playing an important role especially in real-time systems. For example, on multi-core platforms, the problem of co-scheduling CPU and memory resources with hard real-time constraints requires a deep understanding of the memory access patterns of the deployed taskset. While code execution flow can be analyzed by considering the control-flow graph and reasoning in terms of basic blocks, a similar approach cannot apply to data accesses. In this paper, we propose MadT, a tool that uses a novel mechanism to perform memory access detection of general purpose applications. MadT does not perform binary instrumentation and always executes application code natively on the platform. Hence it can operate entirely in user-space without sand-boxing the task under analysis. Furthermore, MadT provides detailed symbolic information about the accessed memory structures, so it is able to translate the virtual addresses to their original symbolic variable names. Finally, it requires no modifications to application source code. The proposed methodology relies on existing OS-level capabilities. In this paper, we describe how MadT can be implemented on commercial hardware and we compare its performance with state-of-the-art software techniques for memory access detection.
Regarding the Amazing Choreography of Clathrin Coats

The growth of contemporary cell biology is due in large part to technological advances. In the 1950s, electron micrographs of thin sections first provided unrivaled in situ views of the delicate intracellular architecture and fine structure of organelles, whereas new subcellular fractionation methods gave access to various biochemical components—especially proteins—enriched in different cellular fractions. A central tenet that emerged from these pioneering studies is that the intracellular biosynthetic and endocytic membrane systems of eukaryotic cells are functionally interconnected, and exchange of material between them often occurs in small (50–100 nm diameter), roughly spherical membranous transport vesicles. In electron micrographs, these vesicles are typically seen in close proximity to a membrane compartment and are frequently covered on their cytosolic face with a fuzzy proteinaceous coating. Subsequent technical advances facilitated further discovery and progress: genetic screens in model organisms and refinement of subcellular fractionation to facilitate cell-free reconstitution of transport reactions allowed the identification and purification of key regulatory and structural components. Persuasively, many of the genes discovered in genetic screens encoded the proteins purified biochemically. More recently, genome sequencing and proteomics efforts have bolstered the identification of sorting components, leading to long lists of evolutionarily conserved proteins that are involved in specific sorting operations at different membranes.
Wi-fi in ad hoc mode: a measurement study

In this paper we investigate the performance of IEEE 802.11b ad hoc networks by means of an experimental study. This analysis reveals several aspects that are usually neglected in simulation studies. Firstly, since different transmission rates are used for control and data frames, different transmission ranges and carrier-sensing ranges may exist at the same time in the network. In addition, the transmission ranges are in practice much shorter than usually assumed in simulation analysis, not constant but highly variable (even in the same session) and depends on several factors (i.e., mobile height, interference condition, etc.). Finally, exploiting our performance measurements, we present a channel model for an 802.11 network that indicates virtual carrier sensing is generally not necessary and the RTS/CTS mechanism only introduces additional overhead.
Finding your way in the testing jungle: a learning approach to web security testing

Black-box security testing of web applications is a hard problem. The main complication lies in the black-box assumption: The testing tool has limited insight into the workings of server-side defenses. This has traditionally led commercial as well as research vulnerability scanners toward heuristic approaches, such as testing each input point (e.g. HTTP parameter) with a short, predefined list of effective test payloads to balance between coverage and performance. We take a fresh approach to the problem of security testing, casting it into a learning setting. In our approach, the testing algorithm has available a comprehensive database of test payloads, such that if the web application's defenses are broken, then with near certainty one of the candidate payloads is able to demonstrate the vulnerability. The question then becomes how to efficiently search through the payload space to find a good candidate. In our solution, the learning algorithm infers from a failed test---by analyzing the website's response---which other payloads are also likely to fail, thereby pruning substantial portions of the search space. We have realized our approach in XSS Analyzer, an industry-level cross-site scripting (XSS) scanner featuring 500,000,000 test payloads. Our evaluation on 15,552 benchmarks shows solid results: XSS Analyzer achieves >99% coverage relative to brute-force traversal over all payloads, while trying only 10 payloads on average per input point. XSS Analyzer also outperforms several competing algorithms, including a mature commercial algorithm---featured in IBM Security AppScan Standard V8.5---by a far margin. XSS Analyzer has recently been integrated into the latest version of AppScan (V8.6) instead of that algorithm.
UNR/CSDE1 Expression Is Critical to Maintain Invasive Phenotype of Colorectal Cancer through Regulation of c-MYC and Epithelial-to-Mesenchymal Transition

CSDE1 (cold shock domain containing E1) gene is located upstream of the N-RAS locus, and codes for an RNA-binding protein named Upstream of N-Ras (UNR). In cancer, CSDE1 has been shown to regulate c-Fos, c-Myc, Pten, Rac1, or Vimentin. UNR/CSDE1 has been studied in breast, melanoma, pancreatic and prostate cancer. Then, the aim of this study is to evaluate the role of CSDE1/UNR in colorectal cancer progression and maintenance of aggressive phenotype. We firstly evaluated UNR/CSDE1 expression in human colon cancer derived cell lines and patient samples. Subsequently, we performed functional experiments by UNR/CSDE1 downregulation. We also evaluated UNR/CSDE1 prognostic relevance in two independent sets of patients. Not only was UNR/CSDE1 expression higher in tumor samples compared to untransformed samples, but also in colonospheres and metastatic origin cell lines than their parental and primary cell lines, respectively. Downregulation of UNR/CSDE1 reduced cell viability and migration throughout a restrain of epithelial-to-mesenchymal transition and increases sensitivity to apoptosis. Interestingly, high UNR/CSDE1 expression was associated with poor prognosis and correlated positively with c-MYC expression in colorectal cancer samples and cell lines. Here, we show for the first time compelling data reporting the oncogenic role of UNR/CSDE1 in human colorectal cancer.
Which Gait Parameters and Walking Patterns Show the Significant Differences Between Parkinson’s Disease and Healthy Participants?

This study investigated the difference in the gait of patients with Parkinson’s disease (PD), age-matched controls and young controls during three walking patterns. Experiments were conducted with 24 PD, 24 age-matched controls and 24 young controls, and four gait intervals were measured using inertial measurement units (IMU). Group differences between the mean and variance of the gait parameters (stride interval, stance interval, swing interval and double support interval) for the three groups were calculated and statistical significance was tested. The results showed that the variance in each of the four gait parameters of PD patients was significantly higher compared with the controls, irrespective of the three walking patterns. This study showed that the variance of any of the gait interval parameters obtained using IMU during any of the walking patterns could be used to differentiate between the gait of PD and control people.
Rewarming Injury after Cold Preservation

Organ dysfunction pertinent to tissue injury related to ischemic ex vivo preservation during transport from donor to recipient still represents a pivotal impediment in transplantation medicine. Cold storage under anoxic conditions minimizes metabolic activity, but eventually cannot prevent energetic depletion and impairment of cellular signal homeostasis. Reoxygenation of anoxically injured tissue may trigger additional damage to the graft, e.g., by abundant production of oxygen free radicals upon abrupt reactivation of a not yet equilibrated cellular metabolism. Paradoxically, this process is driven by the sudden restoration of normothermic conditions upon reperfusion and substantially less pronounced during re-oxygenation in the cold. The massive energy demand associated with normothermia is not met by the cellular systems that still suffer from hypothermic torpor and dys-equilibrated metabolites and eventually leads to mitochondrial damage, induction of apoptosis and inflammatory responses. This rewarming injury is partly alleviated by preceding supply of oxygen already in the cold but more effectively counteracted by an ensuing controlled and slow oxygenated warming up of the organ prior to implantation. A gentle restitution of metabolic turnover rates in line with the resumption of enzyme kinetics and molecular homeostasis improves post transplantation graft function and survival.
SocialCircuits: the art of using mobile phones for modeling personal interactions

We describe SocialCircuits, a platform capable of measuring the face-to-face and phone-based communication network of a real-world community. This platform uses commodity mobile phones to measure social ties between individuals, and uses long and short term surveys to measure the shifts in individual habits, opinions, health, and friendships influenced by those ties. We also describe the flagship experiment using this platform, a year-long study of an entire university undergraduate dormitory. Lastly, we discuss some of the key challenges we met in building and deploying the platform, including mobile phone hardware and software selection, privacy considerations, community selection and recruitment, and techniques for minimizing data loss.
Effectiveness of Nitrification and Denitrification Processes in Biofilters Treating Wastewater from De-Icing Airport Runways

The basic factors determining the efficiency of the removal of nitrogen and carbon compounds from airport wastewater containing de-icing agents are low temperature and the C/N ratio (carbon to nitrogen ratio). Biofilm reactors (biofilters) create better conditions for nitrification and denitrification than suspended biomass reactors. The scope of the study included determination of the influence of the C/N ratio in the wastewater on nitrification, denitrification and organic compound removal in biofilm reactors depending on the temperature. The experiment was performed in 24 circular laboratory biofilters with LECA (Light Expanded Clay Aggregates) filling. The study was divided into three series differing in organic carbon loading. In each series, carried out at the same hydraulic retention time, biofilters were operated at 25, 8, 4 or 0 °C. The study showed the effective removal of nitrogen compounds across a very wide temperature range. The applied filling and properly selected operating parameters of the reactors resulted in effective simultaneous nitrification and denitrification. The highest efficiency of nitrogen removal at 0 °C (34.57 ± 4.54%) was obtained at the C/N ratio of 0.5 gC/gN. The efficiency of denitrification (the lowest at the temperature of 0 °C) increased as the temperature and C/N ratio increased in the wastewater.
A composite registration framework for respiratory motion modelling from 4D MRI

4D MRI is current gaining attention as an imaging modality which is able to capture inter-cycle variability of respiratory motion. Such information is beneficial for example in radiotherapy planning and delivery. However the motion extracted from 4D MRI is dependant on the method of processing the images. Typically a deformable registration algorithm is used so that the 3D motion of every point in the image can be found. We have used several popular registration algorithms which have been recently published with publicly available data. Our findings suggest that due to the low contrast of 4D MRI, the registration is only accurate near clear boundaries, and less accurate elsewhere, to different degrees depending on the algorithm used. We thus suggest modelling organ deformation as an affine transformation, which is then embedded into the deformation field for more accurate modelling of respiratory motion.
Enhanced Proliferation, Survival, and Dopaminergic Differentiation of CNS Precursors in Lowered Oxygen

Standard cell culture systems impose environmental oxygen (O2) levels of 20%, whereas actual tissue O2 levels in both developing and adult brain are an order of magnitude lower. To address whether proliferation and differentiation of CNS precursors in vitro are influenced by the O2 environment, we analyzed embryonic day 12 rat mesencephalic precursor cells in traditional cultures with 20% O2 and in lowered O2 (3 ± 2%). Proliferation was promoted and apoptosis was reduced when cells were grown in lowered O2, yielding greater numbers of precursors. The differentiation of precursor cells into neurons with specific neurotransmitter phenotypes was also significantly altered. The percentage of neurons of dopaminergic phenotype increased to 56% in lowered O2 compared with 18% in 20% O2. Together, the increases in total cell number and percentage of dopaminergic neurons resulted in a ninefold net increase in dopamine neuron yield. Differential gene expression analysis revealed more abundant messages for FGF8, engrailed-1, and erythropoietin in lowered O2. Erythropoietin supplementation of 20% O2cultures partially mimicked increased dopaminergic differentiation characteristic of CNS precursors cultured in lowered O2. These data demonstrate increased proliferation, reduced cell death, and enhanced dopamine neuron generation in lowered O2, making this method an important advance in the ex vivogeneration of specific neurons for brain repair.