Miracle-dz/UniFAR-FTUs huggingface dataset:
Stippling of 2 D Scalar Fields

We propose a technique to represent two-dimensional data using stipples. While stippling is often regarded as an illustrative method, we argue that it is worth investigating its suitability for the visualization domain. For this purpose, we generalize the Linde–Buzo–Gray stippling algorithm for information visualization purposes to encode continuous and discrete 2D data. Our proposed modifications provide more control over the resulting distribution of stipples for encoding additional information into the representation, such as contours. We show different approaches to depict contours in stipple drawings based on locally adjusting the stipple distribution. Combining stipple-based gradients and contours allows for simultaneous assessment of the overall structure of the data while preserving important local details. We discuss the applicability of our technique using datasets from different domains and conduct observation-validating studies to assess the perception of stippled representations.
Interpreting Gradable Adjectives in Context : Domain Distribution vs . Scalar Representation

Gradable adjectives denote properties that are relativized to context dependent thresholds of application: how long an object must be in order to count as long in a context of utterance depends on what the threshold is. In the typical case, thresholds are uncertain, a feature that distinguishes them from other kinds of contextual parameters. Threshold uncertainty has played a prominent role in discussions of vagueness in philosophy of language, but there has been relativelly little attention to this feature of adjective meaning in linguistic semantics and pragmatics, and correspondingly little attention to a fundamental question about communication with gradable adjectives: what are the principles that govern decisions about threshold values in context, and so determine the communicative content of gradable adjectives in a speech situation? In this paper, we consider two recent answers to this question, which differ in the role that formal properties of adjective meaning play in determining threshold values. On one view, decisions about thresholds are based entirely on probabilisitic prior knowledge of how the objects in a gradable adjective’s domain distribute relative to the scalar property it expresses (Lassiter & Goodman 2014, 2015); according to the second view, a formal property of adjective meaning — scale structure — is primarily responsible for threshold determination (Kennedy 2007, Potts 2008, Qing & Franke 2014a,b). We identify different predictions of the two approaches and present the results of an experimental study that supports the representational approach over the distributional one.
On the Predictability of Radiation Fog Formation in a Mesoscale Model: A Case Study in Heterogeneous Terrain

This study evaluates the predictability of the formation phase of a radiation fog event observed during the night of 31 October 2015 to 01 November 2015 in the north-east of France at three sites managed by OPE (Observatoire Pérenne de l’Environnement). The fog layer shows significantly different behaviors at the three areas, which are located only a few kilometers apart. Three fog life cycles were observed: the formation of a dense adiabatic fog, the formation of a thin patchy fog, or no fog formation despite favorable conditions. This event was studied with the Meso-NH numerical mesoscale model at two horizontal resolutions, 500 m and 50 m. Simulations at 50 m allow estimation of the spread of the predicted parameters over the heterogeneous terrain studied. These numerical simulations strongly suggest that this event involved numerous interactions and complex circulations. The wind above the nocturnal boundary layer greatly affects the transition of shallow patchy fog into thick adiabatic fog. These numerical simulations also show that the occurrence and type of fog could be very different over a small but heterogeneous area. It is also interesting to note that the spread of the simulated parameters was very high during the transition from shallow fog to a deep fog layer. The spread was concentrated during the regime transition between the fog formation and its maturity. This appeared to be the result of the complex interplay of processes at numerous ranges of scale. A new concept called “pseudo-process diagram” is presented. These pseudo-process diagrams are very good tools to analyze fog, and allow a good illustration of the spread of fog during this chaotic phase. This kind of concept seems a promising tool to analyze fog predictability in depth.
Model-based Climate Change Impact Assessment on Water Resources of Kurdistan, Iraq

Kurdistan in northern Iraq, a semi-arid region, predominantly a pastureland, is sustained by Lesser Zab, which is a major tributary of Tigris River. The discharge in the tributary, in recent years, has been experiencing increasing variability contributing to more severe droughts and floods which could be due to climate change. For a proper assessment, SWAT model has been used to capture the impact of climate change on its hydrological components for about half-a-century lead time to 20462064 and about one-century lead time to 2080-2100. The suitability of the model was first evaluated, and then, outputs from six GCMs were incorporated to evaluate the impacts of climate change on water resources under three emission scenarios: A1B, A2 and B1. The results showed worsening water resources regime.
Adaptive gravitational softening in gadget

Cosmological simulations of structure formation follow the collisionless evolution of dark matter starting from a nearly homogeneous field at early times down to the highly clustered configuration at redshift zero. The density field is sampled by a number of particles in number infinitely smaller than those believed to be its actual components, and this limits the mass and spatial scales over which we can trust the results of a simulation. Softening of the gravitational force is introduced in collisionless simulations to limit the importance of close encounters between these particles. The scale of softening is generally fixed and chosen as a compromise between the need for high spatial resolution and the need to limit the particle noise. In the scenario of cosmological simulations, where the density field evolves to a highly inhomogeneous state, this compromise results in an appropriate choice only for a certain class of objects, the others being subject to either a biased or a noisy dynamical description. We have implemented adaptive gravitational softening lengths in the cosmological simulation code gadget-3; the formalism allows the softening scale to vary in space and time according to the density of the environment, at the price of modifying the equation of motion for the particles in order to be consistent with the new dependencies introduced in the system’s Lagrangian. We have applied the technique to a number of test cases and to a set of cosmological simulations of structure formation. We conclude that the use of adaptive softening enhances the clustering of particles at small scales, a result visible in the amplitude of the correlation function and in the inner profile of massive objects, thereby anticipating the results expected from much higher resolution simulations.
Study on backscattering from fish school near pump intake

In this master project, acoustic method was applied for estimating the gradually changed fish density during the crowding near the pump intake in salmon plant. The purpose was to detect if the sensitivity of the echo sounder is feasible for density estimation. The experiment was conducted at the Salmar Innovamar harvesting and processing plant with two 200 kHz single beam echo sounder ? Simrad EK15. Two transducers holding by plates were used to collect the acoustic data. The distance between the plates was set as 4, 3, 2.5 and 1.5m, respectively. The experiment consisted of two parts: the first one was a normal group including two tests conducted during two harvesting periods; the second one was a control test that was done after harvesting in a nearly empty cage. Raw data from the echo sounder were processed by Matlab to extract the power data without range compensation. There were some features of the acoustic results which can be explained with the harvesting operation log. However, the fish density was so great that the acoustic energy was decreased rapidly within a range of 2m, thus it is hard to connect the distribution of power with fish density within the sample volume. Additionally, the volume of the netting was always changed manually and it was impossible to quantify the real density.
Chemo-Diversity and Antiradical Potential of Twelve Matricaria chamomilla L. Populations from Iran: Proof of Ecological Effects

Matricaria chamomilla L. is a popular medicinal herb that is used for healing various diseases and is widely distributed worldwide in temperate climate zones, and even in the subtropical climate of Southern and Western Iran. This study was aimed at comparing the volatile oil constituents, along with antiradical potential and HPLC analysis of methanolic extracts from twelve plant samples growing in Iran. The present research was carried out for the first time on these populations. Among seventeen identified volatile chemicals evaluated by GC/MS and GC/FID, representing 92.73–97.71% of the total oils, α-bisabolone oxide A (45.64–65.41%) was the major constituent, except in case of “Sarableh” as a new chemotype, where (E)- and (Z)-γ-bisabolene (42.76 and 40.08%, respectively) were the predominant components. Oxygenated sesquiterpenes (53.31–74.52%) were the most abundant compounds in the samples excluding “Sarableh” with 91.3% sesquiterpene hydrocarbons. “Sarableh” also exerted the most potent antioxidant capacity with EC50 = 7.76 ± 0.3 µg/mL and 6.51 ± 0.63 mmol TE (Trolox® equivalents)/g. In addition, populations “Lali” and “Bagh Malek” contained the highest amounts of apigenin and luteolin with 1.19 ± 0.01 mg/g and 2.20 ± 0.0 mg/g of plant material, respectively. Our findings depict a clear correlation between phytochemical profiles and antiradical potential of M. chamomilla and geographical factors.
Effect modification by ferritin on the relationship between inflammation and arterial stiffness in hypertensive patients with different glucose tolerance

Backgroud: Ferritin, a crucial element for iron homeostasis, is associated with chronic diseases characterized by subclinical inflammation such as essential arterial hypertension and type 2 diabetes mellitus (T2DM), showing a prognostic value in different clinical settings. We investigated whether ferritin is associated with arterial stiffness (AS), an early indicator of atherosclerosis, and if it could act as effect modifier on the relationship between inflammation and AS in hypertensive patients with different glucose tolerance.Methods: We enrolled 462 newly diagnosed untreated hypertensive (HT) patients. All subjects underwent an oral glucose tolerance test. Insulin sensitivity was assessed by MATSUDA index and ferritin levels were estimated by immunoradiometric assay. AS was definied by carotid-femoral pulse wave velocity (PWV). Results: Out of 462 patients, 271 showed normal glucose tolerance (HT/NGT), 146 impaired glucose tolerance (HT/IGT) and 45 were diabetic (HT/T2DM). Iron levels significantly decreased and transferrin and ferritin significantly increased from the first to the third group. PWV values were significantly higher in HT/IGT and HT/T2DM patients. PWV was related directly with ferritin, high sensitivity C reactive protein (hs-CRP), transferrin, and inversely with MATSUDA index. Ferritin resulted the strongest determinant of PWV explaining a 14.9% of its variation; moreover it was a strong modifier of the relationship between hs-CRP and PWV. The estimated augmentation in PWV portended by a fixed increase in hs-CRP, was higher across increasing values of ferritin.Conclusion: Ferritin represents an independent predictor of AS in our study population and a strong effect modifier on the relationship between inflammation and PWV.
Experimental Investigations of Elimination The Stick-Slip Phenomenon in The Presence of Longitudinal Tangential Vibration

Abstract The article presents a scheme and description of the test stand as well as selected experimental results of the influence of longitudinal tangential vibrations on the stick-slip phenomenon. The tests were carried out at a constant forced vibration frequency f = 2000 Hz, as a function of the amplitude of the vibration velocity va. The position of the sliding body and the drive force necessary to make the body slip and maintain this motion were measured. The measurements were made in two successive stages. In the first stage, when the substrate on which the sliding occurred was stationary. In the second one, the substrate is in a vibrating motion in the direction parallel to the slip. The conducted experimental analyses have shown that longitudinal tangential vibrations can contribute to the reduction or even complete elimination of the stick-slip phenomenon.
Habitat Sim Generic Dataset Support Habitat API Habitat Platform

We present Habitat, a platform for research in embodied artificial intelligence (AI). Habitat enables training embodied agents (virtual robots) in highly efficient photorealistic 3D simulation. Specifically, Habitat consists of: (i) Habitat-Sim: a flexible, high-performance 3D simulator with configurable agents, sensors, and generic 3D dataset handling. Habitat-Sim is fast – when rendering a scene from Matterport3D, it achieves several thousand frames per second (fps) running single-threaded, and can reach over 10,000 fps multi-process on a single GPU. (ii) Habitat-API: a modular high-level library for end-toend development of embodied AI algorithms – defining tasks (e.g. navigation, instruction following, question answering), configuring, training, and benchmarking embodied agents. These large-scale engineering contributions enable us to answer scientific questions requiring experiments that were till now impracticable or ‘merely’ impractical. Specifically, in the context of point-goal navigation: (1) we revisit the comparison between learning and SLAM approaches from two recent works [19, 16] and find evidence for the opposite conclusion – that learning outperforms SLAM if scaled to an order of magnitude more experience than previous investigations, and (2) we conduct the first cross-dataset generalization experiments {train, test}⇥ {Matterport3D, Gibson} for multiple sensors {blind, RGB, RGBD, D} and find that only agents with depth (D) sensors generalize across datasets. We hope that our open-source platform and these findings will advance research in embodied AI.
Location Prediction in a Smart Environment

The context prediction and especially the location prediction is an important feature for improving the performance of smart systems. Predicting the next location or context of the user make the system proactive, so the system will be capable to offer the suitable services to the user without his involving. In this paper, a new approach will be presented based on the combination of pattern technique and Bayesian network to predict the next location of the user. This approach was tested on real data set, our model was able to achieve 89% of the next location prediction accuracy.
Recursive Routing Networks: Learning to Compose Modules for Language Understanding

We introduce Recursive Routing Networks (RRNs), which are modular, adaptable models that learn effectively in diverse environments. RRNs consist of a set of functions, typically organized into a grid, and a meta-learner decision-making component called the router. The model jointly optimizes the parameters of the functions and the meta-learner’s policy for routing inputs through those functions. RRNs can be incorporated into existing architectures in a number of ways; we explore adding them to word representation layers, recurrent network hidden layers, and classifier layers. Our evaluation task is natural language inference (NLI). Using the MultiNLI corpus, we show that an RRN’s routing decisions reflect the high-level genre structure of that corpus. To show that RRNs can learn to specialize to more fine-grained semantic distinctions, we introduce a new corpus of NLI examples involving implicative predicates, and show that the model components become fine-tuned to the inferential signatures that are characteristic of these predicates.
Meet Collaborative Consumption: Paving the way to consumer decision-making in Shared Mobility

Title: Meet Collaborative Consumption: Paving the way to consumer decision-making in Shared Mobility Date of the Seminar: June 1st, 2015 Course: BUSN39: Master Thesis in International Marketing and Brand Management Authors: Iana Starostovich and Alejandro Sánchez Contreras Supervisor: Jon Bertilsson
Investigation of tokamak T-10 globular films microstructure.

Institute for Theoretical and Experimental Physics, Moscow, Russia Introduction Inevitable consequences of graphite limiter utilization in ITER are hydrocarbon films formation on vacuum vessel elements. Therefore one of the key processes, determine of reactor ITER economy in use, is tritium absorption of these films . As it was mentioned earlier [1] in the vacuum chamber of tokamak T-10 have been found out carbon globular films and flakes with friable structure and with big ratio of D/C~0.8. Investigations of this films all over again on an scanning electron microscope (SEM), and then on stationary scanning tunneling (STM) and atomic force (AFM) microscopes, has found out fractality of a surface microstructures, from the characteristic dimentions ~ 100 microns and till the dimentions ~ 10 nanometers. In the report results of research of a surface and internal globular films structure, estimation of a surface fractal dimension, model of films growth are submitted, the reasons of occurrence of such structure are discussed. Experimental conditions for globular films generation. Globular films have been found in two operating modes of T-10 tokamak. It improved confinement mode, in which big carbon flux originated from an internal part of a circular graphite limiter, under action of sputtaring by arcing [2]. And as in a mode without a circular graphite limiter where carbon recycling on a plasma periphery increase on the order of value. Fractal analysis of a globular films surface. The analysis of a surface was carried out by various type of microscope – SEM, STM and a b c d Fig.1. Films images with full size: a-300µm, b-5µm, c-1µm, d-50nm,
Super-Hydrophobic Co–Ni Coating with High Abrasion Resistance Prepared by Electrodeposition

Although super-hydrophobic surfaces have great application prospects in industry, their preparation cost and mechanical durability have limited their practical utilization. In this work, we presented a new low-cost process preparation for super-hydrophobic Co–Ni coating on carbon steel substrate via an electrodeposition route. The deposited Co–Ni coating with cauliflower-shaped micro-nano structures exhibited high super-hydrophobic properties with water contact angles over 161° after modification with 1H,1H,2H,2H-Perfluorooctyltrichlorosilane (PFTEOS). Evaluated by the linear abrasion methods, the super-hydrophobic coating can maintain super-hydrophobicity after abrasion distance of 12 m under the applied pressure of 5 kPa, which was attributed to the high cobalt content of the Co–Ni coating. Moreover, electrochemical tests showed that the super-hydrophobic Co–Ni coatings exhibited a good anti-corrosion performance thus providing an adequate protection to the carbon steel substrates.
Functional and Genetic Diversity of Bacteria Associated with the Surfaces of Agronomic Plants

The main objective of this study was to evaluate the genetic diversity and agricultural significance of bacterial communities associated with the surfaces of selected agronomic plants (carrot, cabbage and turnip). The bacterial diversity of fresh agricultural produce was targeted to identify beneficial plant microflora or opportunistic human pathogens that may be associated with the surfaces of plants. Bacterial strains were screened in vitro for auxin production, biofilm formation and antibiotic resistance. 16S rRNA gene sequencing confirmed the presence of several bacterial genera including Citrobacter, Pseudomonas, Pantoea, Bacillus, Kluyvera, Lysinibacillus, Acinetobacter, Enterobacter, Serratia, Staphylococcus, Burkholderia, Exiguobacterium, Stenotrophomonas, Arthrobacter and Klebsiella. To address the biosafety issue, the antibiotic susceptibility pattern of strains was determined against different antibiotics. The majority of the strains were resistant to amoxicillin (25 µg) and nalidixic acid (30 µg). Strains were also screened for plant growth-promoting attributes to evaluate their positive interaction with colonized plants. Maximum auxin production was observed with Stenotrophomonas maltophilia MCt-1 (101 µg mL−1) and Bacillus cereus PCt-1 (97 µg mL−1). Arthrobacter nicotianae Lb-41 and Exiguobacterium mexicanum MCb-4 were strong biofilm producers. In conclusion, surfaces of raw vegetables were inhabited by different bacterial genera. Potential human pathogens such as Bacillus cereus, Bacillus anthracis, Enterobacter cloacae, Enterobacter amnigenus and Klebsiella pneumoniae were also isolated, which makes the biosafety of these vegetable a great concern for the local community. Nevertheless, these microbes also harbor beneficial plant growth-promoting traits that indicated their positive interaction with their host plants. In particular, bacterial auxin production may facilitate the growth of agronomic plants under natural conditions. Moreover, biofilm formation may help bacteria to colonize plant surfaces to show positive interactions with host plants.
Corrigendum to: ‘Live and Large’: Super-Resolution Optical Fluctuation Imaging (SOFI) and Expansion Microscopy (ExM) of Microtubule Remodelling by Rabies Virus P Protein

The field of super-resolution microscopy continues to progress rapidly, both in terms of evolving techniques and methodologies as well as in the development of new multi-disciplinary applications. Two current drivers of innovation are increasing the possible resolution gain and application in live samples. Super-resolution optical fluctuation imaging (SOFI) is well suited to live samples while expansion microscopy (ExM) enables obtainment of sub-diffraction information via conventional imaging. In this Highlight we provide a brief outline of these methods and report results from application of SOFI and ExM in our on-going study into microtubule remodelling by rabies virus P proteins. We show that MT bundles in live cells transfected with rabies virus P3 protein can be visualised using SOFI in a time-lapse fashion for up to half an hour and can be expanded using current Pro-ExM protocols and imaged using conventional microscopy.
Language Modeling Approaches to Blog Postand Feed Finding

We describe our participation in the TREC 2007 Blog track. In the opinion task we looked at the differences in performance between Indri and our mixture model, the influence of external expansion and document priors to improve opinion finding; results show that an out-of-the-box Indri implementation out- performs our mixture model, and that external expan- sion on a news corpus is very benificial. Opinion find- ing can be improved using either lexicons or the number of comments as document priors. Our approach to the feed distillation task is based on ag- gregating post-level scores to obtain a feed-level rank- ing. We integrated time-based and persistence as- pects into the retrieval model. After correcting bugs in our post-score aggregation module we found that time-based retrieval improves results only marginally, while persistence-based ranking results in substantial improvements under the right circumstances.