Miracle-dz/UniFAR-FTUs huggingface dataset:
F EATURE E XTRACTION U SING C ONTOUR P ROJECTION

This paper describes the set of evaluation tests performed over the feature extraction technique proposed by the authors in [11]. As explained in [11], the technique was mainly developed to deal with the problem of cursive character recognition. It is based on projection of the image contour over the edges of a surrounding regular polygon placed around each character. The surrounding polygon can be of any number of sides, from triangle up to the circle. The feature vector is formed by the perpendicular distance taken from each edge of the polygon up to the contour of the image. The evaluation under this investigation compares the proposed approach using two different polygons: square and hexagon, and five different number of projection lines taken over each edge, against two versions of bitmap coding, one taken with the original image and other after its thinning. The power of discrimination of each case is examined through the usage of a MLP model of neural network. Despite its ability to discriminate the patterns, the proposed method is also good in dealing with scale, rotation and translation problems.
CQARE: Contrastive Question-Answering for Few-shot Relation Extraction with Prompt Tuning

Prompt tuning with pre-trained language mod-001 els (PLM) has exhibited outstanding perfor-002 mance by closing the gap between pre-training 003 tasks and various downstream applications, 004 without the need for uninitialized parameters 005 to be introduced. However, prompt tuning 006 requires vast amounts of prompt engineering 007 and predefined label word mapping, which ob-008 structs its implements in practice. Besides, the 009 ample label space makes prompt tuning more 010 arduous and challenging when it comes to re-011 lation extraction (RE). To tackle these issues, 012 we propose a Contrastive Question-Answering 013 method with prompt tuning for few-shot RE 014 (CQARE). CQARE carries out a RE task-015 specific pre-training with four entity-relation-016 aware pre-training objects, including a prompt 017 pre-training to automatically generate contin-018 uous prompts. The proposed pre-training can 019 provide more robust initialization with prompt 020 tuning while maintaining semantic consistency 021 with the proposed PLM. Furthermore, CQARE 022 can effectively avoid label words mapping by 023 reformulating RE as contrastive question an-024 swering. The results indicate CQARE raising 025 averaged accuracy of 5.11% on a cross-domain 026 few-shot dataset, demonstrating that robust ini-027 tialization is crucial for prompt tuning and ef-028 fective contrastive question answering. 029
DISCONTINUOUS GENERALIZED QUASI-VARIATIONAL INEQUALITIES WITH APPLICATION TO FIXED POINTS

We consider the following generalized quasi-variational inequality problem introduced in [7]: given a real normed space $X$ with topological dual $X^*$, two sets $C,D\subseteq X$ and two multifunctions $S:C\to 2^D$ and $\,T:C\to 2^{X^*}$, find $(\hat x,\hat\varphi)\in C\times X^*$ such that $$\hat x\in S(\hat x),\quad\hat\varphi\in T(\hat x)\quad{\rm and}\quad \langle\hat\varphi,\hat x-y\rangle\le 0\quad{\rm for\ all}\quad y\in S(\hat x). $$ We prove an existence theorem where $\,T$ is not assumed to have any continuity or monotonicity property, improving some aspects of the main result of [\chulin]. In particular, the coercivity assumption is meaningfully weakened. As an application, we prove a theorem of the alternative for the fixed points of a Hausdorff lower semicontinuous multifunction. In particular, we obtain sufficient conditions for the existence of a fixed point which belongs to the relative boundary of the corresponding value.
3D object retrieval and segmentation: various approaches including 2D poisson histograms and 3D electrical charge distributions.

Nowadays 3D models play an important role in many applications: viz. games, cultural heritage, medical imaging etc. Due to the fast growth in the number of available 3D models, understanding, searching and retrieving such models have become interesting fields within computer vision. In order to search and retrieve 3D models, we present two different approaches: one is based on solving the Poisson Equation over 2D silhouettes of the models. This method uses 60 different silhouettes, which are automatically extracted from different viewangles. Solving the Poisson equation for each silhouette assigns a number to each pixel as its signature. Accumulating these signatures generates a final histogram-based descriptor for each silhouette, which we call a SilPH (Silhouette Poisson Histogram). For the second approach, we propose two new robust shape descriptors based on the distribution of charge density on the surface of a 3D model. The Finite Element Method is used to calculate the charge density on each triangular face of each model as a local feature. Then we utilize the Bag-of-Features and concentric sphere frameworks to perform global matching using these local features. In addition to examining the retrieval accuracy of the descriptors in comparison to the state-of-the-art approaches, the retrieval speeds as well as robustness to noise and deformation on different datasets are investigated. On the other hand, to understand new complex models, we have also utilized distribution of electrical charge for proposing a system to decompose models into meaningful parts. Our robust, efficient and fully-automatic segmentation approach is able to specify the segments attached to the main part of a model as well as locating the boundary parts of the segments. The segmentation ability of the proposed system is examined on the standard datasets and its timing and accuracy are compared with the existing state-of-the-art approaches.
TWO MORE CANDIDATE AM CANUM VENATICORUM (AM CVn) BINARIES FROM THE SLOAN DIGITAL SKY SURVEY

AM CVn systems are a select group of ultracompact binaries with the shortest orbital periods of any known binary subclass; mass transfer is likely from a low-mass (partially-)degenerate secondary onto a white dwarf primary, driven by gravitational radiation. In the past few years, the Sloan Digital Sky Survey (SDSS) has provided five new AM CVns. Here we report on two further candidates selected from more recent SDSS data. SDSS J1208+3550 is similar to the earlier SDSS discoveries, recognized as an AM CVn via its distinctive spectrum which is dominated by helium emission. From the expanded SDSS Data Release 6 (DR6) spectroscopic area, we provide an updated surface density estimate for such AM CVns of order 10−3.1–10−2.5 deg−2 for 15 < g < 20.5. In addition, we present another new candidate AM CVn, SDSS J2047+0008, which was discovered in the course of follow-up of SDSS-II supernova candidates. It shows nova-like outbursts in multi-epoch imaging data; in contrast to the other SDSS AM CVn discoveries, its (outburst) spectrum is dominated by helium absorption lines, reminiscent of KL Dra, and 2003aw. The variability selection of SDSS J2047+0008 from the 300 deg2 of SDSS Stripe 82 presages further AM CVn discoveries in future deep, multicolor, and time-domain surveys such as the Large Synoptic Survey Telescope (LSST). The new additions bring the total SDSS yield to seven AM CVns thus far, a substantial contribution to this rare subclass, versus the dozen previously known.
Continuous Processing of Micropellets via Hot-Melt Extrusion

Microparticulate drug delivery systems, e.g., micropellets (MPs), are used in a variety of pharmaceutical formulations such as suspensions, injectable systems, and capsules. MPs are currently manufactured mainly via batch, solvent-based processes, e.g., spray-drying and solvent evaporation-extraction. In this paper, we present a novel, solvent-free, continuous hot-melt extrusion–based approach with an inline cold pelletization step and the potential of unprecedented on-the-fly formulation changes, aiming at producing the smallest particles usable for injectable applications. A biodegradable, crystalline dispersion consisting of poly(DL-lactic acid) (PLA) filled with metformin as the model drug was chosen on purpose to elucidate the broad applicability of the process also to formulations with limited stretchability and complex pelletizability. Next to optical/statistical particle analyses and in-line high-speed camera investigations providing insights into the pelletization process, the injectability of the most promising micropellets was compared to that of one marketed formulation. Fast extrudate haul-off speeds and high numbers of pelletizer knives resulted in particles with a narrow and small particle size distribution with a d50 below 270 µm and aspect ratios close to 1. To omit protruding drug particles to ensure sufficient extrudate stretchability and allow for the smallest MPs, it was found that the d90 of the embedded drug must be significantly below the extrudate diameter. Upon adapting the syringe diameter, the produced micropellets revealed similar injectability parameters to the marketed formulation, showcasing the potential that the proposed setup has for the manufacturing of novel microparticulate formulations.
Mutating Sample Solutions to Improve Prolog Exercise Tasks and Their Test Suites

: We report on a tool for analyzing and adapting test suites for Prolog in an educational setting. The key idea is to mutate a known-correct sample solution in order to “simulate” possible student mistakes, and use that to “harden” the test suite that an e-learning system uses for judging submissions and giving feedback.
GAIA: A WINDOW TO LARGE-SCALE MOTIONS

Using redshifts as a proxy for galaxy distances, estimates of the two-dimensional (2D) transverse peculiar velocities of distant galaxies could be obtained from future measurements of proper motions. We provide the mathematical framework for analyzing 2D transverse motions and show that they offer several advantages over traditional probes of large-scale motions. They are completely independent of any intrinsic relations between galaxy properties; hence, they are essentially free of selection biases. They are free from homogeneous and inhomogeneous Malmquist biases that typically plague distance indicator catalogs. They provide additional information to traditional probes that yield line-of-sight peculiar velocities only. Further, because of their 2D nature, fundamental questions regarding vorticity of large-scale flows can be addressed. Gaia, for example, is expected to provide proper motions of at least bright galaxies with high central surface brightness, making proper motions a likely contender for traditional probes based on current and future distance indicator measurements.
Effect of solute segregation on shear-induced grain boundary motion

Atomic-scale simulations are performed to study the effect of solute segregation on the shear-induced motion of select grain boundaries in the classical $\alpha$-Fe/C system. At shear rates larger than the solute diffusion rate, we observe a transition from coupled motion to sliding. Below a critical solute excess, the boundaries break away from the solute cloud and move in a coupled motion. At smaller shear rates, we observe extrinsic coupled motion at small stresses indicating that the coupling is aided by convective solute diffusion along the boundary. Our studies underscore the role of solutes in modifying the bicrystallography, temperature and rate dependence of shear accommodation at grain boundaries.
Case Series: Are the centriacinar nodulary pattern related to Covid-19 Pneumonia?

Introduction: Throughout the world, during the pandemic process, Thorax Computed Tomography (CT) contributed to the diagnosis with higher sensitivity than laboratory tests in COVID-19 pneumonia. Material and Methods: During the pandemic period, 224 COVID-19 Pneumonia cases were followed in our chest diseases clinic. Throughout the pandemic, thorax CT was performed in all cases according to World Health, Organization, European Radiology Association and health ministry guidelines. Thorax CT’s of the cases were evaluated and reported by a Radiologist and a Chest Diseases Specialist. Cases with a rare COVID-19 finding with a centracinar nodule were collected. Results: Demographic data, symptoms, physical examination findings, rt-PCR test results, posteroanterior chest x-ray findings and Thorax CT findings of the cases followed in our clinic were recorded. During the 3-month period, 224 cases were followed in the chest diseases clinic. Sentriacinar nodule pattern was observed in thorax CT in 11 cases. Conclusions: Our case series is presented in terms of the necessity to investigate the case in terms of COVID-19 pneumonia with symptoms and findings in patients with a rare pattern of centriacinar nodule.
Soil pH and plant diversity shape land snail communities in intensively-managed montane and subalpine meadows

Grassland management practices in mountainous regions are often constrained by complex topography and a lack of accessibility for agricultural machinery but little is known about the response of invertebrate communities to the intensification of farming with respect to natural environmental contexts. This study explored the factors influencing the composition of land snail communities in intensively-managed mountain meadows in the SW Swiss Alps (Valais). Land snails were chosen because of their low mobility, making them suitable indicators of small-scale habitat conditions. Variables related to topography, soil properties, vegetation, surrounding landscape and agricultural management were recorded in situ or obtained from interviews with farmers. Generalised linear mixed models were used to analyse the effects of these variables on snail density, species richness and the occurrence of red-listed species, while community composition was investigated using a multivariate model-based approach. Soil pH was the most important factor at our study sites, with high pH values being indicative of a limestone substrate that facilitates the monopolisation of this mineral for shell formation. Snail density and species richness decreased with elevation, probably as a result of shorter periods of activity. Plant diversity favoured the abundance of most snail species, suggesting a higher structural complexity or more diverse food supplies. Remarkably, grassland intensification did not seem to affect snail density, but a 45% loss in species richness is observed in plots having undergone farming intensification in the long run. Based on these results, we recommend maintaining a good proportion of extensively-managed grasslands in areas devoted to pasturing or hay production in order to support the most sensitive species that typically disappear with management intensification.
Morphology Informed Selections for Subword Vocabulary Size

Currently, guidance around selection of an opti-001 mal or appropriate subword vocabulary size is 002 incomplete and confusing at best. Using a mea-003 sure of subword-morpheme overlap, our analy-004 sis shows that one can find a "sweet spot" for 005 a morphology informed subword vocabulary 006 size. This sweet spot exhibits some variation 007 with respect to text complexity and the morpho-008 logical characteristics of a language. However, 009 it is relatively constant with respect to corpus 010 size. 011
Mechanised Robust Safety for Virtual Machines Communicating above FF-A

—Thin hypervisors make it possible to isolate key security components like keychains, ﬁngerprint readers, and digital wallets from the easily-compromised operating system. To work together, virtual machines running on top of the hypervisor can make hypercalls to the hypervisor to share pages between each other in a controlled way. However, the design of such a hypercall ABI remains a delicate balancing task between conﬂicting needs for expressivity, performance, and security. In particular, it raises the question of what makes the speciﬁcation of a hypervisor, and of its hypercall ABIs, good enough for the virtual machines. In this paper, we validate the expressivity/security balance of the design of the hypercall ABIs of Arm’s FF-A. We formalise a substantial fragment of FF-A as a machine with a simpliﬁed ISA in which hypercalls are steps of the machine. We then develop a separation logic, which we prove sound with respect to the machine execution model, and use it to reason modularly about virtual machines which communicate through the hypercall ABIs, demonstrating the hypercall ABIs’ expressivity. Moreover, we use the logic to prove robust safety of communicating virtual machines, that is, that even if some of the virtual machines are compromised and execute unknown code, then they cannot break the safety properties of other virtual machines running known code. This demonstrates the intended security guarantees of the hypercall ABIs. All the results in the paper have been formalised in Coq using the Iris framework.
Subsonic Panel Method for Designing Wing Surfaces From Pressure Distribution

An iterative method has been developed for designing wing section contours corresponding to a prescribed subcritical distribution of pressure. The calculations are initialized by using a surface panel method to analyze a baseline wing or wing-fuselage configuration. A first-order expansion to the baseline panel method equations is then used to calculate a matrix containing the partial derivative of potential at each control point with respect to each unknown geometry parameter. In every iteration cycle, the matrix is used both to calculate the geometry perturbation and to analyze the perturbed geometry. The distribution of potential on the perturbed geometry is established by simple linear extrapolation from the baseline solution. The extrapolated potential is converted to pressure by Bernoulli's equation. Not only is the accuracy of the approach good for very large perturbations, but the computing cost of each complete iteration cycle is substantially less than one analysis solution by a conventional panel method.
Transverse momentum spectra and nuclear modification factors of charged particles in Xe-Xe collisions at root s(NN)=5.44 TeV The ALICE collaboration

The ALICE Collaboration , Acharya , S , Brücken , E J , Chang , B , Hilden , T E , Kim , D J , Litichevskyi , V , Mieskolainen , M M , Orava , R , Parkkila , J E , Rak , J , Räsänen , S S , Saarinen , S , Slupecki , M , Snellman , T W , Trzaska , W H , Vargyas , M & Viinikainen , J 2019 , ' Transverse momentum spectra and nuclear modification factors of charged particles in Xe-Xe collisions at root s(NN)=5.44 TeV ' , Physics Letters B , vol. 788 , pp. 166-179 . https://doi.org/10.1016/j.physletb. 2018.10. 052
Too Much Accessibility is Harmful! Automated Detection and Analysis of Overly Accessible Elements in Mobile Apps

Mobile apps, an essential technology in today’s world, should provide equal access to all, including 15% of the world population with disabilities. Assistive Technologies (AT), with the help of Accessibility APIs, provide alternative ways of interaction with apps for disabled users who cannot see or touch the screen. Prior studies have shown that mobile apps are prone to the under-access problem, i.e., a condition in which functionalities in an app are not accessible to disabled users, even with the use of ATs. We study the dual of this problem, called the over-access problem, and defined as a condition in which an AT can be used to gain access to functionalities in an app that are inaccessible otherwise. Over-access has severe security and privacy implications, allowing one to bypass protected functionalities using ATs, e.g., using VoiceOver to read notes on a locked phone. Over-access also degrades the accessibility of apps by presenting to disabled users information that is actually not intended to be available on a screen, thereby confusing and hindering their ability to effectively navigate. In this work, we first empirically study overly accessible elements in Android apps and define a set of conditions that can result in over-access problem. We then present OverSight, an automated framework that leverages these conditions to detect overly accessible elements and verifies their accessibility dynamically using an AT. Our empirical evaluation of OverSight on real-world apps demonstrates OverSight’s effectiveness in detecting previously unknown security threats, workflow violations, and accessibility issues.
Gated Recursive and Sequential Deep Hierarchical Encoding for Detecting Incongruent News Articles

With the increase in misinformation across digital platforms, incongruent news detection is becoming an important research problem. Earlier, researchers have exploited various feature engineering approaches and deep learning models with embedding to capture incongruity between news headlines and their respective bodies. Studies have broadly considered different combinations of bag-of-words-based features, sequential encoding, hierarchical encoding, headline-guided attention-based encoding, and so on, of the text in headlines and bodies. In this article, we focus on addressing two important limitations observed with hierarchical encoding and headline-guided attention-based encoding methods. The existing hierarchical encoding-based studies limit the hierarchical structure of the body of a news article to paragraph level only, undermining the importance of incorporating long-term dependence from word level to sentence, paragraph, and body. Furthermore, the existing headline-guided attention-based encoding focuses on contextually similar contents in the body of the headline, undermining the importance of incorporating contextually dissimilar contents. Motivated by the above observations, this article proposes a gated recursive and sequential deep hierarchical encoding (GraSHE) method for detecting incongruent news articles by extending the hierarchical structure of the news body from the body to the word level and incorporating incongruity weight. From various experimental setups over three publicly available benchmarks datasets, the experimental results indicate that the proposed model outperforms baseline models with bag-of-word-based features, sequential, hierarchical, and headline-guided attention-based encoding methods. To further validate the performance of the proposed model, we conduct several ablation studies. The following key observations can be made from the ablation study: 1) models with hierarchical encoding outperform models with nonhierarchical encoding; 2) recursive encoding of sentences boosts the performance of models as compared with sequential encoding of sentences within paragraphs; and 3) incongruent news article detection is domain-dependent. Incorporating explicit features further boosts the performance of proposed model and also decreases the domain dependence of models.