Miracle-dz/UniFAR-FTUs huggingface dataset:
An Open-Domain Web Search Engine for Answering Comparative Questions

We present an open-domain web search engine that can help answer comparative questions like ”Is X better than Y for Z? ” by providing argumentative documents. Building such a system requires multiple steps that each includes non-trivial challenges. State-of-the-art search engines do not perform very well on these tasks, and approaches to solve it are part of current research. We present a system to process the following tasks: Detection of comparative relations in a comparative question, ﬁnding claims and arguments relevant to answering comparative questions and scoring the relevance, support and credibility of a website. We follow a rule-based syntactic NLP approach for the comparative relation extraction. To measure the relevance of a document, we combine results from the existing models BERT and CAM. Those results are reused to determine the support through an evidence-based approach, while the credibility consists of a multitude of scores. With this approach, we achieved the best NDCG@5 of all systems participating in task 2 of the Touch´e Lab on Argument Retrieval at CLEF 2020.
Plant Species Identification Using Transfer Learning - PlantCLEF 2020

Automated prediction of plant species from images is immensely useful to conservationists, especially in the case of data-scarce regions of biodiversity. The PlantCLEF 2020 Challenge provides a platform for the creation of a classiﬁer to identify plant species from a large collection of labelled images. The aim of the challenge is to identify which methods work best on the same data, and hence accelerate research progress in the ﬁeld. In this paper, we discuss the submissions made by our team to the challenge, based on transfer learning. For our submissions, we trained our models on Cloud TPUs and TPU Pods available on Google Cloud Platform. All our models, which were initially trained on the ImageNet Dataset, were ﬁne-tuned to the PlantCLEF 2020 Dataset using transfer learning. With our ResNet-50 models, we achieved an over-all MRR of 0.008 in the testing phase. For speciﬁcally chosen classes with fewer training samples, we achieved an MRR of 0.003.
"Draw us how smartphones, video gaming consoles, and robotic vacuum cleaners look like from the inside": students' conceptions of computing system architecture

From a constructivistic perspective on learning, it is essential to build on learners' previous knowledge in learning scenarios. Since computing system hardware design and principles of computing system organization constitute key parts of computer science classes, the identification of respective pre-conceptions is one of the core areas of computer science education. According to cognitive science learning aspects, the knowledge of the individual parts of which such systems are composed plays a decisive role in understanding them. Thus, this paper presents a self-contained substudy of secondary school students' mental modelling of computing systems with special focus on what we conceptualize as part-whole-thinking. Sixty eight secondary school students were asked to draw their conceptions of what three exemplary computing systems (smartphones, video gaming consoles, and robotic vacuum cleaners) look like from the inside. A content analysis of the 204 drawings received was carried out from evaluative, quantitative, and qualitative points of view. From the mental models expressed by the students in their drawings, insights into common conceptions are derived. Looking ahead, recommendations can be implicated from the main results.
A study of high school computer science teacher confidence levels

There has been a growing body of work emerging about effective professional development (PD) models for CS but less research has been conducted around measuring teachers' noncognitive constructs. It is acknowledged that confidence is an essential element of teacher professional performance. In his work Bandura linked teacher self-efficacy to performance in the classroom. Bandura's self-efficacy theory states that an individual's certainty in his or her own capabilities leads to positive interactions with his or her environments. In this study we share our experiences of measuring teacher confidence levels to teach a CS curriculum. This study shares the learning outcomes teachers have most and least confidence teaching, the tools and technologies teachers have most and least confidence using effectively and how these confidence levels change over a two-year PD programme.
Ensemble Model for Profiling Fake News Spreaders on Twitter

Capturing millions of users round the globe, social media has become one of the most popular means of communication and information sharing. Yet, using social media such as Facebook, WhatsApp, Twitter, and Instagram is like a double-edged sword. On one side is the easy accessible, low cost and rapid dissemination of information simultaneously to the large audience while on the other side is the dangerous exposure of fake news. The large spread of fake news has the potential for creating extremely negative impacts on individuals and society. Hence, detecting fake news spreader is the need of the day. To tackle this problem, this paper presents an Ensemble model for profiling fake news spreaders on Twitter which allows using multiple heterogeneous classifiers and combining the results of these classifiers just like a team decision rather than an individual decision. The first step in building the model is to extract three feature sets namely, Unigram TFIDF, N-gram TF and Doc2vec from the PAN 2020 fake news spreader dataset and applying feature reduction on Unigram TFIDF and N-gram TF. Two Linear SVC classifiers and a Logistic Regression classifier are built using three feature sets and are ensembled using majority voting. The results obtained on PAN 2020 test set are encouraging.
CoLe and LYS at BioASQ MESINESP8 Task: Similarity based Descriptor Assigment in Spanish

In this paper, we describe our participation in the MESINESP Task of the BioASQ biomedical semantic indexing challenge. The participating system follows an approach based solely on conventional information retrieval tools. We have evaluated various alternatives for extracting index terms from IBECS/LILACS documents in order to be stored in an Apache Lucene index. Those indexed representations are queried using the contents of the article to be annotated and a ranked list of candidate labels is created from the retrieved documents. We also have evaluated a sort of limited Label Powerset approach which creates meta-labels joining pairs of DeCS labels with high co-occurrence scores, and an alternative method based on label profile matching. Results obtained in official runs seem to confirm the suitability of this approach for languages like Spanish.
Re-use of programming patterns or problem solving?: representation of scratch programs by TGraphs to support static code analysis

Novice programmers seem to learn basic programming skills amazingly fast by using visual programming environments like Scratch or Snap. Yet at a second glance, in many cases, the students' programming projects make use of pre-learned solution patterns like collision detection. Aiming to investigate how far such pre-learned patterns are used and adapted, we have to analyze the program structure of a substantially large number of Scratch projects, e.g. from the Scratch repository, in a very detailed way. To automate the static code analysis of these projects, we developed a scheme to transform Scratch projects into a common graph format (TGraph), which was used up to now to analyze programs in Java and Haskell as well as UML diagrams and mathematical solutions. In a second step, this representation enabled us to apply a SQL-like query language for graphs (GReQL) to detect programming patterns in students' Scratch projects. This paper describes the design of our TGraph scheme for Scratch as well as how to query patterns in Scratch code using GReQL, in order to stimulate the use of this methodology by other researchers. As a feasibility study, we report its application on the outcomes of one of our Scratch courses attended by 143 children aged 8-12 years. The study showed that with the presented methodology any code structure can be detected in Scratch projects. To check the validity of the methodology, the programs were additionally checked manually for the occurrence of two patterns - the results were consistent.
Using short-term surveys and mark–recapture to estimate diversity and population size of orchid bees in forest formations of the Brazilian savanna

ABSTRACT Studies on the diversity and population dynamics of euglossine bees in forest formations of the Brazilian savanna can be notably informative considering that most species are forest-dependent. The current study aimed to estimate the diversity and population size of euglossine bees using short-term surveys and the mark–recapture method. We also compared short-term surveys with monthly surveys over a 1-year period (long-term surveys) to assess the species diversity. The study occurred in seven forest formations of the Brazilian savanna. We collected 14 species and marked 375 males but recaptured only 23 (6.1%). The population size of Euglossa bees ranged from 111.1 ± 34.4 to 1384.5 ± 384.6 males. The diversity indices achieved through the short-term surveys were similar to or higher than those obtained from long-term studies. The low recapture rate of euglossine males seems to be the result of their long-distance dispersal capacity. We also proposed that short-term surveys be viewed as a favourable alternative to long-term studies on diversity estimation and that euglossine bees can occur in small populations in some forest formations studied.
Lung-Wise Tuberculosis Analysis and Automatic CT Report Generation with Hybrid Feature and Ensemble Learning

This article presents the proposed methodology for tuberculosis analysis and generation of the computerized report by using 3D Computed Tomography (CT) images, apropos to the ImageCLEF tuberculosis CT report generation task. The contribution of this paper is based on the combination of handcrafted and non-handcrafted feature extraction strategies. Experiments show that more informative input representation can be obtained by combing diﬀerent feature extraction strategies that lead to improved performance. In this work, non-handcrafted features mined by using a ﬁne-tuned version of a pre-trained VGG19 model and handcrafted features extracted using Local Binary Pattern (LBP), Haralick, and Intensity Histogram (IH) descriptors. Extracted features combined by using early fusion and ﬁnal probability estimation performed with an ensemble-based soft voting approach. The proposed methodology achieved a 70.5% mean area under the curve AUC and ranked 6th on the leaderboard for best participation by each group. The proposed approach can be further improved by adopting optimized feature selection and fusion techniques.
KU-CST at the Profiling Fake News spreaders Shared Task

In this document we present our approach for proﬁling fake news spreaders. The model relies on semantic features, part-of-speech tag related features and other simple features. We have reached an accuracy of 0 . 697 and 0 . 810 for English and Spanish, respectively, on validation data. Test accuracies using these same models reach 0 . 690 and 0 . 725 for English and Spanish data. We believe that this is a simple and robust model that could potentially be used as a baseline for this task.
HCP-MIC at VQA-Med 2020: Effective Visual Representation for Medical Visual Question Answering

This paper describes our submission for the Medical Domain Visual Question Answering Task of ImageCLEF 2020. We desert complex cross-modal fusion strategies and concentrate on how to capture the eﬀective visual representation, due to the information inequality between images and questions in this task. Based on the observation of long-tailed distribution in the training set, we utilize the bilateral-branch network with a cumulative learning strategy to tackle this issue. Besides, to alleviate the issue of limited training data, we design an approach to extend the training set by Kullback-Leibler divergence. Our proposed method achieved the score with 0.426 in accuracy and 0.462 in BLEU, which ranked 4th in the competition. Our code is publicly available 1 .
The cultural impact of navigation design in global e-commerce

Purpose: The present paper investigates the effect of the navigation design (static or dynamic) in e-commerce. Specifically, a comparison is made of consumers from two cultures: the Dutch and the Greek. Methods: A total of 221 Dutch and Greek subjects participated in an experimental survey, where they judged an online search page of a hotel booking website. The study had a 2x2 between-subjects design with the factors navigation design (dynamic or static) and cultural background (Dutch or Greek). The primary dependent variable was the behavioural intention to use (the website). The hedonic and utilitarian attitudes were the mediators. Results: The analysis of the results showed that the navigation design preferences are culturally affected and influence the consumers' attitudes and behavioural intentions. The static navigation design was perceived as less useful, compared to the dynamic navigation design. For the Dutch group the dynamic navigation was more persuasive than the static one, whereas for the Greek group no significant difference was found. Implications: As a future recommendation, localising the websites' content should be considered in global e-commerce, especially when it comes to the hospitality and hotel industry, in order to avoid unintended effects that a specific navigation design may have on the targeted audiences.
Ultrasonic NDT of wind turbine blades using guided waves

In order fully to exploit energy of wind power the construction elements of the wind turbine should be inspected periodically. Ultrasonic air-coupled technique using guided waves has been selected for inspection of wind turbine blades, because only one side access is enough and no contact is needed. Dispersion curves of phase velocities as well as leakage losses versus frequency were calculated using numerical global matrix model. Taking into account the results of the performed simulations the frequency of the ultrasonic transducers was selected to be 290 kHz due to non-dispersive region of phase velocities. The ultrasonic air-coupled technique using guided waves was used for investigation of the artificial internal defects in the wind turbine blade. These defects (diameter 19 mm and 49 mm) were made on the internal side of the main spar. From the ultrasonically obtained images it is possible to recognise the geometry of defects and to estimate approximate dimensions of the defects.
Online Dynamic B-Matching ∗ With Applications to Reconﬁgurable Datacenter Networks

This paper initiates the study of online algorithms for the maximum weight b -matching problem, a generalization of maximum weight matching where each node has at most b ≥ 1 adjacent matching edges. The problem is motivated by emerging optical technologies which allow to enhance datacenter networks with reconﬁgurable matchings, providing direct connectivity between frequently communicating racks. These additional links may improve network performance, by leveraging spatial and temporal structure in the workload. We show that the underlying algorithmic problem features an intriguing connection to online paging (a.k.a. caching), but introduces a novel challenge. Our main contribution is an online algorithm which is O ( b )- competitive; we also prove that this is asymptotically optimal. We complement our theoretical results with extensive trace-driven simulations, based on real-world datacenter workloads as well as synthetic traﬃc traces.
Advances in Nanoscience and Nanotechnology

Plastic is one of the most used materials in the food packaging industry and is essential to food processing [1]. Its global use is mainly because of its versatility, lightness, high mechanical strength, low cost, and consumer-friendliness. Moreover, plastic accomplishes the primary purpose of food packaging which is, maintaining the safety from hazards and quality of food [2]. But plastic waste is one of the biggest environmental problems today and one of the largest contributors comes from the food packaging industry [3]. To solve these problems or at least reduce them requires the cooperation of government, society, industry, and science. The government must create the strategic plans and the financial incentives, the scientific community, with the funds, will develop the alternative products which are then mass-produced by the industry towards the society that will use the alternative products. Without one of these sectors, the whole problem will not be tackled efficiently. Strategic plans for this problem already exist, such as the European strategy for plastics reduction and the scientific community over the last few years has presented several alternatives to replace plastics [4]. The plastic industry, nowadays, is keen on changing their production of plastic to renewable and biodegradable polymers from natural resources thanks to the incentives from the government, and society is more aware of the problem than ever in history and is trying to make some real change, after all, we don’t have a planet B.
Investigation of nanogenerators composed of zinc oxide nanostructures prepared by thermal oxidation of metal zinc

We used the glass, sit all and polyimide substrates. Grown nanostructures were applied to fabricate the nanogenerators using the piezoelectric effect. It was found that the more developed nanostructures grow on inhomogeneities of the gold-zinc interfaces. Internal resistance of fabricated nanogenerators significantly influences on the produced electrical signal. Generated voltage of grown nanogenerators was from 0.4 V up to 1.3 V depending on the voltage applied to the exciting transducers. Structure and electrical properties of grown systems were studied. This paper shows the possibility to use zinc oxide nanostructures as nanogenerators as the acoustic signal sensors.
The Purification and Partial Characterization of the Surface Polysaccharides from Three Fast-Growing Rhizobium japonicum Strains

The fast-growing strains of R. japonicum were originally isolated from China. They are acid-producing Rhizobia and are capable of nodu­ lating soybeans. These isolates share a common host-specificity (Peking soybean) with the slow-growing R. japonicum strains even though their biochemical properties are more closely related to other fast­ growing Rhizobium species. The surface polysaccharides from three fast­ growing R. japonicum strains--USDA201, USDA205, and HC205--were isolated and partially characterized. Strain HC205 is a nod mutant of USDA205 which lacks the symbiotic plasmid. These surface polysaccharides con­ sist of extracellular, capsular and lipopolysaccharides (EPSs, CPSs and LPSs). The EPSs from all three strains are very similar in composi­ tion having galactose, glucose, uronic acid and acetate. These components are similar to the EPSs from other fast-growing Rhizobium species except for pyruvate which is not detected in the EPSs from fast­ growing R. japonicum strains. The CPSs from USDA205 and HC205 are very similar to the EPSs in composition except they contain increased amounts of acetate. The CPS from USDA201 is isolated in very small amounts and is different in composition from the EPSs in that it is reduced in glucose and increased in uronic acid. The EPSs and CPSs are different from those of the slow-growing �· japonicum strains which vary from strain to strain and can consist of methylated sugars and deoxysugars. The LPSs were purified by phenol/water extraction and gel filtration chromatography. The LPSs from USDA205 and HC205 elute as broad peaks from the gel filtration column and contain 2-keto-3-deoxyoctonic acid (KDO) as one of the maj or sugar components. The LPS from HC205 differs from that of USDA205 in that it contains ribose. Both USDA205 and HC205 LPSs have a lamba max at 260 nm. Both the ribose content and the lamba
POLYNOMIAL FILTERING AND IDENTIFICATION FOR DISCRETE-TIME NONLINEAR UNCERTAIN STOCHASTIC SYSTEMS

This paper deals with the problem of system identi¯cation and state estimation for nonlinear uncertain stochastic system, in the discrete-time framework. A polynomial ¯ltering algorithm is here proposed and implemented by opportunely extending the state space with the inclusion of the unknown vector of parameters, so that the ¯ltering and identi¯cation problems are simultaneously solved. Such an algorithm is achieved by applying the optimal polynomial ¯lter of a chosen degree ¹ to the Carleman approximation of the same degree of the extended nonlinear system.
Exploration of anti-inflammatory and hepatoprotective effect of curcumin on co-administration with acetylsalicylic acid

Context: Acetylsalicylic acid (ASA) has been repositioned against different inflammatory disease conditions. However, on long-term use, ASA is reported to cause hepatotoxicity by compromising the antioxidant status. Curcumin is known for its antioxidant and anti-inflammatory action. Accordingly, co-use of curcumin can be expected to enhance the anti-inflammatory effects of ASA while minimizing its hepatotoxicity. Aims: To evaluate the anti-inflammatory and hepatoprotective effects of curcumin when co-administered with ASA. Methods: To evaluate anti-inflammatory activity carrageenan-induced paw edema and cotton pellet induced granuloma models were used. Hepatotoxicity was induced by administration of ASA (100 mg/kg/day) for 28 continuous days. Antioxidant effects were determined by malondialdehyde, superoxide dismutase and reduced glutathione assay of liver tissue. Results: Co-treatment with curcumin and ASA significantly (p<0.001) reduced (57.92%) the paw edema induced by carrageenan. The effect was higher than that of the ASA (45.51%) and curcumin (36.87%). Further, the combination showed higher (57.67%) inhibition of granuloma formation compared to that of ASA (34.22%) and curcumin (28.39%). Co-use of curcumin with ASA lowered the malondialdehyde level while relatively increasing the superoxide dismutase and reduced glutathione compared to ASA and curcumin. The histological findings showed protection against ASA induced hepatotoxicity. Conclusions: Curcumin showed additive effects with ASA against inflammatory granuloma formation in rats. It also showed positive interaction against carrageenan-induced inflammation. With relatively higher antioxidant capacity, the co-use of curcumin showed protection against ASA induced hepatotoxicity.