Miracle-dz/UniFAR-FTUs huggingface dataset:
Computation of certain topological coindices of graphene sheet and C4C8(S) nanotubes and nanotorus

Abstract Topological indices are widely used for quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR). Topological coindices are topological indices that considers the non adjacent pairs of vertices. Here, we consider the following five well-known topological coindices: the first and second Zagreb coindices, the first and second multiplicative Zagreb coindices and the F-coindex. By using graph structural analysis and derivation, we study the above-mentioned topological coindices of some chemical molecular graphs that frequently appear in medical, chemical, and material engineering such as graphene sheet and C4C8(S) nanotubes and nanotorus and obtain the computation formulae of the coindices of these graphs. Furthermore, we analyze the results by MATLAB and obtain the relationship of the coindices which they describe the physcio-chemical properties and biological activities.
Muellerella, a lichenicolous fungal genus recovered as polyphyletic within Chaetothyriomycetidae (Eurotiomycetes, Ascomycota)

Abstract Molecular data and culture-dependent methods have helped to uncover the phylogenetic relationships of numerous species of lichenicolous fungi, a specialized group of taxa that inhabit lichens and have developed diverse degrees of specificity and parasitic behaviors. The majority of lichenicolous fungal taxa are known in either their anamorphic or teleomorphic states, although their anamorph-teleomorph relationships have been resolved in only a few cases. The pycnidium-forming Lichenodiplis lecanorae and the perithecioid taxa Muellerella atricola and M. lichenicola were recently recovered as monophyletic in Chaetothyriales (Eurotiomycetes). Both genera are lichenicolous on multiple lichen hosts, upon which they show a subtle morphological diversity reflected in the description of 14 species in Muellerella (of which 12 are lichenicolous) and 12 in Lichenodiplis. Here we focus on the teleomorphic genus Muellerella and investigate its monophyly by expanding the taxon sampling to other species occurring on diverse lichen hosts. We generated molecular data for two nuclear and one mitochondrial loci (28S, 18S and 16S) from environmental samples. The present multilocus phylogeny confirms the monophyletic lineage of the teleomorphic M. atricola and M. lichenicola with their L. lecanorae-like anamorphs, but places the rest of the Muellerella species studied in two different monophyletic lineages with strong support. The first, Muellerella spp. 1, is nested within some new lineages of black fungi isolated from different epilithic lichen thalli, while the second, Muellerella spp. 2, is closely related to the Verrucariales. Based on these results, we reappraise the phylogenetic placement of Muellerella and suggest its polyphyly within Chaetothyriomycetidae.
Influence of technology on regional brands in Czechia

Abstract This article aims to examine the effects of new technology on the purchase of regional brands in Czechia and draw conclusions that will help to adapt the brands to customer needs. Regional brands are a speciality of Central Europe, which emerged due to consumer dissatisfaction with low-quality of global retail products. These traditional local handmade products are heavily influenced by new technology and customers requiring them to be purchasable online with a massive online presence. The sample consisted of 1050 residents of the Czech Republic. The data were gathered by a professional marketing agency Ipsos using a questionnaire survey. The sample was tested using the one-way Chi-square test, which had good compliance to test the basic sample characteristics, followed with the one-sample Kolmogorov-Smirnov test to test the data distribution, and then, the dependencies were tested with the Kruskal-Wallis test. Finally, a post-hoc test suitable for the type of analysis could be chosen to better understand the type of factors that could influence the results and their possible effect. The main findings indicate a slow change in the demand as customers are neutral in relation to regional brands available from online shops as well as their about social media presence but require them to have a good-quality website. Solutions are proposed using a government-run brand with a platform providing web layouts and hybrid e-shop. The type of content is proposed, indicating the appropriate execution, which should be done based on the researched-derived segmentation criteria.
Some Geotechnical Properties of Pure and Waste Gypsum for Geoelectrical Grounding Applications

Abstract Natural occurring gypsum is a soft mineral consists of hydrated calcium sulphate, mainly used in cement industry. On the other hand, red gypsum (RG) is a waste generated from a sulphate process of ilmenite ore to acquire titanium dioxide. Due to the gypsum content in both materials are similar, it is expected that both gypsum type can be used for similar engineering applications. In this study, RG was tested and compared to pure gypsum for geoelectrical grounding applications. The geotechnical properties and plasticity characteristics were carefully measured and tested. In addition, X-ray fluorescence (XRF) was employed to study the chemical constituents of the materials. Test results showed that, the geotechnical properties of RG is different to that of white gypsum. The plasticity index (PI) of RG was 239.6% greater due to the presence of Fe ions. Surprisingly, the electrical resistivity of both material were found to be similar. It was also noted that, although the plasticity of pure gypsum is high, the plasticity of pure gypsum was found to be short lived primarily due to instantaneous exothermic reaction between water and semi-hydrated gypsum. The change in the plasticity also affected the resistivity as gypsum hardened after short duration. Based on the geotechnical and plasticity characteristics determined, RG was found to be a better as grounding material as compared to gypsum.
Using computational approaches to study dengue virus capsid assembly

Abstract Dengue viral capsid plays a significant role in viral life cycle of dengue, especially in vial genome protection and virus-cell fusion. Revealing mechanisms of the viral capsid protein assembly may lead to the discovery of anti-viral drugs that inhibit the assembly of the viral capsid. The E and M-proteins are arranged into heterotetramers, which consists of two copies of E and M-protein. The heterotetramers are assembled into a highly ordered capsid. While many investigations of the interactions between E and M-proteins have been performed, there are very few studies on the interactions between the heterotetramers and their roles in capsid assembly. Utilizing a series of computational approaches, this study focuses on the assembly mechanism of the heterotetramers. Our electrostatic analyses lead to the identification of four binding modes between each two dengue heterotetramers that repeat periodically throughout the virus capsid. Among these four binding modes, heterotetramers in binding modes I, II and IV are attractive. But in the binding mode III the heterotetramers repel each other, making mode III a suitable target for drug design. Furthermore, MD simulations were performed following by salt bridges analysis. This study demonstrates that using computational approaches is a promising direction to study the dengue virus.
Adding Additional Features to Improve Time Series Prediction

Abstract This paper aims at the time-series data analysis. We propose the possibility of adding additional features to the existing time series data set, to improve the prediction performance of the prediction model. The main goal of our research was to find a proper method for building a prediction model for the time-series data, using also machine learning methods. In this phase of research, we aim at the data analysis and proposal of the ways to add additional features to our dataset. In this paper, we aim at adding derived parameters from one of the original features. We also propose incorporating LAG’s into the dataset as new features, to enhance the prediction performance on the time series based data.
Photophysical and antibacterial activity of light-activated quaternary eosin Y

Abstract The functional characteristics of a new eosin dye with biocidal quaternary ammonium group (E) were studied in aqueous solution and in organic solvents of different polarity. The spectral properties depend on the nature and polarity of the respective solvents. The antimicrobial activity of compound E has been tested in vitro against Gram-negative bacteria (Escherichia coli, Acinetobacter johnsoni and Pseudomonas aeruginosa), Gram-positive bacteria (Sarcina lutea and Bacillus cereus) and the antifungal activity was tested against the yeasts Candida lipolytica in solution and after treated on cotton fabric. Broth dilution test has been used for quantitative evaluation of the antimicrobial activity of compound E against the model strains. The ability of compound E to inhibit the growth of model Gram-negative P. aeruginosa strain was assessed after 16 h of incubation in presence and absence of light. These experiments were conducted in planktonic format in solution and on cotton fabric. The results suggest that the new compound is effective in treating the relevant pathogens with better results being obtained by irradiation with light. In this case the quaternary ammonium group promotes the binding of eosin Y moiety to the bacterial cell wall thus accelerating bacterial photo inactivation.
Geographic trends in range sizes explain patterns in bird responses to urbanization in Europe

Abstract The probability of occurrence of bird species in towns/cities increases with their range sizes, and Rapoport’s rule states that range sizes increase with latitude. To test the hypothesis that the increasing number of bird species persisting in cities at higher latitudes of Europe is linked to their larger range sizes, we compiled data on bird communities of: a) 41 urban bird atlases; b) 37 city core zones from published sources; c) regions of nine grid cells of the EBCC Atlas of European Breeding Birds around each city. We tested whether the proportion of species from particular regional bird assemblages entering cities (i.e., proportional richness) was related to the geographical position, mean range size of regional avifaunas, proportion of vegetated areas and city habitat heterogeneity. The mean range sizes of the observed and randomly selected urban avifaunas were contrasted. The proportional richness of urban avifaunas was positively related to the geographic position and mean range size of birds in regional assemblages. The evidence favoured range sizes if considering the European range sizes or latitudinal extents, but was limited for global range sizes. Randomizations tended to show larger range sizes for the real avifaunas than in the randomly selected ones. For urban core zones, the results were less clear-cut with some evidence only in favour of the European range sizes. No role of vegetation or habitat heterogeneity was found. In conclusion, while vegetation availability or heterogeneity did not show any effects, spatial position and range sizes of birds in regional assemblages seemed to influence the proportional richness of cities and their core zones. Factors correlated with spatial position (e.g., climate) might increase the attractivity of particular cities to birds. However, the effects of range sizes indicated that urbanization possibly has more negative impacts on the avifauna in the regions occupied by less widespread species.
Relationship between serum homocysteine level and cognitive impairment in patients with Parkinson‘s disease

Abstract OBJECTIVE To investigate the correlation between serum homocysteine (Hcy) and cognitive impairment (CI) in patients with Parkinson’s disease (PD). METHODS Eighty-one PD patients were prospectively recruited in this study from Feb 2015 to Jan 2018 in Gansu Provincial Hospital. Of the subjects, 41 were diagnosed with cognitive impairment (PD-CI) vs. the 40 others without PD (PDN). The clinical characteristic and demographic features were recorded for the two groups. The serum Hcy, folate and vitamin B12 (VitB12) were examined by high-performance liquid chromatography (HPLC) and enzyme-linked immunosorbent assay (ELISA). RESULTS The serum Hcy, folate, VitB12 concentration were 21.7±6.2 (μmol/L), 9.2±3.7 (ng/mL), 354.1±123.5 (pg/mL) for PD-CI group and 14.1±5.7 (μmol/L), 12.4±4.5 (ng/mL), 378.7±128.2 (pg/mL) for PDN group respectively. The serum level of Hcy in PD-CI group was significantly higher than that of PDN group (p<0.05), serum folate was significantly lower than PDN group (p<0.05). The diagnostic sensitivity, specificity and AUC were 77.5% (95%CI:61.6%-89.2%), 78.1% (95%CI:62.4%-89.4%), 0.82 (95%CI:0.73-0.91) for serum Hcy and 72.5% (95%CI:56.1%-85.4%), 63.4% (95%CI:46.9%-77.9%), 0.71(95%CI:0060-0.83) for serum folate respectively as serological markers for cognitive impairment diagnosis in patients with PD. Conclusion Serum Hcy and folate were different between PD-CI and PDN patients, which may play an important role in cognitive impairment development in patients with PD and can be used as promising serological diagnostic marker.
Awareness and knowledge of human papillomavirus vaccination and their influential factors among Chinese women: a systematic review

Abstract Objectives To systematically review the knowledge attitudes and the influential factors on human papillomavirus (HPV) vaccination among Chinese women. Methods Published studies on knowledge and attitudes of HPV vaccination for preventing cervical cancer among Chinese female population were retrieved using the major Chinese and English databases. Meanwhile, handwork retrieval was also conducted and the references including in the literature were retrieved. The quality of the literature was rigorously evaluated and extracted independently by two researchers and the data were analyzed and described by review manager 5.3 (RevMan5.3) software. Results In all, 19 articles including 8 articles in Chinese and 11 in English were chosen. A total of 30,176 participants were included and the sample size ranged from 64 to 6,024. The overall awareness of HPV and HPV vaccine among Chinese women was at a low level. Chinese women generally showed poor knowledge about HPV and HPV vaccine. Acceptance of HPV vaccination among Chinese women was at a high level. Vaccination intentions were influenced by the theory of planned behavior (TPB) and measured by attitudes subjective norms and perceived behavioral control. Conclusions The health authorities may evaluate and develop TPB-based interventions to increase HPV vaccination intentions of Chinese women. HPV vaccination programs should focus on carrying out multi-level and targeted health education and developing effective public health strategies after balancing the cost and benefit of HPV vaccine program. Medical staff should play the positive role in promoting the use of HPV vaccines in China. Integration of policy and community perspectives and multi-level interventions are essential to maximize the public health benefits of HPV vaccination.
Lichen species as element bioindicators for air pollution in the eastern United States of America

Abstract Lichen element (N, S, metals) indicators of local air pollution load (a widely used technique) are recommended for five predefined regions covering central and southern parts of the eastern United States. The final recommendations integrate the advice of regional lichenologists, information from regional floras, and species abundance data from a United States Forest Service Forest Inventory and Analysis Program (FIA) lichen database for 11 of the 21 covered eastern states. Recommended species were frequent in their region, easy for nonspecialists to distinguish in the field after training, and easy to handle using clean protocols. Regression models of species abundance in FIA plots from five southeastern states vs. climate, air pollution (both from a regional lichen response model) and type of nearby landcover (from the National Land Cover Database) identified species’ environmental limitations. Punctelia rudecta is recommended for cooler forested uplands of all regions, with three Physcia species combined and Punctelia missouriensis for isolated woodlands or urban areas of three regions. Parmotrema hypotropum and P. hypoleucinum combined (weak environmental limitation) or P. perforatum. and P. subrigidum combined (limited in more polluted areas) are recommended for warmer Coastal Plains in two regions each. Additional species are recommended for single regions. Each species must be quantitatively evaluated in each region, to demonstrate indication reliability in practice and to calculate element data conversions between species for region-wide bioindication.
Extracting word synonyms from text using neural approaches

Extracting synonyms from textual corpora using computational techniques is an interesting research problem in the Natural Language Processing (NLP) domain. Neural techniques (such as Word2Vec) have been recently utilized to produce distributional word representations (also known as word embeddings) that capture semantic similarity/relatedness between words based on linear context. Nevertheless, using these techniques for synonyms extraction poses many challenges due to the fact that similarity between vector word representations does not indicate only synonymy between words, but also other sense relations as well as word association or relatedness. In this paper, we tackle this problem using a novel 2-step approach. We first build distributional word embeddings using Word2Vec then use the induced word embeddings as an input to train a feed-forward neutral network using annotated dataset to distinguish between synonyms and other semantically related words
Boosting training for PDF malware classifier via active learning

Machine learning algorithms are widely used for cybersecurity applications, include spam, malware detection. In these applications, the machine learning model has to face attack by adversarial samples. Therefore, how to train a robust machine learning model with small samples is a very hot research problem. portable document format (PDF) is a widely used file format, and often utilized as a vehicle for malicious behavior. There have been various PDF malware detectors based on machine learning. However, the labeling of large‐scale data samples is time‐consuming and laborious. This paper aims to reduce the size of training set while maintain the performance of detection. We propose a novel PDF malware detection method, using active learning to boost training. Particularly, we first make clear the meaning of uncertain samples in this paper, and theoretically explain the effectiveness of these uncertain samples for malware detection. Second, we present an active‐learning based malware detection model, using mutual agreement analysis to choose the uncertain sample as the data augmentation. The detector is retrained according to the ground truth of the uncertain samples rather than the whole test samples in the previous epoch, which can not only improve the detection performance, but also reduce the training time consumption of the detector. We conduct 10 epochs of retraining experiments for comparison, using the uncertain samples and the whole test samples from the previous epoch respectively as training set augmentation. The experimental results show that our active‐learning based model can achieve the same performance as the traditional model in the tenth epoch of retraining, while the former only needs to use one thirtieth of the latter's training samples.
Identifying the use of a park based on clusters of visitors' movements from mobile phone data

Planning urban parks is a burdensome task, requiring knowledge of countless variables that are impossible to consider all at the same time. One of these variables is the set of people who use the parks. Despite information and communication technologies being a valuable source of data, a standardized method which enables landscape planners to use such information to design urban parks is still broadly missing. The objective of this study is to design an approach that can identify how an urban green park is used by its visitors in order to provide planners and the managing authorities with a standardized method. The investigation was conducted by exploiting tracking data from an existing mobile application developed for Cardeto Park, an urban green area in the heart of the old town of Ancona, Italy. A trajectory clustering algorithm is used to infer the most common trajectories of visitors, exploiting global positioning system and sensor-based tracks. The data used are made publicly available in an open dataset, which is the first one based on real data in this field. On the basis of these user-generated data, the proposed datadriven approach can determine the mission of the park by processing visitors’ trajectories whilst using a mobile application specifically designed for this purpose. The reliability of the clustering method has also been confirmed by an additional statistical analysis. This investigation reveals other important user behavioral patterns or trends.
The Concept of 'empire' in Russian and Czech

The paper is dealing with subject of forming semantic fields. The ‘empire’ semantic field in 2 languages (Russian, Czech) was chosen as an object of investigation. The paper describes a descriptive statistical method of forming semantic fields based on linguistic corpora. The result is a specific lexicographic product (distrubutive thesaurus) for each language with quantitative characteristics of the connectedness of lexical units. At the last step linguistic correlation between elements of these two thesauri is shown. The research is implemented on the basis of Sketch Engine and Czech National Corpus. In the aspect of theory, we get a fragment of the semantic description of Russian and Czech languages and a description of new methods for analyzing vocabulary and semantics of the language.
Approximate String Matching for Detecting Keywords in Scanned Business Documents

Optical Character Recognition (OCR) is achieving higher accuracy. However, to decrease error rate down to zero is still a human desire. This paper presents an approximate string matching method using weighted edit distance for searching keywords in OCR-ed business documents. The evaluation on a Czech invoice dataset shows that the method can detect a signiﬁcant part of erroneous keywords.
A combined method of skin-and depth-based hand gesture recognition

Kinect is a promising acquisition device that provides useful information on a scene through color and depth data. There has been a keen interest in utilizing Kinect in many computer vision areas such as gesture recognition. Given the advantages that Kinect provides, hand gesture recognition can be deployed efficiently with minor drawbacks. This paper proposes a simple and yet efficient way of hand gesture recognition via segmenting a hand region from both color and depth data acquired by Kinect v1. The Inception model of the image recognition system is used to check the reliability of the proposed method. Experimental results are derived from a sample dataset of Microsoft Kinect hand acquisitions. Under the appropriate conditions, it is possible to achieve high accuracy in close to real time