Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Article: Effects of dietary supplementation of Kakuti, Ziziphora clinopodioides, extract on enzymatic and antioxidant parameters of the plasma of common carp, Cyprinus carpio

Kakuti, Ziziphora clinopodioides, is a medicinal herb found in Iran, but its potential benefits have not been studied on fish. Thus, the aim of the present study was to investigate the effects of Kakuti aqueous extract on the plasma antioxidant and enzymatic parameters in common carp, Cyprinus carpio. The aqueous extract was prepared by boiling Kakuti leaves for 2h. Four diets containing %0 (Ctrl), %0.5 (0.5E), %1 (1E), and %2 (2E) of Kakuti extract were fed to fish within a 60-day period. For each diet, three tanks, each with 15 fish with initial weight of 46.2±0.16g, were assigned. Then, blood samples were taken from all treatments to assess plasma alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), glucose, superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA). The results showed that %1 Kakuti extract significantly decreased plasma AST and ALP, but increased CAT activities. There was no significant effect of dietary treatments on plasma ALT activity. 0.5 and %1 Kakuti extract decreased plasma glucose levels significantly, but increased plasma SOD activity. 1 and %2 Kakuti extract decreased plasma MDA levels significantly. According to the results, Kakuti extract is capable of augmenting antioxidant strength, that in turn, may be the reason for boosted tissue health in common carp. Dietary %1 Kakuti extract is recommended for inclusion in common carp diet.
Surface enhanced Raman spectroscopy of collagen I fibrils

xi List of Abbreviations and Symbols Used . xii Acknowledgements . xiv Chapter
Greek Mythology as a Knowledge Graph: From Chaos to Zeus and Beyond

Greek mythology has been exerting a lasting influence on Western culture, but a respective ontology has been missing from the Semantic Web until now. To remedy this deficiency, from 5377 Wikidata items with 283 properties, 34 of these properties were selected to generate a first version of an Ontology of Greek Mythology (OGM). This limited set of properties was used to define a set of classes to instantiate the descriptions of the individuals according to reification requirements. The ontology also includes the representation of contradictions between statements, a well-known symptom of classical storytelling. A retrieval tool was added to use the Wikidata Query Service through SPARQL queries in order to display and download results in various formats, thereby developing OGM into a scholarly tool. Further, as Wikidata has little information about classical sources grounding the truth of its statements, we tested a semantic enrichment workflow to extract additional statement types from source texts in the ‘Theoi Project’ as statement anchors. This workflow experiment proved necessary to go beyond Wikipedia to address mythological complexities in a knowledge graph, but, as discussed in the article, its scalable automation requires further development.
Ultrasound shear wave elastography of the anterior talofibular and calcaneofibular ligaments in healthy subjects

Abstract Aim of study: Most sprained lateral ankle ligaments heal uneventfully, but in some cases the ligament’s elastic function is not restored, leading to chronic ankle instability. Ultrasound shear wave elastography can be used to quantify the elasticity of musculoskeletal soft tissues; it may serve as a test of ankle ligament function during healing to potentially help differentiate normal from ineffective healing. The purpose of this study was to determine baseline shear wave velocity values for the lateral ankle ligaments in healthy male subjects, and to assess inter-observer reliability. Material and methods: Forty-six ankles in 23 healthy male subjects aged 20–40 years underwent shear wave elastography of the lateral ankle ligaments performed by two musculoskeletal radiologists. Each ligament was evaluated three times with the ankle relaxed by both examiners, and under stress by a single examiner. Mean shear wave velocity values were compared for each ligament by each examiner. Inter-observer agreement was evaluated. Results: The mean shear wave velocity at rest for the anterior talofibular ligament was 2.09 ± 0.3 (range 1.41–3.17); and for the calcaneofibular ligament 1.99 ± 0.36 (range 1.29–2.88). Good inter-observer agreement was found for the anterior talofibular ligament and calcaneofibular ligament shear wave velocity measurements with the ankle in resting position. There was a significant difference in mean shear wave velocities between rest and stressed conditions for both anterior talofibular ligament (2.09 m/s vs 3.21 m/s; p <0.001) and calcaneofibular ligament (1.99 m/s vs 3.42 m/s; p <0.0001). Conclusion: Shear wave elastography shows promise as a reproducible method to quantify ankle ligament stiffness. This study reveals that shear waves velocities of the normal lateral ankle ligaments increased with applied stress compared to the resting state.
A Survey of FPGA Logic Cell Designs in the Light of Emerging Technologies

The functional component for an FPGA is the logic element which enables it to adapt to various hardware descriptions. This behavior is mostly due to the MUX-like functional flexibility provided by these logic elements or cells. However, in recent years, decelerating transistor sizing as per Moore’s law has led to diminishing power, area and delay returns over cost. Hence, the idea of venturing into FPGA logic cell designs based on emerging technologies is becoming not merely attractive, but even inescapable. The present work surveys various conventional and non-conventional logic cell designs proposed in the literature by identifying four logic design families, namely LUT-based, cone-based, matrix/cluster-based and transistor array-based. We then carry out a detailed comparison at two levels - a quantitative comparison based on metrics like power, delay and area which govern the overall performance of various FPGA architectures and secondly a qualitative comparison on factors which are important considering the ease of mainstream adoption. We highlight the importance of introducing and co-optimizing novel devices and architectures to maximize the overall FPGA performance.
The Tarteel Dataset: Crowd-Sourced and Labeled Quranic Recitation

We propose a standard schema for paired Quranic audio and text datasets. We describe the collection, labeling, and validation of the Tarteel recitation dataset, the ﬁrst large-scale dataset of Quranic recitation and accompanying Arabic text collected in a crowd-sourced manner. The dataset contains 25,000 audio clips totalling 67.39 hours of audio and represents a wide variety of recitation styles, proﬁciencies, and speeds. The data were collected over a period of six months from over 1,200 unique individuals of different ages, genders, and ethnicities. We describe the composition of the data and contributors, describe in detail how the data was collected and processed, and give some baseline performance for preliminary machine learning algorithms that were trained and evaluated on the dataset.
A Comparison Between Preschool Teachers’ Read-Aloud Techniques With Fictional and Informational Picture Books in Small Groups

Relatively little is known about preschool teachers’ read-aloud techniques with informational picture books. The purpose of this investigation was to identify similarities and differences between preschool teachers’ read-aloud techniques with fictional stories, which are commonly read in preschool, and informational texts. Instrumental case study and purposive sampling were employed to investigate the reading techniques of two White female teachers in one preschool classroom as they read in small groups with children two-and-a-half to five years old. In terms of similarities across genres, teachers made personal connections, prompted children to interpret pictures, used multimodal instruction, and differentiated instruction. In terms of key differences, when reading fictional stories, teachers scaffolded children’s inferences and predictions, whereas for informational texts, teachers described academic vocabulary and content and focused on informational text features. Preschool teachers might expect to use a core set of reading techniques across texts and also differentiate according to the type of picture book.
PREPARATION AND PERFORMANCE OF TANNIN–GLYOXAL–UREA

1 DOI:10.4067/S0718-221X2021005XXXXXX 1 PREPARATION AND PERFORMANCE OF TANNIN–GLYOXAL–UREA 2 RESIN-BONDED GRINDING WHEEL LOADED WITH SiO2 REINFORCING 3 PARTICLES 4 5 Jun Zhang1, Bowen Liu1, Yunxia Zhou1, Hisham Essawy3, Jinxin Li1, Qian Chen2*, 6 Xiaojian Zhou1*, Guanben Du1 7 8 1Southwest Forestry University, Yunnan Key Laboratory of Wood Adhesives and Glued 9 Products, Kunming, China. 10 2Southwest Forestry University, Key Laboratory of State forestry and Grassand 11 Administration on highly efficient utilisation of forestry biomass resources in Southwest of 12 China, Kunming, China. 13 3National Research Centre, Department of Polymers and Pigments, Dokki, Cairo, Egypt. 14 *Corresponding authors: chenqian@hit.edu. cn ; xiaojianzhou1982@163.com 15 Received: September 10, 2020 16 Accepted: April 19, 2021 17 18 ABSTRACT 19 In this study, an easily prepared bio-based abrasive grinding wheel based on 20 tannin–glyoxal–urea (TGU)thermosetting matrix is presented.The synthesised resin was 21 prepared via co-polycondensation reaction of glyoxal and ureawith condensed tannin, which is 22 a forest-derived product. Fourier transform infrared spectroscopy and electrospray ionisation 23 mass spectrometry results confirmed that urea and glyoxal react well under acidic conditions 24 and that –(OH)CH–NH–group is primarily involved in TGU cross-linking. Differential 25 scanning calorimetry, thermomechanical analysis and thermogravimetric analysis 26 investigations showed that the preparation of TGU resin is easier compared to commercial 27 phenol–formaldehyde (PF) resin; moreover, TGU resin has a more robust chemical network 28 structure, which contributes efficiently to heat resistance and improved mechanical properties. 29 This observation is supported by Brinell hardness, compression resistance and grinding testing; 30 these showed that the new grinding wheel acquired higher hardness, superior resistance against 31 compression and stronger abrasion resistance compared with a PF-based grinding wheel 32 prepared in the laboratory. Moreover, few holes and no cracks were found in the new grinding 33 wheel. 34
Effects of some herbicides on the leaf apparatus of young vine (Vitis vinifera L.)

Prodanova-Marinova, N. , Belberova, Y. & Tsvetanov, E. (2021). Effects of some herbicides on the leaf apparatus of young vine (Vitis vinifera L.). Bulg. J. Agric. Sci., 27 (2), 357–363 The study was carried out at the Experimental Base of the Institute of Viticulture and Enology, Pleven, Bulgaria. The soil type where the plantation was located was leached chernozem, formed on clay loess. Vines of Cabernet Sauvignon variety grafted to Berlandieri X Riparia Selection Openheim 4 (SO4) rootstock were used in the experimental work. The vines were planted in stages in the spring of 2015 and 2016. The objective of the study was to determine the impact of the herbicides Lumax and Gardoprim plus Gold in combination with Stratos Ultra on the leaf apparatus of grapevines during the first year after their planting. The treatment with Lumax and Gardoprim plus Gold was carried out on the soil, immediately after the formation of the protective piles, without incorporation, while with Stratos ultra between the thirties and the sixtieth day after that. The size of the leaf area was determined by the method proposed by Carbonneau and improved by T. Slavcheva. Vines from the herbicide-treated plots had been found to form larger-sized leaves and had a larger leaf area than those grown on areas where weed control was only by mechanical removal. Deformities and changes in the coloration of the leaf blades as a result of the phytotoxic response were not observed. Of the factors, sources of variation during the study period (dose – A, herbicide – B and the combination between them – A+B), the set of active substances used for weed control was of the greatest significance for the obtained results, i.e. the factor – herbicide (B).
QFabric: Multi-Task Change Detection Dataset

Detecting change through multi-image, multi-date remote sensing is essential to developing and understanding of global conditions. Despite recent advancements in remote sensing realized through deep learning, novel methods for accurate multi-image change detection remain unrealized. Recently, several promising methods have been proposed to address this topic, but a paucity of publicly available data limits the methods that can be assessed. In particular, there exists limited work on categorizing the nature and status of change across an observation period.This paper introduces the first labeled dataset available for such a task. We present an open-source change detection dataset, termed QFabric, with 450,000 change polygons annotated across 504 locations in 100 different cities covering a wide range of geographies and urban fabrics. QFabric is a temporal multi-task dataset with 6 change types and 9 change status classes. The geography and environment metadata around each polygon provides context that can be leveraged to build robust deep neural networks. We apply multiple benchmarks on our dataset for change detection, change type and status classification tasks. Project page: https://sagarverma.github. io/qfabric
Cetylpyridinium chloride-containing mouthwashes reduce the infectivity of SARS-CoV-2 variants in vitro

Oral mouthwashes decrease the infectivity of several respiratory viruses including SARS-CoV-2. However, the precise agents with antiviral activity present in these oral rinses and their exact mechanism of action remain unknown. Here we show that Cetylpyridinium chloride (CPC), a quaternary ammonium compound present in many oral mouthwashes, reduces SARS-CoV-2 infectivity by inhibiting the viral fusion step with target cells after disrupting the integrity of the viral envelope. We also found that CPC-containing mouth rinses decreased more than a thousand times the infectivity of SARS-CoV-2 in vitro, while the corresponding vehicles had no effect. This activity was effective for different SARS-CoV-2 variants, including the B.1. 1.7 variant, predominant in UK, also in the presence of sterilized saliva. CPC-containing mouth rinses could therefore represent a cost-effective measure to reduce SARS-CoV-2 infectivity in saliva, aiding to reduce viral transmission from infected individuals regardless of the variants they are infected with.
Predicting DOS-DDOS Attacks: Review and Evaluation Study of Feature Selection Methods based on Wrapper Process

Now-a-days, Cybersecurity attacks are becoming increasingly sophisticated and presenting a growing threat to individuals, private and public sectors, especially the Denial Of Service attack (DOS) and its variant Distributed Denial Of Service (DDOS). Dealing with these dangerous threats by using traditional mitigation solutions suffers from several limits and performance issues. To overcome these limitations, Machine Learning (ML) has become one of the key techniques to enrich, complement and enhance the traditional security experiences. In this context, we focus on one of the key processes that improve and optimize Machine Learning DOS-DDOS predicting models: DOS-DDOS feature selection process, particularly the wrapper process. By studying different DOS-DDOS datasets, algorithms and results of several research projects, we have reviewed and evaluated the impact on used wrapper strategies, number of DOS-DDOS features, and many commonly used metrics to evaluate DOS-DDOS prediction models based on the optimized DOS-DDOS features. In this paper, we present three important dashboards that are essential to understand the performance of three wrapper strategies commonly used in DOS-DDOS ML systems: heuristic search algorithms, meta-heuristic search and random search methods. Based on this review and evaluation study, we can observe some of wrapper strategies, algorithms, DOS-DDOS features with a relevant impact can be selected to improve the DOS-DDOS ML existing solutions. Keywords—DOS-DDOS attacks; feature selection; wrapper process; machine learning
Learning to Warp for Style Transfer

Since its inception in 2015, Style Transfer has focused on texturing a content image using an art exemplar. Recently, the geometric changes that artists make have been acknowledged as an important component of style[42], [55], [62], [63]. Our contribution is to propose a neural network that, uniquely, learns a mapping from a 4D array of inter-feature distances to a non-parametric 2D warp field. The system is generic in not being limited by semantic class, a single learned model will suffice; all examples in this paper are output from one model.Our approach combines the benefits of the high speed of Liu et al. [42] with the non-parametric warping of Kim et al. [55]. Furthermore, our system extends the normal NST paradigm: although it can be used with a single exemplar, we also allow two style exemplars: one for texture and another geometry. This supports far greater flexibility in use cases than single exemplars can provide.
Priming the Mental Representation of Tone Sandhi in Kunming Dialect

To recognize spoken words, one needs to map the auditory information to the stored representation in the mental lexicon. However, there is high variability in the acoustic signal. The realization of sounds can be quite different from the stored representation due to different speaking styles, speaking rate and phonological factors such as coarticulation and phonological alternation. Therefore, one of the central goals of research on spoken word recognition are to elucidate the nature of speech sounds, i.e. how are they represented in the mental lexicon, as it could inform the recognition process that accesses those representations. There are two views on the representation of speech sounds. The abstract representation view argued that speech sounds are abstractly represented in the brain, ignoring certain sources of variation and leaving the redundant surface acousticphonetic details underspecified. For example, in English, the nasals in coda position are usually not fully specified and tend to assimilate the place of articulation of the following plosives (Lahiri & Reetz 2010). The surface representation view maintained that episodic details of speech sounds are retained in the brain. For example, talker-specific effects were found in repetition priming (Dufour & Nguyen 2014). Most research in this field has focused on the representation of segmental features, but the representation of suprasegmental elements such as tone is also important, especially for languages that use tone to distinguish word meanings. Tone can go through phonological alternation as well: even though a tone has its citation value when it is produced alone, it may change its value in certain phonological environment, which is called tone sandhi. The alternations may happen because of the adjacent tones or their morpho-syntactic position etc. (Chen 2000). It is unclear whether the words that undergo tone sandhi are stored as the surface forms, i.e. the way they are heard or stored in the underlying forms, i.e. base tone is accessed during spoken word recognition. Recently, a few studies have been done to investigate the representation of tone sandhi in some Chinese dialects. However different dialects seem to internalize the sandhi patterns differently in the mental lexicon. Chien, Sereno & Zhang (2016a) has conducted an auditory-auditory lexical decision priming experiment on standard Mandarin tone sandhi. In Mandarin, Tone 3 (T3; tone value: 213) would change into tone 2 (T2; tone value: 35) when pre-
1 Team 6 : NEMO modelling

The objective of Team 6 is to support the other BaySys teams in investigating the relative impacts of climate change and regulation on freshwater-marine coupling within the Hudson Bay Complex (Foxe Basin, Hudson Bay, James Bay, Hudson Strait). In support of Team 1 hypotheses, a sea ice and oceanographic model will be used to further study the effects of freshwater loading and ice cover on the circulation of Hudson Bay. This modeling perspective will be based on the Nucleus for European Modeling of the Ocean (NEMO) ocean general circulation model coupled to the LIM2 sea ice model. Central also to Team 6 goals is the development of an integrated observational-modeling framework that will provide insight on, and improved representation of, physical, biological and biogeochemical processes in the Hudson Bay system. The modelling will provide a framework and tool with which to simulate projected changes in marine state and dynamic variables, while also enabling an integration of observations and numerical analyses.
Change Detection for Geodatabase Updating

The geodatabase (vectorized data) nowadays becomes a rather standard digital city infrastructure; however, updating geodatabase efficiently and economically remains a fundamental and practical issue in the geospatial industry. The cost of building a geodatabase is extremely high and labor intensive, and very often the maps we use have several months and even years of latency. One solution is to develop more automated methods for (vectorized) geospatial data generation, which has been proven a difficult task in the past decades. An alternative solution is to first detect the differences between the new data and the existing geospatial data, and then only update the area identified as changes. The second approach is becoming more favored due to its high practicality and flexibility. A highly relevant technique is change detection. This article aims to provide an overview the state-of-the-art change detection methods in the field of Remote Sensing and Geomatics to support the task of updating geodatabases. Data used for change detection are highly disparate, we therefore structure our review intuitively based on the dimension of the data, being 1) change detection with 2D data; 2) change detection with 3D data. Conclusions will be drawn based on the reviewed efforts in the field, and we will share our outlooks of the topic of updating geodatabases.
K-Net: Towards Unified Image Segmentation

Semantic, instance, and panoptic segmentations have been addressed using different and specialized frameworks despite their underlying connections. This paper presents a unified, simple, and effective framework for these essentially similar tasks. The framework, named K-Net, segments both instances and semantic categories consistently by a group of learnable kernels, where each kernel is responsible for generating a mask for either a potential instance or a stuff class. To remedy the difficulties of distinguishing various instances, we propose a kernel update strategy that enables each kernel dynamic and conditional on its meaningful group in the input image. K-Net can be trained in an end-to-end manner with bipartite matching, and its training and inference are naturally NMS-free and box-free. Without bells and whistles, K-Net surpasses all previous published state-of-the-art single-model results of panoptic segmentation on MS COCO test-dev split and semantic segmentation on ADE20K val split with 55.2% PQ and 54.3% mIoU, respectively. Its instance segmentation performance is also on par with Cascade Mask R-CNN on MS COCO with 60%-90% faster inference speeds. Code and models will be released at https://github.com/ZwwWayne/K-Net/.