Miracle-dz/UniFAR-FTUs huggingface dataset:
An analysis of trade flows between BRICS and European Union: a quantitative assessment

Abstract BRICS with their outward oriented strategy became the most influential group in international arena. Their economic and political weight which induces the negotiations/discussions with EU, lends the EU a special responsibility for the deeper integration of BRICS. Therefore, the economic impact of EU on the members of BRICS, post 2008 crisis and amidst Brexit declaration is essential to understand and how it affects the trade flows assumes a lot of significance. Against this backdrop, the study attempts to analyse the trade flows and its determinants between EU and BRICS applying gravity model. The estimated results reveal that economic size, market size, distance and the Brexit policy have significant effect on bilateral trade flows between BRICS and EU. BRICS future negotiations with EU as a unified single entity are desirable to expand beyond trade focussing on investments particularly for infrastructure building, technology upgradation and skill development. The study recommends product diversification and digitisation of economies for a smooth and fair trade and to mitigate the risks of present pandemic.
Developing Students' Learning and Innovation Skills Using the Virtual Smart Classroom

This study examined the development of learning and innovation skills among students in the virtual learning environment provided by the smart classroom which is comprised by three technological components containing (1) virtual 3D classroom created by OpenSimulator, (2) Learning Management System (LMS) created by Moodle and (3) the add-on Moodle’s plug-in, known as INNO ED TOOLs. The new system design which make connection between the virtual 3D classroom and the LMS known as Virtual Smart Learning and Innovation System (VSLI). The VSLI was created in accordance with the principles of constructivism in order to guide and foster creative thinking among learners and enhance their skills in innovation.
Simultaneous determination of 17 aphrodisiac chemical drugs illegally added in health products and Chinese patent medicines by high performance liquid chromatography-tandem mass spectrometry

A method was proposed for the simultaneous determination of seventeen aphrodisiac chemical drugs which were illegally mixed into the health products and Chinese patent medi⁃ cines by high performance liquid chromatography⁃mass spectrometry (HPLC⁃MS / MS) . The extraction, chromatographic conditions and mass spectrometry parameters were optimized in order to separate three groups of isomers. The drugs were extracted with methanol under ultra⁃ sonic condition, separated on an Agilent Extend C18 chromatographic column (100 mm×2􀆰 1 mm, 3􀆰 5 μm) with acetonitrile and water ( additional 10 mmol / L ammonium acetate) as mobile phases under gradient elution at a flow rate of 0􀆰 25 mL / min. The determination was conducted by tandem mass spectrometry in positive ESI mode under multiple reaction monito⁃ ring (MRM) mode. The method made seventeen aphrodisiac chemical drugs as well as the three groups of isomers to get the ideal separation and accurate quantitative. The method was proved 第 3 期 黄 芳,等:高效液相色谱⁃串联质谱法同时测定保健品及中成药中 非法添加的 17 种壮阳类化学药 to be rapid, selective, sensitive and stable, and it has been applied to the screening and detec⁃ tion of aphrodisiac chemical drugs illegally added in health products and Chinese patent medi⁃ cines. All the tested samples show that the aphrodisiac chemical drugs have a high detection rate in the recent three years. The relevant regulatory authorities should pay more attention to it.
Ecohydrological characteristics of a newly identified coastal raised bog on the western Olympic Peninsula, Washington State, USA

In western North America, ombrotrophic bogs are known to occur as far south as coastal regions of British Columbia. A recent discovery of a peatland with a raised peat surface on the western Olympic Peninsula in Washington State (Crowberry Bog), USA, suggested that the distribution range of this ecosystem type extends further south along the coast. To confirm if the site was an ombrotrophic peatland, we analysed its topography, hydrologic regime, water chemistry and vegetation. LiDAR data indicated that the peatland is elevated nearly 3 m above the surrounding landscape. Water table variations in the plateau were strongly associated with seasonal and daily precipitation events, indicating ombrotrophy. The hydraulic gradient on the plateau is downward through most of the year, demonstrating that precipitation is percolating vertically into deeper peat layers. In the rand, the hydraulic gradients are horizontal over much of the year, indicating that the plateau is draining through the rand to the lagg. Calcium, magnesium and potassium occur in very low concentrations, and the only ions in higher concentration are sodium and chloride, suggesting inputs of precipitation influenced by Pacific Ocean sea spray. Distinct vegetation composition and structure are associated with the plateau, rand and lagg zones of the site. These multiple lines of evidence indicate that Crowberry Bog is an ombrotrophic peatland, the first of its type identified in the conterminous western USA and the most southerly occurrence of its type in western North America.
Combinatorial Effects of Organophosphate (Temephos), Glyphosate (Roundup) and Sodium Dodecil Sulfate (Sds) on Zebrafish (Danio Rerio) Gills: A Morphometric and Histological Study

Pesticides, as Temephos and Roundup, and surfactants, like Sodium Dodecyl Sulfate (SDS), when dicharged into the environment, are harmful to non-target wildlife, especially fish. To evaluate the effects of those chemicals alone and their binary combinations, we assessed the histological alterations in Danio rerio gills after 15 days of exposure to Temephos (1ppm), Roundup (10ppm), SDS (2ppm), SDS plus Temephos (2ppm+1ppm), SDS plus Roundup (2ppm+10ppm) and Temephos plus Roundup (1ppm+10ppm). Hyperplasia, a regressive change, was significant in all exposed groups. The progressive change, complete fusion of lamellae, was significantly intensive in Roundup plus Temephos group. Regarding to circulatory disturbances, vascular congestion was significant intensive in SDS group, while severe aneurysm was observed in Roundup group. Although xenobiotics in the blend are biologically complex, mainly for long periods, combinatorial exposure incremented only complete lamellar fusion. Our results reinforce the rationalization of indiscriminate use of those compounds alone or in combination.
Automating Data Analysis Methods in Epidemiology

Technological advances in software development effectively handled technical details that made life easier for data analysts, but also allowed for non-experts in statistics and computer science to analyze data. As a result, medical research suffers from statistical errors that could be otherwise prevented such as errors in choosing a hypothesis test and assumption checking of models. Our objective is to create an automated data analysis software package that can help practitioners run non-subjective, fast, accurate and easily interpretable analyses. We used machine learning to predict the normality of a distribution as an alternative to normality tests and graphical methods to avoid their downsides. We implemented methods for detecting outliers, imputing missing values, and choosing a threshold for cutting numerical variables to correct for non-linearity before running a linear regression. We showed that data analysis can be automated. Our normality prediction algorithm outperformed the Shapiro-Wilk test in small samples with Matthews correlation coefficient of 0.5 vs. 0.16. The biggest drawback was that we did not find alternatives for statistical tests to test linear regression assumptions which are problematic in large datasets. We also applied our work to a dataset about smoking in teenagers. Because of the open-source nature of our work, these algorithms can be used in future research and projects.
Model-based estimation of the state of vehicle automation as derived from the driver’s spontaneous visual strategies

When manually steering a car, the driver’s visual perception of the driving scene and his or her motor actions to control the vehicle are closely linked. Since motor behaviour is no longer required in an automated vehicle, the sampling of the visual scene is affected. Autonomous driving typically results in less gaze being directed towards the road centre and a broader exploration of the driving scene, compared to manual driving. To examine the corollary of this situation, this study estimated the state of automation (manual or automated) on the basis of gaze behaviour. To do so, models based on partial least square regressions were computed by considering the gaze behaviour in multiple ways, using static indicators (percentage of time spent gazing at 13 areas of interests), dynamic indicators (transition matrices between areas) or both together. Analysis of the quality of predictions for the different models showed that the best result was obtained by considering both static and dynamic indicators. However, gaze dynamics played the most important role in distinguishing between manual and automated driving. This study may be relevant to the issue of driver monitoring in autonomous vehicles.
Identification of Novel QTLs for Spikelet Fertility, Panicle Compactness and Phytohormone Ethylene to Decipher Poor Grain Filling of Basal Spikelets in Dense Panicle Rice

High grain number is positively correlated with grain yield in rice, but it is compromised because of poor filling of basal spikelets in dense panicle bearing numerous spikelets. The phenomenon that turns the basal spikelets of compact panicle sterile in rice is largely unknown. In order to understand the factor(s) that possibly determines such spikelet sterility in compact panicle cultivars, QTLs and candidate genes were identified for spikelet fertility percentage, panicle compactness and ethylene production that significantly influence the grain filling using recombinant inbred lines developed from a cross between indica rice cultivars, PDK Shriram (compact, high spikelet number) and Heera (lax, low spikelet number). Novel QTLs, qSFP1.1, qSFP3.1 and qSFP6.1 for spikelet fertility percentage; qIGS3.2 and qIGS4.1 for panicle compactness; and qETH1.2, qETH3.1 and qETH4.1 for ethylene production were consistently identified in both kharif seasons of 2017 and 2018. The comparative expression analysis of candidate genes like ERF3, AP2-like ethylene-responsive transcription factor, EREBP, GBSS1, E3 ubiquitin-protein ligase GW2, and LRR receptor-like serine/threonine-protein kinase ERL1 associated with identified QTLs revealed their role in poor grain filling of basal spikelets in dense panicle. These candidate genes thus could be important for improving grain filling in compact-panicle rice cultivars through biotechnological interventions.
Ugly on the internet: from #authenticity to #selflove

This article aims at understanding why people deliberately share ugly photos of themselves on social media. After categorising the ugly pictures, the motivations for posting them are in focus: some people stress authenticity in times of ‘fake’ and a deeper understanding of social media, some refer to coolness, understood as the ‘apathy to cool’, or to a counter-culture, which applies different definitions of beauty and ugliness. Furthermore, there are people on social media using the ugly pictures as tools for empowerment and acceptance, as well as expressions of body-positivity and self-love. Finally, photography also has the power to transcend the body and its appearance when it no longer stands for an individual but is staged to express a concept.
Metagenomic Analyses of Nepoviruses: Diversity, Evolution and Identification of a Hitherto Undescribed Putative Region for Host Range in Subgroup a Species

Datamining and metagenomic analyses of 277 open reading frame sequences of bipartite RNA viruses and variants in the genus Nepovirus documented how delicate it can be to unequivocally identify species, in particular subgroup A and C species, based on some of the currently adopted taxonomic demarcation criteria. It suggests a possible need for their amendment to accommodate pangenome information. In addition, we revealed a host-dependent structure of arabis mosaic virus (ArMV) populations at a cladistic level and confirmed a phylogeographic structure of grapevine fanleaf virus (GFLV) populations. We also identified new putative recombinant events for species of subgroups A, B and C. The evolutionary specificity of some capsid regions of ArMV and GFLV that were previously described and biologically validated as vector determinant was circumscribed in silico. Furthermore, a C-terminal segment of the RNA-dependent RNA polymerase of subgroup A species was predicted as a putative host range determinant based on statistically supported higher π values for GFLV and ArMV isolates infecting Vitis spp. compared to non-Vitis infecting ArMV isolates. This study illustrated how sequence information obtained via high throughput sequencing can increase our understanding of mechanisms that modulate virus diversity and evolution and create new opportunities for advancing studies on the biology of economically important plant viruses.
Molecular Engineering of Mesogenic Constituents Within Liquid Crystalline Elastomers to Sharpen Thermotropic Actuation

Liquid crystalline elastomers (LCE) are stimuli‐responsive materials with a distinguished mechanical response. LCE have been subject to numerous recent functional examinations in robotics, health sciences, and optics. The liquid crystallinity of the elastomeric polymer networks of LCE are largely derived from liquid crystalline monomer precursors. Recent reports have utilized commercially available liquid crystalline diacrylate monomers in chain extension reactions to prepare LCE. These reactions have been largely based on monomeric precursors originally to enhance the and thermal stability of optical films. Here, it is demonstrated that preparing LCE via a liquid crystalline diacrylate with reduced mesogen–mesogen interaction enhances and sharpens the thermotropic actuation of these materials. Robust composition‐response correlations are demonstrated in LCE prepared by three common synthetic methods. The enhanced thermotropic response of LCE prepared from this precursor increases the thermomechanical efficiency by sixfold. Accordingly, this work addresses important limitations in utilizing the thermal response of LCE in robotics, health care, and consumer goods.
Segmentation and removal of surgical instruments for background scene visualization from endoscopic/laparoscopic video

Surgical tool segmentation is becoming imperative to provide detailed information during intra-operative execution. These tools can obscure surgeons' dexterity control due to narrow working space and visual field-of-view, which increases the risk of complications resulting from tissue injuries (e.g. tissue scars and tears). This paper demonstrates a novel application of segmenting and removing surgical instruments from laparoscopic/endoscopic video using digital inpainting algorithms. To segment the surgical instruments, we use a modified U-Net architecture (U-NetPlus) composed of a pre-trained VGG11 or VGG16 encoder and redesigned decoder. The decoder is modified by replacing the transposed convolution operation with an up-sampling operation based on nearest-neighbor (NN) interpolation. This modification removes the artifacts generated by the transposed convolution, and, furthermore, these new interpolation weights require no learning for the upsampling operation. The tool removal algorithms use the tool segmentation mask and either the instrument-free reference frames or previous instrument-containing frames to fill-in (i.e., inpaint) the instrument segmentation mask with the background tissue underneath. We have demonstrated the performance of the proposed surgical tool segmentation/removal algorithms on a robotic instrument dataset from the MICCAI 2015 EndoVis Challenge. We also showed successful performance of the tool removal algorithm from synthetically generated surgical instruments-containing videos obtained by embedding a moving surgical tool into surgical tool-free videos. Our application successfully segments and removes the surgical tool to unveil the background tissue view otherwise obstructed by the tool, producing visually comparable results to the ground truth.
Artificial Intelligence-Guided Subspace Clustering Algorithm for Glioma Images

In order to improve the accuracy of glioma segmentation, a multimodal MRI glioma segmentation algorithm based on superpixels is proposed. Aiming at the current unsupervised feature extraction methods in MRI brain tumor segmentation that cannot adapt to the differences in brain tumor images, an MRI brain tumor segmentation method based on multimodal 3D convolutional neural networks (CNNs) feature extraction is proposed. First, the multimodal MRI is oversegmented into a series of superpixels that are uniform, compact, and exactly fit the image boundary. Then, a dynamic region merging algorithm based on sequential probability ratio hypothesis testing is applied to gradually merge the generated superpixels to form dozens of statistically significant regions. Finally, these regions are postprocessed to obtain the segmentation results of each organization of GBM. Combine 2D multimodal MRI images into 3D original features and extract features through 3D-CNNs, which is more conducive to extracting the difference information between the modalities, removing redundant interference information between the modalities, and reducing the original features at the same time. The size of the neighborhood can adapt to the difference of tumor size in different image layers of the same patient and further improve the segmentation accuracy of MRI brain tumors. The experimental results prove that it can adapt to the differences and variability between the modalities of different patients to improve the segmentation accuracy of brain tumors.
A New Framework for Video-based Frequent Iris Movement Analysis towards Anomaly Observer Detection

: This paper suggested a new framework for detecting abnormal behavior, specifically based on frequent iris movements. It contributed to a decision whereas an individual is dubious or unsuspected from a video. One of the key components of questionable observer detection is to detect some specific suspicious activity. According to the writer, various areas of the body movement and human behaviors may be an indicator of suspicious behavior. In this research, we considered the movement of human eyes to identify suspicious activity. This working field is also a significant aspect of machine vision and artificial intelligence, and a big part of the understanding of human behavior. The system framework comprises three parts to monitor suspicious video activities. First, we used the Multi-task Cascaded Convolutional Networks (MTCNN) classifier to detect eyes. Second, we observe irises from eye representations with the use of Circular Hough Transformation (CHT). Finally, we calculated the average distance of iris movement from eye images using a new morphological method called TRM using some properties of the iris movement. We have observed a particular phenomenon of frequent iris movement. Hence, we are making a case of someone being an abnormal person and referring it to a suspicious observer. To vouch for our work, we created our data set with 100 videos where 30 individuals volunteered to validate this research. Each video comprises 200 frames with a duration of
Biochemical and biophysical characterisation of a small purified lipase from Rhizopus oryzae ZAC3

Abstract The characteristics of a purified lipase from Rhizopus oryzae ZAC3 (RoL-ZAC3) were investigated. RoL-ZAC3, a 15.8 kDa protein, which was optimally active at pH 8 and 55 °C had a half-life of 126 min at 60 °C. The kinetic parameters using p-nitrophenylbutyrate as substrate were 0.19 ± 0.02 mM, 126 ± 5.6 U/ml and 122 s−1 for Km , V max and k cat respectively. RoL-ZAC3 showed stability in methanol and isopropanol with Na+ enhancing the activity. p-nitrophenyloleate and castor oil were the best preferred substrates among the p-nitrophenyl esters and vegetable oils tested respectively. About 43% residual activity was observed after incubation for 30 min at 75 °C. Circular dichroism thermal scan showed that the lipase displayed intense negative ellipticities even at high temperature. Perturbation of the tertiary structure with increasing temperature caused the exposure of hydrophobic side chains to the aqueous environment as revealed by tryptophan fluorescence, with a t−Tm of 50 °C. Differential scanning calorimetry analysis showed melting temperature and calorimetric enthalpy of 55.5 °C and 444 kJ/mol respectively. Dynamic light scattering analysis indicated that the lipase was prone to aggregation upon unfolding at high temperature. It can be concluded that RoL-ZAC3 possesses promising potential for numerous biotechnological applications.
Pharmacophore-Based Comparative Molecular Similarity Indices Analysis of CRTh2 Antagonists

Chemoattractant Receptor Homologous molecule expressed on Th2 cells (CRTh2) is a chemoattractant receptor with seven transmembrane helices targeted for inflammatory diseases such as asthma and allergic rhinitis. In this study, pharmacophore based Comparative Molecular Similarity Indices Analysis (CoMSIA) were performed on the series of 2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl) acetic acids derivatives. Initially, GASP module was used for generation of pharmacophore models using five highly active compounds from the dataset. Among the generated pharmacophores, the best pharmacophore model was selected based on fitness score and was used as template for the alignment of compounds which was used for CoMSIA analysis. The best predictions were obtained utilizing steric, hydrophobic and H-bond acceptor parameters showing a
On the Way to Integrate Increasing Shares of Variable Renewables in China: Experience from Flexibility Modification and Deep Peak Regulation Ancillary Service Market Based on MILP-UC Programming

China has declared ambitious carbon emission reduction targets and will integrate increasing shares of variable renewables for the next decades. The implementation for flexibility modification of thermal power units and deep peak regulation ancillary service market alleviates the contradiction between rapid capacity growth and limited system flexibility. This paper establishes three flexibility modification schemes and two price rules for simulation and proposes an analysis framework for unit commitment problem based on mixed-integer linear programming to evaluate the policy mix effects. Results confirm the promoting effects of flexibility modification on integrating variable renewables and illustrate diverse scheme selections under different renewables curtailment. Particularly, there is no need for selecting expensive schemes which contain more modified units and more developed flexibility, unless the curtailment decrement is compulsorily stipulated or worth for added modification cost. Similarly, results also prove the revenue loss compensation effect of deep peak regulation ancillary service market and illustrate diverse price rule selections under different curtailment intervals. Price rule with more subdivided load intervals and bigger price differences among them is more effective, especially under the higher requirement for curtailment rate. Therefore, the government should further enlarge flexibility modification via but not limited to more targeted compensation price, while generators should further consider a demand-based investment.