Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Diversity Study on Geographical Populations of the Multipurpose Species Elsholtzia stauntonii Using Transferable Microsatellite Markers

Elsholtzia stauntonii Benth. (Lamiaceae) is an economically important ornamental, medicinal and aromatic plant species. To meet the increasing market demand for E. stauntonii, it is necessary to assess genetic diversity within the species to accelerate the process of genetic improvement. Analysis of the transferability of simple sequence repeat (SSR) markers from related species or genera is a fast and economical method to evaluate diversity, and can ensure the availability of molecular markers in crops with limited genomic resources. In this study, the cross-genera transferability of 497 SSR markers selected from other members of the Lamiaceae (Salvia L., Perilla L., Mentha L., Hyptis Jacq., Leonurus L., Pogostemon Desf., Rosmarinus L., and Scutella L.) to E. stauntonii was 9.05% (45 primers). Among the 45 transferable markers, 10 markers revealed relatively high polymorphism in E. stauntonii. The genetic variation among 825 individuals from 18 natural populations of E. stauntonii in Hebei Province of China was analyzed using the 10 polymorphic SSR markers. On the basis of the SSR data, the average number of alleles (NA), expected heterozygosity (HE), and Shannon’s information index (I) of the 10 primers pairs were 7.000, 0.478, and 0.688, respectively. Lower gene flow (Nm = 1.252) and high genetic differentiation (Fst = 0.181) were detected in the populations. Analysis of molecular variance (AMOVA) revealed that most of the variation (81.47%) was within the populations. Integrating the results of STRUCTURE, UPGMA (Unweighted Pair Group Method with Arithmetic Mean) clustering, and principal coordinate analysis, the 825 samples were grouped into two clusters associated with geographical provenance (southwestern and northeastern regions), which was consistent with the results of a Mantel test (r = 0.56, p < 0.001). Overall, SSR markers developed in related genera were effective to study the genetic structure and genetic diversity in geographical populations of E. stauntonii. The results provide a theoretical basis for conservation of genetic resources, genetic improvement, and construction of a core collection for E. stauntonii.
Clinical Strategies to Develop Connections, Promote Health and Address Pain From the Perspectives of Indigenous Youth, Elders, and Clinicians

In this article we discuss findings from a community based, participatory action research study. The aim was to understand how Indigenous youth describe, experience, manage pain and hurt and how they seek care. A critical analysis guided by Two-Eyed Seeing and Medicine Wheel frameworks highlighted important clinical strategies for Indigenous youth to balance their health and reduce pain. This study is a partnership project with an Aboriginal Health Centre in Southern Ontario and the Canadian Institute of Health Research funded Aboriginal Children's Hurt and Healing Initiative (ACHH). The study gathered perspectives of Indigenous youth, Elders, and health clinicians using conversation sessions guided by a First Nations doctoral student and nurse researcher. Using the medicine wheel framework three main thematic areas emerged across the three groups and include (1) Predictors of Imbalance; (2) Indicators of Imbalance; and (3) Strategies to re-establish balance health in relation to pain. The main strategy includes considerations for clinicians using the acronym LISTEN (Language, Individual, Share, Teachable moments, Engage, and Navigate) approach that outlines strategies for clinicians that will be a safe guide to manage pain and hurt.
Computed Tomography-Based Radiomics for Differentiation of Thymic Epithelial Tumors and Lymphomas in Anterior Mediastinum

Objective To investigate the differential diagnostic performance of computed tomography (CT)-based radiomics in thymic epithelial tumors (TETs) and lymphomas in anterior mediastinum. Methods There were 149 patients with TETs and 93 patients with lymphomas enrolled. These patients were assigned to a training set (n = 171) and an external validation set (n = 71). Dedicated radiomics prototype software was used to segment lesions on preoperative chest enhanced CT images and extract features. The multivariable logistic regression algorithm was used to construct three models according to clinico-radiologic features, radiomics features, and combined features, respectively. Performance of the three models was compared by using the area under the receiver operating characteristic curves (AUCs). Decision curve analysis was used to evaluate clinical utility of the three models. Results For clinico-radiologic model, radiomics signature model, and combined model, the AUCs were 0.860, 0.965, 0.975 and 0.843, 0.961, 0.955 in the training cohort and the test cohort, respectively (all P<0.05). The accuracies of each model were 0.836, 0.895, 0.918 and 0.845, 0.901, 0.859 in the two cohorts, respectively (all P<0.05). Compared with the clinico-radiologic model, better diagnostic performances were found in the radiomics signature model and the combined model. Conclusions Radiomics signature model and combined model exhibit outstanding and comparable differential diagnostic performances between TETs and lymphomas. The CT-based radiomics analysis might serve as an effective tool for accurately differentiating TETs from lymphomas before treatment.
Do Oil Price Shocks Matter for Environmental Degradation? Evidence of the Environmental Kuznets Curve in GCC Countries

This paper aims to examine the asymmetric impact of oil price shocks on environmental degradation for a panel of six Gulf Cooperation Council (GCC) countries from 1996 to 2016. We use the dynamic seemingly unrelated regressions (DSUR) approach that considers cross-sectional dependency to reveal the interrelations between oil price shocks and carbon dioxide (CO2) emissions. The finding shows that the positive shocks of oil prices have a statistically significant negative effect on CO2 emissions, while negative shocks of oil prices did not affect CO2 emissions. More specifically, the positive oil price shocks have negatively influenced the CO2 emissions in Oman, Bahrain, Saudi Arabia, Qatar, and United Emirates Arab. In turn, the most negative effect is found in Qatar and Saudi Arabia. Meanwhile, the negative shocks of oil prices have statistically significant effects on the CO2 emission of Oman and Saudi Arabia. While for other countries, it does not have a significant impact. Also, the results support an environmental Kuznets curve in Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates; in contrast, the hypothesis was rejected in Bahrain and Oman. This study could help policymakers adopt renewable energy policies and use energy-saving technologies to sustain economic development and improve environmental quality.
Adenosine in Acute Myocardial Infarction-Associated Reperfusion Injury: Does it Still Have a Role?

The mainstay of acute myocardial infarction has long been timely reperfusion of the culprit obstruction. Reperfusion injury resulting from a multitude of pathophysiological processes has been demonstrated to negatively affect myocardial recovery and function post-infarction. Adenosine interacts directly with the sequential pathophysiological processes culminating in reperfusion injury by inhibiting them upstream. The evidence for adenosine’s benefit in acute myocardial infarction has produced mixed results with regards to myocardial salvage and long-term mortality. The heterogenous evidence with regards to benefits on clinical outcomes has resulted in modest uptake of adenosine in the clinical setting. However, it is critical to analyze the variability in study methodologies. The goal of this review is to evaluate how adenosine dose, route of administration, timing of administration, and site of administration play essential roles in the molecule’s efficacy. The benefits of adenosine, as highlighted in the following review, are clear and its role in the treatment of acute myocardial infarction should not be discounted
An Assessment of Robustness for Adversarial Attacks and Physical Distortions on Image Classification using Explainable AI

Introducing defence mechanisms to overcome the vulnerability of adversarial attacks is a highly focused research area. However recent research highlights that introducing defence approaches for man-made adversarial attacks is not sufficient, because the deep learning models are vulnerable to the perturbations outside the scope of the training set and the physical world itself acts as an adversarial sample generator. Given this caveat, there is a necessity to introduce general defence approaches for both man-made and physical world adversarial samples. Prior to that, a brief explanation of how the model’s decision-making process happens in the inference phase under the various adversarial perturbations is required. However, the deep learning models act as black boxes in the inference phase where the decision-making is not interpretable. As a result, research on model interpretability and explainability has been carried out in the domain which is collectively known as Explainable AI. Using a set of Explainable AI techniques, this study is investigating the deep learning networks’ robustness; i.e., the decision-making process in neural networks and important pixel attributes for the predictions that are captured when the deep learning model inference gets adversarial inputs. These adversarial inputs are perturbed by adversarial attacks or the physical world adversaries using the deep learning network trained on the CIFAR10 dataset. The study reveals, that when the inference gets adversarial samples, the necessary pixel attributes for the prediction captured by the network vary everywhere in the image. However, when the network is re-trained using adversarial training or data transformation-based augmentation, it will be able to capture pixel attributes within the particular object or reduce the capture of negative pixel attributes. Based on the deductions gained from the findings, this paper states some potential research approaches to introduce a general adversarial defence method.
Scalable Machine Learning using Dataflow Graph Analysis

In the past decade, the abundance of computing resources and the growth of data have boosted the development of machine learning applications. Many computation frameworks, e.g., Hadoop, Spark, TensorFlow, and PyTorch, have been proposed and become widely used in the industry. However, programming large-scale machine learning applications is still challenging and requires the manual efforts of developers to achieve good performance. This thesis discusses two major issues with the existing frameworks. First, array is a popular data abstraction for machine learning computation. When parallelizing arrays to hundreds of CPU machines, it is critical to choose a good partition strategy to co-locate the computation arrays to reduce network communication. Unfortunately, existing distributed array frameworks usually use a fixed partition scheme and requires manually partitioning if another parallel strategy is used, making it less easy to develop a distributed array program. Secondly, GPU is widely used for a popular branch of machine learning applications, deep learning. Modern GPU can be orders of magnitude faster than CPU and becomes an attractive computation resource. However, the limited memory size of GPU restricts the scale of the DNN models can be run. It is desirable to iv
Debates on European Integration in the Finnish Parliament (Eduskunta) 1990-2020

In this article I analyse parliamentary debates of the Finnish Parliament ( Eduskunta ) on European integration from 1990 to 2020. Finland joined the European Union (EU) in 1995, but Finland’s integration history dates back to the late 1950s and early 1960s. In the turbulent years following the end of the Cold War and the collapse of the Soviet Union in the early 1990s, European integration rose higher on the Finnish political agenda. The data used in this article consist of a machine-readable database of plenary protocols of the Finnish Parliament. The main database covers the whole lifespan of the modern Finnish Parliament since 1906. The dataset used for the analysis contains all plenary speeches with references to “Europe”, “European” and “Europeanism” (N=25,674), together with adequate metadata. The core analysis focuses on six time windows, each with a span of three years. These focus widows are linked to nationally important key European events. Methodologically, the article is rooted in Exploratory Data Analysis (EDA) and applies different text mining tools to explore, analyse and visualise how members of the Finnish Eduskunta politicise and debate European issues. The analysis is carried out in three steps. First, I use traditional term-based text mining methods to explore the vocabulary used in the debate, both across time and by parliamentary faction. In the second step, I use tf-idf analysis to explore the vocabulary differentiating parliamentary factions. The analysis is rounded out in the third step by the application of Text Network Analysis (TNA). I apply TNA to explore and visualise topics in the collection of plenary speeches and, thus, to evidence the power and usefulness of this novel method as a complement to other topic modelling methods. Overall, the results presented in this article find strong support when critically reflected against findings from previous studies. The results also significantly improve our knowledge and understanding of national parliamentary debates on European integration. Further, the article is encouraging when it comes to the application of computational methods and tools on large corpora of unstructured political texts.
Laboratory Experiments of Wave Attenuation by Mud

Muddy deposits make up a large region of the world’s coastal lands such as the Gulf of Mexico, the Louisiana coastline, and the Persian Gulf. These regions serve as valuable resources for the world’s population for commerce, leisure activities, and sustainability. Human activities depend on the comprehensive understanding of the natural occurrences that take place in these coastal zones. The interaction between waves and the muddy sea bottom has profound effects on these human activities because the damping of waves in these regions creates turbidity, which can disrupt the natural habitat for marine and coastal life. The purpose of this study is to better understand the mechanisms of water wave damping over mud as a function of water depth, wave height and period. In a series of laboratory experiments, the damping rate was determined for different wave parameters in intermediate and shallow water for a kaolinite mud bed. The results show that the damping rate is highly dependent on the rate of work performed by the waves on the bottom. Damping in deep water was also observed in laboratory experiments. Water waves ii
Augmenting Information Flow for Visual Privacy

In the Information Age, visual media take on powerful new forms. Photographs that were once printed on paper and stored in physical albums now exist as digital files. With the rise of social media, photo data has moved to the cloud for rapid dissemination. The upside can be measured in terms of increased efficiency, greater reach, or reduced printing costs. But there is a downside that is harder to quantify: the risk of private photos or videos leaking inappropriately. Human imagery is potentially sensitive, revealing private details of a person’s body, lifestyle, activities, and more. Images create visceral responses and have the potential to permanently damage a person’s reputation. We employ the theory of contextual integrity to explore certain privacy aspects of transmitting the human visual form. In response to privacy threats from new sociotechnical systems, we develop practical solutions that have the potential to restore balance. The main work is a set of client-side, technical interventions that can be used to alter information flows and provide features to support visual privacy. In the first approach, we use crowdsourcing to extract specific, useful human signal from video to decouple it from bundled identity information. The second approach is an attempt to achieve similar ends with pure software. Instead of using information workers, we develop a series of filters that alter video to hide identity information while still revealing motion signal. The final approach is an attempt to control the recipients of photo data by encoding data in the visual channel. The software completely protects data from third-parties who lack proper credentials and maintains data integrity by exploiting the visual coherence of uploaded images, even in the face of JPEG compression. The software offers end-to-end encryption that is compatible with existing social media applications.
Qualitative Comparison of Native and Machine-Translated Parliamentary Debates

Machine translation (MT) models have become increasingly accurate and widely accessible for multiple languages in recent years. They can potentially lift the barriers to applying NLP tools and methods to previously unsupported languages and boost comparative cross-lingual research in digital humanities. This study empirically contrasts results obtained with source and target Slovenian ParlaMint corpus of parliamentary debates on topic modelling. It qualitatively compares three steps in topic interpretation: topic description, topic significance in subcorpora, and marginal topic distribution. The results indicate that the topic modelling on the target corpus only partially replicates the topic modelling on the source corpus, but the overlap is sufficient to provide a starting point for the cross-country comparison.
Three-dimensional bond model considering the coupled damage effect for dowel action

The behaviour of the dowel action as a shear transfer mechanism across interfaces and joints has been recognised as an important component of structural analysis. In this paper, a three-dimensional non-linear bond model considering the coupled damage effect of concrete was developed to simulate the mechanism of interaction between reinforced bars and subgrade concrete. The local axis strain of the rebar and the local compressive strain of concrete were chosen as quantitative indicators of the damage effect. In total, 15 specimens were tested to investigate the effect of the bar diameters, concrete strength, pre-tension and concrete cover on the dowel action. A parameter study based on the experimental data was performed to calibrate the damage index of the model. Verification of the model was conducted by comparing the analysis results with available experimental results. The results show that the proposed model gives good predictions for both failure mechanisms of dowel action.
Influence of motivation on academic performance: an analysis of motivational assessment in mathematics learning

The objective of the study consisted of relating motivation with academic performance in mathematics in schoolchildren in northern Colombia, through the use of Pearson's correlation coefficient, applying the motivational assessment of the learning process (EMPA) questionnaire, to establish the levels of extrinsic and intrinsic motivation of the 65 students belonging to the sample. Academic performance was obtained through second source information provided by the academic coordination of the institution understudy, a quantitative and correlational approach was used. The results show a significant negative correlation in the dimensions of intrinsic and extrinsic motivation with academic performance. Given this, new lines of research are proposed, especially accompaniment by parents and guardians, and socioeconomic characteristics and their relationship to academic motivation.
Autoinhibition of CYP3A4 Leads to Major Role of CYP2C8 in Imatinib Metabolism: Variability in CYP2C8 Activity May Alter Plasma Concentrations and Response

AUC, area under the concentration-time curve; C hepatic clearance; 1-O- β Abstract Recent data suggest that the role of CYP3A4 in imatinib metabolism is smaller than presumed. This study aimed to evaluate the quantitative importance of different cytochrome P450 (P450) enzymes in imatinib pharmacokinetics. First, the metabolism of imatinib was investigated using recombinant P450 enzymes and human liver microsomes with P450 isoform-selective inhibitors. Thereafter, an in silico model for imatinib was constructed to perform pharmacokinetic simulations to assess the roles of P450 enzymes in imatinib elimination at clinically used imatinib doses. In vitro , CYP2C8 inhibitors and CYP3A4 inhibitors inhibited the depletion of 0.1 µM imatinib by 45% and 80%, respectively, and the formation of the main metabolite of imatinib, N-desmethylimatinib, by >50%. Likewise, recombinant CYP2C8 and CYP3A4 metabolized imatinib extensively, whereas other isoforms had minor effect on imatinib concentrations. In the beginning of imatinib treatment, the fractions of its hepatic clearance mediated by CYP2C8 and CYP3A4 were predicted to approximate 40% and 60%, respectively. During long-term treatment with imatinib 400 mg once or twice daily, up to 65% or 75% of its hepatic elimination was predicted to occur via CYP2C8, and only about 35% or 25% by CYP3A4, due to dose-and time-dependent autoinactivation of CYP3A4 by imatinib. Thus, although CYP2C8 and CYP3A4 are the main enzymes in imatinib metabolism in vitro, in silico predictions indicate that imatinib inhibits its own CYP3A4-mediated metabolism, assigning a key role for CYP2C8. During multiple dosing, pharmacogenetic polymorphisms and drug interactions affecting CYP2C8 activity may cause marked interindividual variation in the exposure and response to imatinib. whereas it reduced the AUC of N-DMI by 59%-84%. The inhibition of both CYP2C8 and CYP3A4 was predicted to markedly increase imatinib AUC 2.9-fold, and almost completely inhibit N-DMI formation (by >79%). to evaluate the clinical relevance of CYP2C8 and CYP3A4 in imatinib elimination. Although clinical studies are necessary to confirm our in vitro-in silico findings, it is likely that imatinib time-dependently inhibits its own CYP3A4-mediated metabolism, leading to a key role for CYP2C8 in its elimination. Thus, during multiple dosing, both pharmacogenetic polymorphisms and drug interactions affecting CYP2C8 activity may cause marked interindividual variability in the exposure and response to imatinib. Overall, the present findings highlight the need to carefully evaluate the implications of MBI using integrated in vitro and modeling/simulation approaches.
Incorporating WebQuest as an Internet-based Learning Device in EFL Writing Class

: This article reports the result of a study investigating how WebQuest as an internet-based learning device can be incorporated in EFL writing class which is section of a wider case study on Using WebQuest in Indonesian EFL writing class. Twenty-three EFL students enrolled in the course of Argumentative Writing and an English teacher at the English Education Department of Institut Agama Islam Negeri Palangka Raya Indonesia became the subjects of the study. The activities of teaching writing using WebQuest as an internet-based learning device in EFL writing class were as the data sources. The researcher himself equipped with research instruments; observation checklist, field notes, interview, and documentation, were used for the data collection. The collected data were further analysed to draw a conclusion. The results show that WebQuest could be incorporated in the activities of writing in Indonesian EFL writing class through WebQuest activity as the guideline in the process of producing essay by adjusting the writing process activities according to the guidelines in the WebQuest menu; introduction, tasks, process, resources, evaluation, and conclusion.