Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveling the playing field for international students in IT courses

Australia is a destination of choice for international students studying IT who in 2019 comprised 62% of IT enrolments in universities [9]. Studying in English is often problematic for students from a Non-English Speaking Background (NESB), leading to these students facing barriers with reading instructional materials, reading and writing code and learning English at the same time as learning technical skills. In the area of assessment, NESB students perform at lower levels than domestic students and, anecdotally, these students struggle with exams and tests, where cognitive resources are reduced as a result of stress. This paper is based on an earlier study where the exam format was modified to remove extraneous cognitive load, and keyword glossaries in Mandarin were given to Chinese students as part of a database course exam. The results of the earlier study showed significant improvement in student performance, leading to draft guidelines for developing exams for international students. The current study used these guidelines to redesign an undergraduate database exam, provided students with a choice of keyword glossaries in several languages, and surveyed students immediately after the exam. The results of this intervention were statistically compared with another technical course for students at the same level in the same semester. There was a significant interaction effect, with international students in the Database course performing better than would be expected without intervention. There was no longer a significant difference between international student and domestic student performance in the exam. Results are discussed with respect to cognitive load and mental effort measures.
History-based Model Repair Recommendations

Models in Model-driven Engineering are primary development artifacts that are heavily edited in all stages of software development and that can become temporarily inconsistent during editing. In general, there are many alternatives to resolve an inconsistency, and which one is the most suitable depends on a variety of factors. As also proposed by recent approaches to model repair, it is reasonable to leave the actual choice and approval of a repair alternative to the discretion of the developer. Model repair tools can support developers by proposing a list of the most promising repairs. Such repair recommendations will be only accepted in practice if the generated proposals are plausible and understandable, and if the set as a whole is manageable. Current approaches, which mostly focus on exhaustive search strategies, exploring all possible model repairs without considering the intention of historic changes, fail in meeting these requirements. In this article, we present a new approach to generate repair proposals that aims at inconsistencies that have been introduced by past incomplete edit steps that can be located in the version history of a model. Such an incomplete edit step is either undone or it is extended to a full execution of a consistency-preserving edit operation. The history-based analysis of inconsistencies as well as the generation of repair recommendations are fully automated, and all interactive selection steps are supported by our repair tool called REVISION. We evaluate our approach using histories of real-world models obtained from popular open-source modeling projects hosted in the Eclipse Git repository, including the evolution of the entire UML meta-model. Our experimental results confirm our hypothesis that most of the inconsistencies, namely, 93.4, can be resolved by complementing incomplete edits. 92.6% of the generated repair proposals are relevant in the sense that their effect can be observed in the models’ histories. 94.9% of the relevant repair proposals are ranked at the topmost position.
Examining the Exams: Bloom and Database Modelling and Design

This paper presents the development of an initial framework for the classification and analysis of questions in database modelling and design examinations. Guidelines are provided for the classification of these questions using the revised Bloom’s taxonomy of educational objectives. We report the results of applying the classification scheme to 122 questions from 19 introductory database examinations. We found that there was little variation in the topics and question styles employed and that the degree to which design and modelling is assessed in a typical introductory undergraduate database course’s examination varies widely. We also found gaps in the intellectual complexity of the questions with the examinations failing to provide questions at the analyse and evaluate levels of the revised Bloom’s taxonomy.
Adversarial Specification Mining

There have been numerous studies on mining temporal specifications from execution traces. These approaches learn finite-state automata (FSA) from execution traces when running tests. To learn accurate specifications of a software system, many tests are required. Existing approaches generalize from a limited number of traces or use simple test generation strategies. Unfortunately, these strategies may not exercise uncommon usage patterns of a software system. To address this problem, we propose a new approach, adversarial specification mining, and develop a prototype, Diversity through Counter-examples (DICE). DICE has two components: DICE-Tester and DICE-Miner. After mining Linear Temporal Logic specifications from an input test suite, DICE-Tester adversarially guides test generation, searching for counterexamples to these specifications to invalidate spurious properties. These counterexamples represent gaps in the diversity of the input test suite. This process produces execution traces of usage patterns that were unrepresented in the input test suite. Next, we propose a new specification inference algorithm, DICE-Miner, to infer FSAs using the traces, guided by the temporal specifications. We find that the inferred specifications are of higher quality than those produced by existing state-of-the-art specification miners. Finally, we use the FSAs in a fuzzer for servers of stateful protocols, increasing its coverage.
Macro-economic Factors Influencing Tourism Entrepreneurship: The Case of Kazakhstan

Tourism development contributes to economic development. In emerging economies like Kazakhstan, tourism development needs active entrepreneurship. As the country emerges from the post-Soviet era, there has been an increase in economic development and prosperity. Entrepreneurship in the tourism sector can drive economies forward through the creation of new tourism and hospitality businesses. The macroeconomic environment can influence entrepreneurial activity. We use an autoregressive distributed lag (ARDL) model to examine the impact of macroeconomic factors on tourism entrepreneurship in Kazakhstan. Using data from 1996 to 2018, we find that there is a positive short-run relationship between wages in the tourism sector and entrepreneurship, suggesting that wage growth in the sector attracts entrepreneurs. In the long run, however, tourism sector wages have a negative relationship with entrepreneurship, suggesting that these higher wages represent a higher cost to entrepreneurship. There is also a strong positive relationship between national income and tourism entrepreneurship in Kazakhstan. Implications of macroeconomic policy changes for Kazakhstan and other emerging economies are discussed.
Competing Values Framework as Decoding Tool: Signature Pedagogy in Teaching Business Communication

This article explicates the operationalization of a theoretically robust framework in the teaching of business communication at an institute of higher learning. This article reimagines the design of a business communication course that focuses on the coalescence of both decoding and encoding processes of messages as a unified pedagogical approach in teaching business communication. This approach is in contrast with more conventional approaches in designing communication courses, which tend to prioritize one process over the other. Participants in the study acknowledged the instrumentality in the course design in promoting communicative values with real-world impact.
Mai i te Ao Rangatahi ki te Ao Pakeke Ka Awatea: A Study of Māori Student Success Revisited

This article responds to the paucity of literature on Māori success and presents data from follow-up interviews with eight Māori young adults (pakeke), 6 years after they participated as secondary students (rangatahi) in an initial study titled Ka Awatea: An Iwi Case Study of Māori Students’ Success in 2014. Emerging outcomes reveal the central role of Māori culture and identity in their transition to adulthood. Secondary schooling nurtured their inner confidence and capacity to achieve, but did not play a significant role in development of positive Māori identity and cultural efficacy. However, as school-leavers approaching adulthood, they drew on their cultural efficacy and cultural assets, predominantly acquired from whānau, to navigate dominant culture environments. In doing so, they demonstrate that traditional Māori developmental paths have contemporary relevance, and that their roles—as cultural bearers, passing on the gifts of their ancestors—are fundamental to their aspirations and achievements.
The India–China Confrontation: A View from Seawards

Most Indians assumed that India’s humiliating military defeat at China’s hands in 1962 had jolted its political leadership out of its complacency, engendered by naïve beliefs in the commonality of China’s and India’s aims and aspirations. The current tense confrontation between Indian and Chinese forces in the remote Himalayan wastes of Ladakh, climaxing in the June 2020 sanguinary clash, therefore, came as a rude re-awakening for the Indian public. It is now obvious that over the past three decades, India’s politico-diplomatic establishment has been lulled into the false belief that parleys and summit meetings could ensure peace and tranquillity across the undefined ‘line of actual control’. They also seem oblivious of the fact that growing naval pressure from the south, coupled with existing military pressure in the north, could have ominous security implications for India. Amidst the prevailing perplexity, this essay is a modest attempt to cast some light on the rationale and motivation behind China’s actions and its long-term strategic objectives with a focus on its grandiose maritime ambitions.
Quality evaluation of Cabernet Sauvignon wines in different vintages by 1H nuclear magnetic resonance-based metabolomics

Abstract A proton nuclear magnetic resonance (NMR)-based metabolomic study was used to characterize 2009, 2010, 2011, and 2012 vintages of Cabernet Sauvignon wines from Ningxia, which were vinified using the same fermentation technique. The pattern recognition methods of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal PLS-DA (OPLS-DA) clearly distinguished between the different vintages of wine driven by the following metabolites: valine, 2,3-butanediol, ethyl acetate, proline, succinic acid, lactic acid, acetic acid, glycerol, gallic acid, and choline. The PLS-DA loading plots also differentiated among the metabolites of different vintages. In the 2009 vintage wines, we found the highest levels of gallic acid, valine, proline, and 2,3-butanediol. The 2011 vintage wines contained the highest levels of lactic acid, and the highest levels of ethyl acetate, succinic acid, glycerol, and choline were observed in the 2012 vintage wines. We selected eight metabolites from the 1H NMR spectra that were quantified according to their peak areas, and the concentrations were in agreement with the results of PLS-DA and OPLS-DA analyses.
Euxanthone inhibits traumatic spinal cord injury via anti-oxidative stress and suppression of p38 and PI3K/Akt signaling pathway in a rat model

Abstract Background Owing to neurite promoting, antioxidant and anti-inflammatory effects of Euxanthone (Eux), the investigation was aimed to probe the neuroprotective efficacy of Eux against traumatic spinal cord injury (t-SCI) in rats and whether Eux can improve neuropathic function in t-SCI. Method Sprague-Dawley (SD) rats were randomized in – Sham, t-SCI, Eux30, and Eux60 (t-SCI + 30 and 60 mg/kg respectively). Animals with compression force-induced t-SCI were subjected to estimation of locomotor functions. Spinal cord water content and Evans blue (EB) effusion were determined for quantifying edema and intactness of the spinal cord. Oxidative stress and immunochemical markers were quantified by ELISA and western blotting. Results Findings revealed that Eux60 group animals had greater Basso, Beattie, and Bresnahan (BBB) and (incline plane test) IPT score indicating improved locomotor functions. There was a reduction in the spinal edema and water content after Eux treatment, together with lowering of oxidative stress markers. The expression of IL-6, IL-12, IL-1β, caspase-3, RANKL, TLR4, NF-κB, p-38, PI3K, and Akt in spinal cord tissues of t-SCI-induced rats was lowered after Eux treatment. Conclusion Overall, the investigation advocates that Eux attenuates t-SCI and associated inflammation, oxidative damage, and resulting apoptosis via modulation of TLR4/NF-κB/p38 and PI3K/Akt signaling cascade.
Input/output inconsistencies of daily evapotranspiration conducted empirically using remote sensing data in arid environments

Abstract The reliable quantification of daily evapotranspiration (ET) over vast croplands is a quest in many scholarly works aimed at the precise practice of water resources management. Remote sensing–based empirical and nonempirical models were developed to overcome large-scale quantification issues, which are usually experienced when using conventional approaches for the estimation of ET. The surface energy balance system (SEBS) model was used to quantify the daily ET in the arid/semi-arid over Wadi Ad-Dwaser, Saudi. SEBS input variables are parametrically sensitive and climatic dependent, and the model input/output dependencies are of high comprehensibility; therefore, the optimization analysis of SEBS input/output parameters is the target of the current research. SEBS inputs reciprocal inconsistencies were determined using the artificial neural network analysis, while the output dependencies on the daily ET estimation were mapped. Results demonstrated that the temperature and relative humidity are the most sensitive parameters to be considered in the routine crop monitoring procedure. SEBS output thematic maps showed the robust proportional correlation between the daily ET and the conducted temperature map. Moreover, the estimated daily ET was inversely correlated with the estimated cold sensible heat fluxes. The findings suggest systematic monitoring and forecasting procedures for efficient water-saving management plans in Saudi Arabia.
Moscow University’s field station in the Khibiny Mountains, Russian Arctic: A 70-year history to the present day

Abstract The Khibiny Educational and Scientific Station (KESS) of the Faculty of Geography, M.V. Lomonosov Moscow State University (MSU), was founded in 1948. It is one of the oldest stations of the MSU Faculty of Geography and the only one located north of the Arctic Circle. It is also one of the oldest continuously operating arctic field stations in the world. For more than 70 years, the research station has fostered scientific and international collaboration. Science and education carried out at the station have always gone hand in hand and the research results have been both theoretical and practical. Many generations of Russian geographers owe their successful careers to the research activities at the Khibiny station. Nowadays, it is one of the two major student training bases for the Faculty of Geography as well as a focal point of many national and international research projects, including the International Network for Terrestrial Research and Monitoring in the Arctic (INTERACT) network.
Evolution and biogeography of acidocerine water scavenger beetles (Coleoptera: Hydrophilidae) shaped by Gondwanan vicariance and Cenozoic isolation of South America

The water scavenger beetle subfamily Acidocerinae is a cosmopolitan, ecologically diverse lineage with more than 500 described species whose morphology and classification are poorly understood. We present the first phylogenetic analyses of the subfamily inferred from five loci (18S, 28S, H3, CAD, COI). We used secondary calibrations to estimate divergence times and employ this phylogeny to revise the classification and examine the historical biogeography of this lineage. Most genera are resolved as reciprocally monophyletic, with several exceptions: Horelophopsis syn. n. is recovered as a derived lineage of and placed in synonymy with Agraphydrus. The large genus Helochares, as well as its primary constituent subgenera Helochares (s. str.) and Hydrobaticus are found to be polyphyletic. Batochares stat. n. and Sindolus stat. rev. are elevated from subgenera of Helochares to generic rank. Crephelochares stat. rev. is removed from synonymy with Chasmogenus. We found that the crown Acidocerinae date to the mid‐Jurassic in South America + Africa (West Gondwana). South America and Africa remain important areas of endemism throughout the evolution of the lineage and are resolved either individually or in combination as the ancestral area for all but one clade that is older than 90 million years ago. Six of the seven lineages occurring in South America diverged more than 100 million years ago and are endemic to the region, suggesting the Neotropical acidocerine fauna became isolated following the breakup of West Gondwana. Conversely, lineages found on other Gondwanan fragments (India, Madagascar, Australia) are comparatively young and derived, with all being Cenozoic in age. The few taxa that occur in North America today are all the result of recent Cenozoic dispersal from South America, although North America may have played an important role as an ancestral area in the Mesozoic.
New qsar models for polyhalogenated aromatics

Electronic properties of polychlorinated dibenzo p dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), and polychlorinated diphenyl ethers (PCDEs) were calculated using the semi-empirical AM1 method The calculated electronic descriptors — the energy of the lowest unoccupied molecular orbital (ELUMO), the energy of the highest occupied molecular orbital (EHOMO), the ELUMO-EHOMO gap (dE), and molecular polarizability — are related to the Ah receptor binding affinity values of PCDDs, PCDFs, and PCBs and immunotoxicity values for PCDEs The quantitative structure activity relationships (QSARs) based on chlorine substitution patterns were also constructed, and they proved to be very predictive for Ah receptor binding Significant correlations of the electronic factors were found between the dE and Ah receptor binding affinities for PCDDs, PCDFs, and PCBs and for immunotoxicity of PCDEs A combination of descriptors ELUMO and the total number of chlorine atoms attached to a molecule (nCl) gives significant correlation for the Ah receptor binding of PCDFs and for immunotoxicity of PCDEs Hydrophobicity values taken from the literature were shown to be non-significant for toxicity prediction of these polychlorinated compounds
Numerical solution of variable-order Time fractional Weakly singular Partial integro-differential equations with error estimation

In this paper, we apply Legendre-Laguerre functions (LLFs) and collocation method to obtain the approximate solution of variable-order time-fractional partial integro-diﬀerential equations (VO-TF-PIDEs) with the weakly singular kernel. For this purpose, we derive the pseudo-operational matrices with the use of the transformation matrix. The collocation method and pseudo-operational matrices transfer the problem to a system of algebraic equations. Also, the error analysis of the proposed method is given. We consider several examples to illustrate the proposed method is accurate.
The Effect of Preprocessing Techniques, Applied to Numeric Features, on Classification Algorithms' Performance

It is recognized that the performance of any prediction model is a function of several factors. One of the most significant factors is the adopted preprocessing techniques. In other words, preprocessing is an essential process to generate an effective and efficient classification model. This paper investigates the impact of the most widely used preprocessing techniques, with respect to numerical features, on the performance of classification algorithms. The effect of combining various normalization techniques and handling missing values strategies is assessed on eighteen benchmark datasets using two well-known classification algorithms and adopting different performance evaluation metrics and statistical significance tests. According to the reported experimental results, the impact of the adopted preprocessing techniques varies from one classification algorithm to another. In addition, a statistically significant difference between the considered data preprocessing techniques is demonstrated.
Experimental Study on Feasibility of H2 and N2 as Hydrate Inhibitors in Natural Gas Pipelines

This study applied the temperature search method to investigate the feasibility of pure H2 and N2 gases to inhibit hydrate formation along the subsea natural gas pipeline networks. Hydrates of different mix ratios from CH4 and CO2 were initially formed in a cryogenic sapphire cell to study the component interactions. Each experiment was then repeated by adding either H2 gas or N2 gas to each of the mixes. The component interaction study showed that the risk of hydrates promotion increased with an increase in CH4 content of natural gas. It was discovered that a gas mix of (0.1 CO2 + 0.9 H2) mole fraction did not form hydrate at all pressures up to 20 MPa while that of (0.2 CO2 + 0.8 H2) mole fraction formed at −2 °C at a pressure of 10 MPa. The inability of (0.1 CO2 + 0.9 H2) mole fraction to form hydrate may be due to insufficient CO2 molecules filling the clathrate cage at that particular concentration. Furthermore, all the (CH4 + CO2) mixes formed hydrates and the (0.9 CH4 + 0.1 CO2) mole fraction showe.
Stability analysis for delayed neural networks based on a generalized free-weighting matrix integral inequality

This paper investigates the stability problem of neural networks (NNs) with time-varying delay. Firstly, a new augmented vector and suitable Lyapunov–Krasovskii Functional (LKF) considering activation function are constructed by using more information of time delay. Secondly, a generalized free-weighting matrix integral inequality (GFMII) is chosen to estimate the derivative of single integral terms more accurately. Meanwhile, Jensen integral inequality and improved convex combination are combined to estimate integral terms with activation function; as a result, a novel stability criterion with less conservatism is established. Finally, two numerical examples are employed to illustrate the effectiveness of proposed methods.