Miracle-dz/UniFAR-FTUs huggingface dataset:
TAIT]ORING CLOZE: THREE WAYS TO IMPROVE CLOZE

Cloze procedure first surfaced when Taylor (1953) investigated its effectiveness as a tool for measuring the readability of written materials. Research soon tumed to cloze as a measure of native-speaker reading proficiency (Ruddell, 1964; Gallant, 19651' Bormuth, 1965, 1967; Crawford,1970). In the 1960s, studies began to surface on cloze as a m€asure of overall ESL proficiency(for overviews of this L2 research on cloze, see Alderson, 1978 or Oller, 1979). However, a careful review of the L2 cloze literature in the last three decades reveals results that are far from consistent in terms of their reliability and validity. Studies of cloze test reliability address the issue of the consistency of cloze scores. Reliability statistics can range from a minimum of . 00 (for completely inconsistent scores) to a maximum of 1.00 (for completely consistent scores). To date, the research has shown cloze test reliabilities that have ranged from . 31 to . 96 (Darnell, 1970; Oller,
Spatiotemporal Feature Learning Based Hour-Ahead Load Forecasting for Energy Internet

In this paper, we analyze the characteristics of the load forecasting task in the Energy Internet context and the deficiencies of existing methods and then propose a data driven approach for one-hour-ahead load forecasting based on the deep learning paradigm. The proposed scheme involves three aspects. First, we formulate a historical load matrix (HLM) with spatiotemporal correlation combined with the EI scenario and then create a three-dimensional historical load tensor (HLT) that contains the HLMs for multiple consecutive time points before the forecasted hour. Second, we preprocess the HLT leveraging a novel low rank decomposition algorithm and different load gradients, aiming to provide a forecasting model with richer input data. Third, we develop a deep forecasting framework (called the 3D CNN-GRU) featuring a feature learning module followed by a regression module, in which the 3D convolutional neural network (3D CNN) is used to extract the desired feature sequences with time attributes, while the gated recurrent unit (GRU) is responsible for mapping the sequences to the forecast values. By feeding the corresponding load label into the 3D CNN-GRU, our proposed scheme can carry out forecasting tasks for any zone covered by the HLM. The results of self-evaluation and a comparison with several state-of-the-art methods demonstrate the superiority of the proposed scheme.
SUPERSONIC TWO-DIMENSIONAL PLUG NOZZLE CONCEPTION AT HIGH TEMPERATURE

When the stagnation temperature of a perfect gas increases, the specific heats and their ratio do not remain constant any more and start to vary with this temperature. The gas remains perfect, its state equation remains always valid, except it will name in more calorically imperfect gas or gas at High Temperature. The goal of this research is to trace the profiles of the supersonic Plug Nozzle when this stagnation temperature is taken into account, lower than the threshold of dissociation of the molecules, by using the new formula of the Prandtl Meyer function, and to have for each exit Mach number, several nozzles shapes by changing the value of this temperature. A study on the error given by the PG model compared to our model at high temperature is presented. The comparison is made with the case of a calorically perfect gas aiming to give a limit of application of this model.
Title Genome-wide analysis of ionotropic receptors provides insight into their evolution in Heliconius butterflies Permalink

Background: In a world of chemical cues, smell and taste are essential senses for survival. Here we focused on Heliconius, a diverse group of butterflies that exhibit variation in preand post-zygotic isolation and chemicallymediated behaviors across their phylogeny. Our study examined the ionotropic receptors, a recently discovered class of receptors that are some of the most ancient chemical receptors. Results: We found more ionotropic receptors in Heliconius (31) than in Bombyx mori (25) or in Danaus plexippus (27). Sixteen genes in Lepidoptera were not present in Diptera. Only IR7d4 was exclusively found in butterflies and two expansions of IR60a were exclusive to Heliconius. A genome-wide comparison between 11 Heliconius species revealed instances of pseudogenization, gene gain, and signatures of positive selection across the phylogeny. IR60a2b and IR60a2d are unique to the H. melpomene, H. cydno, and H. timareta clade, a group where chemosensing is likely involved in pre-zygotic isolation. IR60a2b also displayed copy number variations (CNVs) in distinct populations of H. melpomene and was the only gene significantly higher expressed in legs and mouthparts than in antennae, which suggests a gustatory function. dN/dS analysis suggests more frequent positive selection in some intronless IR genes and in particular in the sara/sapho and melpomene/cydno/timareta clades. IR60a1 was the only gene with an elevated dN/dS along a major phylogenetic branch associated with pupal mating. Only IR93a was differentially expressed between sexes. Conclusions: All together these data make Heliconius butterflies one of the very few insects outside Drosophila where IRs have been characterized in detail. Our work outlines a dynamic pattern of IR gene evolution throughout the Heliconius radiation which could be the result of selective pressure to find potential mates or host-plants.
Targeting the RNA Polymerase I Transcription for Cancer Therapy Comes of Age

Transcription of the ribosomal RNA genes (rDNA) that encode the three largest ribosomal RNAs (rRNA), is mediated by RNA Polymerase I (Pol I) and is a key regulatory step for ribosomal biogenesis. Although it has been reported over a century ago that the number and size of nucleoli, the site of ribosome biogenesis, are increased in cancer cells, the significance of this observation for cancer etiology was not understood. The realization that the increase in rRNA expression has an active role in cancer progression, not only through increased protein synthesis and thus proliferative capacity but also through control of cellular check points and chromatin structure, has opened up new therapeutic avenues for the treatment of cancer through direct targeting of Pol I transcription. In this review, we discuss the rational of targeting Pol I transcription for the treatment of cancer; review the current cancer therapeutics that target Pol I transcription and discuss the development of novel Pol I-specific inhibitors, their therapeutic potential, challenges and future prospects.
Compact Ultra-Wideband Bandpass Filters Achieved by Using a Stub-Loaded Stepped Impedance Resonator

In this paper, we develop a bandpass filter using a stub-loaded stepped impedance resonator (SLSIR) and calculate the even and odd resonant modes of this type of resonator using the input impedance/admittance analysis. In this study, two impedance ratios and two length ratios are operated as the design parameters for controlling the resonant modes of the SLSIR. Several resonant mode variation curves operating three resonant modes with different impedance ratios and two length ratios are developed. By tuning the desired impedance ratios and length ratios of the SLSIRs, compact ultra-wideband (UWB) bandpass filters (BPFs) can be achieved. Two examples of the UWB BPFs are designed in this study. The first example is UWB filter with a wide stopband and the second one is dual UWB BPF, namely, with UWB performance and a notch band. The first filter is designed for a UWB response from 3.1 to 5.26 GHz having a stopband from 5.3 to 11 GHz, with an attenuation level better than 18 dB. The second filter example is a dual UWB BPF with the frequency range from 3.1 to 5 GHz and 6 to 10.1 GHz using two sets of the proposed SLSIR. The measured results have insertion loss of less than 1 dB, and return loss greater than 10 dB. Furthermore, the coupling structures and open stub of the SLSIR also provide several transmission zeros at the skirt of the passbands for improving the passband selectivity.
The GEO-URBAN Project-Identification and Assessment of Deep GEOthermal Heat Resources in Challenging URBAN Environments

Deep geothermal resources in challenging, low-enthalpy settings are generally poorly understood and remain largely untapped. The GEO-URBAN project is funded by the EU GEOTHERMICA ERA-NET Co-fund, and aims to investigate the deep geothermal resources of two urban locations using a novel combination of geophysical techniques. This three-year study is conducting an initial assessment of the potential for low enthalpy geothermal energy in two study areas, Dublin City, Ireland and Vallés, Catalonia, Spain. A multi-disciplinary geophysical exploration strategy has been developed for both targets to overcome exploration challenges in the built urban environment. A combination of electromagnetic methods, including magnetotellurics and controlled source electromagnetics, will be utilised in conjunction with passive seismic methods, including H/V and ambient noise cross-correlation. This multi-disciplinary method can be easily deployed in urban regions to increase the understanding of subsurface structures where legacy datasets are inadequate for geothermal exploration, and also for regions where funding for the collection of new data is limited. The GEO-URBAN project includes significant local stakeholder involvement to ensure that exploration activities align with local sustainable energy plans and district heating strategies. Furthermore, a review of the current policy and legislation governing the development of geothermal energy systems is being undertaken in conjunction with the geophysics survey programme; this review will conclude with recommendations and examples of policy measures proven to stimulate market growth in other European countries. This will assist the sustainable exploitation of deep geothermal energy resources in each region by increasing awareness amongst stakeholders and policy makers but also by highlighting the barriers towards geothermal development in an effort to derisk future developments. The overall objective of GEO-URBAN is to identify the geothermal resources available in two challenging urban locations and to demonstrate a commercialisation strategy that has the potential to be adapted in other similar locations, thus advancing the uptake of geothermal energy in the study locations and emerging markets internationally.
Feature Dimension Reduction Using Stacked Sparse Auto-Encoders for Crop Classification with Multi-Temporal, Quad-Pol SAR Data

Crop classification in agriculture is one of important applications for polarimetric synthetic aperture radar (PolSAR) data. For agricultural crop discrimination, compared with single-temporal data, multi-temporal data can dramatically increase crop classification accuracies since the same crop shows different external phenomena as it grows up. In practice, the utilization of multi-temporal data encounters a serious problem known as a “dimension disaster”. Aiming to solve this problem and raise the classification accuracy, this study developed a feature dimension reduction method using stacked sparse auto-encoders (S-SAEs) for crop classification. First, various incoherent scattering decomposition algorithms were employed to extract a variety of detailed and quantitative parameters from multi-temporal PolSAR data. Second, based on analyzing the configuration and main parameters for constructing an S-SAE, a three-hidden-layer S-SAE network was built to reduce the dimensionality and extract effective features to manage the “dimension disaster” caused by excessive scattering parameters, especially for multi-temporal, quad-pol SAR images. Third, a convolutional neural network (CNN) was constructed and employed to further enhance the crop classification performance. Finally, the performances of the proposed strategy were assessed with the simulated multi-temporal Sentinel-1 data for two experimental sites established by the European Space Agency (ESA). The experimental results showed that the overall accuracy with the proposed method was raised by at least 17% compared with the long short-term memory (LSTM) method in the case of a 1% training ratio. Meanwhile, for a CNN classifier, the overall accuracy was almost 4% higher than those of the principle component analysis (PCA) and locally linear embedded (LLE) methods. The comparison studies clearly demonstrated the advantage of the proposed multi-temporal crop classification methodology in terms of classification accuracy, even with small training ratios.
Using Discrete Wavelet Transform for texture classification by using energy

In this paper suggests a new image classification scheme of texture images, using the discrete wavelet transformation (DWT). A good classification relies on feature extraction stage. Several samples (texture images) of several classes were analyzed using wavelet transform which is new and promising set of tools. In this work, it was shown that
Relation between the Friction Angle of Sand at Triaxial Compression and Triaxial Extension and Plane Strain Conditions

The strength of sand is usually characterized by the maximum value of the secant friction angle. The friction angle is a function of deformation mode, density, and stress level and is strongly correlated with dilatancy at failure. Most often, the friction angle is evaluated from results of conventional compression tests, and correlation between the friction angle of sand at triaxial compression and triaxial extension and plane strain conditions is a vital problem of soil mechanics. These correlations can be obtained from laboratory test results. The failure criteria for sand presented in literature also give the possibility of finding correlations between friction angles for different deformation modes. The general stress-dilatancy relationship obtained from the frictional state concept, with some additional assumptions, gives the possibility of finding theoretical relationships between the friction angle of sand at triaxial compression and triaxial extension and plane strain conditions. The theoretically obtained relationships presented in the paper are fully consistent with theoretical and experimental findings of soil mechanics.
Plateau Grass and Greenhouse Flower? Distinct Genetic Basis of Closely Related Toad Tadpoles Respectively Adapted to High Altitude and Karst Caves

Genetic adaptation to extremes is a fascinating topic. Nevertheless, few studies have explored the genetic adaptation of closely related species respectively inhabiting distinct extremes. With deep transcriptome sequencing, we attempt to detect the genetic architectures of tadpoles of five closely related toad species adapted to the Tibetan Plateau, middle-altitude mountains and karst caves. Molecular evolution analyses indicated that not only the number of fast evolving genes (FEGs), but also the functioning coverage of FEGs, increased with elevation. Enrichment analyses correspondingly revealed that the highland species had most of the FEGs involved in high-elevation adaptation, for example, amino acid substitutions of XRCC6 in its binding domains might improve the capacity of DNA repair of the toad. Yet, few FEGs and positively selected genes (PSGs) involved in high-elevation adaptation were identified in the cave species, and none of which potentially contributed to cave adaptation. Accordingly, it is speculated that in the closely related toad tadpoles, genetic selection pressures increased with elevation, and cave adaptation was most likely derived from other factors (e.g., gene loss, pseudogenization or deletion), which could not be detected by our analyses. The findings supply a foundation for understanding the genetic adaptations of amphibians inhabiting extremes.
From The Enzyme List to Pathways and Back Again

The IUBMB Enzyme List is widely used by other databases as a source for avoiding ambiguity in the recognition of enzymes as catalytic entities. However, it was never designed for activities such as pathway tracing, which have become increasingly important in systems biology. This is because it often relies on generic or representative reactions to show the reactions catalysed by enzymes of wide specificity. It is necessary to go to databases such as BRENDA to find further, more detailed, information on what is known about the range of substrates for any particular enzyme. In order to provide a framework for tracing pathways involving any specific enzyme or metabolite, we have created a Reactions Database from the material in the Enzyme list. This allows reactions to be searched by substrate/product and pathways to be traced from any selected starting/seed substrate. An extensive synonym glos-sary allows searches by any of the alternative names, including accepted abbreviations, by which a chemical compound may be known. This database was necessary for the development of the application Reaction Explorer (http://www.reaction-explorer.org/), which was written in REALbasic to search the Reactions Database and draw metabolic pathways from reactions selected by the user. Having input the name of the starting compound (the ‘‘seed’’), the user is presented with a list of all reactions containing that compound and then selects the product of interest as the next point on the ensuing graph. The pathway diagram is then generated as the process iterates. A contextual menu is provided,
Lactate-Fortified Puerariae Radix Fermented by Bifidobacterium breve Improved Diet-Induced Metabolic Dysregulation via Alteration of Gut Microbial Communities

Background: Puerariae Radix (PR), the dried root of Pueraria lobata, is reported to possess therapeutic efficacies against various diseases including obesity, diabetes, and hypertension. Fermentation-driven bioactivation of herbal medicines can result in improved therapeutic potencies and efficacies. Methods: C57BL/6J mice were fed a high-fat diet and fructose in water with PR (400 mg/kg) or PR fermented by Bifidobacterium breve (400 mg/kg) for 10 weeks. Histological staining, qPCR, Western blot, and 16s rRNA sequencing were used to determine the protective effects of PR and fermented PR (fPR) against metabolic dysfunction. Results: Treatment with both PR and fPR for 10 weeks resulted in a reduction in body weight gain with a more significant reduction in the latter group. Lactate, important for energy metabolism and homeostasis, was increased during fermentation. Both PR and fPR caused significant down-regulation of the intestinal expression of the MCP-1, IL-6, and TNF-α genes. However, for the IL-6 and TNF-α gene expressions, the inhibitory effect of fPR was more pronounced (p < 0.01) than that of PR (p < 0.05). Oral glucose tolerance test results showed that both PR and fPR treatments improved glucose homeostasis. In addition, there was a significant reduction in the expression of hepatic gene PPARγ, a key regulator of lipid and glucose metabolism, following fPR but not PR treatment. Activation of hepatic AMPK phosphorylation was significantly enhanced by both PR and fPR treatment. In addition, both PR and fPR reduced adipocyte size in highly significant manners (p < 0.001). Treatment by fPR but not PR significantly reduced the expression of PPARγ and low-density lipoproteins in adipose tissue. Conclusion: Treatment with fPR appears to be more potent than that of PR in improving the pathways related to glucose and lipid metabolism in high-fat diet (HFD)+fructose-fed animals. The results revealed that the process of fermentation of PR enhanced lactate and facilitated the enrichment of certain microbial communities that contribute to anti-obesity and anti-inflammatory activities.
A Variation-Aware Design Methodology for Distributed Arithmetic

Distributed arithmetic (DA) brings area and power benefits to digital designs relevant to the Internet-of-Things. Therefore, new error resilient techniques for DA computation are urgently required to improve robustness against the process, voltage, and temperature (PVT) variations. This paper proposes a new in-situ timing error prevention technique to mitigate the impact of variations in DA circuits by providing a guardband for significant (most significant bit) computations. This guardband is initially achieved by modifying the sign extension block and carefully gate-sizing. Therefore, least significant bit (LSB) computation can correspond to the critical path, and timing error can be tolerated at the cost of acceptable accuracy loss. Our approach is demonstrated on a 16-tap finite impulse respons (FIR) filter using the 65 nm CMOS process and the simulation results show that this design can still maintain high-accuracy performance without worst case timing margin, and achieve up to 32 % power savings by voltage scaling when the worst case margin is considered with only 9 % area overhead.
The Exports of Higher Education Services from OECD Countries to Asian Countries, A Gravity Approach

We analyze bilateral exports of higher education services between OECD countries and Asia, using a gravity equation approach, panel data from 1998 to 2016, and PPML regression. The approach treats higher education consumption by Asian countries as a consumable durable good reflecting investment in human capital. Asian Students come to OECD countries to obtain degrees from their universities. Structurally, the flow of students from Asian country j to OECD country i depends on the higher-education capacity of i, the perceived quality of universities in i, expected earnings in i, a series of bilateral transaction costs between i and j, the income per capita in j, school-age demographics in j, and the usual multilateral trade resistance terms. We find that bilateral flows of students are strongly influenced by wage levels in the host country, bilateral distance, importers’ income, demographics, common language, the visa regime prevailing in bilateral country pairs, and the network of migrants from j in i. These results hold through a variation of specifications, proxies, and estimation methods. We find mixed evidence on the role of tertiary education capacity in OECD countries and no evidence of a country’s universities reputations explaining the flow of students. The evolution over time of education capacity, earnings, visa regimes, migrant networks, strong income growth and changes in demographics in nearby export markets explain the emergence of Australia, Canada, Korea, and New Zealand and the loss of market share by the US, which still strongly dominates international trade in higher education services. The decline in Chinese students coming to the US is also predicted for the most recent years driven by reduced by its college-age population.
2 0 Ja n 20 20 FACTORS AND LOOSE HAMILTON CYCLES IN SPARSE PSEUDO-RANDOM HYPERGRAPHS HIÊ

We investigate the emergence of spanning structures in sparse pseudo-random kuniform hypergraphs, using the following comparatively weak notion of pseudo-randomness. A k-uniform hypergraph H on n vertices is called (p, α, ε)-pseudo-random if for all (not necessarily disjoint) vertex subsets A1, . , Ak⊆V (H) with |A1| · · · |Ak|≥αn k we have e(A1, . . . , Ak) = (1± ε)p|A1| · · · |Ak|. For any linear k-uniform F we provide a bound on α = α(n) in terms of p = p(n) and F , such that (under natural divisibility assumptions on n) any k-uniform (