Miracle-dz/UniFAR-FTUs huggingface dataset:
Disrupting Colonial Tensions in Initial Language Teacher Education: Criteria Based on Critical Interculturality

Colombian English Language Teaching (ELT) is experiencing a paradigmatic change guided by the decolonial turn. This turn has enriched the debate about the implementation of a bilingual policy in Colombia, its impact on languages otherthan English, the purposes of learning English in the country, and English teacher practices and identities. This article shares the results of a critical ethnography that collected data from students and teacher educators from elt preparation programs and institutional and legal documents. Results indicate that, in Colombian elt, there are six discursive tensions representing coloniality. These are (a) English teachers as instructors or as educators; (b) native or non-native English speakers; (c) poor image of foreign language teachers as opposed to an idealized language teacher; (d) instrumental or cognitive and intercultural purposes for learning English; (e) emphasis on disciplinary knowledge or on interdisciplinary knowledge; and (f ) division or integration between theory and practice. To counter these tensions, a set of criteria are proposed. These criteria are: (a) elt preparation graduates are professionals in language pedagogy; (b) they are multilingual educated teachers; (c) they are well-rounded professional educators; (d) English is a means of recognizing diversity; (e) elt preparation programs embrace interdisciplinarity as a decolonizing option; and (f ) ELT preparation programs promote praxis. To conclude, the criteria proposed aim to shift initial language teacher education from an instrumental vision to a reflexive one, considering what is being learned, how, with whom, in what contexts, and the reasons that justify it.
Exploiting Partial Observability for Optimal Deception

Deception is a useful tool in situations where an agent operates in the presence of its adversaries. We consider a setting where a supervisor provides a reference policy to an agent, expects the agent to operate in an environment by following the reference policy, and partially observes the agent's behavior. The agent instead follows a different deceptive policy to achieve a different task. We model the environment with a Markov decision process and study the synthesis of optimal deceptive policies under partial observability. We formalize the notion of deception as a hypothesis testing problem and show that the synthesis of optimal deceptive policies is nondeterministic polynomial-time hard (NP-hard). As an approximation, we consider the class of mixture policies, which provides a convex optimization formulation of the deception problem. We give an algorithm that converges to the optimal mixture policy. We also consider a special class of Markov decision processes where the transition and observation functions are deterministic. For this case, we give a randomized algorithm for path planning that generates a path for the agent in polynomial time and achieves the optimal value for the considered objective function.
Multiple Field Inflation and Signatures of Heavy Physics in the CMB

In this master thesis we study multi-field inflation and the UV sensitivity of certain models of inflation in supergravity. We first introduce inflation and its current observational status. Then we provide an overview of studies of multiple field inflation in the literature. We translate between the different notations and definitions used in various papers and study the different approximation schemes and their regime of validity. Finally we perform a numerical study of models of multi-field inflation from recent papers in the literature. We study if the current and future experiments might be able to detect the presence of the additional fields in these models.
Revisiting Cloud Radiative Heating and the Southern Annular Mode

Cloud‐circulation interactions have a potentially large but uncertain influence on regional climate. Here we use satellite observations to investigate relationships between atmospheric cloud radiative heating and hemispheric‐scale shifts in the Southern Hemisphere extratropical jet stream, as represented by the Southern Annular Mode. In contrast to a previous study, we find that poleward jet shifts cause bottom‐heavy heating anomalies. The heating anomalies arise from two distinct mechanisms: First, poleward jet shifts promote anomalous large‐scale subsidence equatorward of the mean jet latitude. This increases the fraction of low clouds that are exposed to space, thereby enhancing lower‐tropospheric radiative cooling. Second, deep and multi‐layer clouds in extratropical cyclones shift poleward with the jet, causing radiative heating anomalies throughout the troposphere. The bottom‐heavy structure of the heating anomalies occurs because low clouds strongly emit radiation. These results establish new observational benchmarks for understanding extratropical cloud‐circulation interactions.
Clumpy galaxies seen in H α: inflated observed clump properties due to limited spatial resolution and sensitivity

High-resolution simulations of star-forming massive galactic discs have shown that clumps form with a characteristic baryonic mass in the range 107–108 M⊙, with a small tail exceeding 109 M⊙ produced by clump–clump mergers. This is in contrast with the observed kpc-size clumps with masses up to 1010 M⊙ in high-redshift star-forming galaxies. In this paper, we show that the comparison between simulated and observed star-forming clumps is hindered by limited observational spatial resolution and sensitivity. We post-process high-resolution hydrodynamical simulations of clumpy discs using accurate radiative transfer to model the effect of ionizing radiation from young stars and to compute H α emission maps. By comparing the intrinsic clump size and mass distributions with those inferred from convolving the H α maps with different Gaussian apertures, we mimic the typical resolution used in observations. We found that with 100 pc resolution, mock observations can recover the intrinsic clump radii and stellar masses, in agreement with those found by lensing observations. Instead, using a 1 kpc resolution smears out individual clumps, resulting in their apparent merging. This causes significant overestimations of the clump radii and therefore masses derived using methods that use their observed sizes. We show that limited sensitivity can also force observations to significantly overestimate the clump masses. We conclude that a significant fraction of giant clumps detected in the observations may result from artificially inflated radii and masses, and that ≈100 pc spatial resolution is required to capture correctly the physical characteristics of star-forming clumps if they are coherent structures produced by disc fragmentation.
Concept Drift-Based Checkpoint-Restart for Edge Services Rejuvenation

As a nascent technique, mobile edge computing (MEC) is mushrooming with a broad application prospect. By transferring abundant computing and storage resources from cloud to edge servers close to users, it allows services to be hosted on edge servers, which greatly reduces service latency. However, due to environmental dynamics, the edge services’ reliability fluctuates in real-time. When the reliability of an edge service degrades severely, it may be suffering an anomaly, which can seriously impact its real-time performance and users’ quality of experience. To ensure the real-time performance of edge services, this article presents CDCrest, a concept drift-based checkpoint restart approach for edge service rejuvenation. CDCrest employs L-Detection, a concept drift-based approach to detect edge services’ runtime reliability anomalies. L-Detection leverages a sliding window and locality sensitive hashing (LSH)-based sampling to extract features from an edge service's real-time and historic reliability data streams. Then, it calculates the real-time distribution change degree (DCD) based on jensen-shannon (JS) divergence to infer whether the edge service is suffering a reliability anomaly. Once an anomaly for an edge service is identified, CDCrest employs a checkpoint restart mechanism to ensure the rapid rejuvenation of the edge service. Extensive experiments conducted based on a popular real-world dataset demonstrate the effectiveness and efficiency of CDCrest against the state-of-the-art approaches.
Predefined‐time control for Euler–Lagrange systems with model uncertainties and actuator faults

A novel adaptive predefined‐time tracking control algorithm is proposed for the Euler–Lagrange systems (ELSs) with model uncertainties and actuator faults. Compared with traditional finite‐time and fixed‐time studies, the system output tracking error under the proposed predefined‐time controller converges to a small neighborhood of zero in finite time, whose upper bound is exactly a design parameter in the control algorithm. For the uncertain model, radial‐based function neural network (RBFNN) is utilized to approximate the continuous uncertain dynamics. To deal with the actuator faults, an adaptive control law is involved in the fault‐tolerant controller. In order to achieve the predefined‐time bounded, a novel predefined‐time sliding mode surface is designed. It is proved that the tracking error vector trajectory of closed‐loop system is semi‐globally uniformly ultimately predefined‐time bounded, and the upper bounds of both the system settling time and the corresponding output tracking error can be adjusted with a simple parameter. Simulation examples finally demonstrate the effectiveness of the proposed control algorithm.
Lecture Notes On Chern-Simons-Witten Theory

Examples of quantizations classical solutions of gauge field theory quantization of Chern-Simons action Chern-Simons-Witten theory and three manifold invariant renormalized perturbation series of Chern-Simons-Witten theory topological sigma model and localization. Appendices: complex manifold without potential theory, S.S. Chern geometric quantization of Chern-Simons gauge theory, S. Axelrod, S.D. Pietra and E. Witten on holomorphic factorization of WZW and Coset models, E. Witten.
An E Band Wideband Superheterodyne Receiver Front-End Using Large-Dynamic-Range Automatic-Gain-Control Loop

An E-band wideband receiver front-end with stable output power over large input dynamic range is presented in this paper. It adopts a double-conversion superheterodyne structure combined with automatic gain control (AGC) technology to realize the wideband signals reception and dynamic range compression. An E-band mixer is designed based on Schottky diodes which features advantages in broadband and low cost, compared with commercially available chips. The AGC loop in the intermediate frequency circuit utilizes 3 voltage variable attenuators to provide a 78 dB continuously variable gain and uses a logarithmic detector to form an analog feedback loop, which exhibits a stable and high-flatness output power over 73 dB input dynamic range. The measured input dynamic range of the receiver front-end is −55dBm to +5 dBm with output power fluctuation better than ±1 dB, in the operating frequency range of 66.5~75.5 GHz. The power flatness of the output frequency response within the 500 MHz channel bandwidth is better than ±0.5 dB. Besides, the harmonic suppression and spur suppression of the IF output signal is better than 52 dBc and 75 dBc, respectively.
Prolonged Slip on the South Tibetan Detachment Constrains Tectonic Models for Synorogenic Extension in the Central Himalaya

The South Tibetan detachment system (STDS) is one of the most important deformational features in the Himalayan orogen; yet its evolution in space and time remain incompletely understood. Here, we present the results of a new study of the primary, basal strand of the STDS in the Annapurna Himalaya of central Nepal: the Annapurna detachment. The original discovery outcrop of this structure in the Kali Gandaki valley reveals that multiple leucogranite bodies are variably deformed by ductile slip on the detachment. New laser‐ablation (U‐Th)/Pb dating of complex monazite suites from these bodies indicates that leucogranites in this outcrop intruded over a period extending from at least 22.76 ± 0.30–14.95 ± 0.78 Ma. Field relationships and microstructures within studied samples show that ductile slip on the Annapurna detachment was active—at least episodically—throughout this period and also continued into the more recent past. Based on cooling history models for the outcrop constrained by 40Ar/39Ar and (U‐Th)/He data, ductile slip likely continued until at least 12 Ma. These results are at odds with previous inferences that slip on the STDS in central Nepal had ceased by ca. 22 Ma and call into question the popular idea that there was an abrupt geodynamic transition from predominantly N‐S‐directed extension to predominantly E‐W‐directed extension in the central Himalaya in the early Miocene.
Simple Real-Space Picture of Nodeless and Nodal s-wave Gap Functions in Iron Pnictide Superconductors

We propose a simple way to parameterize the gap function in iron pnictides. The key idea is to use orbital representation, not band representation, and to assume real-space short-range pairing. Our parameterization reproduces fairly well the structure of gap function obtained in microscopic calculation. At the same time the present parameterization is simple enough to obtain an intuitive picture and to develop a phenomenological theory. We also discuss simplification of the treatment of the superconducting state.
Interest Point Detection Using Hough Transform and Invariant Patch Feature for Image Retrieval

This paper presents a new technique for corner shape based object retrieval from a database. The proposed feature matrix consists of values obtained through a neighborhood operation of detected corners. This results in a significant small size feature matrix compared to the algorithms using color features and thus is computationally very efficient. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. As the affine transformations preserve the co-linearity of points on a line and their intersection properties, the resulting corner features for image retrieval are robust to affine transformations. Furthermore, the corner features are invariant to noise. It is considered that the proposed algorithm will produce good results in combination with other algorithms in a way of incremental verification for similarity.
Female gender interests and education in women entrepreneurs’ definition of success in Uganda

ABSTRACT Studies on the intersection between women’s education, motivations for entrepreneurship, and the structural constraints women face in Sub-Saharan Africa are scarce. In this study, we analyse the influence of education level on how women entrepreneurs in Uganda define business success. To this end, a total of 109 female agribusiness entrepreneurs were interviewed. The results firstly show that women’s definition of business success and their level of education are intertwined. Secondly, that the main definitions of success are business performance, economic independence, and family welfare, which can be categorized in terms of women’s practical interest, strategic interest, or a continuum of both, and where the education level of women is an influencing factor. The study has practical implications for policies aimed at women’s economic empowerment and education. To transform the structure of gender relations, more opportunities for women’s entrepreneurial training and child education are also needed, as well gender-sensitive indicators of business success that account for the particular interests of women in specific contexts.
The Utility of Voided Urine Samples as a Proxy for the Vaginal Microbiome and for the Prediction of Bacterial Vaginosis

Abstract Recent work has shown that the vaginal microbiome exerts a strong impact on women's gynecological health. However, collection of vaginal specimens is invasive and requires previous clinical training or the involvement of a trained clinician. In contrast, urine sample collection is routine and noninvasive and does not require involvement of a clinician. We sought to compare the vaginal and urogenital microbiomes to assess the utility of voided urine samples as a proxy for the vaginal microbiome. Paired urogenital and vaginal samples were collected from pregnant women and characterized by 16S rRNA taxonomic profiling. We examined diversities and compositions of paired urogenital and vaginal microbiomes using five discrete strategies to explore the similarity between the vaginal and urogenital microbiomes. A strategy comparing the paired urogenital and vaginal microbiomes in which taxa were assigned using the STIRRUPS database and urine-specific taxa were removed showed no significant difference in diversity and composition between the paired urogenital and vaginal microbiomes. Moreover, the relative abundances of common vaginal taxa were linearly correlated with those in the paired urogenital microbiomes. These similarities suggest that voided urine samples could represent a noninvasive protocol for accurate profiling of the vaginal microbiome with likely clinical applications. Finally, a machine learning model was established in which the voided urine microbiome was compared favorably to the vaginal microbiome in predicting bacterial vaginosis.
From vision to transformation: integrating human rights courses in higher education in India

Human Rights Education (HRE) is critical to human development and societal transformation. In India, although HRE emerged in the 1980s, its incorporation in higher education has not yet reached its full potential. Using the state of Tamil Nadu as our case study, this paper evaluates the integration of courses on human rights in universities and colleges, using a descriptive qualitative approach to analyse the nature and content of such courses, their compliance with India’s apex institutional directives, and the challenges faced. The researchers conclude that there is a disconnect between the vision of policy makers and actual implementation of HRE in practice. It is suggested that wider holistic application of HRE in higher education is needed, so that learning becomes a transformative force, empowering the young to develop attitudes of solidarity, tolerance, and respect for social justice.
Traffic volume forecasting model based on composite neural network and regional approach

Traffic flow is one of the most important urban operation and land development indicators. Effective traffic flow prediction is of great significance for optimizing urban transit systems and the improvement of land use planning. In this paper, a method based on area aggregation combined with long and short-term memory neural network + graph convolutional neural network is proposed to overcome the situation that the traditional travel matrix with zero elements makes it impossible to use deep learning methods for prediction. Experimental results show that the method proposed in this paper effectively improves the situation that the direct use of deep learning methods makes the prediction fall into local optimum. In addition, this paper has essential references and implications for traffic volume prediction.
FUZZY SUPERNOVA TEMPLATES. I. CLASSIFICATION

Modern supernova (SN) surveys are now uncovering stellar explosions at rates that far surpass what the world's spectroscopic resources can handle. In order to make full use of these SN data sets, it is necessary to use analysis methods that depend only on the survey photometry. This paper presents two methods for utilizing a set of SN light-curve templates to classify SN objects. In the first case, we present an updated version of the Bayesian Adaptive Template Matching program (BATM). To address some shortcomings of that strictly Bayesian approach, we introduce a method for Supernova Ontology with Fuzzy Templates (SOFT), which utilizes fuzzy set theory for the definition and combination of SN light-curve models. For well-sampled light curves with a modest signal-to-noise ratio (S/N >10), the SOFT method can correctly separate thermonuclear (Type Ia) SNe from core collapse SNe with ⩾98% accuracy. In addition, the SOFT method has the potential to classify SNe into sub-types, providing photometric identification of very rare or peculiar explosions. The accuracy and precision of the SOFT method are verified using Monte Carlo simulations as well as real SN light curves from the Sloan Digital Sky Survey and the SuperNova Legacy Survey. In a subsequent paper, the SOFT method is extended to address the problem of parameter estimation, providing estimates of redshift, distance, and host galaxy extinction without any spectroscopy.
Synthesis, Characterization, and Antiproliferative Effect of CuO-TiO2-Chitosan-Amygdalin Nanocomposites in Human Leukemic MOLT4 Cells

The main aim of this study was to synthesize copper oxide- (CuO-) titanium oxide- (TiO2-) chitosan-amygdalin nanocomposites (CTCANc) and to characterize them physically and biologically (antimicrobial and anticancer activity using MOLT4 blood cancer cell line) to endorse their useful applications as potential drug candidates in anticancer avenues. CuO-TiO2-chitosan-amygdalin nanocomposites were synthesized according to standard, reported methods. Physical characterization of the nanocomposites was performed using methods like X-ray diffractometer (XRD), and morphological and ultrastructural analysis of nanocomposites were done using electron microscope scanning and transmission. FTIR was recorded using a Perkin-Elmer spectrometer, and photoluminescence (PL) spectra were done using the spectrometer. Further, antibacterial activities were assessed using standard bacterial cultures. To demonstrate the nanocomposite's anticancer effects, MTT assay, morphological analysis, apoptosis studies using acridine orange/ethidium bromide (AO/EtBr) dual staining, reactive oxygen species (ROS) analysis, and levels of antioxidant enzymes were analyzed using the MOLT4 blood cancer cell line. Synthesized nanocomposites were characterized using XRD and showed various peaks, respectively, for CuO-TiO2, amygdalin, and chitosan. MTT assay indicated an IC50 value of 38.41 μg/ml concentration of CTCANc. Hence, 30 and 40 μg/ml were used for the subsequent experiments. Morphological analysis, staining for apoptosis using AO/EtBr, mitochondrial membrane potential (MMP or ΔΨm) analysis, ROS analysis, and determination of the SOD, CAT, MDA, and GSH levels were performed. Observations like a significant loss of morphology, induction of apoptosis, elevated ROS, and decreased MMP were significant in 30 and 40 μg/ml nanocomposite-treated cells when compared to control cells. The bimetallic nanocomposites exhibited typical nanocomposites characteristics and significant antibacterial and anticancer effects. The study results endorse the antibacterial, anticancer activity of CuO-TiO2-chitosan-amygdalin nanocomposites and strongly suggest that further in-depth research using CuO-TiO2-chitosan-amygdalin nanocomposites could reveal their efficacy in the clinical scenario.