Miracle-dz/UniFAR-FTUs huggingface dataset:
LEGAL GOVERNANCE OF ROHINGYA REFUGEE AFFAIRS IN ACEH: A CONSTITUTIONAL PERSPECTIVE

This study aims to analyze the implementation of governance for refugees who come to Indonesia, in this case, Rohingya refugees. The arrival of Rohingya refugees in Indonesia has introduced complexity to the regional response, posing challenges for the Indonesian government in upholding humanitarian standards, ensuring proper living conditions, and managing public sentiments. This research employs a juridical-normative approach to analyze the legal norms governing the Indonesian government's policies on Rohingya refugees, focusing on instruments like Presidential Regulation 125/2016. By examining legal regulations and sources, this study identifies and evaluates the legal implications of implemented policies, assessing their alignment with prevailing legal principles. The international legal framework, including the 1951 UN Refugee Convention and the 1967 Protocol, alongside Indonesia's comprehensive immigration legal framework (Law Number 6 of 2011), is crucial. Despite these legal foundations, challenges persist in handling Rohingya refugees in Aceh, highlighting a disconnect between the legal framework and on-the-ground realities, notably in the face of local community rejection.
se-Use of an endoscope in minimally invasive lesion biopsy and removal within the skull and cranial vault in two dogs and one cat

Case Description —2 dogs and 1 cat underwent endoscopic-assisted intracranial procedures for lesion biopsy (1 dog and 1 cat) and definitive lesion removal (1 dog). Clinical Findings —1 cat was treated for an interhemispheric, pedunculated meningioma with an associated arachnoid cyst. Two dogs underwent endoscopic surgery procedures; 1 dog underwent removal of an intranasal dermoid cyst with extension to the olfactory bulb
Automatic microseismic event picking via unsupervised machine learning

Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.
Reflective Practice: The Impact of Self-identified Learning Gaps on Professional Development

The ebb and flow of education creates unique challenges within educational programming. Universities are charged with the directive to offer more diverse field experiences within their course requirements. As a result of the directive, not every topic nor instructional scenario can be addressed in the program coursework, challenging the programs to bridge the pedagogical learning gaps of their candidates. The purpose of the professional development (PD) being studied was to connect pedagogical methods to candidates’ own learning by providing self-selected PD with instructional tools that candidates could directly put into practice. The self-selected PD based on self-reflection of knowledge had the potential to promote meaningful, purposeful, and valued PD.
Edinburgh Research Explorer The Index-Based Subgraph Matching Algorithm with General Symmetries (ISMAGS)

Subgraph matching algorithms are used to find and enumerate specific interconnection structures in networks. By enumerating these specific structures/subgraphs, the fundamental properties of the network can be derived. More specifically in biological networks, subgraph matching algorithms are used to discover network motifs, specific patterns occurring more often than expected by chance. Finding these network motifs yields information on the underlying biological relations modelled by the network. In this work, we present the Index-based Subgraph Matching Algorithm with General Symmetries (ISMAGS), an improved version of the Index-based Subgraph Matching Algorithm (ISMA). ISMA quickly finds all instances of a predefined motif in a network by intelligently exploring the search space and taking into account easily identifiable symmetric structures. However, more complex symmetries (possibly involving switching multiple nodes) are not taken into account, resulting in superfluous output. ISMAGS overcomes this problem by using a customised symmetry analysis phase to detect all symmetric structures in the network motif subgraphs. These structures are then converted to symmetry-breaking constraints used to prune the search space and speed up calculations. The performance of the algorithm was tested on several types of networks (biological, social and computer networks) for various subgraphs with a varying degree of symmetry. For subgraphs with complex (multi-node) symmetric structures, high speed-up factors are obtained as the search space is pruned by the symmetry-breaking constraints. For subgraphs with no or simple symmetric structures, ISMAGS still reduces computation times by optimising set operations. Moreover, the calculated list of subgraph instances is minimal as it contains no instances that differ by only a subgraph symmetry. An implementation of the algorithm is freely available at https://github.com/mhoubraken/ISMAGS.
A Deep Learning-based Data Usability Enhancement Scheme for Differential Privacy

While differential privacy (DP) is widely used to ensure privacy, it can also significantly reduce data accuracy. Current research attempts to improve accuracy by leveraging post-processing techniques, but these methods are sub-optimal and only applicable to specific data types. To address the issue, in this work, we propose a novel deep learning-based data usability enhancement method for differential privacy that is data-type independent. By using image denoising technology, the proposed scheme reduces the mean square error (MSE) of DP-perturbed data and theoretically justifies the relationship between data noise reduction and image noise reduction. The effectiveness of the proposed scheme is demonstrated through a comprehensive evaluation.
Revolutionizing Pandemic Management: A Comprehensive Review and Exploration of Technological Innovations

The COVID-19 pandemic has presented un-paralleled challenges to global healthcare systems, requiring innovative strategies for efficient management. Technology has emerged as a critical tool in addressing this crisis, providing potential solutions for detection, prediction, monitoring, and post-COVID-19 care. This paper explores the use of various technologies in managing the COVID-19 pandemic through a comprehensive review of multiple studies and research papers. Concepts such as Internet of Medical Things (IoMT), Machine Learning (ML), Deep Learning (DD)) Natural Language Processing (NLP), eX-plainable Artificial Intelligence (XAI), Cloud Computing (CC), Fog Computing (FC) and 5G are examined for their relevance in tackling the diverse challenges posed by the pandemic. It provides a valuable overview of the pivotal role played by technology in pandemic management and the advancements achieved in this field.
Design Analysis and Fabrication of High Gain Wideband Antipodal Vivaldi Antenna for Satellite Communication Applications

— A wideband and high gain corrugated epsilon negative index metamaterial (ENG) Antipodal Vivaldi Antenna (AVA) with gain>12 dBi and working in frequency range from 10 GHz - 25 GHz (for SATCOM applications) is proposed in this paper. The overall performance of the proposed Antipodal Vivaldi Antenna (AVA) is enriched by using a triangular shaped corrugation slots and pi (∏) shaped epsilon negative metamaterial cells. The ‘∏’ shaped metamaterial unit cells are positioned on the upper surface amid both radiators of AVA to emanate the intense electric field in the end-fire direction. The proposed antenna size is 22.6 mm × 15.8 mm x 1.6 mm and it is designed on the FR4 substrate. The proposed antenna is then fabricated using photolithography process and tested for its performances. There is good agreement between simulated and measured results. The measured gain varies from 6.2 – 10.7 dBi.
More than the sum of its parts: uncovering emerging effects of microbial interactions in complex communities

Abstract Microbial communities are not only shaped by the diversity of microorganisms and their individual metabolic potential, but also by the vast amount of intra- and interspecies interactions that can occur pairwise interactions among microorganisms, we suggest that more attention should be drawn towards the effects on the entire microbiome that emerge from individual interactions between community members. The production of certain metabolites that can be tied to a specific microbe-microbe interaction might subsequently influence the physicochemical parameters of the habitat, stimulate a change in the trophic network of the community or create new micro-habitats through the formation of biofilms, similar to the production of antimicrobial substances which might negatively affect only one microorganism but cause a ripple effect on the abundance of other community members. Here, we argue that combining established as well as innovative laboratory and computational methods is needed to predict novel interactions and assess their secondary effects. Such efforts will enable future microbiome studies to expand our knowledge on the dynamics of complex microbial communities.
A Corpus-based Evaluation of College English Textbooks in China: From the Perspective of Cultural Functions

: The development of the new era has put forward strict knowledge requirements, quality requirements, and ability requirements for the cultivation of foreign language majors. The requirements of the times for foreign language talent provide an important basis for examining the cultural functions of English textbooks. This paper uses AntConc software to process data on the presentation of Chinese culture in a corpus of English intensive reading materials for English majors, and to explore the alignment of the design of cultural exercises with Hanvey's four levels of intercultural awareness cultivation goals. Results suggest that the Chinese cultural elements are not adequately presented in this set of textbooks, whereas the culture-related exercises in the textbook are designed in accordance with Harvey’s cross-cultural awareness theory.
Foraging strategies and foraging plasticity in harvester ants ( Pogonomyrmex spp., Hymenoptera: Formicidae) of the central Monte desert, Argentina

Foraging strategy determines the way harvester ants use space and therefore their access and impact on seed resources. In this study, we described the foraging strategy of three sympatric South American species of Pogonomyrmex ants to confirm that they are solitary foragers as is suggested anecdotally in the literature. Then we tested whether those foraging strategies are fixed or flexible in response to seed density and distribution. Based on individual and group movements of foraging ants, we determined that P. rastratus M AYR , 1868 is exclusively a solitary foraging species, P. inermis F OREL , 1914 use a group-foraging strategy with limited recruitment, and P. mendozanus C UEZZO & C LAVER , 2009 displays an intermediate foraging system in which workers are typically solitary foragers but also recruit nestmates to high-density seed patches. The addition of seeds near the nest modified the foraging behavior of the three species by different amounts. Individual foragers of each species reduced their search time and search area, and colonies increased their foraging activity rate, probably as a result of a higher returning rate of successful foragers after seed addition. Such behavioral responses were much more conspicuous in P. mendozanus than in the other two species. Flexibility in foraging and diet breadth reported for some of these harvester ants may constitute important adaptive features in the central Monte desert where seed abundance is highly heterogeneous, irregular, and severely affected by anthropic disturbances.
RESEARCH OUTPUTS / RÉSULTATS DE RECHERCHE

Databases are ubiquitous in software and testing of programs manipulating databases is thus essential to enhance the reliability of software. In this paper, we describe a clean and uniﬁed approach to automatically generate test inputs for such database programs. First, we propose a formal language, called ImperDB, to model database programs. ImperDB allows to model common program behaviors and data structures, as well as typical interaction scenarios be-tween programs and databases. Secondly, we present a static analysis technique to generate test inputs for ImperDB programs, according to any chosen structural adequacy criterion. The technique considers an ImperDB program as a sequence of operations over a set of relational variables, modeling both the database original content and the program inputs. The problem of ﬁnding test inputs forcing the execution of a given path can then be transformed into the problem of solving constraints over the relational variables associated to the program. These constraints are expressed with the Alloy language and solved by the Alloy analyzer.
Revisiting Meta-evaluation for Grammatical Error Correction

Metrics are the foundation for automatic evaluation in grammatical error correction (GEC), with their evaluation of the metrics (meta-evaluation) relying on their correlation with human judgments. However, conventional meta-evaluations in English GEC encounter several challenges including biases caused by inconsistencies in evaluation granularity, and an outdated setup using classical systems. These problems can lead to misinterpretation of metrics and potentially hinder the applicability of GEC techniques. To address these issues, this paper proposes SEEDA, a new dataset for GEC meta-evaluation. SEEDA consists of corrections with human ratings along two different granularities: edit-based and sentence-based, covering 12 state-of-the-art systems including large language models (LLMs), and two human corrections with different focuses. The results of improved correlations by aligning the granularity in the sentence-level meta-evaluation, suggest that edit-based metrics may have been underestimated in existing studies. Furthermore, correlations of most metrics decrease when changing from classical to neural systems, indicating that traditional metrics are relatively poor at evaluating fluently corrected sentences with many edits.
Post-hoc and Anytime Valid Permutation and Group Invariance Testing

We study post-hoc ($e$-value-based) and post-hoc anytime valid inference for testing exchangeability and general group invariance. Our methods satisfy a generalized Type I error control that permits a data-dependent selection of both the number of observations $n$ and the significance level $\alpha$. We derive a simple analytical expression for all exact post-hoc valid $p$-values for group invariance, which allows for a flexible plug-in of the test statistic. For post-hoc anytime validity, we derive sequential $p$-processes by multiplying post-hoc $p$-values. In sequential testing, it is key to specify how the number of observations may depend on the data. We propose two approaches, and show how they nest existing efforts. To construct good post-hoc $p$-values, we develop the theory of likelihood ratios for group invariance, and generalize existing optimality results. These likelihood ratios turn out to exist in different flavors depending on which space we specify our alternative. We illustrate our methods by testing against a Gaussian location shift, which yields an improved optimality result for the $t$-test when testing sphericity, connections to the softmax function when testing exchangeability, and an improved method for testing sign-symmetry.
"Digitwashing": The Gap between Words and Deeds in Digital Transformation and Stock Price Crash Risk

The contrast between companies'"fleshy"promises and the"skeletal"performance in digital transformation may lead to a higher risk of stock price crash. This paper selects a sample of Shanghai and Shenzhen A-share listed companies from 2010 to 2021, empirically analyses the specific impact of the gap between words and deeds in digital transformation (GDT) on the stock price crash risk, and explores the possible causes of GDT. We found that GDT significantly increases the stock price crash risk, and this finding is still valid after a series of robustness tests. In a further study, a deeper examination of the causes of GDT reveals that firms' perceptions of economic policy uncertainty significantly increase GDT, and the effect is more pronounced in the sample of loss-making firms. At the same time, the results of the heterogeneity test suggest that investors are more tolerant of state-owned enterprises when they are in the GDT situation. Taken together, we provide a concrete bridge between the two measures of digital transformation - digital text frequency and digital technology share - and offer new insights to enhance capital market stability.
Suppressed weak anti-localization in topological insulator - antiferromagnetic insulator (BiSb)$_2$Te$_3$ - MnF$_2$ thin film bilayers

Thin films of the topological insulator (BiSb)$_2$Te$_3$ oriented along the [0001] direction were grown via molecular beam epitaxy on substrates of Al$_2$O$_3$ (0001) and MgF$_2$ (110) single crystals, as well as on an epitaxial thin film of the antiferromagnetic insulator MnF$_2$ (110). Magnetoconductivity measurements of these samples showed close proximity of the Fermi level to the Dirac point and weak antilocalization at low temperature that was partially suppressed in the sample grown on the MnF$_2$ layer. The magnetoconductivity data were fit to a model that describes the quantum corrections to the conductivity for the Dirac surface state of a 3-dimensional topological insulator, from which values of the Fermi velocity and the phase coherence length of the surface state charge carriers were derived. The magnetoconductivity of the (BiSb)$_2$Te$_3$ - MnF$_2$ bilayer samples were fit to a model describing the crossover from weak antilocalization to weak localization due to magnetic doping. The results are consistent with the opening of an energy gap at the Dirac point in the (BiSb)$_2$Te$_3$ due to magnetic proximity interactions of the topological surface states with the antiferromagnetic MnF$_2$ insulator.
Depth resolution in piezoresponse force microscopy

Piezoresponse Force Microscopy (PFM) is one of the most widespread methods for investigating and visualizing ferroelectric domain structures down to the nanometer length scale. PFM makes use of the direct coupling of the piezoelectric response to the crystal lattice, and hence is most often applied to spatially map the 3-dimensional (3D) near-surface domain distribution of any polar or ferroic sample. Nonetheless, since most samples investigated by PFM are at least semiconducting or fully insulating, the electric ac field emerging from the conductive scanning force microscopy (SFM) tip, penetrates the sample, and hence may also couple to polar features that are deeply buried into the bulk of the sample under investigation. Thus, in the work presented here, we experimentally and theoretically explore the contrast and depth resolution capabilities of PFM, by analyzing the dependence of several key parameters. These key parameters include the depth of the buried feature, i.e. here a domain wall (DW), as well as PFM-relevant technical parameters such as the tip radius, the PFM drive voltage and frequency, and the signal-to-noise ratio. The theoretical predictions are experimentally verified using x-cut periodically-poled lithium niobate single crystals that are specially prepared into wedge-shaped samples, in order to allow the buried feature, here the DW, to be `positioned' at any depth into the bulk. This inspection essentially contributes to the fundamental understanding in PFM contrast analysis, and to the reconstruction of 3D domain structures down to a 1-$\mu$m-penetration depth into the sample.
Minimum acyclic number and maximum dichromatic number of oriented triangle-free graphs of a given order

Let $D$ be a digraph. Its acyclic number $\vec{\alpha}(D)$ is the maximum order of an acyclic induced subdigraph and its dichromatic number $\vec{\chi}(D)$ is the least integer $k$ such that $V(D)$ can be partitioned into $k$ subsets inducing acyclic subdigraphs. We study ${\vec a}(n)$ and $\vec t(n)$ which are the minimum of $\vec\alpha(D)$ and the maximum of $\vec{\chi}(D)$, respectively, over all oriented triangle-free graphs of order $n$. For every $\epsilon>0$ and $n$ large enough, we show $(1/\sqrt{2} - \epsilon) \sqrt{n\log n} \leq \vec{a}(n) \leq \frac{107}{8} \sqrt n \log n$ and $\frac{8}{107} \sqrt n/\log n \leq \vec{t}(n) \leq (\sqrt 2 + \epsilon) \sqrt{n/\log n}$. We also construct an oriented triangle-free graph on 25 vertices with dichromatic number~3, and show that every oriented triangle-free graph of order at most 17 has dichromatic number at most 2.
Quantum superpositions of current states in Rydberg-atom networks

Quantum simulation of many-body quantum systems using Rydberg-atom platforms has become of extreme interest in the last years. The possibility to realize spin Hamiltonians and the accurate control at the single atom level paved the way for the study of quantum phases of matter and dynamics. Here, we propose a quantum optimal control protocol based on the GRAPE algorithm to engineer quantum current states. Besides current states characterized by a single winding number, our approach allow to access superposition of quantum current states. The single current states are eigenstates of the current operator that therefore can define an observable that remains persistent at any time. In particular, the features of the excitations dynamics reflects the nature of current states, a fact that in principle can be used to characterize the nature of the flow experimentally.