Miracle-dz/UniFAR-FTUs huggingface dataset:
Learn-Explain-Reinforce: Counterfactual Reasoning and its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model

Existing studies on disease diagnostic models focus either on diagnostic model learning for performance improvement or on the visual explanation of a trained diagnostic model. We propose a novel learn-explain-reinforce (LEAR) framework that unifies diagnostic model learning, visual explanation generation (explanation unit), and trained diagnostic model reinforcement (reinforcement unit) guided by the visual explanation. For the visual explanation, we generate a counterfactual map that transforms an input sample to be identified as an intended target label. For example, a counterfactual map can localize hypothetical abnormalities within a normal brain image that may cause it to be diagnosed with Alzheimer's disease (AD). We believe that the generated counterfactual maps represent data-driven knowledge about a target task, i.e., AD diagnosis using structural MRI, which can be a vital source of information to reinforce the generalization of the trained diagnostic model. To this end, we devise an attention-based feature refinement module with the guidance of the counterfactual maps. The explanation and reinforcement units are reciprocal and can be operated iteratively. Our proposed approach was validated via qualitative and quantitative analysis on the ADNI dataset. Its comprehensibility and fidelity were demonstrated through ablation studies and comparisons with existing methods.
A Transformer Architecture for Stress Detection from ECG

Electrocardiogram (ECG) has been widely used for emotion recognition. This paper presents a deep neural network based on convolutional layers and a transformer mechanism to detect stress using ECG signals. We perform leave-one-subject-out experiments on two publicly available datasets, WESAD and SWELL-KW, to evaluate our method. Our experiments show that the proposed model achieves strong results, comparable or better than the state-of-the-art models for ECG-based stress detection on these two datasets. Moreover, our method is end-to-end, does not require handcrafted features, and can learn robust representations with only a few convolutional blocks and the transformer component.
DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network

Knowledge graph completion (KGC) has become a focus of attention across deep learning community owing to its excellent contribution to numerous downstream tasks. Although recently have witnessed a surge of work on KGC, they are still insufficient to accurately capture complex relations, since they adopt the single and static representations. In this work, we propose a novel Disentangled Knowledge Graph Attention Network (DisenKGAT) for KGC, which leverages both micro-disentanglement and macro-disentanglement to exploit representations behind Knowledge graphs (KGs). To achieve micro-disentanglement, we put forward a novel relation-aware aggregation to learn diverse component representation. For macro-disentanglement, we leverage mutual information as a regularization to enhance independence. With the assistance of disentanglement, our model is able to generate adaptive representations in terms of the given scenario. Besides, our work has strong robustness and flexibility to adapt to various score functions. Extensive experiments on public benchmark datasets have been conducted to validate the superiority of DisenKGAT over existing methods in terms of both accuracy and explainability.
From loom spaces to veering triangulations

We introduce loom spaces, a generalisation of both the leaf spaces associated to pseudo-Anosov flows and the link spaces associated to veering triangulations. Following work of Gu\'eritaud, we prove that there is a locally veering triangulation canonically associated to every loom space, and that the realisation of this triangulation is homeomorphic to $\mathbb{R}^3$.
Active turbulence in microswimmer suspensions | the role of active hydrodynamic stress and volume exclusion

Microswimmers exhibit an intriguing, highly-dynamic collective motion with large-scale swirling and streaming patterns, denoted as active turbulence — reminiscent of classical high-Reynolds-number hydrodynamic turbulence. Various experimental, numerical, and theoretical approaches have been applied to elucidate similarities and differences to inertial hydrodynamic and active turbulence. These studies reveal a wide spectrum of possible structural and dynamical behaviors of active mesoscale systems, not necessarily consistent with the predictions of the Kolmogorov-Kraichnan theory of turbulence. We use squirmers embedded in a mesoscale fluid, modeled by the multiparticle collision dynamics (MPC) approach, to explore the collective behavior of bacteria-type microswimmers. Our model includes the active hydrodynamic stress generated by propulsion, and a rotlet dipole characteristic for flagellated bacteria. We find emergent clusters, activity-induced phase separation, and swarming, depending on density, active stress, and the rotlet dipole strength. The analysis of the squirmer dynamics in the swarming phase yields Kolomogorov-Kraichnan-type hydrodynamic turbulence and energy spectra for sufficiently high concentrations and strong rotlet dipoles. This emphasizes the paramount importance of the hydrodynamic flow field for swarming and bacterial turbulence.
The "Shut the f**k up" Phenomenon: Characterizing Incivility in Open Source Code Review Discussions

Code review is an important quality assurance activity for software development. Code review discussions among developers and maintainers can be heated and sometimes involve personal attacks and unnecessary disrespectful comments, demonstrating, therefore, incivility. Although incivility in public discussions has received increasing attention from researchers in different domains, the knowledge about the characteristics, causes, and consequences of uncivil communication is still very limited in the context of software development, and more specifically, code review. To address this gap in the literature, we leverage the mature social construct of incivility as a lens to understand confrontational conflicts in open source code review discussions. For that, we conducted a qualitative analysis on 1,545 emails from the Linux Kernel Mailing List (LKML) that were associated with rejected changes. We found that more than half (66.66%) of the non-technical emails included uncivil features. Particularly, frustration, name calling, and impatience are the most frequent features in uncivil emails. We also found that there are civil alternatives to address arguments, while uncivil comments can potentially be made by any people when discussing any topic. Finally, we identified various causes and consequences of such uncivil communication. Our work serves as the first study about the phenomenon of in(civility) in open source software development, paving the road for a new field of research about collaboration and communication in the context of software engineering activities.
Asymptotic Analysis on the Sharp Interface Limit of the Time-Fractional Cahn-Hilliard Equation

In this paper, we aim to study the motions of interfaces and coarsening rates governed by the time-fractional Cahn--Hilliard equation (TFCHE). It is observed by many numerical experiments that the microstructure evolution described by the TFCHE displays quite different dynamical processes comparing with the classical Cahn--Hilliard equation, in particular, regarding motions of interfaces and coarsening rates. By using the method of matched asymptotic expansions, we first derive the sharp interface limit models. Then we can theoretically analyze the motions of interfaces with respect to different timescales. For instance, for the TFCHE with the constant diffusion mobility, the sharp interface limit model is a fractional Stefan problem at the time scale $t = O(1)$. However, on the time scale $t = O({\varepsilon}^{1/{\alpha}} )$ the sharp interface limit model is a fractional Mullins--Sekerka model. Similar asymptotic regime results are also obtained for the case with one-sided degenerated mobility. Moreover, scaling invariant property of the sharp interface models suggests that the TFCHE with constant mobility preserves an ${\alpha}/3$ coarsening rate and a crossover of the coarsening rates from ${\alpha}/3$ to ${\alpha}/4$ is obtained for the case with one-sided degenerated mobility, which are in good agreement with the numerical experiments.
Legitimization of Data Quality Practices in Health Management Information Systems Using DHIS2. Case of Malawi

Medical doctors consider data quality management a secondary priority when delivering health care. Medical practitioners find data quality management practices intrusive to their operations. Using Health Management Information System (HMIS) that uses DHIS2 platform, our qualitative case study establishes that isomorphism leads to legitimization of data quality management practices among health practitioners and subsequently data quality. This case study employed the methods of observation, semi structured interviews and review of artefacts to explore how through isomorphic processes data quality management practices are legitimized among the stakeholders. Data was collected from Ministry of Health’s (Malawi) HMIS Technical Working Group members in Lilongwe and from medical practitioners and data clerks in Thyolo district. From the findings we noted that mimetic isomorphism led to moral and pragmatic legitimacy while and normative isomorphism led to cognitive legitimacy within the HMIS structure and helped to attain correctness and timeliness of the data and reports respectively. Through this understanding we firstly contribute to literature on organizational issues in IS research. Secondly, we contribute to practice as we motivate health service managers to capitalize on isomorphic forces to help legitimization of data quality management practices among health practitioners.
Foliations from left orders

We describe a construction which takes as an input a left order of the fundamental group of a manifold, and outputs a (singular) foliation of this manifold which is analogous to a taut foliation. We investigate this construction in detail in dimension $2$, and exhibit connections to various problems in dimension $3$.
A Systematic Literature Review of Automated Query Reformulations in Source Code Search

Studies show that software maintenance costs up to 80% of the total budget. As a part of maintenance, software developers often resolve critical bugs to ensure the reliability of their software. They might also need to add new features to their software on a regular interval to stay competitive in the market. These bugs and features are reported as change requests (i.e., technical documents written by software users). Developers consult these documents to implement the required changes in the software code. As a part of change implementation, they often choose a few important keywords from a change request as an ad hoc query. Then they execute the query with a code search engine (e.g., Lucene) and attempt to find out the exact locations within the software code that need to be changed. Unfortunately, even the experienced developers often fail to choose the right search queries. As a consequence, the developers often experience difficulties in detecting the appropriate locations within the code and spend the majority of their time in numerous trials and errors. There have been many studies that attempt to support developers in constructing queries by automatically reformulating their ad hoc queries. In this systematic literature review, we carefully select 70 primary studies on query reformulations from 2,970 candidate studies, perform an in-depth qualitative analysis using the Grounded Theory approach, and then answer six important research questions. We analyze the methodologies, evaluation approaches, and challenges of these primary studies, and provide the statistical evidence on the conducted researches during the last 15 years. Our investigation has reported several major findings. First, to date, eight major methodologies (e.g., term weighting, query-term co-occurrence analysis, thesaurus lookup) have been adopted in query reformulation. Second, the existing studies suffer from several major limitations (e.g., lack of generalizability, vocabulary mismatch problem, weak evaluation, the extra burden on the developers) that might prevent their wide adoption. Finally, we discuss several open issues in search query reformulations and suggest multiple future research opportunities.
A Sample of Massive Black Holes in Dwarf Galaxies Detected via [Fe x] Coronal Line Emission: Active Galactic Nuclei and/or Tidal Disruption Events

The massive black hole (BH) population in dwarf galaxies (M BH ≲ 105 M ⊙) can provide strong constraints on the origin of BH seeds. However, traditional optical searches for active galactic nuclei (AGNs) only reliably detect high-accretion, relatively high-mass BHs in dwarf galaxies with low amounts of star formation, leaving a large portion of the overall BH population in dwarf galaxies relatively unexplored. Here, we present a sample of 81 dwarf galaxies (M ⋆ ≤ 3 × 109 M ⊙) with detectable [Fe x]λ6374 coronal line emission indicative of accretion onto massive BHs, only two of which were previously identified as optical AGNs. We analyze optical spectroscopy from the Sloan Digital Sky Survey and find [Fe x]λ6374 luminosities in the range L [Fe x] ≈ 1036–1039 erg s−1, with a median value of 1.6 × 1038 erg s−1. The [Fe x] λ6374 luminosities are generally much too high to be produced by stellar sources, including luminous Type IIn supernovae (SNe). Moreover, based on known SNe rates, we expect at most eight Type IIn SNe in our sample. That said, the [Fe x]λ6374 luminosities are consistent with accretion onto massive BHs from AGNs or tidal disruption events (TDEs). We find additional indicators of BH accretion in some cases using other emission line diagnostics, optical variability, and X-ray and radio emission (or some combination of these). However, many of the galaxies in our sample only have evidence for a massive BH based on their [Fe x]λ6374 luminosities. This work highlights the power of coronal line emission to find BHs in dwarf galaxies missed by other selection techniques and to probe the BH population in bluer, lower-mass dwarf galaxies.
Bias for the Trace of the Resolvent and Its Application on Non-Gaussian and Non-Centered MIMO Channels

The mutual information (MI) of Gaussian multi-input multi-output (MIMO) channels has been evaluated by utilizing random matrix theory (RMT) and shown to asymptotically follow Gaussian distribution, where the ergodic mutual information (EMI) converges to a deterministic quantity. However, with non-Gaussian channels, there is a bias between the EMI and its deterministic equivalent (DE), whose evaluation is not available in the literature. This bias of the EMI is related to the bias for the trace of the resolvent in large RMT. In this paper, we first derive the bias for the trace of the resolvent, which is further extended to compute the bias for the linear spectral statistics (LSS). Then, we apply the above results on non-Gaussian MIMO channels to determine the bias for the EMI. It is also proved that the bias for the EMI is −0.5 times of that for the variance of the MI. Finally, the derived bias is utilized to modify the central limit theory (CLT) and calculate the outage probability. Numerical results show that the modified CLT significantly outperforms previous methods in approximating the distribution of the MI and improves the accuracy for the outage probability evaluation.
Molecular Level Understanding of How Oxygen and Carbon Monoxide Improve NOx Storage in Palladium/SSZ-13 Passive NOx Adsorbers: The Role of NO+ and Pd(II)(CO)(NO) Species

Model Pd/SSZ-13 with high dispersion of Pd ions (0.1 and 1 wt % Pd) was synthesized. The material was characterized with Fourier transform infrared (FTIR) and cryo-scanning transmission electron microscopy. Adsorption of NO leads to the formation of Pd(II)–NO and Pd(I)–NO complexes as well as NO+ species that replace residual H+ (extra-framework) sites. These nitrosyl species have notable thermal stability, with resistance to decomposition under high vacuum at 200 °C. Addition of molecular oxygen to NO-containing stream improves NOx storage of the Pd/H-SSZ-13. In particular, addition of O2 to NO slightly increases the amount of Pd(II)–NO complex with νNO at ∼1865 cm–1, whereas the low frequency νNO band at 1805 cm–1, assigned to Pd(I)–NO, decreases in intensity. Simultaneously, polydentate nitrate species appear in small amounts, contributing to the high temperature NOx release stage during a passive NOx adsorber (PNA) cycle. The concentration of NO+ (characterized by the broad infrared band centered at 2.
On the Optimal Control of Propagation Fronts

We consider a controlled reaction-diffusion equation, motivated by a pest eradication problem. Our goal is to derive a simpler model, describing the controlled evolution of a contaminated set. In this direction, the first part of the paper studies the optimal control of 1-dimensional traveling wave profiles. Using Stokes’ formula, explicit solutions are obtained, which in some cases require measure-valued optimal controls. In the last section we introduce a family of optimization problems for a moving set. We show how these can be derived from the original parabolic problems, by taking a sharp interface limit.
The evolution of turbulent micro-vortices and their effect on convection heat transfer in porous media

Abstract New insight into the contribution of the microscale vortex evolution to convection heat transfer in porous media is presented in this paper. The objective is to determine how the microscale vortices influence convection heat transfer in turbulent flow inside porous media. The microscale temperature distribution is analysed using flow visualization in two dimensions using streamlines and in three dimensions using the Q-criterion. The pertinent observations are supplemented with a comparison of surface skin friction and heat transfer using: (i) surface skin-friction lines and (ii) the joint probability density function of the pressure and skin-friction coefficients, along with the Nusselt number. The microscale flow phenomena observed are corroborated with the features of the frequency spectra of the drag coefficient and macroscale Nusselt number. The large eddy simulation technique is used in this study to investigate the flow field inside a periodic porous medium. The Reynolds numbers of the flow are 300 and 500. The porous medium consists of solid obstacles in the shape of square and circular cylinders. Two distinct flow regimes are represented by using the porosities of 0.50 and 0.87. The results show that the surface Nusselt number distribution is dependent on whether the micro-vortices are attached to or detached from the surface of the obstacle. The spectra of the macroscale Nusselt number and the pressure drag are similar, signifying a correlation between the dynamics of heat transfer and the microscale turbulent structures. Both vortex shedding and secondary flow instabilities are observed that significantly influence the Nusselt number. The fundamental insight gained in this paper can inform the development of more robust macroscale models of convection heat transfer in turbulent flow in porous media.
What do we mean, ‘tipping cascade’?

Based on suggested interactions of potential tipping elements in the Earth’s climate and in ecological systems, tipping cascades as possible dynamics are increasingly discussed and studied. The activation of such tipping cascades would impose a considerable risk for human societies and biosphere integrity. However, there are ambiguities in the description of tipping cascades within the literature so far. Here we illustrate how different patterns of multiple tipping dynamics emerge from a very simple coupling of two previously studied idealized tipping elements. In particular, we distinguish between a two phase cascade, a domino cascade and a joint cascade. A mitigation of an unfolding two phase cascade may be possible and common early warning indicators are sensitive to upcoming critical transitions to a certain degree. In contrast, a domino cascade may hardly be stopped once initiated and critical slowing down-based indicators fail to indicate tipping of the following element. These different potentials for intervention and anticipation across the distinct patterns of multiple tipping dynamics should be seen as a call to be more precise in future analyses of cascading dynamics arising from tipping element interactions in the Earth system.
Construction of a Second-order Six-dimensional Hamiltonian-conserving Scheme

Research has analytically shown that the energy-conserving implicit nonsymplectic scheme of Bacchini, Ripperda, Chen, and Sironi provides a first-order accuracy to numerical solutions of a six-dimensional conservative Hamiltonian system. Because of this, a new second-order energy-conserving implicit scheme is proposed. Numerical simulations of a galactic model hosting a BL Lacertae object and magnetized rotating black hole background support these analytical results. The new method with appropriate time steps is used to explore the effects of varying the parameters on the presence of chaos in the two physical models. Chaos easily occurs in the galactic model as the mass of the nucleus, the internal perturbation parameter, and the anisotropy of the potential of the elliptical galaxy increase. The dynamics of charged particles around the magnetized Kerr spacetime is easily chaotic for larger energies of the particles, smaller initial angular momenta of the particles, and stronger magnetic fields. The chaotic properties are not necessarily weakened when the black-hole spin increases. The new method can be used for any six-dimensional Hamiltonian problems, including globally hyperbolic spacetimes with readily available (3 + 1) split coordinates.
Construction material classification on imbalanced datasets for construction monitoring automation using Vision Transformer (ViT) architecture

: Nowadays, automation is a critical topic due to its significant impacts on the productivity of construction projects. Utilizing automation in this industry brings about great results, such as remarkable improvements in the efficiency, quality, and safety of construction activities. The scope of automation in construction includes a wide range of stages, and monitoring construction projects is no exception. Additionally, it is of great importance in project management since an accurate and timely assessment of project progress enables managers to quickly identify deviations from the schedule and take the required actions at the right time. In this stage, one of the most important tasks is to daily keep track of the project progress, which is very time-consuming and labor-intensive, but automation has facilitated and accelerated this task. It also eliminated or at least decreased the risk of many dangerous tasks. In this way, the first step of construction automation is to detect used materials in a project site automatically. In this paper, a novel deep learning architecture is utilized, called Vision Transformer (ViT), for detecting and classifying construction materials. To evaluate the applicability and performance of the proposed method, it is trained and tested on three large imbalanced datasets, namely Construction Material Library (CML) and Building Material Dataset (BMD), used in the previous papers, as well as a new dataset created by combining them. The achieved results revealed an accuracy of 100 percent in all parameters and also in each material category. It is believed that the proposed method provides a novel and robust tool for detecting and classifying different material types.