Miracle-dz/UniFAR-FTUs huggingface dataset:
AssembleRL: Learning to Assemble Furniture from Their Point Clouds

The rise of simulation environments has enabled learning-based approaches for assembly planning, which is otherwise a labor-intensive and daunting task. Assembling furniture is especially interesting since furniture are intricate and pose challenges for learning-based approaches. Surprisingly, humans can solve furniture assembly mostly given a 2D snapshot of the assembled product. Although recent years have witnessed promising learning-based approaches for furniture assembly, they assume the availability of correct connection labels for each assembly step, which are expensive to obtain in practice. In this paper, we alleviate this assumption and aim to solve furniture assembly with as little human expertise and supervision as possible. To be specific, we assume the availability of the assembled point cloud, and comparing the point cloud of the current assembly and the point cloud of the target product, obtain a novel reward signal based on two measures: Incorrectness and incompleteness. We show that our novel reward signal can train a deep network to successfully assemble different types of furniture. Code and networks available here: https://github.com/METU-KALFA/AssembleRL.
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer

Nowadays self-paced learning (SPL) is an important machine learning paradigm that mimics the cognitive process of humans and animals. The SPL regime involves a self-paced regularizer and a gradually increasing age parameter, which plays a key role in SPL but where to optimally terminate this process is still non-trivial to determine. A natural idea is to compute the solution path w.r. t. age parameter (i.e., age-path). However, current age-path algorithms are either limited to the simplest regularizer, or lack solid theoretical understanding as well as computational efficiency. To address this challenge, we propose a novel \underline{G}eneralized \underline{Ag}e-path \underline{A}lgorithm (GAGA) for SPL with various self-paced regularizers based on ordinary differential equations (ODEs) and sets control, which can learn the entire solution spectrum w.r. t. a range of age parameters. To the best of our knowledge, GAGA is the first exact path-following algorithm tackling the age-path for general self-paced regularizer. Finally the algorithmic steps of classic SVM and Lasso are described in detail. We demonstrate the performance of GAGA on real-world datasets, and find considerable speedup between our algorithm and competing baselines.
An Approach to Mismatched Disturbance Rejection Control for Uncontrollable Systems

This study focuses on the problem of optimal mismatched disturbance rejection control for uncontrollable linear discrete-time systems. In contrast to previous studies, by introducing a quadratic performance index such that the regulated state can track a reference trajectory and minimize the effects of disturbances, mismatched disturbance rejection control is transformed into a linear quadratic tracking problem. The necessary and sufficient conditions for the solvability of this problem over a finite horizon and a disturbance rejection controller are derived by solving a forward-backward difference equation. In the case of an infinite horizon, a sufficient condition for the stabilization of the system is obtained under the detectable condition. This paper details our novel approach to disturbance rejection. Four examples are provided to demonstrate the effectiveness of the proposed method.
TempoWiC: An Evaluation Benchmark for Detecting Meaning Shift in Social Media

Language evolves over time, and word meaning changes accordingly. This is especially true in social media, since its dynamic nature leads to faster semantic shifts, making it challenging for NLP models to deal with new content and trends. However, the number of datasets and models that specifically address the dynamic nature of these social platforms is scarce. To bridge this gap, we present TempoWiC, a new benchmark especially aimed at accelerating research in social media-based meaning shift. Our results show that TempoWiC is a challenging benchmark, even for recently-released language models specialized in social media.
Limit Cycles of AdaBoost

The iterative weight update for the AdaBoost machine learning algorithm may be realized as a dynamical map on a probability simplex. When learning a low-dimensional data set this algorithm has a tendency towards cycling behavior, which is the topic of this paper. AdaBoost’s cycling behavior lends itself to direct computational methods that are ineffective in the general, non-cycling case of the algorithm. From these computational properties we give a concrete correspondence between AdaBoost’s cycling behavior and continued fractions dynamics. Then we explore the results of this correspondence to expound on how the algorithm comes to be in this periodic state at all. What we intend for this work is to be a novel and self-contained explanation for the cycling dynamics of this machine learning algorithm.
The zeta(2) limit in the random assignment problem

The random assignment (or bipartite matching) problem asks about A n = min π P ni =1 c ( i, π ( i )), where ( c ( i, j )) is a n × n matrix with i.i. d. entries, say with exponential(1) distribution, and the minimum is over permutations π . M´ezard and Parisi (1987) used the replica method from statistical physics to argue non-rigorously that EA n → ζ (2) = π 2 / 6. Aldous (1992) identiﬁed the limit in terms of a matching problem on a limit inﬁnite tree. Here we construct the optimal matching on the inﬁnite tree. This yields a rigorous proof of the ζ (2) limit and of the conjectured limit distribution of edge-costs and their rank-orders in the optimal matching. It also yields the asymptotic essential uniqueness property: every almost-optimal matching coincides with the optimal matching except on a small proportion of edges.
GEMS Embeddings of Hayward Regular Black Holes in Massless and Massive Gravities

After finding a solution for the Hayward regular black hole (HRBH) in massive gravity, we embed the (3+1)-dimensional HRBHs both in massless and in massive gravities into (5+2)- and (6+3)-dimensional Minkowski spacetimes, respectively. Here, massive gravity denotes that a graviton acquires a mass holographically by broken momentum conservation in the HRBH. The original HRBH has no holographically added gravitons, which we call ‘massless’. Making use of newly found embedding coordinates, we obtain desired Unruh temperatures and compare them with the Hawking and local fiducial temperatures, showing that the Unruh effect for a uniformly accelerated observer in a higher-dimensional flat spacetime is equal to the Hawking effect for a fiducial observer in a black hole spacetime. We also obtain freely falling temperatures of the HRBHs in massless and massive gravities seen by freely falling observers, which remain finite even at the event horizons while becoming the Hawking temperatures in asymptotic infinity.
Study of the q diagram in GX 339-4

Black hole X-ray binary (BHXB) GX 339-4 produces the most frequent X-ray outbursts (every 2-4 years) among known X-ray binary sources in our galaxy. Here we present the study of the evolution of GX 339-4 over the years of observations using the Hardness Intensity Diagram (HID), i.e., the q diagram. We present an analysis of two outbursts of the source observed by the Monitor of All-sky X-ray Image (MAXI) telescope aboard the International Space Station (ISS).
VIPHY: Probing "Visible" Physical Commonsense Knowledge

In recent years, vision-language models (VLMs) have shown remarkable performance on visual reasoning tasks (e.g. attributes, location). While such tasks measure the requisite knowledge to ground and reason over a given visual instance, they do not, however, measure the ability of VLMs to retain and generalize such knowledge. In this work, we evaluate their ability to acquire"visible"physical knowledge -- the information that is easily accessible from images of static scenes, particularly across the dimensions of object color, size and space. We build an automatic pipeline to derive a comprehensive knowledge resource for calibrating and probing these models. Our results indicate a severe gap between model and human performance across all three tasks. Furthermore, our caption pretrained baseline (CapBERT) significantly outperforms VLMs on both size and spatial tasks -- highlighting that despite sufficient access to ground language with visual modality, they struggle to retain such knowledge. The dataset and code are available at https://github.com/Axe--/ViPhy .
Deep learning in a bilateral brain with hemispheric specialization

The brains of all bilaterally symmetric animals on Earth are divided into left and right hemispheres. The anatomy and functionality of the hemispheres have a large degree of overlap, but there are asymmetries and they specialise to possess different attributes. Other authors have used computational models to mimic hemispheric asymmetries with a focus on reproducing human data on semantic and visual processing tasks. We took a different approach and aimed to understand how dual hemispheres in a bilateral architecture interact to perform well in a given task. We propose a bilateral artificial neural network that imitates lateralisation observed in nature: that the left hemisphere specialises in specificity and the right in generality. We used different training objectives to achieve the desired specialisation and tested it on an image classification task with two different CNN backbones -- ResNet and VGG. Our analysis found that the hemispheres represent complementary features that are exploited by a network head which implements a type of weighted attention. The bilateral architecture outperformed a range of baselines of similar representational capacity that don't exploit differential specialisation, with the exception of a conventional ensemble of unilateral networks trained on a dual training objective for specifics and generalities. The results demonstrate the efficacy of bilateralism, contribute to the discussion of bilateralism in biological brains and the principle may serves as an inductive bias for new AI systems.
Ameliorative effects of high intensity interval training and Lactobacillus rhamnosus GG Protect against tetracycline-induced fatty liver in rats: a gene expression profiling comparative study

Exercise training and probiotics have been suggested as a treatment for the prevention of chronic liver damage such as non-alcoholic fatty liver disease (NAFLD). Lactobacillus rhamnosus Gorbach‐Goldin (LGG) is one of the most widely used probiotic strains that decreases liver damage. Thus, this study aims to consider the ameliorative effects of high intensity interval training (HIIT) and LGG against tetracycline-induced fatty liver in rats. Eighty male Wistar rats were randomly divided into 8 groups of (n=10 each group): control, LGG, HIIT, LGG+HIIT, NAFLD, NAFLD+LGG, NAFLD+HIIT, and NAFLD+LGG+HIIT. The rats are treated by intraperitoneal injection with 140 mg/kg−1 tetracycline, an antibiotic previously known to induce steatosis. The exercise training groups performed HIIT 5 days/week for 5 weeks. 107 colony-forming units (cfu) of LGG were gavaged for LGG groups 5 days/week for 5 weeks. Probiotic supplementation in combination with interval training significantly decreased tissue inhibitor of matrix metalloproteinases-1 (TIMP-1) mRNA and matrix metalloproteinase-2 (MMP-2) mRNA in the liver (p<0.05), while the levels of lysosomal acid lipase (LIPA) mRNA was significantly increased compared to NAFLD group. Also, compared with NAFLD group, NAFLD+LGG, NAFLD+HIIT and NAFLD+LGG+HIIT groups showed a significant decrease in hepatic monocyte chemoattractant protein-1 (MCP-1). Compared to LGG and LGG+HIIT groups, all NAFLD groups showed a significant decrease in apolipoprotein C3 (apoc3) in liver tissue (p<0.05). The results suggested that interval exercise with LGG supplementation minimizes cell destruction and inflammation in liver tissue due to NAFLD by improving gene expression profiles.
Insights into the mechanisms of non-coding RNAs’ implication in the pathogenesis of Alzheimer’s disease

Non-coding RNAs including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are implicated in the regulation of gene expression at transcriptional, posttranscriptional, and epigenetic levels. Several studies in cell lines, animal models, and humans, have revealed that non-coding RNAs play crucial roles in the pathogenesis of Alzheimer's disease (AD). Detailed knowledge on their mechanism of implication in the AD pathogenesis can help to develop novel therapeutic and disease management strategies. The two main pathological hallmarks of AD are amyloid plaques resulting from the β-amyloid accumulation, and neurofibrillary tangles (NFT) due to the phosphorylated tau accumulation. Several lncRNAs and miRNAs play crucial roles in both these hallmarks of the AD pathogenesis and other AD-related pathological procedures such as neuronal and synaptic plasticity, neuroinflammation, neuronal differentiation and neuronal apoptosis. In this review, we outlined the non-coding RNAs and further discussed how they are implicated in these AD-related pathological procedures.
Bubble formation in phi**4 theory in the thin wall limit and beyond

Scalar field theory with an asymmetric potential is studied at zero temperature and high-temperature for phi^4 theory with both phi and phi^3 symmetry breaking. The equations of motion are solved numerically to obtain O(4) symmetric and O(3) cylindrical symmetric bounce solutions. These solutions control the rates for tunneling from the false vacuum to the true vacuum by bubble formation. The range of validity of the thin-wall approximation (TWA) is investigated. An analytical solution for the bounce is presented, which reproduces the action in the thin-wall as well as the thick-wall limits.
Superconductivity interpreted as k-space magnetism

In preceding papers the author proposed a new mechanism of Cooper pair formation that follows within an extended Heisenberg model. The new mechanism operates in narrow, partly filled "superconducting" energy bands of special symmetry and shows resemblances, and also great differences as compared with the familiar BCS mechanism. In the present paper the resulting superconducting state is interpreted as a state in which the spins are ordered within the k space. In this picture, the peculiar features of the new mechanism, as compared with the BCS mechanism, can be understood in a straightforward manner. On the one hand, the new mechanism resembles the BCS picture, because the formation of Cooper pairs is still mediated by bosons (having dominant phonon character in the isotropic lattices of the conventional superconductors). On the other hand, however, the pair formation is not the result of an attractive electron-electron interaction mediated by these bosons. Rather, the bosons carry the crystal-spin angular momentum $hbar$ and generate in a new way constraining forces that constrain the electrons to form Cooper pairs. The scale of the transition temperatures in conventional and high-temperature superconductors is set by the excitation energies of stable crystal-spin-1 bosons that are different in isotropic and anisotropic materials.
Mass Hierarchies versus proton Decay in MSSM Orientifold Compactifications

We review two systematic bottom-up analyses of MSSM quivers recently performed by the authors. We extend the analysis of arXiv:0905.3379 by including constraints arising from proton decay via dimension 5 operators and present all four-stack quivers in the Madrid embedding which satisfy this additional constraint. Furthermore, we investigate and make precise the interplay between mass hierarchies obtained via factorizable Yukawa textures and the presence of dimension 5 proton decay operators in MSSM orientifold compactifications. We discuss this issue in a five-stack quiver, first presented in arXiv:0909.4292, which exhibits proper mass hierarchies and no rapid proton decay.
Cortical activity involved in perception and imagery of visual stimuli in a subject with aphantasia. An EEG case report

ABSTRACT Aphantasia has been described as the inability to voluntarily evoke mental images using the “mind’s eye. ” We studied a congenital aphantasic subject using neuropsychological testsand 64 channel EEG recordings, in order to studycortical activity involved in perception and imagery evaluating event-related potentials(N170, P200, N250). The subject is in the normal range of the neuropsychological tests performed, except for specific imagery tests. The EEG results show that when he evokes the same mental image, he starts the evoking process from left temporal instead of frontal areas, he does not activate occipital visual nor left anterior parietal areas.
Modeling ascending Ureaplasma parvum infection through the female reproductive tract using vagina‐cervix‐decidua‐organ‐on‐a‐chip and feto‐maternal interface‐organ‐on‐a‐chip

Genital mycoplasmas can break the cervical barrier and cause intraamniotic infection and preterm birth. This study developed a six‐chamber vagina‐cervix‐decidua‐organ‐on‐a‐chip (VCD‐OOC) that recapitulates the female reproductive tract during pregnancy with culture chambers populated by vaginal epithelial cells, cervical epithelial and stromal cells, and decidual cells. Cells cultured in VCD‐OOC were characterized by morphology and immunostaining for cell‐specific markers. We transferred the media from the decidual cell chamber of the VCD‐OOC to decidual cell chamber in feto‐maternal interface organ‐on‐a‐chip (FMi‐OOC), which contains the fetal membrane layers. An ascending Ureaplasma parvum infection was created in VCD‐OOC. U. parvum was monitored for 48 h post‐infection with their cytotoxicity (LDH assay) and inflammatory effects (multiplex cytokine assay) in the cells tested. An ascending U. parvum infection model of PTB was developed using CD‐1 mice. The cell morphology and expression of cell‐specific markers in the VCD‐OOC mimicked those seen in lower genital tract tissues. U. parvum reached the cervical epithelial cells and decidua within 48 h and did not cause cell death in VCD‐OOC or FMi‐OOC cells. U. parvum infection promoted minimal inflammation, while the combination of U. parvum and LPS promoted massive inflammation in the VCD‐OOC and FMi‐OOC cells. In the animal model, U. parvum vaginal inoculation of low‐dose U. parvum did not result in PTB, and even a high dose had only some effects on PTB (20%). However, intra‐amniotic injection of U. parvum resulted in 67% PTB. We report the colonization of U. parvum in various cell types; however, inconsistent, and low‐grade inflammation across multiple cell types suggests poor immunogenicity induced by U. parvum.
Hepatocellular Carcinoma Chemoprevention with Generic Agents

Liver cancer, mainly hepatocellular carcinoma (HCC), remains a major cause of cancer-related death worldwide. With the global epidemic of obesity, the major HCC etiologies have been dynamically shifting from viral to metabolic liver diseases. This change has made HCC prevention difficult with increasingly elusive at-risk populations as rational target for preventive interventions. Besides ongoing efforts to reduce obesity and metabolic disorders, chemoprevention in patients who already have metabolic liver diseases will have a significant impact on the poor HCC prognosis. Hepatitis B- and C-related HCC incidences have been substantially reduced by the new anti-virals, but HCC risk can persist over a decade even after successful viral treatment, highlighting the need for HCC-preventive measures also in these patients. Experimental and retrospective studies have suggested potential utility of generic agents such as lipophilic statins and aspirin for HCC chemoprevention given their well characterized safety profile, although anticipated efficacy may be modest. In this review, we overview recent clinical and translational studies of generic agents in the context of HCC chemoprevention under the contemporary HCC etiologies. We also discuss newly emerging approaches to overcome the challenges in clinical testing of the agents to facilitate their clinical translation.
T-cell receptor variable region usage in Chagas disease: A systematic review of experimental and human studies

T cells recognize their ligand, the peptide major histocompatibility complex (MHC), via the T-cell receptor (TCR), which is composed of covalently linked α and β or γ and δ chains. This recognition is critical for T-cell ontogeny and controls the selection, activation, and function of T lymphocytes. Specific TCR αβ variable regions have been associated with immunopathogenesis of Chagas disease. Here, we present a systematic review that compiles experimental in vivo and human data regarding the preferential expression of variable alpha (Vα) and variable beta (Vβ) chain regions in Trypanosoma cruzi infection. The original studies indexed in PubMed/Medline, Scopus, and Web of Science databases were screened according to the PRISMA strategy. The analysis showed that expression of TCR Vα subfamilies were evaluated in one human study, and, unlike TCR Vβ, TCR Vα presented a more restricted usage. Despite the great variability in the usage of TCR Vβ regions in human Chagas disease, a down-regulation of TCR Vβ5 expression by T cells from patients in the acute phase of the disease was shown. Opposingly, this TCR region was found overly expressed in CD4+ T cells from chronic Chagas patients. It was also demonstrated that murine Vβ9+ T cells derived from nonlymphoid organs of T. cruzi-infected animals had a modulatory profile, while splenic Vβ9+ T cells produced inflammatory cytokines, indicating that although they display the same TCR Vβ region usage, these cells are functionally distinct. Despite the limitations of few papers and year of publication of the studies, compiling the data derived from them reveals that further investigation of TCR usage will point to their potential role in protective or pathogenic responses, as biomarkers of disease progression, and in the search for dominant peptides potentially useful for the development of vaccines or therapies.
Outcomes with sacubitril/valsartan in outpatients with heart failure and reduced ejection fraction: The ARIADNE registry

ARIADNE aimed to assess the association between effects of sacubitril/valsartan and no sacubitril/valsartan treatment and clinical characteristics, functional capacity, and clinical outcomes (cause‐specific mortality and hospitalizations) in outpatients with heart failure (HF) with reduced ejection fraction (HFrEF).