Miracle-dz/UniFAR-FTUs huggingface dataset:
Singular fibrations over surfaces

Singular fibrations generalize achiral Lefschetz fibrations of 4-manifolds over surfaces while sharing some of their properties. For instance, relatively minimal singular fibrations are determined by their monodromy. We explain how to construct examples of singular fibrations with a single singularity and Matsumoto's construction of singular fibrations of the sphere $S^4$. Previous results of Hirzebruch and Hopf on 2-plane fields with finitely many singularities are outlined in connection with the work of Neumann and Rudolph on the Hopf invariant. Eventually, we prove that closed orientable 4-manifolds with large first Betti number and vanishing second Betti number do not admit singular fibrations.
Understanding Linearity of Cross-Lingual Word Embedding Mappings

The technique of Cross-Lingual Word Embedding (CLWE) plays a fundamental role in tackling Natural Language Processing challenges for low-resource languages. Its dominant approaches assumed that the relationship between embeddings could be represented by a linear mapping, but there has been no exploration of the conditions under which this assumption holds. Such a research gap becomes very critical recently, as it has been evidenced that relaxing mappings to be non-linear can lead to better performance in some cases. We, for the first time, present a theoretical analysis that identifies the preservation of analogies encoded in monolingual word embeddings as a necessary and sufficient condition for the ground-truth CLWE mapping between those embeddings to be linear. On a novel cross-lingual analogy dataset that covers five representative analogy categories for twelve distinct languages, we carry out experiments which provide direct empirical support for our theoretical claim. These results offer additional insight into the observations of other researchers and contribute inspiration for the development of more effective cross-lingual representation learning strategies.
Noncommutative Bispectral Algebras and Their Presentations

We prove a general result on presentations of finitely generated algebras and apply it to obtain nice presentations for some noncommutative algebras arising in the matrix bispectral problem. By “nice presentation”, we mean a presentation that has as few as possible defining relations. This, in turn, has potential applications in computer algebra implementations and examples. Our results can be divided into three parts. In the first two, we consider bispectral algebras with the eigenvalue in the physical equation to be scalar-valued for 2×2 and 3×3 matrix-valued eigenfunctions. In the third part, we assume the eigenvalue in the physical equation to be matrix-valued and draw an important connection with Spin Calogero–Moser systems. In all cases, we show that these algebras are finitely presented. As a byproduct, we answer positively a conjecture of F. A. Grünbaum about these algebras.
Beyond Natural Motion: Exploring Discontinuity for Video Frame Interpolation

Video interpolation is the task that synthesizes the intermediate frame given two consecutive frames. Most of the previous studies have focused on appropriate frame warping operations and reﬁnement modules for the warped frames. These studies have been conducted on natural videos having only continuous motions. However, many practical videos contain a lot of discontinuous motions, such as chat windows, watermarks, GUI elements, or subtitles. We propose three techniques to expand the concept of transition between two consecutive frames to address these issues. First is a new architecture that can separate continuous and discontinuous motion areas. We also propose a novel data augmentation strategy called ﬁgure-text mixing (FTM) to make our model learn more general scenarios. Finally, we propose loss functions to give supervisions of the discontinuous motion areas with the data augmentation. We collected a special dataset consisting of some mobile games and chatting videos. We show that our method signiﬁcantly improves the interpolation qualities of the videos on the special dataset. Moreover, our model outperforms the state-of-the-art methods for natural video datasets containing only continuous motions, such as DAVIS and UCF101.
Sharp hierarchical upper bounds on the critical two-point function for long-range percolation on Zd

Consider long-range Bernoulli percolation on [Formula: see text] in which we connect each pair of distinct points x and y by an edge with probability 1 − exp(− β‖ x − y‖− d− α), where α > 0 is fixed and β ⩾ 0 is a parameter. We prove that if 0 < α < d, then the critical two-point function satisfies [Formula: see text] for every r ⩾ 1, where [Formula: see text]. In other words, the critical two-point function on [Formula: see text] is always bounded above on average by the critical two-point function on the hierarchical lattice. This upper bound is believed to be sharp for values of α strictly below the crossover value α c( d), where the values of several critical exponents for long-range percolation on [Formula: see text] and the hierarchical lattice are believed to be equal.
The Lp convergence of Fourier series on triangular domains

Abstract We prove Lp norm convergence for (appropriate truncations of) the Fourier series arising from the Dirichlet Laplacian eigenfunctions on three types of triangular domains in $\mathbb{R}^2$: (i) the 45-90-45 triangle, (ii) the equilateral triangle and (iii) the hemiequilateral triangle (i.e. half an equilateral triangle cut along its height). The limitations of our argument to these three types are discussed in light of Lamé’s Theorem and the image method.
Inclusive Study Group Formation at Scale

Underrepresented students face many significant challenges in their education. In particular, they often have a harder time than their peers from majority groups in building long-term high-quality study groups. This challenge is exacerbated in remote-learning scenarios, where students are unable to meet face-to-face and must rely on pre-existing networks for social support. We present a scalable system that removes structural obstacles faced by underrepresented students and supports all students in building inclusive and flexible study groups. One of our main goals is to make the traditionally informal and unstructured process of finding study groups for homework more equitable by providing a uniform but lightweight structure. We aim to provide students from underrepresented groups an experience that is similar in quality to that of students from majority groups. Our process is unique in that it allows students the opportunity to request group reassignments during the semester if they wish. Unlike other collaboration tools our system is not mandatory and does not use peer-evaluation. We trialed our approach in a 1000+ student introductory Engineering and Computer Science course that was conducted entirely online during the COVID-19 pandemic. We find that students from underrepresented backgrounds were more likely to ask for group-matching support compared to students from majority groups. At the same time, underrepresented students that we matched into study groups had group experiences that were comparable to students we matched from majority groups. B-range students in high-comfort and high-quality groups had improved learning outcomes.
Defending against Reconstruction Attacks with Rényi Differential Privacy

Reconstruction attacks allow an adversary to regenerate data samples of the training set using access to only a trained model. It has been recently shown that simple heuristics can reconstruct data samples from language models, making this threat scenario an important aspect of model release. Differential privacy is a known solution to such attacks, but is often used with a relatively large privacy budget (epsilon>8) which does not translate to meaningful guarantees. In this paper we show that, for a same mechanism, we can derive privacy guarantees for reconstruction attacks that are better than the traditional ones from the literature. In particular, we show that larger privacy budgets do not protect against membership inference, but can still protect extraction of rare secrets. We show experimentally that our guarantees hold against various language models, including GPT-2 finetuned on Wikitext-103.
Comparison of proximal femur deformations, failures and fractures in quasi-static and inertially-driven simulations of a sideways fall from standing : an experimental study utilizing novel fall simulation, digital image correlation, and development of digital volume correlation techniques

Knowledge of proximal femur failure mechanics has a pivotal role to play in predicting who might suffer a hip fracture. Previous researchers of sideways falls resulting in hip fracture have investigated the roles of several bone parameters such as bone mineral density and morphology, as well as different modelling boundary conditions. While important advances have been made, current models use constant displacement rates applied at the greater trochanter, which may not allow the bone to respond as it would in a sideways fall. Proximal femurs have been shown to be sensitive to displacement rate, but impacts like those in a sideways falls have never been examined. The goal of this thesis was to compare the results of constant displacement rate testing to more biofidelic, inertially driven, impact fall simulation testing and determine how these methods influence specific test outcomes. In study 1, sub-failure loads were applied to single bones at constant displacement rate, followed by impact loading in the fall simulator. Stiffnesses, energies and strains at a point were compared. In study 2, the same bones were compared using digital image correlation to examine bone strains on the anteriorsuperior femoral neck. In study 3, two cohorts of bones were loaded to failure, one at constant displacement rate and the other in the impact fall simulator. Initial failure locations, fracture patterns, stiffnesses and energies to failure were compared. The results of study 1 indicate that the behaviours of the bones were not affected by the change in loading. In study 2, I found that individual specimen strain maps were sensitive to the change in loading parameters; however, pooling the data from all the specimens yielded no statistical difference. In study 3, I discovered that final fracture patterns were different, but initial failure locations, stiffnesses
Improving Human Sperm Head Morphology Classification With Unsupervised Anatomical Feature Distillation

With rising male infertility, sperm head morphology classification becomes critical for accurate and timely clinical diagnosis. Recent deep learning (DL) morphology analysis methods achieve promising benchmark results, but leave performance and robustness on the table by relying on limited and possibly noisy class labels. To address this, we introduce a new DL training framework that leverages anatomical and image priors from human sperm microscopy crops to extract useful features without additional labeling cost. Our core idea is to distill sperm head information with reliably-generated pseudo-masks and unsupervised spatial prediction tasks. The predicted foreground masks from this distillation step are then leveraged to regularize and reduce image and label noise in the tuning stage. We evaluate our new approach on two public sperm datasets and achieve state-of-the-art performances (e.g. 65.9% SCIAN accuracy and 96.5% HuSHeM accuracy).
PILED: An Identify-and-Localize Framework for Few-Shot Event Detection

Practical applications of event extraction systems have long been hindered by their need for heavy human annotation. In order to scale up to new domains and event types, models must learn to cope with limited supervision, as in few-shot learning settings. To this end, the major challenge is to let the model master the semantics of event types, without requiring abundant event mention annotations. In our study, we employ cloze prompts to elicit event-related knowledge from pretrained language models and further use event deﬁnitions and keywords to pinpoint the trigger word. By formulating the event detection task as an identify-then-localize procedure, we minimize the number of type-speciﬁc parameters, enabling our model to quickly adapt to event detection tasks for new types. Experiments on three event detection benchmark datasets (ACE, FewEvent, MAVEN) show that our proposed method performs favorably under fully supervised settings and surpasses existing few-shot methods by 21% F1 on the FewEvent dataset and 20% on the MAVEN dataset when only 5 examples are provided for each event type.
Coboundaries and eigenvalues of finitary S-adic systems

An S-adic system is a symbolic dynamical system generated by iterating an infinite sequence of substitutions or morphisms, called a directive sequence. A finitary S-adic dynamical system is one where the directive sequence consists of morphisms selected from a finite set. We study eigenvalues and coboundaries for finitary recognizable S-adic dynamical systems. To do this we identify the notions of straightness and essential words, and use them to define a coboundary, which allows us to express necessary and sufficient conditions that a complex number must satisfy in order to be a continuous or measurable eigenvalue. We then apply our results to finitary directive sequences of substitutions of constant length, and show how to create constant-length S-adic shifts with non-trivial coboundaries. We show that in this case all continuous eigenvalues are rational and we give a complete description of the rationals that can be an eigenvalue, indicating how this leads to a Cobham-style result for these systems.
Plasticity in the developing brain: neurophysiological basis for lesion-induced motor reorganization

Abstract The plasticity of the developing brain can be observed following injury to the motor cortex and/or corticospinal tracts, the most commonly injured brain area in the pre- or peri-natal period. Factors such as the timing of injury, lesion size and lesion location may affect a single hemisphere’s ability to acquire bilateral motor representation. Bilateral motor representation of single hemisphere origin is most likely to occur if brain injury occurs before the age of 2 years; however, the link between injury aetiology, reorganization type and functional outcome is largely understudied. We performed a retrospective review to examine reorganized cortical motor maps identified through transcranial magnetic stimulation in a cohort of 52 patients. Subsequent clinical, anthropometric and demographic information was recorded for each patient. Each patient’s primary hand motor cortex centre of gravity, along with the Euclidian distance between reorganized and normally located motor cortices, was also calculated. The patients were classified into broad groups including reorganization type (inter- and intrahemispheric motor reorganization), age at the time of injury (before 2 years and after 2 years) and injury aetiology (developmental disorders and acquired injuries). All measures were analysed to find commonalities between motor reorganization type and injury aetiology, function and centre of gravity distance. There was a significant effect of injury aetiology on type of motor reorganization (P < 0.01), with 60.7% of patients with acquired injuries and 15.8% of patients with developmental disorders demonstrating interhemispheric motor reorganization. Within the interhemispheric motor reorganization group, ipsilaterally and contralaterally projecting hand motor cortex centres of gravity overlapped, indicating shared cortical motor representation. Furthermore, the data suggest significantly higher prevalence of bilateral motor representation from a single hemisphere in cases of acquired injuries compared to those of developmental origin. Functional outcome was found to be negatively affected by acquired injuries and interhemispheric motor reorganization relative to their respective counterparts with developmental lesions and intrahemispheric motor reorganization. These results provide novel information regarding motor reorganization in the developing brain via an unprecedented cohort sample size and transcranial magnetic stimulation. Transcranial magnetic stimulation is uniquely suited for use in understanding the principles of motor reorganization, thereby aiding in the development of more efficacious therapeutic techniques to improve functional recovery following motor cortex injury.
A “Weird” Mitochondrial Fatty Acid Oxidation as a Metabolic “Secret” of Cancer

Cancer metabolism is an extensively studied field since the discovery of the Warburg effect about 100 years ago and continues to be increasingly intriguing and enigmatic so far. It has become clear that glycolysis is not the only abnormally activated metabolic pathway in the cancer cells, but the same is true for the fatty acid synthesis (FAS) and mevalonate pathway. In the last decade, a lot of data have been accumulated on the pronounced mitochondrial fatty acid oxidation (mFAO) in many types of cancer cells. In this article, we discuss how mFAO can escape normal regulation under certain conditions and be overactivated. Such abnormal activation of mitochondrial β-oxidation can also be combined with mutations in certain enzymes of the Krebs cycle that are common in cancer. If overactivated β-oxidation is combined with other common cancer conditions, such as dysfunctions in the electron transport complexes, and/or hypoxia, this may alter the redox state of the mitochondrial matrix. We propose the idea that the altered mitochondrial redox state and/or inhibited Krebs cycle at certain segments may link mitochondrial β-oxidation to the citrate-malate shuttle instead to the Krebs cycle. We call this abnormal metabolic condition “β-oxidation shuttle”. It is unconventional mFAO, a separate metabolic pathway, unexplored so far as a source of energy, as well as a source of cataplerosis, leading to biomass accumulation, accelerated oxygen consumption, and ultimately a source of proliferation. It is inefficient as an energy source and must consume significantly more oxygen per mole of ATP produced when combined with acetyl-CoA consuming pathways, such as the FAS and mevalonate pathway.
Risk Factors for the Absence of Diagnosis of Asthma Despite Disease Symptoms: Results from the Swedish GA2LEN Study

Background Asthma is a common chronic disease presenting with airway symptoms such as wheezing, chest tightness and attacks of breathlessness. Underdiagnosis of asthma is common and correlates to negative outcomes such as a lower quality of life and reduced work capacity. Purpose This study aims to identify factors for not being diagnosed with asthma if presenting with asthma symptoms. Patients and Methods A questionnaire was sent to 45,000 subjects (age 16–74 years) in Sweden. Subjects who reported both wheeze and breathlessness and wheeze when not having a cold were defined as having asthma-related symptoms. Data on demographics, educational level, smoking, physical activity, comorbidities, symptoms and asthma were collected. Logistic regression was used to identify risk factors for not being diagnosed with asthma. Results Of the 25,391 who responded to the survey, 6.2% reported asthma-related symptoms. Of these, 946 had been diagnosed with asthma previously, while 632 had not. Independent risk factors for not being diagnosed with asthma were higher age (OR (95% CI) (2.17 (1.39–3.40))), male sex (1.46 (1.17–1.81)), current smoking (2.92 (2.22–3.84)), low level of education (1.43 (1.01–2.01)), low physical activity (1.36 (1.06–1.74)), and hypertension (1.50 (1.06–2.12)). Conclusion Men, smokers, older subjects, and those with low educational level or low physical activity are less likely to be diagnosed with asthma despite presenting asthma-related symptoms.
Suicide gene therapy by canine mesenchymal stem cell transduced with thymidine kinase in a u-87 glioblastoma murine model: Secretory profile and antitumor activity

The role played by certain domestic species such as dogs as a translational model in comparative oncology shows great interest to develop new therapeutic strategies in brain tumors. Gliomas are a therapeutic challenge that represents the most common form of malignant primary brain tumors in humans and the second most common form in dogs. Gene-directed enzyme/prodrug therapy using adipose mesenchymal stem cells (Ad-MSCs) expressing the herpes simplex virus thymidine kinase (TK) has proven to be a promising alternative in glioblastoma therapy, through its capacity to migrate and home to the tumor and delivering local cytotoxicity avoiding other systemic administration. In this study, we demonstrate the possibility for canine Ad-MSCs (cAd-MSCs) to be genetically engineered efficiently with a lentiviral vector to express TK (TK-cAd-MSCs) and in combination with ganciclovir (GCV) prodrug demonstrated its potential antitumor efficacy in vitro and in vivo in a mice model with the human glioblastoma cell line U87. TK-cAd-MSCs maintained cell proliferation, karyotype stability, and MSCs phenotype. Genetic modification significantly affects its secretory profile, both the analyzed soluble factors and exosomes. TK-cAd-MSCs showed a high secretory profile of some active antitumor immune response cytokines and a threefold increase in the amount of secreted exosomes, with changes in their protein cargo. We also found that the prodrug protein is not released directly into the culture medium by TK-cAd-MSCs. We believe that our work provides new perspectives for glioblastoma gene therapy in dogs and a better understanding of this therapy in view of its possible implantation in humans.
Rationales and functions of disliked music: An in-depth interview study

Background and objectives With a few exceptions, musical taste has been researched via likes or preferences of certain types of music. The present study focuses on disliked music and takes a broad approach to cover explanatory strategies related to personal dislikes. Methods In-depth interviews were conducted with 21 participants in five age groups. Interviewees were asked to prepare a list of their disliked music, and for each item they were asked about the reasons for the dislike. To ensure that the complexity and range of the participants’ dislikes and rationales were captured in the analysis, a structuring content analysis as a mostly theory-driven approach was combined with inductive category creation out of the interview data. Results The most often mentioned type of dislike was musical style, followed by artist and genre. Five main reference points were identified for describing musical dislikes: the music itself, lyrics, performance, artist, and the people who listen to it. The identified rationales for disliked music were assigned to three larger categories: object-related reasons, such as music-compositional aspects, aesthetic dichotomies or lyrics; subject-related reasons, such as emotional or bodily effects, or discrepancies with the self-image; social reasons, which refer to one’s social environment and the taste judgments common to it (in-group) or to other groups of which the participants do not feel part of (out-group). Apart from the rationales for disliked music, the participants described specific reactions when they are confronted with their disliked music, such as emotional, physical, and social reactions. Conclusions While musical dislikes have already been shown to fulfill important social functions, the current study extends the rationales to music-related and self-related reasons. Musical dislikes fulfill similar functions to liked music, such as preservation of a good mood, identity expression and construction, strengthening of group cohesion as well as social distinction.