Miracle-dz/UniFAR-FTUs huggingface dataset:
A Flexible Generative Framework for Graph-based Semi-supervised Learning

We consider a family of problems that are concerned about making predictions for the majority of unlabeled, graph-structured data samples based on a small proportion of labeled samples. Relational information among the data samples, often encoded in the graph/network structure, is shown to be helpful for these semi-supervised learning tasks. However, conventional graph-based regularization methods and recent graph neural networks do not fully leverage the interrelations between the features, the graph, and the labels. In this work, we propose a flexible generative framework for graph-based semi-supervised learning, which approaches the joint distribution of the node features, labels, and the graph structure. Borrowing insights from random graph models in network science literature, this joint distribution can be instantiated using various distribution families. For the inference of missing labels, we exploit recent advances of scalable variational inference techniques to approximate the Bayesian posterior. We conduct thorough experiments on benchmark datasets for graph-based semi-supervised learning. Results show that the proposed methods outperform the state-of-the-art models in most settings.
One Method to Rule Them All: Variance Reduction for Data, Parameters and Many New Methods

We propose a remarkably general variance-reduced method suitable for solving regularized empirical risk minimization problems with either a large number of training examples, or a large model dimension, or both. In special cases, our method reduces to several known and previously thought to be unrelated methods, such as {\tt SAGA}, {\tt LSVRG}, {\tt JacSketch}, {\tt SEGA} and {\tt ISEGA}, and their arbitrary sampling and proximal generalizations. However, we also highlight a large number of new specific algorithms with interesting properties. We provide a single theorem establishing linear convergence of the method under smoothness and quasi strong convexity assumptions. With this theorem we recover best-known and sometimes improved rates for known methods arising in special cases. As a by-product, we provide the first unified method and theory for stochastic gradient and stochastic coordinate descent type methods.
A Block Decomposition Algorithm for Sparse Optimization

Sparse optimization is a central problem in machine learning and computer vision. However, this problem is inherently NP-hard and thus difficult to solve in general. Combinatorial search methods find the global optimal solution but are confined to small-sized problems, while coordinate descent methods are efficient but often suffer from poor local minima. This paper considers a new block decomposition algorithm that combines the effectiveness of combinatorial search methods and the efficiency of coordinate descent methods. Specifically, we consider a random strategy or/and a greedy strategy to select a subset of coordinates as the working set, and then perform a global combinatorial search over the working set based on the original objective function. We show that our method finds stronger stationary points than Amir Beck et al.'s coordinate-wise optimization method. In addition, we establish the convergence rate of our algorithm. Our experiments on solving sparse regularized and sparsity constrained least squares optimization problems demonstrate that our method achieves state-of-the-art performance in terms of accuracy. For example, our method generally outperforms the well-known greedy pursuit method.
Kissing numbers of closed hyperbolic manifolds

Abstract:We prove an upper bound for the number of shortest closed geodesics in a closed hyperbolic manifold of any dimension in terms of its volume and systole, generalizing a theorem of Parlier for surfaces. We also obtain bounds on the number of primitive closed geodesics with length in a given interval that are uniform for all closed hyperbolic manifolds with bounded geometry. The proofs rely on the Selberg trace formula.
GAN2GAN: Generative Noise Learning for Blind Image Denoising with Single Noisy Images

We tackle a challenging blind image denoising problem, in which only single noisy images are available for training a denoiser and no information about noise is known, except for it being zero-mean, additive, and independent of the clean image. In such a setting, which often occurs in practice, it is not possible to train a denoiser with the standard discriminative training or with the recently developed Noise2Noise (N2N) training; the former requires the underlying clean image for the given noisy image, and the latter requires two independently realized noisy image pair for a clean image. To that end, we propose GAN2GAN (Generated-Artiﬁcial-Noise to Generated-Artiﬁcial-Noise) method that can ﬁrst learn to generate synthetic noisy image pairs that simulate independent realizations of the noise in the given images, then carry out the N2N training of a denoiser with those synthetically generated noisy image pairs. Our method consists of three parts: extracting smooth noisy patches to learn the noise distribution in the given images, training a generative model to synthesize the noisy image pairs, and devising an iterative N2N training of a denoiser. In results, we show the denoiser trained with our GAN2GAN, solely based on single noisy images, achieves an impressive denoising performance, almost approaching the performance of the standard discriminatively-trained or N2N-trained models that have more information than ours, and signiﬁcantly outperforming the recent baselines for the same setting.
Emphasis Regularisation by Gradient Rescaling for Training Deep Neural Networks with Noisy Labels

It is fundamental and challenging to train robust and accurate Deep Neural Networks (DNNs) when noisy labels exist. Although great progress has been made, there is still one crucial research question which is not thoroughly explored yet: What training examples should be focused and how much more should they be emphasised when training DNNs under label noise? In this work, we study this question and propose gradient rescaling (GR) to solve it. GR modifies the magnitude of logit vector's gradient to emphasise on relatively easier training data points when severe noise exists, which functions as explicit emphasis regularisation to improve the generalisation performance of DNNs. Apart from regularisation, we also interpret GR from the perspectives of sample reweighting and designing robust loss functions. Therefore, our proposed GR helps connect these three approaches in the literature. We empirically demonstrate that GR is highly noise-robust and outperforms the state-of-the-art noise-tolerant algorithms by a large margin, e.g., increasing 7% on CIFAR-100 with 40% noisy labels. It is also significantly superior to standard regularisors. Furthermore, we present comprehensive ablation studies to explore the behaviours of GR under different cases, which is informative for applying GR in real-world scenarios.
Identification of Novel Virulence Determinants in Mycobacterium paratuberculosis by Screening a Library of Insertional Mutants

ABSTRACT Johne's disease, caused by Mycobacterium paratuberculosis infection, is a worldwide problem for the dairy industry and has a possible involvement in Crohn's disease in humans. To identify virulence determinants of this economically important pathogen, a library of 5,060 transposon mutants was constructed using Tn5367 insertion mutagenesis, followed by large-scale sequencing to identify disrupted genes. In this report, 1,150 mutants were analyzed and 970 unique insertion sites were identified. Sequence analysis of the disrupted genes indicated that the insertion of Tn5367 was more prevalent in genomic regions with G+C content (50.5 to 60.5%) lower than the average G+C content (69.3%) of the rest of the genome. Phenotypic screening of the library identified disruptions of genes involved in iron, tryptophan, or mycolic acid metabolic pathways that displayed unique growth characteristics. Bioinformatic analysis of disrupted genes identified a list of potential virulence determinants for further testing with animals. Mouse infection studies showed a significant decrease in tissue colonization by mutants with a disruption in the gcpE, pstA, kdpC, papA2, impA, umaA1, or fabG2_2 gene. Attenuation phenotypes were tissue specific (e.g., for the umaA1 mutant) as well as time specific (e.g., for the impA mutant), suggesting that those genes may be involved in different virulence mechanisms. The identified potential virulence determinants represent novel functional classes that could be necessary for mycobacterial survival during infection and could provide suitable targets for vaccine and drug development against Johne's and Crohn's diseases.
A Light-curve Analysis of 32 Recent Galactic Novae: Distances and White Dwarf Masses

We obtained the absolute magnitudes, distances, and white dwarf (WD) masses of 32 recent galactic novae based on the time-stretching method for nova light curves. A large part of the light/color curves of two classical novae often overlap each other if we properly squeeze/stretch their timescales. Then, a target nova brightness is related to the other template nova brightness by , where t is the time, MV[t] is the absolute V magnitude, and fs is their timescaling ratio. Moreover, when these two time-stretched light curves, (t/fs)–(MV − 2.5 log fs), overlap each other, (t/fs)–(B − V)0 do too, where (B − V)0 is the intrinsic B − V color. Thus, the two nova tracks overlap each other in the (B − V)0–(MV − 2.5 log fs) diagram. Inversely, using these properties, we obtain/confirm the distance and reddening by comparing each nova light/color curves with well-calibrated template novae. We classify the 32 novae into two types, LV Vul and V1500 Cyg, in the time-stretched (B − V)0–(MV − 2.5 log fs) color–magnitude diagram. The WD mass is obtained by direct comparison of the model V light curves with the observation. Thus, we obtain a uniform set of 32 galactic classical novae that provides the distances and WD masses from a single method. Many novae broadly follow the universal decline law and the present method can be applied to them, while some novae largely deviate from the universal decline law and so the method cannot be directly applied to them. We discuss such examples.
Synchrotron Self-Compton Emission from External Shocks as the Origin of the Sub-TeV Emission in GRB 180720B and GRB 190114C

Recently, very high-energy photons above 100 GeV were reported to be detected from GRB 190114C and GRB 180720B at, respectively, 100–1000 s and 10 hr after the burst. We model the available broadband data of both GRBs with the synchrotron plus synchrotron self-Compton (SSC) emission of the afterglow shocks. We find that the sub-TeV emission of GRB 180720B can be interpreted as the SSC emission from afterglow shocks expanding in a constant-density circumburst medium. The SSC emission of GRB 190114C dominates over the synchrotron component from GeV energies at ∼100 s, which can explain the possible hard spectrum of the GeV emission at this time. The extrapolated flux of this SSC component to sub-TeV energies can explain the high-significance detection of GRB 190114C by the MAGIC telescope. The parameter values (such as the circumburst density and shock microphysical parameters) in the modeling are not unusual for both gamma-ray bursts, implying that the detection of sub-TeV photons from these two bursts should be attributed to their large burst energies and low redshifts.
Review of recent genome‐wide association scans in lupus

We review the systemic lupus erythematosus (SLE) human genetics literature, including the first wave of genome‐wide associations scans (GWAS), to identify confirmed and candidate risk variants that meet stringent statistical criteria. The understanding of the genetic basis of SLE in humans has expanded dramatically over the past year, offering an early glimpse into the primary genetic factors and major dysregulated pathways. A meta‐analysis of published candidate variants was performed incorporating data from a 1310 case and 7859 control GWAS. Our review of the literature and meta‐analysis identifies a total of 17 well‐validated common SLE risk variants, including four candidate variants that achieve our definition of a confirmed SLE risk locus. These variants account for a fraction of the total genetic contribution to SLE risk, with many risk loci remaining to be identified, but may provide insight into the pathways involved in SLE. Initial pathway analyses of the 17 confirmed SLE risk alleles indicate an important role for B‐cell signalling and development, signaling through toll‐like receptors 7 and 9, and neutrophil function.
Theory and design of leaky-wave antennas on a curved surface

Leaky-wave antennas (LWAs) are usually planar in nature, being based on a guiding structure that is oriented along a fixed direction. The phase constant of the radiating leaky wave determines the beam angle, while the attenuation constant determines the beamwidth of the radiated beam. For a periodic LWA, radiation occurs from the n = -1 space harmonic, and the phase constant β-1 can be either positive or negative, resulting in radiation either in the forward direction or the backward direction. Creating a beam at broadside is usually difficult, since this corresponds to the “open stopband at broadside”. Special designs, such at the metamaterial-inspired CRLH LWA, must normally be used to allow for radiation at broadside.
Cathepsin A regulates chaperone‐mediated autophagy through cleavage of the lysosomal receptor

Protective protein/cathepsin A (PPCA) has a serine carboxypeptidase activity of unknown physiological function. We now demonstrate that this protease activity triggers the degradation of the lysosome‐associated membrane protein type 2a (lamp2a), a receptor for chaperone‐mediated autophagy (CMA). Degrada tion of lamp2a is important because its level in the lysosomal membrane is a rate‐limiting step of CMA. Cells defective in PPCA show reduced rates of lamp2a degradation, higher levels of lamp2a and higher rates of CMA. Restoration of PPCA protease activity increases rates of lamp2a degradation, reduces levels of lysosomal lamp2a and reduces rates of CMA. PPCA associates with lamp2a on the lysosomal membrane and cleaves lamp2a near the boundary between the luminal and transmembrane domains. In addition to the well‐studied role of PPCA in targeting and protecting two lysosomal glycosidases, we have defined a role for the proteolytic activity of this multifunctional protein.
Corporate Social Responsibility - In A Developing Country

Purpose: The main purpose is to investigate a multinational corporation subsidiary established in a developing country and their current as well as their future work concerning CSR. Method: To carry out our research, we performed a theoretical study as well as an empirical. Our empirical study consisted of a qualitative case study performed at the company stated above. We used semi-structured interviews, which were conducted with eight representatives from the selected company. Conclusions: Our findings indicate that in developing countries the legislative and social systems are not formulated to restrict undue businesses. Due to this, Corporate Social Responsibility work among global companies established in these countries is important. When constructing these programmes the process has to start from the bottom and the local situation cannot be foreseen. The top-down approach to CSR is a fundamental problem. There are virtually no pressures for social responsibility on corporations in these countries, instead these pressures comes from the individuals within the organisation and from headquarters. We believe that collective corporate social responsibility-programmes are easier to balance with generating profit compared to the individual responsibility. Since corporate social responsibility is not only important for corporations to implement, in order to be effective and contribute to sustainable development in developing countries global corporations need to share the responsibility externally.
World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Schizophrenia, Part 1: Acute treatment of schizophrenia

These guidelines for the biological treatment of schizophrenia were developed by an international Task Force of the World Federation of Societies of Biological Psychiatry (WFSBP). The goal during the development of these guidelines was to review systematically all available evidence pertaining to the treatment of schizophrenia, and to reach a consensus on a series of practice recommendations that are clinically and scientifically meaningful based on the available evidence. These guidelines are intended for use by all physicians seeing and treating people with schizophrenia. The data used for developing these guidelines have been extracted primarily from various national treatment guidelines and panels for schizophrenia, as well as from meta-analyses, reviews and randomised clinical trials on the efficacy of pharmacological and other biological treatment interventions identified by a search of the MEDLINE database and Cochrane Library. The identified literature was evaluated with respect to the strength of evidence for its efficacy and then categorised into four levels of evidence (A–D). This first part of the guidelines covers disease definition, classification, epidemiology and course of schizophrenia, as well as the management of the acute phase treatment. These guidelines are primarily concerned with the biological treatment (including antipsychotic medication, other pharmacological treatment options, electroconvulsive therapy, adjunctive and novel therapeutic strategies) of adults suffering from schizophrenia.
The Evolution of Industrial Districts Changing Governance, Innovation and Internationalisation of Local Capitalism in Italy

The structural evolution of industrial districts and adaptive competitive advantages -- I. Theoretical Perspectives -- Regional governance and economic development: A European perspective -- Italian industrial districts: Facts and theories -- Modelling the structure and evolution of industrial districts -- II. Firm Ownership and District Organisation -- Institutional innovations in industrial districts -- Groups of small and medium-sized firms in industrial districts in Italy -- Ownership linkages and business groups in industrial districts. The case of Emilia Romagna -- The role of medium-sized and large firms in the evolution of industrial districts. The case of Marche -- Entrepreneurship, labour organisation and labour mobility in industrial districts -- Integration and convergence in the internal dynamics of industrial districts. A case study -- III. Innovation -- Can a Marshallian industrial district be innovative? The case of Italy -- Are industrial districts more conducive to innovative production? The case of Emilia Romagna -- Environmental impact and innovation in industrial districts -- IV. Internationalisation -- Local engines of global trade: the case of Italian industrial districts -- Small multinational groups in the Italian industrial districts: interpretations and empirical evidence from the mechanical engineering industry.
Determining Length of Breastfeeding Exclusivity

Background: Infant feeding data are often collected retrospectively through maternal report. Validation studies show that maternal report of initiation and duration of any breastfeeding is accurate but that report of duration of exclusive breastfeeding may be less accurate. Objective: This study aimed to compare infant feeding data collected longitudinally throughout the first 6 months of life with maternal report of duration of exclusive breastfeeding collected 2 years postpartum. Methods: Infant feeding data were collected prospectively throughout the first 6 months of life from medical records and maternal report, including maternal 24-hour recall. At 2 years postpartum, we asked mothers of these same infants how long they exclusively breastfed their infants. Their responses were compared to the prospectively collected data. Simple and multiple linear regressions tested for any significant predictors of the difference between the prospectively collected data and maternal report at 2 years. Results: Of the 292 mothers included in the final analysis, only 88 (30.1%) mothers reported a duration of exclusive breastfeeding at 2 years postpartum that matched the prospectively collected data. Sixty-four women reported exclusively breastfeeding for the recommended 6 months (21.9%), but according to the prospectively collected data, only 2 women (0.7%) breastfed exclusively through 6 months. The median difference between the prospectively collected data and maternal report at 2 years was 1 month (IQR, 0-4). Conclusion: In this sample of mothers, report of exclusive breastfeeding practices 2 years after birth was often inaccurate and mothers tended to overestimate duration.
Insertion of the Tensor Veli Palatini Muscle into the Eustachian Tube Cartilage in Cleft Palate Cases

Differences in insertion of the tensor veli palatini muscle (TVPM) into the lateral lamina of the eustachian tube (ET) cartilage between cleft palate (CP) cases and controls were investigated histologically. Thirty temporal bones with entire ETs were studied: 10 from individuals with CP and 20 controls. The ratio of the length of the ET cartilage with insertion of the TVPM to its total length from the nasopharyngeal end to near the tubal isthmus was calculated in all 30 cases. In all 20 controls, but in only 6 of 10 CP cases, the TVPM inserted into the lateral lamina of the ET cartilage at its tip portion (χ2 test, p < .025). The ratio was significantly smaller in CP cases (0.178 ± 0.172) than in controls (0.419 ± 0.120) (t = 4.305, p < .001). We believe that abnormal insertion of the TVPM into the ET cartilage is one of the causes of the functional obstruction of the ET that contributes to the frequent bouts of otitis media experienced by those with cleft palate.
Magnetometers for space measurements over a wide range of field intensities

The exploration of the earth's magnetic field out to interplanetary regions has required magnetometers capable of measuring a wide range of field intensities. The past decade has witnessed considerable development of such instruments. Representative of these are the rubidium vapor magnetometer and fluxgates flown on OGO-5 by the Goddard Space Flight Center. For scalar measurements the rubidium vapor magnetometer, with a range of three gammas to fifty thousand gammas, has an error which reaches a maximum of 1.5 gamma at fifty thousand gammas. Present development is directed towards reducing the electronic phase shifts and the experiment weight. For vector measurements, the fluxgate system covers a range ± 4,000 gammas in each of three components with an error of of 0.1 % at the top of the range, and a resolution of ± 1/8 gamma. A fluxgate system is being developed to achieve an accuracy of . 01 % up to 60,000 gammas. The current source which has been developed for this system has an accuracy of better than ± . 005 % over a temperature range of ± 25°.