Miracle-dz/UniFAR-FTUs huggingface dataset:
A simple method for domain adaptation of sentence embeddings

Pre-trained sentence embeddings have been shown to be very useful for a variety of NLP tasks. Due to the fact that training such embeddings requires a large amount of data, they are commonly trained on a variety of text data. An adaptation to specific domains could improve results in many cases, but such a finetuning is usually problem-dependent and poses the risk of over-adapting to the data used for adaptation. In this paper, we present a simple universal method for finetuning Google's Universal Sentence Encoder (USE) using a Siamese architecture. We demonstrate how to use this approach for a variety of data sets and present results on different data sets representing similar problems. The approach is also compared to traditional finetuning on these data sets. As a further advantage, the approach can be used for combining data sets with different annotations. We also present an embedding finetuned on all data sets in parallel.
Have coral snake mimics diversified more than non-mimics?

Dipsadidae is the most diversified family of snakes, composed of species showing an impressive variety of color patterns. Some species are cryptic whereas others have contrasting patterns comprised by bright colors alternated with darker shades, including particular combinations of vivid colors characteristic of coral snakes (Elapidae). Species with such patterns are thought to be mimics of coral snakes based on their color pattern similarity, predator avoidance of such patterns in field experiments, and the geographical concordance between models and mimics. Here we test whether color patterns associated with coral snake mimicry and contrasting color patterns in general influenced the diversification dynamics of the group. We compile the largest database of color patterns among reptiles to date, with color descriptions for the majority (594 species) of dipsadids. We used trait-dependent diversification models along with extensive simulations to deal with the recently described statistical bias associated with such methods. Despite the apparent survival advantage associated with coral snake mimicry, we show that there is no detectable influence of color types in the dynamics of diversification in Dipsadidae. We discuss insights into the function of color patterns and argue that non-mimic contrasting patterns might serve as pre-adaptations to mimicry of coral snakes. Data archival location BEAST XML file and BiSSE MCMC results: http://dx.doi. org/10.6084/m9.figshare. 831493 R code for analyses and simulations: https://github.com/Caetanods/Dipsadidae_color_evolution
Differentiating a Tensor Language

How does one compile derivatives of tensor programs, such that the resulting code is purely functional (hence easier to optimize and parallelize) and provably efficient relative to the original program? We show that naively differentiating tensor code---as done in popular systems like Tensorflow and PyTorch---can cause asymptotic slowdowns in pathological cases, violating the Cheap Gradients Principle. However, all existing automatic differentiation methods that guarantee this principle (for variable size data) do so by relying on += mutation through aliases/pointers---which complicates downstream optimization. We provide the first purely functional, provably efficient, adjoint/reverse-mode derivatives of array/tensor code by explicitly accounting for sparsity. We do this by focusing on the indicator function from Iverson's APL. We also introduce a new "Tensor SSA" normal form and a new derivation of reverse-mode automatic differentiation based on the universal property of inner-products.
Cosmology with Rayleigh scattering of the cosmic microwave background

The cosmic microwave background (CMB) has been a treasure trove for cosmology. Over the next decade, current and planned CMB experiments are expected to exhaust nearly all primary CMB information. To further constrain cosmological models, there is a great benefit to measuring signals beyond the primary modes. Rayleigh scattering of the CMB is one source of additional cosmological information. It is caused by the additional scattering of CMB photons by neutral species formed during recombination and exhibits a strong and unique frequency scaling (∝ ν4). We will show that with sufficient sensitivity across frequency channels, the Rayleigh scattering signal should not only be detectable but can significantly improve constraining power for cosmological parameters, with limited or no additional modifications to planned experiments. We will provide heuristic explanations for why certain cosmological parameters benefit from measurement of the Rayleigh scattering signal, and confirm these intuitions using the Fisher formalism. In particular, observation of Rayleigh scattering allows significant improvements on measurements of Neff and ∑ mν.
Classifying minimal vanishing sums of roots of unity.

A vanishing sum of roots of unity is called minimal if no proper, nonempty sub-sum of it vanishes. This paper classifies all minimal vanishing sums of roots of unity of weight at most 16 by hand and then develops and codes an algorithm to extend the classification further, up to weight no greater than 21.
VLTI/PIONIER reveals the close environment of the evolved system HD 101584

Context: The observed orbital characteristics of post-asymptotic giant branch (post-AGB) and post-red giant branch (post-RGB) binaries are not understood. We suspect that the missing ingredients to explain them probably lie in the continuous interaction of the central binary with its circumstellar environment. Aims: We aim at studying the circumbinary material in these complex systems by investigating the connection between the innermost and large-scale structures. Methods: We perform high-angular resolution observations in the near-infrared continuum of HD101584, which has a complex structure as seen at millimeter wavelengths with a disk-like morphology and a bipolar outflow due to an episode of strong binary interaction. To account for the complexity of the target we first perform an image reconstruction and use this result to fit a geometrical model to extract the morphological and thermal features of the environment. Results: The image reveals an unexpected double-ring structure. We interpret the inner ring to be produced by emission from dust located in the plane of the disk and the outer ring to be produced by emission from dust that is located 1.6[D/1kpc] au above the disk plane. The inner ring diameter (3.94[D/1kpc] au), and temperature (T=1540$\pm$10K) are compatible with the dust sublimation front of the disk. The origin of the out-of-plane ring (with a diameter of 7.39[D/1kpc] au and a temperature of 1014$\pm10$K) could be due to episodic ejection or a dust condensation front in the outflow. Conclusion: The observed outer ring is possibly linked with the blue-shifted side of the large scale outflow seen by ALMA and is tracing its launching location to the central star. Such observations give morphological constraints on the ejection mechanism. Additional observations are needed to constrain the origin of the out-of-plane structure.
Popularity and Centrality in Spotify Networks: Critical transitions in eigenvector centrality

The modern age of digital music access has increased the availability of data about music consumption and creation, facilitating the large-scale analysis of the complex networks that connect musical works and artists. Data about user streaming behaviour and the musical collaboration networks are particularly important with new data-driven recommendation systems. Here, we present a new collaboration network of artists from the online music streaming service Spotify and demonstrate a critical change in the eigenvector centrality of artists, as low popularity artists are removed. This critical change in centrality, from a central core of classical artists to a core of rap artists, demonstrates deeper structural properties of the network. Both the popularity and degree of collaborators play an important role in the centrality of these groups. Rap artists have dense collaborations with other popular artists whereas classical artists are diversely connected to a large number of low and medium popularity artists throughout the graph through renditions and compilations. A Social Group Centrality model is presented to simulate this critical transition behaviour, and switching between dominant eigenvectors is observed. By contrasting a group of high-degree diversely connected community leaders to a group of celebrities which only connect to high popularity nodes, this model presents a novel investigation into the effect of popularity bias on how centrality and importance are measured.
Inno at SemEval-2020 Task 11: Leveraging Pure Transfomer for Multi-Class Propaganda Detection

The paper presents the solution of team ”Inno” to a SEMEVAL 2020 task 11 ”Detection of propaganda techniques in news articles”. The goal of the second subtask is to classify textual segments that correspond to one of the 18 given propaganda techniques in news articles dataset. We tested a pure Transformer-based model with an optimized learning scheme on the ability to distinguish propaganda techniques between each other. Our model showed 0:6 and 0:58 overall F1 score on validation set and test set accordingly and non-zero F1 score on each class on both sets.
Cross-Spectral Periocular Recognition with Conditional Adversarial Networks

This work addresses the challenge of comparing periocular images captured in different spectra, which is known to produce significant drops in performance in comparison to operating in the same spectrum. We propose the use of Conditional Generative Adversarial Networks, trained to convert periocular images between visible and near-infrared spectra, so that biometric verification is carried out in the same spectrum. The proposed setup allows the use of existing feature methods typically optimized to operate in a single spectrum. Recognition experiments are done using a number of off-the-shelf periocular comparators based both on hand-crafted features and CNN descriptors. Using the Hong Kong Polytechnic University Cross-Spectral Iris Images Database (PolyU) as benchmark dataset, our experiments show that cross-spectral performance is substantially improved if both images are converted to the same spectrum, in comparison to matching features extracted from images in different spectra. In addition to this, we fine-tune a CNN based on the ResNet50 architecture, obtaining a cross-spectral periocular performance of EER=l%, and GAR>99% @ FAR=l%, which is comparable to the state-of-the-art with the PolyU database.
Comparison of Centralized and Decentralized Approaches in Cooperative Coverage Problems with Energy-Constrained Agents

A multi-agent coverage problem is considered with energy-constrained agents. The objective of this paper is to compare the coverage performance between centralized and decentralized approaches. To this end, a near-optimal centralized coverage control method is developed under energy depletion and repletion constraints. The optimal coverage formation corresponds to the locations of agents where the coverage performance is maximized. The optimal charging formation corresponds to the locations of agents with one agent fixed at the charging station and the remaining agents maximizing the coverage performance. We control the behavior of this cooperative multi-agent system by switching between the optimal coverage formation and the optimal charging formation. Finally, the optimal dwell times at coverage locations, charging time, and agent trajectories are determined so as to maximize coverage over a given time interval. In particular, our controller guarantees that at any time there is at most one agent leaving the team for energy repletion.
Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology

Unsupervised learning enables modeling complex images without the need for annotations. The representation learned by such models can facilitate any subsequent analysis of large image datasets. However, some generative factors that cause irrelevant variations in images can potentially get entangled in such a learned representation causing the risk of negatively affecting any subsequent use. The orientation of imaged objects, for instance, is often arbitrary/irrelevant, thus it can be desired to learn a representation in which the orientation information is disentangled from all other factors. Here, we propose to extend the Variational Auto-Encoder framework by leveraging the group structure of rotation-equivariant convolutional networks to learn orientation-wise disentangled generative factors of histopathology images. This way, we enforce a novel partitioning of the latent space, such that oriented and isotropic components get separated. We evaluated this structured representation on a dataset that consists of tissue regions for which nuclear pleomorphism and mitotic activity was assessed by expert pathologists. We show that the trained models efficiently disentangle the inherent orientation information of single-cell images. In comparison to classical approaches, the resulting aggregated representation of sub-populations of cells produces higher performances in subsequent tasks.
A Multitask Deep Learning Approach for User Depression Detection on Sina Weibo

In recent years, due to the mental burden of depression, the number of people who endanger their lives has been increasing rapidly. The online social network (OSN) provides researchers with another perspective for detecting individuals suffering from depression. However, existing studies of depression detection based on machine learning still leave relatively low classification performance, suggesting that there is significant improvement potential for improvement in their feature engineering. In this paper, we manually build a large dataset on Sina Weibo (a leading OSN with the largest number of active users in the Chinese community), namely Weibo User Depression Detection Dataset (WU3D). It includes more than 20,000 normal users and more than 10,000 depressed users, both of which are manually labeled and rechecked by professionals. By analyzing the user's text, social behavior, and posted pictures, ten statistical features are concluded and proposed. In the meantime, text-based word features are extracted using the popular pretrained model XLNet. Moreover, a novel deep neural network classification model, i.e. FusionNet (FN), is proposed and simultaneously trained with the above-extracted features, which are seen as multiple classification tasks. The experimental results show that FusionNet achieves the highest F1-Score of 0.9772 on the test dataset. Compared to existing studies, our proposed method has better classification performance and robustness for unbalanced training samples. Our work also provides a new way to detect depression on other OSN platforms.
Determinantal Point Process as an alternative to NMS

We present a determinantal point process (DPP) inspired alternative to non-maximum suppression (NMS) which has become an integral step in all state-of-the-art object detection frameworks. DPPs have been shown to encourage diversity in subset selection problems. We pose NMS as a subset selection problem and posit that directly incorporating DPP like framework can improve the overall performance of the object detection system. We propose an optimization problem which takes the same inputs as NMS, but introduces a novel sub-modularity based diverse subset selection functional. Our results strongly indicate that the modifications proposed in this paper can provide consistent improvements to state-of-the-art object detection pipelines.
Private Speech 1 Running head: PRIVATE SPEECH Private Speech on an Executive Task: Relations with Task Difficulty and Task Performance

Measures of private speech and task performance were obtained for a sample of 46 5and 6-year-olds engaged on a mechanical version of the Tower of London (ToL) task. Two different sets of 4 puzzles of increasing difficulty were attempted on 2 occasions. In line with Vygotskian predictions, there was a quadratic relation between private speech and task difficulty, but no evidence of a shift towards self-regulatory sub-types of private speech with increasing task difficulty. Levels of self-regulatory private speech were significantly related to concurrent, but not subsequent, task performance. We discuss the significance of these findings for the Vygotskian view that private speech has an adaptive function in the self-regulation of behaviour.
Good Seeds Bear Good Fruit: Using Benefit-to-Cost Ratios in Multiobjective Spatial Optimization under Epistasis

ABSTRACT:Many biophysical models exhibit epistasis (interdependence), where a conservation action impacts the effectiveness of another elsewhere. At the same time, ranking conservation actions according to the independent benefit-to-cost ratios is cost-efficient when epistasis is absent. We use benefit-to-cost rankings as starting points for an evolutionary algorithm employing an epistatic biophysical model. We model a variety of conservation actions to assess trade-offs for sediment reduction and wildlife conservation in the study watershed. We find that despite the presence of epistasis, the weighted benefit-to-cost ratio-derived solutions perform remarkably well in the decision space, but effects in objective space need the model evaluation. (JEL Q25, Q52)
Variants Promotes Dendritic Cell Than Killer Activity by Natural Epitope Selective Induction of CTL Helper Rather

The ability of HIV-1 to rapidly accumulate mutations provides the virus with an effective means of escaping CD8 + CTL responses. In this study, we describe how subtle alterations in CTL epitopes expressed by naturally occurring HIV-1 variants can result in an incomplete escape from CTL recognition, providing the virus with a selective advantage. Rather than paralyzing the CTL response, these epitope modiﬁcations selectively induce the CTL to produce proinﬂammatory cytokines in the absence of target killing. Importantly, instead of dampening the immune response through CTL elimination of variant Ag-expressing immature dendritic cells (DC), a positive CTL-to-DC immune feedback loop dominates whereby the immature DC differentiate into mature proinﬂammatory DC. Moreover, these CTL-programmed DC exhibit a superior capacity to mediate HIV-1 trans -infection of T cells. This discordant induction of CTL helper activity in the absence of killing most likely contributes to the chronic immune activation associated with HIV-1 infection, and can be used by HIV-1 to promote viral dissemination and persistence. Our ﬁndings highlight the need to address the detrimental potential of eliciting dysfunctional cross-reactive memory CTL responses when designing and implementing anti–HIV-1 immunotherapies. The Journal of Immunology , 2013, 191: 000–000.
Anxiety sensitivity, panic, and depressed mood: A reanalysis teasing apart the contributions of the two levels in the hierarchical structure of the anxiety sensitivity index

Anxiety sensitivity (AS) has been defined as the fear of anxiety and anxiety-related sensations, and evidence suggests that AS plays an important role in the psychopathology of panic. It is entirely unclear whether the relation between AS and panic should be attributed to one (or more) of the AS group factors, the general AS factor, or to factors at both levels of the AS hierarchy. The authors reanalyzed data presented earlier by R. M. Rapee, T. A. Brown, M. A. Antony, and D. H. Barlow (1992) to tease apart the contributions of the different levels of the AS hierarchy to fear responses to hyperventilation and 5.5% carbon dioxide challenges. The results demonstrated that AS-Physical Concerns is the only one of the three AS group factors that contributes to relations with fear responses to these two challenges. However, AS-Mental Incapacitation Concerns had a stronger positive linear association with depressed mood than did AS-Physical Concerns.
Neoproterozoic (Torridonian) alluvial fan succession, northwest Scotland, and its tectonic setting and provenance

The presence of alluvial fan deposits in the lower Neoproterozoic Torridon Group in northwest Scotland illuminates Torridonian basin development at the eastern Laurentian margin. The 450 m thick Cape Wrath Member of the Applecross Formation consists of alluvial fan conglomerate and arkose succeeded by more distal, braidplain feldspathic sandstone. Palaeocurrent data comprising >2650 measurements on trough cross-bedding are of low variability and show overall eastward flow. The projection upcurrent of regionally divergent flow directions for the lower part of the member indicates a fan of c. 50 km radius with its apex 30 km to the west near a basement (pre-Caledonian) normal fault with downthrow to the east beneath the north Minch Basin. Extensional tectonics controlled deposition of the Applecross Formation. Regional uplift, causing erosion of a youthful topography on the Lewisian Gneiss, was followed by the development of the Applecross extensional basin in two main stages. Uplift of a western source area by movement on basin-bounding normal faults occurred first in the north and caused pediplanation and alluvial fan deposition in the Cape Wrath area, with subsequent uplift of the source area for the main body of the Applecross Formation occurring further to the west and south along the line of the Minch Fault. The bulk of the Applecross Formation was derived from a weathered terrain of felsic crystalline and related supracrustal rocks reaching from the Outer Hebrides region westward for up to c. 250 km onto what are now the continental margins of the North Atlantic. The tectonic events may mark an early phase in the crustal extension that led ultimately to the opening of the Iapetus ocean.
Cyclin-Dependent Kinase 1 (CDK1) is Co-Expressed with CDCA5: Their Functions in Gastric Cancer Cell Line MGC-803

Background Gastric cancer (GC) is a worldwide malignancy and the molecular mechanism of the GC carcinogenesis has not been fully elucidated. Our previous study suggested CDCA5 played a role in GC development via regulating cell proliferation, migration, and apoptosis in GC cells. Material/Methods Here, we first carried out bioinformatics analysis and found cyclin-dependent kinase 1 (CDK1) was possibly associated with CDCA5 using STRING. Then, the expression levels of CDK1 and CDCA5 in cancer tissues were estimated through Oncomine and The Cancer Genome Atlas (TCGA) database. After that, functional experiments were exerted to detect the association of CDK1 and CDCA5. Finally, cell proliferation assay, colon formation assay, cell scratch assay, transwell migration and invasion assays were applied to explore the roles of CDK1 and CDCA5 in GC cells MGC-803. Results CDK1 and CDCA5 were both upregulated and co-expressed in GC tissues. The expression of CDK1 and CDCA5 in MGC-803 was positively related. CDK1 or CDCA5 inhibition can suppress the proliferation, colon formation, migration, and invasion abilities of GC cells. Conclusions Co-expression of CDK1 and CDCA5 might confer cell proliferation, migration, and invasion abilities in GC cells, and this can provide some clues for further therapies of gastric tumors.