Miracle-dz/UniFAR-FTUs huggingface dataset:
Merge-Generability as the Key Concept of Human Language: Evidence From Neuroscience

Ever since the inception of generative linguistics, various dependency patterns have been widely discussed in the literature, particularly as they pertain to the hierarchy based on “weak generation” – the so-called Chomsky Hierarchy. However, humans can make any possible dependency patterns by using artificial means on a sequence of symbols (e.g., computer programing). The differences between sentences in human language and general symbol sequences have been routinely observed, but the question as to why such differences exist has barely been raised. Here, we address this problem and propose a theoretical explanation in terms of a new concept of “Merge-generability,” that is, whether the structural basis for a given dependency is provided by the fundamental operation Merge. In our functional magnetic resonance imaging (fMRI) study, we tested the judgments of noun phrase (NP)-predicate (Pred) pairings in sentences of Japanese, an SOV language that allows natural, unbounded nesting configurations. We further introduced two pseudo-adverbs, which artificially force dependencies that do not conform to structures generated by Merge, i.e., non-Merge-generable; these adverbs enable us to manipulate Merge-generability (Natural or Artificial). By employing this novel paradigm, we obtained the following results. Firstly, the behavioral data clearly showed that an NP-Pred matching task became more demanding under the Artificial conditions than under the Natural conditions, reflecting cognitive loads that could be covaried with the increased number of words. Secondly, localized activation in the left frontal cortex, as well as in the left middle temporal gyrus and angular gyrus, was observed for the [Natural – Artificial] contrast, indicating specialization of these left regions in syntactic processing. Any activation due to task difficulty was completely excluded from activations in these regions, because the Natural conditions were always easier than the Artificial ones. And finally, the [Artificial – Natural] contrast resulted in the dorsal portion of the left frontal cortex, together with wide-spread regions required for general cognitive demands. These results indicate that Merge-generable sentences are processed in these specific regions in contrast to non-Merge-generable sentences, demonstrating that Merge is indeed a fundamental operation, which comes into play especially under the Natural conditions.
Neoantigen Fitness Model Predicts Lower Immune Recognition of Cutaneous Squamous Cell Carcinomas Than Actinic Keratoses

A low percentage of actinic keratoses progress to develop into cutaneous squamous cell carcinoma. The immune mechanisms that successfully control or eliminate the majority of actinic keratoses and the mechanisms of immune escape by invasive squamous cell carcinoma are not well-understood. Here, we took a systematic approach to evaluate the neoantigens present in actinic keratosis and cutaneous squamous cell carcinoma specimens. We compared the number of mutations, the number of neoantigens predicted to bind MHC class I, and the number of neoantigens that are predicted to bind MHC class I and be recognized by a T cell receptor in actinic keratoses and cutaneous squamous cell carcinomas. We also considered the relative binding strengths to both MHC class I and the T cell receptor in a fitness cost model that allows for a comparison of the immune recognition potential of the neoantigens in actinic keratosis and cutaneous squamous cell carcinoma samples. The fitness cost was subsequently adjusted by the expression rates of the neoantigens to examine the role of neoantigen expression in tumor immune evasion. Our analyses indicate that, while the number of mutations and neoantigens are not significantly different between actinic keratoses and cutaneous squamous cell carcinomas, the predicted immune recognition of the neoantigen with the highest expression-adjusted fitness cost is lower for cutaneous squamous cell carcinomas compared with actinic keratoses. These findings suggest a role for the down-regulation of expression of highly immunogenic neoantigens in the immune escape of cutaneous squamous cell carcinomas. Furthermore, these findings highlight the importance of incorporating additional factors, such as the quality and expression of the neoantigens, rather than focusing solely on tumor mutational burden, in assessing immune recognition potential.
Facebook Usage and Life Satisfaction

Social networking sites (SNS), such as Facebook, attract millions of users worldwide by offering highly interactive social communications. Although this has many advantages, previous research has suggested there are also drawbacks (e.g., stalking, addiction, invasion of privacy). The question, therefore, arises as to whether Facebook – currently the largest social network – makes us more satisfied with our lives. In two independent samples (Study 1: N = 2,272; Study 2: N = 1,459), Facebook users were neither more satisfied with their lives compared to non-Facebook users, nor were Facebook users with more online friends more satisfied compared to those with fewer online friends. On the contrary, Facebook usage duration was negatively associated with life satisfaction, even after controlling for age and sex differences (Study 1: r = −0.11, Study 2: r = −0.18). Although in general positive effects would have been expected because Facebook should enhance possibilities for social communication and connection, either null-finding or negative associations were found. Results are discussed in light of possible addiction-supporting features of Facebook, which are reflected in Facebook usage patterns (e.g., higher mean duration of Facebook usage per week, larger number of logins to Facebook).
D-PAttNet: Dynamic Patch-Attentive Deep Network for Action Unit Detection

Facial action units (AUs) relate to specific local facial regions. Recent efforts in automated AU detection have focused on learning the facial patch representations to detect specific AUs. These efforts have encountered three hurdles. First, they implicitly assume that facial patches are robust to head rotation; yet non-frontal rotation is common. Second, mappings between AUs and patches are defined a priori, which ignores co-occurrences among AUs. And third, the dynamics of AUs are either ignored or modeled sequentially rather than simultaneously as in human perception. Inspired by recent advances in human perception, we propose a dynamic patch-attentive deep network, called D-PAttNet, for AU detection that (i) controls for 3D head and face rotation, (ii) learns mappings of patches to AUs, and (iii) models spatiotemporal dynamics. D-PAttNet approach significantly improves upon existing state of the art.
Continuous Inking Affects the Biological and Biochemical Responses of Cuttlefish Sepia pharaonis

Several marine mollusks, including cephalopods (cuttlefish, squid, and octopus) and gastropods (e.g., sea hares), can release a colored ink secretion when chased by predators or stimulated. Ink release is part of a defensive response, but the threshold for the biochemical responses caused by stimulation is unknown. The present study aimed to reveal antipredator responses of cuttlefish, such as escaping via inking and/or jetting, and to investigate its biological and biochemical responses to continuous ink release. Results showed that the behavioral responses to continuous ink release mainly manifested as blazing body pattern changes. Cuttlefish escaped from predators covered by jetting/inking and warned the potential threats by displaying a unique body pattern. Moreover, persistent inking in the presence of an overt stimulus caused uncontrollable ink release from the ink duct/anal canal (loss of control). This study first verified the characteristics of the cuttlefish ink solution, prepared a standard curve of ink solution concentrations, and fitted the relationship function between the release frequency and the released ink weight. Biological statistics indicated that cuttlefish has the ability to continuously release ink (releasing ∼90% of the ink from the ink sac) and that the individuals adapted well during the recovery period. However, re-releasing ink would result in “overexploitation” and high mortality. Hexokinase (HK), pyruvate kinase (PK), and superoxide dismutase (SOD) activities, as well as malondialdehyde (MDA) concentration increased or remained stable in different tissues after releasing ink. The expression of heat shock protein 90 and arginine kinase (AK) were upregulated by stimuli in all tissues. Biochemical changes indicated that continuous inking not only consumed considerable energy but also damaged the tissues. In summary, cuttlefish released almost 90% of their ink for active defense against predators, and it took ∼30 days for the ink sac to be refilled, but “overexploitation” resulted in serious physiological damage. These findings will be helpful to further study the defense and ink release mechanisms and to consider animal health and welfare when using cephalopods as experimental animals and for aquaculture practices.
Strong Seasonality in Arctic Estuarine Microbial Food Webs

Microbial communities in the coastal Arctic Ocean experience extreme variability in organic matter and inorganic nutrients driven by seasonal shifts in sea ice extent and freshwater inputs. Lagoons border more than half of the Beaufort Sea coast and provide important habitats for migratory fish and seabirds; yet, little is known about the planktonic food webs supporting these higher trophic levels. To investigate seasonal changes in bacterial and protistan planktonic communities, amplicon sequences of 16S and 18S rRNA genes were generated from samples collected during periods of ice-cover (April), ice break-up (June), and open water (August) from shallow lagoons along the eastern Alaska Beaufort Sea coast from 2011 through 2013. Protist communities shifted from heterotrophic to photosynthetic taxa (mainly diatoms) during the winter–spring transition, and then back to a heterotroph-dominated summer community that included dinoflagellates and mixotrophic picophytoplankton such as Micromonas and Bathycoccus. Planktonic parasites belonging to Syndiniales were abundant under ice in winter at a time when allochthonous carbon inputs were low. Bacterial communities shifted from coastal marine taxa (Oceanospirillaceae, Alteromonadales) to estuarine taxa (Polaromonas, Bacteroidetes) during the winter-spring transition, and then to oligotrophic marine taxa (SAR86, SAR92) in summer. Chemolithoautotrophic taxa were abundant under ice, including iron-oxidizing Zetaproteobacteria. These results suggest that wintertime Arctic bacterial communities capitalize on the unique biogeochemical gradients that develop below ice near shore, potentially using chemoautotrophic metabolisms at a time when carbon inputs to the system are low. Co-occurrence networks constructed for each season showed that under-ice networks were dominated by relationships between parasitic protists and other microbial taxa, while spring networks were by far the largest and dominated by bacteria-bacteria co-occurrences. Summer networks were the smallest and least connected, suggesting a more detritus-based food web less reliant on interactions among microbial taxa. Eukaryotic and bacterial community compositions were significantly related to trends in concentrations of stable isotopes of particulate organic carbon and nitrogen, among other physiochemical variables such as dissolved oxygen, salinity, and temperature. This suggests the importance of sea ice cover and terrestrial carbon subsidies in contributing to seasonal trends in microbial communities in the coastal Beaufort Sea.
Energy-Conserving Enzyme Systems Active During Syntrophic Acetate Oxidation in the Thermophilic Bacterium Thermacetogenium phaeum

The thermophilic acetogen Thermacetogenium phaeum uses the Wood-Ljungdahl pathway (WLP) in both directions, either for the production of acetate from various compounds or for the oxidation of acetate in syntrophic cooperation with methanogens. In this study, energy–conserving enzyme systems in T. phaeum were investigated in both metabolic directions. A gene cluster containing a membrane-bound periplasmically oriented formate dehydrogenase directly adjacent to putative menaquinone synthesis genes was identified in the genome. The protein products of these genes were identified by total proteome analysis, and menaquinone MK-7 had been found earlier as the dominant quinone in the membrane. Enzyme assays with membrane preparations and anthraquinone-2,6-disulfonate as electron acceptor verified the presence of a quinone-dependent formate dehydrogenase. A quinone-dependent methylene–THF reductase is active in the soluble fraction and in the membrane fraction. From these results we conclude a reversed electron transport system from methyl-THF oxidation to CO2 reduction yielding formate as reduced product which is transferred to the methanogenic partner. The redox potential difference between methyl-THF (Eo’ = −200 mV) and formate (Eo’ = −432 mV) does not allow electron transfer through syntrophic formate removal alone. We postulate that part of the ATP conserved by substrate-level phosphorylation has to be invested into the generation of a transmembrane proton gradient by ATPase. This proton gradient could drive the endergonic oxidation of methyl-THF in an enzyme reaction similar to the membrane-bound reversed electron transport system previously observed in the syntrophically butyrate-oxidizing bacterium Syntrophomonas wolfei. To balance the overall ATP budget in acetate oxidation, we postulate that acetate is activated through an ATP-independent path via aldehyde:ferredoxin oxidoreductase (AOR) and subsequent oxidation of acetaldehyde to acetyl-CoA.
Overexpression of SlOFP20 in Tomato Affects Plant Growth, Chlorophyll Accumulation, and Leaf Senescence

Previous studies have shown that OVATE family proteins (OFPs) participate in various aspects of plant growth and development. How OFPs affect leaf chlorophyll accumulation and leaf senescence has not been reported yet. Here, we found that overexpression of SlOFP20 in tomato not only impacted plant architecture but also enhanced the leaf chlorophyll accumulation and retarded leaf senescence. Gene expression analysis of SlGLK1, SlGLK2, and HY5, encoding transcription factors that are putatively involved in chloroplast development and chlorophyll levels, were significantly up-regulated in SlOFP20-OE lines. Both chlorophyll biosynthesis and degradation genes were distinctly regulated in transgenic plants. Moreover, SlOFP20-OE plants accumulated more starch and soluble sugar than wild-type plants, indicating that an increased chlorophyll content conferred some higher photosynthetic performance in SlOFP20-OE plants. Furthermore, The levels of leaf senescence-related indexes, such as hydrogen peroxide, malondialdehyde, and antioxidant enzymes activities, were differently altered, too. SlOFP20 overexpression repressed the expression of senescence-related genes, SAG12, RAV1, and WRKY53. Moreover, abscisic acid and ethylene synthesis genes were down-regulated in transgenic lines. These results provide new insights into how SlOFP20 regulates chlorophyll accumulation and leaf senescence.
Neuroligin 3 Regulates Dendritic Outgrowth by Modulating Akt/mTOR Signaling

Neuroligins (NLs) are a group of postsynaptic cell adhesion molecules that function in synaptogenesis and synaptic transmission. Genetic defects in neuroligin 3 (NL3), a member of the NL protein family, are associated with autism. Studies in rodents have revealed that mutations of NL3 gene lead to increased growth and complexity in dendrites in the central nervous system. However, the detailed mechanism is still unclear. In our study, we found that deficiency of NL3 led to morphological changes of the pyramidal neurons in layer II/III somatosensory cortex in mice, including enlarged somata, elongated dendritic length, and increased dendritic complexity. Knockdown of NL3 in cultured rat neurons upregulated Akt/mTOR signaling, resulting in both increased protein synthesis and dendritic growth. Treating neurons with either rapamycin to inhibit the mTOR or LY294002 to inhibit the PI3K/Akt activity rescued the morphological abnormalities resulting from either NL3 knockdown or knockout (KO). In addition, we found that the hyperactivated Akt/mTOR signaling associated with NL3 defects was mediated by a reduction in phosphatase and tensin (PTEN) expression, and that MAGI-2, a scaffold protein, interacted with both NL3 and PTEN and could be a linker between NL3 and Akt/mTOR signaling pathway. In conclusion, our results suggest that NL3 regulates neuronal morphology, especially dendritic outgrowth, by modulating the PTEN/Akt/mTOR signaling pathway, probably via MAGI-2. Thereby, this study provides a new link between NL3 and neuronal morphology.
Quality of Life and Depressive Symptoms in the Elderly Living in Community

Introduction: the elderly are affected by some chronic diseases that require comprehensive and continuous health care, among them depression, with disabling potential, compromising their quality of life. Objective: discovering the quality of life of seniors residing in community and their relationship with the symptoms of depression. Method: a quantitative study, observational, cross-sectional, whose sample included 110 elderly with preserved cognitive conditions and who agreed to participate voluntarily. Data collection was conducted from October to December 2013. Statistical analysis was performed using the software Statiscal Package for Social Sciences (SPSS), version 20. Results: the quality of life assessed by the WHOQOL-BREF obtained the highest score in the field of social relations (73.93) and lowest score in the environmental field (61.27). The WHOQOL-OLD showed a higher score in sensory abilities facet (76.19) and lowest score on the facet autonomy (61.47). The correlation of quality of life with depressive symptoms presented the psychological domain and facet social participation with strong and negative association. Conclusion: the development of longitudinal studies becomes feasible for a better understanding of the phenomenon studied.
Large-vocabulary Chord Transcription Via Chord Structure Decomposition

While audio chord recognition systems have acquired considerable accuracy on small vocabularies (e.g., major/minor chords), the large-vocabulary chord recognition problem still remains unsolved. This problem hinders the practical usages of audio recognition systems. The difﬁ-culty mainly lies in the intrinsic long-tail distribution of chord qualities, and most chord qualities have too few samples for model training. In this paper, we propose a new model for audio chord recognition under a huge chord vocabulary. The core concept is to decompose any chord label into a set of musically meaningful components (e.g., triad, bass, seventh), each with a much smaller vocabulary compared to the size of the overall chord vocabulary. A multitask classiﬁer is then trained to recognize all the components given the audio feature, and then labels of individual components are re-assembled to form the ﬁnal chord label. Experiments show that the proposed system not only achieves state-of-the-art results on traditional evaluation metrics but also performs well on a large vocabulary.
FraunhoferSIT at GermEval 2019: Can Machines Distinguish Between Offensive Language and Hate Speech? Towards a Fine-Grained Classification

In this paper, we describe the Fraunhofer-SIT submission for the “GermEval 2019 – Shared Task on the Identiﬁcation of Of-fensive Language” . We participated in two subtasks: task 1 is a binary classiﬁcation of German tweets on the identiﬁcation of offensive language. Task 2 is a ﬁne-grained classiﬁcation to distinguish between three subcategories of offensive language. Our best model is an SVM classiﬁer based on tf-idf character n-gram features. Our submitted runs in the shared task are: Fraunhofer-SIT coarse [1-3]. txt for task 1 and Fraun-hoferSIT ﬁne [1-3]. txt for task 2. Our ﬁ-nal system reaches 0.70 macro-average F 1 - score for the binary classiﬁcation and 0.46 F 1 -score for the ﬁne-grained classiﬁcation. The achieved results show that the problem of automatically distinguishing between of-fensive language and “Hate Speech” is far from being solved.
Les modèles de mélange, un outil utile pour la classification semi-supervisée

In supervised classiﬁcation, the classiﬁcation rule is learnt from a learning sample generally composed of labeled data. In most settings obtaining the label is more expensive than obtaining covariates linked with the label, hence the interest to learn a prediction rule of the label given these covariates. So, in many settings a lot of unlabeled data, obtained at a relatively low cost, are available in addition to labeled data. Over past years the semi-supervised classiﬁcation, which uses unlabeled data in order to improve the classiﬁcation rule accuracy, has known a great development, especially in Machine Learning community. Generative models, which model the joint distribution of the label and of the covariates, allow to naturally take into account information contained in unlabeled data when learning the parameters of the model. In this article we give a survey of semi-supervised classiﬁcation and we detail how to use it with generative models.
Controlling Symbolic Music Generation based on Concept Learning from Domain Knowledge

Machine learning allows automatic construction of generative models for music. However, they are learned from only the succession of notes itself without explicitly employing domain knowledge of musical concepts such as rhythm, contour, and fragmentation & consolidation. We approximate such musical domain knowledge as a function, and feed it into our model. Then, two decoupled spaces are learned: the extraction space that captures the target concept, and the residual space that captures the remainder. For monophonic symbolic music, our model exhibits high decoupling/modeling performance. Control-lability in generation is improved: (i) our interpolation enables concept-aware ﬂexible control over blending two musical fragments, and (ii) our variation generation enables users to make concept-aware adjustable variations.
Investigating CNN-based Instrument Family Recognition for Western Classical Music Recordings

Western classical music comprises a rich repertoire composed for different ensembles. Often, these ensembles consist of instruments from one or two of the families wood-winds, brass, piano, vocals, and strings. In this paper, we consider the task of automatically recognizing instrument families from music recordings. As one main contribution, we investigate the inﬂuence of data normalization, pre-processing, and augmentation techniques on the generalization capability of the models. We report on experiments using three datasets of monotimbral recordings covering different levels of timbral complexity: isolated notes, isolated melodies, and polyphonic pieces. While data augmentation and the normalization of spectral patches turned out to be beneﬁcial, pre-processing strategies such as logarithmic compression and channel-energy normalization did not lead to substantial improvements. Furthermore, our cross-dataset experiments indicate the necessity of further optimization routines such as domain adaptation.