julilili42/papers huggingface dataset:
Developing a Metadata Profile for Higher Education OER Repositories
2023-01-01

Abstract To provide Open Educational Resources (OER) according to the recognised FAIR principles (improve Findability, Accessibility, Interoperability, and Reuse of digital assets), it is necessary to describe the educational material by means of meaningful metadata. There are conflicting demands to comply with. On the one hand, the educational resources should be described in as much detail as possible for accurately fitting search results. On the other hand, only strictly necessary information should be obligatory to keep the obstacles for authors as low as possible. An additional goal is to allow easy connection between repositories, thus allowing federated search and harvesting of metadata, for example, by search engines or other interested parties. Operators of OER repositories from several federal states in Germany (HOOU, OERNDS, ORCA.nrw, VCRP, VHB, ZOERR) have developed a metadata profile focussing on OER in the context of higher education. The initiators strive to reach the mentioned objectives and to establish a standard in the field. The metadata profile is based on the well-established Learning Object Metadata Standard (LOM). The chapter describes the decision process and why certain choices are made to reach the intended goals. Furthermore, the importance of editorial supervision for a sound quality of the material and metadata will be discussed. The chances and challenges are illustrated based on practical experiences with the establishment and daily operation of the Zentrales OER Repositorium der Hochschulen in Baden- Württemberg (ZOERR) .
Languages Through the Looking Glass of BPE Compression
2023-01-01

Abstract Byte-pair encoding (BPE) is widely used in NLP for performing subword tokenization. It uncovers redundant patterns for compressing the data, and hence alleviates the sparsity problem in downstream applications. Subwords discovered during the first merge operations tend to have the most substantial impact on the compression of texts. However, the structural underpinnings of this effect have not been analyzed cross-linguistically. We conduct in-depth analyses across 47 typologically diverse languages and three parallel corpora, and thereby show that the types of recurrent patterns that have the strongest impact on compression are an indicator of morphological typology. For languages with richer inflectional morphology there is a preference for highly productive subwords on the early merges, while for languages with less inflectional morphology, idiosyncratic subwords are more prominent. Both types of patterns contribute to efficient compression. Counter to the common perception that BPE subwords are not linguistically relevant, we find patterns across languages that resemble those described in traditional typology. We thus propose a novel way to characterize languages according to their BPE subword properties, inspired by the notion of morphological productivity in linguistics. This allows us to have language vectors that encode typological knowledge induced from raw text. Our approach is easily applicable to a wider range of languages and texts, as it does not require annotated data or any external linguistic knowledge. We discuss its potential contributions to quantitative typology and multilingual NLP.
Low Research-Data Availability in Educational-Psychology Journals: No Indication of Effective Research-Data Policies
2023-01-01

Research-data availability contributes to the transparency of the research process and the credibility of educational-psychology research and science in general. Recently, there have been many initiatives to increase the availability and quality of research data. Many research institutions have adopted research-data policies. This increased awareness might have raised the sharing of research data in empirical articles. To test this idea, we coded 1,242 publications from six educational-psychology journals and the psychological journal Cognition (as a baseline) published in 2018 and 2020. Research-data availability was low (3.85% compared with 62.74% in Cognition) but has increased from 0.32% (2018) to 7.16% (2020). However, neither the data-transparency level of the journal nor the existence of an official research-data policy on the level of the corresponding author’s institution was related to research-data availability. We discuss the consequences of these findings for institutional research-data-management processes.
Improving taxonomic classification with feature space balancing
2023-01-01

Abstract Summary Modern high-throughput sequencing technologies, such as metagenomic sequencing, generate millions of sequences that need to be assigned to their taxonomic rank. Modern approaches either apply local alignment to existing databases, such as MMseqs2, or use deep neural networks, as in DeepMicrobes and BERTax. Due to the increasing size of datasets and databases, alignment-based approaches are expensive in terms of runtime. Deep learning-based approaches can require specialized hardware and consume large amounts of energy. In this article, we propose to use k-mer profiles of DNA sequences as features for taxonomic classification. Although k-mer profiles have been used before, we were able to significantly increase their predictive power significantly by applying a feature space balancing approach to the training data. This greatly improved the generalization quality of the classifiers. We have implemented different pipelines using our proposed feature extraction and dataset balancing in combination with different simple classifiers, such as bagged decision trees or feature subspace KNNs. By comparing the performance of our pipelines with state-of-the-art algorithms, such as BERTax and MMseqs2 on two different datasets, we show that our pipelines outperform these in almost all classification tasks. In particular, sequences from organisms that were not part of the training were classified with high precision. Availability and implementation The open-source code and the code to reproduce the results is available in Seafile, at https://tinyurl.com/ysk47fmr. Supplementary information Supplementary data are available at Bioinformatics Advances online.
Different patterns of intrinsic functional connectivity at the default mode and attentional networks predict crystalized and fluid abilities in childhood
2023-01-01

Abstract Crystallized abilities are skills used to solve problems based on experience, while fluid abilities are linked to reasoning without evoke prior knowledge. To what extent crystallized and fluid abilities involve dissociated or overlapping neural systems is debatable. Due to often deployed small sample sizes or different study settings in prior work, the neural basis of crystallized and fluid abilities in childhood remains largely unknown. Here we analyzed within and between network connectivity patterns from resting-state functional MRI of 2707 children between 9 and 10 years from the ABCD study. We hypothesized that differences in functional connectivity at the default mode network (DMN), ventral, and dorsal attentional networks (VAN, DAN) explain differences in fluid and crystallized abilities. We found that stronger between-network connectivity of the DMN and VAN, DMN and DAN, and VAN and DAN predicted crystallized abilities. Within-network connectivity of the DAN predicted both crystallized and fluid abilities. Our findings reveal that crystallized abilities rely on the functional coupling between attentional networks and the DMN, whereas fluid abilities are associated with a focal connectivity configuration at the DAN. Our study provides new evidence into the neural basis of child intelligence and calls for future comparative research in adulthood during neuropsychiatric diseases.
Preparation, photoluminescence and excited state properties of the homoleptic cluster cation [(W6I8)(CH3CN)6]4+
2023-01-01

Cluster compounds containing the [(W 6 I 8 )(CH 3 CN) 6 ] 4+ ion were established. Photophysical properties of [(W 6 I 8 )(CH 3 CN) 6 ](BF 4 ) 4 are compared to those of compounds featuring the [(W 6 I 8 )L 6 ] 2− ion.
Enhancing the Ranking Context of Dense Retrieval through Reciprocal Nearest Neighbors
2023-01-01

Sparse annotation poses persistent challenges to training dense retrieval models; for example, it distorts the training signal when unlabeled relevant documents are used spuriously as negatives in contrastive learning. To alleviate this problem, we introduce evidence-based label smoothing, a novel, computationally efficient method that prevents penalizing the model for assigning high relevance to false negatives. To compute the target relevance distribution over candidate documents within the ranking context of a given query, we assign a non-zero relevance probability to those candidates most similar to the ground truth based on the degree of their similarity to the ground-truth document(s). To estimate relevance we leverage an improved similarity metric based on reciprocal nearest neighbors, which can also be used independently to rerank candidates in post-processing. Through extensive experiments on two large-scale ad hoc text retrieval datasets, we demonstrate that reciprocal nearest neighbors can improve the ranking effectiveness of dense retrieval models, both when used for label smoothing, as well as for reranking. This indicates that by considering relationships between documents and queries beyond simple geometric distance we can effectively enhance the ranking context.
Sequence Variants in the <i>WNT10B</i> Underlying Non-Syndromic Split-Hand/Foot Malformation
2023-01-01

&lt;b&gt;&lt;i&gt;Introduction:&lt;/i&gt;&lt;/b&gt; Split hand and foot malformation (SHFM) or ectrodactyly is a rare limb deformity characterized by median cleft of the hand and foot with impaired or missing central rays. It can occur as an isolated anomaly or in association with abnormalities of other body parts. &lt;b&gt;&lt;i&gt;Methods:&lt;/i&gt;&lt;/b&gt; After delineating the clinical features of two families (A–B), with non-syndromic SHFM, exome and Sanger sequencing were employed to search for the disease-causing variants. &lt;b&gt;&lt;i&gt;Results:&lt;/i&gt;&lt;/b&gt; Analysis of exome and Sanger sequencing data revealed two causative variants in the &lt;i&gt;WNT10B&lt;/i&gt; gene in affected members of the two families. This included a novel missense change [c.338G&amp;gt;C; p.(Gly113Ala)] in family A and a previously reported frameshift variant [c.884-896delTCCAGCCCCGTCT; p.(Phe295Cysfs*87)] in family B. &lt;b&gt;&lt;i&gt;Conclusion:&lt;/i&gt;&lt;/b&gt; Our findings add a novel variant in &lt;i&gt;WNT10B&lt;/i&gt; gene as the underlying cause of SHFM. The finding adds to the growing body of knowledge about the genetic basis of developmental disorders and provides valuable insights into the molecular mechanisms that regulate limb development.
OmicsTIDE: interactive exploration of trends in multi-omics data
2023-01-01

Abstract Motivation The increasing amount of data produced by omics technologies has enabled researchers to study phenomena across multiple omics layers. Besides data-driven analysis strategies, interactive visualization tools have been developed for a more transparent analysis. However, most state-of-the-art tools do not reconstruct the impact of a single omics layer on the integration result. Results We developed a data classification scheme focusing on different aspects of multi-omics datasets for a systemic understanding. Based on this classification, we developed the Omics Trend-comparing Interactive Data Explorer (OmicsTIDE), an interactive visualization tool for the comparison of gene-based quantitative omics data. The tool consists of a computational part that clusters omics datasets to determine trends and an interactive visualization. The trends are visualized as profile plots and are connected by a Sankey diagram that allows for an interactive pairwise trend comparison to discover concordant and discordant trends. Moreover, large-scale omics datasets are broken down into small subsets that can be analyzed functionally using Gene Ontology enrichment within few analysis steps. We demonstrate the interactive analysis using OmicsTIDE with two case studies focusing on different experimental designs. Availability and implementation OmicsTIDE is a web tool available via http://omicstide-tuevis.cs.uni-tuebingen.de/. Supplementary information Supplementary data are available at Bioinformatics Advances online.
Minanto at SemEval-2023 Task 2: Fine-tuning XLM-RoBERTa for Named Entity Recognition on English Data
2023-01-01

Within the scope of the shared task MultiCoNER II our aim was to improve the recognition of named entities in English. We as team Minanto fine-tuned a cross-lingual model for Named Entity Recognition on English data and achieved an average F1 score of 51.47\\% in the final submission. We found that a monolingual model works better on English data than a cross-lingual and that the input of external data from earlier Named Entity Recognition tasks provides only minor improvements. In this paper we present our system, discuss our results and analyze the impact of external data.
A framework and resource for global collaboration in non-human primate neuroscience
2023-01-01

As science and technology evolve, there is an increasing need for promotion of international scientific exchange. Collaborations, while offering substantial opportunities for scientists and benefit to society, also present challenges for those working with animal models, such as non-human primates (NHPs). Diversity in regulation of animal research is sometimes mistaken for the absence of common international welfare standards. Here, the ethical and regulatory protocols for 13 countries that have guidelines in place for biomedical research involving NHPs were assessed with a focus on neuroscience. Review of the variability and similarity in trans-national NHP welfare regulations extended to countries in Asia, Europe and North America. A tabulated resource was established to advance solution-oriented discussions and scientific collaborations across borders. Our aim is to better inform the public and other stakeholders. Through cooperative efforts to identify and analyze information with reference to evidence-based discussion, the proposed key ingredients may help to shape and support a more informed, open framework. This framework and resource can be expanded further for biomedical research in other countries.
Direct and indirect evidence of compression of word lengths. Zipf’s law of abbreviation revisited
2023-01-01

Zipf’s law of abbreviation, the tendency of more frequent words to be shorter, is one of the most solid candidates for a linguistic universal, in the sense that it has the potential for being exceptionless or with a number of exceptions that is vanishingly small compared to the number of languages on Earth. Since Zipf’s pioneering research, this law has been viewed as a manifestation of a universal principle of communication, i.e. the minimization of word lengths, to reduce the effort of communication. Here we revisit the concordance of written language with the law of abbreviation. Crucially, we provide wider evidence that the law holds also in speech (when word length is measured in time), in particular in 46 languages from 14 linguistic families. Agreement with the law of abbreviation provides indirect evidence of compression of languages via the theoretical argument that the law of abbreviation is a prediction of optimal coding. Motivated by the need of direct evidence of compression, we derive a simple formula for a random baseline indicating that word lengths are systematically below chance, across linguistic families and writing systems, and independently of the unit of measurement (length in characters or duration in time). Our work paves the way to measure and compare the degree of optimality of word lengths in languages.
Triisobutylaluminium-promoted formation of lanthanide hydrides
2023-01-01

Treatment of homoleptic silylamide Ln[N(SiMe 3 ) 2 ] 3 with TIBA affords distinct heteroaluminato ligands revealing both Ln( iii )-amido→Ln( iii )-alkyl and Ln( iii )-amido→Ln( iii )-hydrido transformations.
Sequence Variants in MEGF8 and GJA1 Underlying Syndactyly
2023-01-01

Introduction: Syndactyly is a common congenital limb malformation. It occurs due to embryological failure of digit separation during limb development. Syndactyly often runs in families with an incidence of about one out of every 2,500–3,000 live births. Methods: Here, we have reported two families presenting features of severe forms of syndactyly. The disorder segregated in autosomal recessive in one and in autosomal dominant manner in the second family. Search for the causative variants was carried out using whole-exome sequencing in family A and candidate gene sequencing in family B. Results: Analysis of the sequencing data revealed two novel missense variants, including p.(Cys1925Arg) in MEGF8 in family A and p.(Thr89Ile) in GJA1 in family B. Conclusion: In conclusion, the novel findings, presented here, not only expand the mutation spectrum in the genes MEGF8 and GJA1, but this will also facilitate screening other families carrying similar clinical features in the Pakistani population.
Redoxtrons – An experimental system to study redox processes within the capillary fringe
2023-01-01

Abstract Spatiotemporal characterisation of the soil redox status within the capillary fringe (CF) is a challenging task. Air‐filled porosities (ε), oxygen concentration (O 2 ) and soil redox potential (E H ) are interrelated soil variables within active biogeochemical domains such as the CF. We investigated the impact of water table (WT) rise and drainage in an undisturbed topsoil and subsoil sample taken from a Calcaric Gleysol for a period of 46 days. We merged 1D (E H and matric potential) and 2D (O 2 ) systems to monitor at high spatiotemporal resolution redox dynamics within self‐constructed redoxtron housings and complemented the data set by a 3D pore network characterization using X‐ray microtomography (X‐ray μCT). Depletion of O 2 was faster in the organic matter‐ and clay‐rich aggregated topsoil and the CF extended &gt;10 cm above the artificial WT. The homogeneous and less‐aggregated subsoil extended only 4 cm above the WT as indicated by ε–O 2 –E H data during saturation. After drainage, 2D O 2 imaging revealed a fast aeration towards the lower depths of the topsoil, which agrees with the connected ε derived by X‐ray μCT (ε CT_conn ) of 14.9% of the total porosity. However, small‐scaled anoxic domains with O 2 saturation &lt;5% were apparent even after lowering the WT (down to 0.25 cm 2 in size) for 23 days. These domains remained a nucleus for reducing soil conditions (E H &lt; −100 mV), which made it challenging to characterise the soil redox status in the CF. In contrast, the subsoil aeration reached O 2 saturation after 8 days for the complete soil volume. Values of ε CT_conn around zero in the subsoil highlighted that soil aeration was independent of this parameter suggesting that other variables such as microbial activity must be considered when predicting the soil redox status from ε alone. The use of redoxtrons in combination with localised redox‐measurements and image based pore space analysis resulted in a better 2D/3D characterisation of the pore system and related O 2 transport properties. This allowed us to analyse the distribution and activity of microbiological niches highly associated with the spatiotemporal variable redox dynamics in soil environments. Highlights The time needed to turn from reducing to oxidising (period where all platinum electrodes feature E H &gt; 300 mV) condition differ for two samples with contrasting soil structure. The subsoil with presumably low O 2 consumption rates aerated considerably faster than the topsoil and exclusively by O 2 diffusion through medium‐ and fine‐sized pores. To derive the soil redox status based upon the triplet ε–O 2 –E H is challenging at present in heterogeneous soil domains and larger soil volumes than 250 cm 3 . Undisturbed soil sampling along with 2D/3D redox measurement systems (e.g., redoxtrons) improve our understanding of redox dynamics within the capillary fringe.
The Application of Immersive Virtual Reality and Machine Learning for the Assessment of Unilateral Spatial Neglect
2023-01-01

Abstract Even subtle forms of hemispatial neglect after stroke negatively affect the performance of daily life tasks, increase the risk of injury, and are associated with poor rehabilitation outcomes. Conventional paper-and-pencil tests, however, often underestimate the symptoms. We aimed to identify relevant neglect-specific measures and clinical decision rules based on machine learning techniques on behavioral data generated in a new Virtual Reality (VR) application, the immersive virtual road-crossing task. In total, 59 participants were included in our study: two right-hemispheric stroke groups with left neglect (N = 20) or no neglect (N = 19), classified based on conventional tests and medical diagnosis, and healthy controls (N = 20). A neuropsychological test battery and the VR task were administered to all participants. We applied decision trees and random forest models to predict the respective groups based on the results of the VR task. Our feature selection procedure yielded six features as suitable predictors, most of which involved lateral time-related measures, particularly reaction times, and head movements. Our model achieved a high training accuracy of 96.6% and estimated test accuracy of 76.8%. These results confirm previous reports that temporal behavioral patterns are key to detecting subtle neglect in patients with chronic stroke. Our results indicate that VR combined with machine learning has the potential to achieve higher test accuracies while being highly applicable to clinical practice.
Fruitful interplay between theory and experiment in the design of circularly polarized luminescent materials
2023-01-01

A computational approach identified BINOL-derived emitters for circularly polarized luminescence (CPL). Very good agreement between computed and experimental g lum factors was observed when state-specific solvation was included.
Team ISCL_WINTER at SemEval-2023 Task 12:AfriSenti-SemEval: Sentiment Analysis for Low-resource African Languages using Twitter Dataset
2023-01-01

This paper presents a study on the effectiveness of various approaches for addressing the challenge of multilingual sentiment analysis in low-resource African languages. . The approaches evaluated in the study include Support Vector Machines (SVM), translation, and an ensemble of pre-trained multilingual sentimental models methods. The paper provides a detailed analysis of the performance of each approach based on experimental results. In our findings, we suggest that the ensemble method is the most effective with an F1-Score of 0.68 on the final testing. This system ranked 19 out of 33 participants in the competition.