Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experiment on Implicitly Crowdsourcing Expert Knowledge about Romanian Synonyms from Language Learners

In this paper, we present an experiment performed with the aim of evaluating if linguistic knowledge of expert quality about Romanian synonyms could be crowdsourced from L1 language learners, learning Romanian as their mother tongue, by collecting and aggregating their answers to two types of questions that are automatically generated from a dataset, encoding semantic relations be-tween words. Such an evaluation aimed at conﬁrming the viability of a fully learner-fueled crowdsourcing workﬂow for improving such type of dataset. For this experiment, we reused an existing open-source crowdsourcing vocabulary trainer that we designed for this very purpose and which crowdsourcing potential needed further evaluation, especially with regards to lesser-resourced languages such as Romanian. Our results conﬁrmed that producing expert knowledge regarding Romanian synonyms could be achieved in such a fashion. Additionally, we took the occasion to further evaluate the learning impact of the trainer on the participants and gather their feedback regarding several aspects.
Investigation of Transfer Languages for Parsing Latin: Italic Branch vs. Hellenic Branch

Choosing a transfer language is a crucial step in transfer learning. In much previous research on dependency parsing, related languages have successfully been used. However, when parsing Latin, it has been suggested that languages such as ancient Greek could be helpful. In this work we parse Latin in a low-resource scenario, with the main goal to investigate if Greek languages are more helpful for parsing Latin than related Italic languages, and show that this is indeed the case. We further investigate the influence of other factors including training set size and content as well as linguistic distances. We find that one explanatory factor seems to be the syntactic similarity between Latin and Ancient Greek. The influence of genres or shared annotation projects seems to have a smaller impact.
Decentralized Word2Vec Using Gossip Learning

Advanced NLP models require huge amounts of data from various domains to produce high-quality representations. It is useful then for a few large public and private organizations to join their corpora during training. However, factors such as legislation and user emphasis on data privacy may prevent centralized orchestration and data sharing among these organizations. Therefore, for this specific scenario, we investigate how gossip learning, a massively-parallel, data-private, decentralized protocol, compares to a shared-dataset solution. We find that the application of Word2Vec in a gossip learning framework is viable. Without any tuning, the results are comparable to a traditional centralized setting, with a loss of quality as low as 4.3%. Furthermore, the results are up to 54.8% better than independent local training.
Chunking Historical German

Quantitative studies of historical syntax require large amounts of syntactically annotated data, which are rarely available. The application of NLP methods could reduce manual annotation effort, provided that they achieve sufficient levels of accuracy. The present study investigates the automatic identification of chunks in historical German texts. Because no training data exists for this task, chunks are extracted from modern and historical constituency treebanks and used to train a CRF-based neural sequence labeling tool. The evaluation shows that the neural chunker outperforms an unlexicalized baseline and achieves overall F-scores between 90% and 94% for different historical data sets when POS tags are used as feature. The conducted experiments demonstrate the usefulness of including historical training data while also highlighting the importance of reducing boundary errors to improve annotation precision.
Genomic and acoustic differences separate Lilian's Meadowlark (Sturnella magna lilianae) from Eastern (S. magna) and Western (S. neglecta) meadowlarks

ABSTRACT Examining differences among recently diverged populations can provide insight into the traits and evolutionary mechanisms that drive or maintain divergence. The genus Sturnella includes 2 recently diverged species, Sturnella magna (Eastern Meadowlark) and S. neglecta (Western Meadowlark), the former of which has a complex of subspecies distributed across the Americas. Of the S. magna subspecies that occur in the United States, S. m. lilianae is the only one with a disjunct range, occurring in the southwestern United States and central Mexico. It also has markedly different song patterns than all other S. magna subspecies. In order to assess population differentiation, we performed whole-genome sequencing of 35 birds and analyzed song characteristics from 85 birds. Songs from each species and S. m. lilianae were diagnosable using linear discriminant function analysis and support divergence in song between all taxa. Phylogenetic analysis and admixture proportions support 3 distinct clades within North American meadowlarks, and tests of introgression failed to detect a significant signal. Overall, our results indicate that S. m. lilianae exhibits high levels of genetic and vocal differentiation from both S. magna and S. neglecta, with no evidence of introgression between any group, and forms a distinct evolutionary lineage. We thus recommend the elevation of S. m. lilianae to species status. LAY SUMMARY • Understanding species boundaries helps inform policy. • Meadowlarks are currently classified as two species, but recent research suggests they may be three species. • A population of Eastern Meadowlarks in the southwestern United States and northern Mexico called Lilian's Meadowlark have lighter plumage color and sing different songs than the rest of Eastern Meadowlarks. • Using DNA and birdsong, we compared populations of Eastern, Western, and Lilian's meadowlarks to find how they were related to one another. • Eastern, Western, and Lilian's meadowlarks all have moderate but equal amounts of differentiation from one another, suggesting Lilian's Meadowlarks is a full species.
Sustainable Investing: ESG versus SDG

In this article, we compare the established ESG-oriented to the more recent SDG-driven investment strategies in the United States and Europe. We have built cap-weighted portfolios based on ESG scores (Low, Mid, High) and comparable portfolios based on SDG scores. In the observed period, we show that most of the SDG premium is driven by the sector allocation effect: Technology in the United States and Healthcare in Europe. Thus, we have built sector-adjusted ESG and SDG portfolios to cope with the sector bias. This entails the reduction of the structural sector differences in SDG ratings. Interestingly, although the premium between high- and low-rated SDG stocks vanishes in the US case, the European case exhibits a strong positive premium. Finally, integrating SDG components in investment decisions will certainly be the standard in the years to come, but investors should be aware of the potential undesired bias implied by such an approach. TOPICS: ESG investing, portfolio construction, information providers/credit ratings, performance measurement Key Findings ▪ From an average rating point of view, ESG and SDG sorted portfolios do not overlap much, so high ESG rated companies are not necessarily the best SDG contributors. This is also true the other way around. ▪ SDG-driven strategies carry a structural sector bias in both the US and European cases. ▪ Neutralizing the sector effect, the US case sees its SDG premium vanish while the European case keeps a significant positive one.
Conflict Dynamics and Emotional Dissonance during the Family Business Succession Process: Evidence from the Tunisian Context

Abstract This article aims to understand how emerging conflicts evolve and generate negative emotions during family firms’ succession process. Relying on previous research on emotional dissonance and conflict, we conduct a single longitudinal case study by interviewing the successor, the predecessor, and other family members in a family firm in the Tunisian context. The results show that emotional dissonance plays a critical role in conflict escalation between successors and predecessors. Family systems and cultural factors explain challenges in managing emotions; however, emotions associated with family events can facilitate the evolution of the succession process by resolving conflict. This study thus reveals how and why emotions and conflicts arise during the succession process.
A study on the RR-to-MR transition of shock wave reflections near the leading edge in hypersonic flows

Abstract In this paper, the incident shock–separation shock interactions on a surface plate near the leading edge are studied theoretically and experimentally, and the transition from regular reflection (RR) to Mach reflection (MR) is the main focus. The theoretical method employs free interaction theory (FIT) and the minimum entropy production (MEP) principle to analyse the separation shock strength of flow separated from the boundary layer and separated from the leading edge, respectively, the criterion based on the MEP principle is employed to predict the RR-to-MR transition near the leading edge. The experiments were performed on a rotatable wedge situated over a sharp leading-edge plate such that the wedge could continuously change the flow deflection angle from $0^{\circ }$ to $40^{\circ }$ by means of a high-precision control device. Fast-response transducers and a high-speed camera were used to measure dynamic pressures and to take schlieren images, respectively. The influences of wedge positions, Reynolds numbers and Mach numbers on shock reflections are investigated by careful tests. The theoretical and experimental results for Mach numbers 5, 6, 7 and 8 show good agreement, indicating that the theoretical method is applicable.
Diverse mating phenotypes impact the spread of wtf meiotic drivers in S. pombe

Meiotic drivers are genetic loci that break Mendel’s law of segregation to be transmitted into more than half of the offspring produced by a heterozygote. The success of a driver relies on outcrossing because drivers gain their advantage in heterozygotes. It is, therefore, curious that Schizosaccharomyces pombe, a species reported to rarely outcross, harbors many meiotic drivers. To address this paradox, we measured mating phenotypes in S. pombe natural isolates. We found that the propensity to inbreed varies between natural isolates and can be affected both by cell density and by the available sexual partners. Additionally, we found that the observed level of inbreeding slows, but does not prevent, the spread of a wtf meiotic driver in the absence of additional fitness costs. These analyses reveal parameters critical to understanding the evolution of S. pombe and help explain the success of meiotic drivers in this species.
Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

Motivation Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no comprehensive and direct accuracy comparison of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage) and fetal DNA fraction (FF) on clinically validated NIPT samples. Methods We evaluated computational NIPT aneuploidy analysis tools WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq, on the same set of clinically validated samples, subsampled to different sequencing coverages between 1.25–20M reads per sample (RPS). These clinically validated samples consisted of 423 samples, including 19 samples with fetal chromosome 21 trisomy (T21, Down syndrome), eight trisomy 18 (T18, Edwards syndrome) and three trisomy 13 (T13, Patau syndrome) samples. For each software and sequencing coverage, we determined the number of false-negative and false-positive trisomy/euploidy calls. For a uniform trisomy detection interpretation, we defined a framework based on the percent-point function for determining the cut-off threshold for calling aneuploidy based on the sample Z-score and the reference group Z-score distribution. We also determined the effect of the naturally occurring arbitrary read placement driven uncertainty on T21 detection at very low sequencing coverage and the effect of cell-free fetal DNA fraction (FF) on the accuracy of these computational tools in the case of various sequencing coverages. Results This is the first head-to-head comparison of NIPT aneuploidy detection tools for the low-coverage whole-genome sequencing approach. We determined that, with the currently available software tools, the minimum sequencing coverage with no false-negative trisomic cases was 5M RPS. Secondly, for these compared tools, the number of false-negative trisomic cases could be reduced if the trisomy call cut-off threshold considers the Z-score distribution of euploid reference samples. Thirdly, we observed that in the case of low FF, both aneuploidy Z-score and FF inference was considerably less accurate, especially in NIPT assays with 5M RPS or lower coverage. Conclusions We determined that all compared computational NIPT tools were affected by lower sequencing depth, resulting in systematically increasing the proportions of false-negative trisomy results as the sequencing depth decreased. Trisomy detection for lower coverage NIPT samples (e.g. 2.5M RPS) is technically possible but can increase the proportion of false-positive and false-negative trisomic cases, especially in the case of low FF.
Are plants in sown flower strips suitable for communities of wild bees? Pollination network approach in conservation biology

Drastic reductions of insect diversity and abundance are observed in the highly fragmented agricultural landscapes of central Europe. Declines of pollinators may have detrimental effects on the reproduction of wild insect-pollinated plants as well as the yield of crops. In order to mitigate such impacts, sown flower strips on arable land within Agri-Environment Climate Schemes (AECS) are supported across EU countries. However, it is not clear whether sown flower strips provide equivalent benefits to wild flower-visiting insects as semi-natural habitats. Here, we apply plant-pollinator network approach to evaluate the function of sown flower strips for the communities of wild bees. We compared the structural characteristics and the robustness of plant-pollinator networks in sown flower strips and nearby semi-natural habitats. We also quantified the importance of individual plant species for bees based on simulations of plant-pollinator extinction cascades. We found that assemblages of plants and pollinators were less diverse in sown flower strips than in semi-natural habitats, more generalized, and more nested. However, we did not find any significant differences in network robustness to plant-pollinator coextinctions. Further, simulations revealed a large variation in the functional importance among plant species from both habitats. We conclude that although the analysis of network robustness suggested that plants in the sown flower strips and semi-natural habitats were functionally equivalent, this masked important differences among the two habitats. From the conservation point of view, semi-natural habitats were superior in supporting a more diverse community of solitary bees and bumblebees.
Perceptual clustering in auditory streaming

Perception is dependent on the ability to separate stimuli from different objects and causes in order to perform inference and further processing. We have models of how the human brain can perform such causal inference for simple binary stimuli (e.g., auditory and visual), but the complexity of the models increases dramatically with more than two stimuli. To characterize human perception with more complex stimuli, we developed a Bayesian inference model that takes into account a potentially unlimited number of stimulus sources: it is general enough to factor in any discrete sequential cues from any modality. Because the model employs a non-parametric prior, increased signal complexity does not necessitate the addition of more parameters. The model not only predicts the number of possible sources, but also specifies the source with which each signal is associated. As a test case, we demonstrate that such a model can explain several phenomena in the auditory stream perception literature, that it provides an excellent fit to experimental data, and that it makes novel predictions that we experimentally confirm. These findings have implications not just for human auditory temporal perception, but for a wide range of perceptual phenomena across unisensory and multisensory stimuli.
Network instability dynamics drive a transient bursting period in the developing hippocampus in vivo

Spontaneous correlated activity is a universal hallmark of immature neural circuits. However, the cellular dynamics and intrinsic mechanisms underlying network burstiness in the intact developing brain are largely unknown. Here, we use two-photon Ca2+ imaging to comprehensively map the developmental trajectories of spontaneous network activity in hippocampal area CA1 in vivo. We unexpectedly find that network burstiness peaks after the developmental emergence of effective synaptic inhibition in the second postnatal week. We demonstrate that the enhanced network burstiness reflects an increased functional coupling of individual neurons to local population activity. However, pairwise neuronal correlations are low, and network bursts (NBs) recruit CA1 pyramidal cells in a virtually random manner. Using a dynamic systems modeling approach, we reconcile these experimental findings and identify network bi-stability as a potential regime underlying network burstiness at this age. Our analyses reveal an important role of synaptic input characteristics and network instability dynamics for NB generation. Collectively, our data suggest a mechanism, whereby developing CA1 performs extensive input-discrimination learning prior to the onset of environmental exploration.
Understanding E-Commerce Consumers’ Repeat Purchase Intention: The Role of Trust Transfer and the Moderating Effect of Neuroticism

The dominant position of e-commerce is especially being articulated in the retailing industry once again due to several constraints that the world faces in the COVID-19 pandemic era. In this regard, this study explores the significant role of trust transfer (from offline to online) and the moderating effect of consumers’ neurotic traits in the framework of trust-satisfaction-repurchase intention in the e-commerce context based on a survey with 406 Korean e-commerce consumers. Moreover, a prediction-oriented segmentation (POS) technique combined with structural equation models (SEM) was utilized to reveal consumers’ probable hidden heterogeneous characteristics. The outcomes of the global model SEM analysis indicate that offline-online trust transference occurs in e-commerce, and the conveyed trust significantly influences satisfaction and consumers’ repeat purchase intention through satisfaction. Neuroticism also has significant positive effects on trust transfer in the global model. However, results in three subgroups generated by POS show heterogeneous characteristics that considerably differed from the global model test results. The implications from this study will be beneficial to field practitioners in the e-commerce industry in addressing the importance of trust transfer, negative neurotic traits as well as heterogeneous aspects of consumers.
Hemodynamic Abnormalities in the Aorta of Turner Syndrome Girls

Congenital abnormalities in girls and women with Turner syndrome (TS), alongside an underlying predisposition to obesity and hypertension, contribute to an increased risk of cardiovascular disease and ultimately reduced life expectancy. We observe that children with TS present a greater variance in aortic arch morphology than their healthy counterparts, and hypothesize that their hemodynamics is also different. In this study, computational fluid dynamic (CFD) simulations were performed for four TS girls, and three age-matched healthy girls, using patient-specific inlet boundary conditions, obtained from phase-contrast MRI data. The visualization of multidirectional blood flow revealed an increase in vortical flow in the arch, supra-aortic vessels, and descending aorta, and a correlation between the presence of aortic abnormalities and disturbed flow. Compared to the relatively homogeneous pattern of time-averaged wall shear stress (TAWSS) on the healthy aortae, a highly heterogeneous distribution with elevated TAWSS values was observed in the TS geometries. Visualization of further shear stress parameters, such as oscillatory shear index (OSI), normalized relative residence time (RRTn), and transverse WSS (transWSS), revealed dissimilar heterogeneity in the oscillatory and multidirectional nature of the aortic flow. Taking into account the young age of our TS cohort (average age 13 ± 2 years) and their obesity level (75% were obese or overweight), which is believed to accelerate the initiation and progression of endothelial dysfunction, these findings may be an indication of atherosclerotic disease manifesting earlier in life in TS patients. Age, obesity and aortic morphology may, therefore, play a key role in assessing cardiovascular risk in TS children.
Amygdala Allostasis and Early Life Adversity: Considering Excitotoxicity and Inescapability in the Sequelae of Stress

Early life adversity (ELA), such as child maltreatment or child poverty, engenders problems with emotional and behavioral regulation. In the quest to understand the neurobiological sequelae and mechanisms of risk, the amygdala has been of major focus. While the basic functions of this region make it a strong candidate for understanding the multiple mental health issues common after ELA, extant literature is marked by profound inconsistencies, with reports of larger, smaller, and no differences in regional volumes of this area. We believe integrative models of stress neurodevelopment, grounded in “allostatic load,” will help resolve inconsistencies in the impact of ELA on the amygdala. In this review, we attempt to connect past research studies to new findings with animal models of cellular and neurotransmitter mediators of stress buffering to extreme fear generalization onto testable research and clinical concepts. Drawing on the greater impact of inescapability over unpredictability in animal models, we propose a mechanism by which ELA aggravates an exhaustive cycle of amygdala expansion and subsequent toxic-metabolic damage. We connect this neurobiological sequela to psychosocial mal/adaptation after ELA, bridging to behavioral studies of attachment, emotion processing, and social functioning. Lastly, we conclude this review by proposing a multitude of future directions in preclinical work and studies of humans that suffered ELA.