Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Water Temperature, Salinity, and Currents on the Survival and Distribution of the Infective Copepodid Stage of Sea Lice (Lepeophtheirus Salmonis) Originating on Atlantic Salmon Farms in the Broughton Archipelago of British Columbia, Canada

Recent reports claim that pink salmon fry are heavily infected by Lepeoptheirus salmonis as they pass salmon farms in the Broughton Archipelago. Hydrodynamic studies reveal that the top 25 to 40 m of water generally flows seaward through the archipelago under the influence of freshwater, reducing surface salinity from 15–25% from June through November of most years. Sea lice larvae do not consistently develop to an infectious stage at salinities < 30‰—providing a natural control in the archipelago. The larvae require 4.2–5.8 days to develop to the infective stage at the temperatures typical during the time that pink salmon fry are migrating. Net current speeds measured at 15 salmon farms are predicted to carry most sea lice nauplii 7.3–10.0 km downcurrent and out of the archipelago before they become infective. A particle-tracking model predicts that nauplii released in the vicinity of two farms located deep in the archipelago are carried 10–40 km from the farms before they become infective. These predictions are consistent with the European experience and suggest little potential for salmon farms to be self-infecting or to infect migrating wild fish in their immediate vicinity, except where net current vectors are zero. A clearer picture of sea lice epizootics requires detailed knowledge of site-specific oceanographic characteristics and the affects these have on sea lice survival and dispersal during development to the infectious copepodid stage.
Taylor’s Law in Innovation Processes

Taylor’s law quantifies the scaling properties of the fluctuations of the number of innovations occurring in open systems. Urn-based modeling schemes have already proven to be effective in modeling this complex behaviour. Here, we present analytical estimations of Taylor’s law exponents in such models, by leveraging on their representation in terms of triangular urn models. We also highlight the correspondence of these models with Poisson–Dirichlet processes and demonstrate how a non-trivial Taylor’s law exponent is a kind of universal feature in systems related to human activities. We base this result on the analysis of four collections of data generated by human activity: (i) written language (from a Gutenberg corpus); (ii) an online music website (Last.fm); (iii) Twitter hashtags; (iv) an online collaborative tagging system (Del.icio.us). While Taylor’s law observed in the last two datasets agrees with the plain model predictions, we need to introduce a generalization to fully characterize the behaviour of the first two datasets, where temporal correlations are possibly more relevant. We suggest that Taylor’s law is a fundamental complement to Zipf’s and Heaps’ laws in unveiling the complex dynamical processes underlying the evolution of systems featuring innovation.
Development of the Oleander Mealybug, Paracoccus burnerae (Brain) (Hemiptera: Pseudococcidae), on Citrus at Five Temperatures

The effect of constant temperatures on the development, survival and fecundity of the oleander mealybug, Paracoccus burnerae, on citrus was determined. Developmental time, rate of development, fecundity and survival were investigated at five constant temperatures and a 16L:8D light:dark regime. The rate of development increased linearly with an increase in temperature for the egg, first nymphal and pupal stages as well as the entire development cycle from egg to adult, but was nonlinear for the second and third nymphal stages. Survival decreased with increase in temperature. Paracoccus burnerae required 666.7 degree-days above a lower threshold of 8.7 °C to complete one generation. The highest mean number of 68 eggs per female was recorded at 22 °C. A sex ratio of 1:0.92 (male:female) was obtained from the life table. The net reproductive rate (Ro) was >1 at all five temperatures, an indication that it is capable of increasing its population numbers despite the high mortality experienced in the first and second nymphal stages.
Single photon generation and non-locality of perfect W-state

We study the generation of a single photon perfect W-state. An important aspect of this perfect W-state is that it can be used for perfect teleportation and superdense coding, which are not achievable with maximally entangled W-state. Our scheme for generation involves entanglement between various path degrees of freedom of a single photon in a compact and weakly coupled integrated waveguide system, which can be fabricated precisely with a femtosecond laser direct writing technique. These platforms are interferometrically stable, scalable, less sensitive to decoherence and ensure a very low loss factor of 0.1dBcm−1 during photon propagation, and hence are ideal for generation of a perfect W-state. In addition to generation of the single photon perfect W-state, we study its non-local properties using the theory of local elements of reality.
KPQA: A Metric for Generative Question Answering Using Word Weights

For the automatic evaluation of Generative Question Answering (genQA) systems, it is essential to assess the correctness of the generated answers. However, n-gram similarity metrics, which are widely used to compare generated texts and references, are prone to misjudge fact-based assessments. Moreover, there is a lack of benchmark datasets to measure the quality of metrics in terms of the correctness. To study a better metric for genQA, we collect high-quality human judgments of correctness on two standard genQA datasets. Using our human-evaluation datasets, we show that existing metrics based on n-gram similarity do not correlate with human judgments. To alleviate this problem, we propose a new metric for evaluating the correctness of genQA. Specifically, the new metric assigns different weights on each token via keyphrase prediction, thereby judging whether a predicted answer sentence captures the key meaning of the human judge's ground-truth. Our proposed metric shows a significantly higher correlation with human judgment than widely used existing metrics.
Revisiting Unsupervised Relation Extraction

Unsupervised relation extraction (URE) extracts relations between named entities from raw text without manually-labelled data and existing knowledge bases (KBs). URE methods can be categorised into generative and discriminative approaches, which rely either on hand-crafted features or surface form. However, we demonstrate that by using only named entities to induce relation types, we can outperform existing methods on two popular datasets. We conduct a comparison and evaluation of our findings with other URE techniques, to ascertain the important features in URE. We conclude that entity types provide a strong inductive bias for URE.
TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions

A critical part of reading is being able to understand the temporal relationships between events described in a passage of text, even when those relationships are not explicitly stated. However, current machine reading comprehension benchmarks have practically no questions that test temporal phenomena, so systems trained on these benchmarks have no capacity to answer questions such as "what happened before/after [some event]? " We introduce TORQUE, a new English reading comprehension benchmark built on 3.2k news snippets with 21k human-generated questions querying temporal relationships. Results show that RoBERTa-large achieves an exact-match score of 51% on the test set of TORQUE, about 30% behind human performance.
Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi

Building natural language processing systems for non standardized and low resource languages is a difficult challenge. The recent success of large-scale multilingual pretrained language models provides new modeling tools to tackle this. In this work, we study the ability of multilingual language models to process an unseen dialect. We take user generated North-African Arabic as our case study, a resource-poor dialectal variety of Arabic with frequent code-mixing with French and written in Arabizi, a non-standardized transliteration of Arabic to Latin script. Focusing on two tasks, part-of-speech tagging and dependency parsing, we show in zero-shot and unsupervised adaptation scenarios that multilingual language models are able to transfer to such an unseen dialect, specifically in two extreme cases: (i) across scripts, using Modern Standard Arabic as a source language, and (ii) from a distantly related language, unseen during pretraining, namely Maltese. Our results constitute the first successful transfer experiments on this dialect, paving thus the way for the development of an NLP ecosystem for resource-scarce, non-standardized and highly variable vernacular languages.
Bayesian Characterizations of Properties of Stochastic Processes with Applications

In this article, we primarily propose a novel Bayesian characterization of stationary and nonstationary stochastic processes. In practice, this theory aims to distinguish between global stationarity and nonstationarity for both parametric and nonparametric stochastic processes. Interestingly, our theory builds on our previous work on Bayesian characterization of infinite series, which was applied to verification of the (in)famous Riemann Hypothesis. Thus, there seems to be interesting and important connections between pure mathematics and Bayesian statistics, with respect to our proposed ideas. We validate our proposed method with simulation and real data experiments associated with different setups. In particular, applications of our method include stationarity and nonstationarity determination in various time series models, spatial and spatio-temporal setups, and convergence diagnostics of Markov Chain Monte Carlo. Our results demonstrate very encouraging performance, even in very subtle situations. Using similar principles, we also provide a novel Bayesian characterization of mutual independence among any number of random variables, using which we characterize the properties of point processes, including characterizations of Poisson point processes, complete spatial randomness, stationarity and nonstationarity. Applications to simulation experiments with ample Poisson and non-Poisson point process models again indicate quite encouraging performance of our proposed ideas. We further propose a novel recursive Bayesian method for determination of frequencies of oscillatory stochastic processes, based on our general principle. Simulation studies and real data experiments with varieties of time series models consisting of single and multiple frequencies bring out the worth of our method.
Unsupervised Transfer of Semantic Role Models from Verbal to Nominal Domain

Semantic role labeling (SRL) is an NLP task involving the assignment of predicate arguments to types, called semantic roles. Though research on SRL has primarily focused on verbal predicates and many resources available for SRL provide annotations only for verbs, semantic relations are often triggered by other linguistic constructions, e.g., nominalizations. In this work, we investigate a transfer scenario where we assume role-annotated data for the source verbal domain but only unlabeled data for the target nominal domain. Our key assumption, enabling the transfer between the two domains, is that selectional preferences of a role (i.e., preferences or constraints on the admissible arguments) do not strongly depend on whether the relation is triggered by a verb or a noun. For example, the same set of arguments can fill the Acquirer role for the verbal predicate `acquire' and its nominal form `acquisition'. We approach the transfer task from the variational autoencoding perspective. The labeler serves as an encoder (predicting role labels given a sentence), whereas selectional preferences are captured in the decoder component (generating arguments for the predicting roles). Nominal roles are not labeled in the training data, and the learning objective instead pushes the labeler to assign roles predictive of the arguments. Sharing the decoder parameters across the domains encourages consistency between labels predicted for both domains and facilitates the transfer. The method substantially outperforms baselines, such as unsupervised and `direct transfer' methods, on the English CoNLL-2009 dataset.
Integrated human pseudoislet system and microfluidic platform demonstrates differences in G-protein-coupled-receptor signaling in islet cells.

Pancreatic islets secrete insulin from β cells and glucagon from α cells and dysregulated secretion of these hormones is a central component of diabetes. Thus, an improved understanding of the pathways governing coordinated β and α cell hormone secretion will provide insight into islet dysfunction in diabetes. However, the three-dimensional multicellular islet architecture, essential for coordinated islet function, presents experimental challenges for mechanistic studies of intracellular signaling pathways in primary islet cells. Here, we developed an integrated approach to study the function of primary human islet cells using genetically modified pseudoislets that resemble native islets across multiple parameters. Further, we developed a microperifusion system that allowed synchronous acquisition of GCaMP6f biosensor signal and hormone secretory profiles. We demonstrate the utility of this experimental approach by studying the effects of Gi and Gq GPCR pathways on insulin and glucagon secretion by expressing the designer receptors exclusively activated by designer drugs (DREADDs) hM4Di or hM3Dq. Activation of Gi signaling reduced insulin and glucagon secretion, while activation of Gq signaling stimulated glucagon secretion but had both stimulatory and inhibitory effects on insulin secretion which occur through changes in intracellular Ca2+. The experimental approach of combining pseudoislets with a microfluidic system, allowed the co-registration of intracellular signaling dynamics and hormone secretion and demonstrated differences in GPCR signaling pathways between human β and α cells.
TMPRSS2 and TMPRSS4 mediate SARS-CoV-2 infection of human small intestinal enterocytes

Both gastrointestinal symptoms and fecal shedding of SARS-CoV-2 RNA have been frequently observed in COVID-19 patients. However, whether SARS-CoV-2 replicate in the human intestine and its clinical relevance to potential fecal-oral transmission remain unclear. Here, we demonstrate productive infection of SARS-CoV-2 in ACE2+ mature enterocytes in human small intestinal enteroids. In addition to TMPRSS2, another mucosa-specific serine protease, TMPRSS4, also enhanced SARS-CoV-2 spike fusogenic activity and mediated viral entry into host cells. However, newly synthesized viruses released into the intestinal lumen were rapidly inactivated by human colonic fluids and no infectious virus was recovered from the stool specimens of COVID-19 patients. Our results highlight the intestine as a potential site of SARS-CoV-2 replication, which may contribute to local and systemic illness and overall disease progression.
Conformity and diversity among field isolates of Rhizobium leguminosarum bv. viciae, bv. trifolii, and bv. phaseoli revealed by DNA hybridization using chromosome and plasmid probes

A study was made of 113 bacterial isolates from root nodules of peas, lentils, red clover, and French beans, which had been grown in the same soil. Plasmid band profiles visualized in Eckhardt gels were analysed in relation to DNA hybridization patterns obtained by probing restricted total cellular DNA in Southern blots. Rhizobium leguminosarum chromosomal probes (plac12, pCOS309.1) and various symbiotic plasmid (nod gene region) probes were used. Dominant plasmid DNA hybridization patterns and more frequent combinations of plasmid patterns and chromosomal types were found among the isolates of each host plant species; the occurrence of alternative combinations indicated that genetic transfer and recombination among members of this soil population had taken place. About 40% of all isolates belonged to the same chromosomal type. Isolates of the same chromosomal type were often found with cryptic plasmids of the same size in different host plant species. Although isolates could not be assigned to their resp.
Amyloid-β Aggregation

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease in the growing population of elderly people. A hallmark of AD is the accumulation of plaques in the brain of AD patients. The plaques predominantly consist of aggregates of amyloid-β (Aβ), a peptide of 39–42 amino acids generated in vivo by specific, proteolytic cleavage of the amyloid precursor protein. There is a growing body of evidence that Aβ aggregates are ordered oligomers and the cause rather than a product of AD. The analysis of the assembly pathway of Aβ in vitro and biochemical characterization of Aβ deposits isolated from AD brains indicate that Aβ oligomerization occurs via distinct intermediates, including oligomers of 3–50 Aβ monomers, annular oligomers, protofibrils, fibrils and plaques. Of these, the most toxic species appear to be small Aβ oligomers. This article reviews the current knowledge of the mechanism of Aβ assembly in vivo and in vitro, as well as the influence of inherited amino acid replacements in Aβ and experimental conditions on Aβ aggregation. Challenges regarding the reproducible handling of the Aβ peptide for in vitro assembly studies are discussed.
MiBiOmics: an interactive web application for multi-omics data exploration and integration

Multi-omics experimental approaches are becoming common practice in biological and medical sciences underlining the need to design new integrative techniques and applications to enable the multi-scale characterization of biological systems. The integrative analysis of heterogeneous datasets generally allows to acquire additional insights and generate novel hypotheses about a given biological system. However, it can become challenging given the often-large size of omics datasets and the diversity of existing techniques. Moreover, visualization tools for interpretation are usually non-accessible to biologists without programming skills. Here, we present MiBiOmics, a web-based and standalone application that facilitates multi-omics data visualization, exploration, integration, and analysis by providing easy access to dedicated and interactive protocols. It implements classical ordination techniques and the inference of omics-based (multilayer) networks to mine complex biological systems, and identify robust biomarkers linked to specific contextual parameters or biological states. MiBiOmics provides easy-access to exploratory ordination techniques and to a network-based approach for integrative multi-omics analyses through an intuitive and interactive interface. MiBiOmics is currently available as a Shiny app at https://shiny-bird.univ-nantes.fr/app/Mibiomics and as a standalone application at https://gitlab.univ-nantes.fr/combi-ls2n/mibiomics.
Pairing your Sox: Identification of Sox11 partner proteins and interaction domains in the developing neural plate

Sox11, a member of the SoxC family of transcription factors, has distinct functions at different times in neural development. Studies in mouse, frog, chick and zebrafish show that Sox11 promotes neural fate, neural differentiation, and neuron maturation in the central nervous system. These diverse roles are controlled in part by spatial and temporal-specific protein interactions. However, the partner proteins and Sox11-interaction domains underlying these diverse functions are not well defined. Here, we identify partner proteins and the domains of Xenopus Sox11(xSox11) required for protein interaction and function during neurogenesis. Our data show that Sox11 co-localizes and interacts with Pou3f2 and Ngn2 in the anterior neural plate and in early neurons, respectively. We also demonstrate that xSox11 does not interact with Ngn1, a high affinity partner of Sox11 in the mouse cortex, suggesting that Sox11 has species-specific partner proteins. Additionally, we determined that the N-terminus including the HMG domain of xSox11 is necessary for interaction with Pou3f2 and Ngn2, and established a novel role for the N-terminal 46 amino acids in the establishment of placodal progenitors. This is the first identification of partner proteins for Xenopus Sox11 and of domains required for partner protein interactions and distinct roles in neurogenesis.
Guard Cell Starch Degradation Yields Glucose for Rapid Stomatal Opening in Arabidopsis[CC-BY]

Fast stomatal opening kinetics in response to light in Arabidopsis depends on a tight coordination between membrane ion transport and metabolic rearrangements. Starch in Arabidopsis (Arabidopsis thaliana) guard cells is rapidly degraded at the start of the day by the glucan hydrolases α-AMYLASE3 (AMY3) and β-AMYLASE1 (BAM1) to promote stomatal opening. This process is activated via phototropin-mediated blue light signaling downstream of the plasma membrane H+-ATPase. It remains unknown how guard cell starch degradation integrates with light-regulated membrane transport processes in the fine control of stomatal opening kinetics. We report that H+, K+, and Cl− transport across the guard cell plasma membrane is unaltered in the amy3 bam1 mutant, suggesting that starch degradation products do not directly affect the capacity to transport ions. Enzymatic quantification revealed that after 30 min of blue light illumination, amy3 bam1 guard cells had similar malate levels as the wild type, but had dramatically altered sugar homeostasis, with almost undetectable amounts of Glc. Thus, Glc, not malate, is the major starch-derived metabolite in Arabidopsis guard cells. We further show that impaired starch degradation in the amy3 bam1 mutant resulted in an increase in the time constant for opening of 40 min. We conclude that rapid starch degradation at dawn is required to maintain the cytoplasmic sugar pool, clearly needed for fast stomatal opening. The conversion and exchange of metabolites between subcellular compartments therefore coordinates the energetic and metabolic status of the cell with membrane ion transport.