Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternative foraging strategies enable a mountain ungulate to persist after migration loss

The persistence of many migratory ungulate populations worldwide is threatened due to anthropogenic impacts to seasonal ranges and migration routes. While many studies have linked migratory ungulate declines to migration disruption or loss, very few have explored the underlying factors that determine whether a population perishes or persists. In some cases, populations undergo severe declines and extirpation after migration loss; however, others appear able to persist as residents. We predict that to persist, populations must replace the traditional benefits of migration by altering the foraging strategies they employ as residents within one seasonal range. We propose the alternative foraging strategies (AFS) hypothesis as a framework for identifying various behavioral strategies that populations may use to cope with migration loss. We tested the hypothesis using the formerly migratory Teton bighorn sheep population in northwest Wyoming, which ceased migrating over 60 yr ago, but has persisted as a resident population. We used global positioning system data to evaluate winter and summer habitat selection and seasonal elevational movements for 28 adult female bighorn sheep (Ovis canadensis) from 2008 to 2010. Resource selection functions revealed that bighorn sheep employ winter foraging strategies to survive as residents by seeking out rugged, high-elevation, windswept ridgelines. Seasonal movement analyses indicated that bighorn sheep undergo a newly documented “abbreviated migration” strategy that is closely synchronized with vegetation green-up patterns within their one range. Bighorn sheep descend 500 m in elevation and travel up to 10 km in spring, gaining access to newly emergent forage approximately 30 d before it appears on their high-elevation winter and summer ranges. Our findings indicate that the Teton bighorn sheep population has persisted due to its habitat selection, AFS, and unique movement patterns, which allow migration loss to be mediated to some extent. The identification of AFS and the habitats that support them can help reveal the underlying benefits of migration and conserve populations in the face of future migration loss.
Jointly Modeling Individual Student Behaviors and Social Influence for Prediction Tasks

Prediction tasks about students such as predicting students' academic performances have practical real-world significance at both the student level and the college level. With the rapid construction of smart campuses, colleges not only offer residence and academic programs but also record students' daily life. The digital footprints provide an opportunity to offer better solutions for prediction tasks. In this paper, we aim to propose a general deep neural network which can jointly model student heterogeneous daily behaviors generated from digital footprints and social influence to deal with prediction tasks. To this end, we design a variant of LSTM and a novel attention mechanism to model the daily behavior sequence. The proposed LSTM is able to consider context information (e.g., weather conditions) while modeling the daily behavior sequence. The proposed attention mechanism can dynamically learn the different importance degrees of different days for every student. Based on behavior information, we propose an unsupervised way to construct a social network to model social influence. Moreover, we design a residual network based decoder to model the complex interactions between the features and get the predicted values such as future academic performances. Qualitative and quantitative experiments on two real-world datasets collected from a college have demonstrated the effectiveness of our model.
How the Quantum-inspired Framework Supports Keyword Searches on Multi-model Databases

With the trend of increasing vendors to develop various multi-model databases, people have reaped benefits from using a single and unified platform to manage both well-structured and NoSQL data. However, it causes a steep learning curve of mastering a multi-model query language for the specific multi-model database, not to mention various languages for different databases. Therefore, this research discusses the motivations of performing keyword searches on multi-model databases and then presents our current research. Methodologically, we attempt to use the quantum-inspired framework to query and explore multi-model databases. Firstly, we apply non-classical probabilities to estimate the relevance between a keyword query and candidate answers for guaranteeing getting good accuracy. Then we use the Principle Component Analysis (PCA) method to optimize the quantum language model for capturing good scalability. Finally, experiments show that our approaches are effective and our framework outperforms the state-of-the-art approaches.
AURORA: An Information Extraction System of Domain-specific Business Documents with Limited Data

Information extraction is a well-known topic that plays a critical role in many NLP applications as its outputs can be considered as an entrance step for digital transformation. However, there still exist gaps when applying research results to actual business cases. This paper introduces AURORA, an information extraction for domain-specific business documents. The intuition of AURORA is to use transfer learning for extraction. To do that, it utilizes the power of transformers for dealing with the limitation of training data in business cases and stacks additional layers for domain adaptation. We demonstrate AURORA in the context of actual scenarios where users are invited to experience two functions: fine-grained and whole paragraph extraction of Japanese business documents. A video of the system is available at http://y2u.be/xHQpYE41Tqw.
THE EFFECT OF ROOT STIMULANT ON ECTOMYCORRHIZAL COLONIZATION OF GNETUM SEEDLINGS (Gnetum gnemon L.)

Ectomycorrhizal fungi usually infect the young lateral roots. Root stimulant can induce the growth of new lateral roots after application of root pruning. This research is aimed at determining the exact amount of root stimulant concentration that suffices the condition of increased root colonization of gnetum seedling by mycorrhizal fungi. The research were tested in a greenhouse in a completely randomized design for 8 months. Four levels of root stimulant concentation was used, i.e. 0.00%, 1.00%, 1.25% and 1.67%. All treatments were treated with root pruning and ectomycorrhizal fungi (Scleroderma spp.) inoculation. Growth parameters observed were the number of new roots, the percentage of ectomycorrhizal colonization, diameter, height, shoot wet biomass, shoot dry biomass, root wet biomass, and root dry biomass. The results showed that all the roots of Gnetum seedlings infected by Scleroderma spp. Root stimulant had significant effects on increasing the growth of new roots. Root stimulant with concentration 1.67% gave the best growth response on all parameters except root dry biomass. The number of new roots was 35.50, the percentage of ectomycorrhizal colonization 58.47%, diameter 3.57 mm, height 48.21 cm, shoot wet biomass 8.57 g, shoot dry biomass 3.56 g, and root wet biomass 5.81 g. Key words: Gnetum gnemon, mycorrhizal colonization, plant growth, root stimulant, Scleroderma
CC-News-En: A Large English News Corpus

We describe a static, open-access news corpus using data from the Common Crawl Foundation, who provide free, publicly available web archives, including a continuous crawl of international news articles published in multiple languages. Our derived corpus, CC-News-En, contains 44 million English documents collected between September 2016 and March 2018. The collection is comparable in size with the number of documents typically found in a single shard of a large-scale, distributed search engine, and is four times larger than the news collections previously used in offline information retrieval experiments. To complement the corpus, 173 topics were curated using titles from Reddit threads, forming a temporally representative sampling of relevant news topics over the 583 day collection window. Information needs were then generated using automatic summarization tools to produce textual and audio representations, and used to elicit query variations from crowdworkers, with a total of 10,437 queries collected against the 173 topics. Of these, 10,089 include key-stroke level instrumentation that captures the timings of character insertions and deletions made by the workers while typing their queries. These new resources support a wide variety of experiments, including large-scale efficiency exercises and query auto-completion synthesis, with scope for future addition of relevance judgments to support offline effectiveness experiments and hence batch evaluation campaigns.
Are Negative Links Really Beneficial to Network Embedding?: In-Depth Analysis and Interesting Results

In this paper, we start by pointing out the limitations on the validation of existing signed network embedding (NE) methods. To address the limitations, we design the two research questions: (1) are signed NE methods consistently more effective in various types of tasks than unsigned NE methods? (2) in signed NE methods, does the utilization of negative links help provide higher accuracy in various tasks? To answer the questions, we present our evaluation framework consisting of three components: (1) five signed network datasets; (2) six signed and two unsigned NE methods; (3) five types of tasks. Through extensive experiments on our evaluation framework, we demonstrate that additional utilization of negative links really helps only in some tasks related to negative links but not in tasks related to positive links.
Probabilistic Dynamic Non-negative Group Factor Model for Multi-source Text Mining

Nonnegative matrix factorization (NMF) is a popular approach to model data, however, most models are unable to flexibly take into account multiple matrices across sources and time or apply only to integer-valued data. We introduce a probabilistic, Gaussian Process-based, more inclusive NMF-based model which jointly analyzes nonnegative data such as text data word content from multiple sources in a temporal dynamic manner. The model collectively models observed matrix data, source-wise latent variables, and their dependencies and temporal evolution with a full-fledged hierarchical approach including flexible nonparametric temporal dynamics. Experiments on simulated data and real data show the model out-performs, comparable models. A case study on social media and news demonstrates the model discovers semantically meaningful topical factors and their evolution
The complete mitochondrial genome of the cigarette beetle, Lasioderma serricorne (Coleoptera: Anobiidae)

Abstract The cigarette beetle, Lasioderma serricorne (Fabricius), is an important pest of stored commodities and distributed widely in the world. Here, we report the complete mitochondrial genome of L. serricorne which was 15,958 bp and composed of 13 protein-coding genes (PCGs), two rRNA genes, 22 tRNA genes and a control region. The gene order and orientation of L. serricorne were identical to those of other Coleopteran mitogenomes. ATG, ATA, ATT, ATC, TTG were initiation codons and TAA, TAG, T were termination codons. All 22 tRNA genes were predicted with a typical cloverleaf structure except for trnS1 (AGN). Phylogenetic analysis performed using 13 PCGs with 14 other beetles showed that L. serricorne is closely related to Stegobium paniceum, which agree with the conventional taxonomy.
The study of apple, Malus x domestica, fruit cell division and expansion in vivo and in vitro

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How do Earthworms in Soil Respond to Nitrification Inhibitor? - An investigation from A Microbial Aspect

A laboratorial incubation experiment was conducted to test the response of earthworm (Eisenia fetida)-related microbes to the application of dicyandiamide (DCD), a nitrification inhibitor. The potential of ammonium oxidation in soil was inhibited during the 90 days cultivation. At day 90, it was observed the soil surface was drilled more severely by earthworms in DCD treatment than E treatment. Meanwhile, comparedwith E treatment, the results of soil community level physiological profiles indicated that the potential of carboxylic acids and carbohydrates utilization in soil was enhanced by DCD addition.The active microbial biomass was increased by 43% andthe polyphenol oxidase activity was enhanced by 14% in DCD treated soil than control. More importantly, the number of denitrifying bacteria in earthworm gut content at day 90 was markedlydeclined from 1.79×10 10 g [fresh wt] -1 in control to less than 1×10 6 g [fresh wt] -1 in DCD treatment.These results implied that DCD application was anabiotic selection pressureon the activities of earthworms and themicrobes both in soil and in earthworm, which might led to a shift of interaction between earthworms and the microbes.
Effects of photoperiod, thermoperiod, and salt stress on Gymnocarpos decandrus seeds: potential implications in restoration ecology activities

Gymnocarpos decandrus (Caryophyllaceae) is a perennial plant widely used for its ability to protect the soil from erosion. The aim of this study was to evaluate the effects of salt stress on its seed germination, with the potential objective to sow its seeds instead of planting adult individuals in salt damaged areas, greatly reducing the economic costs of restoration ecology activities. Germination tests were conducted under two photoperiods and three thermoperiods and with several NaCl concentrations. The ability of seeds to recover their germination after the salt exposure was also evaluated. The highest germination occurred at 20/30°C in the light, but no seed germinated in the salt substrate. Only a few seeds (no more than 20%) recovered their germination and only at the lowest salinity highlighting a high glycophytic character for this species. The inability of its seeds to germinate in saline soils and to have successful recovery shows that G. decandrus may be used in rehabilitation programs of deg.
Neumania kyrgyzica sp. nov. a new water mite from Kyrgyzstan based on morphological and molecular data (Acari, Hydrachnidia: Unionicolidae)

Abstract Water mites of the genus Neumania have been found worldwide. In the present study we used morphological data and DNA barcoding to describe a new species of the genus Neumania, N. kyrgyzica sp. nov. from Kyrgyzstan. The results supported the genetic separation between the new species and species examined in this study (N. deltoides, N. imitata, N. limosa, N. spinipes and N. vernalis). The lowest K2P divergence (11.7%) was found between the new species and N. limosa (Koch, 1836), a species widely distributed in the Palaearctic region. Morphologically, the new species seems to be most similar to N. alticola (Stoll, 1887), an abundant and widespread species in the extreme northern Neotropics.
Mixing the waters: a linear hybrid zone between two riverine Neotropical cardinals (Paroaria baeri and P. gularis)

ABSTRACT Amazonian rivers have been more frequently conceptualised as barriers rather than as habitats for birds with their own ecological and biogeographic histories. However, many river-restricted bird species have differentiated within the formidable network formed by the Amazon and its tributaries. Here we demonstrate that the riverine-distributed Crimson-fronted Cardinal (Paroaria baeri) is narrowly distributed along the middle Rio Araguaia basin, where it comes into contact and hybridises with the geographically widespread Red-capped Cardinal (P. gularis). This one-dimensional hybrid zone, which is situated over ca.160 km along the Araguaia and Javaés Rivers, appears to be of recent origin. Admixed individuals between the non-sister P. baeri and P. gularis are phenotypically intermediate between the parental species, and superficially resemble the geographically disjunct and phylogenetically distant Masked Cardinal (P. nigrogenis). Two phenotypically admixed specimens were confirmed as such based on sequences of the mitochondrial Cytb and the Z-linked MUSK gene. Field observations and genetic data indicate that P. baeri × P. gularis hybrids are capable of producing viable offspring, but more data are necessary to confirm hybrid viability and fertility. The non-sister hybridising species P. baeri and P. gularis last shared a common ancestor 1.8–2.8 mya (uncorrected genetic p-distance of 4%), which corresponds closely to when the Araguaia/Tocantins river basin last discharged directly into the Amazon.
Physiological constraints and evolutionary trade-offs underlying bacterial aging, caloric restriction and longevity

The evolutionary theories of aging and the disposable soma theory in particular, have been the theoretical basis for a recent surge of animal aging research. Yet their central assumption about the physiology of cellular maintenance and repair has not been empirically tested. In this thesis, I analysed the physiology of E.coli aging under carbon starvation, as a model system to empirically validate evolutionary theories of aging. Microfluidic tools are used to isolate large populations of isogenic single E.coli cells, and to achieve homogenous carbon starvation. Despite sharing the same genetical background and environmental conditions, individual cells in the population exhibit significant variations in lifespans and causes of death. Distributions of lifespans exhibit typical features of the aging process, often seen in animal and human demographic studies. The rate of aging can be altered by mutations of the general stress response pathway. Resembling caloric restriction induced longevity, the general stress response pathway extends starvation lifespans of E.coli by attenuating the effect of aging at the expense of immediate needs of the cells. A quantitative model of this physiological trade-off is constructed and correctly predicted experimental observations. As a conclusion, I substantiate the dis posable soma theory of aging with the physiological details ofE.coli aging in starvation
Turning Round: Optimizing the Anti-Inflammatory Properties of Equine Bone Marrow Derived Mesenchymal Stem Cells for Osteoarthritis Through Three-Dimensional Culture

Osteoarthritis (OA) is a degenerative disease of diarthrodial joints causing pain and loss of joint function. Etiology is heterogeneous, but commonly involves inflammation arising from impairment of normal tissue homeostasis and/or function. A cycle of low-grade inflammation and global tissue degradation causes alteration of tissue morphology and function via primary mechanisms or inability to withstand physiological forces. Current therapies variably ameliorate symptoms but do not modify progression. Mesenchymal stem cells (MSCs) have multi-modal properties but are ineffective in ameliorating equine OA. However, anti-inflammatory activities of bone marrow derived MSCs (BMSCs) are enhanced by three-dimensional spheroid culture so equine BMSC (eBMSC) spheroids could inhibit intra-articular inflammation. The overarching hypothesis is that eBMSCs can be enhanced to produce an allogeneic eBMSC therapy that inhibits intra-articular inflammation. In vitro experiments compared differences in anti-inflammatory phenotype between spheroid and traditionally cultured monolayer eBMSCs, the viability and health of eBMSC spheroids administered through needles, and the effects of allogeneic donor on the anti-inflammatory potential of eBMSC spheroids. A model of equine LPS induced synovitis was used to investigate anti-inflammatory efficacy of spheroid eBMSCs compared to placebo or monolayer eBMSCs in vivo. eBMSCs aggregate into spheroids that have stable stem cell marker expression with increased secretion and gene expression of IL-6 and PGE2, and gene expression of SDF-1 and TSG-6. IFN and TNF were not produced by eBMSC spheroids and IL-10 production varied between individuals. Spheroids maintain higher viability and lower senescence than monolayer eBMSCs after injection through a needle and form in high-throughput culture without detrimental effects on expression of TSG-6, IL-6 and PGE synthases that denote an anti-inflammatory phenotype. Additionally, there is significant variation in this phenotype depending on the eBMSC donor. eBMSC spheroids reduced total nucleated cell counts and objective lameness measurements at peak levels of intra-articular inflammation compared to monolayer cultured eBMSCs in vivo. In summary, spheroids increase anti-inflammatory potential of eBMSCs and are practical for clinical use. Increased anti-inflammatory efficacy was demonstrated in a model of in vivo inflammation. This dissertation provides an understanding of the anti-inflammatory activities of eBMSC spheroids that can be used to develop an OA therapy. TURNING ROUND: OPTIMIZING THE ANTI-INFLAMMATORY PROPERTIES OF EQUINE BONE MARROW DERIVED MESENCHYMAL STEM CELLS FOR OSTEOARTHRITIS THROUGH THREE-DIMENSIONAL CULTURE
Growth of the burrowing crayfish Parastacus nicoleti (Philippi, 1882) (Crustacea, Decapoda, Parastacidae)

We examined the individual growth of the burrowing crayfish Parastacus nicoleti (Philippi, 1882) based on a sample of 1,425 specimens. Individuals were collected monthly from November 1981 to December 1982, in the marshy wetlands of the “Pangal” homestead in Reumen, southern Chile. The Cephalothorax Length (CL) and Body Weight (BW) were recorded for all specimens. The asymptotic length parameters (L∞) and the growth coefficient (k) were established using the Gulland and Holt method (1959). The t0 parameter was obtained through the inverse von Bertalanffy equation and the length-weight relationship was determined according to the equation proposed by Ricker (1975). The asymptotic size and weight were 45.754 mm and 18.50 g, respectively. The growth constant was 0.703/year. Estimated longevity was 4.32 years. We concluded that P. nicoleti is a relatively small species with poor growth indicators for size and weight and, consequently, is not an attractive species for commercial aquaculture purposes.