Miracle-dz/UniFAR-FTUs huggingface dataset:
Excluding Flying Insects During Flowering does not Affect Soybean Yield

Abstract. The possible role of pollinators enhancing soybean production has been an ongoing topic of study. The effect of flower visitation, especially by honey bees, Apis mellifera L. , in this self-pollinated crop has resulted in no benefit increasing soybean yield, or at times a significant impact on grain production, differences that might be caused by the influence of multiple field condition variables. In this study, an experimental design that excludes insects from soybean plants during the ∼20-day flowering period was used. Results indicated that he number of pods per plant, seeds per pod, and grain yield were not different in plants covered with mesh that prevented insect visitation to flowers, compared with adjacent soybean plants not covered. The single-season studies showed that despite a large number of active honey bee hives 25-50 m away from the evaluated soybean plants, the insects rarely entered the fields, and those that did, spent no time foraging, even when more than 5 million soybean flowers per hectare were available at a very short distance from their hives.
Heteroblasty on Chatham Island: a comparison with New Zealand and New Caledonia.

We used a comparative approach to investigate heteroblasty in the Chatham Islands. Heteroblasty refers to abrupt changes in the morphology of leaves and shoots with plant height. Common on isolated islands such as New Caledonia and New Zealand, which once had flightless, browsing birds, heteroblasty is hypothesised to be an adaptation to deter bird browsing. The Chatham Islands are a small archipelago located 800 km off the east coast of New Zealand, which has clear floristic links to New Zealand. However, unlike New Caledonia and New Zealand, the Chathams never had flightless, browsing birds. We investigated heteroblasty on the Chatham Islands by: (1) comparing height-related changes in leaf morphology and branching architecture in several plant taxa with heteroblastic relatives on the New Zealand mainland; (2) characterising changes in leaf morphology in heteroblastic tree species endemic to the Chathams; and (3) comparing overall trends in leaf heteroblasty on the Chathams with New Caledonia and New Zealand. Reversions to homoblasty were observed in the three Chatham Island taxa with heteroblastic relatives on the New Zealand mainland. However, two endemic tree species were clearly heteroblastic; both produced dramatically larger leaves as juveniles than as adults. Inter-archipelago comparisons showed that this trend in leaf morphology is rare among heteroblastic species in New Caledonia and New Zealand. Therefore, while some of our results were consistent with the hypothesis that heteroblasty is an adaptation to avoid bird browsing, other processes also appear to have shaped the expression of heteroblasty on Chatham Island.
A Study of the Impact of Internet-Based Instruction Integrated Innovation Education on University Student Entrepreneurial Team Collaboration and Strategic Innovation

With the advent of knowledge economy, the competition of comprehensive national power gradually has shifted to talent competition. The cultivation of innovative talents and the incubation of student entrepreneurial teams are the primary educational goals of universities, which is an important part of the national innovation system. University student entrepreneurial teams present the attribute of high technology and unique knowledge advantage. The persistent innovation of student entrepreneurial teams is attributed to knowledge playing a critical role. In particular, in the knowledge-based economic era, student entrepreneurial teams with speed, connection, and intangible value creation have transformed the partly labor-intensive model into a knowledge-intensive competition model. Taking university student entrepreneurial teams as the research object, a total of 500 copies of questionnaire were distributed and 386 valid copies were retrieved, with a retrieval rate of 77%. Through the questionnaire survey, students’ awareness, emotion, and will of innovation in innovation education are understood, and their cognition and intention of team cooperation and strategic innovation are investigated. The research results are concluded as follows: (1) Innovation education presents significantly positive correlations with collaboration. (2) Collaboration shows remarkably positive correlations with strategic innovation. (3) Innovation education reveals notably positive correlations with strategic innovation. According to the research result, suggestions are proposed, expecting that China’s university student entrepreneurial teams could acquire the advantage of technological innovation by applying the opportunities of broadband and wireless network infrastructure and developing innovative applications and entrepreneurial models.
Moral Transgressions by Groups: What Drives Individual Voting Behavior?

We conduct an experiment where subjects are matched in groups of three and vote on a moral transgression. Analyzing different voting rules, the frequency of votes for the moral transgression increases with the number of votes required for it. This effect persists when considering pivotal votes only, which eliminates opportunities to save on own moral costs and to rely instead on sufficiently many votes for the transgression by other group members. A series of novel treatments allows us to identify guilt sharing and preferences for consensual voting as empirically relevant and independent drivers of voting behavior.
Probing machine-learning classifiers using noise, bubbles, and reverse correlation

Background Many scientific fields now use machine-learning tools to assist with complex classification tasks. In neuroscience, automatic classifiers may be useful to diagnose medical images, monitor electrophysiological signals, or decode perceptual and cognitive states from neural signals. However, such tools often remain black-boxes: they lack interpretability. A lack of interpretability has obvious ethical implications for clinical applications, but it also limits the usefulness of these tools to formulate new theoretical hypotheses. New method We propose a simple and versatile method to help characterize the information used by a classifier to perform its task. Specifically, noisy versions of training samples or, when the training set is unavailable, custom-generated noisy samples, are fed to the classifier. Multiplicative noise, so-called “bubbles”, or additive noise are applied to the input representation. Reverse correlation techniques are then adapted to extract either the discriminative information, defined as the parts of the input dataset that have the most weight in the classification decision, and represented information, which correspond to the input features most representative of each category. Results The method is illustrated for the classification of written numbers by a convolutional deep neural network; for the classification of speech versus music by a support vector machine; and for the classification of sleep stages from neurophysiological recordings by a random forest classifier. In all cases, the features extracted are readily interpretable. Comparison with Existing Methods Quantitative comparisons show that the present method can match state-of-the art interpretation methods for convolutional neural networks. Moreover, our method uses an intuitive and well-established framework in neuroscience, reverse correlation. It is also generic: it can be applied to any kind of classifier and any kind of input data. Conclusions We suggest that the method could provide an intuitive and versatile interface between neuroscientists and machine-learning tools. Highlights The heuristics of black-box classifiers can be probed with noisy inputs The relevant features can be visualised in the input representation space The method applies to any kind of data such as 2D images or 1D time series It applies to any classifier such as deep neural networks, support vector machines, random forests
Marine Dadabacteria exhibit genome streamlining and phototrophy-driven niche partitioning

The remineralization of organic material via heterotrophy in the marine environment is performed by a diverse and varied group of microorganisms that can specialize in the type of organic material degraded and the niche they occupy. The marine Dadabacteria are cosmopolitan in the marine environment and belong to a candidate phylum for which there has not been a comprehensive assessment of the available genomic data to date. Here in, we assess the functional potential of the marine pelagic Dadabacteria in comparison to members of the phylum that originate from terrestrial, hydrothermal, and subsurface environments. Our analysis reveals that the marine pelagic Dadabacteria have streamlined genomes, corresponding to smaller genome sizes and lower nitrogen content of their DNA and predicted proteome, relative to their phylogenetic counterparts. Collectively, the Dadabacteria have the potential to degrade microbial dissolved organic matter, specifically peptidoglycan and phospholipids. The marine Dadabacteria belong to two clades with apparent distinct ecological niches in global metagenomic data: a clade with the potential for photoheterotrophy through the use of proteorhodopsin, present predominantly in surface waters up to 100 m depth; and a clade lacking the potential for photoheterotrophy that is more abundant in the deep photic zone.
Behavioral regulation is associated with educational attainment through self-efficacy in ethnic minority preadolescents

In the current study we investigated whether self-efficacy mediated the relation between selfregulation (effortful control and executive function) and educational attainment in secondary school tracks in 70 Turkish minority preadolescents in the Netherlands. Family SES and host language (Dutch) vocabulary were also included as predictors for educational attainment. Self-efficacy fully mediated the relation between effortful control and educational attainment, indicating that behavioral regulation provides children with self-confidence regarding their academic abilities and motivation, which in turn facilitates academic performance. Executive function, on the other hand was not linked to self-efficacy or educational attainment. Family socioeconomic status and Dutch vocabulary showed direct and indirect associations with educational attainment via self-efficacy. Overall, behavioral self-regulation contributes to positive academic adaptation and resilience in ethnic minority students in early adolescence.
External Treatment of Broiler Chickens with Lactic-Acid-Producing Bacteria Before Slaughter 1

Lactic-acid-producing bacterial cultures were applied to the skin of live broilers 24 hours before slaughter to determine whether inoculation with the cultures could affect the numbers of bacteria that are normally found on the skin of processed broiler carcasses. The cultures contained 10,000 to 100,000 cfu/mL and were suspended in 250 mL of a pH 6.0 nutrient medium (including glucose, peptone, beef extract, yeast extract, a surfactant, and salts) intended to enhance the survival and growth of the cultures. With broilers suspended by the feet, feathers were moved aside and the liquid suspension was sprayed directly on the skin. Sprayed broilers were then returned to a pen. In each of three replications, 4 six-wk-old broilers were sprayed and 4 broilers were kept as untreated controls. The following day, broilers were processed in a research processing facility and defeathered carcasses were sampled by rinsing for 1 min in 200 mL o f peptone water after removal of heads and feet. Coliforms, E. coli, lactic-acid bacteria, and Campylobacter in carcass rinses were enumerated by standard methods. After removal of aliquots for plating, the remaining sample volume was enriched to detect Salmonella. No differences were found in log (cfu/mL) of coliforms, 10 E. coli, or lactic-acid bacteria between the treated and control carcasses. Salmonella bacteria were present on some carcasses, but with no difference between treatments. Campylobacter spp. were present in only one replication, so numbers of Campylobacter could not be analyzed statistically. Spraying lactic-acid- producing bacteria with nutrients on the skin of live broilers on the day before processing appears to have no effect on numbers of bacteria that are present on the skin after defeathering.
Companion vaccine Bioinformatic design tool reveals limited functional genomic variability of SARS-Cov-2 Spike Receptor Binding Domain Domain

Tracking the genetic variability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for several reasons, such as to identify target sequences to generate robust vaccines and neutralizing monoclonal antibodies; to track viral genetic temporal and geographic evolution; and to mine for viral variants associated with reduced or increased severity. Several online tools and bioinformatic analyses have been released for this purpose; four main viral clades have been
Mentoring and Schooling Decisions: Causal Evidence

Inequality of opportunity strikes when two children with the same academic performance are sent to different quality schools because their parents differ in socio-economic status. Based on a novel dataset for Germany, we demonstrate that children are significantly less likely to enter the academic track if they come from low socio-economic status (SES) families, even after conditioning on prior measures of school performance. We then provide causal evidence that a low-intensity mentoring program can improve long-run education outcomes of low SES children and reduce inequality of opportunity. Low SES children, who were randomly assigned to a mentor for one year are 20 percent more likely to enter a high track program. The mentoring relationship affects both parents and children and has positive long-term implications for children's educational trajectories.
Aluminum bioaccumulation and tolerance in Plantago algarbiensis Samp. and Plantago almogravensis Franco, assessed by using in vitro cultures and micropropagated plants

vii RESUMO ix CHAPTER 1: General introduction 1 1.1. Acidic soils and aluminum 3 1.2. Aluminum toxicity in plants 5 1.2.1. Plant growth inhibition 5 1.2.2. Changes on nutrient uptake 6 1.2.3. Photosynthesis inhibition 8 1.2.4. Oxidative stress 9 1.3. Aluminum hyperaccumulation 12 1.4. Aluminum detoxification mechanisms 14 1.4. 1. Mechanisms of aluminum resistance 14 1.4. 2. Mechanisms of aluminum tolerance 17 1.4. 3. Organic acids metabolism 18 1.5. The genus Plantago 19 1.5. 1. The species Plantago almogravensis and Plantago algarbiensis 20 1.6. Micropropagation 24 1.7. Objectives 29 1.8. References 30 CHAPTER 2: Micropropagation and conservation of endangered species Plantago algarbiensis and P. almogravensis 43 2.1. Abstract 45 2.2. Introduction 46 2.3. Material and methods 47 2.3. 1. Establishment of in vitro seedlings and culture conditions 47 2.3. 2. Shoot multiplication 47 2.3. 3. Rooting 47 2.3. 4. Acclimatization 48 2.3. 5. Statistical analysis 48 2.4. Results and discussion 49 2.5. References 54 CHAPTER 3: The influence of low pH on in vitro growth and biochemical parameters of Plantago almogravensis and P. algarbiensis 57
Effect of Lactulose on the Composition and Metabolic Activity of the Human Faecal Flora

The effect of dietary supplementation with lactulose (3 g/d for 2 wk) on the faecal flora and faecal bacterial metabolism was studied in eight healthy volunteers. During the intake of lactulose, the number of bifidobacteria increased significantly ( P < 0.01), whereas the numbers of lecithinase-positive clostridia, including Clostridium perfringens , and Bacteroidaceae decreased ( P < 0.05) compared to values before and after the intake. Faecal indole, skatol and phenols, and faecal β-glucuronidase, nitroreductase and azoreductase activities were decreased significantly ( P < 0.05) after 7-14 d of treatment. Mean faecal pH decreased from 7.0 to 6.4, and water content increased 3.5-5.3 per cent during lactulose ingestion. Keywords: Lactulose; Faecal flora; Faecal bacterial metabolism.
Dispersal ability determines the genetic effects of habitat fragmentation in three species of aquatic insect

1. The dispersal ability of species and the geographic scale of habitat fragmentation both may influence the extent of gene flow between fragments, but their interactions have rarely been tested, particularly among co-occurring species. 2. Population genetic structures of three species of aquatic insect were compared in streams fragmented by reservoirs and in unfragmented streams in north-eastern Japan, using 52, 37, and 58 RAPD markers. The three species studied included a strong disperser Cincticostella elongatula (Ephemeroptera: Ephemerellidae), an intermediate disperser Stenopsyche marmorata (Trichoptera: Stenopsychidae), and a weak disperser Hydropsyche orientalis (Trichoptera: Hydropsychidae). 3. The patterns of genetic isolation by distance (IBD) supported a priori hypotheses of dispersal ability. The strong disperser (C. elongatula) exhibited significant IBD only at the largest spatial scale studied (among drainages, r=0.50, P<0.01). The intermediate disperser (S. marmorata) showed IBD both within (r=0.22, P<0.01) and among (r=0.45, P<0.01) drainages. The weak disperser (H. orientalis) did not exhibit significant IBD at any scale. 4. Pairwise genetic differentiation (θ) indicated that neither the weak disperser nor the strong disperser were genetically differentiated above and below reservoirs when compared with reference sites. This was in contrast to previous results for S. marmorata, for which subpopulations were genetically fragmented across larger (>4.1 km), but not smaller (<2.9 km) reservoirs. 5. We suggest that intermediate dispersers, i.e. those at equilibrium between migration and genetic drift within drainages, are more likely to be affected by fragmentation than either strong or weak dispersers. Intermediate dispersers could therefore be used as indicator species in studies aimed at detecting the effects of distance between habitat fragments (e.g. reservoir size) for conservation planning. Copyright © 2010 John Wiley & Sons, Ltd.
Antagonistic Effects of Trichoderma Species in Biocontrol of Armillaria Mellea in Fruit Trees in Iran

Root and butt rot caused by species of Armillaria is one of the most serious diseases of fruit and forest trees in Iran. In this study, antagonistic effects of Trichoderma in biocontrol of Armillaria were investigated. Armillaria mellea was isolated from infected roots and butts of cherry and almond trees and identified with pairing tests method. Trichoderma species were recovered from rhizomorphs and around soil of Armillaria infected roots. Trichoderma species identified were T. virens (nine isolates) and T. harzianum (three isolates). Trichoderma discs were placed onto cultures of Armillaria to study an- tagonistic effects. All isolates of Trichoderma colonized Armillaria colonies within 5-7 days. Volatile compounds of Trichoderma isolates inhibited Armillaria colony growth and rhizomorph formation. Mechanisms of biocontrol were investigated by light and scanning electron microscopy, these in- cluded penetration of Trichoderma hyphae in rhizomorphs, colonization of rhizomorphs by Tricho- derma mycelia, colonization of apex meristemic center and apical buds of rhizomorphs, sporulation of Trichoderma in outer and inner surface of rhizomorphs, degeneration and lysis of rhizomorph tissue, and discharge of rhizomorph content.
Preventing Critical Scoring Errors in Short Answer Scoring with Confidence Estimation

Many recent Short Answer Scoring (SAS) systems have employed Quadratic Weighted Kappa (QWK) as the evaluation measure of their systems. However, we hypothesize that QWK is unsatisfactory for the evaluation of the SAS systems when we consider measuring their effectiveness in actual usage. We introduce a new task formulation of SAS that matches the actual usage. In our formulation, the SAS systems should extract as many scoring predictions that are not critical scoring errors (CSEs). We conduct the experiments in our new task formulation and demonstrate that a typical SAS system can predict scores with zero CSE for approximately 50% of test data at maximum by filtering out low-reliablility predictions on the basis of a certain confidence estimation. This result directly indicates the possibility of reducing half the scoring cost of human raters, which is more preferable for the evaluation of SAS systems.
A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction

Recently BERT has achieved a state-of-the-art performance in temporal relation extraction from clinical Electronic Medical Records text. However, the current approach is inefficient as it requires multiple passes through each input sequence. We extend a recently-proposed one-pass model for relation classification to a one-pass model for relation extraction. We augment this framework by introducing global embeddings to help with long-distance relation inference, and by multi-task learning to increase model performance and generalizability. Our proposed model produces results on par with the state-of-the-art in temporal relation extraction on the THYME corpus and is much “greener” in computational cost.
Efficient Automatic Punctuation Restoration Using Bidirectional Transformers with Robust Inference

Though people rarely speak in complete sentences, punctuation confers many benefits to the readers of transcribed speech. Unfortunately, most ASR systems do not produce punctuated output. To address this, we propose a solution for automatic punctuation that is both cost efficient and easy to train. Our solution benefits from the recent trend in fine-tuning transformer-based language models. We also modify the typical framing of this task by predicting punctuation for sequences rather than individual tokens, which makes for more efficient training and inference. Finally, we find that aggregating predictions across multiple context windows improves accuracy even further. Our best model achieves a new state of the art on benchmark data (TED Talks) with a combined F1 of 83.9, representing a 48.7% relative improvement (15.3 absolute) over the previous state of the art.
Adaptation of Multilingual Transformer Encoder for Robust Enhanced Universal Dependency Parsing

This paper presents our enhanced dependency parsing approach using transformer encoders, coupled with a simple yet powerful ensemble algorithm that takes advantage of both tree and graph dependency parsing. Two types of transformer encoders are compared, a multilingual encoder and language-specific encoders. Our dependency tree parsing (DTP) approach generates only primary dependencies to form trees whereas our dependency graph parsing (DGP) approach handles both primary and secondary dependencies to form graphs. Since DGP does not guarantee the generated graphs are acyclic, the ensemble algorithm is designed to add secondary arcs predicted by DGP to primary arcs predicted by DTP. Our results show that models using the multilingual encoder outperform ones using the language specific encoders for most languages. The ensemble models generally show higher labeled attachment score on enhanced dependencies (ELAS) than the DTP and DGP models. As the result, our best models rank the third place on the macro-average ELAS over 17 languages.
University of Tsukuba’s Machine Translation System for IWSLT20 Open Domain Translation Task

In this paper, we introduce University of Tsukuba’s submission to the IWSLT20 Open Domain Translation Task. We participate in both Chinese→Japanese and Japanese→Chinese directions. For both directions, our machine translation systems are based on the Transformer architecture. Several techniques are integrated in order to boost the performance of our models: data filtering, large-scale noised training, model ensemble, reranking and postprocessing. Consequently, our efforts achieve 33.0 BLEU scores for Chinese→Japanese translation and 32.3 BLEU scores for Japanese→Chinese translation.