Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of vertical and horizontal transmission in the assembly of seed fungal endophyte communities in wheat and wheat wild relatives

Plants acquire fungal endophytes either from the environment or from their progenitors. These transmission modes are central in shaping the community as they affect species composition and balance. We studied fungal endophyte communities (FEC) and their seed-to-seed transmission in three Triticeae plant species: bread wheat (Triticum aestivum), wild emmer wheat (Triticum turgidum dicoccoides) and wild barley (Hordeum spontaneum). The FECs in the three plant species contained similar fungal taxa, however they were overall different. The most prevalent class of fungi was Dothideomycetes, which was dominated by the taxon Alternaria infectoria. In field collected plants, the number of taxa in the seeds was less than half the number in stems, with close to 90% of the taxa found in seeds also found in stems. Growing the same plant species in a controlled environment infection greatly affected their FEC composition; the FECs in the stems and seeds of these plants were richer and more diverse than in the original seeds, they were not dominated by a single taxon, and FECs in the new seeds had a similar richness and diversity to the stem FECs, with only 40% overlap. The controlled environment experiment confirmed vertical transmission of certain species, but also showed that external infection of the seeds is the main source for specific taxa, including A. infectoria. Collectively, our results show that many taxa can reach the seeds through the internal pathway, albeit in different abundance, and both internal and external sources significantly affect the composition of seed FECs.
A ubiquitination-mediated degradation system to target phospho-14-3-3-binding-motif embedded proteins

The phosphorylation of 14-3-3 binding motif is involved in many cellular processes. A strategy that enables targeted degradation of phospho-14-3-3-binding-motif embedded (P-14-3-3-BME) proteins for studying their functions is highly desirable for basic research. Here, we report a phosphorylation-induced, ubiquitin-proteasome-system-mediated targeted protein degradation (TPD) strategy that allows specific degradation of P-14-3-3-BME proteins. Specifically, by ligating a modified von Hippel-Lindau E3-ligase with an engineered 14-3-3 bait, we generated a protein chimera referred to as Targeted Degradation of P-14-3-3-BME Protein (TDPP). TDPP can serve as a universal degrader for P-14-3-3-BME proteins based on the specific recognition of the phosphorylation in 14-3-3 binding motifs. TDPP shows high efficiency and specificity to a difopein-EGFP reporter, general and specific P-14-3-3-BME proteins. TDPP can also be applied for the validation of P-14-3-3-BME proteins. These results strongly support TDPP as a powerful tool for 14-3-3 related research.
TaKG: A New Dataset for Paragraph-level Table-to-Text Generation Enhanced with Knowledge Graphs

Table-to-text generation refers to a task that generates text using information provided by a given fact table. We introduce TaKG, a new table-to-text generation dataset with the following highlights: (1) TaKG defines a long-text (paragraph-level) generation task as opposed to well-established short-text (sentence-level) generation datasets. (2) TaKG is the first large-scale dataset for this task, containing three application domains and ∼ 750,000 samples. (3) To address the divergence phenomenon, TaKG enhances table input using external knowledge graphs, extracted by a new Wikidata-based method. We then propose a new Transformer-based multimodal sequence-to-sequence architecture for TaKG that integrates two pretrained language models RoBERTa and GPT-2. Our model shows reliable performance on long-text generation across a variety of metrics, and out-performs existing models for short-text generation tasks.
Convolutional Neural Network for Audibility Assessment of Acoustic Alarms

In noisy workplaces, the audibility of acoustic alarms is essential to ensure worker safety. In practice, some criteria are required in international standards to make sure that the alarms are “clearly au-dible”. However, the recommendations may lead to overly loud alarms, thereby exposing workers to unnecessary high sound levels, especially when ambient sound levels are high themselves. For this reason, it appears necessary to properly assess the audibility of alarms at design stage. Existing psychoacoustical meth-ods rely on repeated subjective measurements at different sound levels and therefore require time-consuming procedures. In addition, they must be repeated each time the alarm or sound environment changes. To overcome this issue, we propose a data-driven approach to estimate the audibility of new alarm signals without having to test each new condition experimentally. In this study, a convolutional neural network model is trained to perform a binary classification task on short sound clips labeled with the outcomes of psychoacoustical experiments. We propose a proof of concept of this approach and analyze its performance depending on the data used at training and the temporal context used by the networks to predict the audibility of the alarm.
Spa: On the Sparsity of Virtual Adversarial Training for Dependency Parsing

Virtual adversarial training (VAT) is a powerful approach to improving robustness and performance, leveraging both labeled and unlabeled data to compensate for the scarcity of labeled data. It is adopted on lots of vision and language classification tasks. However, for tasks with structured output ( e.g ., dependency parsing), the application of VAT is nontrivial due to the intrinsic proprieties of structures: (1) the non-sparse problem and (2) exponential complexity. Against this background, we pro-pose the S parse P arse A djustment algorithm ( Spa ) and successfully applied VAT to the dependency parsing task. Spa refers to the learning algorithm which combines the graph-based dependency parsing model with VAT in an exact computational manner and enhances the dependency parser with controllable and adjustable sparsity. Empirical studies show that the TreeCRF parser optimized using Spa out-performs other methods without sparsity regularization.
A Multilingual Multiway Evaluation Data Set for Structured Document Translation of Asian Languages

Translation of structured content is an important application of machine translation, but the scarcity of evaluation data sets, especially for Asian languages, limits progress. In this paper we present a novel multilingual multiway evaluation data set for the translation of structured documents of the Asian languages Japanese, Korean and Chinese. We describe the data set, its creation process and important characteristics, followed by establishing and evaluating baselines using the direct translation as well as detag-project approaches. Our data set is well suited for multilingual evaluation, and it contains richer annotation tag sets than existing data sets. Our results show that massively multilingual translation models like M2M-100 and mBART-50 perform surprisingly well despite not being explicitly trained to handle structured content. The data set described in this paper and used in our experiments is released publicly.
Almost Beatty Partitions

Given $0<\alpha<1$, the Beatty sequence of density $\alpha$ is the sequence $B_{\alpha}=(\lfloor n/\alpha\rfloor)_{n\in\mathbb{N}}$. Beatty's theorem states that if $\alpha,\beta$ are irrational numbers with $\alpha+\beta=1$, then the Beatty sequences $B_{\alpha}$ and $B_{\beta}$ partition the positive integers, that is, each positive integer belongs to exactly one of these two sequences. On the other hand, Uspensky showed that this result breaks down completely for partitions into three (or more) sequences: There does not exist a single triple $(\alpha,\beta,\gamma)$ such that the Beatty sequences $B_\alpha,B_\beta,B_\gamma$ partition the positive integers. In this paper we consider the question of how close we can come to a three-part Beatty partition by considering "almost" Beatty sequences, that is, sequences that represent small perturbations of an "exact" Beatty sequence. We first characterize all cases in which there exists a partition into two exact Beatty sequences and one almost Beatty sequence with given densities, and we determine the approximation error involved. We then give two general constructions that yield partitions into one exact Beatty sequence and two almost Beatty sequences with prescribed densities, and we determine the approximation error in these constructions. Finally, we show that in many situations these constructions are best-possible in the sense that they yield the closest approximation to a three-part Beatty partition.
Strong Convexity for Risk-Averse Two-Stage Models with Fixed Complete Linear Recourse

This paper generalizes results concerning strong convexity of two-stage mean-risk models with linear recourse to distortion risk measures. Introducing the concept of (restricted) partial strong convexity, we conduct an in-depth analysis of the expected excess functional with respect to the decision variable and the threshold parameter. These results allow to derive sufficient conditions for strong convexity of models building on the conditional value-at-risk due to its variational representation. Via Kusuoka representation these carry over to comonotonic and distortion risk measures, where we obtain verifiable conditions in terms of the distortion function. For stochastic optimisation models, we point out implications for quantitative stability with respect to perturbations of the underlying probability measure. Recent work in \cite{Ba14} and \cite{WaXi17} also gives testimony to the importance of strong convexity for the convergence rates of modern stochastic subgradient descent algorithms and in the setting of machine learning.
A new variational formulation based on discontinuous Galerkin technique for a reaction-diffusion problem ✩

In this paper, a new variational formulation based on discontinuous Galerkin technique for a reaction-diffusion problem is introduced, and the discontinuous Galerkin technique of this work is different from the general discontinuous Galerkin methods. The well posedness of the new formulation is given. Finally, it is pointed that the new variational formulation will be helpful to design better hybrid numerical methods which will not only strongly stable in spatial variable and absolutely stable in temporal variable but also be
The Eigenvalue Point Process for Symmetric Group Permutation Representations on $k$-tuples.

Equip the symmetric group $\mathfrak{S}_n$ with the Ewens distribution. We study the eigenvalue point process of the permutation representation of $\mathfrak{S}_n$ on $k$-tuples of distinct integers chosen from the set $\{1,2,. ,n\}$. Taking $n \to \infty$, we find the limiting point process in the microscopic regime, i.e. when the eigenvalue point process is viewed at the scale of the mean eigenvalue spacing. A formula for the limiting eigenvalue gap probability in an interval is also given. In certain cases, a power series representation exists and a combinatorial procedure is given for computing the coefficients.
Cohomology of the moduli space of non-hyperelliptic genus four curves

We compute the intersection Betti numbers of the GIT model of the moduli space of non-hyperelliptic Petri-general curves of genus 4. This space was shown to be the final non-trivial log canonical model for the moduli space of stable genus four curves, under the Hassett-Keel program. The strategy of the cohomological computation relies on a general method developed by Kirwan to calculate the cohomology of GIT quotients of projective varieties, based on the HKKN equivariantly perfect stratification, a partial resolution of singularities and the Decomposition Theorem.
A Systematic Map of the Research Trends in Wildfire Management in Mediterranean-Climate Regions

 Abstract — Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.
Transition to efﬁcient, unsuppressed bulk-target ion acceleration via high-ﬂuence laser irradiation

A high-intensity laser irradiating a few- μ m solid foil will accelerate ions from the bulk of the target as well as protons from a surface contaminant layer. Experimental measurements of ion spectra using the OMEGA EP laser (0.25–1 kJ, 10 ps) show, as suggested previously [Petrov et al. , Phys. Plasmas 17 , 103111 (2010)], that at a laser ﬂuence exceeding 1 J /μ m 2 , the contaminant layer is accelerated enough that ions from the bulk of the target are more effectively accelerated. When using CD 2 as a target, the high ﬂuence results in a 100-fold increase in deuteron acceleration efﬁciency (near 1% of laser energy) compared to subthreshold ﬂuence. This is found to be due to the fact that the deuterons have a higher density at many locations during acceleration, allowing a larger electric ﬁeld to develop, leading to improved efﬁciency. Using a pitcher-catcher setup, these deuterons, as well as protons from the contaminant layer, strike a LiF target and generate neutrons via ( d,n ) and ( p,n ) nuclear reactions. CR39 plastic and nuclear activation detectors measured broadband neutron yields of 4 × 10 9 sr − 1 and yields of 10 8 sr − 1 for neutrons above 11 MeV.
Magnetotransport properties of the ternary carbide Ti3SiC2: Hall effect, magnetoresistance, and magnetic susceptibility

In this study we report on the transport properties of the Ti-based ternary carbide Ti 3 SiC 2 . The Hall effect and longitudinal magnetoresistance have been measured as a function of temperature in the 4-300 K range and atmagnetic fields up to 5 T. The magnetoresistance is dominated by a positive quadratic field dependence at low temperatures The Hall voltage is a linear function of magnetic field over the range of temperatures investigated. The effective carrier concentration and mobilities were calculated based on the sign and value of the Hall coefficient. These results are discussed in terms of a two-band model and compared to the single-band approximation. The magnetic susceptibility (4. 1 × 10 - 6 ) was found to be independent of temperature and field. These results were used to evaluate the charge concentration in light of Pauli paramaganetism theory.
A Sentinel-2 Based Multi-Temporal Monitoring Framework for Wind and Bark Beetle Detection and Damage Mapping

The occurrence of extreme windstorms and increasing heat and drought events induced by climate change leads to severe damage and stress in coniferous forests, making trees more vulnerable to spruce bark beetle infestations. The combination of abiotic and biotic disturbances in forests can cause drastic environmental and economic losses. The first step to containing such damage is establishing a monitoring framework for the early detection of vulnerable plots and distinguishing the cause of forest damage at scales from the management unit to the region. To develop and evaluate the functionality of such a monitoring framework, we first selected an area of interest affected by windthrow damage and bark beetles at the border between Italy and Austria in the Friulian Dolomites, Carnic and Julian Alps and the Carinthian Gailtal. Secondly, we implemented a framework for time-series analysis with open-access Sentinel-2 data over four years (2017–2020) by quantifying single-band sensitivity to disturbances. Additionally, we enhanced the framework by deploying vegetation indices to monitor spectral changes and perform supervised image classification for change detection. A mean overall accuracy of 89% was achieved; thus, Sentinel-2 imagery proved to be suitable for distinguishing stressed stands, bark-beetle-attacked canopies and wind-felled patches. The advantages of our methodology are its large-scale applicability to monitoring forest health and forest-cover changes and its usability to support the development of forest management strategies for dealing with massive bark beetle outbreaks.
Psychological Impact of COVID-19 on Community Pharmacists: A Cross-Sectional Study in Lusaka District, Zambia

Introduction The coronavirus disease 2019 (COVID-19) pandemic has caused serious health problems globally. This has included increased psychological challenges among frontline healthcare workers (HCWs). Community pharmacists are critical in the fight against COVID-19 and in sensitising the public about vaccinations and other public health interventions. However, little is known about the psychological impact of COVID-19 and the acceptance of vaccinations among community pharmacists in Zambia. Therefore, this study assessed the psychological impact of COVID-19 among community pharmacists in Lusaka, Zambia. Materials and Methods: This cross-sectional study was conducted among 188 community pharmacists from August to October 2021 using a structured questionnaire. Statistical Package for Social Sciences (SPSS) version 22.0 was used to analyse the data. The statistical significance was conducted at a 95% confidence level. Results: Of the 188 participants, 108 (57.4%) were male, while 80 (42.6%) were female. Most of the participants were in the age group of 20−30 years (n=109, 58.0%). The study found that 36.7% of the participants experienced anxiety, while 50.5% experienced depression. Anxiety was associated with fear of dying from COVID-19 if one contracted it (p=0.001), fear of infecting loved ones if infected (p=0.003) and experiencing a traumatic event (p=0.036). Depression was associated with a fear of dying if one contracted COVID-19 (p=0.001). Overall, about 70.2% of the participants expressed willingness to receive the COVID-19 vaccine. Conclusion: Community pharmacists experienced anxiety and depression due to the COVID-19 pandemic. Most of the community pharmacists were willing to receive the COVID-19 vaccine. There is a need for urgent interventions to address the mental health challenges of community pharmacists during pandemics.
Louis de Broglie und die Entdeckung der Materiewelle

Biographisches Louis de Broglie erhielt im Jahre 1929 den Nobelpreis „fur die Entdeckung der Wellennatur des Elektrons'*. Mit dieser Auszeichnung wurdigte die Preiskommission nicht twa eine experiment ll Arbeit, welche die Wellennat r des Elektrons bewiesen hatte, wie man vermuten konnte. Im Gegenteil, ie Ehr wurde rein theoretischen Ub rlegungen zu rkan t, welche Louis de Broglie in seiner Dissertation angestellt hatte. Die Doktoratsprufung a te am 25. Nove be 1924 vor einer Kommission der Sorbonne stattge den, welche Jean Perrin prasidierte. Anlaslich dieses Examens r g e Louis de Broglie in Experiment an, welches seine theoretische Folgerungen beweisen konnte. Er hatte d es Idee schon ein Jahr vorher, am 24. S ptember 1923 in einem Aufsatz geaus rt, w lcher in den Comptes rendus de Γ Academie de Paris erschie en war, worin er schrieb:
Wide-Field Video Observation and Statistical Analysis of the Leonid Meteor Storm in 2001

We show a detailed analysis of a wide-field video observation of the Leonid Meteor Storm from 14 h 41 m through 20 h 03 m (UT) on 2001 November 18. We detected 1573 meteors of Leonids and 64 meteors of others. The peak of the storm appeared at 18 h 20 m and its duration was 1.9hr (FWHM). Bright (m ≤ 2.5) and faint (m ≥ 2.5) meteors showed significantly different behavior in their activity. Especially, after 19 h 15 m , bright objects dominated the meteor events. We found many local peaks in the count record, and most of local peaks consisted of faint meteors. The autocorrelation function and the interval distribution between the meteor arrivals suggest that the distribution of dust in the cometary trails has no significant spatial structures that give rise to a temporally coherent behavior with a time-scale of seconds to minutes.
Transcriptome analysis reveals potential marker genes for diagnosis of Alzheimer’s disease and vascular dementia

Alzheimer’s disease (AD) and vascular dementia (VD) are the two most common forms of dementia, share similar symptoms, and are sometimes difficult to distinguish. To investigate the potential mechanisms by which they differ, we identified differentially expressed genes in blood and brain samples from patients with these diseases, and performed weighted gene co-expression network analysis and other bioinformatics analyses. Weighted gene co-expression network analysis resulted in mining of different modules based on differences in gene expression between these two diseases. Enrichment analysis and generation of a protein-protein interaction network were used to identify core pathways for each disease. Modules were significantly involved in cAMP and AMPK signaling pathway, which may be regulated cell death in AD and VD. Genes of cAMP and neurotrophin signaling pathways, including ATP1A3, PP2A, NCEH1, ITPR1, CAMKK2, and HDAC1, were identified as key markers. Using the least absolute shrinkage and selection operator method, a diagnostic model for AD and VD was generated and verified through analysis of gene expression in blood of patients. Furthermore, single sample gene set enrichment analysis was used to characterize immune cell infiltration into brain tissue. That results showed that infiltration of DCs and pDCs cells was increased, and infiltration of B cells and TFH cells was decreased in the brain tissues of patients with AD and VD. In summary, classification based on target genes showed good diagnostic efficiency, and filled the gap in the diagnostic field or optimizes the existing diagnostic model, which could be used to distinguish between AD and VD.