Miracle-dz/UniFAR-FTUs huggingface dataset:
A major myna problem; invasive predator removal benefits female survival and population growth of a translocated island endemic

Invasive predators are a major driver of extinctions and continue to threaten native populations worldwide. Island eradications of (mostly mammalian) invasive predators have facilitated the (re)establishment of numerous island-endemic populations. Other invasive taxa, such as some predatory birds, could pose a more persistent threat due to their ability to fly and actively re-invade even remote and isolated islands. However, the impact of invasive predatory birds has been largely overlooked. We report on a novel sex-specific impact of an invasive-nest predator, the common myna (Acridotheres tristis), on a reintroduced population of Seychelles warblers (Acrocephalus sechellensis); translocated from Cousin Island to Denis Island in 2004. Regular post-translocation monitoring revealed that female mortality was 20% higher than males, leading to a 60–70% male-biased population sex-ratio between 2005–2015. This was attributed to mynas inflicting severe injuries to incubating female warblers while attempting to prey upon eggs in their nests. These effects likely contributed to the slower-than-expected population growth observed (relative to previous translocations of Seychelles warblers to other islands) over the same period. An eradication programme beginning in 2011 removed all mynas from Denis by 2015. Subsequently, we observed a balancing of sex-specific survival and the population sex-ratio of Seychelles warblers and, consequently, accelerated population growth. This study demonstrates the importance of assessing the threat posed by all invasive taxa (not just mammals) to island conservation. Furthermore, we show how extended monitoring is needed to identify problems, and develop solutions, post-translocation.
Chromosome-Level Genome Assembly and Circadian Gene Repertoire of the Patagonia Blennie Eleginops maclovinus—The Closest Ancestral Proxy of Antarctic Cryonotothenioids

The basal S. American notothenioid Eleginops maclovinus (Patagonia blennie) occupies a uniquely important phylogenetic position in Notothenioidei as the singular closest sister species to the Antarctic cryonotothenioid fishes. Its genome and the traits encoded therein would be nearest representatives of the temperate ancestor from which the Antarctic clade arose, providing an ancestral reference for deducing polar derived changes. In this study, we generated a gene- and chromosome-complete assembly of E. maclovinus genome using long read sequencing and HiC scaffolding. We compared its genome architecture with the more basally divergent Cottoperca gobio and the derived genomes of nine cryonotothenioids representing all five Antarctic families. We additionally curated its repertoire of circadian rhythm genes, ascertained their functionality by transcriptome sequencing, and compared its pattern of gene retention with C. gobio and the derived cryonotothenioids. Both analyses found E. maclovinus to share greater conservation with the Antarctic clade, solidifying its evolutionary status as direct sister and best suited ancestral proxy of cryonotothenioids. The high quality genome of E. maclovinus will facilitate inquiries into cold derived traits in temperate to polar evolution, as well as inform on the paths of readaptation to non-freezing habitats in various secondarily temperate cryonotothenioids through comparative genomic analyses.
The evolution of multi-component weapons in the superfamily of leaf-footed bugs

Sexually selected weapons, such as the antlers of deer, claws of crabs, and tusks of beaked whales, are strikingly diverse across taxa and even within groups of closely related species. Phylogenetic comparative studies have typically taken a simplified approach to investigating the evolution of weapon diversity, examining the gains and losses of entire weapons, major shifts in size or type, or changes in location. Less understood is how individual weapon components evolve and assemble into a complete weapon. We addressed this question by examining weapon evolution in the diverse, multi-component hind-leg and body weapons of leaf-footed bugs, Superfamily Coreoidea (Hemiptera: Heteroptera). Male leaf-footed bugs use their weapons to fight for access to mating territories. We used a large multilocus dataset comprised of ultraconserved element loci for 248 species and inferred evolutionary transitions among component states using ancestral state estimation. We found that weapons added components over time with some evidence of a cyclical evolutionary pattern — gains of components followed by losses and then gains again. Further, we found that certain trait combinations evolved repeatedly across the phylogeny. This work reveals the remarkable and dynamic evolution of weapon form in the leaf-footed bugs. It also highlights that multi-component weapons may be especially useful in providing insights into the evolutionary interplay of form and function. TEASER TEXT For centuries, humans have been fascinated by the morphological weapons animals use to engage in battle. The diversity of sexually selected weapons is surprising, with considerable variation across even closely related groups of animals. Studies are needed that take a detailed view of the components that comprise weapons and the evolutionary assembly of these components into a complete structure. Here, we reconstruct the evolution of a multi-component weapon in a superfamily of insects. Male leaf-footed bugs use spiky, enlarged hind legs to wrestle over mating territories. We measured 15 putative weapon components across 248 species, using phylogenetic comparative analyses. We found that the number of weapon components generally increased over time, with many gains and losses of components along the way. We found that certain components were more likely to evolve with others, suggesting that specific trait combinations might be especially functional in battle. This work highlights that evolutionary studies of complex, multi-component weapons may be useful for reconstructing the evolutionary assembly of weapons and the interplay of form and function.
A guide to the in vitro reconstitution of Cdc42 GTPase activity and its regulation

Cdc42 is a small Rho-type GTPase and the main regulator of cell division in eukaryotes. It is surrounded by a large network of regulatory proteins. To understand the processes around cell division, in-depth understanding of Cdc42 and its regulation is required. In vitro reconstitutions are a suitable tool for such detailed mechanistic studies, as they allow a high level of control over the conditions and components used and. For these Cdc42 and its regulators need to be expressed, purified, and tested for their activity. There are many methods described for this, but their details, possible difficulties, and points of failure are rarely discussed. This makes in vitro studies on Cdc42 less accessible to scientists that have a background different from biochemistry. We here present our experience with working with Cdc42 in vitro. We describe the recombinant expression and purification behaviour of 12 Cdc42, six Cdc42-mNeonGreenSW and four Cdc42-sfGFPSW constructs in E. coli. We explore Cdc42 dimerisation in vitro and assess its activity using GTPase Glo assays and Flag-pulldown assays. GTPase Glo assays turn out to be a reliable tool to quantitatively asses GTPase activities, wheareas pulldown experiments are more error prone. We find that most Cdc42 constructs, with the exception of those with an N-terminal Twin-Step-tag, show a similar GTPase activity and interaction with the GDP/GTP exchange factor Cdc24. We close with using enterokinase and TEV protease to generate untagged Cdc42. Enterokinase also cuts Cdc42 in an undesired position. TEV protease leads to the desired product, which retains its GTPase activity but shows a reduced Cdc24 interaction. The work presented here acts as a guide for scientists desiring to work with Cdc42 in vitro through describing Cdc42’s properties in detail and examining assays that can be used to study its behaviour or act as activity checks. Graphical abstract
Mycobacterium tuberculosis employs atypical and different classes of B12 switches to control separate operons

Vitamin B12 (B12), an essential cofactor in all domains of life, is produced de novo by only a small subset of prokaryotes, but B12-sensing riboswitches are some of the most widely distributed riboswitches in bacteria. Mycobacterium tuberculosis, the causative agent of the ongoing tuberculosis pandemic, encodes two distinct vitamin B12 riboswitches. One controls the expression of metE, encoding a B12-independent methionine synthase, while the other is located upstream of ppe2, a PE/PPE family gene whose function is still unresolved. Here, we analyse ligand sensing, secondary structure architecture, and gene expression control mechanisms of these two riboswitches. Our results provide the first evidence of direct ligand binding by metE and ppe2 riboswitches and show that the two switches exhibit different preferences for natural isoforms of B12, use distinct regulatory and structural elements, and act as translational OFF switches. Based on our results, we propose that the ppe2 switch represents a new Class IIc of B12-sensing riboswitches. Moreover, we have identified small translated open reading frames (uORFs) upstream of both metE and ppe2, which modulate the expression of the respective downstream genes in opposite directions. Translation of the metE riboswitch uORF suppresses MetE expression, while translation of the uORF in the ppe2 switch is essential for PPE2 expression via the synthesis of a uORF-PPE2 fusion protein. In summary, our findings reveal an unexpected diversity and complexity of B12-dependent cis-regulation in M. tuberculosis, with potential implications for host-pathogen interactions.
Interpreting Adversarial Examples in Deep Learning: A Review

Deep learning technology is increasingly being applied in safety-critical scenarios but has recently been found to be susceptible to imperceptible adversarial perturbations. This raises a serious concern regarding the adversarial robustness of deep neural network (DNN)–based applications. Accordingly, various adversarial attacks and defense approaches have been proposed. However, current studies implement different types of attacks and defenses with certain assumptions. There is still a lack of full theoretical understanding and interpretation of adversarial examples. Instead of reviewing technical progress in adversarial attacks and defenses, this article presents a framework consisting of three perspectives to discuss recent works focusing on theoretically explaining adversarial examples comprehensively. In each perspective, various hypotheses are further categorized and summarized into several subcategories and introduced systematically. To the best of our knowledge, this study is the first to concentrate on surveying existing research on adversarial examples and adversarial robustness from the interpretability perspective. By drawing on the reviewed literature, this survey characterizes current problems and challenges that need to be addressed and highlights potential future research directions to further investigate adversarial examples.
Effectof Fabric And Initial Stresses On The Anisotropic Behavior Of Sand

This study investigates the anisotropy in the stress-strain-strength behavior of Firoozkuh sand, focusing on the e ect of the initial stress state and soil fabric. The experiments are performed using a hollow cylinder apparatus. Di erent initial conditions are considered by maintaining the principal stress ratio (i.e. Rc = 01 c=03c) and the inclination of initial principal stress (i.e. c) during consolidation. The specimens are prepared using two di erent methods to assess the influence of soil fabric. The direction of increments of principal stresses, , is controlled to remain constant during the test. Generally, the results showed a decrease in the shear strength of sand by increasing . In specimens consolidated under the inclined anisotropic stresses, the trend of shear strength variation versus  di ered and depended on c. The vertical consolidated sands (Rc = 2, c = 0) were found to be highly in uenced by . The anisotropic behavior of medium dense sands was observed to be strongly dependent on the initial stress state. The results showed that the stress-strain behavior of specimens prepared by the wet tamping method is strongly in uenced by . The e ect of soil fabric and initial stress state on the shear modulus was more noticeable than that on the shear strength of sand.
Crustal Architecture Across Southern California and Its Implications on San Andreas Fault Development

In this study, we perform a 2‐frequency sequential receiver function stacking investigation in Southern California. The resulting Moho depths exhibit similar patterns to previous studies while the crystalline crustal Vp/Vs values show more regional variations. Most Vp/Vs variations can be explained by compositional differences. We observe a dichotomy in Moho depth, Vp/Vs, and crustal strain rates between the Peninsular Ranges and Southern San Andreas Fault system. Comparisons between strain rates, Vp/Vs, and temperature suggest that crustal compositional variations may have played a more critical role in influencing the crustal strain rate variations in the Peninsular Ranges and Southern San Andreas than temperature. The structural and compositional variations provide a new insight into the causes of the migration of the Southern San Andreas Fault system and the formation of the “Big Bend. ”
Glacier Mass Loss Between 2010 and 2020 Dominated by Atmospheric Forcing

We generate a high spatial and temporal record of ice loss across glaciers globally for the first time from CryoSat‐2 swath interferometric radar altimetry. We show that between 2010 and 2020, glaciers lost a total of 272 ± 11 Gt yr−1 of ice, equivalent to a loss of 2% of their total volume during the 10‐year study period. Using a simple parameterization, we demonstrate that during this period, surface mass balance anomaly dominated the mass budget, accounting for 89% ± 5% of the total ice loss. Ice discharge anomaly was responsible for 11% ± 1% of the total ice loss, and 28% ± 2% of the ice loss when excluding land‐terminating sectors. Strong discharge anomaly is found over areas of changing oceanic conditions such as in the Barents and Kara Seas or in Antarctica, and areas fringed by lakes and fjords in Patagonia.
Translation of systems biology markup language into process algebra

We address the automatic translation of Systems Biology Mark-Up Language (SBML) models of network of biochemical reactions into the Biochemical Stochastic π-calculus. SBML is XML-based widespread exchange language for systems biology. The Biochemical Stochastic π-calculus can describe the concurrency of a network of biochemical reactions. Available tools allow to simulate π-calculus models to obtain qualitative as well as quantitative results, but the translation from SBML into a process algebra requires a level of encoding detail that deters biologists from performing the conversion. To perform an automatic translation we define the assumptions and the formal rules that allow the unsupervised definition of specifications into π-calculus from SBML models lacking formality and biological information. We design and implement an automatic translation tool that implements the translation rules. To test the translation process we present and discuss the results of the simulations performed on two models translated with our tool. The simulation results are in excellent agreement, both qualitatively and quantitatively, with the literature. We discuss some problems that remain open and suggest possible solutions that need further investigation. To our knowledge, up to now no one has tackled the problem to convert SBML into a process algebra. Our tool allows to perform simulation on a great number of already available SBML models in order to exploit the huge amount of biological knowledge contained in SBML repositories.
On the Inductive Bias Transfer with Knowledge Distillation for Real-World Data

In the lack of data, an appropriate inductive bias is one of the key factors for the successful training of a model. One approach to transfer inductive bias between the different structures of networks is to utilize knowledge distillation. Several studies have achieved promising results in computer vision datasets using response-based knowledge distillation. However, we observe that the previous method fails to transfer inductive bias when the dataset contains fewer data points or classes. To solve the problem, we propose to use feature-based knowledge distillation instead of response-based knowledge distillation for effective inductive bias transfer. Through extensive experimentation and analysis, we demonstrate that the suggested method can transfer inductive bias and outperform previous methods.
StructExtSum - Bulgarian Legislation Text Extractive Summarization by Structure Understanding

Determining the most important part of documents in the legal field has great value because the texts are very long and hard to understand. In this paper, a new approach is proposed for long EU legislative documents in Bulgarian. The approach uses the inner structure of the documents. It relies on the structure of the text and trains a model to predict the importance of each sentence of the text. A dataset has been collected consisting of texts in Bulgarian with initially 1739 documents and 1657 after cleansing. Multiple experiments have been conducted. The results show that the proposed approach improves the rouge score and performs better than the other algorithms.
Digital responses by small businesses during COVID-19: the role of entrepreneurial success factors

Small businesses ’ revenues worldwide were affected drastically when governments introduced lockdowns to mitigate the effects of the COVID-19 pandemic. As a response, many small businesses introduced digital technology initiatives. This article examines digital responses introduced by 68 small businesses that have been sourced from Google News. The news stories were analysed according to how small businesses behaved across different phases of their pandemic response (initial impact, digital response and evaluation of the response). The results, which used entrepreneurial success factors as an analytical lens, suggested that success factors were front of mind for small business owners throughout all phases of their responses. These involved traditional measures of financial success (such as measures of turnover or profit) and owner/managers’ personally oriented measures (such as wanting to assist the local community and taking care of employees and customers during the pandemic). The paper proposes new entrepreneurial success measures.
Radiative capture of stopped kaons: K/sup -/p. --> lambda gamma. and K/sup -/p. --> sigma. /sup 0/. gamma

The radiative-capture reactions K/sup -/p.--> lambda gamma. and K/sup -/p.--> sigma. /sup 0/. gamma. are investigated within a pole-model calculation. Both pseudoscalar and pseudovector coupling schemes are used and both give branching ratios comparable to current experimental bounds. The sensitivity to the . lambda. (1405) is investigated and improved constraints are determined for its contribution. Our methods and results are compared with those of other recent calculations of these reactions.
Using Virtual Reality to Assess Age-related Differences in Driving Behaviour

Artificial intelligence can be used in a variety of ways to mitigate the cognitive and psychophysical decline that accompanies ageing. However, it is not always easy to assess this decline. Several laboratory tests have been developed, but ecological assessment is still an open problem in many areas. Driving is one of these areas. Evaluating driving behaviour in a real-world environment raises ethical, practical, and economic issues. Virtual reality (VR), on the other hand, is already being used in several areas as a diagnostic and therapeutic aid. There are previous attempts to assess attention while driving using VR, but they are less than ecological. In this work, we propose a protocol to assess and quantify attention while driving and its effect on driving behavior. The protocol does not require expensive instruments and is easy to apply. Since its main goal is to assess age-related cognitive decline, it can be used to evaluate possible intervention areas for artificial intelligence and to quantify the effectiveness of these techniques.
The fate of the false vacuum in Einstein gravity theory with nonminimally-coupled scalar field

The decay of false vacuum via the true vacuum bubble nucleation has been explored in Einstein theories of gravity with nonminimally-coupled scalar field using Coleman–De Luccia's semiclassical instanton approximation. In this case the false vacuum decay rates and the radius of the bubbles in Coleman's thin-wall approximation have been computed analytically and numerically with several values of nonminimal coupling constant and compared with the standard result obtained by Coleman–De Luccia in the context of scalar field minimally-coupled to Einstein gravity.
Stochastic parallel model adaptation: theory and applications to active noise canceling, feedforward control, IIR filtering, and identification

General stochastic parallel model adaptation problems that consist of an unknown linear time-invariant system and a partially or wholly tunable system connected in parallel, with a common input, are considered. The goal of adaptation is to tune the partially tunable system so that its output matches that of the unknown system, despite the presence of any disturbance which is stochastically uncorrelated with the input. The general formulation allows applications to adaptive feedforward control and adaptive active noise canceling with input contamination, in addition to output error identification and adaptive IIR filtering. It is shown that in all the applications, the goal of adaptation is met whenever a matching condition and a positive real condition are satisfied. A special case of the results therefore resolves the long-standing problem of the convergence and the unbiasedness of the output error identification scheme in the presence of colored noise. A simple general technique for analyzing the strong consistency of parameter estimation with projection is also developed. >