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Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

There is evidence of the impact of school segregation on students' academic achievement, but it is debated whether the extent of this impact is dependent on students' socioeconomic status, or on their native or non-native condition. This research addresses the problem in Spain, seeking to determine how immigrant and socioeconomic segregation affect the academic achievement of native and non-native students. With this aim, the PISA study database was specially exploited by means of two-tier Multilevel Models, estimating school segregation through the Hutchens Square Root Index. Specifically, the study estimates the influence of school segregation on students' academic achievement in the subjects of Mathematics, Language and Science. The results confirm that school socioeconomical and immigrant segregation affect students' academic achievement differently. Whereas socioeconomic segregation negatively affects both groups in all three subjects, immigrant segregation affects non-native students more strongly. Thus, data shows school segregation on socioeconomic grounds is always significant, and always has a considerable impact on achievement, regardless of students' national origin. School segregation reproduces and accentuates conditions of social injustice. To counter its harmful effects, it is necessary to act first and foremost on socioeconomic segregation, as this causes the most devastating effects in education, particularly for non-native students.

Abstract Background Mosquito borne viruses, such as dengue, Zika, yellow fever and Chikungunya, cause millions of infections every year. These viruses are mostly transmitted by two urban-adapted mosquito species, Aedes aegypti and Aedes albopictus. Although mechanistic understanding remains largely unknown, Aedes mosquitoes may have unique adaptations that lower the impact of viral infection. Recently, we reported the identification of an Aedes specific double-stranded RNA binding protein (dsRBP), named Loqs2, that is involved in the control of infection by dengue and Zika viruses in mosquitoes. Preliminary analyses suggested that the loqs2 gene is a paralog of loquacious (loqs) and r2d2, two co-factors of the RNA interference (RNAi) pathway, a major antiviral mechanism in insects. Results Here we analyzed the origin and evolution of loqs2. Our data suggest that loqs2 originated from two independent duplications of the first double-stranded RNA binding domain of loqs that occurred before the origin of the Aedes Stegomyia subgenus, around 31 million years ago. We show that the loqs2 gene is evolving under relaxed purifying selection at a faster pace than loqs, with evidence of neofunctionalization driven by positive selection. Accordingly, we observed that Loqs2 is localized mainly in the nucleus, different from R2D2 and both isoforms of Loqs that are cytoplasmic. In contrast to r2d2 and loqs, loqs2 expression is stage- and tissue-specific, restricted mostly to reproductive tissues in adult Ae. aegypti and Ae. albopictus. Transgenic mosquitoes engineered to express loqs2 ubiquitously undergo developmental arrest at larval stages that correlates with massive dysregulation of gene expression without major effects on microRNAs or other endogenous small RNAs, classically associated with RNA interference. Conclusions Our results uncover the peculiar origin and neofunctionalization of loqs2 driven by positive selection. This study shows an example of unique adaptations in Aedes mosquitoes that could ultimately help explain their effectiveness as virus vectors.

This article is a tribute to Kadir Beycioglu, a Turkish academic who passed away prematurely in August 2021 due to a terrible illness. His death was met with a deep shock and great sadness by all who knew him. The different sections of this article summarise his influential work in the field of educational leadership and social justice and invite the reader to take a brief journey through his relentless struggle to improve the rights of children and youth, both in his home country and abroad. The text discusses the pillars underpinning social justice and the steps to be taken for its implementation in schools. The article relies on the principle that every child's dream matters, emphasising the need to eradicate the scourge of segregation and exclusion from schools to which Kadir so often referred in his work. The conclusion reflects on the evolution that social justice leadership has taken so far and looks to the future by considering the emergence of networking as a useful ally at the service of education for social justice, which is making a true difference on the road to a more socially just school.

Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime's many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Fabrication of modern solid-state devices demands precise control of shape and dimensions, which requires an accurate knowledge of the role that surfaces play in such devices. To contribute to the understanding of surface effects on silicon nanowires, we present an atomistic study of the electronic properties of silicon nanostructures exhibiting surface facets over the (100) , (110) , (111) , and (112) crystallographic planes. We calculate the electronic structure of slabs in such a way that the effect of individual facets may be observed. Subsequently, we determine the electronic structure of nanowires grown along the [ 100 ] , [ 110 ] , [ 111 ] , and [ 112 ] directions, with surfaces defined by a combination of the mentioned facets. Our nanowires comprise diameters ranging from 1 to 6.7 nm and structures with more than 1000 atoms. We discuss the band structure, the relation between direct and indirect bandgaps, and the density of states. We base our calculations on semiempirical pseudopotentials where we implement complex potentials to describe passivants. We find that there is a transition from direct to indirect gap for the [ 111 ] direction at approximately 2 nm and that the difference between the direct and indirect gap may reach more than 300 meV depending on the diameter. We show that the occurrence of a direct bandgap is favored by the presence of the (100) facet and that it is related to a higher surface density of states. Conversely, we find that the (111) facet is the most inert surface type with a lower surface density of states. [ABSTRACT FROM AUTHOR]

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

It is known that new power transmission line inspection techniques have been developed over the last few years with great potential to improve and, in some cases, even replace traditional inspection procedures such as using helicopters and cars. A series of Unmanned Aerial Vehicles (UAVs) such as fixed-wing or rotary-wing UAVs, and vehicles that climb on the power transmission line, promise to revolutionize the inspection market. In this light, at least 39 new research studies and/or products have been conducted and/or introduced to the market, respectively. However, in an incipient way, some works point to the fusion of some technologies: the development of multi-rotor UAVs and the ability to connect and move over the power transmission line. In line with this, the current work was proposed, with significant unprecedented advances (such as an over-actuated control capacity with tilt rotors, the capability of a displacement in the angle, and the maintenance of active motors on the power transmission line), and the design, modeling, and control of an over-actuated UAV able to move over the conductor cable without the need for a new locomotion system is presented. The aircraft allows for a greater response and the indispensable ability to approximate landing in a power transmission line arbitrary position rather than the catenary lowest point (due to its ability to forward/backward move using the tilting rotors). Its design is detailed, its subsystems are described, and its normal and coupled flight mode dynamics are modeled. The results show good stability and reliable maneuvers for the coupling-to-power-transmission-line flight mode, without any overshoots, and the ability to follow the entire catenary through different Real Control Action (RCA) sets.

Copyright of REICE. Ibero-American Journal on Quality, Effectiveness & Change in Education / REICE. Revista Iberoamericana Sobre Calidad, Eficacia y Cambio en Educación is the property of Red Iberoamericana de Investigacion sobre Cambio y Eficacia en Educacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It is pressing to understand how animal populations evolve in response to climate change. We argue that new sequencing technologies and the use of historical samples are opening unprecedented opportunities to investigate genome-wide responses to changing environments. However, there are important challenges in interpreting the emerging findings. First, it is essential to differentiate genetic adaptation from phenotypic plasticity. Second, it is extremely difficult to map genotype, phenotype, and fitness. Third, neutral demographic processes and natural selection affect genetic variation in similar ways. We argue that Drosophila melanogaster, a classical model organism with decades of climate adaptation research, is uniquely suited to overcome most of these challenges. In the near future, long-term time series genome-wide datasets of D. melanogaster natural populations will provide exciting opportunities to study adaptation to recent climate change and will lay the groundwork for related research in non-model systems.

Copyright of Revista Colombiana de Educación is the property of Universidad Pedaggica Nacional and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Speciation genomic studies aim to interpret patterns of genome-wide variation in light of the processes that give rise to new species. However, interpreting the genomic "landscape" of speciation is difficult, because many evolutionary processes can impact levels of variation. Facilitated by the first chromosome-level assembly for the group, we use whole-genome sequencing and simulations to shed light on the processes that have shaped the genomic landscape during a radiation of monkeyflowers. After inferring the phylogenetic relationships among the 9 taxa in this radiation, we show that highly similar diversity (π) and differentiation (FST) landscapes have emerged across the group. Variation in these landscapes was strongly predicted by the local density of functional elements and the recombination rate, suggesting that the landscapes have been shaped by widespread natural selection. Using the varying divergence times between pairs of taxa, we show that the correlations between FST and genome features arose almost immediately after a population split and have become stronger over time. Simulations of genomic landscape evolution suggest that background selection (BGS; i.e., selection against deleterious mutations) alone is too subtle to generate the observed patterns, but scenarios that involve positive selection and genetic incompatibilities are plausible alternative explanations. Finally, tests for introgression among these taxa reveal widespread evidence of heterogeneous selection against gene flow during this radiation. Combined with previous evidence for adaptation in this system, we conclude that the correlation in FST among these taxa informs us about the processes contributing to adaptation and speciation during a rapid radiation.