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Abstract Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud‐based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research.

ABSTRACTResearch reproducibility is essential for scientific development. Yet, rates of reproducibility are low. As increasingly more research relies on computers and software, efforts for improving reproducibility rates have focused on making research products digitally available, such as publishing analysis workflows as computer code, and raw and processed data in computer readable form. However, research products that are digitally available are not necessarily friendly for learners and interested parties with little to no experience in the field. This renders research products unapproachable, counteracts their availability, and hinders scientific reproducibility. To improve both short- and long-term adoption of reproducible scientific practices, research products need to be made approachable for learners, the researchers of the future. Using a case study within evolutionary biology, we identify aspects of research workflows that make them unapproachable to the general audience: use of highly specialized language; unclear goals and high cognitive load; and lack of trouble-shooting examples. We propose principles to improve the unapproachable aspects of research workflows and illustrate their application using an online teaching resource. We elaborate on the general application of these principles for documenting research products and teaching materials, to provide present learners and future researchers with tools for successful scientific reproducibility. Supplementary materials for this article are available online.

ABSTRACT Bioenergy production relies on resources such as agricultural waste, which has prompted extensive research on biofuels. The heating value is a crucial parameter for evaluating energy sources. This study aims to analyze and propose formulations for estimating the higher heating value (HHV) based on proximate and ultimate chemical analysis of biomass. A database consisting of 142 samples was created, and 14 formulas available in the literature were initially tested. The datasets for each composition type were classified using the k-means algorithm, and the new sample spaces were validated. For proximate analysis data, specific multiple linear regression models were developed for two classes, one with an average of 0.697 and SE of 1.05 MJ kg -1 , and the other with an average of 0.678 and SE of 1.27 MJ kg -1 . For samples with ultimate analysis, a general model was formulated with an average of 0.701 and SE of 1.11 MJ kg -1 . Sample classification for proximate analysis did not significantly affect the fit of models. Considering that proximate analysis is less expensive than ultimate analysis, the proposed method shows promise in optimizing and reducing costs for determining the HHV of biomass for energy production.

Abstract Background Phylogenies are a key part of research in many areas of biology. Tools that automate some parts of the process of phylogenetic reconstruction, mainly molecular character matrix assembly, have been developed for the advantage of both specialists in the field of phylogenetics and non-specialists. However, interpretation of results, comparison with previously available phylogenetic hypotheses, and selection of one phylogeny for downstream analyses and discussion still impose difficulties to one that is not a specialist either on phylogenetic methods or on a particular group of study. Results Physcraper is a command-line Python program that automates the update of published phylogenies by adding public DNA sequences to underlying alignments of previously published phylogenies. It also provides a framework for straightforward comparison of published phylogenies with their updated versions, by leveraging upon tools from the Open Tree of Life project to link taxonomic information across databases. The program can be used by the nonspecialist, as a tool to generate phylogenetic hypotheses based on publicly available expert phylogenetic knowledge. Phylogeneticists and taxonomic group specialists will find it useful as a tool to facilitate molecular dataset gathering and comparison of alternative phylogenetic hypotheses (topologies). Conclusion The Physcraper workflow showcases the benefits of doing open science for phylogenetics, encouraging researchers to strive for better scientific sharing practices. Physcraper can be used with any OS and is released under an open-source license. Detailed instructions for installation and usage are available at https://physcraper.readthedocs.io.

A comprehensive phylogeny of species, i.e., a tree of life, has potential uses in a variety of contexts, including research, education, and public policy. Yet, accessing the tree of life typically requires special knowledge, complex software, or long periods of training. The Phylotastic project aims make it as easy to get a phylogeny of species as it is to get driving directions from mapping software. In prior work, we presented a design for an open system to validate and manage taxon names, find phylogeny resources, extract subtrees matching a user’s taxon list, scale trees to time, and integrate related resources such as species images. Here, we report the implementation of a set of tools that together represent a robust, accessible system for on-the-fly delivery of phylogenetic knowledge. This set of tools includes a web portal to execute several customizable workflows to obtain species phylogenies (scaled by geologic time and decorated with thumbnail images); more than 30 underlying web services (accessible via a common registry); and code toolkits in R and Python (allowing others to develop custom applications using Phylotastic services). The Phylotastic system, accessible via http://www.phylotastic.org , provides a unique resource to access the current state of phylogenetic knowledge, useful for a variety of cases in which a tree extracted quickly from online resources (as distinct from a tree custom-made from character data) is sufficient, as it is for many casual uses of trees identified here.

This work proposes a mixed-integer linear programming model for the operational cost function of lithium-ion batteries that should be applied in a microgrid centralized controller. Such a controller aims to supply loads while optimizing the leveled cost of energy, and for that, the cost function of the battery must compete with the cost functions of other energy resources, such as distribution network, dispatchable generators, and renewable sources. In this paper, in order to consider the battery lifetime degradation, the proposed operational cost model is based on the variation in its state of health (SOH). This variation is determined by experimental data that relate the number of charge and discharge cycles to some of the most important factors that degrade the lifespan of lithium-ion batteries, resulting in a simple empirical model that depends on the battery dispatch power and the current state of charge (SOC). As proof-of-concept, hardware-in-the-loop (HIL) simulations of a real microgrid are performed considering a centralized controller with the proposed battery degradation cost function model. The obtained results demonstrate that the proposed cost model properly maintains the charging/discharging rates and the SOC at adequate levels, avoiding accelerating the battery degradation with use. For the different scenarios analyzed, the battery is only dispatched to avoid excess demand charges and to absorb extra power produced by the non-dispatchable resources, while the daily average SOC ranges from 48.86% to 65.87% and the final SOC converges to a value close to 50%, regardless of the initial SOC considered.

While research on the prevalence of co-occurring autism spectrum conditions (ASC) and trans gender modality (TGM) is available, less is known about the underlying mechanism of this association. Insight is needed to improve treatment of trans autistic people. This review provides an overview of theories on the ASC-TGM link and the available evidence for/against them published between January 2016 and October 2020. A systematic search was performed in PubMed, PsycINFO, Web of Science, and Scopus. This resulted in 36 studies, in which 15 theories were identified. Results indicate all theories lack substantial empirical support. Unlikely and promising theories were identified. The most promising theories were those on resistance to social norms and weakened sex differences. Future directions are provided.

Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud-based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research.

The biological sciences community is increasingly recognizing the value of open, reproducible and transparent research practices for science and society at large. Despite this recognition, many researchers fail to share their data and code publicly. This pattern may arise from knowledge barriers about how to archive data and code, concerns about its reuse, and misaligned career incentives. Here, we define, categorize and discuss barriers to data and code sharing that are relevant to many research fields. We explore how real and perceived barriers might be overcome or reframed in the light of the benefits relative to costs. By elucidating these barriers and the contexts in which they arise, we can take steps to mitigate them and align our actions with the goals of open science, both as individual scientists and as a scientific community.

Nb3Sn is a promising thin film material for superconducting radio frequency (SRF) applications. Although surface resistivity, critical temperature, and critical field are advantageous in comparison to pure Nb, currently the performance of Nb3Sn is lacking behind due to its complex defect structure and phase inhomogeneities. In this work, the influence of the kinetic energy of the deposited particles on the defect structure in Nb3Sn thin films synthesized at low temperatures is investigated. A combination of extended x-ray absorption fine structure analysis, x-ray absorption spectroscopy mapping, and transmission electron microscopy reveals an improved local order and elemental homogeneity of the Nb3Sn films induced by higher kinetic energies of the elemental species during deposition. Even more, these process conditions lead to suppressed local inhomogeneities at grain boundaries, which can be one of the causes of critically reduced superconducting properties of low temperature sputter-coated Nb3Sn thin films. Finally, we show that the magnetic field-induced reduction of critical currents across weak-links formed at grain boundaries can be eliminated by the suggested materials' synthesis. [ABSTRACT FROM AUTHOR]

Objective: Patients with anorexia nervosa (AN) are often anxious, display inflexible behavior and disrupted reward processing. Emerging evidence suggests that gut dysbiosis in patients contributes to the disease phenotype and progression. Methods: In a preclinical study, we explored whether AN‐derived microbiota impacts cognitive flexibility, anxiety, and dopamine signaling using fecal microbiota transplantation (FMT) in tyrosine hydroxylase‐cre rats. We performed probabilistic reversal learning task (PRLT) at the baseline, after antibiotic treatment, and following FMT from patients with AN and controls. We assessed flexible behavior, task engagement, and ventral tegmental area (VTA) dopamine signaling during and in the absence of reward. Furthermore, anxiety‐like behavior was evaluated with open field (OF) and elevated plus maze (EPM) tests. Results: Neither antibiotic‐induced dysbiosis nor AN FMT led to significant alterations in the number of reversals or lever press strategies after reinforced or nonreinforced lever presses (win and lose‐stay) in the PRLT. However, the number of initiated trials decreased after antibiotic treatment while remaining unchanged after FMT. No significant differences were observed in VTA dopamine activity, anxiety measures in the OF and EPM tests. Microbiome analysis revealed limited overlap between the microbiota of the donors and recipients. Discussion: No evidence was found that the microbiota of patients compared to controls, nor a depleted microbiome impacts cognitive flexibility. Nonetheless, antibiotic‐induced dysbiosis resulted in reduced task engagement during the PRLT. The relatively low efficiency of the FMT is a limitation of our study and highlights the need for improved protocols to draw robust conclusions in future studies. Public Significance: While our study did not reveal direct impacts of AN‐associated gut microbiota on cognitive flexibility or anxiety behaviors in our preclinical model, we observed a decrease in task engagement after antibiotic‐induced dysbiosis, underscoring that the presence of a gut microbiome matters. Our findings underscore the need for further refinement in FMT protocols to better elucidate the complex interplay between gut microbiota and behaviors characteristic of anorexia nervosa. [ABSTRACT FROM AUTHOR]

A domestic ferret from Lima, Peru, died after ten days of non-specific clinical signs. Based on pathology, immunohistochemistry and molecular analysis, ferret systemic coronavirus (FRSCV)-associated disease was diagnosed for the first time in South America. This report highlights the potential spread of pathogens by the international pet trade.

Chronograms—phylogenies with branch lengths proportional to time—represent key data on timing of evolutionary events, allowing us to study natural processes in many areas of biological research. Chronograms also provide valuable information that can be used for education, science communication, and conservation policy decisions. Yet, achieving a high-quality reconstruction of a chronogram is a difficult and resource-consuming task. Here we present DateLife, a phylogenetic software implemented as an R package and an R Shiny web application available at www.datelife.org , that provides services for efficient and easy discovery, summary, reuse, and reanalysis of node age data mined from a curated database of expert, peer-reviewed, and openly available chronograms. The main DateLife workflow starts with one or more scientific taxon names provided by a user. Names are processed and standardized to a unified taxonomy, allowing DateLife to run a name match across its local chronogram database that is curated from Open Tree of Life's phylogenetic repository, and extract all chronograms that contain at least two queried taxon names, along with their metadata. Finally, node ages from matching chronograms are mapped using the congruification algorithm to corresponding nodes on a tree topology, either extracted from Open Tree of Life's synthetic phylogeny or one provided by the user. Congruified node ages are used as secondary calibrations to date the chosen topology, with or without initial branch lengths, using different phylogenetic dating methods such as BLADJ, treePL, PATHd8, and MrBayes. We performed a cross-validation test to compare node ages resulting from a DateLife analysis (i.e, phylogenetic dating using secondary calibrations) to those from the original chronograms (i.e, obtained with primary calibrations), and found that DateLife's node age estimates are consistent with the age estimates from the original chronograms, with the largest variation in ages occurring around topologically deeper nodes. Because the results from any software for scientific analysis can only be as good as the data used as input, we highlight the importance of considering the results of a DateLife analysis in the context of the input chronograms. DateLife can help to increase awareness of the existing disparities among alternative hypotheses of dates for the same diversification events, and to support exploration of the effect of alternative chronogram hypotheses on downstream analyses, providing a framework for a more informed interpretation of evolutionary results. [ABSTRACT FROM AUTHOR]