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The current strategy for biodiversity conservation is doomed. Based on a study of evidence-based summaries known as environmental impact assessment reports produced over the past 44 years, we suggest that biodiversity loss has not been halted because of a failure to accurately identify and assess the ecological effects of the drivers of change linked to land use planning. This failure is due to the poor representativeness of biological diversity in the practices of planners and the inadequate involvement of the ecologist community. Researchers in ecology could play a key role in improving the environmental considerations in project designs by focusing on preventive assessments instead of curative solutions.

By protein structure prediction (PSP) we refer to the prediction of the 3-dimensional (3D) folding of a protein, known as tertiary structure, starting from its amino acid sequence, known as primary structure. The state-of-the-art in PSP is currently achieved by complex deep learning pipelines that require several input features extracted from amino acid sequences. It has been demonstrated that features that grasp the relative orientation of amino acids in space positively impacts the prediction accuracy of the 3D coordinates of atoms in the protein backbone. In this paper, we demonstrate the relevance of Geometric Algebra (GA) in instantiating orientational features for PSP problems. We do so by proposing two novel GA-based metrics which contain information on relative orientations of amino acid residues. We then employ these metrics as an additional input features to a Graph Transformer (GT) architecture to aid the prediction of the 3D coordinates of a protein, and compare them to classical angle-based metrics. We show how our GA features yield comparable results to angle maps in terms of accuracy of the predicted coordinates. This is despite being constructed from less initial information about the protein backbone. The features are also fewer and more informative, and can be (i) closely associated to protein secondary structures and (ii) more readily predicted compared to angle maps. We hence deduce that GA can be employed as a tool to simplify the modeling of protein structures and pack orientational information in a more natural and meaningful way.

The ability of satellite instruments to accurately observe long-term changes in atmospheric temperature depends on many factors including the absolute accuracy of the measurement, the stability of the calibration of the instrument, the stability of the satellite orbit, and the stability of the numerical algorithm that produces the temperature data. We present an example of algorithm instability recently discovered in the temperature dataset from the SABER instrument on the NASA TIMED satellite. The instability resulted in derived temperatures that were substantially colder than anticipated from mid-December 2019 to mid-2022. This algorithm-induced change in temperature over one to two years corresponded to the expected change over several decades from increasing anthropogenic CO2. This paper highlights the importance of algorithm stability in developing Geospace Data Records (GDRs) for Earth’s mesosphere and lower thermosphere. A corrected version (Version 2.08) of the temperatures from SABER is described.

We're in a crisis We are in the midst of an unprecedented global crisis. Just weeks since its outbreak, the Coronavirus pandemic (COVID-19) has already affected, and will continue to affect, our daily lives, around the globe, for the foreseeable future. The answers and the solutions to this crisis will come from science. But the crisis affects science, too.It affects students, educators, and researchers; not just their day-to-day lives, social ties, and work routines, but also their ability to actively collaborate, convene in face-to-face meetings, attend academic conferences, teach and learn in an open university setting, pay a visit to the library, work overnight at the laboratory, and so on.But the thing is: science cannot stop. Scientific progress must go on. For each one of the challenges that scientists face in this time of crisis, there is, or there will be, a solution. We believe that the solution is not to be found in a single technological tool, product, framework, institution, funding agency, or company. It is the global cyber-infrastructure of scientific collaboration, built on scientific rigor, intellectual curiosity, and cooperation, that will enable science to advance in such difficult times. The power of scientific collaborationAs scientists, publishers, science communicators and technologists, we believe that: a. Science is the solution to the ongoing crisis. Now more than ever, reliance on the scientific method, rigor and clarity of scientific communication, transparency, reproducibility, and seamless sharing of all research data (including negative results), are fundamental to solving this health crisis and advancing human progress.b. Global collaboration and cooperation, beyond and above national and economic interests, is necessary not only at the scientific level, but also at the political and societal level. We're more interconnected and interdependent today than ever. And such interconnectedness extends to the ecological ecosystem in which we live. A crisis of such scale requires global solidarity, bipartisan political action, civic participation, and long-term thinking.

In 2016, Crossref launched a metadata schema for ‘posted content’ with the aim of better accommodating the metadata needs for preprints, working papers, theses, reports, and related outputs, which are not typically peer-reviewed. In 2021, Crossref formed an Advisory Group (AG) to discuss how the quality of metadata for preprints using this schema could be improved. The group focused on four topics: 1) preprints as an article type (rather than subtype of posted-content); 2) relationships to/from preprints; 3) versioning; and 4) withdrawal/removal of preprints. The recommendations that resulted from the group’s deliberations have been published previously. Here we provide further background to the recommendations and report more details of the discussions.

In order for science to be truly open, readers and reviewers must be able to understand how authors produced the computational results, which parameters were used for the analysis, and how manipulations to these parameters affect the results. Increasingly, journals and funding agencies are mandating that researchers share their code and data when reporting on computational results. However, even when data and code are provided by authors, and published, they are oftentimes just posted as links and relegated to platforms entirely separated from publishing workflows, disconnected from the published “full text”. We believe that preprints are better suited than external repositories in enabling open, reproducible science because they are connected to the published full text via scholarly infrastructure, they are author-centric, and allow versioning. In particular, we propose a simple (yet innovative and experimental) workflow whereby authors deposit a preprint version of their articles in an html-first preprint server. In it, authors can then enhance the preprint, through edits and revisions, with data, code, computational notebooks, interactive visualizations, and dashboards. As such, preprints can be used as an experimental vehicle for directly disseminating the interactive, data-driven, and multi-media nature of Open Science outputs, in parallel and connected with more traditional published outputs.

14 pags., 13 figs., 5 tabs. -- MSC Classification: 68T40, 68T45, 68U05, Many problems in computer vision today are solved via deep learning. Tasks like pose estimation from images, pose estimation from point clouds or structure from motion can all be formulated as a regression on rotations. However, there is no unique way of parametrizing rotations mathematically: matrices, quaternions, axis-angle representation or Euler angles are all commonly used in the field. Some of them, however, present intrinsic limitations, including discontinuities, gimbal lock or antipodal symmetry. These limitations may make the learning of rotations via neural networks a challenging problem, potentially introducing large errors. Following recent literature, we propose three case studies: a sanity check, a pose estimation from 3D point clouds and an inverse kinematic problem. We do so by employing a full geometric algebra (GA) description of rotations. We compare the GA formulation with a 6D continuous representation previously presented in the literature in terms of regression error and reconstruction accuracy. We empirically demonstrate that parametrizing rotations as bivectors outperforms the 6D representation. The GA approach overcomes the continuity issue of representations as the 6D representation does, but it also needs fewer parameters to be learned and offers an enhanced robustness to noise. GA hence provides a broader framework for describing rotations in a simple and compact way that is suitable for regression tasks via deep learning, showing high regression accuracy and good generalizability in realistic high-noise scenarios., This work has been supported by the Signal Processing & Communications Group of Cambridge University EngineeringDepartment (CUED)

The Crossref Preprint Advisory Group (AG) was formed in June 2021 to discuss metadata issues related to preprints. It has the following aims...

This Supporting information includes supporting fugures and videos for our paper. The information’s Fig. 16 is the high-quality version of the article’s Supplementary Movie 1. Corresponding author(s) Email: nakashima@robot.t.u-tokyo.ac.jp

Introducción: El Síndrome de Burnout es un trastorno adaptativo, crónico, asociado con inadecuado afrontamiento de las demandas psicológicas del trabajo, es el origen de daño laboral de causa psicosocial más importante. Objetivo: Conocer el riesgo de Burnout en médicos de la ciudad de Córdoba, su relación con factores sociodemográficos y con especialidades clínicas o quirúrgicas. Métodos: Se realizó un estudio observacional de corte transversal en 10 centros asistenciales públicos y privados de la Ciudad de Córdoba. Se entrevistaron 483 médicos, recogiendo variables sociodemográficas y cuestionario Maslach Burnout Inventory evaluando el riesgo de Burnout. La edad fue estratificada desde los 20 años, de 10 en 10 hasta 60. p < 0,05 fue significativa. Resultados: Se entrevistaron 483 médicos, 62,1% mujeres, el 70% entre los 20 y los 40 años; 54,2% solteros, 42.9% ejerció < de 5 años la profesión; el 66 del total (16,5%) tuvo alto riesgo de Burnout, las variables asociadas fueron: trabajar en un establecimiento público (p < 0,00001), ser soltero (p < 0,009), trabajar más de 60 hs (p < 0,001), dormir menos de 42 hs semanales (p< 0,005), tener entre 20 y 29 años (p

Mortality from cardiovascular disease (CVD) is increased in rheumatoid arthritis, not explained by traditional cardiovascular risk factors (CVRF), suggesting a role of inflammation. This process would occur early. The common sonographic markers of subclinical atherosclerosis (SA), are increased carotid intima-media thickness (cIMT) or the presence of carotid atherosclerotic plaque and they are closely related to CVD.To evaluate sonographic markers and cardiovascular risk factors in early Arthritis (EA).A case control study of patients with EA, defined by 3 joints swollen with1 year of evolution, served consecutively from January 2011 to may 2013, matched with healthy controls, by sex, age and cardiovascular risk factors (hypertension, diabetes mellitus, cardiovascular disease -IAM and ACV, dyslipidemia, family history of CVD) was conducted. We studied demographics data, cardiovascular risk factors, carotid ultrasound measuring increased cIMT or the presence of carotid atherosclerotic plaque in Common Carotid Artery (CCA) and Carotid Bulb (BC), laboratory test that included cholesterol, LDL, HDL, triglycerides in mg%, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR ), anti citrullinated peptide (ACCP), rheumatoid factor (RF), antinuclear antibodies (ANA). EA activity was measured by DAS 28, considering high disease activity (HDA) 5.1; moderate (MDA) from 5.1 to 3.2; and low (LDA)3.2. Statistics: test Mann-Whitney and chi-square were used, p0.05 was significant.25 women, 5 men, average age 43 years (DS 14.7) and 30 controls were included. The average DAS 28 was 4, 8 ± 1. 8; 47% had HDA, 33%MDA and 20%BDA. Both groups had similar values cIMT CCA (0, 57 ± 0.10 mm vs. 0.58 ± 0.15 mm, respectively, P = 0.82) and cIMT BC (0.18mm ± 0.67 vs 0.62 ± 0.15 mm respectively, P = 0.47). There were no carotid plaques. The median total cholesterol was 181,5 vs 183,5 (p = 0.35); triglycerides 99 vs 92,5 (p = 0.68); HDL 54,5 vs 52,5 (p = 0.921 and LDL 105 vs 110 (p = 0.27) in EA and controls respectively. The cIMT CCA and CB were not related to RF, ACCP, CRP, DAS 28 and smoking (NS). There was no difference in other cardiovascular risk factorsUltrasound evidence of atherosclerosis subclinical markers was not found in this study, suggesting that this process may occur after a year of diagnosis.La mortalidad por Enfermedad cardiovascular (ECV) temprana está incrementada en enfermedades inflamatorias. Los marcadores ecográficos de aterosclerosis subclínica (AS) están estrechamente relacionados con ECV.Evaluar marcadores de AS ecográficos y Factores de Riesgo Cardiovascular (FRCV) en Artritis temprana (AT) y correlacionarlo con la actividad de la enfermedad.Estudio transversal de casos y controles en pacientes con AT, definida por 3 articulaciones inflamadas con menos de 1 año de evolución, realizado desde 2011 a 2013, apareados con controles sanos, por sexo, edad y FRCV. Se registraron datos demográficos, FRCV, rigidez de pared (cIMT) en Arteria Carótida Común (ACC) y en Bulbo Carotídeo (BC) y presencia de placas ateroscleróticas por ecografía, perfil lipídico, Proteína C Reactiva, eritrosedimentación, anticuerpos anti péptido citrulinado, Factor reumatoide, anticuerpos antinucleares. La actividad de AT se midió por Disease Activity Score (DAS) 28. Estadística: Se usaron test U de Mann-Whitney, Kruskal Wallis y chi-cuadrado, plt;0,05 fue significativo.Se incluyeron 25 mujeres, 5 hombres con edad promedio 40 años (18-61) y 30 controles. El DAS 28 promedio fue 4,8 ±1.8. Pacientes y controles tuvieron similares valores cIMT ACC (0, 57 ±0.10 mm vs 0,58 ± 0,15 mm, respectivamente) y cIMT CB (0,67 ±0,18mm vs 0,62 ±0,15 mm), no hubo placas carotídeas y el perfil lipídico fue similar en ambos grupos, PNS. El cIMT CCA y CB no tuvieron relación con DAS 28, serología, ni FRCV, P: NS.La aterosclerosis subclínica se produciría después del primer año de enfermedad en artritis temprana.