Scientists have long been trying to understand why the Neotropical region holds the highest diversity of birds on Earth. Recently, there has been increased interest in morphological variation between and within species, and in how climate, topography, and anthropogenic pressures may explain and affect phenotypic variation. Because morphological data are not always available for many species at the local or regional scale, we are limited in our understanding of intra‐ and interspecies spatial morphological variation. Here, we present the ATLANTIC BIRD TRAITS, a data set that includes measurements of up to 44 morphological traits in 67,197 bird records from 2,790 populations distributed throughout the Atlantic forests of South America. This data set comprises information, compiled over two centuries (1820–2018), for 711 bird species, which represent 80% of all known bird diversity in the Atlantic Forest. Among the most commonly reported traits are sex (n = 65,717), age (n = 63,852), body mass (n = 58,768), flight molt presence (n = 44,941), molt presence (n = 44,847), body molt presence (n = 44,606), tail length (n = 43,005), reproductive stage (n = 42,588), bill length (n = 37,409), body length (n = 28,394), right wing length (n = 21,950), tarsus length (n = 20,342), and wing length (n = 18,071). The most frequently recorded species are Chiroxiphia caudata (n = 1,837), Turdus albicollis (n = 1,658), Trichothraupis melanops (n = 1,468), Turdus leucomelas (n = 1,436), and Basileuterus culicivorus (n = 1,384). The species recorded in the greatest number of sampling localities are Basileuterus culicivorus (n = 243), Trichothraupis melanops (n = 242), Chiroxiphia caudata (n = 210), Platyrinchus mystaceus (n = 208), and Turdus rufiventris (n = 191). ATLANTIC BIRD TRAITS (ABT) is the most comprehensive data set on measurements of bird morphological traits found in a biodiversity hotspot; it provides data for basic and applied research at multiple scales, from individual to community, and from the local to the macroecological perspectives. No copyright or proprietary restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications or teaching and educational activities.

A major barrier to advancing ornithology is the systemic exclusion of professionals from the Global South. A recent special feature, Advances in Neotropical Ornithology, and a shortfalls analysis therein, unintentionally followed a long-standing pattern of highlighting individuals, knowledge, and views from the Global North, while largely omitting the perspectives of people based within the Neotropics. Here, we review current strengths and opportunities in the practice of Neotropical ornithology. Further, we discuss problems with assessing the state of Neotropical ornithology through a northern lens, including discovery narratives, incomplete (and biased) understanding of history and advances, and the promotion of agendas that, while currently popular in the north, may not fit the needs and realities of Neotropical research. We argue that future advances in Neotropical ornithology will critically depend on identifying and addressing the systemic barriers that hold back ornithologists who live and work in the Neotropics: unreliable and limited funding, exclusion from international research leadership, restricted dissemination of knowledge (e.g., through language hegemony and citation bias), and logistical barriers. Moving forward, we must examine and acknowledge the colonial roots of our discipline, and explicitly promote anti-colonial agendas for research, training, and conservation. We invite our colleagues within and beyond the Neotropics to join us in creating new models of governance that establish research priorities with vigorous participation of ornithologists and communities within the Neotropical region. To include a diversity of perspectives, we must systemically address discrimination and bias rooted in the socioeconomic class system, anti-Blackness, anti-Brownness, anti-Indigeneity, misogyny, homophobia, tokenism, and ableism. Instead of seeking individual excellence and rewarding top-down leadership, institutions in the North and South can promote collective leadership. In adopting these approaches, we, ornithologists, will join a community of researchers across academia building new paradigms that can reconcile our relationships and transform science. Spanish and Portuguese translations are available in the Supplementary Material.

International audienceThe semiconductor manufacturing industry has a large-volume multistage manufacturing system. To insure the high stability and the production yield on-line a reliable wafer monitoring is required. The approach, called Virtual Metrology (VM) is defined as the prediction of metrology variables (either measurable or non measurable) using process and wafer state information. It consists in the definition and the application of some predictive and corrective models for metrology outputs (physical measurements) in function of the previous metrology outputs and of the equipment parameters of current and previous steps of fabrication. The goals of this paper are to present a methodology for VM module for individual process applications in semiconductor manufacturing and to present a case study based on industrial data

A major barrier to advancing ornithology is the systemic exclusion of professionals from the Global South. A recent special dossier, Advances in Neotropical Ornithology, and a shortfalls analysis therein, unintentionally followed a long-standing pattern of highlighting individuals, knowledge, and views from the Global North, while largely omitting the perspectives of people based within the Neotropics. Here, we review problems with assessing the state of Neotropical ornithology through a northern lens, including discovery narratives, incomplete (and biased) understanding of history and advances, and the promotion of agendas that, while currently popular in the north, may not fit the needs and realities of Neotropical research. We argue that future advances in Neotropical ornithology will critically depend on identifying and addressing the systemic barriers that hold back ornithologists who live and work in the Neotropics: unreliable and limited funding, exclusion from international research leadership, restricted dissemination of knowledge (e.g., through language hegemony and citation bias), and logistical barriers. Moving forward, we must examine and acknowledge the colonial roots of our discipline, and explicitly promote anticolonial research, training, and conservation agendas. We invite our colleagues within and beyond the Neotropics to join us in creating a new model of governance that establishes research priorities with vigorous partici-pation of ornithologists and other stakeholders within the Neotropical region. To include a diversity of perspectives, we must systemically address discrimination and bias rooted in the socioeconomic class system, anti-Blackness, anti-Brownness, anti-Indigeneity, misogyny, homophobia, tokenism, and ableism. Instead of seeking individual excellence and rewarding top-down leadership, institutions in the North and South can promote collective leadership. Authentic collaborations should value the perspectives of those directly involved and affected by policies. In adopting these approaches, we, ornithologists, will join a community of researchers across academia building new paradigms that can reconcile our relationships and transform science.

The semiconductor industry is continuously facing four main challenges in film characterization techniques: accuracy, speed, throughput and flexibility. Virtual Metrology (VM), defined as the prediction of metrology variables using process and wafer state information, is able to successfully address these four challenges. VM is understood as definition and application of predictive and corrective mathematical models to specify metrology outputs (physical measurements). These statistical models are based on metrology data and equipment parameters. The objective of this study is to develop a model predicting the CVD oxide thickness (average) for an IMD (Inter Metal Dielectric) deposition process using FDC data (Fault Detection and Classification) and metrology data. In this paper, two VM models are studied: one based on Partial Least Squares Regression (PLS) and one based on Tree ensembles. We will demonstrate that both models show good predictive strength. Finally, we will highlight that model update is key for ensuring a good model robustness over time and that an indicator of confidence of the predicted values is necessary too if the VM model has to be use on-line in a production environment.