Standardizing wastewater pathogen genomics data is key to better surveillance & response! Our Wastewater Contextual Data Specification ensures harmonized, ontology-based metadata for global use. 💧🦠
Learn more & contribute: https://t.co/uYYSfJN084
Mais do que retirada dos Estados Unidos da OMS, estamos diante de uma ruptura, bem mais complexa do que parece ser. É o que tento explicar em minha coluna no Jornal da USP @usponline 👇
https://t.co/ujSrNDQlK2
The thing that hasn’t sunk in for most people is the scale of climate change. We’re talking about the whole planet.
I saw a scientist on the news today saying not only is 2024 the hottest year ever recorded, the 🌎 is hotter now than in at least 100,000 years.
#LosAngelesFires
Great (and scary) visualization of 2024 daily temperatures compared to prior years by the BBC today. Evocative of the iconic Joy Division album cover from 1979: https://t.co/o2zLigFV7h
I’m pleased to share a collaboratively developed article showcasing a collective effort to apply a transdisciplinary approach to synthesis dynamics. I hope the learnings gained will inspire other initiatives at the science-policy interface - https://t.co/7PB7gex7sc
Neste #DiaDaConsciênciaNegra, compartilho um pouco da minha história enquanto cientista.
Que possamos construir uma sociedade mais justa, onde crianças negras tenham oportunidades iguais e cresçam cercadas de referências inspiradoras que as façam acreditar no seu potencial.
Understanding the difference between Standard Deviation (SD) and Standard Error (SE) is crucial for accurate data interpretation. SD measures the variability within your data, indicating how spread out the individual data points are from the mean.
In contrast, SE measures the uncertainty around the sample mean as an estimate of the population mean. It reflects the precision of the mean, with SE decreasing as the sample size increases, making your estimate more reliable.
The relationship between SD and SE is given by the formula: SE = SD / √(sample size). While SD remains relatively constant with larger samples, SE diminishes, highlighting the reduced uncertainty in the mean estimate.
A common mistake in research is using the “±” notation without specifying whether it refers to SD or SE, leading to potential misinterpretation of the data. Clear distinction is essential for transparency and accuracy in reporting.
Key Takeaways:
• Use SD to describe data variability.
• Use SE to indicate the precision of the mean.
• Always specify which measure you are reporting.
Elsevier is one of the largest, most hated and most influential academic publishing companies in the world.
How it started & how it's going
A thread🧵
O mundo enfrenta uma ameaça conhecida e negligenciada e que hoje, foi declarada como Emergência de Saúde Pública de Interesse Internacional: #mpox
Nesse fio, falo de sintomas, transmissão, vacinas e por que temos uma 2ª emergência declarada num período de 2 anos 🔻
Antricola is one of the few ticks with maternal behaviour. Actually with altruistic behaviour: females carry larvae of any other female. Survival of the species, not the lineage
#AcessoLivre | [opinião] “No Brasil, eventos climáticos extremos mostram como as decisões políticas locais influenciam a relação entre a crise climática e suas consequências.” Leia no ensaio de Gabriela Di Giulio e Jean Paul Metzger do @BiotaFAPESP https://t.co/ngEakyXs38