A Statistical Estimation of the Occurrence of Extraterrestrial Intelligence in the Milky Way Galaxy

In the field of astrobiology, the precise location, prevalence, and age of potential extraterrestrial intelligence (ETI) have not been explicitly explored. Here, we address these inquiries using an empirical galactic simulation model to analyze the spatial–temporal variations and the prevalence of potential ETI within the Galaxy. This model estimates the occurrence of ETI, providing guidance on where to look for intelligent life in the Search for ETI (SETI) with a set of criteria, including well-established astrophysical properties of the Milky Way. Further, typically overlooked factors such as the process of abiogenesis, different evolutionary timescales, and potential self-annihilation are incorporated to explore the growth propensity of ETI. We examine three major parameters: (1) the likelihood rate of abiogenesis (λ_A); (2) evolutionary timescales (T_(evo)); and (3) probability of self-annihilation of complex life (P_(ann)). We found P_(ann) to be the most influential parameter determining the quantity and age of galactic intelligent life. Our model simulation also identified a peak location for ETI at an annular region approximately 4 kpc from the galactic center around 8 billion years (Gyrs), with complex life decreasing temporally and spatially from the peak point, asserting a high likelihood of intelligent life in the galactic inner disk. The simulated age distributions also suggest that most of the intelligent life in our galaxy are young, thus making observation or detection difficult

Avoiding the Great Filter : predicting the timeline for humanity to reach Kardashev Type I civilization

The level of technological development of any civilization can be gauged in large part by the amount of energy it produces for its use, but also encompasses that civilization’s stewardship of its home world. Following the Kardashev definition, a Type I civilization is able to store and use all the energy available on its planet. In this study, we develop a model based on Carl Sagan’s K formula, and use this model to analyze the consumption and energy supply of the three most important energy sources: fossil fuels (e.g., coal, oil, natural gas, crude, NGL, and feedstocks), nuclear energy, and renewable energy. We also consider environmental limitations suggested by the United Nations Framework Convention on Climate Change, the International Energy Agency, and those specific to our calculations, to predict when humanity will reach the level of a Kardashev Scale Type I civilization. Our findings suggest that the best estimate for our civilization to attain Type I status is within the common calendar year range of 2333 to 2404

Avoiding the Great Filter: A Simulation of Important Factors for Human Survival

Humanity's path to avoiding extinction is a daunting and inevitable challenge which proves difficult to solve, partially due to the lack of data and evidence surrounding the concept. We aim to address this confusion by addressing the most dangerous threats to humanity, in hopes of providing a direction to approach this problem. Using a probabilistic model, we observed the effects of nuclear war, climate change, asteroid impacts, artificial intelligence and pandemics, which are the most harmful disasters in terms of their extent of destruction on the length of human survival. We consider the starting point of the predicted average number of survival years as the present calendar year. Nuclear war, when sampling from an artificial normal distribution, results in an average human survival time of 60 years into the future starting from the present, before a civilization-ending disaster. While climate change results in an average human survival time of 193 years, the simulation based on impact from asteroids results in an average of 1754 years. Since the risks from asteroid impacts could be considered to reside mostly in the far future, it can be concluded that nuclear war, climate change, and pandemics are presently the most prominent threats to humanity. Additionally, the danger from superiority of artificial intelligence over humans, although still somewhat abstract, is worthy of further study as its potential for impeding humankind's progress towards becoming a more advanced civilization cannot be confidently dismissed

Forecasting the Impact of Stellar Activity on Transiting Exoplanet Spectra

Exoplanet host star activity, in the form of unocculted starspots or faculae, alters the observed transmission and emission spectra of the exoplanet. This effect can be exacerbated when combining data from different epochs if the stellar photosphere varies between observations due to activity. Here, we present a method to characterize and correct for relative changes due to stellar activity by exploiting multi-epoch (⩾2 visits/transits) observations to place them in a consistent reference frame. Using measurements from portions of the planet's orbit where negligible planet transmission or emission can be assumed, we determine changes to the stellar spectral amplitude. With the analytical methods described here, we predict the impact of stellar variability on transit observations. Supplementing these forecasts with Kepler-measured stellar variabilities for F-, G-, K-, and M-dwarfs, and predicted transit precisions by the James Webb Space Telescope's (JWST) NIRISS, NIRCam, and MIRI, we conclude that stellar activity does not impact infrared transiting exoplanet observations of most presently known or predicted TESS targets by current or near-future platforms, such as JWST, as activity-induced spectral changes are below the measurement precision

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Avoiding the “Great Filter”: A Projected Timeframe for Human Expansion Off-World

A foundational model has been developed based on trends built from empirical data of space exploration and computing power through the first six plus decades of the Space Age, which projects the earliest possible launch dates for human-crewed missions from cis-lunar space to selected Solar System and interstellar destinations. The model uses computational power, expressed as transistors per microprocessor, as a key broadly limiting factor for deep space missions’ reach and complexity. The goal of this analysis is to provide a projected timeframe for humanity to become a multi-world species through off-world colonization, and in so doing all but guarantee the long-term survival of the human race from natural and human-caused calamities that could befall life on Earth. Beginning with the development and deployment of the first nuclear weapons near the end of World War II, humanity entered a ‘Window of Peril’, which will not be safely closed until robust off-world colonies become a reality. Our findings suggest that the first human-crewed missions to land on Mars, selected Asteroid Belt objects, and selected moons of Jupiter and Saturn can occur before the end of the 21st century. Launches of human-crewed interstellar missions to exoplanet destinations within roughly 40 lightyears of the Solar System are seen as possible during the 23rd century and launch of intragalactic missions by the end of the 24th century. An aggressive and sustained space exploration program, which includes colonization, is thus seen as critical to the long-term survival of the human race

A Statistical Estimation of the Occurrence of Extraterrestrial Intelligence in the Milky Way Galaxy

In the field of astrobiology, the precise location, prevalence, and age of potential extraterrestrial intelligence (ETI) have not been explicitly explored. Here, we address these inquiries using an empirical galactic simulation model to analyze the spatial–temporal variations and the prevalence of potential ETI within the Galaxy. This model estimates the occurrence of ETI, providing guidance on where to look for intelligent life in the Search for ETI (SETI) with a set of criteria, including well-established astrophysical properties of the Milky Way. Further, typically overlooked factors such as the process of abiogenesis, different evolutionary timescales, and potential self-annihilation are incorporated to explore the growth propensity of ETI. We examine three major parameters: (1) the likelihood rate of abiogenesis (λA); (2) evolutionary timescales (Tevo); and (3) probability of self-annihilation of complex life (Pann). We found Pann to be the most influential parameter determining the quantity and age of galactic intelligent life. Our model simulation also identified a peak location for ETI at an annular region approximately 4 kpc from the galactic center around 8 billion years (Gyrs), with complex life decreasing temporally and spatially from the peak point, asserting a high likelihood of intelligent life in the galactic inner disk. The simulated age distributions also suggest that most of the intelligent life in our galaxy are young, thus making observation or detection difficult