The organic electrochemical transistor (OECT), with its organic mixed ionic–electronic conductor (OMIEC) channel, serves as an amplifying transducer of biological signals. This Review highlights OMIEC design milestones and illustrates how incorporating specific properties into OMIECs can extend OECT applications beyond biosensing.
There is no doubt that water is significant. Without it, life would never have begun, let alone continue today—not to mention its role in the environment itself, with oceans covering over 70% of Earth.
But despite its ubiquity, liquid water features some electronic intricacies that have long puzzled scientists in chemistry, physics, and technology. For example, the electron affinity, i.e., the energy stabilization undergone by a free electron when captured by water, has remained poorly characterized from an experimental point of view.
Even today’s most accurate electronic structure theory has been unable to clarify the picture, which means that important physical quantities like the energy at which electrons from external sources can be injected in liquid water remain elusive. These properties are crucial for understanding the behavior of electrons in water and could play a role in biological systems, environmental cycles, and technological applications like solar energy conversion.
Posted in biological, mathematics, neuroscience
Alex Rosenberg is professor of Philosophy at Duke University and has made several important contributions to the philosophy of science, biology, and social science.
0:00 intro.
2:53 scientism.
5:09 naturalism and the manifest image.
7:25 pragmatism.
10:40 intentionality.
12:38 objections to eliminativism and truth.
14:35 consciousness.
16:50 biological functions, purposes, and the selected effects theory.
22:28 reductionism.
28:05 causality.
31:02 multiple realizability.
35:13 math.
39:45 morality.
44:51 humanism, art, and history.
Alex Rosenberg’s website: https://alexrosenbergbooks.com/
Alex Rosenberg Books:
Alex Rosenberg is the R. Taylor Cole Professor of Philosophy at Duke University. His research focuses on the philosophy of biology and science more generally, mind, and economics.
/ friction.
/ discord.
/ frictionphilo.
00:00 — Introduction.
01:47 — Scientism.
05:16 — Naturalism.
08:08 — Methodological or substantive?
09:40 — Eliminativism about intentionality.
11:50 — Moorean shift.
13:28 — Arguments against eliminativism.
21:19 — Papineau on intentionality.
25:43 — Consciousness.
29:29 — Companions in guilt.
31:30 — Fodor and natural selection.
37:26 — No selection for?
38:16 — Properties.
39:21 — Selection for/against.
40:34 — Selection for long necks in giraffes.
42:26 — Speaking with the vulgar?
44:26 — Selection against as intensional.
47:12 — Function and selection for.
49:11 — Skepticism.
50:59 — Example.
52:06 — Mereological nihilism.
53:23 — Value of philosophy.
55:22 — Nihilism?
1:00:03 — Conclusion.
Music: PaulFromPayroll — High Rise
Eyes with lower pigment (blue or grey eyes) don’t need to absorb as much light as brown or dark eyes before this information reaches the retinal cells. This might provide light-eyed people with some resilience to SAD.
Other theories propose it happens due to an imbalance in serotonin and melatonin in the body. Serotonin makes us feel energetic, while the release of melatonin makes us feel sleepy. Since melatonin is made from serotonin, people with SAD may potentially produce too much melatonin during the winter months, leaving them feeling lethargic or down.
All these studies are inconsistent and, in some cases, contradictory. But because SAD is likely due to a combination of many biological and physiological factors working together, these different explanations for what causes SAD may well be interconnected.
We have uncovered evidence that a person’s eye colour can have a direct effect on how susceptible they are to SAD.
An international team of researchers, led by Swinburne University of Technology, demonstrated what it claimed is the world’s fastest and most powerful optical neuromorphic processor for artificial intelligence (AI). It operates faster than 10 trillion operations per second (TeraOPs/s) and is capable of processing ultra-large scale data.
The researchers said this breakthrough represents an enormous leap forward for neural networks and neuromorphic processing in general. It could benefit autonomous vehicles and data-intensive machine learning tasks such as computer vision.
Artificial neural networks can ‘learn’ and perform complex operations with wide applications. Inspired by the biological structure of the brain’s visual cortex system, artificial neural networks extract key features of raw data to predict properties and behaviour with unprecedented accuracy and simplicity.
Do the impacts of deforestation go beyond the environment? What about human health, specifically the health of children? This is what a recent study published in Economics & Human Biology hopes to address as Dr. Gabriel Fuentes Cordoba, who is an associate professor of economics from Sophia University in Japan, investigated how deforestation in Cambodia effects the health of children around the time of their birth. This study holds the potential to help scientists, conservationists, and the public better understand the health effects of deforestation, specifically with the increasing effects of climate change around the world.
For the study, Dr. Fuentes Cordoba analyzed data obtained from the Cambodian Demographic Health Surveys and forest loss to ascertain the health impacts for pregnant women and children under five years of age who reside in areas of deforestation. In the end, Dr. Fuentes Cordoba discover alarming results that suggest deforestation exposure to women less than one year before pregnancy could lead to development of anemia, which is a precursor to malaria. This could result in significant health impacts on children being born, specifically reductions in birth weight, along with overall height and weight as they age.
“This research shows a negative impact of deforestation on child health,” Dr. Fuentes Cordoba said in a statement. “This negative impact may persist into adulthood and affect other aspects of wellbeing such as education acquisition and even wages. My findings indicate that future research should explore this aspect further.”
This definitely is a Lifeboat post embodying what Lifeboat is about, and it’s only about AI. They did a really good job explaining the 10 stages.
This video explores the 10 stages of AI, including God-Like AI. Watch this next video about the Technological Singularity: • Technological Singularity: 15 Ways It…
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While Artificial Intelligence (AI) focuses on simulating and surpassing human intelligence, Artificial Life (A-Life) takes a different approach. Instead of replicating cognitive abilities, A-Life seeks to understand and model fundamental biological processes through software, hardware, and even… wetware.
Forget Turing tests and chess games. A-Life scientists don’t care if their creations are “smart” in the traditional sense. Instead, they’re fascinated by the underlying rules that govern life itself. Think of it as rewinding the movie of evolution, watching it unfold again in a digital petri dish.
Explaining isolated steps on the road from simple chemicals to complex living organisms is not enough. Looking at the big picture could help to bridge rifts in this fractured research field.
