In this enlightening episode, we welcome Dr. Cheng, a leading researcher in the field of machine learning (ML). We explore the innovative approach of ML in representing molecular-orbital-based (MOB) features for predicting post-Hartree–Fock correlation energies. Though previous applications of MOB-ML using Gaussian Process Regression (GPR) have shown promise, Dr. Cheng addresses the limitations of this method, particularly its computational constraints, when dealing with large datasets.

Dr. Cheng introduces us to an advanced approach, employing a clustering/regression/classification model of MOB-ML. He elaborates on the three-step process: partitioning the training data using regression clustering (RC), independently regressing each cluster using either linear regression (LR) or GPR, and training a random forest classifier (RFC) for predicting cluster assignments based on MOB feature values. Dr. Cheng's explanation underscores how this method dramatically reduces computational time while maintaining prediction accuracy.

This episode offers fascinating insights into how this pioneering approach can reach chemical accuracy with limited training data, demonstrating significant speed increases compared to traditional MOB-ML techniques. Moreover, we learn how the developed models can predict large-molecule energies accurately, even when trained only on small-molecule data.

Join us as we delve into this captivating topic, shedding light on the intersection of chemistry and ML and the transformative potential these methodologies hold for the future of scientific computation.

Keywords: Machine Learning, ML, Molecular-Orbital-Based Features, MOB-ML, Gaussian Process Regression, GPR, Regression Clustering, RC, Linear Regression, LR, Random Forest Classifier, RFC, Computational Chemistry, Post-Hartree–Fock Correlation Energies.

https://pubs.acs.org/doi/abs/10.1021/acs.jctc.9b00884

In a fascinating conversation with Dr. Guo, we delve into the world of canine emotion perception and their ability to understand both human and dog emotions. Domestic dogs, unlike many other species, have uniquely evolved to recognize and interpret the emotions of not only their own species but also those of humans, their closest companions.

In this episode, Dr. Guo illuminates his research by employing a cross-modal preferential-looking paradigm to study dogs' reactions to different emotional expressions. Dogs were presented with either human or dog faces displaying varying emotional states—ranging from happiness and playfulness to anger and aggression. These visual cues were paired with vocalizations that either matched the emotion displayed or contradicted it, or with neutral Brownian noise.

Dr. Guo shares the intriguing finding that dogs spent significantly longer periods looking at the face that matched the emotional tone of the vocalization. This behavior was observed not only with other dogs but also with human emotions, indicating a level of emotional comprehension previously believed to be exclusive to humans.

This conversation provides insights into the incredible cognitive abilities of dogs, and how they can extract, integrate, and differentiate between positive and negative emotions from both humans and dogs. Tune in for an eye-opening discussion about the emotional intelligence of our canine companions.

Keywords: Canine emotion perception, cross-modal preferential looking paradigm, emotional valence, cognitive representation, bimodal sensory, emotional information, human emotions, dog emotions, animal behavior, animal cognition.

https://doi.org/10.1098/rsbl.2015.0883 Dogs can extract and integrate bimodal sensory emotional information and discriminate between positive and negative emotions from both humans and dogs.

In this fascinating episode, we welcome Dr. Ulijn, a pioneering researcher in the field of peptide sequence buildup and molecular adaptation. He delves into his groundbreaking study that illuminates the behavior of living systems and their distinctive ability to distribute stress among a vast number of covalent and noncovalent interactions in mixtures of molecules.

Dr. Ulijn takes us on a journey into the world of biomolecular complexity, starting from the basics. He discusses how the selection of a chemical interaction space of mixtures of 5 or 15 dipeptides, through reversible enzymatic sequence exchange, can produce 25 or 225 dynamically interacting tetrapeptides. This setup allows his team to study complex systems that are usually challenging to investigate due to their inherent complexity.

Dr. Ulijn describes the complex process through which the abundance of tetrapeptide sequences can be analyzed, leading to patterns that are surprisingly interpretable. These patterns reveal that a system with this level of complexity is capable of responding stochastically, self-organizing, and driving sequence selective oligomerization in response to changes in external conditions.

Moreover, he explains how the system exhibits robustness, demonstrating its ability to distribute the impact of a change of conditions across a multitude of interactions. The episode culminates in a fascinating discussion of the implications of this research on our understanding of living systems.

If you're interested in peptide sequences, molecular complexity, and the adaptive capabilities of living systems, this conversation with Dr. Ulijn will captivate you.

Keywords: Peptide Sequence Buildup, Enzymatic Exchange, Dipeptides, Tetrapeptides, Biomolecular Complexity, Molecular Adaptation, Robustness, Stochastic Processes.

https://doi.org/10.1016/j.chempr.2022.03.016 Enzymatic exchange of mixes of dipeptides leads to the buildup of tetrapeptides that can be tracked. Self-organization drives selective peptide sequence buildup

In this intriguing episode, we welcome Dr. Gäbelein, a scientist at the forefront of cell biology, as he introduces us to a revolutionary approach for manipulating organelle structures within single live cells. This technique, based on FluidFM, involves atomic force microscopy, optical microscopy, and nanofluidics to achieve precision in force and volume control and provides real-time examination capabilities.

Dr. Gäbelein walks us through the process of developing this innovative technology, highlighting the role of specially designed probes that facilitate minimal invasive entry into cells. He further elaborates on how optimizing fluid flow allows for the extraction of specific organelles.

Dr. Gäbelein shares fascinating findings from his study, particularly the transformation of mitochondria into a pearls-on-a-string phenotype when single or a specific number of mitochondria are extracted. He also explains how this process is calcium independent, leading to isolated, intact mitochondria.

Dr. Gäbelein sheds light on the successful transplantation of mitochondria into host cells, and how these fuse into the host cells' mitochondrial network. He shares intriguing results from a study involving the transplantation of healthy and drug-impaired mitochondria into primary keratinocytes and the monitoring of mitochondrial subpopulation rescue.

In conclusion, Dr. Gäbelein underscores the immense potential this approach holds for the study of organelle physiology and homeostasis, mechanobiology, synthetic biology, and therapeutic applications. This episode is a must-listen for anyone interested in cell biology and the future of biomedical research.

Keywords: Organelle Transplantation, Mitochondria, FluidFM, Atomic Force Microscopy, Nanofluidics, Cell Biology, Mechanobiology, Synthetic Biology.

doi:10.1371/journal.pbio.3001576

In this episode, we're thrilled to host Dr. Boolani, who delves into the intriguing scientific connections between our moods and our gut microbiome. The discussion kicks off with an exploration into how traits like energy and fatigue could be unique unipolar moods with their own mental and physical components. This sets the stage for a revealing exploration of Dr. Boolani's recent study that sought to uncover the correlations between these moods and the gut microbiome.

Twenty physically active, non-obese subjects participated in the study, and the results were astonishing. The analysis revealed how different bacterial communities, primarily Bacteroidetes and Firmicutes, correlated with the energy and fatigue traits. The bacterium Anaerostipes, for instance, was found to positively correlate with mental energy and negatively with both mental and physical fatigue.

Moreover, Dr. Boolani discusses the role of diet, particularly processed meat, and its significant correlation with the four moods. One particular genus from the Firmicutes family, Holdemania, was found to be correlated with the intake of processed meat.

Although distinct metabolic profiles were observed, no significant correlation was found between them and the energy and fatigue traits. These exploratory findings suggest that our energy and fatigue traits could be defined by distinct bacterial communities in our gut, independent of our diet.

Join us as Dr. Boolani enlightens us on these groundbreaking findings and what they could mean for our understanding of energy, fatigue, and the fascinating world of the gut microbiome. He also emphasizes the need for more comprehensive studies to affirm these insights and their potential implications for health and wellbeing. This is an episode you won't want to miss!

https://dx.doi.org/10.3390%2Fnu14030466 Trait Energy and Fatigue May Be Connected to Gut Bacteria among Young Physically Active Adults: An Exploratory Study

Join us in this enlightening episode with Dr. Bolton, who explores the fascinating relationships between early-life adversity (ELA), the maturation of stress-related brain circuits, and subsequent mental health vulnerabilities. Her recent study delves into the profound ways ELA influences brain development, specifically impacting the hypothalamic corticotropin-releasing hormone (CRH) neurons.

Dr. Bolton reveals that ELA increases functional excitatory synapses onto these stress-sensitive neurons, disrupting the typical developmental synapse pruning process performed by adjacent microglia. The disrupted activity of these microglia is connected to diminished signaling of the microglial phagocytic receptor MerTK in mice exposed to ELA.

This intricate neural dance doesn't stop there. Dr. Bolton delves deeper, sharing how selective chronic chemogenetic activation of ELA microglia can help increase microglial process dynamics and reduce excitatory synapse density to control levels. Notably, such selective activation during early life can normalize adult acute and chronic stress responses, hormonal stress-induced secretion, and even behavioral threat responses.

As we navigate through this complex world of early-life stress and its long-term impact on stress regulation and mental health, Dr. Bolton's insights shed valuable light. The episode underscores the critical role of microglial actions during development and how they shape our stress-response system, adding a fresh perspective to the discussion of mental illnesses arising from early-life stress.

Intrigued about the power of early-life events on your brain and mental health? Tune into this episode and uncover the fascinating mechanisms of stress regulation with Dr. Bolton!

https://doi.org/10.1016/j.celrep.2022.110600

In this insightful episode, we're delighted to welcome Dr. Felici, an innovator pushing the boundaries of sustainable energy production through nuclear fusion. Dr. Felici introduces us to the complex world of magnetic confinement in tokamak configurations, highlighting the promise and challenges this path toward sustainable energy presents.

One of the core challenges in this field is shaping and maintaining high-temperature plasma within the tokamak vessel. Dr. Felici discusses the necessity of high-dimensional, high-frequency, closed-loop control using magnetic actuator coils and the complications posed by diverse requirements across a wide range of plasma configurations.

Delving into his groundbreaking work, Dr. Felici introduces an autonomous learning architecture for tokamak magnetic controller design. This approach elegantly meets control objectives specified at a high level while satisfying physical and operational constraints, offering unparalleled flexibility and generality in problem specification. What's even more exciting is how this approach dramatically reduces the design effort required to produce new plasma configurations.

Dr. Felici takes us on a journey of how this new approach was applied to produce and control a diverse set of plasma configurations on the Tokamak à Configuration Variable (TCV). The approach enabled the creation of advanced configurations, including elongated, conventional shapes, as well as negative triangularity and 'snowflake' configurations. The episode also delves into how the team demonstrated sustained 'droplets' on TCV, where two separate plasmas are maintained simultaneously within the vessel.

By showcasing the potential of reinforcement learning in accelerating research in the fusion domain, this conversation with Dr. Felici sheds light on the most challenging real-world systems where reinforcement learning has been successfully applied. If you're interested in sustainable energy, advanced learning systems, or the intersection of the two, this is an episode you won't want to miss!

https://doi.org/10.1038/s41586-021-04301-9

Join us for this summary episode, where we dive into the highlights from our recent guest speaker series. Each week, we hosted exceptional thought leaders and researchers from diverse fields, who shared their pioneering research, intriguing discoveries, and insightful perspectives.

Our lineup featured some of the greatest minds in fields spanning from neuroscience and genomics to environmental science and artificial intelligence. These discussions touched on everything from the intricacies of brain development and the mysteries of the human genome to groundbreaking solutions for environmental challenges and innovative advancements in AI technology.

In this episode, we'll revisit the key takeaways from each speaker, reflect on the questions posed by our audience, and look at how these discussions contribute to our understanding of these complex topics. We will also provide a sneak peek into our upcoming lineup of guest speakers.

This is a fantastic opportunity to catch up on any discussions you may have missed, refresh your memory on those you attended, and gain an overview of the diverse topics we've explored so far in our series. Don't miss out on this comprehensive review of our enriching conversations with these trailblazing guests!

Keywords: guest speaker series, neuroscience, genomics, environmental science, artificial intelligence, recap, summary, research, discovery, advancements.

In this episode, we are joined by Dr. Soshany, a researcher delving into the realm of time travel and its potential paradoxes. If time travel were possible, it would seemingly lead to perplexing paradoxes, including the famous grandfather paradox and bootstrap paradoxes where creation appears to come from nothing.

Dr. Soshany introduces us to his groundbreaking mathematical model for a spacetime with a time machine. He explains two intriguing multiple-histories models, which propose solutions to time travel paradoxes by allowing for multiple timelines or histories. Any changes to the past, under these models, would occur in a new history, separate from the one from which the time traveler originated.

In this enlightening discussion, Dr. Soshany constructs novel and concrete examples of multiple-histories resolutions to time travel paradoxes. He delves into intriguing questions such as the possibility of returning to a previously visited history and whether a finite or infinite number of histories would be necessary.

Surprisingly, under certain conditions, Dr. Soshany reveals that these histories could be finite and cyclic, thereby extending the Novikov self-consistency conjecture to multiple histories and demonstrating hybrid behavior combining the two.

Towards the end of the episode, Dr. Soshany discusses how observers might experimentally differentiate between multiple histories and the Hawking and Novikov conjectures. Tune in for a riveting journey into the world of theoretical physics and time travel.

Keywords: Time Travel, Paradoxes, Multiple Histories, Spacetime, Grandfather Paradox, Bootstrap Paradoxes, Novikov Self-Consistency Conjecture, Theoretical Physics.

https://doi.org/10.48550/arXiv.1907.04178 Lectures on Faster-than-Light Travel and Time Travel

In this compelling episode, we sit down with Dr. Singh to discuss the future of sustainable energy via an artificial photosynthetic (AP) system. Dr. Singh guides us through the fascinating concept of artificial photosynthesis, highlighting the challenges and opportunities of capturing CO2 directly from dilute sources such as flue gas and air to produce fuels and chemicals.

Delving into the core of his research, Dr. Singh introduces us to the design and evaluation of an integrated AP system that harnesses sunlight to convert captured CO2 into fuels. His work explores the solar-to-fuel (STF) efficiency of such a system, revealing promising thermodynamic limits ranging from 34% to 40% for a variety of products.

The conversation deepens as Dr. Singh describes two different integration schemes—integrated cascade systems and fully integrated systems. We learn how fully integrated systems can be significantly more efficient, as they bypass the need for additional energy for compression, separation, and recycling of CO2. These insights shed light on the synthesis of higher-electron products, their role in maintaining the robust operation of an integrated AP system, and their compatibility with different carbon capture processes.

Lastly, Dr. Singh proposes a design for a fully integrated AP system that uses a moisture gradient across an anion-exchange membrane to capture CO2 from the air, convert it directly to fuels using water and sunlight, and simultaneously reduce the CO2 level of the surrounding air.

This episode with Dr. Singh is a must-listen for anyone interested in sustainable energy solutions. His research offers an intriguing glimpse into the future where artificial photosynthesis systems could potentially outperform natural leaves by 14 times in efficiency, representing a quantum leap forward in our quest for sustainability.

https://doi.org/10.1021/acssuschemeng.8b04969 Assessment of Artificial Photosynthetic Systems for Integrated Carbon Capture and Conversion