BINA

We study ergodic properties of one-dimensional Brownian motion with resetting. Using generic classes of statistics of times between resets, we find respectively for thin/fat tailed distributions, the normalized/non-normalised invariant density of this process. The former case corresponds to known results in the resetting literature and the latter to infinite ergodic theory. Two types of ergodic transitions are found in this system. The first is when the mean waiting time between resets diverges, when standard ergodic theory switches to infinite ergodic theory. The second is when the mean of the square root of time between resets diverges and the properties of the invariant density are drastically modified. We then find a fractional integral equation describing the density of particles. This finite time tool is particularly useful close to the ergodic transition where convergence to asymptotic limits is logarithmically slow. Our study implies rich ergodic behaviors for this non-equilibrium process which should hold far beyond the case of Brownian motion analyzed here.

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of …

The brain is likely the most complex organ, given the variety of functions it controls, the number of cells it comprises, and their corresponding diversity. Studying and identifying neurons, the brain's primary building blocks, is a crucial milestone and essential for understanding brain function in health and disease. Recent developments in machine learning have provided advanced abilities for classifying neurons. However, these methods remain black boxes with no explainability and reasoning. This paper aims to provide a robust and explainable deep-learning framework to classify neurons based on their electrophysiological activity. Our analysis is performed on data provided by the Allen Cell Types database containing a survey of biological features derived from single-cell recordings of mice and humans. First, we classify neuronal cell types of mice data to identify excitatory and inhibitory neurons. Then, neurons are categorized to their broad types in humans using domain adaptation from mice data. Lastly, neurons are classified into sub-types based on transgenic mouse lines using deep neural networks in an explainable fashion. We show state-of-the-art results in a dendrite-type classification of excitatory vs. inhibitory neurons and transgenic mouse lines classification. The model is also inherently interpretable, revealing the correlations between neuronal types and their electrophysiological properties.

The brain is likely the most complex organ, given the variety of functions it controls, the number of cells it comprises, and their corresponding connectivity and diversity. Identifying and studying neurons, the major building blocks of the brain, is a crucial milestone and is essential for understanding brain functionality in health and disease. Recent developments in machine learning have provided advanced abilities for classifying neurons, mainly according to their morphology. This paper aims to provide an explainable deep-learning framework to classify neurons based on their electrophysiological activity. Our analysis is performed on data provided by the Allen Cell Types database. The data contains a survey of biological features derived from single-cell recordings from mice. Neurons are classified into subtypes based on Cre mouse lines using an inherently interpretable locally sparse deep neural network model …

Despite having the ability to deliver 650 W h kg−1 in addition to the impressive rate capability, superior thermal stability, and facilitated electronic and ionic lithium conduction, LiNi0.5Mn1.5O4 (LNMO) is far from commercial applications. LNMO suffers from irreversible electrolytic degradation on its surface under high voltage operations leading to capacity fading and poor battery life. Therefore, this work aims to improve the stability and electrochemical behavior of LNMO by creating a Zn-enriched cathode layer interface via eccentric and facile diethyl zinc-assisted atomic surface reduction (Zn-ASR). In-depth surface characterization tools and computational calculations demonstrates a conformal 7-8 nm thin Zn-O and C-O enriched layer encapsulating the cathode particles resulting from Zn-ASR. The intensive comparative electrochemical and spectroscopic analysis, indicates superior electrochemical performance of …

We study ergodic properties of one-dimensional Brownian motion with resetting. Using generic classes of statistics of times between resets, we find respectively for thin/fat tailed distributions, the normalized/non-normalised invariant density of this process. The former case corresponds to known results in the resetting literature and the latter to infinite ergodic theory. Two types of ergodic transitions are found in this system. The first is when the mean waiting time between resets diverges, when standard ergodic theory switches to infinite ergodic theory. The second is when the mean of the square root of time between resets diverges and the properties of the invariant density are drastically modified. We then find a fractional integral equation describing the density of particles. This finite time tool is particularly useful close to the ergodic transition where convergence to asymptotic limits is logarithmically slow. Our study implies rich ergodic behaviors for this non-equilibrium process which should hold far beyond the case of Brownian motion analyzed here.

Hospital-acquired (nosocomial) infections account for the majority of adverse health effects during care delivery, placing an immense financial strain on healthcare systems around the world. For the first time, the present article provides evidence of a straightforward pollution-free technique to fabricate a heteroatom-doped carbon dot immobilized fluorescent biopolymer composite for the development of functional textiles with antioxidant and antimicrobial properties. A simple, facile, and eco-friendly approach was devised to prepare heteroatom-doped carbon dots from waste green tea and a biopolymer. The carbon dots showed an excitation-dependent emission behavior, and the XPS data unveiled that they are co-doped with nitrogen and sulfur. A facile physical compounding strategy was adopted to fabricate a carbon dot reinforced biopolymeric composite followed by immobilization onto the textile. The composite …

Dynamical evolution can be reconstructed within stationary, closed quantum systems by employing the Page-Wootters" timeless approach". When conditioning upon the state of a" clock" subsystem, the rest of the system regains its time dependence. This mechanism, involving entanglement between the above subsystems has gained much attention during the last few years. After a brief introduction to the topic we will elaborate on a few recent results: The derivation of new time-energy uncertainty relations, emergence of non-Hermitian dynamics when utilizing non-inertial quantum clocks and dynamical nonlocality in quantum time.

Purpose: Single nucleotide editing can be performed at the RNA level using the human deaminase acting on RNA (ADAR) enzyme and can serve as a tool for gene therapy of inherited diseases, including inherited retinal diseases (IRDs). ADAR-based RNA editing requires the delivery of an efficient guideRNA (gRNA) that is designed to recruit the endogenously expressed ADAR enzyme to a mutated RNA. Our aim is to design and test gRNAs that induce targeted ADAR editing for relatively common IRD-causing mutations including nonsense, missense, and splice-site mutations.Methods: A yeast model was used to identify candidate gRNAs for nonsense mutations by measuring yeast survival and percent editing using next generation sequencing (NGS). A fluorescence-expressing plasmid reporter system was used in HeLa cells overexpressing either ADAR1/2. The cells were transfected by a plasmid that includes …

The brain is likely the most complex organ, given the variety of functions it controls, the number of cells it comprises, and their corresponding connectivity and diversity. Identifying and studying neurons, the major building blocks of the brain, is a crucial milestone and is essential for understanding brain functionality in health and disease. Recent developments in machine learning have provided advanced abilities for classifying neurons, mainly according to their morphology. This paper aims to provide an explainable deep-learning framework to classify neurons based on their electrophysiological activity. Our analysis is performed on data provided by the Allen Cell Types database. The data contains a survey of biological features derived from single-cell recordings from mice. Neurons are classified into subtypes based on Cre mouse lines using an inherently interpretable locally sparse deep neural network model …

Despite having the ability to deliver 650 W h kg−1 in addition to the impressive rate capability, superior thermal stability, and facilitated electronic and ionic lithium conduction, LiNi0.5Mn1.5O4 (LNMO) is far from commercial applications. LNMO suffers from irreversible electrolytic degradation on its surface under high voltage operations leading to capacity fading and poor battery life. Therefore, this work aims to improve the stability and electrochemical behavior of LNMO by creating a Zn-enriched cathode layer interface via eccentric and facile diethyl zinc-assisted atomic surface reduction (Zn-ASR). In-depth surface characterization tools and computational calculations demonstrates a conformal 7-8 nm thin Zn-O and C-O enriched layer encapsulating the cathode particles resulting from Zn-ASR. The intensive comparative electrochemical and spectroscopic analysis, indicates superior electrochemical performance of …

Atopic dermatitis (AD) is associated with dysregulated type 1 IFN‒mediated responses, in parallel with the dominant type 2 inflammation. However, the pathophysiology of this dysregulation is largely unknown. Adenosine-to-inosine RNA editing plays a critical role in immune regulation by preventing double-stranded RNA recognition by MDA5 and IFN activation. We studied global adenosine-to-inosine editing in AD to elucidate the role played by altered editing in the pathophysiology of this disease. Analysis of three RNA-sequencing datasets of AD skin samples revealed reduced levels of adenosine-to-inosine RNA editing in AD. This reduction was seen globally throughout Alu repeats as well as in coding genes and in specific pre-mRNA loci expected to create long double-stranded RNA, the main substrate of MDA5 leading to type I IFN activation. Consistently, IFN signature genes were upregulated. In contrast …

Casimir forces, related to London-van der Waals forces, arise if the spectrum of electromagnetic fluctuations is restricted by boundaries. There is great interest both from fundamental science and technical applications to control these forces on the nano scale. Scientifically, the Casimir effect being the only known quantum vacuum effect manifesting between macroscopic objects, allows to investigate the poorly known physics of the vacuum. In this work, we experimentally investigate the influence of self-assembled molecular bio and organic thin films on the Casimir force between a plate and a sphere. We find that molecular thin films, despite being a mere few nanometers thick, reduce the Casimir force by up to 14%. To identify the molecular characteristics leading to this reduction, five different bio-molecular films with varying chemical and physical properties were investigated. Spectroscopic data reveal a broad absorption band whose presence can be attributed to the mixing of electronic states of the underlying gold layer and those of the molecular film due to charge rearrangement in the process of self-assembly. Using Lifshitz theory we calculate that the observed change in the Casimir force is consistent with the appearance of the new absorption band due to the formation of molecular layers. The desired Casimir force reduction can be tuned by stacking several monolayers, using a simple self-assembly technique in a solution. The molecules - each a few nanometers long - can penetrate small cavities and holes, and cover any surface with high efficiency. This process seems compatible with current methods in the production of micro …

The collective tunneling of a a Wigner necklace - a crystalline state of a small number of strongly interacting electrons confined to a suspended nanotube and subject to a double well potential - is theoretically analyzed and compared with experiments in [Shapir , Science , 870 (2019)]. Density Matrix Renormalization Group computations, exact diagonalization, and instanton theory provide a consistent description of this very strongly interacting system, and show good agreement with experiments. Experimentally extracted and theoretically computed tunneling amplitudes exhibit a scaling collapse. Collective quantum fluctuations renormalize the tunneling, and substantially enhance it as the number of electrons increases.

The electrochemical response of ethereal solutions containing magnesium organohaloaluminate complexes has drawn great interest in recent decades owing to their relevance to rechargeable magnesium batteries, as demonstrated with solutions containing complexes formed by reacting R2Mg and AlCl2R moieties in ethers like tetrahydrofuran (THF). However, most of previous reports focused on battery related performances, and less on the structure of the active species. Herein, we focus on (1) identifying electroactive species and (2) correlating the electrochemical properties of their solutions to the preparation modes: either through reactions of their precursors in THF, or by dissolving isolated crystallized products in the ether solvent. Specifically, we explore the products of the reaction of the Grignard reagent t-BuMgCl with AlCl3 (1:1) in THF, and how their presence in solutions affect their electrochemical …

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of …

Phase retardation is a cornerstone of modern optics, yet, at mid-infrared (mid-IR) frequencies, it remains a major challenge due to the scarcity of simultaneously transparent and birefringent crystals. Most materials resonantly absorb due to lattice vibrations occurring at mid-IR frequencies, and natural birefringence is weak, calling for hundreds of microns to millimeters-thick phase retarders for sufficient polarization rotation. We demonstrate mid-IR phase retardation with flakes of -molybdenum trioxide (-MoO) that are more than ten times thinner than the operational wavelength, achieving 90 degrees polarization rotation within one micrometer of material. We report conversion ratios above 50% in reflection and transmission mode, and wavelength tunability by several micrometers. Our results showcase that exfoliated flakes of low-dimensional crystals can serve as a platform for mid-IR miniaturized integrated polarization control.

X-ray Fluorescence Ghost Imaging (XRF-GI) was recently demonstrated for x-ray lab sources. It has the potential to reduce acquisition time and deposited dose by choosing their trade-off with spatial resolution, while alleviating the focusing constraints of the probing beam. Here, we demonstrate the realization of synchrotron-based XRF-GI: We present both an adapted experimental setup and its corresponding required computational technique to process the data. This not only extends the above-mentioned advantages to synchrotron XRF imaging, it also presents new possibilities for developing strategies to improve precision in nano-scale imaging measurements.

Chiral interactions play a crucial role in both chemistry and biology. Understanding the behavior of chiral molecules and their interactions with other molecules is essential, and chiral interactions in solutions are particularly important for studying chiral compounds. Chirality influences the physical and chemical properties of molecules, including solubility, reactivity, and biological activity. In this work, we used Isothermal Titration Calorimetry (ITC), a powerful technique for studying molecular interactions, including chiral interactions in solutions. We conducted a series of ITC measurements to investigate the heat of dilution and the heat of racemization of several amino acids (Asn, His, Ser, Ala, Met, and Phe). We also performed ITC measurements under different solute concentrations and temperatures to examine the effects of these parameters on chiral interactions, as well as the heat of dilution and racemization. The results of our measurements indicated that the heat of dilution, specifically the interactions between the solvent (water) and solute (chiral molecules), had a significant impact compared to the chiral interactions in the solution, which were found to be negligible. This suggests that the interactions between chiral molecules and the solvent play a more dominant role in determining the overall behavior and properties of the system. By studying chiral interactions in solutions, we can gain valuable insights into the behavior of chiral compounds, which can have implications in various fields, including drug design, chemical synthesis, and biological processes.