BINA

Analysis of dynamic differential speckle patterns, scattered from human tissues illuminated by a laser beam, has been found by many researchers to be applicable for noncontact sensing of various biomedical parameters. The COVID-19 global pandemic brought the need for massive rapid-remote detection of a fever in closed public spaces. The existing non-contact temperature measurement methods have a significant tradeoff between the measurement distance and accuracy. This paper aims to prove the feasibility of an accurate temperature measurement system based on speckle patterns analysis, enabling the sensing of human temperature from an extended distance greater than allowed by the existing methods. In this study, we used speckle patterns analysis combined with artificial intelligence (AI) methods for human temperature extraction, starting with fever/no fever binary classification and continuing with …

Since the times of Holtsmark (1911), statistics of fields in random environments have been widely studied, for example in astrophysics, active matter, and line-shape broadening. The power-law decay of the two-body interaction, of the form , and assuming spatial uniformity of the medium particles exerting the forces, imply that the fields are fat-tailed distributed, and in general are described by stable L\'evy distributions. With this widely used framework, the variance of the field diverges, which is non-physical, due to finite size cutoffs. We find a complementary statistical law to the L\'evy-Holtsmark distribution describing the large fields in the problem, which is related to the finite size of the tracer particle. We discover bi-scaling, with a sharp statistical transition of the force moments taking place when the order of the moment is , where is the dimension. The high-order moments, including the variance, are described by the framework presented in this paper, which is expected to hold for many systems. The new scaling solution found here is non-normalized similar to infinite invariant densities found in dynamical systems.

Background Progress has been achieved with the introduction of biologics for the management of inflammatory/autoimmune diseases such as rheumatoid arthritis (RA), however such medications induce immune suppression, which is nonselective to the pathogenesis of the disease, resulting in higher rates of infections. Therefore, there are unmet medical needs in the treatment of such diseases, which should be addressed by novel approaches. Accumulating evidence suggests that extracellular vesicles (EVs) play a role in the establishment, maintenance and modulation of autoimmune processes.Objectives In the current study, we hypothesized that isolation of circulating autologous tissue-specific homing EVs from RA patients - may improve the delivery of current FDA-approved anti-inflammatory drugs, which will be encapsulated into these EVs. The drug-loaded EVs will be injected back to the diseased subjects …

We present our current understanding of various aspects of Efimov physics originating from the complex multichannel hyperfine structure which further help us to understand puzzling 7Li experimental observations. Our results indicates that spin-exchange for 7Li atoms play an important role in the determination of Efimov resonances along with the narrow character of its Feshbach resonances. We show that the structure of three-body potentials is strongly dependent on the resonance width giving further insights to other atomic species.

Interferometers are highly sensitive to phase differences and are utilized in numerous schemes. Of special interest is the quantum SU (1, 1) interferometer which is able to improve the sensitivity of classical interferometers. We theoretically develop and experimentally demonstrate a temporal SU (1, 1) interferometer based on two time lenses in a 4 f configuration. This temporal SU (1, 1) interferometer has a high temporal resolution, imposes interference on both time and spectral domains, and is sensitive to the phase derivative which is important for detecting ultrafast phase changes. Therefore, this interferometer can be utilized for temporal mode encoding, imaging, and studying the ultrafast temporal structure of quantum light.

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.

Maxwell's fisheye is a paradigm for an absolute optical instrument with a refractive index deduced from the stereographic projection of a sphere on a plane. We investigate experimentally the dynamics of flexural waves in a thin plate with a thickness varying according to the Maxwell fisheye index profile and a clamped boundary. We demonstrate subwavelength focusing and temporal pulse compression at the image point. This is achieved by introducing a sink emitting a cancelling signal optimally shaped using a time-reversal procedure. Perfect absorption and outward going wave cancellation at the focus point are demonstrated. The time evolution of the kinetic energy stored inside the cavity reveals that the sink absorbs energy out of the plate ten times faster than the natural decay rate.

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.

Clean water is essential for maintaining human health. To ensure clean water, it is important to use sensitive detection methods that can identify contaminants in real time. Most techniques do not rely on optical properties and require calibrating the system for each level of contamination. Therefore, we suggest a new technique to measure water contamination using the full scattering profile, which is the angular intensity distribution. From this, we extracted the iso-pathlength (IPL) point which minimizes the effects of scattering. The IPL point is an angle where the intensity values remain constant for different scattering coefficients while the absorption coefficient is set. The absorption coefficient does not affect the IPL point but only attenuates its intensity. In this paper, we show the appearance of the IPL in single scattering regimes for small concentrations of Intralipid. We extracted a unique point for each sample diameter …

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.

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 …

Clean water is essential for maintaining human health. To ensure clean water, it is important to use sensitive detection methods that can identify contaminants in real time. Most techniques do not rely on optical properties and require calibrating the system for each level of contamination. Therefore, we suggest a new technique to measure water contamination using the full scattering profile, which is the angular intensity distribution. From this, we extracted the iso-pathlength (IPL) point which minimizes the effects of scattering. The IPL point is an angle where the intensity values remain constant for different scattering coefficients while the absorption coefficient is set. The absorption coefficient does not affect the IPL point but only attenuates its intensity. In this paper, we show the appearance of the IPL in single scattering regimes for small concentrations of Intralipid. We extracted a unique point for each sample diameter …

Extending polymer chains results in a positive chain tension, fch, primarily due to conformational restrictions. At the level of individual bonds, however, tension, fb, is either negative or positive and depends on both chain tension and bulk pressure. Typically, the chain and bond tension are assumed to be directly related. In specific systems, however, this dependence may not be intuitive, whereby fch increases while fb decreases; i.e., the entire chain is extended while bonds are compressed. Specifically, increasing the grafting density of a polymer brush results in chain extension along the direction perpendicular to the grafting surface while the underlying bonds are compressed. Similarly, upon compression of polymer networks, the extension of chains oriented in the “free” direction increases while their bonds are getting more compressed. We demonstrate this phenomenon in molecular dynamics simulations and …

Interferometers are highly sensitive to phase differences and are utilized in numerous schemes. Of special interest is the quantum SU (1, 1) interferometer which is able to improve the sensitivity of classical interferometers. We theoretically develop and experimentally demonstrate a temporal SU (1, 1) interferometer based on two time lenses in a 4 f configuration. This temporal SU (1, 1) interferometer has a high temporal resolution, imposes interference on both time and spectral domains, and is sensitive to the phase derivative which is important for detecting ultrafast phase changes. Therefore, this interferometer can be utilized for temporal mode encoding, imaging, and studying the ultrafast temporal structure of quantum light.

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 …

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 …

Analysis of an individual's immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but …

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.

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 …

X-ray based imaging modalities are widely used in research, industry, and in the medical field. Consequently, there is a strong motivation to improve their performances with respect to resolution, dose, and contrast. Ghost imaging (GI) is an imaging technique in which the images are reconstructed from measurements with a single-pixel detector using correlation between the detected intensities and the intensity structures of the input beam. The method that has been recently extended to X-rays provides intriguing possibilities to overcome several fundamental challenges of X-ray imaging. However, understanding the potential of the method and designing X-ray GI systems pose challenges since in addition to geometric optic effects, radiation-matter interactions must be considered. Such considerations are fundamentally more complex than those at longer wavelengths as relativistic effects such as Compton scattering become significant. In this work we present a new method for designing and implementing GI systems using the particle transport code FLUKA, that rely on Monte Carlo (MC) sampling. This new approach enables comprehensive consideration of the radiation-matter interactions, facilitating successful planning of complex GI systems. As an example of an advanced imaging system, we simulate a high-resolution scattered photons GI technique.