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CRISPR (clustered regularly interspaced short palindromic repeat)- based diagnostics are at the forefront of rapid detection platforms of infectious diseases. The integration of reverse transcription-loop-mediated isothermal amplification (RT-LAMP) with CRISPR-Cas protein systems has led to the creation of advanced one-pot assays. The sensitivity of these assays has been bolstered by the utilization of a thermophilic Cas12 protein, BrCas12b, and its engineered variant, which exhibits enhanced thermal stability and allows for broader operation temperatures of the assay. Here, we perform all-atom molecular dynamics (MD) simulations on wild-type and mutant BrCas12b to reveal the mechanism of stabilization conferred by the mutation. High-temperature simulations reveal a small structural change along with greater flexibility in the PAM-interacting domain of the mutant BrCas12b, with marginal structural and flexibility changes in the other mutated domains. Comparative essential dynamics analysis between the wild-type and mutant BrCas12b at both ambient and elevated temperatures provides insights into the stabilizing effects of the mutations. Our findings not only offer a comprehensive insight into the dynamic alterations induced by mutations but reveal important motions in BrCas12b, important for the rational design of diagnostic and therapeutic platforms of Cas12 proteins.

Forensic sketch-to-mugshot matching is a challenging task in face recognition, primarily hindered by the scarcity of annotated forensic sketches and the modality gap between sketches and photographs. To address this, we propose CLIP4Sketch, a novel approach that leverages diffusion models to generate a large and diverse set of sketch images, which helps in enhancing the performance of face recognition systems in sketch-to-mugshot matching. Our method utilizes Denoising Diffusion Probabilistic Models (DDPMs) to generate sketches with explicit control over identity and style. We combine CLIP and Adaface embeddings of a reference mugshot, along with textual descriptions of style, as the conditions to the diffusion model. We demonstrate the efficacy of our approach by generating a comprehensive dataset of sketches corresponding to mugshots and training a face recognition model on our synthetic data. Our results show significant improvements in sketch-to-mugshot matching accuracy over training on an existing, limited amount of real face sketch data, validating the potential of diffusion models in enhancing the performance of face recognition systems across modalities. We also compare our dataset with datasets generated using GAN-based methods to show its superiority.

As a signature of competing correlations, stripes occur in a variety of strongly correlated systems, such as high temperature superconductors (SCs) and quantum Hall effect. We study a double layer SC in the presence of a parallel magnetic field $B$ within the Bogoliubov-de Gennes framework. We find that for low $B$ the system remains in the ``Bardeen-Cooper-Schrieffer (BCS) phase" with a spatially uniform gap, but with increasing $B$, a transition occurs into a phase which contains stripes of the BCS phase separated by regions where the interlayer phase difference rotates by $2\pi$ due to the presence of inter-layer vortices. This stripe phase is predicted to manifest through oscillations in the amplitude of the SC gap and an alternating pattern of supercurrents. We will comment on the relation to previous works based on the Landau-Ginzburg formalism as well as on the possible experimental realization and signature of this phase., Comment: 6 pages, 2 figures

The quasiparticles (QPs) or quasiholes (QHs) of fractional quantum Hall states have been predicted to obey fractional braid statistics, which refers to the Berry phase (in addition to the usual Aharonov-Bohm phase) associated with an exchange of two QPs or two QHs, or equivalently, to half of the phase associated with a QP/QH going around another. Certain phase slips in interference experiments in the fractional quantum Hall regime have been attributed to fractional braid statistics, where the interference probes the Berry phase associated with a closed path which has segments along the edges of the sample as well as through the bulk (where tunneling occurs). Noting that QPs / QHs with sharply quantized fractional charge and fractional statistics do not exist at the edge of a fractional quantum Hall state due to the absence of a gap there, we provide arguments that the existence of composite fermions at the edge is sufficient for understanding the primary experimental observations; composite fermions are known to occur in compressible states without a gap. We further propose that transport through a closed $\textit{tunneling}$ loop contained entirely in the bulk can, in principle, allow measurement of the braid statistics in a way that the braiding object explicitly has a fractionally quantized charge over the entire loop. Optimal parameters for this experimental geometry are determined from quantitative calculations., Comment: Revised manuscript

Following O'Meara's result [Journal of Algebra and Its Applications Vol~\textbf{13}, No. 8 (2014)], it follows that the block matrix $A=\begin{pmatrix} B & 0 0 & 0 \end{pmatrix} \in M_{n+r}(R)$, $B\in M_n(R)$, $r\ge 1$, over a von Neumann regular separative ring $R$, is a product of idempotent matrices. Furthermore, this decomposition into idempotents of $A$ also holds when $B$ is an invertible matrix and $R$ is a GE ring (defined by Cohn [New mathematical monographs: {\bf 3}, Cambridge University Press (2006)]). As a consequence, it follows that if there exists an example of a von Neumann regular ring $R$ over which the matrix $ A=\begin{pmatrix} B & 0 0 & 0 \end{pmatrix} \in M_{n+r}(R) $ where $B\in M_n(R)$, $r\ge 1$ , cannot be expressed as a product of idempotents, then $R$ is not separative, thus providing an answer to an open question whether there exists a von Neumann regular ring which is not separative. The paper concludes with an example of an open question whether every totally nonnegative matrix is a product of nonnegative idempotent matrices., Comment: 8 pages

In this work, we demonstrate that the modulation of carrier density can alter the superconducting transition temperature by up to $204$ mK in epitaxial Indium Nitride on Gallium Nitride, accounting for the $10$% of the transition temperature in ungated conditions. Our samples are likely free from strong localization effects and significant granularity, as indicated by $( k_{f l} \gg 1 )$, suggesting that the primary determinant of the transition temperature in InN is carrier density, rather than disorder scattering. The observed behavior is consistent with BCS s-wave superconductivity, corroborated by the superconducting parameters we measured. Furthermore, we observed a $60$% bipolar suppression of the supercurrent in our experiments., Comment: 6 pages, 5 figures, supplementary material attached. Comments are welcome

A fundamental manifestation of the nontrivial correlations of an incompressible fractional quantum Hall (FQH) state is that an electron added to it disintegrates into more elementary particles, namely fractionally-charged composite fermions (CFs). We show here that the Girvin-MacDonald-Platzman (GMP) density-wave excitation of the $\nu{=}n/(2pn{\pm }1)$ FQH states also splits into more elementary single CF excitons. In particular, the GMP graviton, which refers to the recently observed spin-2 neutral excitation in the vanishing wave vector limit [Liang et al., Nature 628, 78 (2024)], remains undivided for $\nu{=}n/(2n{\pm} 1)$ but splits into two gravitons at $\nu{=}n/(4n{\pm} 1)$ with $n{>}1$. A detailed experimental confirmation of the many observable consequences of the splitting of the GMP mode should provide a unique window into the correlations underlying the FQH effect., Comment: 9 pages, 4 figures, includes supplemental material

The scarcity of large-scale palmprint databases poses a significant bottleneck to advancements in contactless palmprint recognition. To address this, researchers have turned to synthetic data generation. While Generative Adversarial Networks (GANs) have been widely used, they suffer from instability and mode collapse. Recently, diffusion probabilistic models have emerged as a promising alternative, offering stable training and better distribution coverage. This paper introduces a novel palmprint generation method using diffusion probabilistic models, develops an end-to-end framework for synthesizing multiple palm identities, and validates the realism and utility of the generated palmprints. Experimental results demonstrate the effectiveness of our approach in generating palmprint images which enhance contactless palmprint recognition performance across several test databases utilizing challenging cross-database and time-separated evaluation protocols.

India is one of the worst affected countries in the world in terms of fatalities and economic damage due to natural disasters, particularly floods. For planning flood mitigating and relief measures, granular historical information on a pan-India basis is required, which has been missing. Through recent efforts, a few national scale datasets have been created, but they lack the requisite information on fatalities and damages, which has limited the ability to develop a flood severity index. This paper describes the development of the India Flood Inventory with Impacts (IFI-Impacts) database, which contains death and damage statistics, and combines population and historically flooded area information sourced from a national hydrologic-hydrodynamic modeling system. We also propose a novel District Flood Severity Index (DFSI), which accounts for the historical severity of floods in India based on the number of people they have affected and the spread and duration of such floods. Districts being the administrative units of the government, this novel index fulfills a major need and gap in currently available flood management tools. The dataset as well as the index is expected to significantly advance disaster preparedness towards floods in the country. DFSI can be improved further by collecting and incorporating additional variables, e.g., economic losses and by improving the reliability/robustness of the data of other variables. Based on DFSI, actions need to be addressed to mitigate flood damages, beginning with the districts with the high DFSI values.

The utilization of synthetic data for fingerprint recognition has garnered increased attention due to its potential to alleviate privacy concerns surrounding sensitive biometric data. However, current methods for generating fingerprints have limitations in creating impressions of the same finger with useful intra-class variations. To tackle this challenge, we present GenPrint, a framework to produce fingerprint images of various types while maintaining identity and offering humanly understandable control over different appearance factors such as fingerprint class, acquisition type, sensor device, and quality level. Unlike previous fingerprint generation approaches, GenPrint is not confined to replicating style characteristics from the training dataset alone: it enables the generation of novel styles from unseen devices without requiring additional fine-tuning. To accomplish these objectives, we developed GenPrint using latent diffusion models with multimodal conditions (text and image) for consistent generation of style and identity. Our experiments leverage a variety of publicly available datasets for training and evaluation. Results demonstrate the benefits of GenPrint in terms of identity preservation, explainable control, and universality of generated images. Importantly, the GenPrint-generated images yield comparable or even superior accuracy to models trained solely on real data and further enhances performance when augmenting the diversity of existing real fingerprint datasets.

A system in equilibrium keeps ``exploring" nearby states in the phase space and consequently, fluctuations can contain information, that the mean value does not. However, such measurements involve a fairly complex interplay of effects arising in the device and measurement electronics, that are non-trivial to disentangle. In this paper, we briefly analyse some of these issues and show the relevance of a two-amplifier cross-correlation technique for semiconductors and thin films commonly encountered. We show that by using home-built amplifiers costing less than $10$ USD/piece one can measure spectral densities as low as $\sim 10^{-18}-10^{-19}~ {\rm {V^2}{Hz^{-1}}}$. We apply this method to an ionic liquid gated Ga:ZnO channel and show that the glass transition of the ionic liquid brings about a change in the exponent of the low frequency resistance fluctuations. Our analysis suggests that a log-normal distribution of the Debye relaxation times of the fluctuations and an increased weight of the long timescale relaxations can give a semi-quantitative explanation of the observed change in the exponent., Comment: 6 pages, 5 figures, supplementary material attached. Comments are welcome

Context - Around the year 2000, Triton's south pole experienced an extreme summer solstice that occurs every about 650 years, when the subsolar latitude reached about 50{\deg}. Bracketing this epoch, a few occultations probed Triton's atmosphere in 1989, 1995, 1997, 2008 and 2017. A recent ground-based stellar occultation observed on 6 October 2022 provides a new measurement of Triton's atmospheric pressure which is presented here. Aims- The goal is to constrain the Volatile Transport Models (VTMs) of Triton's atmosphere that is basically in vapor pressure equilibrium with the nitrogen ice at its surface. Methods - Fits to the occultation light curves yield Triton's atmospheric pressure at the reference radius 1400 km, from which the surface pressure is induced. Results - The fits provide a pressure p_1400= 1.211 +/- 0.039 microbar at radius 1400 km (47 km altitude), from which a surface pressure of p_surf= 14.54 +/- 0.47 microbar is induced (1-sigma error bars). To within error bars, this is identical to the pressure derived from the previous occultation of 5 October 2017, p_1400 = 1.18 +/- 0.03 microbar and p_surf= 14.1 +/- 0.4 microbar, respectively. Based on recent models of Triton's volatile cycles, the overall evolution over the last 30 years of the surface pressure is consistent with N2 condensation taking place in the northern hemisphere. However, models typically predict a steady decrease in surface pressure for the period 2005-2060, which is not confirmed by this observation. Complex surface-atmosphere interactions, such as ice albedo runaway and formation of local N2 frosts in the equatorial regions of Triton could explain the relatively constant pressure between 2017 and 2022., Comment: 8 pages, 4 figures, accepted for publication in Astronomy and Astrophysics

The parton theory constructs candidate fractional quantum Hall states by decomposing the physical particles into unphysical partons, placing the partons in integer quantum Hall states, and then gluing the partons back into the physical particles. Field theoretical formulations execute the gluing process through the device of emergent gauge fields. Here we study numerically the process of going from the integer quantum Hall effect of two species of fermionic partons to the fractional quantum Hall effect of bosons by introducing an attractive interaction between the fermions of different species and continuously increasing its strength to glue them into bosons. To properly capture the physics in the bulk, we implement this process in a lattice version of the spherical geometry, which allows us to keep the full Hilbert space. Even though the two end-point states are topologically distinct, we find that, for the small system sizes accessible to our study, the energy gap remains open, indicating a crossover between these two states., Comment: 11 pages, 8 figures

The fractional quantum Hall states are non-Fermi liquids of electrons, in that their ground states and low energy excitations are described not in terms of electrons but in terms of composite fermions which are bound states of electrons and $2p$ quantized vortices. An electron or a hole at filling factor $\nu=n/(2pn+1)$, where $p,n$ are integers, is a complex molecule of $2pn+ 1$ quasiparticles (excited composite fermions) or quasiholes (missing composite fermions) and has its own internal excitations. Recent scanning tunneling microscopy experiments have succeeded in measuring the electron spectral functions of these states, which provides valuable information on the nature of these strongly correlated molecules and thereby on the short-distance correlations in the fractional quantum Hall liquids. These experiments exhibit several sharp peaks in the tunneling spectra. Detailed calculations based on the composite-fermion theory demonstrate multiple peaks in the local density of states, and we argue that the separation between the peaks represents interaction-corrected composite-fermion cyclotron energy. We discuss what aspects of experiments are explained by our model and which ones remain to be explained.

Evaluating the risk level of adversarial images is essential for safely deploying face authentication models in the real world. Popular approaches for physical-world attacks, such as print or replay attacks, suffer from some limitations, like including physical and geometrical artifacts. Recently, adversarial attacks have gained attraction, which try to digitally deceive the learning strategy of a recognition system using slight modifications to the captured image. While most previous research assumes that the adversarial image could be digitally fed into the authentication systems, this is not always the case for systems deployed in the real world. This paper demonstrates the vulnerability of face authentication systems to adversarial images in physical world scenarios. We propose AdvGen, an automated Generative Adversarial Network, to simulate print and replay attacks and generate adversarial images that can fool state-of-the-art PADs in a physical domain attack setting. Using this attack strategy, the attack success rate goes up to 82.01%. We test AdvGen extensively on four datasets and ten state-of-the-art PADs. We also demonstrate the effectiveness of our attack by conducting experiments in a realistic, physical environment., Comment: 10 pages, 9 figures, Accepted to the International Joint Conference on Biometrics (IJCB 2023)

The Halperin-Lee-Read Fermi sea of composite fermions (CFs) at half-filled lowest Landau level is the realization of a fascinating non-Fermi liquid metallic phase. Remarkably, experiments have found that as the width of the quantum well is increased, this state makes a transition into a fractional quantum Hall (FQH) state, the origin of which has remained an important puzzle since its discovery more than three decades ago. We perform detailed and accurate quantitative calculations using a systematic variational framework for the pairing of CFs that closely mimics the BCS theory of superconductivity. We find: (i) as the quantum-well width is increased, the single-component CF Fermi sea occupying the lowest symmetric subband of the quantum well undergoes an instability into a single-component p-wave paired state of CFs; (ii) the theoretical phase diagram in the quantum-well width - electron density plane is in excellent agreement with experiments; (iii) a sufficient amount of asymmetry in the charge distribution of the quantum well destroys the FQH effect, as observed experimentally; and (iv) the two-component 331 state is energetically less favorable than the single component paired state. Evidence for FQH effect has been seen in wide quantum wells also at quarter-filled lowest Landau level; here our calculations indicate an f-wave paired state of CFs. We further investigate bosons in the lowest Landau level at filling factor equal to one and show that a p-wave pairing instability of CFs, which are bosons carrying a single flux quantum, in agreement with exact diagonalization studies. The general consistency of the composite-fermion BCS approach with experiments lends support to the notion of CF pairing as the mechanism of FQH effects at even-denominator filling factors. Various experimental implications are mentioned., Comment: 25 pages, 10 figures

Lee, Kim, and coworkers have recently claimed room-temperature and ambient-pressure superconductivity in a copper-doped lead apatite material named LK-99. However, the polycrystalline material synthesized has a significant fraction of copper(I) sulfide. Copper(I) sulfide has a known phase transition at 104 degrees C from an ordered low-temperature phase to a high-temperature superionic phase. As a result of this phase transition, copper(I) sulfide exhibits sharp transitions in electrical resistivity and heat capacity, which are expected to coincide with the temperature-induced transitions reported for LK-99. This implies that LK-99 must be synthesized without any copper(I) sulfide to allow unambiguous validation of the superconducting properties of LK-99., Comment: 6 pages, 3 figures

A comprehensive study of favoured and unfavoured $\alpha$-decay, cluster decay, weak-decay along with spontaneous fission in undetected superheavy nuclei within the range for proton number 111$\leq$Z$\leq$118 and neutron number 161$\leq$N$\leq$192 is performed. Half-lives for various mentioned decays are estimated with good accuracy on the basis of NUBASE2020 and are found in excellent match with the known half-lives. $\alpha$-decay mode is found most probable in this wide range and correspondingly potential $\alpha$-decay chains are reckoned. Peculiarly, the chances of cluster emission, as well as weak-decay, are also anticipated in this region of the periodic chart which open new pathways of detection of superheavy nuclei., Comment: 24 pages, 6 figures, 5 tables, Accepted in Physica Scripta

This document presents a preliminary approach to latent fingerprint enhancement, fundamentally designed around a mixed Unet architecture. It combines the capabilities of the Resnet-101 network and Unet encoder, aiming to form a potentially powerful composite. This combination, enhanced with attention mechanisms and forward skip connections, is intended to optimize the enhancement of ridge and minutiae features in fingerprints. One innovative element of this approach includes a novel Fingerprint Enhancement Gabor layer, specifically designed for GPU computations. This illustrates how modern computational resources might be harnessed to expedite enhancement. Given its potential functionality as either a CNN or Transformer layer, this Gabor layer could offer improved agility and processing speed to the system. However, it is important to note that this approach is still in the early stages of development and has not yet been fully validated through rigorous experiments. As such, it may require additional time and testing to establish its robustness and usability in the field of latent fingerprint enhancement. This includes improvements in processing speed, enhancement adaptability with distinct latent fingerprint types, and full validation in experimental approaches such as open-set (identification 1:N) and open-set validation, fingerprint quality evaluation, among others.