Miracle-dz/UniFAR-FTUs huggingface dataset:
Mueller-matrix imaging polarimetry elevated by wavelet decomposition and polarization-singular processing for analysis of specific cancerous tissue pathology

Abstract. Significance Mueller-matrix polarimetry is a powerful method allowing for the visualization of malformations in biological tissues and quantitative evaluation of alterations associated with the progression of various diseases. This approach, in fact, is limited in observation of spatial localization and scale-selective changes in the poly-crystalline compound of tissue samples. Aim We aimed to improve the Mueller-matrix polarimetry approach by implementing the wavelet decomposition accompanied with the polarization-singular processing for express differential diagnosis of local changes in the poly-crystalline structure of tissue samples with various pathology. Approach Mueller-matrix maps obtained experimentally in transmitted mode are processed utilizing a combination of a topological singular polarization approach and scale-selective wavelet analysis for quantitative assessment of the adenoma and carcinoma histological sections of the prostate tissues. Results A relationship between the characteristic values of the Mueller-matrix elements and singular states of linear and circular polarization is established within the framework of the phase anisotropy phenomenological model in terms of linear birefringence. A robust method for expedited (up to ∼15 min) polarimetric-based differential diagnosis of local variations in the poly-crystalline structure of tissue samples containing various pathology abnormalities is introduced. Conclusions The benign and malignant states of the prostate tissue are identified and assessed quantitatively with a superior accuracy provided by the developed Mueller-matrix polarimetry approach.
The Hybrid Multiscale Simulation Technology: An Introduction with Application to Space and Plasma Physics

From the Publisher: This book is a comprehensive description of hybrid plasma simulation models and will provide a very useful summary and guide to the vast literature on this topic. It addresses researchers and graduate students knowledgeable about computational science and numerical analysis, and can be used in courses on astrophysical and space plasmas. It is also meant for plasma installation designers. The coupled VlasovMaxwell equations with collisions describing well the physical system are far too heavy for numerical siumulations. Hybrid models treat some aspects kinetically and some as fluids. In the first part the author discusses hybrid codes, which include a wide spectrum of description for ions, positrons, dust grains, atoms and electrons. In the second part he treats the applications to basic plasma phenomena like particle acceleration and dissipation processes as well as to the global interaction of the solar wind with nonmagnetic planets, comets, and the local interstellar medium.
Average scattered field from a random PEC cylinder buried below a slightly rough surface

Scattering from a perfect electric conducting cylinder with random radius buried below a half space dielectric homogenous interface is studied. The cylindrical wave scattered by cylinder is expanded in terms of plane wave spectrum. Small perturbation method is used to study the interaction of each plane wave with the interface. The zeroth order term yields solution for a flat interface, whereas scattering from a rough surface is given by first-order term. Results are obtained for both TM and TE polarizations. Analytical expressions of the average scattered field are obtained and verified using numerical evaluation. Different scattering scenarios are simulated by varying the distribution of the radius. It is observed that average scattering cross section of an ensemble with normal/uniform distribution is almost equal to that of a cylinder with mean radius.
Mechanical properties of a dissimilar aluminum alloy joint welded by hybrid laser-MIG welding

Two dissimilar Al alloys, 5083-H111 and 6005A-T6, were joined by hybrid laser–MIG welding method. Mechanical properties of the welded joint were investigated and compared. The results show that the tensile strength of the dissimilar joint is 219.8 MPa, 11.7% higher than that of 6005A-T5 joint. After statistical analysis of the fatigue data, the P–S–N curves of the dissimilar joint were obtained. The mean fatigue strength at Nf = 107 of the dissimilar joint is 112.5 MPa. The fatigue strength at Nf = 107 of the dissimilar joint for a given 10% probability of failure, at a confidence level of 95%, is 101.4 MPa. The fatigue strength at Nf = 107 of the dissimilar joint is almost same as that of the 6005A-T6 joint. In welded structure designing, different P–S–N curves should be chosen according to the different service conditions and reliability requirements.
Labelling Hierarchy for Street Maps Using Centrality Measures

ABSTRACT This paper proposes a compound hierarchy to be used in cartographic labelling of streets. The main purposes of this hierarchy are to ease navigation of street maps and to provide more understandability and legibility of street features for map users. The hierarchy uses centrality measures along with functional classes of the streets to order features according to their spatial importance in each used zoom level. The calculation of a proper radius, to be employed in the calculations of centrality measures, is based on extracting proper field of view in the map user’s focus status. The used measures are integrated using fuzzy-analytic hierarchy process, yielding proper coefficients to create the hierarchy. The hierarchy is applied for the thinning process and later for using the styled layer descriptor to label street features. Quality constrains are implemented to make the street labels more understandable and readable.
Linear stochastic Schrödinger equations in terms of quantum Bernoulli noises

Quantum Bernoulli noises (QBN) are the family of annihilation and creation operators acting on Bernoulli functionals, which satisfy a canonical anti-commutation relation. In this paper, we study linear stochastic Schrodinger equations (LSSEs) associated with QBN in the space of square integrable complex-valued Bernoulli functionals. We first rigorously prove a formula concerning the number operator N on Bernoulli functionals. And then, by using this formula as well as Mora and Rebolledo’s results on a general LSSE [C. M. Mora and R. Rebolledo, Infinite. Dimens. Anal. Quantum Probab. Relat. Top. 10, 237–259 (2007)], we obtain an easily checking condition for a LSSE associated with QBN to have a unique Nr-strong solution of mean square norm conservation for given r≥0. Finally, as an application of this condition, we examine a special class of LSSEs associated with QBN and some further results are proven.
Orexin recruits non‐selective cationic conductance and endocannabinoid to dynamically modulate firing of caudal pontine reticular nuclear neurones

The neuropeptide orexin is involved in motor circuit function. However, its modulation on neuronal activities of motor structures, integrating orexin's diverse downstream molecular cascades, remains elusive. By combining whole‐cell patch‐clamp recordings and neuropharmacological methods, we revealed that both non‐selective cationic conductance (NSCC) and endocannabinoids (eCBs) are recruited by orexin signalling on reticulospinal neurones in the caudal pontine reticular nucleus (PnC). The orexin–NSCC cascade provides a depolarizing force that proportionally enhances the firing‐responsive gain of these neurones. Meanwhile, the orexin–eCB cascade selectively attenuates excitatory synaptic strength in these neurones by activating presynaptic cannabinoid receptor type 1. This cascade restrains the firing response of the PnC reticulospinal neurones to excitatory inputs. Intriguingly, non‐linear or linear interactions between orexin postsynaptic excitation and presynaptic inhibition can influence the firing responses of PnC reticulospinal neurones in different directions. When presynaptic inhibition is in the lead, non‐linear interactions can prominently downregulate or even gate the firing response. Conversely, linear interactions occur to promote the firing response, and these linear interactions can be considered a proportional reduction in the contribution of depolarization to firing by presynaptic inhibition. Through the dynamic employment of these interactions, adaptive modulation may be achieved by orexin to restrain or even gate the firing output of the PnC to weak/irrelevant input signals and facilitate those to salient signals.
Analysis and Simulation for Homogeneous and Heterogeneous SIR Models

In mathematical epidemiology, disease transmission is commonly assumed to behave in accordance with the law of mass action; however, other disease incidence terms also exist in the literature. A homogeneous Susceptible-Infectious-Removed (SIR) model with a generalized incidence term is presented along with analytic and numerical results concerning effects of the generalization on the global disease dynamics. The spatial heterogeneity of the metapopulation with nonrandom directed movement between populations is incorporated into a heterogeneous SIR model with nonlinear incidence. The analysis of the combined effects of the spatial heterogeneity and nonlinear incidence on the disease dynamics of our model is presented along with supporting simulations. New global stability results are established for the heterogeneous model utilizing a graph-theoretic approach and Lyapunov functions. Numerical simulations confirm nonlinear incidence gives raise to rich dynamics such as synchronization and phase-lock oscillations.
Frailty, Treatments, and Outcomes in Older Patients With Myocardial Infarction: A Nationwide Registry‐Based Study

Background Guidelines recommend that patients with myocardial infarction (MI) receive equal care regardless of age. However, withholding treatment may be justified in elderly and frail patients. This study aimed to investigate trends in treatments and outcomes of older patients with MI according to frailty. Methods and Results All patients aged ≥75 years with first‐time MI during 2002 to 2021 were identified through Danish nationwide registries. Frailty was categorized using the Hospital Frailty Risk Score. One‐year risk and hazard ratios (HRs) for days 0 to 28 and 29 to 365 were calculated for all‐cause death. A total of 51 022 patients with MI were included (median, 82 years; 50.2% women). Intermediate/high frailty increased from 26.7% in 2002 to 2006 to 37.1% in 2017 to 2021. Use of treatment increased substantially regardless of frailty: for example, 28.1% to 48.0% (statins), 21.8% to 33.7% (dual antiplatelet therapy), and 7.6% to 28.0% (percutaneous coronary intervention) for high frailty (all P‐trend <0.001). One‐year death decreased for low frailty (35.1%–17.9%), intermediate frailty (49.8%–31.0%), and high frailty (62.8%–45.6%), all P‐trend <0.001. Age‐ and sex‐adjusted 29‐ to 365‐day HRs (2017–2021 versus 2002–2006) were 0.53 (0.48–0.59), 0.62 (0.55–0.70), and 0.62 (0.46–0.83) for low, intermediate, and high frailty, respectively (P‐interaction=0.23). When additionally adjusted for treatment, HRs attenuated to 0.74 (0.67–0.83), 0.83 (0.74–0.94), and 0.78 (0.58–1.05), respectively, indicating that increased use of treatment may account partially for the observed improvements. Conclusions Use of guideline‐based treatments and outcomes improved concomitantly in older patients with MI, irrespective of frailty. These results indicate that guideline‐based management of MI may be reasonable in the elderly and frail.
A real-world data analysis of acetylsalicylic acid in FDA Adverse Event Reporting System (FAERS) database

ABSTRACT Background Acetylsalicylic acid (Aspirin), one of the oldest medicines, is widely used in various clinical fields. However, numerous adverse events (AEs) have been reported. In this study, we aimed to investigate adverse drug reactions (ADRs) of aspirin using real-worlddata from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Methods We assessed the disproportionality of aspirin-related AEs by calculating measures such as reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagationneural network (BCPNN), and Gamma-Poisson Shrinker (GPS). Results Out of 7,510,564 casereports in the FAERS database, 18644 reports of aspirin as the ‘primary suspected (PS)’ AEs were recorded. Disproportionality analyses identified 493 aspirin-related preferred terms (PTs) across 25 organ systems. Notably, unexpected significant AEs such as pallor (p=5.66E–33), dependence (p=6.45E–67), and compartment syndrome (p=1.95E–28) were observed, which were not mentioned in the drug’s instructions. Conclusion Our findings align with clinical observations, highlighting potential new and unexpected ADR signals associated with aspirin. Further prospective clinical studies are necessary to confirm and elucidate the relationship between aspirin and these ADRs. This study offers a fresh and unique perspective for studying drug-AEs.
HERO: a space based low frequency interferometric observatory for heliophysicsenabled by novel vector sensor technology

Abstract : HeRO (Heliophysics Radio Observer) is a proposed hybrid ground and space interferometric instrument. The space segment (HeRO-S) covers low frequencies,100 kHz { 20 MHz, and is composed of 6 free-flying CubeSats equipped with vector sensors. The ground segment (HeRO-G), covers higher frequencies, 15 MHz - 300MHz. HeRO will explore conditions and disturbances in a key region of the helio-sphere, from two to tens of solar radii, using interferometric observations of solar radio bursts at frequencies that do not reach the ground. This will provide precise positions and basic structural information. The morphology of CME shock fronts will be traced via type II burst emissions, and heliospheric magnetic field geometries will be probed by measuring precise trajectories of type III bursts. Refraction in the heliospheric plasma on large and intermediate scales will be investigated throughout large volumes via the frequency dependence of accurate interferometric positional data on bursts. The data will also be information rich with high resolution in time, frequency and spatial position, and high SNR, creating fertile ground for discovery of new phenomena.
RBOHF activates stomatal immunity by modulating both reactive oxygen species and apoplastic pH dynamics in Arabidopsis

SUMMARY Stomatal defences are important for plants to prevent pathogen entry and further colonisation of leaves. Apoplastic reactive oxygen species (ROS) generated by NADPH oxidases and apoplastic peroxidases play an important role in activating stomatal closure upon perception of bacteria. However, downstream events, particularly the factors influencing cytosolic hydrogen peroxide (H2O2) signatures in guard cells are poorly understood. We used the H2O2 sensor roGFP2‐Orp1 and a ROS‐specific fluorescein probe to study intracellular oxidative events during stomatal immune response using Arabidopsis mutants involved in the apoplastic ROS burst. Surprisingly, the NADPH oxidase mutant rbohF showed over‐oxidation of roGFP2‐Orp1 by a pathogen‐associated molecular pattern (PAMP) in guard cells. However, stomatal closure was not tightly correlated with high roGFP2‐Orp1 oxidation. In contrast, RBOHF was necessary for PAMP‐mediated ROS production measured by a fluorescein‐based probe in guard cells. Unlike previous reports, the rbohF mutant, but not rbohD, was impaired in PAMP‐triggered stomatal closure resulting in defects in stomatal defences against bacteria. Interestingly, RBOHF also participated in PAMP‐induced apoplastic alkalinisation. The rbohF mutants were also partly impaired in H2O2‐mediated stomatal closure at 100 μm while higher H2O2 concentration up to 1 mm did not promote stomatal closure in wild‐type plants. Our results provide novel insights on the interplay between apoplastic and cytosolic ROS dynamics and highlight the importance of RBOHF in plant immunity.
Mutually Exclusive Weighted Graph Matching Algorithm for Protein-Protein Interaction Network Alignment

Motivation: Understanding and analyzing proteins interacting within a species is a topic of interest in various biological studies. These interactions can be aligned as a full network, allowing research to view the system of interactions that occur globally. Given this global alignment, one common area of research is comparing the protein interactions produced by different species to determine similarity. Results: In this paper, we analyze current alignment methodologies for both a constrained and an unconstrained version of the protein-protein interaction network alignment problem. We also provide a new algorithm, Mutual Exclusion Matching, which scores higher and finds larger alignments than most other algorithms. Finally, we analyze all algorithms tested in a variety of biological and topological measures, showing that Mutual Exclusion produces some of the best alignments found throughout the course of the study, including finding larger connected components, conserving a larger number of edges, and finding some of the highest biologically scoring alignments when compared to other algorithms. Code necessary for running Mutual Exclusion Matching, as well as some example datasets, can be found at: https://sourceforge.net/projects/mutual-exclusion-matching/
Mean age and body mass index at type 2 diabetes diagnosis: Pooled analysis of 56 health surveys across income groups and world regions

Screening for type 2 diabetes mellitus (T2DM) targets people aged 35+ years and those with overweight/obesity. With mounting evidence on young‐onset T2DM and T2DM patients with lean phenotypes, it is worth revising the screening criteria to include younger and leaner adults. We quantified the mean age and body mass index (BMI; kg/m2) at T2DM diagnosis in 56 countries.
Absolute value linear programming

We deal with linear programming problems involving absolute values in their formulations, so that they are no more expressible as standard linear programs. The presence of absolute values causes the problems to be nonconvex and nonsmooth, so hard to solve. In this paper, we study fundamental properties on the topology and the geometric shape of the solution set, and also conditions for convexity, connectedness, boundedness and integrality of the vertices. Further, we address various complexity issues, showing that many basic questions are NP-hard to solve. We show that the feasible set is a (nonconvex) polyhedral set and, more importantly, every nonconvex polyhedral set can be described by means of absolute value constraints. We also provide a necessary and sufficient condition when a KKT point of a nonconvex quadratic programming reformulation solves the original problem.
Modeling critical connectivity constraints in random and empirical networks

Random networks are a powerful tool in the analytical modeling of complex networks as they allow us to write approximate mathematical models for diverse properties and behaviors of networks. One notable shortcoming of these models is that they are often used to study processes in terms of how they affect the giant connected component of the network, yet they fail to properly account for that component. As an example, this approach is often used to answer questions such as how robust is the network to random damage but fails to capture the structure of the network before any inflicted damage. Here, we introduce a simple conceptual step to account for such connectivity constraints in existing models. We distinguish network neighbors into two types of connections that can lead or not to a component of interest, which we call critical and subcritical degrees. In doing so, we capture important structural features of the network in a system of only one or two equations. In particular cases where the component of interest is surprising under classic random network models, such as sparse connected networks, a single equation can approximate state-of-the art models like message passing which require a number of equations linear in system size. We discuss potential applications of this simple framework for the study of infrastructure networks where connectivity constraints are critical to the function of the system.
Polybot: Training One Policy Across Robots While Embracing Variability

Reusing large datasets is crucial to scale vision-based robotic manipulators to everyday scenarios due to the high cost of collecting robotic datasets. However, robotic platforms possess varying control schemes, camera viewpoints, kinematic configurations, and end-effector morphologies, posing significant challenges when transferring manipulation skills from one platform to another. To tackle this problem, we propose a set of key design decisions to train a single policy for deployment on multiple robotic platforms. Our framework first aligns the observation and action spaces of our policy across embodiments via utilizing wrist cameras and a unified, but modular codebase. To bridge the remaining domain shift, we align our policy's internal representations across embodiments through contrastive learning. We evaluate our method on a dataset collected over 60 hours spanning 6 tasks and 3 robots with varying joint configurations and sizes: the WidowX 250S, the Franka Emika Panda, and the Sawyer. Our results demonstrate significant improvements in success rate and sample efficiency for our policy when using new task data collected on a different robot, validating our proposed design decisions. More details and videos can be found on our anonymized project website: https://sites.google. com/view/polybot-multirobot
Cantelli's bounds for generalized tail inequalities in Euclidean spaces

Let $X$ be a centered random vector in a finite dimensional real inner product space $\mathcal{E}$. For a subset $C$ of the ambient vector space $V$ of $\mathcal{E}$ and $x,\,y\in V$, write $x\preceq_C y$ if $y-x\in C$. When $C$ is a closed convex cone in $\mathcal{E}$, then $\preceq_C$ is a pre-order on $V$, whereas if $C$ is a proper cone in $\mathcal{E}$, then $\preceq_C$ is actually a partial order on $V$. In this paper we give sharp Cantelli's type inequalities for generalized tail probabilities like $\text{Pr}\{X\succeq_C b\}$ for $b\in V$. These inequalities are obtained by ``scalarizing'' $X\succeq_C b$ via cone duality and then by minimizing the classical univariate Cantelli's bound over the scalarized inequalities.
A Vulnerability of Attribution Methods Using Pre-Softmax Scores

We discuss a vulnerability involving a category of attribution methods used to provide explanations for the outputs of convolutional neural networks working as classifiers. It is known that this type of networks are vulnerable to adversarial attacks, in which imperceptible perturbations of the input may alter the outputs of the model. In contrast, here we focus on effects that small modifications in the model may cause on the attribution method without altering the model outputs.
Molecular Environment of the Thermal Composite Supernova Remnant G352.7-0.1

Galactic supernova remnants (SNRs) play an important role in our understanding of supernovae and their feedback on the interstellar environment. SNR G352.7-0.1 is special for its thermal composite morphology and double-ring structure. We have performed spectroscopic mapping of the 12CO and 13CO J = 2–1 lines toward G352.7-0.1 with the Atacama Pathfinder Experiment telescope. Broad 12CO lines are found in the northeastern ring at a local-standard-of-rest velocity range of ∼−50 to −30 km s−1, suggesting that the remnant is interacting with molecular clouds at ∼−51 km s−1. Thus, we adopt a distance of ∼10.5 kpc for this SNR. The momentum and kinetic energy of the shocked gas along the line of sight are estimated to be ∼102 M ☉ km s−1 and ∼1046 erg, respectively. We also find an expanding structure around the remnant, which is possibly related to the wind-blown bubble of the progenitor star. From Fermi-LAT data in the energy range 0.1–500 GeV, we find no gamma-ray counterparts to G352.7-0.1.