Miracle-dz/UniFAR-FTUs huggingface dataset:
A certain sublattice of the lattice of congruences on a regular semigroup

It is well known that, with respect to the natural partial ordering, the set of all congruences on a group forms a modular lattice. In the present paper we develop an extension of this result to the case of a regular semigroup S (α ∈ αSα for all α in S). Let Σ(ℋ) denote the set of all congruences on S with the property that congruent elements generate the same principal left ideal and the same principal right ideal of S. We show (Theorem 1) that, under the natural partial ordering, Σ(ℋ) is a modular lattice with a greatest and a least element.
Electrophoretic trajectories of non-uniformly charged particles in viscoelastic fluids: the weak surface charge limit

Abstract Electrophoretic motion of a particle carrying a weak but arbitrary non-uniform surface charge density in an Oldroyd-B fluid is analysed here in the thin electrical double layer limit. A semi-analytical generic framework, based on regular perturbation, the Lamb's general solutions and the generalized reciprocal theorem, assuming the viscoelastic effects to remain subdominant, is developed for tracing the particle's trajectory using its instantaneous translational velocity and accounting for the temporal evolution of its surface charge driven by rotation. Our results reveal that in a viscoelastic medium, non-uniformly charged particles may generally follow distinct trajectories depending on their sizes, which is in stark contrast to Newtonian fluids. By considering the multipole moments of the surface charge, we show that the particle may initially rotate until its dipole moment becomes collinear with the imposed electric field, and the nature of the surrounding medium does not alter this fundamental behaviour. However, during the course of rotation, the excess polymeric stresses within the electrical double layer and the bulk may cause the particle to migrate perpendicular to the applied field, by forcing the multipole moments of the surface charge to interact with each other. The final steady-state trajectory of the particle and its possible migration normal to the applied electric field are also largely governed by these interactions and more specifically, presence of non-zero quadrupole moments. The present framework may be helpful towards designing tools for particle separation and sorting, relevant in many biological applications.
A non-marine horseshoe crab from the Middle Triassic (Anisian) of the Netherlands

Abstract Horseshoe crabs (Xiphosura) have a long evolutionary history starting in the Ordovician, but they have rarely been reported from the Netherlands. We report on the first Triassic horseshoe crab from the Netherlands identifiable to the species level, a specimen of the limulid Limulitella bronnii. We provide the first diagnosis for this species and refigure the holotype. The new specimen was found in the Middle Triassic (Anisian) Muschelkalk sediments of the Vossenveld Formation, in the Illyrian part of the stratigraphic profile of the Winterswijk quarry complex. The Winterswijk specimen represents the youngest occurrence of L. bronnii. The inferred non-marine habitat of this horseshoe crab species elsewhere in conjunction with occurrences of plant and insect remains within the same layer at Winterswijk suggest the specimen herein most probably did not live in marine conditions either. This species has previously been found in non-marine sediments in France and Germany, expanding its geographic range northward. Several faunal elements from Winterswijk including L. bronnii show resemblance to the roughly co-eval non-marine components of the Anisian Grès à Voltzia Formation in NE France, suggesting a paleobiogeographic connection between these regions in Western Europe.
A comprehensive study of medically serious suicide attempts in France: incidence and associated factors

Abstract Aims People who make medically serious suicide attempts (MSSAs) share a number of features with those who die by suicide, and are at a high risk of suicide themselves. Studies to date have mostly focused on clinical samples of MSSAs. An epidemiological examination at a national level can help to identify risk profiles and pathways of care in this population. Methods We explored the French nationwide hospital discharge database (Programme de Médicalisation des Systèmes d'Information, PMSI) to identify any MSSA taking place between 2012 and 2019. Relevant demographic and medical information was collected about the first MSSA of each attempter. Data from 2010 and 2011 were used to verify the absence of prior attempts. Results First occurrences of MSSAs amounted to 81 959 cases over 8 years, with a mean age of 45.8 years, and 53.6% women. Incidence was higher in women (18.1 v. 17.3 per 1 00 000). The most common suicide method was deliberate self-poisoning (64.9% of cases). In comparison, violent methods associated higher mortality and comorbidity and were more frequent in men. The most common mental disorders were mood disorders (55.6%) and substance use disorders (46.2%). A minority of MSSA survivors were hospitalised in psychiatry (32.5%), mostly women. Conclusions MSSAs are frequent and easy to identify. There is a need to reinforce the continuity of psychiatric care for this population given the high risk of subsequent suicide, and the low rates of psychiatric hospitalisation after an MSSA even if violent methods are used. Specific care targeting this population could reduce treatment gaps.
Modeling vehicular and pedestrian delays at signalized midblock crosswalk under mixed traffic conditions

ABSTRACT The present study aims to develop vehicular and pedestrians delay models for signalized midblock crosswalks under mixed traffic conditions. In this study, the primary data on pedestrian and vehicle flow characteristics were recorded using video-graphic technique. The mixed traffic characteristics and other field conditions were simulated in the Vissim micro-simulation tool. The traffic flow characteristics were calibrated and validated using GEH statistics, which came out to be 2.5. For modeling the pedestrian and vehicle delays, several scenarios were simulated by varying the traffic flow and traffic signal characteristics. For each scenario, the simulated delay values were recorded. Considering the data set simulated, the delay models were developed using multiple linear regression technique with 10-fold cross validation. These models were then validated which yielded an error (MAPE) of 17% and 13% in estimating pedestrian and vehicle delays respectively. These models can be used as a tool designing better pedestrian facilities at signalized midblock crosswalks.
Impacts of Adjunct Incorporation on Flavor Stability Metrics at Early Stages of Beer Production

Abstract The fresh flavor of a beer brand is one of its most important quality parameters and should be retained as long as possible through shelf-life. Early stages of beer production can have significant impacts on beer flavor stability. The use of cereal adjuncts – either malted or unmalted – is now widespread practice in brewing. This laboratory mashing study investigated the impacts of incorporating common solid adjuncts (corn and rice) at increasing grist percentages (0-50%) on flavor stability indicators measured in wort. Sweet worts were analysed for metal ion levels (ICP-MS), thiol content (RP-HPLC), oxidative stability (EPR spectroscopy), staling aldehydes (HS-SPME-GC-MS), trihydroxy fatty acids (GC-FID), t-2-nonenal potential (GC-MS), color and thiobarbituric acid (TBI). Mashing conditions for each formulation were adjusted in order to achieve target FAN values. Unmalted rice or corn adjuncts significantly reduced the total metal ion content, color, TBI and staling aldehydes in sweet worts at 50% adjunct incorporation (p < 0.05), relative in each case to the respective all-malt control mash. Our findings showed that unmalted rice or corn adjunct incorporation generally improved flavor stability metrics in sweet worts when similar mashing conditions were applied, whilst increasing the length of the ‘protein stand’ in mashing to reach target FAN in general had a negative impact on flavor stability indicators – e.g., wort T150 values significantly decreased in each recipe at 25% and 35% adjunct relative to the 12.5% adjunct brew but increased again at 50% adjunct, presumably due to the prolonged proteolytic stand employed to achieve target FAN content.
Revealing the differences in the SMBH accretion rate distributions of starburst and non-starburst galaxies

We infer and compare the specific X-ray luminosity distributions for a sample of massive (i.e. $\log_{10} (M*/M\odot) > 10.5$) galaxies split according to their far-infrared-derived star-forming properties (i.e., starburst and non-starburst) and redshift. We model each distribution as a power-law with an upper and lower turnover, and adopt a maximum likelihood method to include information from non-detections in the form of upper limits. When we use our inferred distributions to calculate the ratios of high to low sLx AGN (corresponding to above and below $0.1\lambda_{\text{Edd}}$, respectively) we find that starbursts have significantly higher proportions of high sLx AGN compared to their non-starburst counterparts. These findings help explain the increase in average X-ray luminosity in bins of increasing SFR reported by previous studies.
Shortcomings of Interpretability Taxonomies for Deep Neural Networks

Taxonomies are vehicles for thinking about what’s possible, for identifying unconsidered options, as well as for establishing formal relations between entities. We identify several shortcomings in 10 existing taxonomies for interpretability methods for explainable artificial intelligence (XAI), focusing on methods for deep neural networks. The shortcomings include redundancies, incompleteness, and inconsistencies. We design a new taxonomy based on two orthogonal dimensions and show how it can be used to derive results about entire classes of interpretability methods for deep neural networks.
Two-dimensional vector-coupled-mode theory for textured planar waveguides

We develop a model to treat coupling between guided modes in planar dielectric waveguides that have been textured in two dimensions with a thin surface grating. The formulation is based on a general Green's-function technique that self-consistently determines the field in the surface grating due to the polarization there. With simplifying approximations, this formalism is cast into a two-dimensional (2D) vector-coupled-mode theory that is more computationally efficient, and that gives considerable insight into the nature of mode coupling in 2D textured structures. These models are applied, by way of example, to illustrate some interesting properties of leaky and bound modes that are coupled together by 2D periodic texture. In particular we discuss the complex photonic band structure describing the dispersion, lifetimes, and polarization properties of the resonant states associated with the textured waveguide. In our analysis we emphasize the fundamental differences between coupling in 2D textured waveguides and infinite 2D photonic crystals. We also show that the vector-coupled-mode theory agrees well with the self-consistent formulation.
Want robust explanations? Get smoother predictions first

Model-agnostic machine learning interpretability methods like LIME which explain the predictions of elaborate machine learning models suffer from a lack of robustness in the explanations they provide. Small targeted changes to the input can result in large changes in explanations even when there are no significant changes in the predictions made by the machine learning model. This is a serious problem as it undermines the trust one has in the explanations made. We propose to solve the problem by smoothening the predictions of the machine learning model as a preprocessing step. We smoothen the predictions by taking multiple samples from the neighbourhood of each input data point and averaging the output predictions. Through our preliminary experiments, we show that the explanations are more robust because of smoothening thus making them more reliable.
Asymptotics of the 1/2-dimension, Discrete Airy Equation and its Approximating Differential Equation

A discrete finite difference model is constructed for the Airy equation using a nonstandard scheme formulated by Mickens and Ramadhani. The method of dominant balance is then applied to obtain a first-order difference equation for the solution that increases sufficiently fast as k→∞. We then calculate the corresponding approximating differential equation and obtain its exact solution as well as its “exact” discrete finite difference representation. The application of various symmetry operations allows the determination of the related rapidly decreasing solution and the oscillatory solutions for negative values of x k>=hk, where h=▵x.
Meta-Learning Convolutional Neural Architectures for Multi-Target Concrete Defect Classification With the COncrete DEfect BRidge IMage Dataset

Recognition of defects in concrete infrastructure, especially in bridges, is a costly and time consuming crucial first step in the assessment of the structural integrity. Large variation in appearance of the concrete material, changing illumination and weather conditions, a variety of possible surface markings as well as the possibility for different types of defects to overlap, make it a challenging real-world task. In this work we introduce the novel COncrete DEfect BRidge IMage dataset (CODEBRIM) for multi-target classification of five commonly appearing concrete defects. We investigate and compare two reinforcement learning based meta-learning approaches, MetaQNN and efficient neural architecture search, to find suitable convolutional neural network architectures for this challenging multi-class multi-target task. We show that learned architectures have fewer overall parameters in addition to yielding better multi-target accuracy in comparison to popular neural architectures from the literature evaluated in the context of our application.
Multitarget Bayes filtering via first-order multitarget moments

The theoretically optimal approach to multisensor-multitarget detection, tracking, and identification is a suitable generalization of the recursive Bayes nonlinear filter. Even in single-target problems, this optimal filter is so computationally challenging that it must usually be approximated. Consequently, multitarget Bayes filtering will never be of practical interest without the development of drastic but principled approximation strategies. In single-target problems, the computationally fastest approximate filtering approach is the constant-gain Kalman filter. This filter propagates a first-order statistical moment - the posterior expectation - in the place of the posterior distribution. The purpose of this paper is to propose an analogous strategy for multitarget systems: propagation of a first-order statistical moment of the multitarget posterior. This moment, the probability hypothesis density (PHD), is the function whose integral in any region of state space is the expected number of targets in that region. We derive recursive Bayes filter equations for the PHD that account for multiple sensors, nonconstant probability of detection, Poisson false alarms, and appearance, spawning, and disappearance of targets. We also show that the PHD is a best-fit approximation of the multitarget posterior in an information-theoretic sense.
Convex models, MLE and misspecification

We analyze the asymptotic behavior of maximum likelihood estimators (MLE) in convex dominated models when the true distribution generating the independent data does not necessarily belong to the model. Inspired by the Hellinger distance and its properties, we introduce a family of divergences (contrast functions) which allow a unified treatment of well- and misspecified convex models. Convergence and rates of convergence of the MLE with respect to our divergences are obtained from inequalities satisfied by these divergences and results from empirical process theory (uniform laws of large numbers and maximal inequalities). As a particular case we recover existing results for Hellinger convergence of MLE in well-specified convex models. Four examples are considered: mixtures of discrete distributions, monotone densities, decreasing failure rate distributions and a finite-dimensional parametric model.
Suppression of lusitropy as a disease mechanism in cardiomyopathies

In cardiac muscle the action of adrenaline on β1 receptors of heart muscle cells is essential to adjust cardiac output to the body’s needs. Adrenergic activation leads to enhanced contractility (inotropy), faster heart rate (chronotropy) and faster relaxation (lusitropy), mainly through activation of protein kinase A (PKA). Efficient enhancement of heart output under stress requires all of these responses to work together. Lusitropy is essential for shortening the heartbeat when heart rate increases. It therefore follows that, if the lusitropic response is not present, heart function under stress will be compromised. Current literature suggests that lusitropy is primarily achieved due to PKA phosphorylation of troponin I (TnI) and phospholamban (PLB). It has been well documented that PKA-induced phosphorylation of TnI releases Ca2+ from troponin C faster and increases the rate of cardiac muscle relaxation, while phosphorylation of PLB increases SERCA activity, speeding up Ca2+ removal from the cytoplasm. In this review we consider the current scientific evidences for the connection between suppression of lusitropy and cardiac dysfunction in the context of mutations in phospholamban and thin filament proteins that are associated with cardiomyopathies. We will discuss what advances have been made into understanding the physiological mechanism of lusitropy due to TnI and PLB phosphorylation and its suppression by mutations and we will evaluate the evidence whether lack of lusitropy is sufficient to cause cardiomyopathy, and under what circumstances, and consider the range of pathologies associated with loss of lusitropy. Finally, we will discuss whether suppressed lusitropy due to mutations in thin filament proteins can be therapeutically restored.
Editorial: MISS innovations: Approaches, predictive outcomes, and risk avoidance

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Analysis of genetic diversity and selection characteristics using the whole genome sequencing data of five buffaloes, including Xilin buffalo, in Guangxi, China

Buffalo is an economically important livestock that renders useful services to manhood in terms of meat, milk, leather, and draught. The Xilin buffalo is among the native buffalo breeds of China. In the present study, the genetic architecture and selection signature signals of Xilin buffalo have been explored. Correlation analysis of the population structure of Xilin buffalo was conducted by constructing NJ tree, PCA, ADMIXTURE and other methods. A total of twenty-five (n = 25) Xilin buffalo whole genome data and data of forty-six (n = 46) buffaloes published data were used. The population structure analysis showed that the Xilin buffalo belong to the Middle-Lower Yangtze. The genome diversity of Xilin buffalo was relatively high. The CLR, π ratio, F ST, and XP-EHH were used to detect the candidate genes characteristics of positive selection in Xilin buffalo. Among the identified genes, most of the enriched signal pathways were related to the nervous system and metabolism. The mainly reported genes were related to the nervous system (GRM5, GRIK2, GRIA4), reproductive genes (CSNK1G2, KCNIP4), and lactation (TP63). The results of this study are of great significance for understanding the molecular basis of phenotypic variation of related traits of Xilin buffalo. We provide a comprehensive overview of sequence variations in Xilin buffalo genomes. Selection signatures were detected in genomic regions that are possibly related to economically important traits in Xilin buffalo and help in future breeding and conservation programs of this important livestock genetic resource.
Ixodes ricinus ticks have a functional association with Midichloria mitochondrii

In addition to being vectors of pathogenic bacteria, ticks also harbor intracellular bacteria that associate with ticks over generations, aka symbionts. The biological significance of such bacterial symbiosis has been described in several tick species but its function in Ixodes ricinus is not understood. We have previously shown that I. ricinus ticks are primarily inhabited by a single species of symbiont, Midichloria mitochondrii, an intracellular bacterium that resides and reproduces mainly in the mitochondria of ovaries of fully engorged I. ricinus females. To study the functional integration of M. mitochondrii into the biology of I. ricinus, an M. mitochondrii-depleted model of I. ricinus ticks was sought. Various techniques have been described in the literature to achieve dysbiosed or apo-symbiotic ticks with various degrees of success. To address the lack of a standardized experimental procedure for the production of apo-symbiotic ticks, we present here an approach utilizing the ex vivo membrane blood feeding system. In order to deplete M. mitochondrii from ovaries, we supplemented dietary blood with tetracycline. We noted, however, that the use of tetracycline caused immediate toxicity in ticks, caused by impairment of mitochondrial proteosynthesis. To overcome the tetracycline-mediated off-target effect, we established a protocol that leads to the production of an apo-symbiotic strain of I. ricinus, which can be sustained in subsequent generations. In two generations following tetracycline administration and tetracycline-mediated symbiont reduction, M. mitochondrii was gradually eliminated from the lineage. Larvae hatched from eggs laid by such M. mitochondrii-free females repeatedly performed poorly during blood-feeding, while the nymphs and adults performed similarly to controls. These data indicate that M. mitochondrii represents an integral component of tick ovarian tissue, and when absent, results in the formation of substandard larvae with reduced capacity to blood-feed.