Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalised Local Extra Dimensions as a Basis for the Elementary Structure of Matter

A central aim of theoretical physics is to account for the structure of matter at the most elementary level as underlying the Standard Model of particle physics, and ideally also as a basis for a substantial dark sector, as distributed in 4-dimensional spacetime. A broad class of theories augment the global 4-dimensional spacetime arena itself to a higher-dimensional spacetime structure, with the properties of matter then deriving from the properties of the extra spatial dimensions. We motivate an alternative approach in which we begin with the local structure of 4-dimensional spacetime and augment the local form for a proper time interval. The symmetries and properties of the residual components, over the local 4-dimensional spacetime form, are found to exhibit appropriate features to account for the visible Standard Model sector while in parallel direct connections can also be identified with dark sector models.
Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction

Skills play a central role in the job market and many human resources (HR) processes. In the wake of other digital experiences, today's online job market has candidates expecting to see the right opportunities based on their skill set. Similarly, enterprises increasingly need to use data to guarantee that the skills within their workforce remain future-proof. However, structured information about skills is often missing, and processes building on self- or manager-assessment have shown to struggle with issues around adoption, completeness, and freshness of the resulting data. Extracting skills is a highly challenging task, given the many thousands of possible skill labels mentioned either explicitly or merely described implicitly and the lack of finely annotated training corpora. Previous work on skill extraction overly simplifies the task to an explicit entity detection task or builds on manually annotated training data that would be infeasible if applied to a complete vocabulary of skills. We propose an end-to-end system for skill extraction, based on distant supervision through literal matching. We propose and evaluate several negative sampling strategies, tuned on a small validation dataset, to improve the generalization of skill extraction towards implicitly mentioned skills, despite the lack of such implicit skills in the distantly supervised data. We observe that using the ESCO taxonomy to select negative examples from related skills yields the biggest improvements, and combining three different strategies in one model further increases the performance, up to 8 percentage points in RP@5. We introduce a manually annotated evaluation benchmark for skill extraction based on the ESCO taxonomy, on which we validate our models. We release the benchmark dataset for research purposes to stimulate further research on the task.
The recursive representation of Gaussian quantum mechanics

We introduce a uniﬁed and diﬀerentiable Fock space representation of Gaussian objects, namely, pure and mixed states, unitaries and channels in terms of a single linear recurrence relation that can generate their Fock space amplitudes recursively. Due to its recursive and diﬀerentiable nature, it makes for a simple and fast computational implementation that enables calculating the gradient of the Fock amplitudes with respect to parametrizations. To demonstrate the ﬂexibility and the generality of the gradient calculation, we show how to optimize M -mode Gaussian objects without the need to express them using fundamental components, by performing an optimization directly on the manifold of the symplectic group (or the unitary group for M -mode interferometers). We also ﬁnd the composition rule of Gaussian operations expressed as the parameters of the recurrence relation, which allows us to obtain the correct global phase when composing Gaussian operations (which normally is absent from the description of Gaussian objects), and therefore to extend our model to states that can be written as linear combinations of Gaussians. We implemented all of these methods in the freely available open-source library MrMustard [1] and we show an example in which we ﬁnd 3-mode circuits to generate cat states with unprecedented success probability and ﬁdelity.
Master regulators of evolution and the microbiome in higher dimensions

A longstanding goal of biology is to identify the key genes and species that critically impact evolution, ecology, and health. Network analysis has revealed keystone species that regulate ecosystems (1) and master regulators that regulate cellular genetic networks (2–4). Yet these studies have focused on pairwise biological interactions, which can be affected by the context of genetic background (5,6) and other species present (7–10) generating higher-order interactions. The important regulators of higher-order interactions are unstudied. To address this, we applied a new high-dimensional geometry approach that quantifies epistasis in a fitness landscape (11) to ask how individual genes
A Spectroscopic Model of the Type Ia Supernova–Host-galaxy Mass Correlation from SALT3

The unknown cause of the correlation between Type Ia supernova (SN Ia) Hubble residuals and their host-galaxy masses (the “mass step”) may bias cosmological parameter measurements. To better understand the mass step, we develop a SALT3 light-curve model for SN cosmology that uses the host-galaxy masses of 296 low-redshift SNe Ia to derive a spectral energy distribution–host-galaxy mass relationship. The resulting model has larger Ca ii H and K, Ca ii near-infrared triplet, and Si ii equivalent widths for SNe in low-mass host galaxies at 2.2–2. 7σ significance; this indicates higher explosion energies per unit mass in low-mass-hosted SNe. The model has phase-dependent changes in SN Ia colors as a function of host mass, indicating intrinsic differences in mean broadband light curves. Although the model provides a better fit to the SN data overall, it does not substantially reduce data–model residuals for a typical light curve in our sample nor does it significantly reduce Hubble residual dispersion. This is because we find that previous SALT models parameterized most host-galaxy dependencies with their first principal component, although they failed to model some significant spectral variations. Our new model is luminosity and cosmology independent, and applying it to data reduces the mass step by 0.021 ± 0.002 mag (uncertainty accounts for correlated data sets); these results indicate that ∼35% of the mass step can be attributed to luminosity-independent effects. This SALT model version could be trained using alternative host-galaxy properties and at different redshifts, and therefore will be a tool for understanding redshift-dependent correlations between SNe Ia and their host properties as well as their impact on cosmological parameter measurements.
An Embedding-Based Grocery Search Model at Instacart

The key to e-commerce search is how to best utilize the large yet noisy log data. In this paper, we present our embedding-based model for grocery search at Instacart. The system learns query and product representations with a two-tower transformer-based encoder architecture. To tackle the cold-start problem, we focus on content-based features. To train the model efficiently on noisy data, we propose a self-adversarial learning method and a cascade training method. On an offline human evaluation dataset, we achieve 10% relative improvement in RECALL@20, and for online A/B testing, we achieve 4.1% cart-adds per search (CAPS) and 1.5% gross merchandise value (GMV) improvement. We describe how we train and deploy the embedding based search model and give a detailed analysis of the effectiveness of our method.
On limitations of conventional approaches to homogenization applied to uniaxial dielectric composite materials

Under certain conditions, the Bruggeman formalism yields estimates of the effective constitutive parameters of homogenized composite materials (HCMs) which are physically implausible. Furthermore, under these conditions, the generalized Hashin-Shtrikman bounds (which are equivalent to the estimates of the effective constitutive parameters of the HCMs provided by the Maxwell Garnett formalism) exhibit strong resonances. The conditions are that (i) the real parts of the constitutive parameters of the constituent materials have opposite signs; and (ii) the constituent materials are weakly dissipative. These limitations - which we had previously established for isotropic dielectric HCMs - are shown to afflict uniaxial dielectric HCMs.
Hamburger Beitr Age Zur Angewandten Mathematik Inexact Trust-region Methods for Nonlinear Complementarity Problems Hamburger Beitr Age Zur Angewandten Mathematik Reihe a Preprints Reihe B Berichte Reihe C Mathematische Modelle Und Simulation Reihe D Elektrische Netzwerke Und Bauelemente Reihe E Scie

In order to solve the nonlinear complementarity problem, we rst refor-mulate it as a nonsmooth system of equations by using a recently introduced NCP-function. We then apply a trust-region-type method to this system of equations. Our trust-region method allows an inexact solution of the trust-region-subproblem. We show that the algorithm is well-deened for a general nonlinear complementarity problem and that it has some nice global and local convergence properties. Numerical results indicate that the new method is quite promising.
A Cross-lingual Comparison of Human and Model Relative Word Importance

Relative word importance is a key metric for natural language processing. In this work, we compare human and model relative word importance to investigate if pretrained neural language models focus on the same words as humans cross-lingually. We perform an extensive study using several importance metrics (gradient-based saliency and attention-based) in monolingual and multilingual models, including eye-tracking corpora from four languages (German, Dutch, English, and Russian). We find that gradient-based saliency, first-layer attention, and attention flow correlate strongly with human eye-tracking data across all four languages. We further analyze the role of word length and word frequency in determining relative importance and find that it strongly correlates with length and frequency, however, the mechanisms behind these non-linear relations remain elusive. We obtain a cross-lingual approximation of the similarity between human and computational language processing and insights into the usability of several importance metrics.
Integrative biology of persister cell formation: molecular circuitry, phenotypic diversification and fitness effects

Microbial populations often contain persister cells, which reduce the extinction risk upon sudden stresses. Persister cell formation is deeply intertwined with physiology. Due to this complexity, it cannot be satisfactorily understood by focusing only on mechanistic, physiological or evolutionary aspects. In this review, we take an integrative biology perspective to identify common principles of persister cell formation, which might be applicable across evolutionary-distinct microbes. Persister cells probably evolved to cope with a fundamental trade-off between cellular stress and growth tasks, as any biosynthetic resource investment in growth-supporting proteins is at the expense of stress tasks and vice versa. Natural selection probably favours persister cell subpopulation formation over a single-phenotype strategy, where each cell is prepared for growth and stress to a suboptimal extent, since persister cells can withstand harsher environments and their coexistence with growing cells leads to a higher fitness. The formation of coexisting phenotypes requires bistable molecular circuitry. Bistability probably emerges from growth-modulated, positive feedback loops in the cell's growth versus stress control network, involving interactions between sigma factors, guanosine pentaphosphate and toxin–antitoxin (TA) systems. We conclude that persister cell formation is most likely a response to a sudden reduction in growth rate, which can be achieved by antibiotic addition, nutrient starvation, sudden stresses, nutrient transitions or activation of a TA system.
Assessing the usability and acceptability of Face IT@home: an online CBT intervention for people with visible differences

Abstract To increase access to support, an online psychosocial support tool for adults with visible differences was adapted for use without referral or supervision. This intervention combines a cognitive behavioural and social skills model of support. This study aimed to assess the usability and acceptability of Face IT@home as a self-help intervention. Eighty-one participants were recruited (32 with visible differences). Stage 1 included 14 participants (11 female, all with visible differences) who viewed two sessions of Face IT@home and undertook a semi-structured telephone interview. Stage 2 consisted of 14 think-aloud sessions (13 female, none with visible differences) with participants, supervised by researchers. Stage 3 employed 53 participants (47 female; 19 with visible differences), to view one session of Face IT@home and complete an online survey to evaluate usability and acceptability. User interviews, think-aloud studies and questionnaires identified usability and acceptability factors of Face IT@home that make it fit for purpose as a self-help tool. Participants suggested some changes to the Face IT@home program to improve usability. Participants reported that Face IT@home was a useful tool for people with visible differences and could be effective. The CBT-based model was considered a useful approach to addressing psychosocial concerns. The online self-help format will increase access to psychological support for adults with visible differences. Key learning aims (1) The paper outlines an important cognitive behavioural framework for supporting adults with visible differences. (2) The paper demonstrates the importance of user testing and client involvement in developing intervention models. (3) The studies highlight one approach to the process of user testing that can produce a robust online intervention.
Seasonal structure of interactions enhances multidimensional stability of mutualistic networks

Community ecologists have made great advances in understanding how natural communities can be both diverse and stable by studying communities as interaction networks. However, focus has been on interaction networks aggregated over time, neglecting the consequences of the seasonal organization of interactions (hereafter 'seasonal structure') for community stability. Here, we extended previous theoretical findings on the topic in two ways: (i) by integrating empirical seasonal structure of 11 plant–hummingbird communities into dynamic models, and (ii) by tackling multiple facets of network stability together. We show that, in a competition context, seasonal structure enhances community stability by allowing diverse and resilient communities while preserving their robustness to species extinctions. The positive effects of empirical seasonal structure on network stability vanished when using randomized seasonal structures, suggesting that eco-evolutionary dynamics produce stabilizing seasonal structures. We also show that the effects of seasonal structure on community stability are mainly mediated by changes in network structure and productivity, suggesting that the seasonal structure of a community is an important and yet neglected aspect in the diversity–stability and diversity–productivity debates.
How statistical are quantum states

A novel no-go theorem is presented which sets a bound upon the extent to which '\Psi-epistemic' interpretations of quantum theory are able to explain the overlap between non-orthogonal quantum states in terms of an experimenter's ignorance of an underlying state of reality. The theorem applies to any Hilbert space of dimension greater than two. In the limit of large Hilbert spaces, no more than half of the overlap between quantum states can be accounted for. Unlike other recent no-go theorems no additional assumptions, such as forms of locality, invasiveness, or non-contextuality, are required.
The energy density of meals and snacks consumed by young Australian adults (18–30 years old) are influenced by preparation location but not screen use nor social interactions: findings from the MYMeals wearable camera study

Abstract The present study examined the association of contextual factors (social and food preparation location) with the energy density of meals and snacks consumed in a sample of young Australian adults (18–30 years old) identified using wearable camera technology. Over three consecutive days, a subsample of young adults wore a wearable camera that captured images in 30 s intervals. Eating episodes from 133 participants were annotated for preparation location and social context (covering social interaction and screen use). Over the same period, participants completed daily 24 h recalls. The nutritional composition of meals and snacks was calculated by matching the items identified in the camera to the 24 h recall using time and date stamps. Self-reported data (weight and height) was used to calculate body mass index and (residential postcode) to assign socio-economic status. The association of context and demographic factors with energy density was determined using a mixed linear regression model employing the bootstrap method with bias-corrected and accelerated. In total, 1817 eating episodes were included in the analysis (n 8 preparation unclear and n 15 food components could not be identified excluded). Food prepared within the home was 1⋅1 kJ/g less energy-dense than other preparation locations. Lunches (CI −1⋅7 to −0⋅3) and dinners (CI −1⋅6 to −0⋅5) were both 1⋅0 kJ/g lower in energy density than breakfasts. Snacks were 3⋅5 kJ/g (CI 2⋅8–4⋅1) more energy-dense than breakfasts. Food prepared outside the home and food consumption during snacking appear to be adversely contributing to energy-dense food intake.
Phoresis in cellular flows: from enhanced dispersion to blockage

Abstract In this article, we study numerically the dispersion of colloids in a two-dimensional cellular flow in the presence of an imposed mean salt gradient. Owing to the additional scalar, the colloids do not follow exactly the Eulerian flow field, but have a (small) extra-velocity proportional to the salt gradient, $\boldsymbol {v}_{dp}=\alpha \boldsymbol {\nabla } S$, where $\alpha$ is the phoretic constant and $S$ the salt concentration. We study the demixing of an homogenous distribution of colloids and how their long-term mean velocity $\boldsymbol {V_m}$ and effective diffusivity $D_{eff}$ are influenced by the phoretic drift. We observe two regimes of colloids dynamics depending on a blockage criterion $R=\alpha G L/\sqrt {4 D_cD_s}$, where $G$ is the mean salt gradient amplitude, $L$ the length scale of the flow and $D_c$ and $D_s$ the molecular diffusivities of colloids and salt. When $R<1$, the mean velocity is strongly enhanced with $V_m \propto \alpha G \sqrt {Pe_s}$, ${Pe}_s$ being the salt Péclet number. When $R > 1$, the compressibility effect due to the phoretic drift is so strong that a depletion of colloids occurs along the separatrices inhibiting cell-to-cell transport.
Tonic and phasic effects of reward on the pupil: implications for locus coeruleus function

The locus coeruleus (LC), a nucleus in the pons of the brainstem, plays a significant role in attention and cognitive control. Here, we use an adapted auditory oddball paradigm and measured the pupil dilation response, to provide a marker of LC activity in humans. In Experiment 1, we show event-related pupil responses to rare auditory events which were further elevated by task relevant. In Experiment 2, by asking participants to silently count the number of oddballs, we demonstrated that the task-relevance elevation was not a result of the generation or execution of the manual response. In Experiment 3, we observed two separate effects of reward on the pupil response. First, we found an overall increase in pupil area in the high compared to the low-reward blocks: a sustained effect reminiscent of the tonic changes that occur in LC. Second, we found elevated event-related pupil responses to behaviourally relevant stimuli in the high-reward condition compared with the low-reward condition, consistent with phasic changes in LC in response to a stimulus. These results highlight the complexity of the relationship between the pupil response and reward, and the inferred role of LC in both top-down and bottom-up cognitive control.
Longitudinal Evaluation of the QuantiFERON-TB Gold Plus Assay in Hospitalized COVID-19 Patients with a First Indeterminate Result: Resolution of Inflammation and Restoration of T-Lymphocyte Counts and Interferon-Gamma Production

S everal studies report an increased rate of indeterminate QuantiFERON-TB Gold Plus (QFT-P) results in patients hospitalized because of severe Coronavirus Disease (COVID)-19, and this is due to peripheral blood T-lymphocyte depletion and dysfunction (1 – 6), which are known to be associated with COVID-19 disease severity and mortality (7 – 9). So far, there are no reports concerning QFT-P responses and relations with lymphocyte counts or in ﬂ ammation markers in subjects who survived COVID-19 and received a previous indeterminate result after the acute phase of the disease. For this reason, patients hospitalized because of COVID-19 from March 2020 to August 2021 in the Infectious Disease Unit of Policlinico Tor Vergata University Hospital who received an indeterminate QFT-P test during hospitalization were recalled for reassessment after recovery in the post-COVID outpatient clinic. Those who gave written informed consent were enrolled in the study. Collection tubes for the QFT-P test were purchased from Qiagen, and the interferon gamma (IFN- g ) levels were assessed via chemiluminescence immu-noassay using the Liaison XL Analyzer. In a
Similarity and Compatibility in Fuzzy Set Theory: Assessment And Applications

Assessing the degree to which two objects, an object and a query, or two concepts are similar or compatible is a fundamental component of human reasoning and consequently is critical in the development of automated diagnosis, classification, information retrieval and decision systems. The assessment of similarity has played an important role in such diverse disciplines such as taxonomy, psychology, and the social sciences. Each discipline has proposed methods for quantifying similarity judgments suitable for its particular applications. This book presents a unified approach to quantifying similarity and compatibility within the framework of fuzzy set theory and examines the primary importance of these concepts in approximate reasoning. Examples of the application of similarity measures in various areas including expert systems, information retrieval, and intelligent database systems are provided.