Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution du flux de matière, de l'architecture et de la rhéologie d'un prisme d'accrétion crustal (Dôme d'Orlica-Śnieżnik, Sudètes)

L'evolution du flux de matiere, de l'architecture et de la rheologie d'un prisme d'accretion orogenique au cours du temps est abordee a l'aide d'une etude geologique multimethode. Le dome d'Orlica-Śnieznik dans les Sudetes est situe au front d'un butoir rigide. La formation de ce dome est expliquee par l'influx de croute continentale felsique issue de la marge passive subductee jusqu'a 50-60km de profondeur dans un prisme d'accretion d'echelle crustale. La racine ainsi formee comprend une croute inferieure felsique avec quelques lentilles basiques partiellement fondues en profondeur et separees de la croute moyenne (metasediments, metavolcanites) par une couche rigide d'orthogneiss peu deformee. Cette infrastructure rheologiquement heterogene resultant du remplissage du prisme est fortement remaniee au front du butoir par des plissements plurikilometriques de longueurs d'onde variables. Ceux-ci permettent des echanges verticaux aboutissant a l'exhumation des differents niveaux crustaux de l'infrastructure. La croissance du dome par plissement au front du butoir s'acheve par le decoiffement de la suprastructure associe a un amincissement ductile localise et a un remplissage des bassins syn-orogeniques adjacents. Cette etude montre bien la formation et l'evolution conjuguee des differents niveaux crustaux en particulier lors de l'enfouissement le long de la zone de subduction au sein du prisme. Ici, la deformation dans les orthogneiss est tres localisee et permet le transport passif de larges portions de roches peu deformees et rigides. Ceci est explique par un changement dans le mecanisme de recristallisation des roches quartzo feldspathiques d'un fluage- dislocation intense vers un glissement aux joints de grains. Ce changement est initie par la croissance de phases interstitielles dans les agregats monomineraux. Ce type d'evolution dans un gradient prograde eclogitique est aussi observe dans les migmatites formant le cœur des anticlinaux proches du butoir. Ils permettent l'adoucissement rheologique necessaire au fluage dans le prisme d'accretion crustal.
A phase 2 study of ibrutinib maintenance following first‐line high‐dose methotrexate‐based chemotherapy for elderly patients with primary central nervous system lymphoma

Elderly patients account for nearly 70% of all primary central nervous system lymphoma (PCNSL) cases. They cannot tolerate aggressive treatment and have poor prognosis with a median overall survival (OS) of less than 2 years and progression‐free survival (PFS) of 6–16 months. Ibrutinib penetrates the blood–brain barrier and has shown activity in PCNSL.
Challenges in using data on fathers/partners to study prenatal exposures and offspring health

Introduction: Paternal exposures (and other non-maternal factors) around pregnancy could have important effects on offspring health. One challenge in research of paternal effects is that study samples with data on partners are usually a subgroup of those with data on mothers, which could introduce selection bias and limit generalisability of the findings. Here, we use maternal and father/partner data on prenatal behaviours to explore the extent to which selection in partner analyses might bias findings. Methods: We characterise the availability of data on father/partner and mother health behaviours (smoking, alcohol consumption, caffeine consumption and physical activity) in the prenatal period from three UK cohort studies: the Avon Longitudinal Study of Parents and Children (ALSPAC), Born in Bradford (BiB) and the Millennium Cohort Study (MCS). We assess the extent of sample selection in these cohorts by comparing the characteristics of families where the father/partner does and does not participate. Using the association of parental smoking during pregnancy and child birthweight as an exemplar, we used simulations to explore the extent to which missing father/partner data may bias estimates. Results: In all three cohorts, data on prenatal health behaviours of fathers/partners were less detailed and collected at fewer timepoints than data on prenatal health behaviours of mothers. Partners of mothers who had a lower socioeconomic position were less likely to participate. Estimates of the association between maternal smoking and offspring birthweight were similar in samples with and without participating partners in all three cohorts. In simulations based on ALSPAC data, there was little evidence of selection bias in associations of maternal smoking with birthweight, and although bias was observed for father/partner smoking, its magnitude was relatively small. Discussion: Using real and simulated data, we show that bias due to selected recruitment of partners into ALSPAC, BiB and MCS had a relatively small impact on estimates of the effects of maternal and partner smoking on offspring birthweight. In other applications, the impact of selection bias will depend on both the analysis model and the selection mechanism. We have shown how to use a simulation study to assess that and recommend that applied researchers working with partner data use simulations and other sensitivity analyses to assess the robustness of their results.
Challenging the Conventional Treatment Initiation Paradigm: Early Detection of Irreversible Cellular Damage in Cardiac Biopsies of Fabry Disease Before the Formation of Gb3 Inclusion Bodies

Background: Fabry disease (FD) is a rare X-linked lysosomal storage disorder that affects multiple organs including the heart. In this study, we investigated if early-stage globotriaosylceramide (Gb3) accumulation, before occurrence of inclusion bodies, could cause significant stress and irreversible damages of the cardiomyocytes in FD patients. Methods: Immunofluorescent (IF) staining was performed on fibroblasts from FD patients with IVS4 mutation and myocardial biopsies from G3Stg/GLAko mice and IVS4 FD patients. The staining targeted interleukin-18 (IL-18), nuclear factor-? B (NF-? B), and inducible nitric oxide synthase (iNOS) as inflammatory and oxidative stress markers. Remarkably, the mouse and human myocardial biopsies selected for this study showed detectable Gb3 accumulation under fluorescence but did not exhibit typical FD (Gb3 inclusion body) pathology. Additionally, alpha-smooth muscle actin (? -SMA) IF staining was conducted to detect fibrosis. Results: The results showed that fibroblasts and cardiomyocytes of mice and patients had significant accumulation of inflammatory markers IL-18 and NF-? B, and oxidative stress marker iNOS. The presence of fibrosis was confirmed in these myocardial biopsies through strong positive staining of ? -SMA, despite the absence of typical FD pathology. Conclusions: This study suggests that significant cellular stress and even irreversible damages could exist before the typical pathological changes (inclusion bodies formation) in cardiomyocytes of FD. Based on our findings, it is evident that to prevent irreversible damage and improve the prognosis of patients with FD, treatment should be initiated much earlier than we currently thought.
Privacy preserving association rule mining with scalar product

One crucial aspect of distributed data mining is privacy preserving. Secure multiparty computation (SMC) is a useful approach to solve privacy preserving in distributed data mining. When data is vertically partitioned, scalar product is a feasible tool to securely discover frequent itemsets of association rule mining. We first show that several of the private scalar product protocols and analysis their insecurity. Then we develop a new and efficient protocol to perform two-party scalar product with an untrusted third party. The method is described in detail in this paper with complete analysis to demonstrate its effectiveness. Our protocol maintains integrity and high security of the data sets of each party while keeping communication and computation cost low.
Dip range for intracontinental reverse fault ruptures: Truth not stranger than friction?

Histograms of fault dips have been compiled for moderate to large (M > 5.5) reverse-slip intracontinental earthquakes with the slip-vector raking 90 ± 30° in the fault plane. The principal data set is restricted to earthquakes where the fault plane in the focal mechanism can be unambiguously distinguished from the auxilliary plane; the reverse fault dips are bracketed within the range 12° < δ < 60° with a prominent peak in the 25° to 35° interval and a subsidiary peak in the 45° to 55° interval. Assuming horizontal trajectories for maximum compressive stress (σ1), the observed dip range is consistent with reactivation of faults possessing rock friction coefficients within Byerlee's (1978) range (0.85 > μs > 0.6), undergoing frictional lockup at dips approaching 60°. The broad 25° to 35° peak may arise from progressive domino steepening of imbricate reverse faults above the optimal dip for reactivation in regions undergoing bulk shortening. Paucity of very low-angle thrusts implies that it is generally the steeper ramps within ramp-flat assemblages that fail in moderate to large earthquakes. The subsidiary peak at 45° to 55° likely results from compressional reactivation of former normal faults in areas undergoing tectonic inversion, requiring some degree of fluid overpressuring. The results are consistent with previous studies on the dip range for active normal faults that again demonstrate frictional lockup at reactivation angles approaching 60°; together, these analyses suggest that “Byerlee” friction coefficients apply to faults with displacements of up to a few kilometers.
An effective gauge field theory of the nucleon interactions

We discuss the possibility of constructing an effective gauge field theory of the nucleon interations based on the ideas of isotopic invariance as well as hypercharge invariance as a local gauge symmetry and spontaneous breaking of this symmetry. The constructed model predicts the structure of interactions of protons and neutrons with $\rho$- and $\sigma$-mesons, with pi-mesons and photons, as well as interactions of these particles with each other. The Lagrangian of the model consists of several parts parts involving dimension 4 and 5 gauge invariant operators. Feynman rules for physical degrees of freedom as follow from the Lagrangian define the structure of diagrams for one-boson exchanges between nucleons predicting the internucleon one-boson exchange potential as well as nucleon scattering amplitudes. The range of applicability of the model is discussed and estimates are made of the resulting coupling constants. The model predicts the mass of the neutral $\rho^0$-meson to be about $1\,MeV$ larger than the mass of the charged mesons $\rho^{\pm}$. The vector $\omega$-meson, which is a sterile particle with respect to the considered gauge group $SU_I(2)\times U_Y(1)$, can be added to the scheme by means of a gauge-invariant operator of dimension 5, as shown in Appendix ~A.
Neural Conversation Models and How to Rein Them in: A Survey of Failures and Fixes

Recent conditional language models are able to continue any kind of text source in an often seemingly fluent way. This fact encouraged research in the area of open-domain conversational systems that are based on powerful language models and aim to imitate an interlocutor by generating appropriate contributions to a written dialogue. From a linguistic perspective, however, the complexity of contributing to a conversation is high. In this survey, we interpret Grice's maxims of cooperative conversation from the perspective of this specific research area and systematize the literature under the aspect of what makes a contribution appropriate: A neural conversation model has to be fluent, informative, consistent, coherent, and follow social norms. In order to ensure these qualities, recent approaches try to tame the underlying language models at various intervention points, such as data, training regime or decoding. Sorted by these categories and intervention points, we discuss promising attempts and suggest novel ways for future research.
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation

Recent research has shown that the integration of Reinforcement Learning (RL) with Moving Target Defense (MTD) can enhance cybersecurity in Internet-of-Things (IoT) devices. Nevertheless, the practicality of existing work is hindered by data privacy concerns associated with centralized data processing in RL, and the unsatisfactory time needed to learn right MTD techniques that are effective against a rising number of heterogeneous zero-day attacks. Thus, this work presents CyberForce, a framework that combines Federated and Reinforcement Learning (FRL) to collaboratively and privately learn suitable MTD techniques for mitigating zero-day attacks. CyberForce integrates device fingerprinting and anomaly detection to reward or penalize MTD mechanisms chosen by an FRL-based agent. The framework has been deployed and evaluated in a scenario consisting of ten physical devices of a real IoT platform affected by heterogeneous malware samples. A pool of experiments has demonstrated that CyberForce learns the MTD technique mitigating each attack faster than existing RL-based centralized approaches. In addition, when various devices are exposed to different attacks, CyberForce benefits from knowledge transfer, leading to enhanced performance and reduced learning time in comparison to recent works. Finally, different aggregation algorithms used during the agent learning process provide CyberForce with notable robustness to malicious attacks.
Can G4-like composite
 Ab Initio
 methods accurately predict vibrational harmonic frequencies?

Minimally empirical G4-like composite wavefunction theories [E. Semidalas and J. M. L. Martin, \textit{J. Chem. Theory Comput. } {\bf 16}, 4238-4255 and 7507-7524 (2020)] trained against the large and chemically diverse GMTKN55 benchmark suite have demonstrated both accuracy and cost-effectiveness in predicting thermochemistry, barrier heights, and noncovalent interaction energies. Here, we assess the spectroscopic accuracy of top-performing methods: G4-\textit{n}, cc-G4-\textit{n}, and G4-\textit{n}-F12, and validate them against explicitly correlated coupled cluster CCSD(T*)(F12*) harmonic vibrational frequencies and experimental data from the HFREQ2014 dataset, of small first- and second-row polyatomics. G4-T is three times more accurate than plain CCSD(T)/def2-TZVP, while G4-T$_{\rm ano}$ is two times superior to CCSD(T)/ano-pVTZ. Combining CCSD(T)/ano-pVTZ with MP2-F12 in a parameter-free composite scheme results to a root-mean-square deviation of ~5 cm$^{-1}$ relative to experiment, comparable to CCSD(T) at the complete basis set limit. Application to the harmonic frequencies of benzene reveals a significant advantage of composites with ANO basis sets -- MP2/ano-pV\textit{m}Z and [CCSD(T)-MP2]/ano-pVTZ (\textit{m} = Q or 5) -- over similar protocols based on CCSD(T)/def2-TZVP. Overall, G4-type composite energy schemes, particularly when combined with ANO basis sets in CCSD(T), are accurate and comparatively inexpensive tools for computational vibrational spectroscopy.
Comparing Width Parameters on Graph Classes

We study how the relationship between non-equivalent width parameters changes once we restrict to some special graph class. As width parameters, we consider treewidth, clique-width, twin-width, mim-width, sim-width and tree-independence number, whereas as graph classes we consider $K_{t,t}$-subgraph-free graphs, line graphs and their common superclass, for $t \geq 3$, of $K_{t,t}$-free graphs. We first provide a complete comparison when restricted to $K_{t,t}$-subgraph-free graphs, showing in particular that treewidth, clique-width, mim-width, sim-width and tree-independence number are all equivalent. This extends a result of Gurski and Wanke (2000) stating that treewidth and clique-width are equivalent for the class of $K_{t,t}$-subgraph-free graphs. Next, we provide a complete comparison when restricted to line graphs, showing in particular that, on any class of line graphs, clique-width, mim-width, sim-width and tree-independence number are all equivalent, and bounded if and only if the class of root graphs has bounded treewidth. This extends a result of Gurski and Wanke (2007) stating that a class of graphs ${\cal G}$ has bounded treewidth if and only if the class of line graphs of graphs in ${\cal G}$ has bounded clique-width. We then provide an almost-complete comparison for $K_{t,t}$-free graphs, leaving one missing case. Our main result is that $K_{t,t}$-free graphs of bounded mim-width have bounded tree-independence number. This result has structural and algorithmic consequences. In particular, it proves a special case of a conjecture of Dallard, Milani\v{c} and \v{S}torgel. Finally, we consider the question of whether boundedness of a certain width parameter is preserved under graph powers. We show that the question has a positive answer for sim-width precisely in the case of odd powers.
Experts Weights Averaging: A New General Training Scheme for Vision Transformers

Structural re-parameterization is a general training scheme for Convolutional Neural Networks (CNNs), which achieves performance improvement without increasing inference cost. As Vision Transformers (ViTs) are gradually surpassing CNNs in various visual tasks, one may question: if a training scheme specifically for ViTs exists that can also achieve performance improvement without increasing inference cost? Recently, Mixture-of-Experts (MoE) has attracted increasing attention, as it can efficiently scale up the capacity of Transformers at a fixed cost through sparsely activated experts. Considering that MoE can also be viewed as a multi-branch structure, can we utilize MoE to implement a ViT training scheme similar to structural re-parameterization? In this paper, we affirmatively answer these questions, with a new general training strategy for ViTs. Specifically, we decouple the training and inference phases of ViTs. During training, we replace some Feed-Forward Networks (FFNs) of the ViT with specially designed, more efficient MoEs that assign tokens to experts by random uniform partition, and perform Experts Weights Averaging (EWA) on these MoEs at the end of each iteration. After training, we convert each MoE into an FFN by averaging the experts, transforming the model back into original ViT for inference. We further provide a theoretical analysis to show why and how it works. Comprehensive experiments across various 2D and 3D visual tasks, ViT architectures, and datasets validate the effectiveness and generalizability of the proposed training scheme. Besides, our training scheme can also be applied to improve performance when fine-tuning ViTs. Lastly, but equally important, the proposed EWA technique can significantly improve the effectiveness of naive MoE in various 2D visual small datasets and 3D visual tasks.
Finding Long Directed Cycles Is Hard Even When DFVS Is Small Or Girth Is Large

We study the parameterized complexity of two classic problems on directed graphs: Hamiltonian Cycle and its generalization {\sc Longest Cycle}. Since 2008, it is known that Hamiltonian Cycle is W[1]-hard when parameterized by directed treewidth [Lampis et al., ISSAC'08]. By now, the question of whether it is FPT parameterized by the directed feedback vertex set (DFVS) number has become a longstanding open problem. In particular, the DFVS number is the largest natural directed width measure studied in the literature. In this paper, we provide a negative answer to the question, showing that even for the DFVS number, the problem remains W[1]-hard. As a consequence, we also obtain that Longest Cycle is W[1]-hard on directed graphs when parameterized multiplicatively above girth, in contrast to the undirected case. This resolves an open question posed by Fomin et al. [ACM ToCT'21] and Gutin and Mnich [arXiv:2207.12278]. Our hardness results apply to the path versions of the problems as well. On the positive side, we show that Longest Path parameterized multiplicatively above girth} belongs to the class XP.
Assessing adult physical activity and compliance with 2008 CDC guidelines using a Bayesian two-part measurement error model

While there is wide agreement that physical activity is an important component of a healthy lifestyle, it is unclear how many people adhere to public health recommendations on physical activity. The Physical Activity Guidelines (PAG), published by the CDC, provides guidelines to American adults, but it is difficult to assess compliance with these guidelines. The PAG further complicates adherence assessment by recommending activity to occur in at least 10 min bouts. To better understand the measurement capabilities of various instruments to quantify activity, and to propose an approach to evaluate activity relative to the PAG, researchers at Iowa State University administered the Physical Activity Measurement Survey (PAMS) to over 1000 participants in four different Iowa counties. In this paper, we develop a two-part Bayesian measurement error model and apply it to the PAMS data in order to assess compliance with the PAG in the Iowa adult population. The model accurately accounts for the 10 min bout requirement put forth in the PAG. The measurement error model corrects biased estimates and accounts for day-to-day variation in activity. The model is also applied to the nationally representative National Health and Nutrition Examination Survey.
SNR-based beaconless multi-scan link acquisition model with vibration for LEO-to-ground laser communication

We propose a link acquisition time model deeply involving the process from the transmitted power to received signal-to-noise ratio (SNR) for LEO-to-ground laser communication for the first time. Compared with the conventional acquisition models founded on geometry analysis with divergence angle threshold, utilizing SNR as the decision criterion is more appropriate for practical engineering requirements. Specially, under the combined effects of platform vibration and turbulence, we decouple the parameters of beam divergence angle, spiral pitch, and coverage factor at a fixed transmitted power for a given average received SNR threshold. Then the single-scan acquisition probability is obtained by integrating the field of uncertainty (FOU), probability distribution of coverage factor, and receiver field angle. Consequently, the closed-form analytical expression of acquisition time expectation adopting multi-scan, which ensures acquisition success, with essential reset time between single-scan is derived. The optimizations concerning the beam divergence angle, spiral pitch, and FOU are presented. Moreover, the influence of platform vibration is investigated. All the analytical derivations are confirmed by Monte Carlo simulations. Notably, we provide a theoretical method for designing the minimum divergence angle modulated by the laser, which not only improves the acquisition performance within a certain vibration range, but also achieves a good trade-off with the system complexity.
Gain-compensated metal cavity modes and a million-fold improvement of Purcell factors

Using a rigorous mode theory for gain-compensated plasmonic dimers, we demonstrate how quality factors and Purcell factors can be dramatically increased, improving the quality factors from 10 to over 26,000 and the peak Purcell factors from around 3000 to over 10 billion. Full three-dimensional calculations are presented for gold dimers in a finite-size gain medium, which allows one to easily surpass fundamental Purcell factor limits of lossy media. Within a regime of linear system response, we show how the Purcell factors are modified from the contributions from the projected local density of states as well as a non-local gain. Further, we show that the effective mode volume and radiative beta factors remain relatively constant, despite the significant enhancement of the Purcell factors.