Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Directionality, Heterogeneity, and Correlations in Epidemic Risk and Spread

Most models of epidemic spread, including many designed specifically for COVID-19, implicitly assume mass-action contact patterns and undirected contact networks, meaning that the individuals most likely to spread the disease are also the most at risk to receive it from others. Here, we review results from the theory of random directed graphs which show that many important quantities, including the reproduction number and the epidemic size, depend sensitively on the joint distribution of in- and out-degrees ("risk" and "spread"), including their heterogeneity and the correlation between them. By considering joint distributions of various kinds, we elucidate why some types of heterogeneity cause a deviation from the standard Kermack-McKendrick analysis of SIR models, i.e., so-called mass-action models where contacts are homogeneous and random, and some do not. We also show that some structured SIR models informed by realistic complex contact patterns among types of individuals (age or activity) are simply mixtures of Poisson processes and tend not to deviate significantly from the simplest mass-action model. Finally, we point out some possible policy implications of this directed structure, both for contact tracing strategy and for interventions designed to prevent superspreading events. In particular, directed graphs have a forward and backward version of the classic "friendship paradox" -- forward edges tend to lead to individuals with high risk, while backward edges lead to individuals with high spread -- such that a combination of both forward and backward contact tracing is necessary to find superspreading events and prevent future cascades of infection.
Structure and innervation of the swim bladder musculature in the weakfish, Cynoscion regalis (Teleostei: Sciaenidae)

The striated swim bladder muscles of the weakfish Cynoscion regalis are deep red in color but cannot be classified histologically as having typical red fibers. The muscle fibers are homogeneous and average 29.6 ± 5.3 μm in diameter, one-fifth the diameter of the adjacent hypaxialis fibers. Each muscle fiber contains thin, ribbonlike myofibrils which are radially arranged around a central core of mitochondria, glycogen, and sarcoplasmic reticulum. Myofibrils are extremely regular in pattern. Triads occur at the Z line. Numerous mitochondria and muscle nuclei are located at the periphery of each muscle fiber. The muscle fibers are multiply innervated with motor endplates distributed along their entire lengths. Well-developed folding of the postsynaptic membrane, not previously reported in fishes, is present at the motor endplate.
Unsupervised Domain Adaptation in Semantic Segmentation: a Review

The aim of this paper is to give an overview of the recent advancements in the Unsupervised Domain Adaptation (UDA) of deep networks for semantic segmentation. This task is attracting a wide interest since semantic segmentation models require a huge amount of labeled data and the lack of data fitting specific requirements is the main limitation in the deployment of these techniques. This field has been recently explored and has rapidly grown with a large number of ad-hoc approaches. This motivates us to build a comprehensive overview of the proposed methodologies and to provide a clear categorization. In this paper, we start by introducing the problem, its formulation and the various scenarios that can be considered. Then, we introduce the different levels at which adaptation strategies may be applied: namely, at the input (image) level, at the internal features representation and at the output level. Furthermore, we present a detailed overview of the literature in the field, dividing previous methods based on the following (non mutually exclusive) categories: adversarial learning, generative-based, analysis of the classifier discrepancies, self-teaching, entropy minimization, curriculum learning and multi-task learning. Novel research directions are also briefly introduced to give a hint of interesting open problems in the field. Finally, a comparison of the performance of the various methods in the widely used autonomous driving scenario is presented.
Scanner data in inflation measurement: From raw data to price indices

Scanner data offer new opportunities for CPI or HICP calculation. They can be obtained from a wide variety of retailers (supermarkets, home electronics, Internet shops, etc.) and provide information at the level of the barcode. One of advantages of using scanner data is the fact that they contain complete transaction information, i.e. prices and quantities for every sold item. After clearing data and unifying product names, products should be carefully classified (e.g. into COICOP 5 or below), matched, filtered and aggregated. One of new challenges connected with scanner data is the appropriate choice of the index formula. In this article we present a proposal for the implementation of individual stages of handling scanner data. We also point out potential problems during scanner data processing and their solutions. We compare a large number of price index methods based on real scanner data sets and we verify their sensitivity on adopted data filtering and aggregating methods. One of the aims is also to compare calculations of multilateral indices in terms of how time-consuming they are. Finally, the paper investigates distances between these indices and the theoretical, expected value of the price share when prices are log-normally distributed. It is a new approach to providing an additional criterion in the price index selection.
Model Evidence with Fast Tree Based Quadrature

High dimensional integration is essential to many areas of science, ranging from particle physics to Bayesian inference. Approximating these integrals is hard, due in part to the difficulty of locating and sampling from regions of the integration domain that make significant contributions to the overall integral. Here, we present a new algorithm called Tree Quadrature (TQ) that separates this sampling problem from the problem of using those samples to produce an approximation of the integral. TQ places no qualifications on how the samples provided to it are obtained, allowing it to use state-of-the-art sampling algorithms that are largely ignored by existing integration algorithms. Given a set of samples, TQ constructs a surrogate model of the integrand in the form of a regression tree, with a structure optimised to maximise integral precision. The tree divides the integration domain into smaller containers, which are individually integrated and aggregated to estimate the overall integral. Any method can be used to integrate each individual container, so existing integration methods, like Bayesian Monte Carlo, can be combined with TQ to boost their performance. On a set of benchmark problems, we show that TQ provides accurate approximations to integrals in up to 15 dimensions; and in dimensions 4 and above, it outperforms simple Monte Carlo and the popular Vegas method.
T-RECS: a Transformer-based Recommender Generating Textual Explanations and Integrating Unsupervised Language-based Critiquing

Supporting recommendations with personalized and relevant explanations increases trust and perceived quality, and helps users make better decisions. Prior work attempted to generate a synthetic review or review segment as an explanation, but they were not judged convincing in evaluations by human users. We propose T-RECS, a multi-task learning Transformer-based model that jointly performs recommendation with textual explanations using a novel multi-aspect masking technique. We show that human users significantly prefer the justifications generated by T-RECS than those generated by state-of-the-art techniques. At the same time, experiments on two datasets show that T-RECS slightly improves on the recommendation performance of strong state-of-the-art baselines. Another feature of T-RECS is that it allows users to react to a recommendation by critiquing the textual explanation. The system updates its user model and the resulting recommendations according to the critique. This is based on a novel unsupervised critiquing method for single- and multi-step critiquing with textual explanations. Experiments on two real-world datasets show that T-RECS is the first to obtain good performance in adapting to the preferences expressed in multi-step critiquing.
Global Strong Solution for Cauchy Problem of a Diffusion interface model in 1-D

In this paper, we study the Cauchy problem for a diffusion interface model of compressible immiscible two-phase flow, which is described by Navier-Stokes/Allen-Cahn system. The global existence and uniqueness of strong solutions for compressible non-isentropic Navier-Stokes/Allen-Cahn system is established in 1-D. This result suggest that no phase transition, no vacuum, mass or heat concentration will be developed in finite time.
Production and purification of an extracellular β-galactosidase from the Dutch elm disease fungus Ophiostoma novo-ulmi

The causal agents of Dutch elm disease, Ophiostoma ulmi (isolate H200) and Ophiostoma novo-ulmi (isolate CKT-11), secreted similar amounts of β-galactosidase in liquid shake cultures when grown on galacturonic acid or sodium pectate (1.45 ± 0.16 and 1.03 ± 0.24 nkat∙mL−1 for O. ulmi, respectively, and 1.30 ± 0.08 and 1.28 ± 0.26 nkat∙mL−1 for O. novo-ulmi, respectively). Rhamnose and pectin also stimulated secretion but to a lesser extent, whereas on glucose, enzyme activity was barely detectable (≤0.01 nkat∙mL−1). Ophiostoma novo-ulmi was shown by Q-Sepharose chromatography to form two β-galactosidases, named β-galactosidases I and II. In cultures grown on galacturonic acid β-galactosidase I accounted for approximately 75% of the total activity in the culture filtrate. β-Galactosidase I was further purified to apparent electrophoretic homogeneity by means of Sephacryl gel filtration chromatography, chromatofocusing, and Superdex75 gel filtration. The molecular mass of the enzyme was 135 kDa by SDS–PAGE a.
Magnetar outburst and spin-down glitch

The outburst and spin-down glitch of magnetars are modeled from the magnetospheric point of view. We try to discuss the following four questions: (1) Which pulsar on the period and peirod-derivative diagram are more likely to show magnetar outburst? (2) Which outburst will make the glitch that triggered the outburst to become a spin-down glitch? (3) Can we model the outburst and spin-down glitch in PSR J1119$-$6127 simultaneously? (4) Why the torque variation is delayed compared with the peak of the X-ray luminosity in 1E 1048.1$-$5937 and PSR J1119$-$6127? It is found that both the global and local twisted magnetic field will affect the radiation and timing behaviors of magnetars. Especially, the delay of torque variations may due to the combined effect of increasing twist in the j-bundle and untwisting of the global magnetosphere. A toy model is build for magnetar outburst and torque variations. It can catch the general trend of magnetar outburst: decaying flux, shrinking hot spot, and torque variations.
Comparison of survival and growth in germlings of six fucoid species (Fucales, Phaeophyceae) at two different temperature and nutrient levels

During their initial post‐settlement period, fucoid germlings will be exposed to large variations in environmental factors such as temperature and nutrient concentration, which may influence survival and growth. Factorially designed culture experiments were used to compare the effects of temperature and nutrient concentration on the survival and growth of germlings in six fucoid species from the Norwegian Skagerrak coast. In four of the species (Ascophyllum nodosum, Fucus evanescens, F. serratus, and F. vesiculosus), survival did not differ between the two temperatures tested (7 and 17°C), whereas survival was reduced at 7°C in F. spiralis and Sargassum muticum. The effect of nutrient enrichment (seawater enriched with 32 μmol N and 2 μmol P per litre) on germling growth depended on the temperature regime, and differed little between species. The relative growth rate of germlings increased with increasing temperature in all six species and was higher in S. muticum (∼0.21 day ) than in the other fucoids (0.09–0.14 day ) at 17°C. At 7°C, F. serratus germlings had the highest relative growth rate (∼0.13 day ), whereas those of S. muticum and F. spiralis were reduced to ∼0.05 and ∼0.03 day , respectively. These results are in accordance with the reproductive season for the species, as germlings of the summer/autumn reproducers, F. spiralis and S. muticum, were less tolerant to low temperatures than the other Skagerrak fucoids whose reproduction occurs earlier in the year. Egg volume varied almost 10‐fold across species, from F. vesiculosus (smallest) to S. muticum (largest), and showed no correlation with relative growth rates or survival, wherease the size of germlings was positively related to egg volume after 15 days of cultivation under nutrient‐enriched conditions at 17°C. These results suggest that summer reproduction, larger eggs and a higher growth rate of germlings may give the introduced species, S. muticum, a competitive advantage.
Epidemiological monitoring and control perspectives: application of a parsimonious modelling framework to the COVID-19 dynamics in France

SARS-Cov-2 virus has spread over the world creating one of the fastest pandemics ever. The absence of immunity, asymptomatic transmission, and the relatively high level of virulence of the COVID-19 infection it causes led to a massive flow of patients in intensive care units (ICU). This unprecedented situation calls for rapid and accurate mathematical models to best inform public health policies. We develop an original parsimonious model that accounts for the effect of the age of infection on the natural history of the disease. Analysing the ongoing COVID-19 in France, we estimate the value of the key epidemiological parameters, such as the basic reproduction number (R0), and the efficiency of the national control strategy. We then use our deterministic model to explore several scenarios posterior to lock-down lifting and compare the efficiency of non pharmaceutical interventions (NPI) described in the literature.
Repurposing Ellipticine Hydrochloride to Combat Colistin-Resistant Extraintestinal Pathogenic E. coli (ExPEC)

Extraintestinal pathogenic Escherichia coli (ExPEC) strains are the cause of a majority of human extraintestinal infections globally, resulting in enormous direct economic and medical costs. The plasmid-mediated, colistin-resistant gene mcr-1 has broken through the ultimate defense line against MDR Gram-negative pathogens. There is an urgent need to discover the new compound intended for colistin-resistant E. coli. In this study, antibacterial targets of ellipticine hydrochloride (EH) were confirmed by localized surface plasmon resonance (LSPR) and decatenation assay. The LSPR analysis exhibited good binding between EH and E. coli topoisomerase IV. In this study, a synergistic effect is obvious in the combination of EH and colistin, to which eight of ten strains showed synergy, while two isolates (20%) showed no difference. The bacteria enumeration analysis of EH treatment group suggested that the decreased bacterial titer can be observed in various tissues of infected mice. EH treatment significantly decreased the levels of a variety of pro-inflammatory factors, such as TNF-α and IL-6. Moreover, other related lesions, such as inflammatory cell infiltration, alveolar interstitial congestion, and edema were observed to be relieved to different extents. This study reveals the anti-E. coli potential activities and molecular mechanism of EH and the therapeutical effectiveness of EH application to animals. It provides us with a new option for fighting against multidrug-resistant ExPEC infections in the future.
A revised medium for rapid growth and bio assays with tobacco tissue cultures

48 Metabolic fluctuations in chloroplasts and mitochondria can trigger retrograde signals 49 to modify nuclear gene expression. Mobile signals likely to be involved are reactive oxygen 50 species (ROS), which can operate protein redox switches by oxidation of specific cysteine 51 residues. Redox buffers such as the highly reduced glutathione pool serve as reservoirs of 52 reducing power for several ROS scavenging and ROS-induced damage repair pathways. 53 Formation of glutathione disulfide (GSSG) and a shift of the glutathione redox potential 54 ( E GSH ) towards less negative values is considered a hallmark of several stress conditions. 55 Here we used the herbicide methyl viologen (MV) to generate ROS locally in chloroplasts of 56 intact Arabidopsis seedlings and recorded dynamic changes in E GSH and H 2 O 2 levels with the 57 genetically-encoded biosensors Grx1-roGFP2 (for E GSH ) and roGFP2-Orp1 (for H 2 O 2 ) 58 targeted to chloroplasts, the cytosol or mitochondria. Treatment of seedlings with MV caused 59 a rapid oxidation in chloroplasts and subsequently also in the cytosol and mitochondria. The 60 MV-induced oxidation was significantly boosted by illumination with actinic light and 61 largely abolished by inhibitors of photosynthetic electron transport. In addition, MV also 62 induced an autonomous oxidation in the mitochondrial matrix in an electron transport chain 63 activity-dependent manner that was milder than the oxidation triggered in chloroplasts by the 64 combination of MV and light. In vivo redox biosensing resolves the spatiotemporal dynamics 65 of compartmental responses to local ROS generation and provide a basis for understanding how compartment-specific redox dynamics may operate in retrograde signaling and stress 67 acclimation in plants.
Expression of Three Related to ABI3/VP1 Genes in Medicago truncatula Caused Increased Stress Resistance and Branch Increase in Arabidopsis thaliana

Related to ABSCISIC ACID INSENSITIVE3 (ABI3)/VIVIPAROUS1(VP1)(RAV) transcription factors, which encode a B3 domain and an APETALA2(AP2) domain, belong to the APETALA2/ethylene-responsive element binding factor(AP2/ERF) or B3 superfamily and play an important role in regulating plant growth and development and responding to abiotic stress. Although there have been many functional studies on RAV, the functional differences between RAVs are not clear. Therefore, in this study, the functional differences of RAVs of Medicago truncatula were analyzed. Based on sequence data from the plant transcription factor database and the M. truncatula genome database, we cloned three RAV genes from M. truncatula, named MtRAV1, MtRAV2, and MtRAV3. The cis-acting elements of these genes promoters were predicted, and the expression patterns of MtRAVs under exogenous conditions (4°C, NaCl, Polyethylene Glycol, Abscisic acid) were analyzed. MtRAVs transgenic Arabidopsis thaliana were obtained and subjected to adversity treatment. Subcellular localization results indicated that MtRAVs were located in the nucleus. A much lower expression level was observed for MtRAV3 than the levels of MtRAV1 and MtRAV2 in M. truncatula for growth in normal conditions, but under 4°C or PEG and NaCl treatment, the expression level of MtRAV3 was significantly increased. Only the MtRAV3 overexpression transgenic plants showed strong cold resistance, but the overexpressed MtRAV1 and MtRAV2 transgenic plants showed no difference from wild type plants. MtRAV transgenic plants exhibited similar response to exogenous mannitol, NaCl, and ABA, and the expression of some adverse-related marker genes were up-regulated, such as COLD REGULATED 414 THYLAKOID MEMBRANE 1 (COR414-TM1), Arabidopsis thaliana drought-induced 21 (AtDI21), and Arabidopsis thaliana phosphatidylinositol-specific phospholipase C (ATPLC). MtRAVs transgenic Arabidopsis thaliana exhibited increasing of branch number. These results indicated that there was some function redundancy during MtRAVs proteins of M. truncatula, and MtRAV3 has increased function compared to the other two genes. The results of this study should provide the foundation for future application of MtRAVs in legumes.
Personalization of electro-mechanical models of the pressure-overloaded left ventricle: fitting of Windkessel-type afterload models

Computer models of left ventricular (LV) electro-mechanics (EM) show promise as a tool for assessing the impact of increased afterload upon LV performance. However, the identification of unique afterload model parameters and the personalization of EM LV models remains challenging due to significant clinical input uncertainties. Here, we personalized a virtual cohort of N = 17 EM LV models under pressure overload conditions. A global–local optimizer was developed to uniquely identify parameters of a three-element Windkessel (Wk3) afterload model. The sensitivity of Wk3 parameters to input uncertainty and of the EM LV model to Wk3 parameter uncertainty was analysed. The optimizer uniquely identified Wk3 parameters, and outputs of the personalized EM LV models showed close agreement with clinical data in all cases. Sensitivity analysis revealed a strong dependence of Wk3 parameters on input uncertainty. However, this had limited impact on outputs of EM LV models. A unique identification of Wk3 parameters from clinical data appears feasible, but it is sensitive to input uncertainty, thus depending on accurate invasive measurements. By contrast, the EM LV model outputs were less sensitive, with errors of less than 8.14% for input data errors of 10%, which is within the bounds of clinical data uncertainty. This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.
Coupling Between Carbon and Nitrogen Metabolic Processes Mediated by Coastal Microbes in Synechococcus-Derived Organic Matter Addition Incubations

Phytoplankton are major contributors to labile organic matter in the upper ocean. Diverse heterotrophic bacteria successively metabolize these labile compounds and drive elemental biogeochemical cycling. We investigated the bioavailability of Synechococcus-derived organic matter (SOM) by estuarine and coastal microbes during 180-day dark incubations. Variations in organic carbon, inorganic nutrients, fluorescent dissolved organic matter (FDOM), and total/active microbial communities were monitored. The entire incubations could be partitioned into three phases (labeled I, II, and III) based on the total organic carbon (TOC) consumption rates of 6.38–7.01, 0.53–0.64, and 0.10–0.13 μmol C L–1 day–1, respectively. This corresponded with accumulation processes of NH4+, NO2–, and NO3–, respectively. One tryptophan-like (C1) and three humic-like (C2, C3, and C4) FDOM components were identified. The intensity variation of C1 followed bacterial growth activities, and C2, C3, and C4 displayed labile, semi-labile, and refractory DOM characteristics, respectively. Alphaproteobacteria, Gammaproteobacteria, Bacteroidetes, and Actinobacteria dominated the quickly consumed process of SOM (phase I) coupled with a substantial amount of NH4+ generation. Thaumarchaeota became an abundant population with the highest activities in phase II, especially in the free-living size-fraction, and these organisms could perform chemoautotroph processes through the ammonia oxidation. Microbial populations frequently found in the dark ocean, even the deep sea, became abundant during phase III, in which Nitrospinae/Nitrospirae obtained energy through nitrite oxidation. Our results shed light on the transformation of different biological availability of organic carbon by coastal microorganisms which coupled with the regeneration of different form of inorganic nitrogen.