Miracle-dz/UniFAR-FTUs huggingface dataset:
Duck traps: two-dimensional critical manifolds in planar systems

ABSTRACT In this work we consider two-dimensional critical manifolds in planar fast-slow systems near fold and so-called canard (‘duck’) points. These higher-dimension, and lower-codimension, situation is directly motivated by the case of hysteresis operators limiting onto fast-slow systems as well as by systems with constraints. We use geometric desingularization via blow-up to investigate two situations for the slow flow: generic fold (or jump) points, and canards in one-parameter families. We directly prove that the fold case is analogous to the classical fold involving a one-dimensional critical manifold. However, for the canard case, considerable differences and difficulties appear. Orbits can get trapped in the two-dimensional manifold after a canard-like passage thereby preventing small-amplitude oscillations generated by the singular Hopf bifurcation occurring in the classical canard case, as well as certain jump escapes.
Adaptability and stability of sweet sorghum cultivars

The objective of this study was to evaluate the phenotypic stability and adaptability of 25 sweet sorghum cultivars of Embrapa Maize and Sorghum. The experiments were conducted in five Brazilian environments, three in the state of Minas Gerais, and the others in Sinop, Mato Grosso and Pelotas, Rio Grande do Sul. Fresh biomass yield (FBY), and total soluble solids (TSS) of the juice were evaluated in a randomized complete block design with three replications. Analysis of variance showed significant genotype by environment interaction for both traits. According to the Annicchiarico methodology analysis, genotypes CMSXS634, BRS506, and CMSXS646 were the most stable and adapted for FBY and TSS concomitantly; CMSXS634 being more adapted to favorable environments and CMSXS646 being more adapted to unfavorable environments.
Pathogenic immune response to therapeutic factor VIII: exacerbated response or failed induction of tolerance?

Therapeutic factor VIII is highly immunogenic. Despite intensive research in the last decades, the reasons why 5-30% of patients with hemophilia A (of all severities) develop inhibitory anti-factor VIII antibodies (inhibitors) following replacement therapy remain an enigma. Under physiological conditions, endogenous factor VIII is recognized by the immune system. Likewise, numerous observations indicate that, in hemophilia A patients without inhibitors, exogenous therapeutic factor VIII is immunologically assessed and tolerated. A large part of the research on the immunogenicity of therapeutic factor VIII is attempting to identify the ‘danger signals’ that act as adjuvants to the deleterious anti-factor VIII immune responses. However, several of the inflammatory assaults concomitant to factor VIII administration initially hypothesized as potential sources of danger signals (e.g., bleeding, infection, and vaccination) have been disproved to be such signals. Conversely, recent evidence suggests that cells from inhibitor-negative patients are able to activate anti-inflammatory and tolerogenic mechanisms required to suppress deleterious immune responses, while cells from inhibitor-positive patients are not. Based on the available observations, we propose a model in which all hemophilia A patients develop anti-factor VIII immune responses during replacement therapy irrespective of associated danger signals. We further postulate that the onset of clinically relevant factor VIII inhibitors results from an inability to develop counteractive tolerogenic responses to exogenous factor VIII rather than from an exacerbated activation of the immune system at the time of factor VIII administration. A better understanding of the pathogenesis of neutralizing anti-factor VIII antibodies will have repercussions on the clinical management of patients and highlight new strategies to achieve active immune tolerance to therapeutic factor VIII.
Development of Somatic Complaints Among Adolescents and Young Adults in Switzerland

Abstract In this study we explored the development of somatic complaints among adolescents and young adults aged 16 to 30 years in Switzerland. Using data from the Transitions from Education to Employment (TREE) study, we applied a hidden Markovian model with covariates to cluster trajectories representing the sum of eight somatic complaints. The resulting groups differed mainly in terms of gender, reading literacy, and substance use. The trajectories of somatic complaints were also related to the number of critical events experienced by the respondents.
Transcription factor motif quality assessment requires systematic comparative analysis

Transcription factor (TF) binding site prediction remains a challenge in gene regulatory research due to degeneracy and potential variability in binding sites in the genome. Dozens of algorithms designed to learn binding models (motifs) have generated many motifs available in research papers with a subset making it to databases like JASPAR, UniPROBE and Transfac. The presence of many versions of motifs from the various databases for a single TF and the lack of a standardized assessment technique makes it difficult for biologists to make an appropriate choice of binding model and for algorithm developers to benchmark, test and improve on their models. In this study, we review and evaluate the approaches in use, highlight differences and demonstrate the difficulty of defining a standardized motif assessment approach. We review scoring functions, motif length, test data and the type of performance metrics used in prior studies as some of the factors that influence the outcome of a motif assessment. We show that the scoring functions and statistics used in motif assessment influence ranking of motifs in a TF-specific manner. We also show that TF binding specificity can vary by source of genomic binding data. We also demonstrate that information content of a motif is not in isolation a measure of motif quality but is influenced by TF binding behaviour. We conclude that there is a need for an easy-to-use tool that presents all available evidence for a comparative analysis.
Simulation of a persistent medium-term precipitation event over the western Iberian Peninsula

This study evaluated the performance of the WRF- ARW (Weather Research and Forecasting with Advanced Research) weather prediction model in simulating the spa- tial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed during the rainy season and, more specifically, the month of December 2009. In this period, the region of interest was under the influence of a sequen- tial passage of low-pressure systems associated with frontal surfaces. These synoptic weather patterns were responsi- ble for long periods of rainfall, resulting in a high monthly precipitation. The WRF model results during the study period were fur- thermore evaluated with the specific objective to complement gaps in the precipitation recordings of a reference meteoro- logical station (located in Pousadas), the data of which are fundamental for hydrological studies in nearby experimental catchments. Three distinct WRF model runs were forced with ini- tial fields and boundary conditions obtained from a global domain model: (1) a reference experiment with no nudg- ing (RunRef); (2) observational nudging for a specific lo- cation, i.e. the above-mentioned Pousadas reference station (RunObsN); and (3) nudging to the analysed field (Run- GridN). Model performance was evaluated, using several statistical parameters, against a dataset of 27 rainfall sta- tions that were grouped by elevation. The three model runs had similar performances, even though RunGridN resulted in a slight improvement. Regarding the other two experi- ments, this improvement justifies its use for complementing the surface measurements at the Pousadas reference station. Overall model accuracy, expressed in root mean square error (RMSE), of the three runs was comparable for the stations of the different elevations classes. Even so, it was slightly better for stations in the lowlands than the highlands. Fur- thermore, model predictions tended to be less accurate for stations located in rough terrain and deep valleys.
The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery

We explore the application of super-resolution techniques to satellite imagery, and the effects of these techniques on object detection algorithm performance. Specifically, we enhance satellite imagery beyond its native resolution, and test if we can identify various types of vehicles, planes, and boats with greater accuracy than native resolution. Using the Very Deep Super-Resolution (VDSR) framework and a custom Random Forest Super-Resolution (RFSR) framework we generate enhancement levels of 2x, 4x, and 8x over five distinct resolutions ranging from 30 cm to 4.8 meters. Using both native and super-resolved data, we then train several custom detection models using the SIMRDWN object detection framework. SIMRDWN combines a number of popular object detection algorithms (e.g. SSD, YOLO) into a unified framework that is designed to rapidly detect objects in large satellite images. This approach allows us to quantify the effects of super-resolution techniques on object detection performance across multiple classes and resolutions. We also quantify the performance of object detection as a function of native resolution and object pixel size. For our test set we note that performance degrades from mean average precision (mAP) = 0.53 at 30 cm resolution, down to mAP = 0.11 at 4.8 m resolution. Super-resolving native 30 cm imagery to 15 cm yields the greatest benefit; a 13-36% improvement in mAP. Super-resolution is less beneficial at coarser resolutions, though still provides a small improvement in performance.
Initial phases of massive star formation in high infrared extinction clouds - I. Physical parameters

Aims. The earliest phases of massive star formation are found in cold and dense infrared dark clouds (IRDCs). Since the detection method of IRDCs is very sensitive to the local properties of the background emission, we present here an alternative method to search for high column density in the Galactic plane by using infrared extinction maps. Using this method we find clouds between 1 and 5 kpc, of which many were missed by previous surveys. By studying the physical conditions of a subsample of these clouds, we aim at a better understanding of the initial conditions of massive star formation. Methods. We have made extinction maps of the Galactic plane based on the 3.6−4.5 μm color excess between the two shortest wavelength Spitzer IRAC bands, reaching to visual extinctions of ∼100 mag and column densities of 9 × 10 22 cm −2 . F rom this we compiled a new sample of cold and compact high extinction clouds. We used the MAMBO array at the IRAM 30 m telescope to study the morphology, masses and densities of the clouds and the dense clumps within them. The latter were followed up by pointed ammonia observations with the 100 m Effelsberg telescope, to determine rotational temperatures and kinematic distances. Results. Extinction maps of the Galactic plane trace large scale structures such as the spiral arms. The extinction method probes lower column densities, NH2 ∼ 4 × 10 22 cm −2 , than the 1.2 mm continuum, which reaches up to NH2 ∼ 3 × 10 23 cm −2 but is less sensitive to large scale structures. The 1.2 mm emission maps reveal that the high extinction clouds contain extended cold dust emission, from filamentary structures to still diffuse clouds. Most of the clouds are dark in 24 μm, but several show already signs of star formation via maser emission or bright infrared sources, suggesting that the high extinction clouds contain a variety of evolutionary stages. The observations suggest an evolutionary scheme from dark, cold and diffuse clouds, to clouds with a stronger 1.2 mm peak and to finally clouds with many strong 1.2 mm peaks, which are also warmer, more turbulent and already have some star formation signposts.
Study on free amino acid concentrations in umbilical cord blood plasma of newborns from normoglycaemic and gestational diabetes-complicated pregnancies

Introduction and objective. Gestational diabetes mellitus is a common disease among pregnant women. The aim of the study was to compare plasma concentrations of 24 amino acids in umbilical cord blood in newborns from normoglycaemic pregnancies versus those complicated by gestational diabetes. The relationship between birth weight and length of newborns and placental concentrations of individual amino acids were also assessed. Material and methods. The study comprised 76 pregnant women at the gestational age of 37 weeks and more. The control group consisted of 31 women whose 75-g glucose load test excluded gestational diabetes mellitus. The study group encompassed 45 women with diagnosed gestational diabetes mellitus. The placental plasma concentrations of 24 amino acids were determined using ion-exchange chromatography with an automated amino acid analyser. Results. The concentrations of cysteic acid, aspartic acid, threonine, glutamic acid, cystine, and alpha-aminobutyric acid in umbilical cord blood plasma were higher in the group complicated by gestational diabetes compared to normoglycemic pregnancies; otherwise, concentrations of glutamine, alanine, valine, phenylalanine, lysine and, arginine were lower in the group complicated by gestational diabetes than in the normoglycaemic group. Conclusions. The results show that despite optimal control of carbohydrate metabolism during gestational diabetes mellitus, there are many abnormalities in the amino acids metabolism. This suggests that research on the effects of amino acids concentration in umbilical cord blood on the foetal development in gestational diabetes-complicated pregnancies should be continued.
Wage-led versus profit-led demand: What have we learned? A Kalecki-Minsky view

The Bhaduri-Marglin model has become a widely used workhorse model in heterodox macroeconomics and it has given rise to a dozen or so empirical studies, which at times have given conflicting results. Neo-Kaleckians and neo-Goodwinians have applied different estimation strategies, with the former typically estimating behavioural equations, while the latter have often used reduced-form demand equations. Further differences include the lag structure, the output measure, the control variables and the sample. The paper, firstly, tries to clarify the terms of the debate. While neo-Kaleckians interpret the model as medium-term, partial-equilibrium goods market model, neo-Goodwinians are interested in the interaction of demand and distribution and regard the model as a long-run model with short-run cycles. Second, we elaborate a Kalecki-Minsky view of the economy as characterised by a wage-led demand regime and cycles driven by financial fragility. Many of the reported results may suffer from omitted variable bias as they do not include financial control variables. At least in the recent past, financial effects on demand have been much larger in size than distribution effects. A wage-led Minsky model with reserve army distribution function gives rise to pseudo-Goodwin cycles.
Essays on Stock Return Predictability: Novel Measures Based on Technology Spillover and Firm's Public Announcement

I show that technology spillovers are important information phenomena that benefit both other innovators (as emphasized in the Industrial Organization literature) and stock market investors. A growing body of literature documents that measures of R&D investment and innovation output (e.g., patents, patent citations) predict stock returns. I find that the premium associated with R&D and patenting activities is largely restricted to firms located in more isolated technology spaces with fewer spillovers. Moreover, there is a strong lead-lag effect among firms engaging in innovative activities: the stock prices of firms in more isolated technology spaces react more slowly to new information than do the stock prices of firms in more competitive technology spaces. Finally, announcement-day returns to patent grants are greater for more technologically important patents (measured by forward citations), but only for firms in more crowded technology spaces. My results indicate that investors are able to value innovative investments by exploiting the information flows associated with greater technology spillovers.
Miro proteins prime mitochondria for Parkin translocation and mitophagy

The Parkinson's disease‐associated protein kinase PINK1 and ubiquitin ligase Parkin coordinate the ubiquitination of mitochondrial proteins, which marks mitochondria for degradation. Miro1, an atypical GTPase involved in mitochondrial trafficking, is one of the substrates tagged by Parkin after mitochondrial damage. Here, we demonstrate that a small pool of Parkin interacts with Miro1 before mitochondrial damage occurs. This interaction does not require PINK1, does not involve ubiquitination of Miro1 and also does not disturb Miro1 function. However, following mitochondrial damage and PINK1 accumulation, this initial pool of Parkin becomes activated, leading to the ubiquitination and degradation of Miro1. Knockdown of Miro proteins reduces Parkin translocation to mitochondria and suppresses mitophagic removal of mitochondria. Moreover, we demonstrate that Miro1 EF‐hand domains control Miro1's ubiquitination and Parkin recruitment to damaged mitochondria, and they protect neurons from glutamate‐induced mitophagy. Together, our results suggest that Miro1 functions as a calcium‐sensitive docking site for Parkin on mitochondria.
Optimal pricing decisions for a closed-loop supply chain with retail competition under fuzziness

Abstract In this paper, we consider a pricing and remanufacturing decision problem in a fuzzy closed-loop supply chain with one manufacturer, two competitive retailers and one third-party collector. The fuzziness is associated with collecting costs, remanufacturing costs, and customer demands. Two game models are proposed to formulate the pricing and remanufacturing decision problem under different power structures. The channel members’ optimal decisions in fuzzy environment are derived from these models. Numerical experiments are also given to explore the impacts of the power structure and fuzziness on the performance of the chain. It is found that the manufacturer has more advantages in pursuing higher expected profit when it performs as a Stackelberg leader. The existence of dominance in the closed-loop supply chain may lead to poor performance of the total system: higher sales prices, lower collecting rate, and lower expected profit of the whole supply chain. The results also show that the fuzziness of costs may have positive influence on the recycling level.
Dominant Species Constrain Effects of Species Diversity on Temporal Variability in Biomass Production of Tallgrass Prairie

Species diversity is thought to stabilize functioning of plant communities. An alternative view is that stability depends more on dynamics of dominant species than on diversity. We compared inter-annual variability (inverse of stability) of aboveground biomass in paired restored and remnant tallgrass prairies at two locations in central Texas, USA. Data from these two locations were used to test the hypothesis that greater richness and evenness in remnant than restored prairies would reduce variability in aboveground biomass in response to natural variation in rainfall. Restored prairies were chosen to be similar to paired remnant prairies in characteristics other than species diversity that affect temporal variability in biomass. Variability was measured as the coefficient of variation among years (square root of variance/mean; CV), where variance in community biomass equals the sum of variances of individual plant species plus the summed covariances between species pairs. Species diversity over five years was greater by a factor of 2 or more in remnant than restored prairies because richness and evenness were greater in remnant than restored prairies. Still, the CV of community biomass during spring and CV of annual biomass production did not differ consistently between prairie types. Neither the sum of species covariances nor total community biomass differed between prairies. Biomass varied relatively little in restored compared to remnant prairies because biomass of the dominant species in restored prairies (the grass Schizachyrium scoparium) varied less than did biomass of other dominant and sub-dominant species. In these grasslands, biomass response to natural variation in precipitation depended as much on characteristics of a dominant grass as on differences in diversity.
In Vivo Assessment of Antiviral Reactivity in Chronic HIV Infection

Abstract Purpose and Method: Chronic infection with HIV renders individuals incapable of mounting an effective host antiviral response, as defined by in vitro assays. Therefore, to determine whether antiviral reactivity could be detected in vivo, we interrupted effective antiviral treatment prospectively in nine chronically infected aviremic individuals. Low-dose interleukin-2 (IL-2) was administered before and after treatment interruption to compensate for any potential IL-2 production deficiency. In vivo antiviral reactivity was monitored subsequent to the interruption of antiviral therapy via viral and lymphocyte dynamics. The study was terminated when the plasma HIV RNA concentration reached a plateau, defined as four successive determinations that were <25% from the mean. Results: Plasma viral relapse occurred in all participants; reaching a peak concentration within 2.5 weeks. However, over the subsequent 2 weeks viremia was reduced an order of magnitude coincident with a 2-fold lymphocytosis of the CD8 + T cell subset. A second treatment interruption resulted in attenuation of the peak and trough virus concentrations by <10-fold in 3 of 4 participants, while the CD8 + T cell concentrations remained elevated. Conclusion: These findings indicate that chronic HIV infection prior to successful antiviral therapy does not preclude host antiviral reactivity. In addition, in vivo antiviral reactivity as revealed by viral and lymphocyte dynamics after antiviral treatment interruption can be useful to monitor the efficacy of different therapies.
A 3-D look into the atmosphere?

Abstract The atmospheres of chemically peculiar stars can be highly structured in both the horizontal and vertical dimensions. While most prevalent in the magnetic stars, these structures can also exist in non-magnetic stars. In addition to providing an important window to understanding the physical processes at play in these complex atmospheres, they can also be exploited to study stellar pulsations. This article reviews contributions to the session “A 3D look into the atmosphere” of the Joint Discussion “Progress in understanding the physics of Ap and related stars”. It is divided into 3 sections: “Magnetic field and surface structures”, “Pulsations in the atmospheres of roAp stars/inversions”, and “Spectral synthesis/atmospheric models”.
Investigation of Size Effects on the Al Nanoclusters Physical Properties via Molecular Dynamics Simulations

Molecular dynamics (MD) simulation has been carried out for study of size effects on physical properties of Al nanoclusters with different sizes (N = 256, 500, 864, 1372, 2048 and 4000) in the temperature range 300 K ≤ T ≤ 1200 K for both free and periodic boundary conditions. Energy per site for periodic and free boundary conditions was calculated for the mentioned sizes and temperature. By increasing size of Al nanocluster, the energy per atom was convergence to that of the bulk. By use of molecular dynamics some physical properties such as melting point, surface energy, sublimation energy, thermodynamic limit and pair distribution function have been obtained. Melting point of bulk state is 875 K which proportional the jump of energy and sharp peak in heat capacity. Our calculated sublimation energy (ΔHs-calculated = 330 kJ/mol) was in good agreement with experimental result (ΔHs-experimental = 318 kJ/mol).