Miracle-dz/UniFAR-FTUs huggingface dataset:
LIMIT CYCLES CAN REDUCE THE WIDTH OF THE HABITABLE ZONE

The liquid water habitable zone (HZ) describes the orbital distance at which a terrestrial planet can maintain above-freezing conditions through regulation by the carbonate-silicate cycle. Recent calculations have suggested that planets in the outer regions of the HZ cannot maintain stable, warm climates, but rather should oscillate between long, globally glaciated states and shorter periods of climatic warmth. Such conditions, similar to “Snowball Earth” episodes experienced on Earth, would be inimical to the development of complex land life, including intelligent life. Here, we build on previous studies with an updated energy balance climate model to calculate this “limit cycle” region of the HZ where such cycling would occur. We argue that an abiotic Earth would have a greater CO2 partial pressure than today because plants and other biota help to enhance the storage of CO2 in soil. When we tune our abiotic model accordingly, we find that limit cycles can occur but that previous calculations have overestimated their importance. For G stars like the Sun, limit cycles occur only for planets with CO2 outgassing rates less than that on modern Earth. For K- and M-star planets, limit cycles should not occur; however, M-star planets may be inhospitable to life for other reasons. Planets orbiting late G-type and early K-type stars retain the greatest potential for maintaining warm, stable conditions. Our results suggest that host star type, planetary volcanic activity, and seafloor weathering are all important factors in determining whether planets will be prone to limit cycling.
Genomic and clinical characterization of B/T mixed phenotype acute leukemia reveals recurrent features and T‐ALL like mutations

The B/T subtype of mixed phenotype acute leukemia (B/T MPAL) is defined by co‐expression of antigens of both B‐ and T‐cell lineages on leukemic blasts. Although it has been suggested that multilineage antigen expression portends poor response to chemotherapy, the clinical characteristics and driver mutations that underlie the pathogenesis of this rare subtype of acute leukemia are scarcely known. We identified nine cases of B/T MPAL from multiple institutions and correlated clinical and immunophenotypic findings with next‐generation sequencing data. We report that B/T MPAL commonly presents with lymphadenopathy in adolescence and young adulthood. While the tumors have diverse cytogenetic and genomic perturbations, recurrent acquired aberrations include mutations in the putative transcriptional regulator PHF6 and the JAK‐STAT and Ras signaling pathways. Alterations were also identified in genes encoding hematopoietic transcription factors, cell cycle regulators/tumor suppressors, and chromatin modifying enzymes. The genomic landscape of B/T MPAL strongly resembles that of T‐ALL subgroups associated with early developmental arrest, while genetic alterations that are common in B‐ALL were rarely seen. Two‐thirds of the patients responded to ALL‐based chemotherapy with or without stem cell transplantation. Our observations lay the groundwork for further study of the unique biology and clinical trajectory of B/T MPAL.
Success Factors in a Reward and Equity Based Crowdfunding Campaign

As the world changes, financial sector changes with it, and alternative finance emerge. Crowdfunding is part of this evolution and its use is becoming more widespread day by day. As more entrepreneurs and organizations seek crowdfunding to fund their ventures, and to solve the most important obstacle to achieve a successful crowdfunding campaign, which is not the information available about how to create a successful campaign, but rather its dispersion, it becomes of uttermost importance to create a framework to help them to succeed raising finance. It is, therefore, the main goal of this paper, to provide a valuable guide to help entrepreneurs in the hard task of raising finance through crowdfunding, mainly those using equity and reward crowdfunding. To accomplish the purposed goal, it is important to understand the underlying motivations of those investing in crowdfunding, in order to offer them what they seek and what motivates them. It is also essential to identify which kind of crowdfunding fits better the entrepreneur's goals and which one increases the likelihood of achieving them. Finally, is crucial to understand the specific success factors for a successful crowdfunding campaign. One of the main findings of this work, is that the motivations for investors in equity and reward crowdfunding are similar. This is very important, since it solves the problem of the scarcity of data for the equity model. With similar motivations it is possible to apply the data available for reward crowdfunding to equity crowdfunding, since both campaign can be design to answer the same needs and motivations.
Prenylated Flavonoids from Roots of Glycyrrhiza uralensis Induce Differentiation of B16-F10 Melanoma Cells

Roots of Glycyrrhiza uralensis have been used as herbal medicine and natural sweetener. By activity-guided phytochemical investigation of the extracts from G. uralensis root, ten flavonoids, namely GF-1–GF-10, of which five were prenylated flavonoids, were found to show antiproliferative effects in melanoma B16-F10 cells. Three of the prenylated flavonoids, namely GF-1, GF-4 and GF-9, significantly induced the differentiation of B16-F10 cells; the inductions included increase of tyrosinase activity, tyrosinase protein, and melanin content. In GF-1 and GF-9 induced melanoma differentiation, the phosphorylation of p38 MAPK (mitogen activated potein kinase) was identified; while GF-4 could trigger the phosphorylation of PI3K/AKT (phosphatidylinositol 3-kinase/Protein Kinase B) signaling. However, application of GF-6 to the melanoma cells did not induce differentiation; but which promoted cell apoptotic signaling, i.e., increase levels of cleaved-PRAP, cleaved-caspase 3, and cleaved-caspase 9. These results suggested that different types of prenylated flavonoids from G. uralensis might have potential anticancer effects against melanoma cells by acting through different signaling pathways.
Modeling of the Nonstationary Combustion Process of Methane-Air Mixture in Coal Mines

Simulation of the nonstationary combustion process for methane-air mixture in coal mines has been performed. Analytical dependencies are formulated to perform simulation of nonstationary combustion for methane-air mixture based on the FlowVision software package. The adequacy of the computer model was verified on the experimental data, given in the literature for 7 experiments, and on its own experimental data. The average relative error of the model is from 10 to 20%. The developed model is scaled for ducts with large diameters from 2 to 4 m. Model can be used to calculate non-stationary combustion for coal mine conditions. Modeling of nonstationary combustion for coal mine conditions was carried out. As result, it is established that for the considered configurations of the mines: maximum velocity of the flame front during detonation reaches 1400 m/s; maximum temperature in the calculated region during detonation is 2440 °C; maximum overpressure at detonation is 4 MPa; the calculated values of the radiation flux density at detonation reach 2200 kW/m2.
Audiences’ acts of authentication in the age of fake news: A conceptual framework

Through an analysis of relevant literature and open-ended survey responses from 2501 Singaporeans, this article proposes a conceptual framework to understand how individuals authenticate the information they encounter on social media. In broad strokes, we find that individuals rely on both their own judgment of the source and the message, and when this does not adequately provide a definitive answer, they turn to external resources to authenticate news items.
Collaborative Task Offloading in Vehicular Edge Multi-Access Networks

Mobile edge computing (MEC) has emerged as a promising paradigm to realize user requirements with low-latency applications. The deep integration of multi-access technologies and MEC can significantly enhance the access capacity between heterogeneous devices and MEC platforms. However, the traditional MEC network architecture cannot be directly applied to the Internet of Vehicles (IoV) due to high speed mobility and inherent characteristics. Furthermore, given a large number of resource-rich vehicles on the road, it is a new opportunity to execute task offloading and data processing onto smart vehicles. To facilitate good merging of the MEC technology in IoV, this article first introduces a vehicular edge multi-access network that treats vehicles as edge computation resources to construct the cooperative and distributed computing architecture. For immersive applications, co-located vehicles have the inherent properties of collecting considerable identical and similar computation tasks. We propose a collaborative task offloading and output transmission mechanism to guarantee low latency as well as the application- level performance. Finally, we take 3D reconstruction as an exemplary scenario to provide insights on the design of the network framework. Numerical results demonstrate that the proposed scheme is able to reduce the perception reaction time while ensuring the application-level driving experiences.
MS-based lipidomics of human blood plasma: a community-initiated position paper to develop accepted guidelines1

Human blood is a self-regenerating lipid-rich biological fluid that is routinely collected in hospital settings. The inventory of lipid molecules found in blood plasma (plasma lipidome) offers insights into individual metabolism and physiology in health and disease. Disturbances in the plasma lipidome also occur in conditions that are not directly linked to lipid metabolism; therefore, plasma lipidomics based on MS is an emerging tool in an array of clinical diagnostics and disease management. However, challenges exist in the translation of such lipidomic data to clinical applications. These relate to the reproducibility, accuracy, and precision of lipid quantitation, study design, sample handling, and data sharing. This position paper emerged from a workshop that initiated a community-led process to elaborate and define a set of generally accepted guidelines for quantitative MS-based lipidomics of blood plasma or serum, with harmonization of data acquired on different instrumentation platforms across independent laboratories as an ultimate goal. We hope that other fields may benefit from and follow such a precedent.
Transfer Learning for Brain–Computer Interfaces: A Euclidean Space Data Alignment Approach

Objective: This paper targets a major challenge in developing practical electroencephalogram (EEG)-based brain–computer interfaces (BCIs): how to cope with individual differences so that better learning performance can be obtained for a new subject, with minimum or even no subject-specific data? Methods: We propose a novel approach to align EEG trials from different subjects in the Euclidean space to make them more similar, and hence improve the learning performance for a new subject. Our approach has three desirable properties: first, it aligns the EEG trials directly in the Euclidean space, and any signal processing, feature extraction, and machine learning algorithms can then be applied to the aligned trials; second, its computational cost is very low; and third, it is unsupervised and does not need any label information from the new subject. Results: Both offline and simulated online experiments on motor imagery classification and event-related potential classification verified that our proposed approach outperformed a state-of-the-art Riemannian space data alignment approach, and several approaches without data alignment. Conclusion: The proposed Euclidean space EEG data alignment approach can greatly facilitate transfer learning in BCIs. Significance: Our proposed approach is effective, efficient, and easy to implement. It could be an essential pre-processing step for EEG-based BCIs.
First use of synoptic vector magnetograms for global nonlinear, force-free coronal magnetic field models

Context. The magnetic field permeating the solar atmosphere is generally thought to provide the energy for much of the activity seen in the solar corona, such as flares, coronal mass ejections (CMEs), etc. To overcome the unavailability of coronal magnetic field measurements, photospheric magnetic field vector data can be used to reconstruct the coronal field. Currently, there are several modelling techniques being used to calculate three-dimensional field lines into the solar atmosphere. Aims. For the first time, synoptic maps of a photospheric-vector magnetic field synthesized from the vector spectromagnetograph (VSM) on Synoptic Optical Long-term Investigations of the Sun (SOLIS) are used to model the coronal magnetic field and estimate free magnetic energy in the global scale. The free energy (i.e., the energy in excess of the potential field energy) is one of the main indicators used in space weather forecasts to predict the eruptivity of active regions. Methods. We solve the nonlinear force-free field equations using an optimization principle in spherical geometry. The resulting threedimensional magnetic fields are used to estimate the magnetic free energy content E(sub free) = E(sub nlfff) E(sub pot), which is the difference of the magnetic energies between the nonpotential field and the potential field in the global solar corona. For comparison, we overlay the extrapolated magnetic field lines with the extreme ultraviolet (EUV) observations by the atmospheric imaging assembly (AIA) on board the Solar Dynamics Observatory (SDO). Results. For a single Carrington rotation 2121, we find that the global nonlinear force-free field (NLFFF) magnetic energy density is 10.3% higher than the potential one. Most of this free energy is located in active regions.
Wrapped Gaussian Process Regression on Riemannian Manifolds

Gaussian process (GP) regression is a powerful tool in non-parametric regression providing uncertainty estimates. However, it is limited to data in vector spaces. In fields such as shape analysis and diffusion tensor imaging, the data often lies on a manifold, making GP regression nonviable, as the resulting predictive distribution does not live in the correct geometric space. We tackle the problem by defining wrapped Gaussian processes (WGPs) on Riemannian manifolds, using the probabilistic setting to generalize GP regression to the context of manifold-valued targets. The method is validated empirically on diffusion weighted imaging (DWI) data, directional data on the sphere and in the Kendall shape space, endorsing WGP regression as an efficient and flexible tool for manifold-valued regression.
Allicin improves endothelium-dependent relaxation in diabetic rats through maintaining eNOS protein stability

Endothelial nitric oxide (NO) synthase (eNOS) dysfunction-mediated endothelium-dependent relaxation impairment has been suggested to be a principal feature of diabetes-related cardiovascular complications. Allicin is one of the most biologically active compounds in garlic and exerts therapeutic potentials in many pathologic conditions. However, the protective effects of Allicin on eNOS expression and endothelium-dependent relaxation in diabetes remain unknown. In the present study, diabetic rats were induced by intravenous injection of streptozotocin and then orally treated with various concentration of Allicin for 4 weeks. EVC-304 endothelial cells were pretreated with Allicin in prior to incubation of high glucose for 48 h. NO production was determined by biochemical and cellular approaches. eNOS expression was analyzed by immunohistochemistry, real-time quantitative PCR and western blot, respectively. We found that Allicin administration suppressed the elevation of blood pressure in diabetic rats. In addition, Allicin remarkably attenuated diabetes-induced the decrease of NO production and eNOS expression, with a concomitant improvement in endothelial-dependent relaxation. Furthermore, rather than affecting eNOS transcriptional activity and mRNA expression, Allicin prolonged eNOS protein half-life and decreased eNOS ubiquitination. Collectively, Allicin restored eNOS expression through inhibition of ubiquitin-mediated eNOS protein degradation in diabetes, suggesting a novel mechanism for Allicin in the treatment for diabetes-related cardiovascular complications.
Leaf, stem and root tissue strategies across 758 Neotropical tree species

1. Trade-offs among functional traits reveal major plant strategies that can give insight into species distributions and ecosystem processes. However, current identification of plant strategies lacks the integration of root structural traits together with leaf and stem traits. 2. We examined correlations among 14 traits representing leaf, stem and woody root tissues. Traits were measured on 1084 individuals representing 758 Neotropical tree species, across 13 sites representative of the environmental variation encompassed by three widespread habitats (seasonally flooded, clay terra firme and white-sand forests) at opposite ends of Amazonia (French Guiana and Peru). 3. Woody root traits were closely aligned with stem traits, but not with leaf traits. Altogether leaf, stem and woody root traits delineated two orthogonal axes of functional trade-offs: a first axis defined by leaf traits, corresponding to a leaf economics spectrum, and a second axis defined by covarying stem and woody root traits, corresponding to a wood economics spectrum. These axes remained consistent when accounting for species evolutionary history with phylogenetically independent contrasts. 4. Despite the strong species turnover across sites, the covariation among root and stem structural traits as well as their orthogonality to leaf traits were strongly consistent across habitats and regions. 5. We conclude that root structural traits mirrored stem traits rather than leaf traits in Neotropical trees. Leaf and wood traits define an integrated whole-plant strategy in lowland South American forests that may contribute to a more complete understanding of plant responses to global changes in both correlative and modelling approaches. We suggest further meta-analyses in expanded environmental and geographic zones to determine the generality of this pattern.
Variability in Glucosinolate Content among Camelina Species

Glucosinolate content in Camelina sativa (L.) Crantz (false flax, gold-of-pleasure) and its relatives C. microcarpa, C. alyssum, C. rumelica and C. hispida was investigated. With the exception of C. hispida in which GSL3 was absent, in all remaining species, three characteristic glucosinolates (GSL1, GSL2 and GSL3) were identified. Camelina genotypes of spring type (C. sativa CAM134, C. alyssum CAM21) showed a typical pattern of glucosenolates with GSL1 > GSL3. GSL1 was present in traces in C. microcarpa and at low levels in C. rumelica and C. alyssum subsp. alyssum. In C. hispida, the GSL1 content was greater than GSL2 and, only in this specie, GSL2 represented less than 50% of total glucosinolates. These differences in the glucosinolate pattern among Camelina species could be exploited to reduce the total content of glucosinolates in C. sativa.
Arctic ice export events and their potential impact on global climate during the late Pleistocene

[1] Ice sheets in the North American Arctic and, to a lesser extent, those in northern Eurasia calved large quantities of icebergs that drifted through Fram Strait into the Greenland Sea several times during the late Pleistocene. These icebergs deposited Fe oxide grains (45–250 μm) and coarse lithic clasts >250 μm matched to specific circum-Arctic sources. Four massive Arctic iceberg export events are identified from the Laurentide and the Innuitian ice sheets, between 14 and 34 ka (calendar years) in a sediment core from Fram Strait. These relatively short duration (<1–4 kyr) events contain 3–5 times the background levels of Fe oxide grains. They began suddenly, as indicated by a steep rise in the number of grains matched to an ice sheet source, suggesting rapid purges of ice through Fram Strait, due perhaps to collapse of ice sheets. The larger events from the northwestern Laurentide ice sheet are preceded by events from the Innuitian ice sheet. Despite the chronological uncertainties, the Arctic export events appear to occur prior to Heinrich events.
Wave Evolution in Water Bodies using Turbulent MPS Simulation

Moving Particle Semi-implicit (MPS) which is a meshless and full Lagrangian method is employed to simulate nonlinear hydrodynamic behavior in a wide variety of engineering application including free surface water waves. In the present study, a numerical particle-based model is developed by the authors using MPS method to simulate different wave problems in the coastal waters. In this model fluid and solid are treated as separate phases and governing equations of momentum and continuity are solved for them concurrently. For simulations of turbulent wavy flows, constant eddy viscosity, Prandtl’s mixing length theory and k-e models were considered. In addition, higher order of MPS operators was applied to suppress numerical oscillation in comparison with previous studies. The developed method was applied to some cases, including still water reservoir, solitary wave propagation in a tank, tsunami run-up on an inclined wall and wave generation due to the landslide. Evaluation of the developed model results, in compare with data cited in the literature showed enhancement in the accuracy of the developed numerical model especially in compare with existing inviscid models. Besides, the numerical tests results have shown that applying k-e turbulence model, have equipped MPS model with a useful, powerful and reliable tool for simulating water free surface in wave motion, wave impact and the breaking process.
Entry of painters in the Amsterdam market of the Golden Age

We analyze the evolution of the entry of painters and price of paintings in the XVII century Amsterdam art market. In line with evolutionary theory, demand-driven entry in the market was first associated with product innovations and a rapid increase in the number of painters. After reaching a peak, the number of painters started to decrease in parallel with a price decline and the introduction of process innovations. To test for the role of profitability in the art market as a determinant of endogenous entry of painters, we build a price index for the representative painting inventoried in Dutch houses. This is based on hedonic regressions controlling for characteristics of the paintings (size, genre, placement in the house), the owners (job, religion, value of the collection, size of the house) and the painters. After a peak at the beginning of the century, the real price of paintings decreased until the end of the century. We provide anecdotal evidence for which high initial prices attracted entry of innovators, and econometric evidence on the causal relation between price movements and entry.
How Internal Violence Lowers Economic Growth: A Theoretical and Empirical Study

In this paper, we introduce a new variable called Internal Violence Index (IVI) and study its effects on economic growth both theoretically and empirically. The first part builds a stochastic endogenous growth model which demonstrates that Internal Violence harms economic growth. On the theoretical side, this paper is the first to introduce a fully-micro-founded endogenous economic growth model that illustrates the explicit effect of Internal Violence on long-run growth in a stochastic dynamic optimization in continuous time framework. On the empirical side, this paper is also the first to employ Linear Regressions and Instrumental Variables Estimations techniques to empirically study the impact of Internal Violence on economic growth. The empirical results corroborate the theoretical predictions that Internal Violence acts negatively on economic growth. The negative impact of Internal Violence on growth are maintained when we use alternative measurements of Internal Violence and subsamples of Least Developed Countries (LDCs) and Non Least Developed Countries.