Miracle-dz/UniFAR-FTUs huggingface dataset:
Characteristics of the Atmospheric Pressure Argon Plasma Jet

In order to produce uniform,steady and large volume dielectric barrier discharge(DBD) argon plasma jets at atmospheric pressure,a plasma generator with a screw-like inner electrode configuration was proposed.A uniform,steady and visibly glow-like discharge plasma jet was obtained at an open environment using this newly-designed plasma generator.The experimental and preliminary zero-dimensional modeling results show that,the discharges can be operated at an initial,transitional,stable or unstable discharge modes with the increase of the applied voltage;the glow-like discharge can occupy the whole glass tube with an inner-diameter of 8.9 mm at a stable discharge mode;the optical emission spectrum shows that there are different kinds of chemically reactive species in the plasma jet region;the estimated length of the plasma jet(longer than 30 mm) based on the modeling and experiments are consistent with each other qualitatively.The axial profile of the emission intensity of the plasma jet is related with the de-excitation process of the metastables in the plasma jet region.
DIFERENTES PROPORÇÕES DE LODO DE ESGOTO NA QUALIDADE DE MUDAS Schinus terebinthifolius RADDI

Considerando o problema do tratamento final do esgoto e a necessidade crescente de produção de mudas florestais, este estudo objetivou avaliar o efeito de diferentes substratos contendo Lodo de Esgoto (LE) na produção de mudas de Schinus terebinthifolius Raddi. Quatro tratamentos foram implementados contendo diferentes proporções de LE. Após 180 dias de semeadura, foram avaliados macro e micronutrientes das mudas, assim como medidas morfométricas. Também, o Índice de Qualidade de Dickson (IQD) foi calculado, quantificando o teor de macro e micronutrientes da raiz e parte aérea. Nossos resultados mostraram um aumento nos níveis de Zn, Cu, Fe e Mn nos substratos testados com a adição de LE. Para as mudas dispostas aos tratamentos com LE, ocorreu um acúmulo de macronutrientes no sistema radicular na ordem N>K>Ca>P>Mg>S e na parte aérea Ca>N>K>Mg>P>S. Para os micronutrientes, o acúmulo no sistema radicular ocorreu Fe>Zn>Mn>B>Cu e na parte aérea Fe>Mn>Zn>B>Cu. S. terebinthifolius mostrou eficácia para a produção de mudas de qualidade com os tratamentos compostos de 40% LE + 60% composto orgânico e 60% LE + 40% composto orgânico. Assim, a utilização de LE como substrato se mostrou eficiente na obtenção de mudas viáveis para o plantio no campo.
Content of total polyphenols and antioxidant activity in selected varieties of onion (Allium cepa L.)

Onion ( Allium cepa L.) is one of the most important vegetable crops widely consumed in the world. The bulb onion is grown as fresh shoots and as bulbs for consuming uncooked, cooked, and pickled or production of seed and sets. They can be eaten raw, boiled, steamed and roasted. Onion has high nutritional value. Onions are a good source of vitamins, minerals and major component like polyphenols, ﬂavonoids, fructooligosaccharides, thiosulﬁnates and other sulfur compounds. Polyphenols belong to significant antioxidants in human diet. Antioxidant compounds (polyphenols, flavonoids) scavenge free radicals, inhibit the oxidative mechanisms that lead to degenerative diseases. Antioxidant compounds in food play an important role as a health protecting factor. Onions have a wide range of beneficial properties for human health, such as anti-cholesterolaemic, anti-mutagenic and antioxidant capacity. In this work we evaluated content of total polyphenols and antioxidant activity in selected varieties of onion. Samples of plant material we collected at the stage of full maturity in the locality of Pružina. Pružina is locality without negative influences and emission sources. Total polyphenols content and antioxidant activity were measured in six varieties of onion, namely in red variety (Red matte), in yellow varieties (Boston, Bingo, Sherpa) and white varieties of onion (Diamond, White dry). The content of the total polyphenols was determined by using the Folin-Ciocalteu reagent (FCR). Antioxidant activity was measured by using a compound DPPH˙. In the present experiment it was detected, that total polyphenols content in samples ranges from 142.01 mg.kg -1 GAE (white variety of onion- White dry) to 1083.04 mg.kg -1 GAE (red variety of onion- Red matte). Statistically significant highest value of total polyphenols (1083.04 mg.kg -1 GAE) was recorded in variety Red matte. Another indicator that has been evaluated and compared was the antioxidant activity. The values of antioxidant activity were in interval from 7.74% to 41.67%. Based on the measured values of antioxidant activity in onion the samples can beclassified as follows: Red matte (41.67%) > Boston (25.77%) > Sherpa (24.34%) > Bingo (19.54%) > White dry (8.10%) > Diamond (7.74%).
Does Inequality Impede Risk Management? Evidence from a Lab-in-the-Field Experiment in Ghana

Low income households in agrarian developing economies continue to face considerable livelihood risks, which have serious negative impacts on household welfare. Incomplete financial markets present an external constraint on risk management and are well studied in the literature. A growing literature has focused on internal constraints on development, which can negatively affect saving and investment behavior. Here I propose that internal constraints may also hinder risk management. Specifically, I propose that fairness preferences may create an internal constraint on risk-sharing, particularly in a context of wealth inequality. To test this theory, I utilize a lab-in-the-field experiment to investigate the impact of wealth inequality on utilization of risk-management tools and explore how fairness preferences may mediate this effect. I find that inequality reduces risk-sharing and increases demand for insurance. Moreover, I find evidence that fairness preferences create an internal constraint on risk-sharing under inequality.
The Structure and Degree of Dependence in Government Bond Markets

Abstract Our study provides new evidence on asymmetric dependencies in international government bond markets, by examining bonds from developed, emerging, and frontier countries, using a quantile regression methodology. We find that the dependence structure for emerging and frontier markets significantly changes during financial crisis periods, which we show has important implications for international diversification of investment strategies. Moreover, we also examine in detail stock–bond correlations and uncover several instances of decoupling. In contrast, developed markets exhibit a more stable dependence pattern. In addition, we document that the degree and structure of dependence vary when foreign currencies are hedged or unhedged, and across bond maturity segments.
Relationship of Multimorbidity, Obesity Status, and Grip Strength among Older Adults in Taiwan

Background: The combination of multiple disease statuses, muscle weakness, and sarcopenia among older adults is an important public health concern, and a health burden worldwide. This study evaluates the association between chronic disease statuses, obesity, and grip strength (GS) among older adults in Taiwan. Methods: A community-based survey was conducted every 3 years among older adults over age 65, living in Chiayi County, Taiwan. Demographic data and several diseases statuses, such as diabetes mellitus, hypertension, cerebrovascular disease, cardiovascular disease, and certain cancers, were collected using a questionnaire. Anthropometric characteristics were measured using standard methods. Grip strength was measured using a digital dynamometer (TKK5101) method. Results: A total of 3739 older individuals were recruited (1600 males and 2139 females) with the mean age of 72.9 years. The mean GS was 32.8 ± 7.1 kg for males and 21.6 ± 4.8 kg for females. GS significantly decreased most in males with cerebrovascular disease (from 33.0—29.5 kg, p < 0.001) and in females with diabetes mellitus (from 21.8—21.0 kg, p < 0.01). GS was highest in older adults with obesity (body mass index ≥ 27 kg/m2); however, there was no significant change of GS as the disease number increased. Conclusion: Older adults who have two, rather than one or greater than three chronic diseases, have significantly lower GSs than those who are healthy. Stroke and CKD for males, and hypertension and diabetes for females, are important chronic diseases that are significantly associated with GS. Furthermore, being overweight may be a protective factor for GS in older adults of both sexes.
The Impact of Sedentary Behavior and Self-Rated Health on Cardiovascular Disease and Cancer among South Korean Elderly Persons Using the Korea National Health and Nutrition Examination Survey (KNHANES) 2014–2018 Data

Cardiovascular disease and cancer have increased the risk of mortality and morbidity in elderly persons worldwide. The aim of this study was to investigate the association of sedentary behavior and self-rated health with cardiovascular disease or cancer in elderly people. The data of 6785 elderly persons aged above 65 years from the Korea National Health and Nutrition Examination Survey 2014–2018 were examined. Binary logistic regression analyses assessed the association of sedentary behavior, self-rated health, and other risk factors with cardiovascular disease or cancer. Prolonged sedentary behavior in elderly people was associated with a high risk for cardiovascular disease (odds ratio (OR): 1.28, 95% confidence interval (CI): 1.08–1.52). There was a high risk for cardiovascular disease (OR: 2.36, 95% CI: 1.85–3.01) or cancer (OR: 1.48, 95% CI: 1.17–1.88) in elderly people who had poor self-rated health. This study identified the association between prolonged sedentary behavior and cardiovascular disease, and between poor self-rated health and cancer. Since prolonged sedentary behavior is related to cardiovascular disease, efforts are needed to reduce sedentary behavior hours and maintain good self-rated health.
Workplace training in Myanmar: Determinants and wage returns

Using linked employer-worker panel data from Myanmar, we estimate wage returns to workplace training. First, we document a low prevalence of training in manufacturing enterprises. Second, we find the wage premium associated with training of about 7%, which is in the range found in other South-East Asian countries. Third, we show that workplace training is offered selectively to workers and when this is the case, the wage gap between trained and untrained workers doubles. Fourth, we find that previous training does not contribute to higher present wage, which indicates low transferability of workplace training in Myanmar. While this setup may benefit employers, workers get short-lived benefits from training, which do not carry throughout the working life. Fifth, we find a convex profile of the returns to training with respect to education and that specific industries such as food, apparel and printing lend themselves more to the benefits from training. Considering the wage return as a lower bound of productivity gains from training, our results suggest that government support of workplace training programs could help increase performance of the manufacturing sector in Myanmar. <br>
On the determination of vortex ring vorticity using Lagrangian particles

Abstract Particles are a widespread tool for obtaining information from fluid flows. When Eulerian data are unavailable, they may be employed to estimate flow fields or to identify coherent flow structures. Here we numerically examine the possibility of using particles to capture the dynamics of isolated vortex rings propagating in a quiescent fluid. The analysis is performed starting from numerical simulations of the Navier–Stokes and the Hall–Vinen–Bekarevich–Khalatnikov equations, respectively describing the dynamics of a Newtonian fluid and a finite-temperature superfluid. The flow-induced positions and velocities of particles suspended in the fluid are specifically used to compute the Lagrangian pseudovorticity field, a proxy for the Eulerian vorticity field recently employed in the context of superfluid $^{4}\textrm {He}$ experiments. We show that, when calculated from ideal Lagrangian tracers or from particles with low inertia, the pseudovorticity field can be accurately used to estimate the propagation velocity and the growth of isolated vortex rings, although the quantitative reconstruction of the corresponding vorticity fields remains challenging. On the other hand, particles with high inertia tend to preferentially sample specific flow regions, resulting in biased pseudovorticity fields that pollute the estimation of the vortex ring properties. Overall, this work neatly demonstrates that the Lagrangian pseudovorticity is a valuable tool for estimating the strength of macroscopic vortical structures in the absence of Eulerian data, which is, for example, the case for superfluid $^{4}\textrm {He}$ experiments.
Is the Value Premium Smaller Than We Thought?

The construction of the original HML portfolio (Fama and French, 1993) includes six seemingly innocuous decisions that could easily have been replaced with alternatives that are just as reasonable. I propose such alternatives and construct HML portfolios. In sample, the average estimate of the value premium is dramatically smaller than the original estimate of the value premium. The difference is 0.09% per month and statistically significant. Out of sample, however, this difference is statistically indistinguishable from zero. The results suggest that the original value premium estimate is upward biased because of a chance result in the original research decisions.
Towards an Interpretable Latent Space in Structured Models for Video Prediction

We focus on the task of future frame prediction in video governed by underlying physical dynamics. We work with models which are object-centric, i.e., explicitly work with object representations, and propagate a loss in the latent space. Specifically, our research builds on recent work by Kipf et al. \cite{kipf&al20}, which predicts the next state via contrastive learning of object interactions in a latent space using a Graph Neural Network. We argue that injecting explicit inductive bias in the model, in form of general physical laws, can help not only make the model more interpretable, but also improve the overall prediction of model. As a natural by-product, our model can learn feature maps which closely resemble actual object positions in the image, without having any explicit supervision about the object positions at the training time. In comparison with earlier works \cite{jaques&al20}, which assume a complete knowledge of the dynamics governing the motion in the form of a physics engine, we rely only on the knowledge of general physical laws, such as, world consists of objects, which have position and velocity. We propose an additional decoder based loss in the pixel space, imposed in a curriculum manner, to further refine the latent space predictions. Experiments in multiple different settings demonstrate that while Kipf et al. model is effective at capturing object interactions, our model can be significantly more effective at localising objects, resulting in improved performance in 3 out of 4 domains that we experiment with. Additionally, our model can learn highly intrepretable feature maps, resembling actual object positions.
Globally Convergent Multilevel Training of Deep Residual Networks

We propose a globally convergent multilevel training method for deep residual networks (ResNets). The devised method can be seen as a novel variant of the recursive multilevel trust-region (RMTR) method, which operates in hybrid (stochastic-deterministic) settings by adaptively adjusting mini-batch sizes during the training. The multilevel hierarchy and the transfer operators are constructed by exploiting a dynamical system's viewpoint, which interprets forward propagation through the ResNet as a forward Euler discretization of an initial value problem. In contrast to traditional training approaches, our novel RMTR method also incorporates curvature information on all levels of the multilevel hierarchy by means of the limited-memory SR1 method. The overall performance and the convergence properties of our multilevel training method are numerically investigated using examples from the field of classification and regression.
Hausdorff dimension of union of lines that cover a curve

We construct a continuously differentiable curve in the plane that can be covered by a collection of lines such that every line intersects the curve at a single point and the union of the lines has Hausdorff dimension 1. We show that for twice differentiable curves this is impossible. In that case, the union of the lines must have Hausdorff dimension 2. If we use only tangent lines then the differentiability of the curve already implies that the union of the lines must have Hausdorff dimension 2, unless the curve is a line. We also construct a continuous curve, which is in fact the graph of a strictly convex function, such that the union of (one sided) tangent lines has Hausdorff dimension 1.
Simulating the Negative Jet Feedback Mechanism in Common Envelope Jet Supernovae

We use the stellar evolution code MESA to study the negative jet feedback mechanism in common envelope jet supernovae (CEJSNe), in which a neutron star (NS) launches jets in the envelope of a red supergiant (RSG). We find that the feedback reduces the mass accretion rate to be χ j ≃ 0.04–0.3 times the mass accretion rate without the operation of jets. We mimic the effect of the jets on the RSG envelope by depositing the energy that the jets carry into the envelope zones outside the NS orbit. The energy deposition inflates the envelope, therefore reducing the density in the NS vicinity, which in turn reduces the mass accretion rate in a negative feedback cycle. In calculating the above values for the negative jet feedback coefficient (the further reduction in the accretion rate) χ j, we adopt the canonical ratio of jet power to actual accretion power of 0.1, and the results of numerical simulations that show the actual mass accretion rate to be a fraction of 0.1–0.5 of the Bondi–Hoyle–Lyttleton mass accretion rate.
Intrinsic Dimension Adaptive Partitioning for Kernel Methods

We prove minimax optimal learning rates for kernel ridge regression, resp. ~support vector machines based on a data dependent partition of the input space, where the dependence of the dimension of the input space is replaced by the fractal dimension of the support of the data generating distribution. We further show that these optimal rates can be achieved by a training validation procedure without any prior knowledge on this intrinsic dimension of the data. Finally, we conduct extensive experiments which demonstrate that our considered learning methods are actually able to generalize from a dataset that is non-trivially embedded in a much higher dimensional space just as well as from the original dataset.
A primer on the differential geometry of quaternionic curves

This paper describes the foundations of a differential geometry of a quaternionic curves. The Frenet–Serret equations and the evolutes and evolvents of a particular quaternionic curve are accordingly determined. This new formulation takes benefit of the quaternionic structure, and the results are much simpler than the present formulations of quaternionic curves.
Elyite, Pb4Cu(SO4)O2(OH)4·H2O: Crystal structure and new data

Abstract The crystal structure of elyite, Pb4Cu(SO4)O2(OH)4·H2O, a = 14.233(2), b = 11.532(1), c = 14.611(2) Å, β = 100.45(1)°, V = 2358.4(5) Å3, Z = 8, was solved by direct methods and refined in space group P21/c to R1 = 3.64% and wR2 = 5.10% for the 5861 independent reflections. Data were collected on a tiny untwinned crystal fragment with a four-circle diffractometer (MoKα radiation, CCD area detector). The structure contains eight unique Pb atoms, two isolated Cu atoms in planar fourfold-coordination ( = 1.933, 1.927 Å) and two isolated, almost ideal SO4 tetrahedra. All anions coordinating Cu are OH groups. Two H2O molecules are weakly bound to Pb atoms. The Pb atoms show highly variable coordinations due to variable stereochemical activities of the Pb2+ lone electron pairs. The connectivity of the structure is based on Pb-O polyhedra which are closely linked by common O ligands to form rod-like structure elements parallel to the b axis. The structure framework is held together by sharing ligands with CuO4 squares and SO4 tetrahedra. The CuO4 squares can be considered as struts connecting the Pb-O rods along the c axis and, intermittently, along the a axis. A complex hydrogen bond system provides additional strengthening. The non-merohedral twinning parallel to {100} reported previously is explained by the presence of a pseudo-mirror plane in the structure. Comparisons are drawn with the structures of the related Pb-Cu-sulfates chenite, Pb4Cu(SO4)2(OH)6, and linarite, PbCu(SO4)(OH)2. The violet color of elyite and other Cu compounds might be related to the planar fourfold-coordination of Cu.
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation

Large-scale vision and language representation learning has shown promising improvements on various vision-language tasks. Most existing methods employ a transformer-based multimodal encoder to jointly model visual tokens (region-based image features) and word tokens. Because the visual tokens and word tokens are unaligned, it is challenging for the multimodal encoder to learn image-text interactions. In this paper, we introduce a contrastive loss to ALign the image and text representations BEfore Fusing (ALBEF) them through cross-modal attention, which enables more grounded vision and language representation learning. Unlike most existing methods, our method does not require bounding box annotations nor high-resolution images. In order to improve learning from noisy web data, we propose momentum distillation, a self-training method which learns from pseudo-targets produced by a momentum model. We provide a theoretical analysis of ALBEF from a mutual information maximization perspective, showing that different training tasks can be interpreted as different ways to generate views for an image-text pair. ALBEF achieves state-of-the-art performance on multiple downstream vision-language tasks. On image-text retrieval, ALBEF outperforms methods that are pre-trained on orders of magnitude larger datasets. On VQA and NLVR$^2$, ALBEF achieves absolute improvements of 2.37% and 3.84% compared to the state-of-the-art, while enjoying faster inference speed. Code and pre-trained models are available at https://github.com/salesforce/ALBEF/.
A new empirical model for self-leveling behavior of cylindrical particle beds

ABSTRACT During the material relocation phase of core disruptive accidents in sodium-cooled fast reactors, the rapid quenching and fragmentation of molten materials discharged from the reactor core into the lower plenum region can lead to the formation of debris beds. Coolant boiling may lead to leveling of the mound-shaped beds, which changes both the beds' coolability with decay heat in the fuel and the neutronic characteristics. In this study, a series of experiments using simulant materials were performed to develop an experimental database of self-leveling processes of particle beds in a cylindrical system. To simulate the coolant boiling in the beds in the experiments, a gas injection method was used to percolate nitrogen gas uniformly through the base of a bed with a conical-shaped mound. Time variations in bed height during the self-leveling process were measured for different particle sizes, densities and sphericities, and gas injection velocities. Using a dimensional analysis approach, a new model was proposed. This model correlates the experimental data on transient bed height with an empirical equation using a characteristic time for self-leveling development and an equilibrium bed height. The proposed model reasonably predicts the self-leveling development of particle beds.